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Christian Hansen

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Timothy G. Conley & Christian B. Hansen & Peter E. Rossi, 2012. "Plausibly Exogenous," The Review of Economics and Statistics, MIT Press, vol. 94(1), pages 260-272, February.

    Mentioned in:

    1. Plausibly Exogenous
      by Liam Delaney in Economics and Psychology Research on 2012-05-12 21:21:00
    2. Metrics Monday: Dealing with Imperfect Instruments I
      by Marc F. Bellemare in Marc F. Bellemare on 2017-01-16 17:00:47

RePEc Biblio mentions

As found on the RePEc Biblio, the curated bibliography of Economics:
  1. Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2014. "High-Dimensional Methods and Inference on Structural and Treatment Effects," Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 29-50, Spring.

    Mentioned in:

    1. > Econometrics > Big Data

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Alexandre Belloni & Victor Chernozhukov & Christian Hansen & Damian Kozbur, 2016. "Inference in High-Dimensional Panel Models With an Application to Gun Control," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 590-605, October.

    Mentioned in:

    1. Inference in High Dimensional Panel Models with an Application to Gun Control (J Business & Econ Statistics 2016) in ReplicationWiki ()
  2. A. Belloni & D. Chen & V. Chernozhukov & C. Hansen, 2012. "Sparse Models and Methods for Optimal Instruments With an Application to Eminent Domain," Econometrica, Econometric Society, vol. 80(6), pages 2369-2429, November.

    Mentioned in:

    1. Sparse Models and Methods for Optimal Instruments With an Application to Eminent Domain (ECTA 2012) in ReplicationWiki ()

Working papers

  1. Achim Ahrens & Christian B. Hansen & Mark E. Schaffer & Thomas Wiemann, 2023. "ddml: Double/debiased machine learning in Stata," Papers 2301.09397, arXiv.org, revised Jan 2024.

    Cited by:

    1. Ahrens, Achim & Hansen, Christian B. & Schaffer, Mark E & Wiemann, Thomas, 2024. "Model Averaging and Double Machine Learning," IZA Discussion Papers 16714, Institute of Labor Economics (IZA).

  2. Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2022. "pystacked: Stacking generalization and machine learning in Stata," Papers 2208.10896, arXiv.org, revised Mar 2023.

    Cited by:

    1. Ahrens, Achim & Hansen, Christian B. & Schaffer, Mark E & Wiemann, Thomas, 2024. "Model Averaging and Double Machine Learning," IZA Discussion Papers 16714, Institute of Labor Economics (IZA).
    2. Philipp Bach & Oliver Schacht & Victor Chernozhukov & Sven Klaassen & Martin Spindler, 2024. "Hyperparameter Tuning for Causal Inference with Double Machine Learning: A Simulation Study," Papers 2402.04674, arXiv.org.

  3. Freyaldenhoven Simon & Hansen Christian & Pérez Pérez Jorge & Shapiro Jesse M., 2022. "Visualization, Identification, and Estimation in the Linear Panel Event Study Design," Working Papers 2022-07, Banco de México.

    Cited by:

    1. Rik Chakraborti & Gavin Roberts, 2023. "How price-gouging regulation undermined COVID-19 mitigation: county-level evidence of unintended consequences," Public Choice, Springer, vol. 196(1), pages 51-83, July.
    2. Di, Wenhua & Pattison, Nathaniel, 2023. "Industry Specialization and Small Business Lending," Journal of Banking & Finance, Elsevier, vol. 149(C).
    3. Boto-García, David & Balado-Naves, Roberto & Mayor, Matías & Baños-Pino, José Francisco, 2023. "Consumers' demand for operational licencing: evidence from Airbnb in Paris," Annals of Tourism Research, Elsevier, vol. 100(C).
    4. Dario Caldara & Francesco Ferrante & Matteo Iacoviello & Andrea Prestipino & Albert Queraltó, 2023. "The International Spillovers of Synchronous Monetary Tightening," International Finance Discussion Papers 1384, Board of Governors of the Federal Reserve System (U.S.).
    5. Gabriel Garber & Atif R. Mian & Jacopo Ponticelli & Amir Sufi, 2021. "Consumption Smoothing or Consumption Binging? The effects of government-led consumer credit expansion in Brazil," NBER Working Papers 29386, National Bureau of Economic Research, Inc.
    6. Arboleda Cárcamo, David, 2024. "Fitting a Curve to the Pre-Trends," Documentos CEDE 21199, Universidad de los Andes, Facultad de Economía, CEDE.
    7. Calderón, Mariana & Cortés, Josué & Pérez Pérez, Jorge & Salcedo, Alejandrina, 2023. "Disentangling the Effects of Large Minimum Wage and VAT Changes on Prices: Evidence from Mexico," Labour Economics, Elsevier, vol. 80(C).
    8. Jonathan Roth & Pedro H. C. Sant'Anna & Alyssa Bilinski & John Poe, 2022. "What's Trending in Difference-in-Differences? A Synthesis of the Recent Econometrics Literature," Papers 2201.01194, arXiv.org, revised Jan 2023.
    9. Ander Iraizoz & José M Labeaga, 2022. "Incidence and Avoidance Effects of Spatial Fuel Tax Differentials: Evidence using Regional Tax Variation in Spain," PSE Working Papers halshs-03789430, HAL.
    10. Shang, Longfei & Saffar, Walid, 2024. "Pay transparency and entrepreneurship," Journal of Banking & Finance, Elsevier, vol. 162(C).
    11. Donato Masciandaro & Ariela Caglio & Sébastien Laffitte & Gianmarco Ottaviano, 2022. "Has Financial Fair Play Changed European Football?," BAFFI CAREFIN Working Papers 22189, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    12. Navid Sabet, 2023. "Out of the Shadows and into the Classroom: Immigrant Legalization, Hispanic Schooling and Hispanic Representation on School Boards," CESifo Working Paper Series 10677, CESifo.
    13. Emaad Manzoor & Nikhil Malik, 2023. "Designing Effective Music Excerpts," Papers 2309.14475, arXiv.org.
    14. Rodríguez-Puello, Gabriel & Rickardsson, Jonna, 2024. "Spatial Diffusion of Economic Shocks in the Labor Market: Evidence from a Mining Boom and Bust," OSF Preprints tzmf2, Center for Open Science.
    15. Capuno, Joseph & Corpuz, Jose & Samuel Lordemus, 2022. "Natural disasters and local government finance: Evidence from typhoon Haiyan," CAGE Online Working Paper Series 620, Competitive Advantage in the Global Economy (CAGE).
    16. Goyal, Raghav & Steinbach, Sandro, 2023. "Agricultural commodity markets in the wake of the black sea grain initiative," Economics Letters, Elsevier, vol. 231(C).
    17. Di Cataldo, Marco & Romani, Giulia, 2023. "The local impact of closing undersized schools," LSE Research Online Documents on Economics 119359, London School of Economics and Political Science, LSE Library.
    18. Soojung Ahn & Dongin Kim & Sandro Steinbach, 2023. "The impact of the Russian invasion of Ukraine on grain and oilseed trade," Agribusiness, John Wiley & Sons, Ltd., vol. 39(1), pages 291-299, January.
    19. Marco Di Cataldo & Giulia Romani, 2023. "Rational cuts? The local impact of closing undersized schools," Working Papers 2023:03, Department of Economics, University of Venice "Ca' Foscari".
    20. Chen, Guowen & Herrera, Ana María & Lugauer, Steven, 2022. "Policy and misallocation: Evidence from Chinese firm-level data," European Economic Review, Elsevier, vol. 149(C).
    21. Tancredi Buscemi & Giulia Romani, 2022. "Allocation of authority and tactical redistribution of public investments: A historical quasi-experiment," Working Papers 2022:18, Department of Economics, University of Venice "Ca' Foscari", revised 2024.
    22. Luis Alvarez & Bruno Ferman, 2023. "Extensions for Inference in Difference-in-Differences with Few Treated Clusters," Papers 2302.03131, arXiv.org.
    23. Arindrajit Dube & Michael Reich & Akash Bhatt & Denis Sosinskiy, 2024. "Restaurant Employment, Minimum Wages, and Border Discontinuities," NBER Working Papers 32902, National Bureau of Economic Research, Inc.
    24. Campos, Nicolás & Chalup, Miguel & Mitnik, Oscar A. & Urquidi, Manuel, 2024. "The Impact of Labor Intermediation and Training in High Informality Contexts. Evidence from Paraguay," IZA Discussion Papers 17254, Institute of Labor Economics (IZA).
    25. Kotyrlo, Elena, 2024. "Simple and complex difference-in-differences approach," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 73, pages 119-142.

  4. Victor Chernozhukov & Christian Hansen & Yuan Liao & Yinchu Zhu, 2021. "Inference for Low-Rank Models," Papers 2107.02602, arXiv.org, revised Jan 2023.

    Cited by:

    1. Choi, Jungjun & Kwon, Hyukjun & Liao, Yuan, 2024. "Inference for low-rank completion without sample splitting with application to treatment effect estimation," Journal of Econometrics, Elsevier, vol. 240(1).
    2. Hugo Freeman & Martin Weidner, 2021. "Linear panel regressions with two-way unobserved heterogeneity," CeMMAP working papers CWP39/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

  5. Victor Chernozhukov & Christian Hansen & Kaspar Wuthrich, 2020. "Instrumental Variable Quantile Regression," Papers 2009.00436, arXiv.org.

    Cited by:

    1. Jun Ma & Vadim Marmer & Zhengfei Yu, 2021. "Inference on Individual Treatment Effects in Nonseparable Triangular Models," Papers 2107.05559, arXiv.org, revised Feb 2023.
    2. Wenjie Wang & Yichong Zhang, 2021. "Wild Bootstrap for Instrumental Variables Regressions with Weak and Few Clusters," Papers 2108.13707, arXiv.org, revised Jan 2024.
    3. He, Xuming & Pan, Xiaoou & Tan, Kean Ming & Zhou, Wen-Xin, 2023. "Smoothed quantile regression with large-scale inference," Journal of Econometrics, Elsevier, vol. 232(2), pages 367-388.
    4. Javier Alejo & Antonio F. Galvao & Gabriel Montes-Rojas, 2021. "A first-stage representation for instrumental variables quantile regression," Papers 2102.01212, arXiv.org, revised Feb 2022.
    5. Aluko, Olufemi Adewale & Opoku, Eric Evans Osei, 2022. "The financial development impact of financial globalization revisited: A focus on OECD countries," International Economics, Elsevier, vol. 169(C), pages 13-29.
    6. Elisa Toledo & Wilman Santiago Ochoa-Moreno & Rafael Alvarado & Lizeth Cuesta & Muntasir Murshed & Abdul Rehman, 2022. "Forest Area: Old and New Factors That Affect Its Dynamics," Sustainability, MDPI, vol. 14(7), pages 1-17, March.

  6. Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2019. "lassopack: Model selection and prediction with regularized regression in Stata," Papers 1901.05397, arXiv.org.

    Cited by:

    1. Alain Naef & Jacob P. Weber, 2021. "Regional How Powerful is Unannounced, Sterilized Foreign Exchange Intervention?," Working papers 834, Banque de France.
    2. Martin, Stephen & Claxton, Karl & Lomas, James & Longo, Francesco, 2023. "The impact of different types of NHS expenditure on health: Marginal cost per QALY estimates for England for 2016/17," Health Policy, Elsevier, vol. 132(C).
    3. Suah, Jing Lian, 2020. "Veiled Expectations: The Heterogeneous Impact of Exchange Rate Shocks at the Sectoral-Level," MPRA Paper 109086, University Library of Munich, Germany.
    4. Ekaterina Oparina & Caspar Kaiser & Niccol`o Gentile & Alexandre Tkatchenko & Andrew E. Clark & Jan-Emmanuel De Neve & Conchita D'Ambrosio, 2022. "Human Wellbeing and Machine Learning," Papers 2206.00574, arXiv.org.
    5. Marco Due~nas & Federico Nutarelli & V'ictor Ortiz & Massimo Riccaboni & Francesco Serti, 2021. "Assessing the Heterogeneous Impact of Economy-Wide Shocks: A Machine Learning Approach Applied to Colombian Firms," Papers 2104.04570, arXiv.org, revised Nov 2024.
    6. Alessandro V. M. Oliveira & Bruno F. Oliveira & Moises D. Vassallo, 2024. "Airport service quality perception and flight delays: examining the influence of psychosituational latent traits of respondents in passenger satisfaction surveys," Papers 2401.02139, arXiv.org.
    7. Qiu, Yun & Chen, Xi & Shi, Wei, 2020. "Impacts of Social and Economic Factors on the Transmission of Coronavirus Disease 2019 (COVID-19) in China," GLO Discussion Paper Series 494 [pre.], Global Labor Organization (GLO).
    8. Biewen, Martin & Erhardt, Pascal, 2024. "Using Post-Regularization Distribution Regression to Measure the Effects of a Minimum Wage on Hourly Wages, Hours Worked and Monthly Earnings," IZA Discussion Papers 16894, Institute of Labor Economics (IZA).
    9. Alain Naef & Jacob P. Weber, 2023. "How Powerful Is Unannounced, Sterilized Foreign Exchange Intervention?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 55(5), pages 1307-1319, August.
    10. Mert Hakan Hekimoğlu & Burak Kazaz, 2020. "Analytics for Wine Futures: Realistic Prices," Production and Operations Management, Production and Operations Management Society, vol. 29(9), pages 2096-2120, September.
    11. Gorodnichenko, Yuriy & Pham, Tho & Talavera, Oleksandr, 2021. "Conference presentations and academic publishing," Economic Modelling, Elsevier, vol. 95(C), pages 228-254.
    12. Eduardo Correia & Rodrigo Calili & José Francisco Pessanha & Maria Fatima Almeida, 2023. "Definition of Regulatory Targets for Electricity Non-Technical Losses: Proposition of an Automatic Model-Selection Technique for Panel Data Regressions," Energies, MDPI, vol. 16(6), pages 1-22, March.
    13. Suah, Jing Lian, 2020. "Uncertainty and Exchange Rates: Global Dynamics (Well, I Don't Quite Know Anymore)," MPRA Paper 109087, University Library of Munich, Germany.
    14. Kadriye Hilal Topal & Ebru Çağlayan Akay, 2020. "Hanehalkı Tüketim Harcamalarının Mikroekonometrik Analizi: LAD-LASSO Yöntemi," EKOIST Journal of Econometrics and Statistics, Istanbul University, Faculty of Economics, vol. 0(33), pages 13-31, December.
    15. Camacho, Christine & Webb, Roger T. & Bower, Peter & Munford, Luke, 2024. "Risk factors for deaths of despair in England: An ecological study of local authority mortality data," Social Science & Medicine, Elsevier, vol. 342(C).
    16. Ladina Knapp & David Wuepper & Robert Finger, 2021. "Preferences, personality, aspirations, and farmer behavior," Agricultural Economics, International Association of Agricultural Economists, vol. 52(6), pages 901-913, November.
    17. Fateh Belaïd & Christophe Rault, 2021. "Energy Expenditure in Egypt: Empirical Evidence Based on a Quantile Regression Approach," CESifo Working Paper Series 8815, CESifo.
    18. Li, Qiang & An, Lian & Zhang, Ren, 2023. "Corruption drives brain drain: Cross-country evidence from machine learning," Economic Modelling, Elsevier, vol. 126(C).
    19. Indrawan Nugrahanto & Hariyanto Gunawan & Hsing-Yu Chen, 2024. "Innovative Approaches to Sustainable Computer Numeric Control Machining: A Machine Learning Perspective on Energy Efficiency," Sustainability, MDPI, vol. 16(9), pages 1-22, April.
    20. Simon B chler, Maximilian v. Ehrlich, 2021. "Quantifying Land Use Regulation and its Determinants - Ease of Residential Development across Swiss Municipalities," Diskussionsschriften credresearchpaper32, Universitaet Bern, Departement Volkswirtschaft - CRED.
    21. Yue Cai, 2021. "Measuring Market Power in the IPO Underwriter," Working Papers 2108, Waseda University, Faculty of Political Science and Economics.
    22. Julia Mink, 2024. "Putting a Price Tag on Air Pollution: The Social Healthcare Costs of Air Pollution in France," ECONtribute Discussion Papers Series 320, University of Bonn and University of Cologne, Germany.
    23. Joshua D. Angrist & Brigham Frandsen, 2022. "Machine Labor," Journal of Labor Economics, University of Chicago Press, vol. 40(S1), pages 97-140.
    24. Falco J. Bargagli-Stoffi & Fabio Incerti & Massimo Riccaboni & Armando Rungi, 2023. "Machine Learning for Zombie Hunting: Predicting Distress from Firms' Accounts and Missing Values," Papers 2306.08165, arXiv.org.
    25. Sinéad Keogh & Stephen O’Neill & Kieran Walsh, 2021. "Composite Measures for Assessing Multidimensional Social Exclusion in Later Life: Conceptual and Methodological Challenges," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 155(2), pages 389-410, June.
    26. Sujeong Park & David Powell, 2020. "Is the Rise in Illicit Opioids Affecting Labor Supply and Disability Claiming Rates?," NBER Working Papers 27804, National Bureau of Economic Research, Inc.
    27. Carlos Aller & Lorenzo Ductor & Daryna Grechyna, 2020. "Robust Determinants of CO2 Emissions," ThE Papers 20/13, Department of Economic Theory and Economic History of the University of Granada..
    28. Arusha Cooray & Ibrahim Özmen, 2024. "Institutions and carbon emissions: an investigation employing STIRPAT and machine learning methods," Empirical Economics, Springer, vol. 67(3), pages 1015-1044, September.
    29. Lee, Seungmin & Barrett, Christopher B. & Hoddinott, John F., 2021. "Food Security Dynamics in the United States, 2001-2017," Working Papers 316604, Cornell University, Department of Applied Economics and Management.
    30. Karen Arulsamy & Liam Delaney, 2020. "The Impact of Automatic Enrolment on the Mental Health Gap in Pension Participation: Evidence from the UK," Working Papers 202004, Geary Institute, University College Dublin.
    31. Adamecz-Völgyi, Anna & Szabó-Morvai, Ágnes, 2021. "Confidence in public institutions is critical in containing the COVID-19 pandemic," GLO Discussion Paper Series 861, Global Labor Organization (GLO).
    32. Luca J. Santos & Alessandro V. M. Oliveira & Dante Mendes Aldrighi, 2021. "Testing the differentiated impact of the COVID-19 pandemic on air travel demand considering social inclusion," Papers 2108.00850, arXiv.org.
    33. Achim Ahrens & Sean Lyons, 2021. "Do rising rents lead to longer commutes? A gravity model of commuting flows in Ireland," Urban Studies, Urban Studies Journal Limited, vol. 58(2), pages 264-279, February.
    34. Gonzalo E. Sánchez, 2022. "Non-compliance notifications and taxpayer strategic behavior: evidence from Ecuador," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 29(3), pages 627-666, June.
    35. Moritz Meister & Annekatrin Niebuhr & Jan Cornelius Peters & Johannes Stiller, 2023. "Local attributes and migration balance – evidence for different age and skill groups from a machine learning approach," Regional Science Policy & Practice, Wiley Blackwell, vol. 15(4), pages 794-825, May.
    36. Fluchtmann, Jonas & Glenny, Anita Marie & Harmon, Nikolaj & Maibom, Jonas, 2021. "The Gender Application Gap: Do Men and Women Apply for the Same Jobs?," IZA Discussion Papers 14906, Institute of Labor Economics (IZA).
    37. Francesca Micocci & Armando Rungi, 2021. "Predicting Exporters with Machine Learning," Papers 2107.02512, arXiv.org, revised Sep 2022.
    38. Natalia Pecorari & Jose Cuesta, 2024. "Citizen Participation and Political Trust in Latin America and the Caribbean: A Machine Learning Approach," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 36(5), pages 1227-1252, October.
    39. Shree Saha & Sudha Narayanan, 2020. "A Simplified measure of nutritional empowerment using machine learning to abbreviate the Women's Empowerment in Nutrition Index (WENI)," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2020-031, Indira Gandhi Institute of Development Research, Mumbai, India.
    40. Daniel Homocianu, 2024. "Life Satisfaction: Insights from the World Values Survey," Societies, MDPI, vol. 14(7), pages 1-47, July.
    41. Mariarosaria Comunale, 2020. "The persistently high rate of suicide in Lithuania: an updated view," Bank of Lithuania Discussion Paper Series 21, Bank of Lithuania.
    42. Pettersson-Lidbom, Per, 2022. "Exit, Voice and Political Change: Evidence from Swedish Mass Migration to the United States. A Comment on Karadja and Prawitz (Journal of Political Economy, 2019)," Journal of Comments and Replications in Economics (JCRE), ZBW - Leibniz Information Centre for Economics, vol. 1(2022-3), pages 1-13.
    43. Piotr Lewandowski & Wojciech Szymczak, 2024. "Automation, Trade Unions and Involuntary Atypical Employment," IBS Working Papers 02/2024, Instytut Badan Strukturalnych.
    44. Alessandro V. M. Oliveira & Thiago Caliari & Rodolfo R. Narcizo, 2024. "An empirical model of fleet modernization: on the relationship between market concentration and innovation adoption in the Brazilian airline industry," Papers 2401.06876, arXiv.org.
    45. Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2023. "pystacked: Stacking generalization and machine learning in Stata," Stata Journal, StataCorp LP, vol. 23(4), pages 909-931, December.
    46. Falco J. Bargagli-Dtoffi & Massimo Riccaboni & Armando Rungi, 2020. "Machine Learning for Zombie Hunting. Firms Failures and Financial Constraints," Working Papers 01/2020, IMT School for Advanced Studies Lucca, revised Jun 2020.
    47. Dueñas, Marco & Ortiz, Víctor & Riccaboni, Massimo & Serti, Francesco, 2021. "Assessing the Impact of COVID-19 on Trade: a Machine Learning Counterfactual Analysis," Working papers 79, Red Investigadores de Economía.
    48. Collins, Alan & Fan, Jingwen & Mahabir, Aruneema, 2022. "Actual versus ‘natural’ rates of suicide: Evidence from the USA," Economic Modelling, Elsevier, vol. 106(C).
    49. Cochrane, William & Poot, Jacques & Roskruge, Matthew, 2022. "Urban Resilience and Social Security Uptake: New Zealand Evidence from the Global Financial Crisis and the COVID-19 Pandemic," IZA Discussion Papers 15510, Institute of Labor Economics (IZA).
    50. Patel, Pankaj C. & Tsionas, Mike G., 2022. "Cultural interconnectedness in supply chain networks and change in performance: An internal efficiency perspective," International Journal of Production Economics, Elsevier, vol. 243(C).
    51. Tovar Reaños, Miguel A., 2021. "Fuel for poverty: A model for the relationship between income and fuel poverty. Evidence from Irish microdata," Energy Policy, Elsevier, vol. 156(C).
    52. Daniel Homocianu, 2023. "Exploring the Predictors of Co-Nationals’ Preference over Immigrants in Accessing Jobs—Evidence from World Values Survey," Mathematics, MDPI, vol. 11(3), pages 1-29, February.
    53. Gu, Bingmei & Liu, Jiaguo, 2022. "Determinants of dry bulk shipping freight rates: Considering Chinese manufacturing industry and economic policy uncertainty," Transport Policy, Elsevier, vol. 129(C), pages 66-77.
    54. Caglayan, Mustafa & Pham, Tho & Talavera, Oleksandr & Xiong, Xiong, 2020. "Asset mispricing in peer-to-peer loan secondary markets," Journal of Corporate Finance, Elsevier, vol. 65(C).
    55. Lehner, Lukas & Parolin, Zachary & Wilmers, Nathan, 2024. "Declining Earnings Inequality, Rising Income Inequality: What Explains Discordant Inequality Trends in the United States?," IZA Discussion Papers 16874, Institute of Labor Economics (IZA).
    56. Theresa Graefe, 2023. "The effect of the Austrian-German bidding zone split on unplanned cross-border flows," Papers 2303.14182, arXiv.org.
    57. Jana Bischler & Eva-Maria Egger & Paul Jasper & Ivan Manhique, 2022. "Determinants of gender gaps in youth employment in urban Mozambique," WIDER Working Paper Series wp-2022-164, World Institute for Development Economic Research (UNU-WIDER).
    58. Daniel Homocianu & Dinu Airinei, 2022. "PCDM and PCDM4MP: New Pairwise Correlation-Based Data Mining Tools for Parallel Processing of Large Tabular Datasets," Mathematics, MDPI, vol. 10(15), pages 1-27, July.
    59. Jianhua Zhang & Mohammad Shahidul Islam, 2020. "The Heterogeneous Impacts of R&D on Innovation in Services Sector: A Firm-Level Study of Developing ASEAN," Sustainability, MDPI, vol. 12(4), pages 1-22, February.
    60. Oliveira, Alessandro V.M. & Oliveira, Bruno F. & Vassallo, Moisés D., 2023. "Airport service quality perception and flight delays: Examining the influence of psychosituational latent traits of respondents in passenger satisfaction surveys," Research in Transportation Economics, Elsevier, vol. 102(C).

  7. Victor Chernozhukov & Christian Hansen & Yuan Liao & Yinchu Zhu, 2019. "Inference for heterogeneous effects using low-rank estimations," CeMMAP working papers CWP31/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Miao, Ke & Phillips, Peter C.B. & Su, Liangjun, 2023. "High-dimensional VARs with common factors," Journal of Econometrics, Elsevier, vol. 233(1), pages 155-183.
    2. Yiren Wang & Liangjun Su & Yichong Zhang, 2022. "Low-rank Panel Quantile Regression: Estimation and Inference," Papers 2210.11062, arXiv.org.
    3. Jungjun Choi & Hyukjun Kwon & Yuan Liao, 2023. "Inference for Low-rank Completion without Sample Splitting with Application to Treatment Effect Estimation," Papers 2307.16370, arXiv.org.
    4. Jianqing Fan & Kunpeng Li & Yuan Liao, 2020. "Recent Developments on Factor Models and its Applications in Econometric Learning," Papers 2009.10103, arXiv.org.
    5. Choi, Jungjun & Kwon, Hyukjun & Liao, Yuan, 2024. "Inference for low-rank completion without sample splitting with application to treatment effect estimation," Journal of Econometrics, Elsevier, vol. 240(1).
    6. Belloni, Alexandre & Chen, Mingli & Madrid Padilla, Oscar Hernan & Wang, Zixuan (Kevin), 2019. "High Dimensional Latent Panel Quantile Regression with an Application to Asset Pricing," The Warwick Economics Research Paper Series (TWERPS) 1230, University of Warwick, Department of Economics.
    7. Junlong Feng, 2019. "Regularized Quantile Regression with Interactive Fixed Effects," Papers 1911.00166, arXiv.org, revised Mar 2021.

  8. Simon Freyaldenhoven & Christian Hansen & Jesse Shapiro, 2019. "Pre-event Trends in the Panel Event-study Design," Working Papers 19-27, Federal Reserve Bank of Philadelphia.

    Cited by:

    1. Liu, Duan & Yu, Nizhou & Wan, Hong, 2022. "Does water rights trading affect corporate investment? The role of resource allocation and risk mitigation channels," Economic Modelling, Elsevier, vol. 117(C).
    2. Haddou, Samira, 2024. "Determinants of CDS in core and peripheral European countries: A comparative study during crisis and calm periods," The North American Journal of Economics and Finance, Elsevier, vol. 71(C).
    3. Sheng, Di, 2021. "Emission Trading System and Air Quality: Evidence from China," 2021 Annual Meeting, August 1-3, Austin, Texas 314071, Agricultural and Applied Economics Association.
    4. Rebollo-Sanz, Yolanda & Rodríguez-López, Jesús & Rodríguez-Planas, Núria, 2021. "Penalty-point system, deterrence and road safety: A quasi-experimental analysis," Journal of Economic Behavior & Organization, Elsevier, vol. 190(C), pages 408-433.
    5. Pérez, Jorge & Vial, Felipe & Zárate, Román, 2022. "Urban Transit Infrastructure: Spatial Mismatch and Labor Market Power," Research Department working papers 1992, CAF Development Bank Of Latinamerica.
    6. Jonathan Roth & Pedro H. C. Sant'Anna, 2021. "Efficient Estimation for Staggered Rollout Designs," Papers 2102.01291, arXiv.org, revised May 2023.
    7. Piotr Lukaszuk, 2021. "You can smuggle but you can't hide: Sanction evasion during the Ukraine crisis," Aussenwirtschaft, University of St. Gallen, School of Economics and Political Science, Swiss Institute for International Economics and Applied Economics Research, vol. 71(01), pages 73-125, December.
    8. Clément de Chaisemartin & Xavier D’haultfœuille, 2022. "Two-Way Fixed Effects and Differences-in-Differences with Heterogeneous Treatment Effects: A Survey," Post-Print hal-03873885, HAL.
    9. Camilla Adams & Jonathan Meer & CarlyWill Sloan, 2018. "The Minimum Wage and Search Effort," NBER Working Papers 25128, National Bureau of Economic Research, Inc.
    10. Anderson, Michael L. & Davis, Lucas W., 2020. "An empirical test of hypercongestion in highway bottlenecks," Journal of Public Economics, Elsevier, vol. 187(C).
    11. Petra E. Todd & Weilong Zhang, 2022. "Distributional Effects of Local Minimum Wages: A Spatial Job Search Approach," PIER Working Paper Archive 22-027, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    12. Clarke, Damian & Tapia Schythe, Kathya, 2020. "Implementing the Panel Event Study," MPRA Paper 101669, University Library of Munich, Germany.
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    65. Simon Freyaldenhoven & Christian B. Hansen & Jorge Pérez Pérez & Jesse M. Shapiro & Constantino Carreto, 2024. "Policy Effect Estimation and Visualization in Linear Panel Event-Study Designs: Introducing the xtevent Package," Working Papers 2024-09, Banco de México.
    66. Callaway, Brantly & Karami, Sonia, 2023. "Treatment effects in interactive fixed effects models with a small number of time periods," Journal of Econometrics, Elsevier, vol. 233(1), pages 184-208.
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    71. Di Matteo, Dante & Cardinale, Bernardo, 2023. "Impact of high-speed rail on income inequalities in Italy," Journal of Transport Geography, Elsevier, vol. 111(C).
    72. Jacob Conway & Jack Glaser & Matthew Plosser, 2023. "Does the Community Reinvestment Act Improve Consumers’ Access to Credit," Staff Reports 1048, Federal Reserve Bank of New York.
    73. Romeo, Charles & Sandler, Ryan, 2021. "The effect of debt collection laws on access to credit," Journal of Public Economics, Elsevier, vol. 195(C).
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    75. Constantino Carreto & Simon Freyaldenhoven & Christian Hansen & Jorge Perez Perez & Jesse Shapiro, 2024. "xtevent: Estimation and Visualization in the Linear Panel Event-Study Design," Working Papers 24-15, Federal Reserve Bank of Philadelphia.
    76. Chu, Ziyan & Zhou, Yichen Christy, 2023. "The effect of adopting the Next Generation Air Transportation System (NextGen) on air travel performance," Regional Science and Urban Economics, Elsevier, vol. 102(C).
    77. ITO Tadashi & TANAKA Ayumu, 2023. "Inward Foreign Direct Investment, Transactions, and Domestic Firms' Performance: Evidence from firm-to-firm transaction linkage," Discussion papers 23026, Research Institute of Economy, Trade and Industry (RIETI).
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    81. Israel García, 2023. "Budget Forecast Errors in Spanish Municipalities: The Role of Transparency," MAGKS Papers on Economics 202327, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
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  9. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Christian Hansen & Kengo Kato, 2018. "High-Dimensional Econometrics and Regularized GMM," Papers 1806.01888, arXiv.org, revised Jun 2018.

    Cited by:

    1. Andrii Babii & Xi Chen & Eric Ghysels & Rohit Kumar, 2020. "Binary Choice with Asymmetric Loss in a Data-Rich Environment: Theory and an Application to Racial Justice," Papers 2010.08463, arXiv.org, revised Nov 2021.
    2. Yoici Arai & Taisuke Otsu & Myung Hwan Seo, 2022. "Regression discontinuity design with potentially many covariates," STICERD - Econometrics Paper Series 626, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    3. Kea BARET, 2021. "Fiscal rules’ compliance and Social Welfare," Working Papers of BETA 2021-38, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    4. Saulius Jokubaitis & Remigijus Leipus, 2022. "Asymptotic Normality in Linear Regression with Approximately Sparse Structure," Mathematics, MDPI, vol. 10(10), pages 1-28, May.
    5. Byol Kim & Song Liu & Mladen Kolar, 2021. "Two‐sample inference for high‐dimensional Markov networks," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(5), pages 939-962, November.
    6. Chen, Bin & Maung, Kenwin, 2023. "Time-varying forecast combination for high-dimensional data," Journal of Econometrics, Elsevier, vol. 237(2).
    7. Denis Chetverikov & Daniel Wilhelm & Dongwoo Kim, 2020. "An Adaptive Test of Stochastic Monotonicity," CeMMAP working papers CWP17/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    8. Andrii Babii, 2022. "High-Dimensional Mixed-Frequency IV Regression," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(4), pages 1470-1483, October.
    9. Adam Baybutt & Manu Navjeevan, 2023. "Doubly-Robust Inference for Conditional Average Treatment Effects with High-Dimensional Controls," Papers 2301.06283, arXiv.org.
    10. Dmitry Arkhangelsky & Vasily Korovkin, 2020. "On Policy Evaluation with Aggregate Time-Series Shocks," CERGE-EI Working Papers wp657, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    11. Victor Chernozhukov & Chen Huang & Weining Wang, 2021. "Uniform Inference on High-dimensional Spatial Panel Networks," Papers 2105.07424, arXiv.org, revised Sep 2023.
    12. Manu Navjeevan, 2023. "An Identification and Dimensionality Robust Test for Instrumental Variables Models," Papers 2311.14892, arXiv.org.
    13. Victor Chernozhukov & Denis Chetverikov & Kengo Kato & Yuta Koike, 2019. "Improved Central Limit Theorem and bootstrap approximations in high dimensions," Papers 1912.10529, arXiv.org, revised May 2022.
    14. Baris Ata & Alexandre Belloni & Ozan Candogan, 2018. "Latent Agents in Networks: Estimation and Targeting," Papers 1808.04878, arXiv.org, revised Jan 2022.
    15. Masayuki Sawada & Kohei Kawaguchi, 2020. "Estimating High-Dimensional Discrete Choice Model of Differentiated Products with Random Coefficients," Papers 2004.08791, arXiv.org.
    16. Kea BARET, 2021. "Fiscal rules’ compliance and Social Welfare," Working Papers of BETA 2021-50, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    17. Xinwei Ma & Jingshen Wang, 2018. "Robust Inference Using Inverse Probability Weighting," Papers 1810.11397, arXiv.org, revised May 2019.

  10. Achim Ahrens & Christian B Hansen & Mark E Schaffer, 2018. "LASSOPACK and PDSLASSO: Prediction, model selection and causal inference with regularized regression," London Stata Conference 2018 12, Stata Users Group.

    Cited by:

    1. Alison Andrew & Sonya Krutikova & Gabriela Smarrelli & Hemlata Verma, 2022. "Gender norms, violence and adolescent girls’ trajectories: evidence from a field experiment in India," IFS Working Papers W22/41, Institute for Fiscal Studies.
    2. Alison Andrew & Sonya Krutikova & Gabriela Smarrelli & Hemlata Verma, 2022. "Gender norms, violence and adolescent girls' trajectories: evidence from a field experiment in India," Economics Series Working Papers 984, University of Oxford, Department of Economics.

  11. Alexandre Belloni & Christian Hansen & Whitney Newey, 2017. "Simultaneous Confidence Intervals for High-dimensional Linear Models with Many Endogenous Variables," Papers 1712.08102, arXiv.org, revised Aug 2019.

    Cited by:

    1. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Christian Hansen & Kengo Kato, 2018. "High-Dimensional Econometrics and Regularized GMM," Papers 1806.01888, arXiv.org, revised Jun 2018.
    2. Caner, Mehmet, 2023. "Generalized linear models with structured sparsity estimators," Journal of Econometrics, Elsevier, vol. 236(2).
    3. Breunig, Christoph & Mammen, Enno & Simoni, Anna, 2020. "Ill-posed estimation in high-dimensional models with instrumental variables," Journal of Econometrics, Elsevier, vol. 219(1), pages 171-200.
    4. Victor Chernozhukov & Chen Huang & Weining Wang, 2021. "Uniform Inference on High-dimensional Spatial Panel Networks," Papers 2105.07424, arXiv.org, revised Sep 2023.
    5. Baris Ata & Alexandre Belloni & Ozan Candogan, 2018. "Latent Agents in Networks: Estimation and Targeting," Papers 1808.04878, arXiv.org, revised Jan 2022.

  12. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney K. Newey & James Robins, 2017. "Double/debiased machine learning for treatment and structural parameters," CeMMAP working papers 28/17, Institute for Fiscal Studies.

    Cited by:

    1. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Christian Hansen & Kengo Kato, 2018. "High-Dimensional Econometrics and Regularized GMM," Papers 1806.01888, arXiv.org, revised Jun 2018.
    2. Nicolaj N. Mühlbach, 2020. "Tree-based Synthetic Control Methods: Consequences of moving the US Embassy," CREATES Research Papers 2020-04, Department of Economics and Business Economics, Aarhus University.
    3. Kyle Colangelo & Ying-Ying Lee, 2019. "Double debiased machine learning nonparametric inference with continuous treatments," CeMMAP working papers CWP72/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Julián Caballero & Christian Upper, 2023. "What happens to EMEs when US yields go up?," BIS Working Papers 1081, Bank for International Settlements.
    5. Tang, Shengfang & Huang, Zhilin, 2022. "Empirical likelihood confidence interval for difference-in-differences estimator with panel data," Economics Letters, Elsevier, vol. 216(C).
    6. Pedro H. C. Sant'Anna & Jun B. Zhao, 2018. "Doubly Robust Difference-in-Differences Estimators," Papers 1812.01723, arXiv.org, revised May 2020.
    7. Harsh Parikh & Carlos Varjao & Louise Xu & Eric Tchetgen Tchetgen, 2022. "Validating Causal Inference Methods," Papers 2202.04208, arXiv.org, revised Jul 2022.
    8. Kaspar Wuthrich & Ying Zhu, 2019. "Omitted variable bias of Lasso-based inference methods: A finite sample analysis," Papers 1903.08704, arXiv.org, revised Sep 2021.
    9. Xiong, Ruoxuan & Koenecke, Allison & Powell, Michael & Shen, Zhu & Vogelstein, Joshua T. & Athey, Susan, 2021. "Federated Causal Inference in Heterogeneous Observational Data," Research Papers 3990, Stanford University, Graduate School of Business.
    10. Huber, Martin, 2019. "An introduction to flexible methods for policy evaluation," FSES Working Papers 504, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    11. Patrick M. Schnell & Richard Baumgartner & Shahrul Mt‐Isa & Vladimir Svetnik, 2022. "A principal stratification approach to estimating the effect of continuing treatment after observing early outcomes," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1065-1084, November.
    12. Victor Chernozhukov & Mert Demirer & Esther Duflo & Ivan Fernandez-Val, 2017. "Generic machine learning inference on heterogenous treatment effects in randomized experiments," CeMMAP working papers CWP61/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    13. Khanh Duong, 2024. "Is meritocracy just? New evidence from Boolean analysis and Machine learning," Journal of Computational Social Science, Springer, vol. 7(2), pages 1795-1821, October.
    14. Susan Athey & Guido W. Imbens & Stefan Wager, 2018. "Approximate residual balancing: debiased inference of average treatment effects in high dimensions," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 80(4), pages 597-623, September.
    15. Borusyak, Kirill & Hull, Peter & Jaravel, Xavier, 2024. "Design-based identification with formula instruments: a review," LSE Research Online Documents on Economics 123848, London School of Economics and Political Science, LSE Library.
    16. Conti, Gabriella & Kliem, Soeren & Sandner, Malte, 2024. "Early Home Visiting Delivery Model and Maternal and Child Mental Health at Primary School Age," CEPR Discussion Papers 19327, C.E.P.R. Discussion Papers.
    17. Jelena Bradic & Weijie Ji & Yuqian Zhang, 2021. "High-dimensional Inference for Dynamic Treatment Effects," Papers 2110.04924, arXiv.org, revised May 2023.
    18. Davide Viviano & Jelena Bradic, 2019. "Synthetic learner: model-free inference on treatments over time," Papers 1904.01490, arXiv.org, revised Aug 2022.
    19. Goller, Daniel & Lechner, Michael & Moczall, Andreas & Wolff, Joachim, 2019. "Does the estimation of the propensity score by machine learning improve matching estimation? The case of Germany’s programmes for long term unemployed," Economics Working Paper Series 1910, University of St. Gallen, School of Economics and Political Science.
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    503. Zacharias Bragoudakis & Dimitrios Panas, 2021. "Investigating government spending multiplier for the US economy: empirical evidence using a triple lasso approach," Working Papers 292, Bank of Greece.
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    507. Denis Chetverikov & Yukun Liu & Aleh Tsyvinski, 2022. "Weighted-average quantile regression," Papers 2203.03032, arXiv.org.
    508. Qizhao Chen & Vasilis Syrgkanis & Morgane Austern, 2022. "Debiased Machine Learning without Sample-Splitting for Stable Estimators," Papers 2206.01825, arXiv.org, revised Nov 2022.
    509. Tomasz Olma, 2021. "Nonparametric Estimation of Truncated Conditional Expectation Functions," Papers 2109.06150, arXiv.org.
    510. Sourabh Balgi & Adel Daoud & Jose M. Pe~na & Geoffrey T. Wodtke & Jesse Zhou, 2024. "Deep Learning With DAGs," Papers 2401.06864, arXiv.org.
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    512. Sylvia Klosin, 2021. "Automatic Double Machine Learning for Continuous Treatment Effects," Papers 2104.10334, arXiv.org.
    513. Barbara Felderer & Jannis Kueck & Martin Spindler, 2021. "Big Data meets Causal Survey Research: Understanding Nonresponse in the Recruitment of a Mixed-mode Online Panel," Papers 2102.08994, arXiv.org.
    514. Bilancini, Ennio & Boncinelli, Leonardo & Di Paolo, Roberto & Menicagli, Dario & Pizziol, Veronica & Ricciardi, Emiliano & Serti, Francesco, 2022. "Prosocial behavior in emergencies: Evidence from blood donors recruitment and retention during the COVID-19 pandemic," Social Science & Medicine, Elsevier, vol. 314(C).
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    517. Yuqian Zhang & Weijie Ji & Jelena Bradic, 2021. "Dynamic treatment effects: high-dimensional inference under model misspecification," Papers 2111.06818, arXiv.org, revised Jun 2023.
    518. Falco J. Bargagli Stoffi & Kenneth De Beckker & Joana E. Maldonado & Kristof De Witte, 2021. "Assessing Sensitivity of Machine Learning Predictions.A Novel Toolbox with an Application to Financial Literacy," Papers 2102.04382, arXiv.org.
    519. Chen Qiu & Taisuke Otsu, 2022. "Information theoretic approach to high‐dimensional multiplicative models: Stochastic discount factor and treatment effect," Quantitative Economics, Econometric Society, vol. 13(1), pages 63-94, January.
    520. Daniel Jacob, 2021. "Variable Selection for Causal Inference via Outcome-Adaptive Random Forest," Papers 2109.04154, arXiv.org.
    521. Noemi Kreif & Andrew Mirelman & Rodrigo Moreno-Serra & Taufik Hidayat, & Karla DiazOrdaz & Marc Suhrcke, 2020. "Who benefits from health insurance? Uncovering heterogeneous policy impacts using causal machine learning," Working Papers 173cherp, Centre for Health Economics, University of York.
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    Cited by:

    1. Philippe Goulet Coulombe, 2020. "The Macroeconomy as a Random Forest," Papers 2006.12724, arXiv.org, revised Mar 2021.
    2. Vogt, M. & Walsh, C. & Linton, O., 2022. "CCE Estimation of High-Dimensional Panel Data Models with Interactive Fixed Effects," Cambridge Working Papers in Economics 2242, Faculty of Economics, University of Cambridge.
    3. Philippe Goulet Coulombe, 2021. "The Macroeconomy as a Random Forest," Working Papers 21-05, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
    4. Harold D. Chiang & Kengo Kato & Yukun Ma & Yuya Sasaki, 2022. "Multiway Cluster Robust Double/Debiased Machine Learning," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 1046-1056, June.
    5. Simon Freyaldenhoven & Christian Hansen & Jesse M. Shapiro, 2018. "Pre-event Trends in the Panel Event-study Design," NBER Working Papers 24565, National Bureau of Economic Research, Inc.
    6. Oliver Linton & Maximilian Ruecker & Michael Vogt & Christopher Walsh, 2022. "Estimation and Inference in High-Dimensional Panel Data Models with Interactive Fixed Effects," Papers 2206.12152, arXiv.org, revised Nov 2024.
    7. Victor Chernozhukov & Kaspar Wüthrich & Yinchu Zhu, 2021. "An Exact and Robust Conformal Inference Method for Counterfactual and Synthetic Controls," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(536), pages 1849-1864, October.
    8. Jad Beyhum & Jonas Striaukas, 2023. "Factor-augmented sparse MIDAS regressions with an application to nowcasting," Papers 2306.13362, arXiv.org, revised Nov 2024.
    9. Smeekes, Stephan & Wijler, Etiënne, 2016. "Macroeconomic Forecasting Using Penalized Regression Methods," Research Memorandum 039, Maastricht University, Graduate School of Business and Economics (GSBE).
    10. Vogt, M. & Walsh, C. & Linton, O., 2022. "CCE Estimation of High-Dimensional Panel Data Models with Interactive Fixed Effects," Janeway Institute Working Papers 2218, Faculty of Economics, University of Cambridge.

  14. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins, 2016. "Double/Debiased Machine Learning for Treatment and Causal Parameters," Papers 1608.00060, arXiv.org, revised Nov 2024.

    Cited by:

    1. Pedro H. C. Sant'Anna & Jun B. Zhao, 2018. "Doubly Robust Difference-in-Differences Estimators," Papers 1812.01723, arXiv.org, revised May 2020.
    2. Xiong, Ruoxuan & Koenecke, Allison & Powell, Michael & Shen, Zhu & Vogelstein, Joshua T. & Athey, Susan, 2021. "Federated Causal Inference in Heterogeneous Observational Data," Research Papers 3990, Stanford University, Graduate School of Business.
    3. Victor Chernozhukov & Mert Demirer & Esther Duflo & Ivan Fernandez-Val, 2017. "Generic machine learning inference on heterogenous treatment effects in randomized experiments," CeMMAP working papers CWP61/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Yoganathan, Vignesh & Osburg, Victoria-Sophie, 2024. "The mind in the machine: Estimating mind perception's effect on user satisfaction with voice-based conversational agents," Journal of Business Research, Elsevier, vol. 175(C).
    5. Maximilian Maurice Gail & Phil-Adrian Klotz, 2021. "The Impact of the Agency Model on E-book Prices: Evidence from the UK," MAGKS Papers on Economics 202111, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    6. Jong Hee Park & Byung Koo Kim, 2020. "Why your neighbor matters: Positions in preferential trade agreement networks and export growth in global value chains," Economics and Politics, Wiley Blackwell, vol. 32(3), pages 381-410, November.
    7. Ziwei Cong & Jia Liu & Puneet Manchanda, 2021. "The Role of "Live" in Livestreaming Markets: Evidence Using Orthogonal Random Forest," Papers 2107.01629, arXiv.org, revised Sep 2022.
    8. Susan Athey & Guido Imbens & Jonas Metzger & Evan Munro, 2019. "Using Wasserstein Generative Adversarial Networks for the Design of Monte Carlo Simulations," Papers 1909.02210, arXiv.org, revised Jul 2020.
    9. Miquel Oliu-Barton & Bary S R Pradelski & Nicolas Woloszko & Lionel Guetta-Jeanrenaud & Philippe Aghion & Patrick Artus & Arnaud Fontanet & Philippe Martin & Guntram B Wolff, 2022. "The Effect of COVID Certificates on Vaccine Uptake, Health Outcomes, and the Economy," Post-Print hal-03813557, HAL.
    10. Waverly Wei & Maya Petersen & Mark J van der Laan & Zeyu Zheng & Chong Wu & Jingshen Wang, 2023. "Efficient targeted learning of heterogeneous treatment effects for multiple subgroups," Biometrics, The International Biometric Society, vol. 79(3), pages 1934-1946, September.
    11. Jinyong Hahn & Jerry Hausman, 2021. "Problems with the Control Variable Approach in Achieving Unbiased Estimates in Nonlinear Models in the Presence of Many Instruments," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 39-58, December.
    12. Wang, Hongning & Ma, Sanjun, 2022. "Preventing crimes against public health with artificial intelligence and machine learning capabilities," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    13. Monica Andini & Emanuele Ciani & Guido de Blasio & Alessio D'Ignazio & Viola Salvestrini, 2017. "Targeting policy-compliers with machine learning: an application to a tax rebate programme in Italy," Temi di discussione (Economic working papers) 1158, Bank of Italy, Economic Research and International Relations Area.
    14. Francesco Decarolis & Cristina Giorgiantonio, 2020. "Corruption red flags in public procurement: new evidence from Italian calls for tenders," Questioni di Economia e Finanza (Occasional Papers) 544, Bank of Italy, Economic Research and International Relations Area.
    15. Hoang, Daniel & Wiegratz, Kevin, 2022. "Machine learning methods in finance: Recent applications and prospects," Working Paper Series in Economics 158, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    16. Huber, Martin & Wüthrich, Kaspar, 2019. "Local Average and Quantile Treatment Effects Under Endogeneity: A Review," University of California at San Diego, Economics Working Paper Series qt4j29d8sc, Department of Economics, UC San Diego.
    17. Valente, Marica, 2023. "Policy evaluation of waste pricing programs using heterogeneous causal effect estimation," Journal of Environmental Economics and Management, Elsevier, vol. 117(C).
    18. Anna Baiardi & Andrea A. Naghi, 2021. "The Value Added of Machine Learning to Causal Inference: Evidence from Revisited Studies," Papers 2101.00878, arXiv.org.
    19. Andr'es Ram'irez-Hassan & Raquel Vargas-Correa & Gustavo Garc'ia & Daniel Londo~no, 2020. "Optimal selection of the number of control units in kNN algorithm to estimate average treatment effects," Papers 2008.06564, arXiv.org.
    20. Zhen Li & Jie Chen & Eric Laber & Fang Liu & Richard Baumgartner, 2023. "Optimal Treatment Regimes: A Review and Empirical Comparison," International Statistical Review, International Statistical Institute, vol. 91(3), pages 427-463, December.
    21. Ganesh Karapakula, 2023. "Stable Probability Weighting: Large-Sample and Finite-Sample Estimation and Inference Methods for Heterogeneous Causal Effects of Multivalued Treatments Under Limited Overlap," Papers 2301.05703, arXiv.org, revised Jan 2023.
    22. Wang, Xiqian & Bian, Yong & Zhang, Qin, 2023. "The effect of cooking fuel choice on the elderly’s well-being: Evidence from two non-parametric methods," Energy Economics, Elsevier, vol. 125(C).
    23. Elliott Ash & Daniel L. Chen & Sergio Galletta, 2022. "Measuring Judicial Sentiment: Methods and Application to US Circuit Courts," Economica, London School of Economics and Political Science, vol. 89(354), pages 362-376, April.
    24. Pradhi Aggarwal & Alec Brandon & Ariel Goldszmidt & Justin Holz & John List & Ian Muir & Gregory Sun & Thomas Yu, 2022. "High-frequency location data shows that race affects the likelihood of being stopped and fined for speeding," Natural Field Experiments 00764, The Field Experiments Website.
    25. Songul Cinaroglu, 2020. "Modelling unbalanced catastrophic health expenditure data by using machine‐learning methods," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 27(4), pages 168-181, October.
    26. Matt Goldman & Brian Quistorff, 2018. "Pricing Engine: Estimating Causal Impacts in Real World Business Settings," Papers 1806.03285, arXiv.org, revised Jun 2018.
    27. Nikolaos Ignatiadis & Wolfgang Huber, 2021. "Covariate powered cross‐weighted multiple testing," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(4), pages 720-751, September.
    28. Miruna Oprescu & Vasilis Syrgkanis & Zhiwei Steven Wu, 2018. "Orthogonal Random Forest for Causal Inference," Papers 1806.03467, arXiv.org, revised Sep 2019.
    29. Gareth Liu-Evans & Shalini Mitra, 2023. "Formal sector enforcement and welfare," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 30(3), pages 706-728, June.
    30. Jiaming Mao & Jingzhi Xu, 2020. "Ensemble Learning with Statistical and Structural Models," Papers 2006.05308, arXiv.org.
    31. Aristide Houndetoungan & Abdoul Haki Maoude, 2024. "Inference for Two-Stage Extremum Estimators," THEMA Working Papers 2024-01, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    32. Fernando Delbianco & Fernando Tohmé, 2023. "Individualized Conformal," Working Papers 247, Red Nacional de Investigadores en Economía (RedNIE).
    33. Sander Gerritsen & Mark Kattenberg & Sonny Kuijpers, 2019. "The impact of age at arrival on education and mental health," CPB Discussion Paper 389, CPB Netherlands Bureau for Economic Policy Analysis.
    34. Fukuyama, Hirofumi & Tsionas, Mike & Tan, Yong, 2023. "Dynamic network data envelopment analysis with a sequential structure and behavioural-causal analysis: Application to the Chinese banking industry," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1360-1373.
    35. Mark Kattenberg & Bas Scheer & Jurre Thiel, 2023. "Causal forests with fixed effects for treatment effect heterogeneity in difference-in-differences," CPB Discussion Paper 452, CPB Netherlands Bureau for Economic Policy Analysis.
    36. Jonas Metzger, 2022. "Adversarial Estimators," Papers 2204.10495, arXiv.org, revised Jun 2022.
    37. Yuya Sasaki & Takuya Ura & Yichong Zhang, 2022. "Unconditional quantile regression with high‐dimensional data," Quantitative Economics, Econometric Society, vol. 13(3), pages 955-978, July.
    38. Guido W. Imbens, 2020. "Potential Outcome and Directed Acyclic Graph Approaches to Causality: Relevance for Empirical Practice in Economics," Journal of Economic Literature, American Economic Association, vol. 58(4), pages 1129-1179, December.
    39. Alexander Buchholz & Vito Bellini & Giuseppe Di Benedetto & Yannik Stein & Matteo Ruffini & Fabian Moerchen, 2022. "Fair Effect Attribution in Parallel Online Experiments," Papers 2210.08338, arXiv.org.
    40. Duncan Simester & Artem Timoshenko & Spyros I. Zoumpoulis, 2020. "Targeting Prospective Customers: Robustness of Machine-Learning Methods to Typical Data Challenges," Management Science, INFORMS, vol. 66(6), pages 2495-2522, June.
    41. Heigle, Julia & Pfeiffer, Friedhelm, 2019. "An analysis of selected labor market outcomes of college dropouts in Germany: A machine learning estimation approach. Research report," ZEW Expertises, ZEW - Leibniz Centre for European Economic Research, number 222378.
    42. Belloni, Alexandre & Hansen, Christian & Newey, Whitney, 2022. "High-dimensional linear models with many endogenous variables," Journal of Econometrics, Elsevier, vol. 228(1), pages 4-26.
    43. Sven Klaassen & Jannis Kück & Martin Spindler & Victor Chernozhukov, 2019. "Uniform inference in high-dimensional Gaussian graphical models," CeMMAP working papers CWP29/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    44. Ashkan Ertefaie & Nima S. Hejazi & Mark J. van der Laan, 2023. "Nonparametric inverse‐probability‐weighted estimators based on the highly adaptive lasso," Biometrics, The International Biometric Society, vol. 79(2), pages 1029-1041, June.
    45. Victor Chernozhukov & Carlos Cinelli & Whitney Newey & Amit Sharma & Vasilis Syrgkanis, 2022. "Long Story Short: Omitted Variable Bias in Causal Machine Learning," NBER Working Papers 30302, National Bureau of Economic Research, Inc.
    46. Jushan Bai & Sung Hoon Choi & Yuan Liao, 2019. "Feasible Generalized Least Squares for Panel Data with Cross-sectional and Serial Correlations," Papers 1910.09004, arXiv.org, revised Aug 2020.
    47. Esfandiar Maasoumi & Jianqiu Wang & Zhuo Wang & Ke Wu, 2024. "Identifying factors via automatic debiased machine learning," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(3), pages 438-461, April.
    48. Retsef Levi & Elisabeth Paulson & Georgia Perakis & Emily Zhang, 2024. "Heterogeneous Treatment Effects in Panel Data," Papers 2406.05633, arXiv.org.
    49. Abadie, Alberto & Gu, Jiaying & Shen, Shu, 2024. "Instrumental variable estimation with first-stage heterogeneity," Journal of Econometrics, Elsevier, vol. 240(2).
    50. Ke Sun & Linglong Kong & Hongtu Zhu & Chengchun Shi, 2024. "Optimal Treatment Allocation Strategies for A/B Testing in Partially Observable Time Series Experiments," Papers 2408.05342, arXiv.org, revised Oct 2024.
    51. Whitney K. Newey & James M. Robins, 2017. "Cross-fitting and fast remainder rates for semiparametric estimation," CeMMAP working papers 41/17, Institute for Fiscal Studies.
    52. Xing, Lu & Han, DongHao & Hui, Xie, 2023. "The impact of carbon policy on corporate risk-taking with a double/debiased machine learning based difference-in-differences approach," Finance Research Letters, Elsevier, vol. 58(PC).
    53. Delprato, Marcos & Frola, Alessia & Antequera, Germán, 2022. "Indigenous and non-Indigenous proficiency gaps for out-of-school and in-school populations: A machine learning approach," International Journal of Educational Development, Elsevier, vol. 93(C).
    54. Anna Baiardi & Andrea A. Naghi, 2021. "The Value Added of Machine Learning to Causal Inference: Evidence from Revisited Studies," Tinbergen Institute Discussion Papers 21-001/V, Tinbergen Institute.
    55. Aristide Houndetoungan & Abdoul Haki Maoude, 2024. "Inference for Two-Stage Extremum Estimators," Papers 2402.05030, arXiv.org, revised Nov 2024.
    56. Oliver Hines & Stijn Vansteelandt & Karla Diaz-Ordaz, 2021. "Robust Inference for Mediated Effects in Partially Linear Models," Psychometrika, Springer;The Psychometric Society, vol. 86(2), pages 595-618, June.
    57. Ziwei Mei & Zhentao Shi, 2022. "On LASSO for High Dimensional Predictive Regression," Papers 2212.07052, arXiv.org, revised Jan 2024.
    58. Vira Semenova, 2017. "Debiased Machine Learning of Set-Identified Linear Models," Papers 1712.10024, arXiv.org, revised Dec 2022.
    59. Amit Sharma & Emre Kiciman, 2020. "DoWhy: An End-to-End Library for Causal Inference," Papers 2011.04216, arXiv.org.
    60. Feng, Sanying & Kong, Kaidi & Kong, Yinfei & Li, Gaorong & Wang, Zhaoliang, 2022. "Statistical inference of heterogeneous treatment effect based on single-index model," Computational Statistics & Data Analysis, Elsevier, vol. 175(C).
    61. Victor Chernozhukov & Whitney Newey & Vira Semenova, 2019. "Welfare Analysis in Dynamic Models," Papers 1908.09173, arXiv.org, revised Nov 2024.
    62. Yong Bian & Xiqian Wang & Qin Zhang, 2023. "How Does China's Household Portfolio Selection Vary with Financial Inclusion?," Papers 2311.01206, arXiv.org.
    63. Ricardo P. Masini & Marcelo C. Medeiros & Eduardo F. Mendes, 2020. "Machine Learning Advances for Time Series Forecasting," Papers 2012.12802, arXiv.org, revised Apr 2021.
    64. Jules Gazeaud & Nausheen Khan & Eric Mvukiyehe & Olivier Sterck, 2023. "With or without him? Experimental evidence on cash grants and gender-sensitive trainings in Tunisia," Post-Print hal-04364356, HAL.
    65. Sven Klaassen & Jannis Kueck & Martin Spindler, 2017. "Transformation Models in High-Dimensions," Papers 1712.07364, arXiv.org.
    66. Helmut Wasserbacher & Martin Spindler, 2022. "Machine learning for financial forecasting, planning and analysis: recent developments and pitfalls," Digital Finance, Springer, vol. 4(1), pages 63-88, March.
    67. Jikai Jin & Vasilis Syrgkanis, 2024. "Structure-agnostic Optimality of Doubly Robust Learning for Treatment Effect Estimation," Papers 2402.14264, arXiv.org, revised Mar 2024.
    68. Andrew Bennett & Nathan Kallus & Xiaojie Mao & Whitney Newey & Vasilis Syrgkanis & Masatoshi Uehara, 2023. "Source Condition Double Robust Inference on Functionals of Inverse Problems," Papers 2307.13793, arXiv.org.
    69. Vira Semenova, 2018. "Machine Learning for Dynamic Discrete Choice," Papers 1808.02569, arXiv.org, revised Nov 2018.
    70. Carl Bonander & Mikael Svensson, 2021. "Using causal forests to assess heterogeneity in cost‐effectiveness analysis," Health Economics, John Wiley & Sons, Ltd., vol. 30(8), pages 1818-1832, August.
    71. Maria Cuellar & Edward H. Kennedy, 2020. "A non‐parametric projection‐based estimator for the probability of causation, with application to water sanitation in Kenya," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(4), pages 1793-1818, October.
    72. Paolo Libenzio Brignoli & Alessandro Varacca & Cornelis Gardebroek & Paolo Sckokai, 2024. "Machine learning to predict grains futures prices," Agricultural Economics, International Association of Agricultural Economists, vol. 55(3), pages 479-497, May.
    73. Su, Liangjun & Ura, Takuya & Zhang, Yichong, 2017. "Non-separable Models with High-dimensional Data," Economics and Statistics Working Papers 15-2017, Singapore Management University, School of Economics.
    74. Andres Algaba & David Ardia & Keven Bluteau & Samuel Borms & Kris Boudt, 2020. "Econometrics Meets Sentiment: An Overview Of Methodology And Applications," Journal of Economic Surveys, Wiley Blackwell, vol. 34(3), pages 512-547, July.
    75. Anna Baiardi & Andrea A Naghi, 2024. "The value added of machine learning to causal inference: evidence from revisited studies," The Econometrics Journal, Royal Economic Society, vol. 27(2), pages 213-234.
    76. Madadkhani, Shiva & Ikonnikova, Svetlana, 2024. "Toward high-resolution projection of electricity prices: A machine learning approach to quantifying the effects of high fuel and CO2 prices," Energy Economics, Elsevier, vol. 129(C).
    77. Whitney K. Newey & James M. Robins, 2017. "Cross-fitting and fast remainder rates for semiparametric estimation," CeMMAP working papers CWP41/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    78. Julia Hatamyar & Noemi Kreif, 2023. "Policy Learning with Rare Outcomes," Papers 2302.05260, arXiv.org, revised Oct 2023.
    79. Heiler, Phillip & Kazak, Ekaterina, 2021. "Valid inference for treatment effect parameters under irregular identification and many extreme propensity scores," Journal of Econometrics, Elsevier, vol. 222(2), pages 1083-1108.
    80. Jiaming Mao & Zhesheng Zheng, 2020. "Structural Regularization," Papers 2004.12601, arXiv.org, revised Jun 2020.
    81. Mochen Yang & Edward McFowland & Gordon Burtch & Gediminas Adomavicius, 2022. "Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem," INFORMS Joural on Data Science, INFORMS, vol. 1(2), pages 138-155, October.
    82. Dmitry Arkhangelsky & Guido Imbens, 2023. "Causal Models for Longitudinal and Panel Data: A Survey," Papers 2311.15458, arXiv.org, revised Jun 2024.
    83. Andrew Bennett & Nathan Kallus & Xiaojie Mao & Whitney Newey & Vasilis Syrgkanis & Masatoshi Uehara, 2022. "Inference on Strongly Identified Functionals of Weakly Identified Functions," Papers 2208.08291, arXiv.org, revised Jun 2023.
    84. Dongcheng Zhang & Kunpeng Zhang, 2020. "Weighting-Based Treatment Effect Estimation via Distribution Learning," Papers 2012.13805, arXiv.org, revised May 2023.
    85. Falco J. Bargagli Stoffi & Kenneth De Beckker & Joana E. Maldonado & Kristof De Witte, 2021. "Assessing Sensitivity of Machine Learning Predictions.A Novel Toolbox with an Application to Financial Literacy," Papers 2102.04382, arXiv.org.
    86. Guber, Raphael, 2018. "Instrument Validity Tests with Causal Trees: With an Application to the Same-sex Instrument," MEA discussion paper series 201805, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
    87. Pranjal Rawat, 2024. "A Deep Learning Approach to Heterogeneous Consumer Aesthetics in Retail Fashion," Papers 2405.10498, arXiv.org.
    88. Phillip Heiler, 2020. "Efficient Covariate Balancing for the Local Average Treatment Effect," Papers 2007.04346, arXiv.org.
    89. Johannes Jakubik & Stefan Feuerriegel, 2022. "Data‐driven allocation of development aid toward sustainable development goals: Evidence from HIV/AIDS," Production and Operations Management, Production and Operations Management Society, vol. 31(6), pages 2739-2756, June.

  15. Victor Chernozhukov & Christian Hansen & Martin Spindler, 2016. "hdm: High-Dimensional Metrics," CeMMAP working papers 37/16, Institute for Fiscal Studies.

    Cited by:

    1. Edward I. Altman & Marco Balzano & Alessandro Giannozzi & Stjepan Srhoj, 2023. "Revisiting SME default predictors: The Omega Score," Journal of Small Business Management, Taylor & Francis Journals, vol. 61(6), pages 2383-2417, November.
    2. Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen, 2016. "Program evaluation and causal inference with high-dimensional data," CeMMAP working papers 13/16, Institute for Fiscal Studies.
    3. Daniels, David P. & Zlatev, Julian J., 2019. "Choice architects reveal a bias toward positivity and certainty," Organizational Behavior and Human Decision Processes, Elsevier, vol. 151(C), pages 132-149.
    4. Wallimann, Hannes & Imhof, David & Huber, Martin, 2020. "A Machine Learning Approach for Flagging Incomplete Bid-rigging Cartels," FSES Working Papers 513, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    5. Harold D. Chiang, 2019. "Many Average Partial Effects: with an Application to Text Regression," 2019 Papers pch1836, Job Market Papers.
    6. Gangl, Selina & Huber, Martin, 2021. "From homemakers to breadwinners? How mandatory kindergarten affects maternal labour market attachment," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203636, Verein für Socialpolitik / German Economic Association, revised 2021.
    7. Imhof, David & Wallimann, Hannes, 2021. "Detecting bid-rigging coalitions in different countries and auction formats," International Review of Law and Economics, Elsevier, vol. 68(C).
    8. Philipp Bach & Victor Chernozhukov & Malte S. Kurz & Martin Spindler & Sven Klaassen, 2021. "DoubleML -- An Object-Oriented Implementation of Double Machine Learning in R," Papers 2103.09603, arXiv.org, revised Jun 2024.
    9. Philipp Bach & Victor Chernozhukov & Martin Spindler, 2018. "Valid Simultaneous Inference in High-Dimensional Settings (with the hdm package for R)," Papers 1809.04951, arXiv.org.
    10. Huber, Martin & Imhof, David, 2018. "Machine Learning with Screens for Detecting Bid-Rigging Cartels," FSES Working Papers 494, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    11. Abadie, Alberto & Gu, Jiaying & Shen, Shu, 2024. "Instrumental variable estimation with first-stage heterogeneity," Journal of Econometrics, Elsevier, vol. 240(2).
    12. Godzinski, Alexandre & Suarez Castillo, Milena, 2021. "Disentangling the effects of air pollutants with many instruments," Journal of Environmental Economics and Management, Elsevier, vol. 109(C).
    13. Ismael Mourifié, 2019. "A marriage matching function with flexible spillover and substitution patterns," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 67(2), pages 421-461, March.
    14. Stefan Seifert & Marica Valente, 2018. "An Offer that you Can't Refuse? Agrimafias and Migrant Labor on Vineyards in Southern Italy," Discussion Papers of DIW Berlin 1735, DIW Berlin, German Institute for Economic Research.
    15. Selina Gangl & Martin Huber, 2021. "From homemakers to breadwinners? How mandatory kindergarten affects maternal labour market outcomes," Papers 2111.14524, arXiv.org, revised Mar 2022.
    16. Elena Denisova-Schmidt & Martin Huber & Elvira Leontyeva & Anna Solovyeva, 2021. "Combining experimental evidence with machine learning to assess anti-corruption educational campaigns among Russian university students," Empirical Economics, Springer, vol. 60(4), pages 1661-1684, April.
    17. Ruben Dezeure & Peter Bühlmann & Cun-Hui Zhang, 2017. "High-dimensional simultaneous inference with the bootstrap," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(4), pages 685-719, December.
    18. Pawel Dlotko & Simon Rudkin & Wanling Qiu, 2019. "Topologically Mapping the Macroeconomy," Papers 1911.10476, arXiv.org.
    19. Marica Valente & Timm Gries & Lorenzo Trapani, 2023. "Informal employment from migration shocks," Working Papers 2023-09, Faculty of Economics and Statistics, Universität Innsbruck.
    20. Simone Maxand & Hend Sallam, 2024. "Local Fiscal Effects of Immigration in Germany," CESifo Working Paper Series 11162, CESifo.

  16. Christian Hansen & Damian Kozbur & Sanjog Misra, 2016. "Targeted undersmoothing," ECON - Working Papers 282, Department of Economics - University of Zurich, revised Apr 2018.

    Cited by:

    1. Victor Chernozhukov & Mert Demirer & Esther Duflo & Ivan Fernandez-Val, 2017. "Generic machine learning inference on heterogenous treatment effects in randomized experiments," CeMMAP working papers CWP61/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Victor Chernozhukov & Mert Demirer & Esther Duflo & Iván Fernández-Val, 2023. "Fischer-Schultz Lecture: Generic Machine Learning Inference on Heterogenous Treatment Effects in Randomized Experiments, with an Application to Immunization in India," Working Papers hal-04238425, HAL.
    3. Jean-Pierre Dubé & Sanjog Misra, 2017. "Personalized Pricing and Consumer Welfare," NBER Working Papers 23775, National Bureau of Economic Research, Inc.
    4. Damian Kozbur, 2013. "Inference in additively separable models with a high-dimensional set of conditioning variables," ECON - Working Papers 284, Department of Economics - University of Zurich, revised Apr 2018.
    5. Shi, Zhentao & Huang, Jingyi, 2023. "Forward-selected panel data approach for program evaluation," Journal of Econometrics, Elsevier, vol. 234(2), pages 512-535.

  17. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney K. Newey, 2016. "Double machine learning for treatment and causal parameters," CeMMAP working papers 49/16, Institute for Fiscal Studies.

    Cited by:

    1. Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen, 2016. "Program evaluation and causal inference with high-dimensional data," CeMMAP working papers 13/16, Institute for Fiscal Studies.
    2. Christian Hansen & Damian Kozbur & Sanjog Misra, 2016. "Targeted undersmoothing," ECON - Working Papers 282, Department of Economics - University of Zurich, revised Apr 2018.
    3. Christian Hansen & Yuan Liao, 2016. "The Factor-Lasso and K-Step Bootstrap Approach for Inference in High-Dimensional Economic Applications," Papers 1611.09420, arXiv.org, revised Dec 2016.
    4. Alexandrov, Alexei & Pittman, Russell & Ukhaneva, Olga, 2018. "Pricing of Complements in the U.S. freight railroads: Cournot versus Coase," MPRA Paper 86279, University Library of Munich, Germany.
    5. Bernard Koch & Tim Sainburg & Pablo Geraldo & Song Jiang & Yizhou Sun & Jacob Gates Foster, 2021. "A Primer on Deep Learning for Causal Inference," Papers 2110.04442, arXiv.org, revised Nov 2023.
    6. Damian Kozbur, 2015. "Testing-Based Forward Model Selection," ECON - Working Papers 283, Department of Economics - University of Zurich, revised Apr 2018.
    7. Susan Athey & Julie Tibshirani & Stefan Wager, 2016. "Generalized Random Forests," Papers 1610.01271, arXiv.org, revised Apr 2018.
    8. Khashayar Khosravi & Greg Lewis & Vasilis Syrgkanis, 2019. "Non-Parametric Inference Adaptive to Intrinsic Dimension," Papers 1901.03719, arXiv.org, revised Jun 2019.
    9. Victor Chernozhukov & Juan Carlos Escanciano & Hidehiko Ichimura & Whitney K. Newey & James M. Robins, 2016. "Locally Robust Semiparametric Estimation," Papers 1608.00033, arXiv.org, revised Aug 2020.
    10. Zhengyuan Zhou & Susan Athey & Stefan Wager, 2018. "Offline Multi-Action Policy Learning: Generalization and Optimization," Papers 1810.04778, arXiv.org, revised Nov 2018.
    11. Kueck, Jannis & Luo, Ye & Spindler, Martin & Wang, Zigan, 2023. "Estimation and inference of treatment effects with L2-boosting in high-dimensional settings," Journal of Econometrics, Elsevier, vol. 234(2), pages 714-731.
    12. Lauren Cappiello & Zhiwei Zhang & Changyu Shen & Neel M. Butala & Xinping Cui & Robert W. Yeh, 2021. "Adjusting for population differences using machine learning methods," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(3), pages 750-769, June.
    13. Yan-Yu Chiou & Mei-Yuan Chen & Jau-er Chen, 2017. "Nonparametric Regression with Multiple Thresholds: Estimation and Inference," Papers 1705.09418, arXiv.org, revised Feb 2018.
    14. Jannis Kueck & Ye Luo & Martin Spindler & Zigan Wang, 2017. "Estimation and Inference of Treatment Effects with $L_2$-Boosting in High-Dimensional Settings," Papers 1801.00364, arXiv.org, revised Jul 2021.
    15. Jiaming Mao & Jingzhi Xu, 2020. "Ensemble Learning with Statistical and Structural Models," Papers 2006.05308, arXiv.org.
    16. Dmitry Arkhangelsky & Guido W. Imbens, 2019. "The Role of the Propensity Score in Fixed Effect Models," Working Papers wp2019_1905, CEMFI.
    17. Jean-Pierre Dubé & Sanjog Misra, 2017. "Personalized Pricing and Consumer Welfare," NBER Working Papers 23775, National Bureau of Economic Research, Inc.
    18. Daniel L. Chen & Markus Loecher, 2022. "Mood and the Malleability of Moral Reasoning: The Impact of Irrelevant Factors on Judicial Decisions," Working Papers hal-03864854, HAL.
    19. Victor Chernozhukov & Vira Semenova, 2018. "Simultaneous inference for Best Linear Predictor of the Conditional Average Treatment Effect and other structural functions," CeMMAP working papers CWP40/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    20. Ryo Aruga & Keiichi Goshima & Takashi Chiba, 2022. "CO2 Emissions and Corporate Performance: Japan's Evidence with Double Machine Learning," IMES Discussion Paper Series 22-E-01, Institute for Monetary and Economic Studies, Bank of Japan.
    21. Susan Athey & Guido Imbens, 2016. "The State of Applied Econometrics - Causality and Policy Evaluation," Papers 1607.00699, arXiv.org.
    22. Susan Athey & Stefan Wager, 2021. "Policy Learning With Observational Data," Econometrica, Econometric Society, vol. 89(1), pages 133-161, January.
    23. Jushan Bai & Sung Hoon Choi & Yuan Liao, 2019. "Feasible Generalized Least Squares for Panel Data with Cross-sectional and Serial Correlations," Papers 1910.09004, arXiv.org, revised Aug 2020.
    24. Crane-Droesch, Andrew, 2017. "Semiparametric Panel Data Using Neural Networks," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258128, Agricultural and Applied Economics Association.
    25. Chernozhukov, Victor & Härdle, Wolfgang Karl & Huang, Chen & Wang, Weining, 2018. "LASSO-Driven Inference in Time and Space," IRTG 1792 Discussion Papers 2018-021, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    26. Alexandrov, Alexei & Pittman, Russell & Ukhaneva, Olga, 2017. "Royalty stacking in the U.S. freight railroads: Cournot vs. Coase," MPRA Paper 78249, University Library of Munich, Germany.
    27. Jiaming Mao & Zhesheng Zheng, 2020. "Structural Regularization," Papers 2004.12601, arXiv.org, revised Jun 2020.
    28. Mochen Yang & Edward McFowland & Gordon Burtch & Gediminas Adomavicius, 2022. "Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem," INFORMS Joural on Data Science, INFORMS, vol. 1(2), pages 138-155, October.
    29. Chiou, Yan-Yu & Chen, Mei-Yuan & Chen, Jau-er, 2018. "Nonparametric regression with multiple thresholds: Estimation and inference," Journal of Econometrics, Elsevier, vol. 206(2), pages 472-514.
    30. Lester Mackey & Vasilis Syrgkanis & Ilias Zadik, 2017. "Orthogonal Machine Learning: Power and Limitations," Papers 1711.00342, arXiv.org, revised Aug 2018.
    31. Thai T. Pham & Yuanyuan Shen, 2017. "A Deep Causal Inference Approach to Measuring the Effects of Forming Group Loans in Online Non-profit Microfinance Platform," Papers 1706.02795, arXiv.org.

  18. Victor Chernozhukov & Christian Hansen & Yuan Liao, 2015. "A lava attack on the recovery of sums of dense and sparse signals," Papers 1502.03155, arXiv.org, revised Mar 2015.

    Cited by:

    1. Victor Chernozhukov & Christian Hansen & Yuan Liao, 2015. "A lava attack on the recovery of sums of dense and sparse signals," CeMMAP working papers 05/15, Institute for Fiscal Studies.

  19. Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Post-Selection and Post-Regularization Inference in Linear Models with Many Controls and Instruments," Papers 1501.03185, arXiv.org.

    Cited by:

    1. Bottmer, Lea & Croux, Christophe & Wilms, Ines, 2022. "Sparse regression for large data sets with outliers," European Journal of Operational Research, Elsevier, vol. 297(2), pages 782-794.
    2. Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen, 2016. "Program evaluation and causal inference with high-dimensional data," CeMMAP working papers 13/16, Institute for Fiscal Studies.
    3. Franz Huber & Alan Ponce & Francesco Rentocchini & Thomas Wainwright, 2020. "The Wealth of (Open Data) Nations? Examining the interplay of open government data and country-level institutions for entrepreneurial activity at the country-level," SEEDS Working Papers 1120, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Nov 2020.
    4. Peter C. B. Phillips & Zhentao Shi, 2021. "Boosting: Why You Can Use The Hp Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 62(2), pages 521-570, May.
    5. Shukla, Pallavi & Pullabhotla, Hemant K. & Baylis, Kathy, 2022. "Trouble with zero: The limits of subsidizing technology adoption," Journal of Development Economics, Elsevier, vol. 158(C).
    6. Giuseppe de Luca & Jan Magnus & Franco Peracchi, 2017. "Weighted-Average Least Squares Estimation of Generalized Linear Models," Tinbergen Institute Discussion Papers 17-029/III, Tinbergen Institute.
    7. Bilgin, Rumeysa, 2023. "The Selection Of Control Variables In Capital Structure Research With Machine Learning," SocArXiv e26qf, Center for Open Science.
    8. Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2019. "lassopack: Model selection and prediction with regularized regression in Stata," Papers 1901.05397, arXiv.org.
    9. Cameron, Lisa & Gertler, Paul & Shah, Manisha & Alzua, Maria Laura & Martinez, Sebastian & Patil, Sumeet, 2022. "The dirty business of eliminating open defecation: The effect of village sanitation on child height from field experiments in four countries," Journal of Development Economics, Elsevier, vol. 159(C).
    10. Alessandro V. M. Oliveira & Bruno F. Oliveira & Moises D. Vassallo, 2024. "Airport service quality perception and flight delays: examining the influence of psychosituational latent traits of respondents in passenger satisfaction surveys," Papers 2401.02139, arXiv.org.
    11. Seojeong Lee & Youngki Shin, 2021. "Complete subset averaging with many instruments," The Econometrics Journal, Royal Economic Society, vol. 24(2), pages 290-314.
    12. Peter C.B. Phillips & Zhentao Shi, 2019. "Boosting the Hodrick-Prescott Filter," Cowles Foundation Discussion Papers 2192, Cowles Foundation for Research in Economics, Yale University.
    13. Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Post-selection and post-regularization inference in linear models with many controls and instruments," CeMMAP working papers CWP02/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    14. Kaila, Heidi & Azad, Abul, 2023. "The effects of crime and violence on food insecurity and consumption in Nigeria," Food Policy, Elsevier, vol. 115(C).
    15. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney K. Newey & James Robins, 2017. "Double/debiased machine learning for treatment and structural parameters," CeMMAP working papers CWP28/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    16. Frank Windmeijer & Helmut Farbmacher & Neil Davies & George Davey Smith, 2016. "On the Use of the Lasso for Instrumental Variables Estimation with Some Invalid Instruments," Bristol Economics Discussion Papers 16/674, School of Economics, University of Bristol, UK, revised 08 Aug 2017.
    17. Li, Jing & Li, Liyao & Liu, Shimeng, 2022. "Attenuation of agglomeration economies: Evidence from the universe of Chinese manufacturing firms," Journal of Urban Economics, Elsevier, vol. 130(C).
    18. Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen, 2014. "Program evaluation with high-dimensional data," CeMMAP working papers CWP33/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    19. Christian B. Hansen & Mark E. Schaffer & Thomas Wiemann & Achim Ahrens, 2022. "ddml: Double/debiased machine learning in Stata," Swiss Stata Conference 2022 02, Stata Users Group.
    20. Breunig, Christoph & Mammen, Enno & Simoni, Anna, 2020. "Ill-posed estimation in high-dimensional models with instrumental variables," Journal of Econometrics, Elsevier, vol. 219(1), pages 171-200.
    21. Tomaso Duso & Claus Michelsen & Maximilian Schäfer & Kevin Ducbao Tran, 2021. "Airbnb and Rental Markets: Evidence from Berlin," CESifo Working Paper Series 9089, CESifo.
    22. Wang, Steven Shuye & Xu, Kuan & Zhang, Hao, 2019. "A microstructure study of circuit breakers in the Chinese stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 57(C).
    23. Isaac K. Ofori & Christopher Quaidoo & Pamela E. Ofori, 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," Working Papers 21/074, European Xtramile Centre of African Studies (EXCAS).
    24. Lai Xinglin, 2021. "Modelling hetegeneous treatment effects by quantitle local polynomial decision tree and forest," Papers 2111.15320, arXiv.org, revised Mar 2022.
    25. Samarth Gupta, 2020. "Model-Selection Inference for Causal Impact of Clusters and Collaboration on MSMEs in India," NCAER Working Papers 129, National Council of Applied Economic Research.
    26. Guo, Zijian & Kang, Hyunseung & Cai, T. Tony & Small, Dylan S., 2018. "Testing endogeneity with high dimensional covariates," Journal of Econometrics, Elsevier, vol. 207(1), pages 175-187.
    27. Joshua D. Angrist & Brigham Frandsen, 2022. "Machine Labor," Journal of Labor Economics, University of Chicago Press, vol. 40(S1), pages 97-140.
    28. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney K. Newey, 2016. "Double machine learning for treatment and causal parameters," CeMMAP working papers CWP49/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    29. Sander Gerritsen & Mark Kattenberg & Sonny Kuijpers, 2019. "The impact of age at arrival on education and mental health," CPB Discussion Paper 389, CPB Netherlands Bureau for Economic Policy Analysis.
    30. Pushan Dutt & Ilia Tsetlin, 2021. "Income distribution and economic development: Insights from machine learning," Economics and Politics, Wiley Blackwell, vol. 33(1), pages 1-36, March.
    31. Tomaso Duso & Claus Michelsen & Maximilian Schäfer & Kevin Ducbao Tran, 2020. "Airbnb and Rents: Evidence from Berlin," Discussion Papers of DIW Berlin 1890, DIW Berlin, German Institute for Economic Research.
    32. Philipp Bach & Victor Chernozhukov & Malte S. Kurz & Martin Spindler & Sven Klaassen, 2021. "DoubleML -- An Object-Oriented Implementation of Double Machine Learning in R," Papers 2103.09603, arXiv.org, revised Jun 2024.
    33. Alexandre Belloni & Mingli Chen & Victor Chernozhukov, 2017. "Quantile graphical models: prediction and conditional independence with applications to systemic risk," CeMMAP working papers 54/17, Institute for Fiscal Studies.
    34. Brito, Igor R.S. & Oliveira, Alessandro V.M. & Dresner, Martin E., 2021. "An econometric study of the effects of airport privatization on airfares in Brazil," Transport Policy, Elsevier, vol. 114(C), pages 338-349.
    35. Duso, Tomaso & Michelsen, Claus & Schaefer, Maximilian & Tran, Kevin Ducbao, 2024. "Airbnb and rental markets: Evidence from Berlin," Regional Science and Urban Economics, Elsevier, vol. 106(C).
    36. Seojeong Lee & Youngki Shin, 2018. "Optimal Estimation with Complete Subsets of Instruments," Department of Economics Working Papers 2018-15, McMaster University.
    37. Luca J. Santos & Alessandro V. M. Oliveira & Dante Mendes Aldrighi, 2021. "Testing the differentiated impact of the COVID-19 pandemic on air travel demand considering social inclusion," Papers 2108.00850, arXiv.org.
    38. Belloni, Alexandre & Hansen, Christian & Newey, Whitney, 2022. "High-dimensional linear models with many endogenous variables," Journal of Econometrics, Elsevier, vol. 228(1), pages 4-26.
    39. Koen van Ruijven & Joep Tijm, 2021. "Housing Market Effects of a Railroad Tunneling: Evidence from a quasi-experiment," CPB Discussion Paper 423, CPB Netherlands Bureau for Economic Policy Analysis.
    40. Rishabh Tyagi & Peter Eibich & Vegard Skirbekk, 2024. "Gender norms and partnership dissolution following involuntary job loss in Germany," MPIDR Working Papers WP-2024-027, Max Planck Institute for Demographic Research, Rostock, Germany.
    41. Zhong, Wei & Gao, Yang & Zhou, Wei & Fan, Qingliang, 2021. "Endogenous treatment effect estimation using high-dimensional instruments and double selection," Statistics & Probability Letters, Elsevier, vol. 169(C).
    42. Krüger, Jens J. & Rhiel, Mathias, 2016. "Determinants of ICT infrastructure: A cross-country statistical analysis," Darmstadt Discussion Papers in Economics 228, Darmstadt University of Technology, Department of Law and Economics.
    43. Godzinski, Alexandre & Suarez Castillo, Milena, 2021. "Disentangling the effects of air pollutants with many instruments," Journal of Environmental Economics and Management, Elsevier, vol. 109(C).
    44. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins, 2016. "Double/Debiased Machine Learning for Treatment and Causal Parameters," Papers 1608.00060, arXiv.org, revised Nov 2024.
    45. Christis Katsouris, 2023. "High Dimensional Time Series Regression Models: Applications to Statistical Learning Methods," Papers 2308.16192, arXiv.org.
    46. Woodruff, Christopher & Menzel, Andreas, 2019. "Gender Wage Gaps and Worker Mobility: Evidence from the Garment Sector in Bangladesh," CEPR Discussion Papers 13577, C.E.P.R. Discussion Papers.
    47. Gal Amedi, 2023. "The Determinants of the Transit Accessibility Premium," Bank of Israel Working Papers 2023.12, Bank of Israel.
    48. Aglasan, Serkan & Goodwin, Barry K. & Rejesus, Roderick, 2020. "Genetically Modified Rootworm-Resistant Corn, Risk, and Weather: Evidence from High Dimensional Methods," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 305181, Agricultural and Applied Economics Association.
    49. Bendini,Maria Magdalena & Dinarte Diaz,Lelys Ileana, 2020. "Does Maternal Depression Undermine Childhood Cognitive Development? Evidence from the Young Lives Survey in Peru," Policy Research Working Paper Series 9479, The World Bank.
    50. Michael Danquah & Abdul Malik Iddrisu & Ernest Owusu Boakye & Solomon Owusu, 2021. "Do gender wage differences within households influence women's empowerment and welfare?: Evidence from Ghana," WIDER Working Paper Series wp-2021-40, World Institute for Development Economic Research (UNU-WIDER).
    51. Ruf, Daniel, 2017. "Agglomeration Effects and Liquidity Gradients in Local Rental Housing Markets," Working Papers on Finance 1702, University of St. Gallen, School of Finance.
    52. Susan Athey & Guido Imbens, 2016. "The Econometrics of Randomized Experiments," Papers 1607.00698, arXiv.org.
    53. Max-Sebastian Dov`i, 2021. "Inference on the New Keynesian Phillips Curve with Very Many Instrumental Variables," Papers 2101.09543, arXiv.org, revised Mar 2021.
    54. Marianne Bl'ehaut & Xavier D'Haultfoeuille & J'er'emy L'Hour & Alexandre B. Tsybakov, 2020. "An alternative to synthetic control for models with many covariates under sparsity," Papers 2005.12225, arXiv.org, revised Jun 2021.
    55. Su, Liangjun & Ura, Takuya & Zhang, Yichong, 2017. "Non-separable Models with High-dimensional Data," Economics and Statistics Working Papers 15-2017, Singapore Management University, School of Economics.
    56. Pettersson-Lidbom, Per, 2022. "Exit, Voice and Political Change: Evidence from Swedish Mass Migration to the United States. A Comment on Karadja and Prawitz (Journal of Political Economy, 2019)," Journal of Comments and Replications in Economics (JCRE), ZBW - Leibniz Information Centre for Economics, vol. 1(2022-3), pages 1-13.
    57. Madina Kurmangaliyeva & Matteo Sostero, 2022. "Walking while Black :Racial Gaps in Hit-and-Run Cases," Working Papers ECARES 2022-08, ULB -- Universite Libre de Bruxelles.
    58. Natalia Garbiras-Díaz & Mateo Montenegro, 2022. "All Eyes on Them: A Field Experiment on Citizen Oversight and Electoral Integrity," American Economic Review, American Economic Association, vol. 112(8), pages 2631-2668, August.
    59. Alessandro V. M. Oliveira & Thiago Caliari & Rodolfo R. Narcizo, 2024. "An empirical model of fleet modernization: on the relationship between market concentration and innovation adoption in the Brazilian airline industry," Papers 2401.06876, arXiv.org.
    60. Sophie Brana & Dalila Chenaf-Nicet & Delphine Lahet, 2023. "Drivers of cross-border bank claims: The role of foreign-owned banks in emerging countries," Working Papers 2023.06, International Network for Economic Research - INFER.
    61. James M. Carson & Cameron M. Ellis & Robert E. Hoyt & Krzysztof Ostaszewski, 2020. "Sunk Costs and Screening: Two‐Part Tariffs in Life Insurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 87(3), pages 689-718, September.
    62. Doğan, Osman & Taşpınar, Süleyman & Bera, Anil K., 2021. "A Bayesian robust chi-squared test for testing simple hypotheses," Journal of Econometrics, Elsevier, vol. 222(2), pages 933-958.
    63. Eufrásio, Ana Beatriz R. & Eller, Rogéria A.G. & Oliveira, Alessandro V.M., 2021. "Are on-time performance statistics worthless? An empirical study of the flight scheduling strategies of Brazilian airlines," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
    64. Bai Huang & Tae-Hwy Lee & Aman Ullah, 2017. "A combined estimator of regression models with measurement errors," Indian Economic Review, Springer, vol. 52(1), pages 73-91, December.
    65. Daniel Brunstein & Georges Casamatta & Sauveur Giannoni, 2023. "Hétérogénéité de l'impact du développement d'Airbnb sur le marché immobilier en Corse," Post-Print hal-04122192, HAL.
    66. Liu, Yan & Chen, Minjie & Yu, Jianyu & Wang, Xiaobing, 2024. "Being a happy farmer: Technology adoption and subjective well-being," Journal of Economic Behavior & Organization, Elsevier, vol. 221(C), pages 385-405.
    67. Cocker Liu & Adam Nowak & Patrick Smith, 2017. "Some Remarks on Real Estate Pricing," Working Papers 17-20, Department of Economics, West Virginia University.
    68. Guber, Raphael, 2018. "Instrument Validity Tests with Causal Trees: With an Application to the Same-sex Instrument," MEA discussion paper series 201805, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
    69. Kyle Myers & Wei Yang Tham, 2023. "Money, Time, and Grant Design," Papers 2312.06479, arXiv.org.
    70. Oliveira, Alessandro V.M. & Oliveira, Bruno F. & Vassallo, Moisés D., 2023. "Airport service quality perception and flight delays: Examining the influence of psychosituational latent traits of respondents in passenger satisfaction surveys," Research in Transportation Economics, Elsevier, vol. 102(C).

  20. Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Valid Post-Selection and Post-Regularization Inference: An Elementary, General Approach," Papers 1501.03430, arXiv.org, revised Aug 2015.

    Cited by:

    1. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Christian Hansen & Kengo Kato, 2018. "High-Dimensional Econometrics and Regularized GMM," Papers 1806.01888, arXiv.org, revised Jun 2018.
    2. Daniel Garcia & Juha Tolvanen & Alexander K. Wagner, 2022. "Demand Estimation Using Managerial Responses to Automated Price Recommendations," Management Science, INFORMS, vol. 68(11), pages 7918-7939, November.
    3. Christian Hansen & Damian Kozbur & Sanjog Misra, 2016. "Targeted undersmoothing," ECON - Working Papers 282, Department of Economics - University of Zurich, revised Apr 2018.
    4. Brunow, Stephan & Lösch, Stefanie & Okhrin, Ostap, 2022. "Labor market tightness and individual wage growth: evidence from Germany," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 56, pages 1-16.
    5. Croux, Christophe & Jagtiani, Julapa & Korivi, Tarunsai & Vulanovic, Milos, 2020. "Important factors determining Fintech loan default: Evidence from a lendingclub consumer platform," Journal of Economic Behavior & Organization, Elsevier, vol. 173(C), pages 270-296.
    6. Giannone, Domenico & Lenza, Michele & Primiceri, Giorgio, 2017. "Economic Predictions with Big Data: The Illusion Of Sparsity," CEPR Discussion Papers 12256, C.E.P.R. Discussion Papers.
    7. Helmut Wasserbacher & Martin Spindler, 2021. "Machine Learning for Financial Forecasting, Planning and Analysis: Recent Developments and Pitfalls," Papers 2107.04851, arXiv.org.
    8. Victor Chernozhukov & Whitney Newey & Rahul Singh & Vasilis Syrgkanis, 2020. "Adversarial Estimation of Riesz Representers," Papers 2101.00009, arXiv.org, revised Apr 2024.
    9. Kaila, Heidi & Azad, Abul, 2023. "The effects of crime and violence on food insecurity and consumption in Nigeria," Food Policy, Elsevier, vol. 115(C).
    10. Stépahne Auray & Nicolas Lepage-Saucier & Purevdorj Tuvaandor, 2018. "Doubly Robust GMM Inference and Differentiated Products Demand Models," Working Papers 2018-13, Center for Research in Economics and Statistics.
    11. Victor Chernozhukov & Juan Carlos Escanciano & Hidehiko Ichimura & Whitney K. Newey & James M. Robins, 2016. "Locally Robust Semiparametric Estimation," Papers 1608.00033, arXiv.org, revised Aug 2020.
    12. Victor Chernozhukov & Whitney K. Newey & Victor Quintas-Martinez & Vasilis Syrgkanis, 2021. "Automatic Debiased Machine Learning via Riesz Regression," Papers 2104.14737, arXiv.org, revised Mar 2024.
    13. Kueck, Jannis & Luo, Ye & Spindler, Martin & Wang, Zigan, 2023. "Estimation and inference of treatment effects with L2-boosting in high-dimensional settings," Journal of Econometrics, Elsevier, vol. 234(2), pages 714-731.
    14. Guo, Xu & Li, Runze & Liu, Jingyuan & Zeng, Mudong, 2023. "Statistical inference for linear mediation models with high-dimensional mediators and application to studying stock reaction to COVID-19 pandemic," Journal of Econometrics, Elsevier, vol. 235(1), pages 166-179.
    15. Robert Adamek & Stephan Smeekes & Ines Wilms, 2020. "Lasso Inference for High-Dimensional Time Series," Papers 2007.10952, arXiv.org, revised Sep 2022.
    16. Susan Athey, 2018. "The Impact of Machine Learning on Economics," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 507-547, National Bureau of Economic Research, Inc.
    17. Jau-er Chen & Chien-Hsun Huang & Jia-Jyun Tien, 2019. "Debiased/Double Machine Learning for Instrumental Variable Quantile Regressions," Papers 1909.12592, arXiv.org, revised Feb 2021.
    18. Isaac K. Ofori & Christopher Quaidoo & Pamela E. Ofori, 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," Working Papers 21/074, European Xtramile Centre of African Studies (EXCAS).
    19. Jannis Kueck & Ye Luo & Martin Spindler & Zigan Wang, 2017. "Estimation and Inference of Treatment Effects with $L_2$-Boosting in High-Dimensional Settings," Papers 1801.00364, arXiv.org, revised Jul 2021.
    20. Tom Boot & Didier Nibbering, 2017. "Inference in high-dimensional linear regression models," Tinbergen Institute Discussion Papers 17-032/III, Tinbergen Institute, revised 05 Jul 2017.
    21. Yanqin Fan & Fang Han & Wei Li & Xiao-Hua Zhou, 2019. "On rank estimators in increasing dimensions," Papers 1908.05255, arXiv.org.
    22. Yoshimasa Uematsu & Takashi Yamagata, 2020. "Inference in Weak Factor Models," ISER Discussion Paper 1080, Institute of Social and Economic Research, Osaka University.
    23. Isaac K. Ofori & Camara K. Obeng & Simplice A. Asongu, 2022. "What Really Drives Economic Growth in Sub-Saharan Africa? Evidence from The Lasso Regularization and Inferential Techniques," Working Papers 22/061, European Xtramile Centre of African Studies (EXCAS).
    24. Aristide Houndetoungan & Abdoul Haki Maoude, 2024. "Inference for Two-Stage Extremum Estimators," THEMA Working Papers 2024-01, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    25. Victor Chernozhukov & Whitney K Newey & Rahul Singh, 2018. "Automatic Debiased Machine Learning of Causal and Structural Effects," Papers 1809.05224, arXiv.org, revised Oct 2022.
    26. Belloni, Alexandre & Hansen, Christian & Newey, Whitney, 2022. "High-dimensional linear models with many endogenous variables," Journal of Econometrics, Elsevier, vol. 228(1), pages 4-26.
    27. Sandro Heiniger, 2024. "Data-driven model selection within the matrix completion method for causal panel data models," Papers 2402.01069, arXiv.org.
    28. Neng-Chieh Chang, 2020. "The Mode Treatment Effect," Papers 2007.11606, arXiv.org.
    29. Aristide Houndetoungan & Abdoul Haki Maoude, 2024. "Inference for Two-Stage Extremum Estimators," Papers 2402.05030, arXiv.org, revised Nov 2024.
    30. Fan, Yanqin & Han, Fang & Li, Wei & Zhou, Xiao-Hua, 2020. "On rank estimators in increasing dimensions," Journal of Econometrics, Elsevier, vol. 214(2), pages 379-412.
    31. Guo, Xu & Li, Runze & Liu, Jingyuan & Zeng, Mudong, 2024. "Reprint: Statistical inference for linear mediation models with high-dimensional mediators and application to studying stock reaction to COVID-19 pandemic," Journal of Econometrics, Elsevier, vol. 239(2).
    32. Victor Chernozhukov & Whitney Newey & Vira Semenova, 2019. "Welfare Analysis in Dynamic Models," Papers 1908.09173, arXiv.org, revised Nov 2024.
    33. Markus Pelger & Jiacheng Zou, 2022. "Inference for Large Panel Data with Many Covariates," Papers 2301.00292, arXiv.org, revised Mar 2023.
    34. Victor Chernozhukov & Whitney Newey & Rahul Singh, 2018. "De-Biased Machine Learning of Global and Local Parameters Using Regularized Riesz Representers," Papers 1802.08667, arXiv.org, revised Oct 2022.
    35. Helmut Wasserbacher & Martin Spindler, 2022. "Machine learning for financial forecasting, planning and analysis: recent developments and pitfalls," Digital Finance, Springer, vol. 4(1), pages 63-88, March.
    36. Victor Chernozhukov & Christian Hansen & Kaspar Wuthrich, 2020. "Instrumental Variable Quantile Regression," Papers 2009.00436, arXiv.org.
    37. Jelena Bradic & Victor Chernozhukov & Whitney K. Newey & Yinchu Zhu, 2019. "Minimax Semiparametric Learning With Approximate Sparsity," Papers 1912.12213, arXiv.org, revised Aug 2022.
    38. Su, Liangjun & Ura, Takuya & Zhang, Yichong, 2017. "Non-separable Models with High-dimensional Data," Economics and Statistics Working Papers 15-2017, Singapore Management University, School of Economics.
    39. Rahul Singh, 2021. "Kernel Ridge Riesz Representers: Generalization, Mis-specification, and the Counterfactual Effective Dimension," Papers 2102.11076, arXiv.org, revised Jul 2024.
    40. Yves Staudt & Joël Wagner, 2021. "Assessing the Performance of Random Forests for Modeling Claim Severity in Collision Car Insurance," Risks, MDPI, vol. 9(3), pages 1-28, March.
    41. Ali Charkhi & Gerda Claeskens, 2018. "Asymptotic post-selection inference for the Akaike information criterion," Biometrika, Biometrika Trust, vol. 105(3), pages 645-664.
    42. Doğan, Osman & Taşpınar, Süleyman & Bera, Anil K., 2021. "A Bayesian robust chi-squared test for testing simple hypotheses," Journal of Econometrics, Elsevier, vol. 222(2), pages 933-958.
    43. Geonwoo Kim & Suyong Song, 2024. "Double/Debiased CoCoLASSO of Treatment Effects with Mismeasured High-Dimensional Control Variables," Papers 2408.14671, arXiv.org.
    44. Neng-Chieh Chang, 2018. "Semiparametric Difference-in-Differences with Potentially Many Control Variables," Papers 1812.10846, arXiv.org, revised Jan 2019.
    45. Victor Chernozhukov & Whitney K. Newey & James Robins, 2018. "Double/de-biased machine learning using regularized Riesz representers," CeMMAP working papers CWP15/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    46. Qizhao Chen & Vasilis Syrgkanis & Morgane Austern, 2022. "Debiased Machine Learning without Sample-Splitting for Stable Estimators," Papers 2206.01825, arXiv.org, revised Nov 2022.
    47. Barbara Felderer & Jannis Kueck & Martin Spindler, 2021. "Big Data meets Causal Survey Research: Understanding Nonresponse in the Recruitment of a Mixed-mode Online Panel," Papers 2102.08994, arXiv.org.
    48. Stephan Martin, 2022. "Estimation of Conditional Random Coefficient Models using Machine Learning Techniques," Papers 2201.08366, arXiv.org.
    49. Ghysels, Eric & Qian, Hang, 2019. "Estimating MIDAS regressions via OLS with polynomial parameter profiling," Econometrics and Statistics, Elsevier, vol. 9(C), pages 1-16.

  21. Alexandre Belloni & Victor Chernozhukov & Christian Hansen & Damian Kozbur, 2014. "Inference in High Dimensional Panel Models with an Application to Gun Control," Papers 1411.6507, arXiv.org.

    Cited by:

    1. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Christian Hansen & Kengo Kato, 2018. "High-Dimensional Econometrics and Regularized GMM," Papers 1806.01888, arXiv.org, revised Jun 2018.
    2. Breinlich, Holger & Corradi, Valentina & Rocha, Nadia & Ruta, Michele & Santos Silva, JMC & Zylkin, Thomas, 2022. "Machine Learning in International Trade Research - Evaluating the Impact of Trade Agreements," CEPR Discussion Papers 17325, C.E.P.R. Discussion Papers.
    3. Julián Caballero & Christian Upper, 2023. "What happens to EMEs when US yields go up?," BIS Working Papers 1081, Bank for International Settlements.
    4. Meera Mahadevan, 2024. "The Price of Power: Costs of Political Corruption in Indian Electricity," American Economic Review, American Economic Association, vol. 114(10), pages 3314-3344, October.
    5. Kaspar Wuthrich & Ying Zhu, 2019. "Omitted variable bias of Lasso-based inference methods: A finite sample analysis," Papers 1903.08704, arXiv.org, revised Sep 2021.
    6. Sun, Yuying & Hong, Yongmiao & Wang, Shouyang & Zhang, Xinyu, 2023. "Penalized time-varying model averaging," Journal of Econometrics, Elsevier, vol. 235(2), pages 1355-1377.
    7. Christian Hansen & Damian Kozbur & Sanjog Misra, 2016. "Targeted undersmoothing," ECON - Working Papers 282, Department of Economics - University of Zurich, revised Apr 2018.
    8. Julián Caballero, 2020. "Corporate dollar debt and depreciations: all's well that ends well?," BIS Working Papers 879, Bank for International Settlements.
    9. Christian Hansen & Yuan Liao, 2016. "The Factor-Lasso and K-Step Bootstrap Approach for Inference in High-Dimensional Economic Applications," Papers 1611.09420, arXiv.org, revised Dec 2016.
    10. Raja, Akash, 2023. "The impact of changes in bank capital requirements," Bank of England working papers 1004, Bank of England.
    11. Paul Clarke & Annalivia Polselli, 2023. "Double Machine Learning for Static Panel Models with Fixed Effects," Papers 2312.08174, arXiv.org, revised Sep 2024.
    12. Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2019. "lassopack: Model selection and prediction with regularized regression in Stata," Papers 1901.05397, arXiv.org.
    13. Damian Kozbur, 2015. "Testing-Based Forward Model Selection," ECON - Working Papers 283, Department of Economics - University of Zurich, revised Apr 2018.
    14. Marta Serra-Garcia & Uri Gneezy, 2023. "Improving Human Deception Detection Using Algorithmic Feedback," CESifo Working Paper Series 10518, CESifo.
    15. Vogt, M. & Walsh, C. & Linton, O., 2022. "CCE Estimation of High-Dimensional Panel Data Models with Interactive Fixed Effects," Cambridge Working Papers in Economics 2242, Faculty of Economics, University of Cambridge.
    16. Szabó-Morvai Ágnes & Hubert János Kiss, 2020. "Locus of control and Human Capital Investment Decisions: The Role of Effort, Parental Preferences and Financial Constraints," CERS-IE WORKING PAPERS 2055, Institute of Economics, Centre for Economic and Regional Studies.
    17. Borgschulte, Mark & Vogler, Jacob, 2019. "Did the ACA Medicaid Expansion Save Lives?," IZA Discussion Papers 12552, Institute of Labor Economics (IZA).
    18. Qiu, Yun & Chen, Xi & Shi, Wei, 2020. "Impacts of Social and Economic Factors on the Transmission of Coronavirus Disease 2019 (COVID-19) in China," GLO Discussion Paper Series 494 [pre.], Global Labor Organization (GLO).
    19. Jonathan Fuhr & Philipp Berens & Dominik Papies, 2024. "Estimating Causal Effects with Double Machine Learning -- A Method Evaluation," Papers 2403.14385, arXiv.org, revised Apr 2024.
    20. Joseph S Shapiro, 2021. "The Environmental Bias of Trade Policy," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 136(2), pages 831-886.
    21. Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Post-selection and post-regularization inference in linear models with many controls and instruments," CeMMAP working papers CWP02/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    22. Mert Hakan Hekimoğlu & Burak Kazaz, 2020. "Analytics for Wine Futures: Realistic Prices," Production and Operations Management, Production and Operations Management Society, vol. 29(9), pages 2096-2120, September.
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    34. Damian Kozbur, 2013. "Inference in additively separable models with a high-dimensional set of conditioning variables," ECON - Working Papers 284, Department of Economics - University of Zurich, revised Apr 2018.
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    36. Maria Laura Alzua & Natalia Cantet & Ana C Dammert & Damilola Olajide, 2024. "The Well-being Effects of an Old-Age Pension: Experimental Evidence for Ekiti State in Nigeria," Journal of African Economies, Centre for the Study of African Economies, vol. 33(3), pages 240-270.
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    38. Davide Viviano & Jelena Bradic, 2021. "Dynamic covariate balancing: estimating treatment effects over time with potential local projections," Papers 2103.01280, arXiv.org, revised Jan 2024.
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    40. Achim Ahrens & Sean Lyons, 2021. "Do rising rents lead to longer commutes? A gravity model of commuting flows in Ireland," Urban Studies, Urban Studies Journal Limited, vol. 58(2), pages 264-279, February.
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    43. Fluchtmann, Jonas & Glenny, Anita Marie & Harmon, Nikolaj & Maibom, Jonas, 2021. "The Gender Application Gap: Do Men and Women Apply for the Same Jobs?," IZA Discussion Papers 14906, Institute of Labor Economics (IZA).
    44. Aristide Houndetoungan & Abdoul Haki Maoude, 2024. "Inference for Two-Stage Extremum Estimators," Papers 2402.05030, arXiv.org, revised Nov 2024.
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    46. Godzinski, Alexandre & Suarez Castillo, Milena, 2021. "Disentangling the effects of air pollutants with many instruments," Journal of Environmental Economics and Management, Elsevier, vol. 109(C).
    47. Aglasan, Serkan & Goodwin, Barry K. & Rejesus, Roderick, 2020. "Genetically Modified Rootworm-Resistant Corn, Risk, and Weather: Evidence from High Dimensional Methods," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 305181, Agricultural and Applied Economics Association.
    48. Achim Ahrens & Alessandra Stampi-Bombelli & Selina Kurer & Dominik Hangartner, 2023. "Optimal multi-action treatment allocation: A two-phase field experiment to boost immigrant naturalization," Papers 2305.00545, arXiv.org, revised Feb 2024.
    49. Francesca Micocci & Armando Rungi, 2021. "Predicting Exporters with Machine Learning," Papers 2107.02512, arXiv.org, revised Sep 2022.
    50. Michael Danquah & Abdul Malik Iddrisu & Ernest Owusu Boakye & Solomon Owusu, 2021. "Do gender wage differences within households influence women's empowerment and welfare?: Evidence from Ghana," WIDER Working Paper Series wp-2021-40, World Institute for Development Economic Research (UNU-WIDER).
    51. Jonathan Fuhr & Dominik Papies, 2024. "Double Machine Learning meets Panel Data -- Promises, Pitfalls, and Potential Solutions," Papers 2409.01266, arXiv.org.
    52. Achim Ahrens, 2015. "Civil conflicts in Africa: Climate, economic shocks, nighttime lights and spill-over effects," SEEC Discussion Papers 1501, Spatial Economics and Econometrics Centre, Heriot Watt University.
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  22. Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen, 2014. "Program evaluation with high-dimensional data," CeMMAP working papers 33/14, Institute for Fiscal Studies.

    Cited by:

    1. Alexandre Belloni & Victor Chernozhukov & Kengo Kato, 2019. "Valid Post-Selection Inference in High-Dimensional Approximately Sparse Quantile Regression Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 114(526), pages 749-758, April.
    2. Christian Hansen & Damian Kozbur & Sanjog Misra, 2016. "Targeted undersmoothing," ECON - Working Papers 282, Department of Economics - University of Zurich, revised Apr 2018.
    3. Christian Hansen & Yuan Liao, 2016. "The Factor-Lasso and K-Step Bootstrap Approach for Inference in High-Dimensional Economic Applications," Papers 1611.09420, arXiv.org, revised Dec 2016.
    4. Alexandre Belloni & Victor Chernozhukov & Christian Hansen & Damian Kozbur, 2014. "Inference in High Dimensional Panel Models with an Application to Gun Control," Papers 1411.6507, arXiv.org.
    5. Damian Kozbur, 2015. "Testing-Based Forward Model Selection," ECON - Working Papers 283, Department of Economics - University of Zurich, revised Apr 2018.
    6. Susan Athey & Julie Tibshirani & Stefan Wager, 2016. "Generalized Random Forests," Papers 1610.01271, arXiv.org, revised Apr 2018.
    7. Xu, Ning & Hong, Jian & Fisher, Timothy, 2016. "Finite-sample and asymptotic analysis of generalization ability with an application to penalized regression," MPRA Paper 73622, University Library of Munich, Germany.
    8. Max H. Farrell, 2013. "Robust Inference on Average Treatment Effects with Possibly More Covariates than Observations," Papers 1309.4686, arXiv.org, revised Feb 2018.
    9. Kasy Maximilian, 2019. "Uniformity and the Delta Method," Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-19, January.
    10. Shao, Shuai & Xu, Le & Yang, Lili & Yu, Dianfan, 2024. "How do energy-saving policies improve environmental quality: Evidence from China’s Top 10,000 energy-consuming enterprises program," World Development, Elsevier, vol. 175(C).
    11. Guo, Zijian & Kang, Hyunseung & Cai, T. Tony & Small, Dylan S., 2018. "Testing endogeneity with high dimensional covariates," Journal of Econometrics, Elsevier, vol. 207(1), pages 175-187.
    12. Denis Chetverikov & . ., 2016. "On cross-validated Lasso," CeMMAP working papers CWP47/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    13. Guido W. Imbens, 2020. "Potential Outcome and Directed Acyclic Graph Approaches to Causality: Relevance for Empirical Practice in Economics," Journal of Economic Literature, American Economic Association, vol. 58(4), pages 1129-1179, December.
    14. Victor Chernozhukov & Vira Semenova, 2018. "Simultaneous inference for Best Linear Predictor of the Conditional Average Treatment Effect and other structural functions," CeMMAP working papers CWP40/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    15. Kaspar W thrich, 2015. "Semiparametric estimation of quantile treatment effects with endogeneity," Diskussionsschriften dp1509, Universitaet Bern, Departement Volkswirtschaft.
    16. Susan Athey & Guido Imbens, 2016. "The State of Applied Econometrics - Causality and Policy Evaluation," Papers 1607.00699, arXiv.org.
    17. Alexandre Belloni & Victor Chernozhukov & Lie Wang, 2013. "Pivotal estimation via square-root lasso in nonparametric regression," CeMMAP working papers 62/13, Institute for Fiscal Studies.
    18. Matias D. Cattaneo & Michael Jansson, 2014. "Bootstrapping Kernel-Based Semiparametric Estimators," CREATES Research Papers 2014-25, Department of Economics and Business Economics, Aarhus University.
    19. Michael Danquah & Abdul Malik Iddrisu & Ernest Owusu Boakye & Solomon Owusu, 2021. "Do gender wage differences within households influence women's empowerment and welfare?: Evidence from Ghana," WIDER Working Paper Series wp-2021-40, World Institute for Development Economic Research (UNU-WIDER).
    20. Huber, Martin & Wüthrich, Kaspar, 2017. "Evaluating local average and quantile treatment effects under endogeneity based on instruments: a review," FSES Working Papers 479, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    21. Denis Chetverikov & . ., 2016. "On cross-validated Lasso," CeMMAP working papers 47/16, Institute for Fiscal Studies.
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    23. Thai T. Pham & Yuanyuan Shen, 2017. "A Deep Causal Inference Approach to Measuring the Effects of Forming Group Loans in Online Non-profit Microfinance Platform," Papers 1706.02795, arXiv.org.

  23. Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2013. "High dimensional methods and inference on structural and treatment effects," CeMMAP working papers 59/13, Institute for Fiscal Studies.

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    1. Andrii Babii & Xi Chen & Eric Ghysels & Rohit Kumar, 2020. "Binary Choice with Asymmetric Loss in a Data-Rich Environment: Theory and an Application to Racial Justice," Papers 2010.08463, arXiv.org, revised Nov 2021.
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    3. Emily Cuddy & Janet Currie, 2020. "Rules vs. Discretion: Treatment of Mental Illness in U.S. Adolescents," Working Papers 2020-10, Princeton University. Economics Department..
    4. TELLO, Mario D., 2024. "Inversión Pública En Infraestructura Y Crecimiento Regional En Perú, 2005-2020: Un Análisis Basado En Técnicas De Aprendizaje Automático Causal," Regional and Sectoral Economic Studies, Euro-American Association of Economic Development, vol. 24(2), pages 195-222.
    5. Mounu Prem & Juan F. Vargas & Olga Namen, 2023. "The Human Capital Peace Dividend," Journal of Human Resources, University of Wisconsin Press, vol. 58(3), pages 962-1002.
    6. Anil Kumar, 2014. "Do restrictions on home equity extraction contribute to lower mortgage defaults? evidence from a policy discontinuity at the Texas border," Working Papers 1410, Federal Reserve Bank of Dallas.
    7. Ingrid Gould Ellen & Keren Mertens Horn & Davin Reed, 2017. "Has Falling Crime Invited Gentrification?," Working Papers 17-27, Center for Economic Studies, U.S. Census Bureau.
    8. Jonathan Hersh & Matthew Harding, 2018. "Big Data in economics," IZA World of Labor, Institute of Labor Economics (IZA), pages 451-451, September.
    9. Jean-Sauveur Ay & Julie Le Gallo, 2021. "The signaling value of nested wine names," Post-Print hal-03268014, HAL.
    10. Panagopoulos, Orestis P. & Pappu, Vijay & Xanthopoulos, Petros & Pardalos, Panos M., 2016. "Constrained subspace classifier for high dimensional datasets," Omega, Elsevier, vol. 59(PA), pages 40-46.
    11. Elena Esposito, 2018. "Side Effects of Immunity: The Rise of African Slavery in the US South," Cahiers de Recherches Economiques du Département d'économie 18.07, Université de Lausanne, Faculté des HEC, Département d’économie.
    12. Li, Yuexin & Ma, X. & Renneboog, Luc, 2021. "In Art We Trust," Other publications TiSEM b9bb6522-9f8d-4c51-b039-3, Tilburg University, School of Economics and Management.
    13. Davide Viviano & Jelena Bradic, 2019. "Synthetic learner: model-free inference on treatments over time," Papers 1904.01490, arXiv.org, revised Aug 2022.
    14. Prem, Mounu & Vargas, Juan F. & Mejía, Daniel, 2020. "The Rise and Persistence of Illegal Crops: Evidence from a Naive Policy Announcement," SocArXiv 6gmpd, Center for Open Science.
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    22. Martin, Stephen & Claxton, Karl & Lomas, James & Longo, Francesco, 2023. "The impact of different types of NHS expenditure on health: Marginal cost per QALY estimates for England for 2016/17," Health Policy, Elsevier, vol. 132(C).
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    25. Sudarno Sumarto & Benjamin A Olken & Abhijit Banerjee & Rema Hanna, . "(Ketiadaan) Efek Distorsi dari Proxy-Means Test: Hasil dari Eksperimen Berskala Nasional di Indonesia," Journal Article, Publications Department.
    26. Damian Kozbur, 2015. "Testing-Based Forward Model Selection," ECON - Working Papers 283, Department of Economics - University of Zurich, revised Apr 2018.
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    28. Bernal, Carolina & Prem, Mounu & Vargas, Juan F. & Ortiz, Mónica, 2024. "Peaceful entry: Entrepreneurship dynamics during Colombia’s peace agreement," Journal of Development Economics, Elsevier, vol. 166(C).
    29. Nelson, Kelly & Brown, Zachary S. & Parton, Lee, 2019. "Biofuels Policy and Innovation Impacts: Evidence from Biofuels and Agricultural Patent Indicators," 2019 Annual Meeting, July 21-23, Atlanta, Georgia 291243, Agricultural and Applied Economics Association.
    30. Yukun Ma, 2023. "Identification-robust inference for the LATE with high-dimensional covariates," Papers 2302.09756, arXiv.org, revised Nov 2023.
    31. Yanqing Yang & Xingcheng Xu & Jinfeng Ge & Yan Xu, 2024. "Machine Learning for Economic Forecasting: An Application to China's GDP Growth," Papers 2407.03595, arXiv.org.
    32. Khishigsuren Davagdorj & Van Huy Pham & Nipon Theera-Umpon & Keun Ho Ryu, 2020. "XGBoost-Based Framework for Smoking-Induced Noncommunicable Disease Prediction," IJERPH, MDPI, vol. 17(18), pages 1-22, September.
    33. Alessandro V. M. Oliveira & Bruno F. Oliveira & Moises D. Vassallo, 2024. "Airport service quality perception and flight delays: examining the influence of psychosituational latent traits of respondents in passenger satisfaction surveys," Papers 2401.02139, arXiv.org.
    34. Teck-Hua Ho & Noah Lim & Sadat Reza & Xiaoyu Xia, 2017. "OM Forum—Causal Inference Models in Operations Management," Manufacturing & Service Operations Management, INFORMS, vol. 19(4), pages 509-525, October.
    35. Sabrin A. Beg & Adrienne M. Lucas & Waqas Halim & Umar Saif, 2019. "Engaging Teachers with Technology Increased Achievement, Bypassing Teachers Did Not," NBER Working Papers 25704, National Bureau of Economic Research, Inc.
    36. Eli Ben-Michael & Avi Feller & Jesse Rothstein, 2018. "The Augmented Synthetic Control Method," Papers 1811.04170, arXiv.org, revised Jul 2020.
    37. Mullally, Conner & Chakravarty, Shourish, 2018. "Are Matching Funds for Smallholder Irrigation Money Well Spent?," SocArXiv x5vmz, Center for Open Science.
    38. Benjamin A Olken & Abhijit Banerjee & Rema Hanna & Sudarno Sumarto, . "The (Lack of) Distortionary Effects of Proxy-Means Tests: Results from a Nationwide Experiment in Indonesia," Journal Article, Publications Department.
    39. Michael C. Knaus, 2018. "A Double Machine Learning Approach to Estimate the Effects of Musical Practice on Student's Skills," Papers 1805.10300, arXiv.org, revised Jan 2019.
    40. Szabó-Morvai Ágnes & Hubert János Kiss, 2020. "Locus of control and Human Capital Investment Decisions: The Role of Effort, Parental Preferences and Financial Constraints," CERS-IE WORKING PAPERS 2055, Institute of Economics, Centre for Economic and Regional Studies.
    41. Chaohua Dong & Jiti Gao & Oliver Linton, 2018. "High dimensional semiparametric moment restriction models," CeMMAP working papers CWP69/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    42. Croux, Christophe & Jagtiani, Julapa & Korivi, Tarunsai & Vulanovic, Milos, 2020. "Important factors determining Fintech loan default: Evidence from a lendingclub consumer platform," Journal of Economic Behavior & Organization, Elsevier, vol. 173(C), pages 270-296.
    43. Shakya, Shishir & Plemmons, Alicia, 2021. "The Impact of Economic Freedom on Startups," Journal of Regional Analysis and Policy, Mid-Continent Regional Science Association, vol. 51(1), January.
    44. Daisuke Ikeda & Mayumi Ojima & Koji Takahashi, 2019. "Financial Interconnectedness, Amplification, and Cross-Border Activity," Bank of Japan Working Paper Series 19-E-11, Bank of Japan.
    45. Clement De Chaisemartin & Nicolás Navarrete, 2023. "The Direct and Spillover Effects of a Nationwide Socio-Emotional Learning Program for Disruptive Students," Post-Print hal-03796424, HAL.
    46. Everding, Jakob & Marcus, Jan, 2019. "The effect of unemployment on the smoking behavior of couples," hche Research Papers 17, University of Hamburg, Hamburg Center for Health Economics (hche).
    47. Michael C Knaus & Michael Lechner & Anthony Strittmatter, 2021. "Machine learning estimation of heterogeneous causal effects: Empirical Monte Carlo evidence," The Econometrics Journal, Royal Economic Society, vol. 24(1), pages 134-161.
    48. Jonathan Fuhr & Philipp Berens & Dominik Papies, 2024. "Estimating Causal Effects with Double Machine Learning -- A Method Evaluation," Papers 2403.14385, arXiv.org, revised Apr 2024.
    49. Helmut Wasserbacher & Martin Spindler, 2021. "Machine Learning for Financial Forecasting, Planning and Analysis: Recent Developments and Pitfalls," Papers 2107.04851, arXiv.org.
    50. Giuseppe De Luca & Jan R. Magnus & Franco Peracchi, 2020. "Sampling properties of the Bayesian posterior mean with anapplication to WALS estimation," EIEF Working Papers Series 2003, Einaudi Institute for Economics and Finance (EIEF), revised Mar 2020.
    51. Emanuele Ciani & Marco Gallo & Zeno Rotondi, 2020. "Public credit guarantee and financial additionalities across SME risk classes," Temi di discussione (Economic working papers) 1265, Bank of Italy, Economic Research and International Relations Area.
    52. Gallego, J & Prem, M & Vargas, J. F., 2022. "Predicting Politicians Misconduct: Evidence From Colombia," Documentos de Trabajo 20504, Universidad del Rosario.
    53. Yijun YU & Hisaki KONO, 2024. "Fertility Policy and Gender Discrimination in the Workplace:Evidence from the Two-Child Policy Reform in China," Discussion papers e-24-001, Graduate School of Economics , Kyoto University.
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    200. Tatiana de Macedo Nogueira Lima, 2022. "Documento de Trabalho 03/2022 - Aprendizado de máquina e antitruste," Documentos de Trabalho 2022030, Conselho Administrativo de Defesa Econômica (Cade), Departamento de Estudos Econômicos.
    201. Joann Jasiak & Peter MacKenzie & Purevdorj Tuvaandorj, 2023. "Digital Divide: Empirical Study of CIUS 2020," Papers 2301.07855, arXiv.org, revised Oct 2024.
    202. Giuseppe Albanese & Guido de Blasio & Andrea Locatelli, 2019. "Place-based Policy and Local TFP," Temi di discussione (Economic working papers) 1253, Bank of Italy, Economic Research and International Relations Area.
    203. Costa, Francisco J M & Szerman, Dimitri & Assunção, Juliano, 2018. "Local Economic Impacts of Hydroelectric Power Plants: Evidence from Brazil," SocArXiv kzhs6, Center for Open Science.
    204. Bonaccolto-Töpfer, Marina & Briel, Stephanie, 2022. "The gender pay gap revisited: Does machine learning offer new insights?," Labour Economics, Elsevier, vol. 78(C).
    205. Igor Asanov & Christoph Buehren & Panagiota Zacharodimou, 2020. "The power of experiments: How big is your n?," MAGKS Papers on Economics 202032, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    206. Alena Skolkova, 2023. "Instrumental Variable Estimation with Many Instruments Using Elastic-Net IV," CERGE-EI Working Papers wp759, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    207. Jinyong Kim & Mingook Kim & Yongsik Kim, 2020. "Bank Transparency and the Market’s Perception of Bank Risk," Journal of Financial Services Research, Springer;Western Finance Association, vol. 58(2), pages 115-142, December.
    208. Luis Aguiar Wicht & Joel Waldfogel & Sarah Waldfogel, 2018. "Playlisting Favorites: Is Spotify Gender-Biased?," JRC Working Papers on Digital Economy 2018-07, Joint Research Centre.
    209. Ng Cheuk Fai, 2022. "Robust Inference in High Dimensional Linear Model with Cluster Dependence," Papers 2212.05554, arXiv.org.
    210. d'Adda, Giovanna & Mahmud, Mahreen & Said, Farah & Bonan, Jacopo, 2020. "The Role of Flexibility and Planning in Repayment Discipline: Evidence from a Field Experiment on Pay-as-You-Go Off-Grid Electricity," RFF Working Paper Series 20-14, Resources for the Future.
    211. Geonwoo Kim & Suyong Song, 2024. "Double/Debiased CoCoLASSO of Treatment Effects with Mismeasured High-Dimensional Control Variables," Papers 2408.14671, arXiv.org.
    212. Skoufias,Emmanuel & Vinha,Katja Pauliina, 2020. "Child Stature, Maternal Education, and Early Childhood Development," Policy Research Working Paper Series 9396, The World Bank.
    213. Leander Andres & Marc Fabel & Helmut Rainer, 2021. "How Much Violence Does Football Hooliganism Cause?," CESifo Working Paper Series 9431, CESifo.
    214. Merino Troncoso, Carlos, 2023. "Introduction to Competition Economics," MPRA Paper 115999, University Library of Munich, Germany.
    215. Fonseca Morello, Thiago, 2023. "Hospitalization due to fire-induced pollution in the Brazilian Amazon: A causal inference analysis with an assessment of policy trade-offs," World Development, Elsevier, vol. 161(C).
    216. Gray, Colin, 2019. "Leaving benefits on the table: Evidence from SNAP," Journal of Public Economics, Elsevier, vol. 179(C).
    217. Jermain C. Kaminski & Christian Hopp, 2020. "Predicting outcomes in crowdfunding campaigns with textual, visual, and linguistic signals," Small Business Economics, Springer, vol. 55(3), pages 627-649, October.
    218. Yusuke Narita, 2020. "A Theory of Quasi-Experimental Evaluation of School Quality," Working Papers 2020-085, Human Capital and Economic Opportunity Working Group.
    219. Diego A. Martin, 2024. "Women Seeking Jobs with Limited Information: Evidence from Iraq," CID Working Papers 157a, Center for International Development at Harvard University.
    220. Clarissa Lotti & Giancarlo Spagnolo, 2022. "Indirect Savings from Public Procurement Centralization," CEIS Research Paper 532, Tor Vergata University, CEIS, revised 01 Feb 2022.
    221. Eufrásio, Ana Beatriz R. & Eller, Rogéria A.G. & Oliveira, Alessandro V.M., 2021. "Are on-time performance statistics worthless? An empirical study of the flight scheduling strategies of Brazilian airlines," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
    222. Karolis Matikonis & Matthew Gobey, 2024. "Small Business Property Tax Reductions and Firm Productivity," Small Business Economics, Springer, vol. 62(1), pages 307-324, January.
    223. Faber, Marius, 2020. "Robots and reshoring: Evidence from Mexican labor markets," Journal of International Economics, Elsevier, vol. 127(C).
    224. Susanna Loeb & Michala Iben Riis-Vestergaard & Marianne Simonsen, 2023. "Supporting Language Development through a Texting Program: Initial Results from Denmark," Economics Working Papers 2023-01, Department of Economics and Business Economics, Aarhus University.
    225. Huntington-Klein Nick, 2020. "Instruments with Heterogeneous Effects: Bias, Monotonicity, and Localness," Journal of Causal Inference, De Gruyter, vol. 8(1), pages 182-208, January.
    226. Fabio Pammolli & Paolo Bonaretti & Massimo Riccaboni & Valentina Tortolini, 2019. "Quali Regole per la Spesa Farmaceutica? - Criticità, Impatti, Proposte," Working Papers CERM 01-2019, Competitività, Regole, Mercati (CERM).
    227. Patricia Boyallian & Pablo Ruiz-Verdú, 2018. "Leverage, CEO Risk-Taking Incentives, and Bank Failure during the 2007–10 Financial Crisis [Endogenous matching and the empirical determinants of contract form]," Review of Finance, European Finance Association, vol. 22(5), pages 1763-1805.
    228. Bai, Jushan & Liao, Yuan, 2017. "Inferences in panel data with interactive effects using large covariance matrices," Journal of Econometrics, Elsevier, vol. 200(1), pages 59-78.
    229. Hui-Ching Chuang & Jau-er Chen, 2023. "Exploring Industry-Distress Effects on Loan Recovery: A Double Machine Learning Approach for Quantiles," Econometrics, MDPI, vol. 11(1), pages 1-20, February.
    230. Oliveira, Alessandro V.M. & Oliveira, Bruno F. & Vassallo, Moisés D., 2023. "Airport service quality perception and flight delays: Examining the influence of psychosituational latent traits of respondents in passenger satisfaction surveys," Research in Transportation Economics, Elsevier, vol. 102(C).
    231. Alex Krumer & Michael Lechner, 2018. "Midweek Effect On Soccer Performance: Evidence From The German Bundesliga," Economic Inquiry, Western Economic Association International, vol. 56(1), pages 193-207, January.
    232. Marta Auricchio & Emanuele Ciani & Alberto Dalmazzo & Guido de Blasio, 2017. "The consequences of public employment: evidence from Italian municipalities," Temi di discussione (Economic working papers) 1125, Bank of Italy, Economic Research and International Relations Area.
    233. David C. Phillips, 2017. "Stopping on Nine: Evidence of Heuristic Managerial Decision‐Making in Major League Baseball Pitcher Substitutions," Southern Economic Journal, John Wiley & Sons, vol. 84(2), pages 577-599, October.
    234. Tianxi Cai & T. Tony Cai & Zijian Guo, 2021. "Optimal statistical inference for individualized treatment effects in high‐dimensional models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(4), pages 669-719, September.

  24. Victor Chernozhukov & Christian Hansen, 2013. "Quantile Models with Endogeneity," Papers 1303.7050, arXiv.org.

    Cited by:

    1. Victor Chernozhukov & Ivan Fernandez-Val & Whitney K. Newey & Sami Stouli & Francis Vella, 2017. "Semiparametric estimation of structural functions in nonseparable triangular models," CeMMAP working papers CWP48/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Han, Jidong & Popkowski Leszczyc, Peter T.L. & Zhang, Zelin, 2021. "Empirical Analyses of Nonlinear Effects of Reserve Prices on Ending Prices in Online Auctions," Journal of Interactive Marketing, Elsevier, vol. 54(C), pages 86-102.
    3. Simone Balestra & Uschi Backes-Gellner, 2014. "Heterogeneous effects of pupil-to-teacher ratio policies - A look at class size reduction and teacher aide," Economics of Education Working Paper Series 0102, University of Zurich, Department of Business Administration (IBW), revised Apr 2017.
    4. Blaise Melly und Kaspar W thrich, 2016. "Local quantile treatment effects," Diskussionsschriften dp1605, Universitaet Bern, Departement Volkswirtschaft.
    5. Clarke, Damian & Llorca-Jaña, Manuel & Pailañir, Daniel, 2021. "The Use of Quantile Methods in Economic History," IZA Discussion Papers 14659, Institute of Labor Economics (IZA).
    6. Callaway, Brantly & Li, Tong & Oka, Tatsushi, 2018. "Quantile treatment effects in difference in differences models under dependence restrictions and with only two time periods," Journal of Econometrics, Elsevier, vol. 206(2), pages 395-413.
    7. Chen, Xiaohong & Pouzo, Demian & Powell, James L., 2019. "Penalized sieve GEL for weighted average derivatives of nonparametric quantile IV regressions," Journal of Econometrics, Elsevier, vol. 213(1), pages 30-53.
    8. Shawkat Hammoudeh & Duc Khuong Nguyen & Ricardo M. Sousa, 2014. "Energy prices and CO2 emission allowance prices: A quantile regression approach," Working Papers 2014-185, Department of Research, Ipag Business School.
    9. Dilshad Ahmad & Muhammad Afzal, 2022. "Impact of violent conflicts and environmental hazards on pastoral sustainable development in Punjab, Pakistan," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(9), pages 11260-11281, September.
    10. Christina Christou & Ruthira Naraidoo & Rangan Gupta & Won Joong Kim, 2017. "Monetary Policy Reaction Functions of the TICKs: A Quantile Regression Approach," Working Papers 201738, University of Pretoria, Department of Economics.
    11. Michael Chletsos & Stelios Roupakias, 2020. "Education and wage inequality before and during the fiscal crisis: A quantile regression analysis for Greece 2006–2016," Review of Development Economics, Wiley Blackwell, vol. 24(4), pages 1333-1364, November.
    12. Nahid Farnaz, 2023. "Does Financial Development Relieve or Exacerbate Income Inequality? A Quantile Regression Approach," Economics Discussion Paper Series 2311, Economics, The University of Manchester.
    13. Paul. B. Kenfac Dongmezo & P. N. Mwita & I. R. Kamga Tchwaket, 2018. "Distributive and Quantile Treatment Effects: Imputation Based Estimators Approach," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 7(2), pages 1-3.
    14. Saifullahi Sani Ibrahim & Huseyin Ozdeser & Behiye Cavusoglu, 2020. "Testing the impact of environmental hazards and violent conflicts on sustainable pastoral development: micro-level evidence from Nigeria," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(5), pages 4169-4190, June.
    15. Balestra, Simone & Backes-Gellner, Uschi, 2017. "Heterogeneous returns to education over the wage distribution: Who profits the most?," Labour Economics, Elsevier, vol. 44(C), pages 89-105.
    16. Hiroaki Kaido & Kaspar Wüthrich, 2018. "Decentralization estimators for instrumental variable quantile regression models," CeMMAP working papers CWP72/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    17. Wüthrich, Kaspar, 2020. "A Comparison of Two Quantile Models With Endogeneity," University of California at San Diego, Economics Working Paper Series qt0q43931f, Department of Economics, UC San Diego.
    18. Bola Amoke Awotide & Adebayo Ogunniyi & Kehinde Oluseyi Olagunju & Lateef Olalekan Bello & Amadou Youssouf Coulibaly & Alexander Nimo Wiredu & Bourémo Kone & Aly Ahamadou & Victor Manyong & Tahirou Ab, 2022. "Evaluating the Heterogeneous Impacts of Adoption of Climate-Smart Agricultural Technologies on Rural Households’ Welfare in Mali," Agriculture, MDPI, vol. 12(11), pages 1-16, November.
    19. Kaspar W thrich, 2015. "Semiparametric estimation of quantile treatment effects with endogeneity," Diskussionsschriften dp1509, Universitaet Bern, Departement Volkswirtschaft.
    20. David Powell, 2020. "Quantile Treatment Effects in the Presence of Covariates," The Review of Economics and Statistics, MIT Press, vol. 102(5), pages 994-1005, December.
    21. Saifullahi Sani Ibrahim & Haruna Mohammad Aliero, 2020. "Testing the impact of financial inclusion on income convergence: Empirical evidence from Nigeria," African Development Review, African Development Bank, vol. 32(1), pages 42-54, March.
    22. Fusejima, Koki, 2024. "Identification of multi-valued treatment effects with unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 238(1).
    23. Victor Chernozhukov & Christian Hansen & Kaspar Wuthrich, 2020. "Instrumental Variable Quantile Regression," Papers 2009.00436, arXiv.org.
    24. Pengzhou Wu & Kenji Fukumizu, 2021. "$\beta$-Intact-VAE: Identifying and Estimating Causal Effects under Limited Overlap," Papers 2110.05225, arXiv.org.
    25. Valizadeh, Pourya & Smith, Travis A., 2017. "How Did the American Recovery and Reinvestment Act (ARRA) Impact the Material Well-being of SNAP Participants? A Distributional Approach," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258496, Agricultural and Applied Economics Association.
    26. Wüthrich, Kaspar, 2019. "A closed-form estimator for quantile treatment effects with endogeneity," Journal of Econometrics, Elsevier, vol. 210(2), pages 219-235.
    27. Ghosh, Pallab Kumar, 2014. "The contribution of human capital variables to changes in the wage distribution function," Labour Economics, Elsevier, vol. 28(C), pages 58-69.
    28. Apergis, Nicholas & Christou, Christina, 2015. "The behaviour of the bank lending channel when interest rates approach the zero lower bound: Evidence from quantile regressions," Economic Modelling, Elsevier, vol. 49(C), pages 296-307.
    29. Mark Stater & Jeffrey B Wenger, 2017. "The Immediate Hardship of Unemployment: Evidence from the US Unemployment Insurance System," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 43(1), pages 17-36, January.
    30. Pourya Valizadeh & Travis A Smith, 2020. "How Did The American Recovery and Reinvestment Act Affect the Material Well‐Being of SNAP Participants? A Distributional Approach," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 42(3), pages 455-476, September.
    31. Bai Huang & Tae-Hwy Lee & Aman Ullah, 2017. "A combined estimator of regression models with measurement errors," Indian Economic Review, Springer, vol. 52(1), pages 73-91, December.
    32. Myoung‐jae Lee & Jin‐young Choi, 2022. "Finding mover–stayer quantile difference due to unobservables using quantile selection corrections," Bulletin of Economic Research, Wiley Blackwell, vol. 74(3), pages 704-721, July.
    33. Santiago Pereda Fernández, 2016. "Estimation of counterfactual distributions with a continuous endogenous treatment," Temi di discussione (Economic working papers) 1053, Bank of Italy, Economic Research and International Relations Area.

  25. Alexandre Belloni & Victor Chernozhukov & Ivan Fern'andez-Val & Christian Hansen, 2013. "Program Evaluation and Causal Inference with High-Dimensional Data," Papers 1311.2645, arXiv.org, revised Jan 2018.

    Cited by:

    1. Lechner, Michael, 2019. "Modified Causal Forests for Estimating Heterogeneous Causal Effects," CEPR Discussion Papers 13430, C.E.P.R. Discussion Papers.
    2. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Christian Hansen & Kengo Kato, 2018. "High-Dimensional Econometrics and Regularized GMM," Papers 1806.01888, arXiv.org, revised Jun 2018.
    3. Yamin Ahmad & Adam Check & Ming Chien Lo, 2024. "Unit Roots in Macroeconomic Time Series: A Comparison of Classical, Bayesian and Machine Learning Approaches," Computational Economics, Springer;Society for Computational Economics, vol. 63(6), pages 2139-2173, June.
    4. Mazzocchi, Mario & Capacci, Sara & Biondi, Beatrice, 2022. "Causal inference on the impact of nutrition policies using observational data," Bio-based and Applied Economics Journal, Italian Association of Agricultural and Applied Economics (AIEAA), vol. 11(1), April.
    5. Kyle Colangelo & Ying-Ying Lee, 2019. "Double debiased machine learning nonparametric inference with continuous treatments," CeMMAP working papers CWP72/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Belloni, Alexandre & Chen, Mingli & Chernozhukov, Victor, 2016. "Quantile Graphical Models : Prediction and Conditional Independence with Applications to Financial Risk Management," Economic Research Papers 269321, University of Warwick - Department of Economics.
    7. Pedro H. C. Sant'Anna & Jun B. Zhao, 2018. "Doubly Robust Difference-in-Differences Estimators," Papers 1812.01723, arXiv.org, revised May 2020.
    8. Huber, Martin, 2019. "An introduction to flexible methods for policy evaluation," FSES Working Papers 504, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    9. Hartley, Robert Paul & Lamarche, Carlos, 2017. "Behavioral Responses and Welfare Reform: Evidence from a Randomized Experiment," IZA Discussion Papers 10905, Institute of Labor Economics (IZA).
    10. Davide Viviano & Jelena Bradic, 2019. "Synthetic learner: model-free inference on treatments over time," Papers 1904.01490, arXiv.org, revised Aug 2022.
    11. Vira Semenova, 2023. "Aggregated Intersection Bounds and Aggregated Minimax Values," Papers 2303.00982, arXiv.org, revised Jun 2024.
    12. Pedro H. C. Sant'Anna & Xiaojun Song & Qi Xu, 2022. "Covariate distribution balance via propensity scores," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(6), pages 1093-1120, September.
    13. Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stephane Surprenant, 2020. "How is Machine Learning Useful for Macroeconomic Forecasting?," Working Papers 20-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Aug 2020.
    14. Michael Lechner & Jana Mareckova, 2024. "Comprehensive Causal Machine Learning," Papers 2405.10198, arXiv.org.
    15. Giuseppe de Luca & Jan Magnus & Franco Peracchi, 2017. "Weighted-Average Least Squares Estimation of Generalized Linear Models," Tinbergen Institute Discussion Papers 17-029/III, Tinbergen Institute.
    16. Alejandro Sanchez-Becerra, 2023. "Robust inference for the treatment effect variance in experiments using machine learning," Papers 2306.03363, arXiv.org.
    17. Denis Fougère & Nicolas Jacquemet, 2020. "Policy Evaluation Using Causal Inference Methods," SciencePo Working papers Main hal-03455978, HAL.
    18. Gallego, J & Rivero, G & Martínez, J.D., 2018. "Preventing rather than Punishing: An Early Warning Model of Malfeasance in Public Procurement," Documentos de Trabajo 16724, Universidad del Rosario.
    19. Michael C. Knaus, 2018. "A Double Machine Learning Approach to Estimate the Effects of Musical Practice on Student's Skills," Papers 1805.10300, arXiv.org, revised Jan 2019.
    20. Cattaneo, Matias D & Jansson, Michael & Newey, Whitney K, 2018. "Inference in Linear Regression Models with Many Covariates and Heteroscedasticity," Department of Economics, Working Paper Series qt6rp7p9gs, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    21. Yuehao Bai & Jizhou Liu & Azeem M. Shaikh & Max Tabord-Meehan, 2023. "On the Efficiency of Finely Stratified Experiments," Papers 2307.15181, arXiv.org, revised Aug 2024.
    22. Rodney V. Fonseca & Aluísio Pinheiro, 2020. "Wavelet estimation of the dimensionality of curve time series," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(5), pages 1175-1204, October.
    23. Michael C Knaus & Michael Lechner & Anthony Strittmatter, 2021. "Machine learning estimation of heterogeneous causal effects: Empirical Monte Carlo evidence," The Econometrics Journal, Royal Economic Society, vol. 24(1), pages 134-161.
    24. Entorf, Horst & Hou, Jia, 2018. "Financial education for the disadvantaged? A review," SAFE Working Paper Series 205, Leibniz Institute for Financial Research SAFE.
    25. Jonathan Fuhr & Philipp Berens & Dominik Papies, 2024. "Estimating Causal Effects with Double Machine Learning -- A Method Evaluation," Papers 2403.14385, arXiv.org, revised Apr 2024.
    26. Victor Chernozhukov & Whitney Newey & Rahul Singh & Vasilis Syrgkanis, 2020. "Adversarial Estimation of Riesz Representers," Papers 2101.00009, arXiv.org, revised Apr 2024.
    27. Tymon Sloczynski & Derya Uysal & Jeffrey Wooldridge, 2023. "Abadie's Kappa and Weighting Estimators of the Local Average Treatment Effect," Rationality and Competition Discussion Paper Series 424, CRC TRR 190 Rationality and Competition.
    28. Zemin Zheng & Jie Zhang & Yang Li, 2022. "L 0 -Regularized Learning for High-Dimensional Additive Hazards Regression," INFORMS Journal on Computing, INFORMS, vol. 34(5), pages 2762-2775, September.
    29. Khashayar Khosravi & Greg Lewis & Vasilis Syrgkanis, 2019. "Non-Parametric Inference Adaptive to Intrinsic Dimension," Papers 1901.03719, arXiv.org, revised Jun 2019.
    30. Kyle Colangelo & Ying-Ying Lee, 2019. "Double debiased machine learning nonparametric inference with continuous treatments," CeMMAP working papers CWP54/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    31. Undral Byambadalai & Tatsushi Oka & Shota Yasui, 2024. "Estimating Distributional Treatment Effects in Randomized Experiments: Machine Learning for Variance Reduction," Papers 2407.16037, arXiv.org.
    32. Victor Chernozhukov & Juan Carlos Escanciano & Hidehiko Ichimura & Whitney K. Newey & James M. Robins, 2016. "Locally Robust Semiparametric Estimation," Papers 1608.00033, arXiv.org, revised Aug 2020.
    33. Zhengyuan Zhou & Susan Athey & Stefan Wager, 2018. "Offline Multi-Action Policy Learning: Generalization and Optimization," Papers 1810.04778, arXiv.org, revised Nov 2018.
    34. Pedro H. C. Sant'Anna & Xiaojun Song, 2016. "Specification Tests for the Propensity Score," Papers 1611.06217, arXiv.org, revised Feb 2019.
    35. Guo, Xu & Li, Runze & Liu, Jingyuan & Zeng, Mudong, 2023. "Statistical inference for linear mediation models with high-dimensional mediators and application to studying stock reaction to COVID-19 pandemic," Journal of Econometrics, Elsevier, vol. 235(1), pages 166-179.
    36. Christian B. Hansen & Mark E. Schaffer & Thomas Wiemann & Achim Ahrens, 2022. "ddml: Double/debiased machine learning in Stata," Swiss Stata Conference 2022 02, Stata Users Group.
    37. Cerqua, Augusto & Letta, Marco, 2022. "Local inequalities of the COVID-19 crisis," Regional Science and Urban Economics, Elsevier, vol. 92(C).
    38. Valente, Marica, 2023. "Policy evaluation of waste pricing programs using heterogeneous causal effect estimation," Journal of Environmental Economics and Management, Elsevier, vol. 117(C).
    39. Le-Yu Chen & Yu-Min Yen, 2021. "Estimations of the Local Conditional Tail Average Treatment Effect," Papers 2109.08793, arXiv.org, revised May 2024.
    40. Robert Adamek & Stephan Smeekes & Ines Wilms, 2020. "Lasso Inference for High-Dimensional Time Series," Papers 2007.10952, arXiv.org, revised Sep 2022.
    41. Berden, Carolien & Croes, R. & Kemp, R. & Mikkers, Misja & van der Noll, Rob & Shestalova, V. & Svitak, Jan, 2019. "Hospital Competition in the Netherlands : An Empirical Investigation," Other publications TiSEM 5302ab6a-9099-4b5d-9874-8, Tilburg University, School of Economics and Management.
    42. Ana Fernandes & Martin Huber & Giannina Vaccaro, 2020. "Gender Differences in Wage Expectations," Papers 2003.11496, arXiv.org.
    43. Bryan T. Kelly & Asaf Manela & Alan Moreira, 2019. "Text Selection," NBER Working Papers 26517, National Bureau of Economic Research, Inc.
    44. Karun Adusumilli & Friedrich Geiecke & Claudio Schilter, 2019. "Dynamically Optimal Treatment Allocation," Papers 1904.01047, arXiv.org, revised Nov 2024.
    45. Johann Pfitzinger, 2021. "An Interpretable Neural Network for Parameter Inference," Papers 2106.05536, arXiv.org.
    46. Breunig, Christoph & Mammen, Enno & Simoni, Anna, 2020. "Ill-posed estimation in high-dimensional models with instrumental variables," Journal of Econometrics, Elsevier, vol. 219(1), pages 171-200.
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    51. Victor Chernozhukov & Iv'an Fern'andez-Val & Blaise Melly, 2019. "Fast Algorithms for the Quantile Regression Process," Papers 1909.05782, arXiv.org, revised Apr 2020.
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    56. Cattaneo, Matias D & Jansson, Michael & Ma, Xinwei, 2019. "Two-Step Estimation and Inference with Possibly Many Included Covariates," University of California at San Diego, Economics Working Paper Series qt86c7x315, Department of Economics, UC San Diego.
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    119. Byron Botha & Rulof Burger & Kevin Kotze & Neil Rankin & Daan Steenkamp, 2022. "Big data forecasting of South African inflation," School of Economics Macroeconomic Discussion Paper Series 2022-03, School of Economics, University of Cape Town.
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    Cited by:

    1. Toru Kitagawa & Chris Muris, 2015. "Model averaging in semiparametric estimation of treatment effects," CeMMAP working papers CWP46/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Shukla, Pallavi & Pullabhotla, Hemant K. & Baylis, Kathy, 2022. "Trouble with zero: The limits of subsidizing technology adoption," Journal of Development Economics, Elsevier, vol. 158(C).
    3. Chakravorty, Bhaskar & Arulampalam, Wiji & Bhatiya, Apurav Yash & Imbert, Clement & Rathelot, Roland, 2021. "Can information about jobs improve the effectiveness of vocational training? Experimental evidence from India," CAGE Online Working Paper Series 567, Competitive Advantage in the Global Economy (CAGE).
    4. Alexandre Belloni & Victor Chernozhukov & Christian Hansen & Damian Kozbur, 2014. "Inference in High Dimensional Panel Models with an Application to Gun Control," Papers 1411.6507, arXiv.org.
    5. González, F & Muñoz, P & Prem, M, 2019. "Lost in Transition? The Persistence of Dictatorship Mayors," Documentos de Trabajo 17431, Universidad del Rosario.
    6. Teck-Hua Ho & Noah Lim & Sadat Reza & Xiaoyu Xia, 2017. "OM Forum—Causal Inference Models in Operations Management," Manufacturing & Service Operations Management, INFORMS, vol. 19(4), pages 509-525, October.
    7. Wunsch, Conny & Strittmatter, Anthony, 2021. "The Gender Pay Gap Revisited with Big Data: Do Methodological Choices Matter?," CEPR Discussion Papers 15840, C.E.P.R. Discussion Papers.
    8. Alexandre Belloni & Victor Chernozhukov & Ying Wei, 2016. "Post-Selection Inference for Generalized Linear Models With Many Controls," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 606-619, October.
    9. Kaila, Heidi & Azad, Abul, 2023. "The effects of crime and violence on food insecurity and consumption in Nigeria," Food Policy, Elsevier, vol. 115(C).
    10. Haroon, Maryiam & Said, Farah & Zafar, Mahniya, 2022. "Fostering non-cognitive skills and academic performance: Experimental evidence from women’s-only colleges in Pakistan," Journal of Asian Economics, Elsevier, vol. 81(C).
    11. Lechner, Michael & Strittmatter, Anthony & Knaus, Michael C., 2017. "Heterogeneous Employment Effects of Job Search Programmes: A Machine Learning Approach," CEPR Discussion Papers 12224, C.E.P.R. Discussion Papers.
    12. Miric, Milan & Boudreau, Kevin J. & Jeppesen, Lars Bo, 2019. "Protecting their digital assets: The use of formal & informal appropriability strategies by App developers," Research Policy, Elsevier, vol. 48(8), pages 1-1.
    13. Helmut Wasserbacher & Martin Spindler, 2024. "Credit Ratings: Heterogeneous Effect on Capital Structure," Papers 2406.18936, arXiv.org.
    14. John A. List & Ian Muir & Gregory K. Sun, 2022. "Using Machine Learning for Efficient Flexible Regression Adjustment in Economic Experiments," NBER Working Papers 30756, National Bureau of Economic Research, Inc.
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    17. Byol Kim & Song Liu & Mladen Kolar, 2021. "Two‐sample inference for high‐dimensional Markov networks," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(5), pages 939-962, November.
    18. Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2013. "High dimensional methods and inference on structural and treatment effects," CeMMAP working papers CWP59/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    19. Ian W. McKeague & Min Qian, 2015. "An Adaptive Resampling Test for Detecting the Presence of Significant Predictors," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(512), pages 1422-1433, December.
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    21. Renée, Laëtitia, 2022. "The long-term effects of financial aid and career education: Evidence from a randomized experiment," CLEF Working Paper Series 46, Canadian Labour Economics Forum (CLEF), University of Waterloo.
    22. Alexandre Belloni & Victor Chernozhukov, 2015. "Comment," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(512), pages 1449-1451, December.
    23. David Cheng & Abhishek Chakrabortty & Ashwin N. Ananthakrishnan & Tianxi Cai, 2020. "Estimating average treatment effects with a double‐index propensity score," Biometrics, The International Biometric Society, vol. 76(3), pages 767-777, September.
    24. Pollack, Adam B. & Kaufmann, Robert K., 2022. "Increasing storm risk, structural defense, and house prices in the Florida Keys," Ecological Economics, Elsevier, vol. 194(C).
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    26. Bütikofer, Aline & Ginja, Rita & Landaud, Fanny & Løken, Katrine V., 2020. "School Selectivity, Peers, and Mental Health," Working Papers in Economics 5/20, University of Bergen, Department of Economics.
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    29. McKenzie, David & Sansone, Dario, 2017. "Man vs. Machine in Predicting Successful Entrepreneurs: Evidence from a Business Plan Competition in Nigeria," CEPR Discussion Papers 12523, C.E.P.R. Discussion Papers.
    30. D’Amour, Alexander & Ding, Peng & Feller, Avi & Lei, Lihua & Sekhon, Jasjeet, 2021. "Overlap in observational studies with high-dimensional covariates," Journal of Econometrics, Elsevier, vol. 221(2), pages 644-654.
    31. Ahsan Jansson, Cecilia & Patil, Vikram & Vecci, Joe & Chellattan Veettil , Prakashan & Yashodha, Yashodha, 2023. "Locus of Control and Economic Decision-Making: A Field Experiment in Odisha, India," Working Papers in Economics 833, University of Gothenburg, Department of Economics.
    32. Joseph Antonelli & Matthew Cefalu & Nathan Palmer & Denis Agniel, 2018. "Doubly robust matching estimators for high dimensional confounding adjustment," Biometrics, The International Biometric Society, vol. 74(4), pages 1171-1179, December.
    33. Michael Danquah & Solomon Owusu, 2021. "Digital technology and productivity of informal enterprises: Empirical evidence from Nigeria," WIDER Working Paper Series wp-2021-114, World Institute for Development Economic Research (UNU-WIDER).
    34. Rao, Manaswini & Shenoy, Ashish, 2023. "Got (clean) milk? Organization, incentives, and management in Indian dairy cooperatives," Journal of Economic Behavior & Organization, Elsevier, vol. 212(C), pages 708-722.
    35. Michael J. Weir & Thomas W. Sproul, 2019. "Identifying Drivers of Genetically Modified Seafood Demand: Evidence from a Choice Experiment," Sustainability, MDPI, vol. 11(14), pages 1-21, July.
    36. Yash Raj Shrestha & Vivianna Fang He & Phanish Puranam & Georg von Krogh, 2021. "Algorithm Supported Induction for Building Theory: How Can We Use Prediction Models to Theorize?," Organization Science, INFORMS, vol. 32(3), pages 856-880, May.
    37. Clarke, Damian, 2023. "The Economics of Abortion Policy," IZA Discussion Papers 16395, Institute of Labor Economics (IZA).
    38. Alex Armand & Britta Augsburg & Antonella Bancalari, 2021. "Coordination and the poor maintenance trap: an experiment on public infrastructure in India," IFS Working Papers W21/16, Institute for Fiscal Studies.
    39. Stefano Cabras & J. D. Tena, 2023. "Implicit institutional incentives and individual decisions: Causal inference with deep learning models," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(6), pages 3739-3754, September.
    40. Alexander Kreiss & Christoph Rothe, 2023. "Inference in regression discontinuity designs with high-dimensional covariates," The Econometrics Journal, Royal Economic Society, vol. 26(2), pages 105-123.
    41. Ji, Chengyuan & Jiang, Junyan & Zhang, Yujin, 2024. "Political trust and government performance in the time of COVID-19," World Development, Elsevier, vol. 176(C).
    42. Jin, Wei & van der Ploeg, Frederick & Zhang, Lin, 2024. "How clean capital slows down disinvestment of carbon-intensive capital in the low-carbon transition," Journal of Economic Dynamics and Control, Elsevier, vol. 162(C).
    43. Chakravorty, Bhaskar & Bhatiya, Apurav Yash & Imbert, Clement & Lohnert, Maximilian & Panda, Poonam & Rathelot, Roland, 2022. "Impact of the COVID-19 Crisis on India’s Rural Youth : Evidence from a Panel Survey and an Experiment," The Warwick Economics Research Paper Series (TWERPS) 1419, University of Warwick, Department of Economics.
    44. Travis J. Lybbert & Ashish Shenoy & Tomoé Bourdier & Caitlin Kieran, 2024. "Striving to revive pulses in India with extension, input subsidies, and output price supports†," American Journal of Agricultural Economics, John Wiley & Sons, vol. 106(3), pages 1167-1192, May.
    45. Byron Botha & Rulof Burger & Kevin Kotze & Neil Rankin & Daan Steenkamp, 2022. "Big data forecasting of South African inflation," School of Economics Macroeconomic Discussion Paper Series 2022-03, School of Economics, University of Cape Town.
    46. Simone Maxand & Hend Sallam, 2024. "Local Fiscal Effects of Immigration in Germany," CESifo Working Paper Series 11162, CESifo.
    47. Gabriel Okasa, 2022. "Meta-Learners for Estimation of Causal Effects: Finite Sample Cross-Fit Performance," Papers 2201.12692, arXiv.org.
    48. Sylvain Barde & Rowan Cherodian & Guy Tchuente, 2023. "Moran's I Lasso for models with spatially correlated data," Papers 2310.02773, arXiv.org.

  27. Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2011. "Inference on Treatment Effects After Selection Amongst High-Dimensional Controls," Papers 1201.0224, arXiv.org, revised May 2012.

    Cited by:

    1. Toru Kitagawa & Chris Muris, 2015. "Model averaging in semiparametric estimation of treatment effects," CeMMAP working papers CWP46/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Imbens, Guido W., 2014. "Matching Methods in Practice: Three Examples," IZA Discussion Papers 8049, Institute of Labor Economics (IZA).
    3. Shukla, Pallavi & Pullabhotla, Hemant K. & Baylis, Kathy, 2022. "Trouble with zero: The limits of subsidizing technology adoption," Journal of Development Economics, Elsevier, vol. 158(C).
    4. Chakravorty, Bhaskar & Arulampalam, Wiji & Bhatiya, Apurav Yash & Imbert, Clement & Rathelot, Roland, 2021. "Can information about jobs improve the effectiveness of vocational training? Experimental evidence from India," CAGE Online Working Paper Series 567, Competitive Advantage in the Global Economy (CAGE).
    5. Mehmet Caner & Anders Bredahl Kock, 2014. "Asymptotically Honest Confidence Regions for High Dimensional Parameters by the Desparsified Conservative Lasso," CREATES Research Papers 2014-36, Department of Economics and Business Economics, Aarhus University.
    6. Alexandre Belloni & Victor Chernozhukov & Christian Hansen & Damian Kozbur, 2014. "Inference in High Dimensional Panel Models with an Application to Gun Control," Papers 1411.6507, arXiv.org.
    7. González, F & Muñoz, P & Prem, M, 2019. "Lost in Transition? The Persistence of Dictatorship Mayors," Documentos de Trabajo 17431, Universidad del Rosario.
    8. Alexander Krei{ss} & Christoph Rothe, 2021. "Inference in Regression Discontinuity Designs with High-Dimensional Covariates," Papers 2110.13725, arXiv.org, revised May 2022.
    9. Teck-Hua Ho & Noah Lim & Sadat Reza & Xiaoyu Xia, 2017. "OM Forum—Causal Inference Models in Operations Management," Manufacturing & Service Operations Management, INFORMS, vol. 19(4), pages 509-525, October.
    10. Wunsch, Conny & Strittmatter, Anthony, 2021. "The Gender Pay Gap Revisited with Big Data: Do Methodological Choices Matter?," CEPR Discussion Papers 15840, C.E.P.R. Discussion Papers.
    11. Alexandre Belloni & Victor Chernozhukov & Ying Wei, 2016. "Post-Selection Inference for Generalized Linear Models With Many Controls," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 606-619, October.
    12. Kaila, Heidi & Azad, Abul, 2023. "The effects of crime and violence on food insecurity and consumption in Nigeria," Food Policy, Elsevier, vol. 115(C).
    13. Haroon, Maryiam & Said, Farah & Zafar, Mahniya, 2022. "Fostering non-cognitive skills and academic performance: Experimental evidence from women’s-only colleges in Pakistan," Journal of Asian Economics, Elsevier, vol. 81(C).
    14. Hensel, Lukas & Tekleselassie, Tsegay & Witte, Marc J., 2021. "Formalized Employee Search and Labor Demand," IZA Discussion Papers 14839, Institute of Labor Economics (IZA).
    15. Lechner, Michael & Strittmatter, Anthony & Knaus, Michael C., 2017. "Heterogeneous Employment Effects of Job Search Programmes: A Machine Learning Approach," CEPR Discussion Papers 12224, C.E.P.R. Discussion Papers.
    16. Miric, Milan & Boudreau, Kevin J. & Jeppesen, Lars Bo, 2019. "Protecting their digital assets: The use of formal & informal appropriability strategies by App developers," Research Policy, Elsevier, vol. 48(8), pages 1-1.
    17. Liran Einav & Jonathan D. Levin, 2013. "The Data Revolution and Economic Analysis," NBER Working Papers 19035, National Bureau of Economic Research, Inc.
    18. Helmut Wasserbacher & Martin Spindler, 2024. "Credit Ratings: Heterogeneous Effect on Capital Structure," Papers 2406.18936, arXiv.org.
    19. John A. List & Ian Muir & Gregory K. Sun, 2022. "Using Machine Learning for Efficient Flexible Regression Adjustment in Economic Experiments," NBER Working Papers 30756, National Bureau of Economic Research, Inc.
    20. Kovacs, Roxanne J. & Lagarde, Mylene & Cairns, John, 2022. "Can patients improve the quality of care they receive? Experimental evidence from Senegal," World Development, Elsevier, vol. 150(C).
    21. Matthias Breuer & Harm H. Schütt, 2023. "Accounting for uncertainty: an application of Bayesian methods to accruals models," Review of Accounting Studies, Springer, vol. 28(2), pages 726-768, June.
    22. Byol Kim & Song Liu & Mladen Kolar, 2021. "Two‐sample inference for high‐dimensional Markov networks," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(5), pages 939-962, November.
    23. Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2013. "High dimensional methods and inference on structural and treatment effects," CeMMAP working papers CWP59/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    24. Ian W. McKeague & Min Qian, 2015. "An Adaptive Resampling Test for Detecting the Presence of Significant Predictors," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(512), pages 1422-1433, December.
    25. Martin C. Arnold & Thilo Reinschlussel, 2024. "Bootstrap Adaptive Lasso Solution Path Unit Root Tests," Papers 2409.07859, arXiv.org.
    26. Renée, Laëtitia, 2022. "The long-term effects of financial aid and career education: Evidence from a randomized experiment," CLEF Working Paper Series 46, Canadian Labour Economics Forum (CLEF), University of Waterloo.
    27. Alexandre Belloni & Victor Chernozhukov, 2015. "Comment," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(512), pages 1449-1451, December.
    28. David Cheng & Abhishek Chakrabortty & Ashwin N. Ananthakrishnan & Tianxi Cai, 2020. "Estimating average treatment effects with a double‐index propensity score," Biometrics, The International Biometric Society, vol. 76(3), pages 767-777, September.
    29. Pollack, Adam B. & Kaufmann, Robert K., 2022. "Increasing storm risk, structural defense, and house prices in the Florida Keys," Ecological Economics, Elsevier, vol. 194(C).
    30. Armand, Alex & Augsburg, Britta & Bancalari, Antonella & Kameshwara, Kalyan Kumar, 2024. "Religious proximity and misinformation: Experimental evidence from a mobile phone-based campaign in India," Journal of Health Economics, Elsevier, vol. 96(C).
    31. Bütikofer, Aline & Ginja, Rita & Landaud, Fanny & Løken, Katrine V., 2020. "School Selectivity, Peers, and Mental Health," Working Papers in Economics 5/20, University of Bergen, Department of Economics.
    32. Joshua Angrist & Miikka Rokkanen, 2012. "Wanna Get Away? RD Identification Away from the Cutoff," NBER Working Papers 18662, National Bureau of Economic Research, Inc.
    33. Chen, Ya & Tsionas, Mike G. & Zelenyuk, Valentin, 2021. "LASSO+DEA for small and big wide data," Omega, Elsevier, vol. 102(C).
    34. Ben Gillen & Erik Snowberg & Leeat Yariv, 2015. "Experimenting with Measurement Error: Techniques with Applications to the Caltech Cohort Study," NBER Working Papers 21517, National Bureau of Economic Research, Inc.
    35. Toru Kitagawa & Chris Muris, 2013. "Covariate selection and model averaging in semiparametric estimation of treatment effects," CeMMAP working papers CWP61/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    36. He, Yi & Jaidee, Sombut & Gao, Jiti, 2023. "Most powerful test against a sequence of high dimensional local alternatives," Journal of Econometrics, Elsevier, vol. 234(1), pages 151-177.
    37. McKenzie, David & Sansone, Dario, 2017. "Man vs. Machine in Predicting Successful Entrepreneurs: Evidence from a Business Plan Competition in Nigeria," CEPR Discussion Papers 12523, C.E.P.R. Discussion Papers.
    38. D’Amour, Alexander & Ding, Peng & Feller, Avi & Lei, Lihua & Sekhon, Jasjeet, 2021. "Overlap in observational studies with high-dimensional covariates," Journal of Econometrics, Elsevier, vol. 221(2), pages 644-654.
    39. Rishabh Tyagi & Peter Eibich & Vegard Skirbekk, 2024. "Gender norms and partnership dissolution following involuntary job loss in Germany," MPIDR Working Papers WP-2024-027, Max Planck Institute for Demographic Research, Rostock, Germany.
    40. Ahsan Jansson, Cecilia & Patil, Vikram & Vecci, Joe & Chellattan Veettil , Prakashan & Yashodha, Yashodha, 2023. "Locus of Control and Economic Decision-Making: A Field Experiment in Odisha, India," Working Papers in Economics 833, University of Gothenburg, Department of Economics.
    41. Joseph Antonelli & Matthew Cefalu & Nathan Palmer & Denis Agniel, 2018. "Doubly robust matching estimators for high dimensional confounding adjustment," Biometrics, The International Biometric Society, vol. 74(4), pages 1171-1179, December.
    42. Michael Danquah & Solomon Owusu, 2021. "Digital technology and productivity of informal enterprises: Empirical evidence from Nigeria," WIDER Working Paper Series wp-2021-114, World Institute for Development Economic Research (UNU-WIDER).
    43. Ya Chen & Mike Tsionas & Valentin Zelenyuk, 2020. "LASSO DEA for small and big data," CEPA Working Papers Series WP022020, School of Economics, University of Queensland, Australia.
    44. Rao, Manaswini & Shenoy, Ashish, 2023. "Got (clean) milk? Organization, incentives, and management in Indian dairy cooperatives," Journal of Economic Behavior & Organization, Elsevier, vol. 212(C), pages 708-722.
    45. Michael J. Weir & Thomas W. Sproul, 2019. "Identifying Drivers of Genetically Modified Seafood Demand: Evidence from a Choice Experiment," Sustainability, MDPI, vol. 11(14), pages 1-21, July.
    46. Yash Raj Shrestha & Vivianna Fang He & Phanish Puranam & Georg von Krogh, 2021. "Algorithm Supported Induction for Building Theory: How Can We Use Prediction Models to Theorize?," Organization Science, INFORMS, vol. 32(3), pages 856-880, May.
    47. Clarke, Damian, 2023. "The Economics of Abortion Policy," IZA Discussion Papers 16395, Institute of Labor Economics (IZA).
    48. Alex Armand & Britta Augsburg & Antonella Bancalari, 2021. "Coordination and the poor maintenance trap: an experiment on public infrastructure in India," IFS Working Papers W21/16, Institute for Fiscal Studies.
    49. Stefano Cabras & J. D. Tena, 2023. "Implicit institutional incentives and individual decisions: Causal inference with deep learning models," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(6), pages 3739-3754, September.
    50. Alexander Kreiss & Christoph Rothe, 2023. "Inference in regression discontinuity designs with high-dimensional covariates," The Econometrics Journal, Royal Economic Society, vol. 26(2), pages 105-123.
    51. Ji, Chengyuan & Jiang, Junyan & Zhang, Yujin, 2024. "Political trust and government performance in the time of COVID-19," World Development, Elsevier, vol. 176(C).
    52. Zhu, Ying, 2013. "Sparse Linear Models and Two-Stage Estimation in High-Dimensional Settings with Possibly Many Endogenous Regressors," MPRA Paper 49846, University Library of Munich, Germany.
    53. Jin, Wei & van der Ploeg, Frederick & Zhang, Lin, 2024. "How clean capital slows down disinvestment of carbon-intensive capital in the low-carbon transition," Journal of Economic Dynamics and Control, Elsevier, vol. 162(C).
    54. Loh, Wen Wei & Ren, Dongning, 2021. "Data-driven Covariate Selection for Confounding Adjustment by Focusing on the Stability of the Effect Estimator," OSF Preprints yve6u, Center for Open Science.
    55. Chakravorty, Bhaskar & Bhatiya, Apurav Yash & Imbert, Clement & Lohnert, Maximilian & Panda, Poonam & Rathelot, Roland, 2022. "Impact of the COVID-19 Crisis on India’s Rural Youth : Evidence from a Panel Survey and an Experiment," The Warwick Economics Research Paper Series (TWERPS) 1419, University of Warwick, Department of Economics.
    56. Travis J. Lybbert & Ashish Shenoy & Tomoé Bourdier & Caitlin Kieran, 2024. "Striving to revive pulses in India with extension, input subsidies, and output price supports†," American Journal of Agricultural Economics, John Wiley & Sons, vol. 106(3), pages 1167-1192, May.
    57. Byron Botha & Rulof Burger & Kevin Kotze & Neil Rankin & Daan Steenkamp, 2022. "Big data forecasting of South African inflation," School of Economics Macroeconomic Discussion Paper Series 2022-03, School of Economics, University of Cape Town.
    58. Linton, O. & Seo, M. & Whang, Y-J., 2020. "Testing Stochastic Dominance with Many Conditioning Variables," Cambridge Working Papers in Economics 2004, Faculty of Economics, University of Cambridge.
    59. Simone Maxand & Hend Sallam, 2024. "Local Fiscal Effects of Immigration in Germany," CESifo Working Paper Series 11162, CESifo.
    60. Gabriel Okasa, 2022. "Meta-Learners for Estimation of Causal Effects: Finite Sample Cross-Fit Performance," Papers 2201.12692, arXiv.org.
    61. Sylvain Barde & Rowan Cherodian & Guy Tchuente, 2023. "Moran's I Lasso for models with spatially correlated data," Papers 2310.02773, arXiv.org.

  28. Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2011. "Inference for High-Dimensional Sparse Econometric Models," Papers 1201.0220, arXiv.org.

    Cited by:

    1. Sophie-Charlotte Klose & Johannes Lederer, 2020. "A Pipeline for Variable Selection and False Discovery Rate Control With an Application in Labor Economics," Papers 2006.12296, arXiv.org, revised Jun 2020.
    2. Liqian Cai & Arnab Bhattacharjee & Roger Calantone & Taps Maiti, 2019. "Variable Selection with Spatially Autoregressive Errors: A Generalized Moments LASSO Estimator," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(1), pages 146-200, September.
    3. Belloni, Alexandre & Chen, Mingli & Chernozhukov, Victor, 2016. "Quantile Graphical Models : Prediction and Conditional Independence with Applications to Financial Risk Management," Economic Research Papers 269321, University of Warwick - Department of Economics.
    4. Bottmer, Lea & Croux, Christophe & Wilms, Ines, 2022. "Sparse regression for large data sets with outliers," European Journal of Operational Research, Elsevier, vol. 297(2), pages 782-794.
    5. Mueller, Hannes & Rauh, Christopher, 2016. "Reading Between the Lines: Prediction of Political Violence Using Newspaper Text," CEPR Discussion Papers 11516, C.E.P.R. Discussion Papers.
    6. Daniels, David P. & Zlatev, Julian J., 2019. "Choice architects reveal a bias toward positivity and certainty," Organizational Behavior and Human Decision Processes, Elsevier, vol. 151(C), pages 132-149.
    7. Mehmet Caner & Anders Bredahl Kock, 2014. "Asymptotically Honest Confidence Regions for High Dimensional Parameters by the Desparsified Conservative Lasso," CREATES Research Papers 2014-36, Department of Economics and Business Economics, Aarhus University.
    8. Aureo de Paula & Imran Rasul & Pedro Souza, 2019. "Identifying Network Ties from Panel Data: Theory and an Application to Tax Competition," Papers 1910.07452, arXiv.org, revised Oct 2023.
    9. Gambacorta, Leonardo & Huang, Yiping & Qiu, Han & Wang, Jingyi, 2019. "How do machine learning and non-traditional data affect credit scoring? New evidence from a Chinese fintech firm," CEPR Discussion Papers 14259, C.E.P.R. Discussion Papers.
    10. Giannone, Domenico & Lenza, Michele & Primiceri, Giorgio, 2017. "Economic Predictions with Big Data: The Illusion Of Sparsity," CEPR Discussion Papers 12256, C.E.P.R. Discussion Papers.
    11. Anders Bredahl Kock & Laurent A.F. Callot, 2012. "Oracle Inequalities for High Dimensional Vector Autoregressions," CREATES Research Papers 2012-16, Department of Economics and Business Economics, Aarhus University.
    12. Song Song & Peter J. Bickel, 2011. "Large Vector Auto Regressions," Papers 1106.3915, arXiv.org.
    13. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney K. Newey & James Robins, 2017. "Double/debiased machine learning for treatment and structural parameters," CeMMAP working papers CWP28/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    14. Carlos A. Manzanares & Ying Jiang & Patrick Bajari, 2015. "Improving Policy Functions in High-Dimensional Dynamic Games," NBER Working Papers 21124, National Bureau of Economic Research, Inc.
    15. André Nunes Maranhão & Nicole Rennó Castro, 2023. "Dissecting Brazilian agriculture business cycles in high-dimensional and time-irregular span contexts," Empirical Economics, Springer, vol. 65(4), pages 1543-1578, October.
    16. Xu, Ning & Hong, Jian & Fisher, Timothy, 2016. "Model selection consistency from the perspective of generalization ability and VC theory with an application to Lasso," MPRA Paper 71670, University Library of Munich, Germany.
    17. Yichen Gao & Yu Zhang & Ximing Wu, 2015. "Penalized exponential series estimation of copula densities with an application to intergenerational dependence of body mass index," Empirical Economics, Springer, vol. 48(1), pages 61-81, February.
    18. Scoles, Brooke & Nicodemo, Catia, 2022. "Doctors’ attitudes toward specific medical conditions," Journal of Economic Behavior & Organization, Elsevier, vol. 204(C), pages 182-199.
    19. Alexandre Belloni & Victor Chernozhukov & Kengo Kato, 2013. "Robust inference in high-dimensional approximately sparse quantile regression models," CeMMAP working papers CWP70/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    20. Guo, Zijian & Kang, Hyunseung & Cai, T. Tony & Small, Dylan S., 2018. "Testing endogeneity with high dimensional covariates," Journal of Econometrics, Elsevier, vol. 207(1), pages 175-187.
    21. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney K. Newey, 2016. "Double machine learning for treatment and causal parameters," CeMMAP working papers CWP49/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    22. Kock, Anders Bredahl, 2016. "Oracle inequalities, variable selection and uniform inference in high-dimensional correlated random effects panel data models," Journal of Econometrics, Elsevier, vol. 195(1), pages 71-85.
    23. Sander Gerritsen & Mark Kattenberg & Sonny Kuijpers, 2019. "The impact of age at arrival on education and mental health," CPB Discussion Paper 389, CPB Netherlands Bureau for Economic Policy Analysis.
    24. Demian Pouzo, 2015. "On the Non-Asymptotic Properties of Regularized M-estimators," Papers 1512.06290, arXiv.org, revised Oct 2016.
    25. Barigozzi, Matteo & Brownlees, Christian T., 2018. "Nets: network estimation for time series," LSE Research Online Documents on Economics 90493, London School of Economics and Political Science, LSE Library.
    26. De La Maza, Cristóbal & Davis, Alex & Azevedo, Inês, 2021. "Welfare analysis of the ecological impacts of electricity production in Chile using the sparse multinomial logit model," Ecological Economics, Elsevier, vol. 184(C).
    27. Philipp Bach & Victor Chernozhukov & Malte S. Kurz & Martin Spindler & Sven Klaassen, 2021. "DoubleML -- An Object-Oriented Implementation of Double Machine Learning in R," Papers 2103.09603, arXiv.org, revised Jun 2024.
    28. Alexandre Belloni & Mingli Chen & Victor Chernozhukov, 2017. "Quantile graphical models: prediction and conditional independence with applications to systemic risk," CeMMAP working papers 54/17, Institute for Fiscal Studies.
    29. Damian Kozbur, 2013. "Inference in additively separable models with a high-dimensional set of conditioning variables," ECON - Working Papers 284, Department of Economics - University of Zurich, revised Apr 2018.
    30. Ng, Serena, 2013. "Variable Selection in Predictive Regressions," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 752-789, Elsevier.
    31. Huseynov, Samir & Palma, Marco A., 2018. "Does California’s LCFS Reduce CO2 Emissions?," 2018 Annual Meeting, August 5-7, Washington, D.C. 274200, Agricultural and Applied Economics Association.
    32. Alec Smith & B. Douglas Bernheim & Colin F. Camerer & Antonio Rangel, 2014. "Neural Activity Reveals Preferences without Choices," American Economic Journal: Microeconomics, American Economic Association, vol. 6(2), pages 1-36, May.
    33. Roberto Casarin & Daniel Felix Ahelegbey & Monica Billio, 2014. "Sparse Graphical Vector Autoregression: A Bayesian Approach," Working Papers 2014:29, Department of Economics, University of Venice "Ca' Foscari".
    34. Bo Cowgill & Patryk Perkowski, 2024. "Delegation in Hiring: Evidence from a Two-Sided Audit," Journal of Political Economy Microeconomics, University of Chicago Press, vol. 2(4), pages 852-882.
    35. Natalia Bailey & George Kapetanios & M. Hashem Pesaran, 2020. "Measurement of Factor Strength: Theory and Practice," Monash Econometrics and Business Statistics Working Papers 7/20, Monash University, Department of Econometrics and Business Statistics.
    36. Florens, Jean-Pierre & Van Bellegem, Sébastien, 2015. "Instrumental variable estimation in functional linear models," Journal of Econometrics, Elsevier, vol. 186(2), pages 465-476.
    37. Chatterjee, A. & Gupta, S. & Lahiri, S.N., 2015. "On the residual empirical process based on the ALASSO in high dimensions and its functional oracle property," Journal of Econometrics, Elsevier, vol. 186(2), pages 317-324.
    38. Youngjoo Cho & Debashis Ghosh, 2021. "Quantile-Based Subgroup Identification for Randomized Clinical Trials," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 13(1), pages 90-128, April.
    39. Li, Zhaoyuan & Yao, Jianfeng, 2019. "Testing for heteroscedasticity in high-dimensional regressions," Econometrics and Statistics, Elsevier, vol. 9(C), pages 122-139.
    40. Matthew Gentzkow & Bryan T. Kelly & Matt Taddy, 2017. "Text as Data," NBER Working Papers 23276, National Bureau of Economic Research, Inc.
    41. Chernozhukov, Victor & Härdle, Wolfgang Karl & Huang, Chen & Wang, Weining, 2018. "LASSO-Driven Inference in Time and Space," IRTG 1792 Discussion Papers 2018-021, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    42. Riccardo Di Francesco, 2024. "Ordered Correlation Forest," CEIS Research Paper 577, Tor Vergata University, CEIS, revised 06 May 2024.
    43. Dai, Wei & Tsang, Ka Wai, 2023. "A resampling approach for confidence intervals in linear time-series models after model selection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 611(C).
    44. Alain Hecq & Luca Margaritella & Stephan Smeekes, 2023. "Granger Causality Testing in High-Dimensional VARs: A Post-Double-Selection Procedure," Journal of Financial Econometrics, Oxford University Press, vol. 21(3), pages 915-958.
    45. Alexandre Belloni & Victor Chernozhukov & Lie Wang, 2013. "Pivotal estimation via square-root lasso in nonparametric regression," CeMMAP working papers 62/13, Institute for Fiscal Studies.
    46. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins, 2016. "Double/Debiased Machine Learning for Treatment and Causal Parameters," Papers 1608.00060, arXiv.org, revised Nov 2024.
    47. Aglasan, Serkan & Goodwin, Barry K. & Rejesus, Roderick, 2020. "Genetically Modified Rootworm-Resistant Corn, Risk, and Weather: Evidence from High Dimensional Methods," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 305181, Agricultural and Applied Economics Association.
    48. Bonan, Jacopo & Burlacu, Sergiu & Galliera, Arianna, 2023. "Prosociality in variants of the dictator game: Evidence from children in El Salvador," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 107(C).
    49. Federico A. Bugni & Mehmet Caner & Anders Bredahl Kock & Soumendra Lahiri, 2016. "Inference in partially identified models with many moment inequalities using Lasso," CREATES Research Papers 2016-12, Department of Economics and Business Economics, Aarhus University.
    50. Helmut Wasserbacher & Martin Spindler, 2022. "Machine learning for financial forecasting, planning and analysis: recent developments and pitfalls," Digital Finance, Springer, vol. 4(1), pages 63-88, March.
    51. Myrto Kalouptsidi, 2014. "Time to Build and Fluctuations in Bulk Shipping," American Economic Review, American Economic Association, vol. 104(2), pages 564-608, February.
    52. Gold, David & Lederer, Johannes & Tao, Jing, 2020. "Inference for high-dimensional instrumental variables regression," Journal of Econometrics, Elsevier, vol. 217(1), pages 79-111.
    53. Lim, Dennis & Wang, Wenjie & Zhang, Yichong, 2024. "A conditional linear combination test with many weak instruments," Journal of Econometrics, Elsevier, vol. 238(2).
    54. Awijen, Haithem & Ben Zaied, Younes & Ben Lahouel, Béchir & Khlifi, Foued, 2023. "Machine learning for US cross-industry return predictability under information uncertainty," Research in International Business and Finance, Elsevier, vol. 64(C).
    55. Victor Chernozhukov & Chris Hansen & Martin Spindler, 2016. "High-Dimensional Metrics in R," Papers 1603.01700, arXiv.org, revised Aug 2016.
    56. Zhu, Ying, 2018. "Sparse linear models and l1-regularized 2SLS with high-dimensional endogenous regressors and instruments," Journal of Econometrics, Elsevier, vol. 202(2), pages 196-213.

  29. Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2011. "Estimation of treatment effects with high-dimensional controls," CeMMAP working papers 42/11, Institute for Fiscal Studies.

    Cited by:

    1. Shi, Zhentao, 2016. "Econometric estimation with high-dimensional moment equalities," Journal of Econometrics, Elsevier, vol. 195(1), pages 104-119.
    2. Chen, Daniel L., 2016. "Priming Ideology: Why Presidential Elections Affect U.S. Judges," TSE Working Papers 16-681, Toulouse School of Economics (TSE), revised Aug 2016.
    3. Chen, Daniel L. & Michaeli, Moti & Spiro, Daniel, 2016. "Ideological Perfectionism," TSE Working Papers 16-694, Toulouse School of Economics (TSE).

  30. Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2010. "LASSO Methods for Gaussian Instrumental Variables Models," Papers 1012.1297, arXiv.org, revised Feb 2011.

    Cited by:

    1. Nepp, Alexander & Okhrin, Ostap & Egorova, Julia & Dzhuraeva, Zarnigor & Zykov, Alexander, 2022. "What threatens stock markets more - The coronavirus or the hype around it?," International Review of Economics & Finance, Elsevier, vol. 78(C), pages 519-539.
    2. Breunig, Christoph & Mammen, Enno & Simoni, Anna, 2020. "Ill-posed estimation in high-dimensional models with instrumental variables," Journal of Econometrics, Elsevier, vol. 219(1), pages 171-200.
    3. Felipe González & Magdalena Larreboure, 2021. "The Impact of the Women’s March on the U.S. House Election," Documentos de Trabajo 560, Instituto de Economia. Pontificia Universidad Católica de Chile..
    4. Ellora Derenoncourt, 2022. "Can You Move to Opportunity? Evidence from the Great Migration," American Economic Review, American Economic Association, vol. 112(2), pages 369-408, February.
    5. Andrii Babii, 2022. "High-Dimensional Mixed-Frequency IV Regression," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(4), pages 1470-1483, October.
    6. Belloni, Alexandre & Hansen, Christian & Newey, Whitney, 2022. "High-dimensional linear models with many endogenous variables," Journal of Econometrics, Elsevier, vol. 228(1), pages 4-26.
    7. Mehmet Caner & Esfandiar Maasoumi & Juan Andrés Riquelme, 2016. "Moment and IV Selection Approaches: A Comparative Simulation Study," Econometric Reviews, Taylor & Francis Journals, vol. 35(8-10), pages 1562-1581, December.
    8. Adel Javanmard & Jason D. Lee, 2020. "A flexible framework for hypothesis testing in high dimensions," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(3), pages 685-718, July.
    9. Alena Skolkova, 2023. "Instrumental Variable Estimation with Many Instruments Using Elastic-Net IV," CERGE-EI Working Papers wp759, The Center for Economic Research and Graduate Education - Economics Institute, Prague.

  31. Alexandre Belloni & Daniel Chen & Victor Chernozhukov & Christian Hansen, 2010. "Sparse Models and Methods for Optimal Instruments with an Application to Eminent Domain," Papers 1010.4345, arXiv.org, revised Apr 2015.

    Cited by:

    1. Emily Cuddy & Janet Currie, 2020. "Rules vs. Discretion: Treatment of Mental Illness in U.S. Adolescents," Working Papers 2020-10, Princeton University. Economics Department..
    2. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Christian Hansen & Kengo Kato, 2018. "High-Dimensional Econometrics and Regularized GMM," Papers 1806.01888, arXiv.org, revised Jun 2018.
    3. Alexandre Belloni & Victor Chernozhukov & Kengo Kato, 2019. "Valid Post-Selection Inference in High-Dimensional Approximately Sparse Quantile Regression Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 114(526), pages 749-758, April.
    4. Breinlich, Holger & Corradi, Valentina & Rocha, Nadia & Ruta, Michele & Santos Silva, JMC & Zylkin, Thomas, 2022. "Machine Learning in International Trade Research - Evaluating the Impact of Trade Agreements," CEPR Discussion Papers 17325, C.E.P.R. Discussion Papers.
    5. Liqian Cai & Arnab Bhattacharjee & Roger Calantone & Taps Maiti, 2019. "Variable Selection with Spatially Autoregressive Errors: A Generalized Moments LASSO Estimator," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(1), pages 146-200, September.
    6. Julián Caballero & Christian Upper, 2023. "What happens to EMEs when US yields go up?," BIS Working Papers 1081, Bank for International Settlements.
    7. Belloni, Alexandre & Chen, Mingli & Chernozhukov, Victor, 2016. "Quantile Graphical Models : Prediction and Conditional Independence with Applications to Financial Risk Management," Economic Research Papers 269321, University of Warwick - Department of Economics.
    8. Linton, Oliver & Seo, Myung Hwan & Whang, Yoon-Jae, 2023. "Testing stochastic dominance with many conditioning variables," Journal of Econometrics, Elsevier, vol. 235(2), pages 507-527.
    9. Kaspar Wuthrich & Ying Zhu, 2019. "Omitted variable bias of Lasso-based inference methods: A finite sample analysis," Papers 1903.08704, arXiv.org, revised Sep 2021.
    10. Chen, Daniel L. & Lind, Jo Thori, 2016. "The Political Economy of Beliefs: Why Fiscal and Social Conservatives/Liberals (Sometimes) Come Hand-in-Hand," TSE Working Papers 16-722, Toulouse School of Economics (TSE).
    11. Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen, 2016. "Program evaluation and causal inference with high-dimensional data," CeMMAP working papers 13/16, Institute for Fiscal Studies.
    12. Anil Kumar, 2014. "Do restrictions on home equity extraction contribute to lower mortgage defaults? evidence from a policy discontinuity at the Texas border," Working Papers 1410, Federal Reserve Bank of Dallas.
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    348. Simone Maxand & Hend Sallam, 2024. "Local Fiscal Effects of Immigration in Germany," CESifo Working Paper Series 11162, CESifo.
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    355. Cho, Hyunkeun, 2016. "The analysis of multivariate longitudinal data using multivariate marginal models," Journal of Multivariate Analysis, Elsevier, vol. 143(C), pages 481-491.
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  32. Theodossiou, Panayiotis & McDonald, James B. & Hansen, Christian B., 2007. "Some Flexible Parametric Models for Partially Adaptive Estimators of Econometric Models," Economics Discussion Papers 2007-13, Kiel Institute for the World Economy (IfW Kiel).

    Cited by:

    1. BenSaïda, Ahmed & Slim, Skander, 2016. "Highly flexible distributions to fit multiple frequency financial returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 203-213.
    2. Larsen, Bradley J. & Oswald, Florian & Reich, Gregor & Wunderli, Dan, 2012. "A test of the extreme value type I assumption in the bus engine replacement model," Economics Letters, Elsevier, vol. 116(2), pages 213-216.
    3. Martin Møller Andreasen, 2008. "Ensuring the Validity of the Micro Foundation in DSGE Models," CREATES Research Papers 2008-26, Department of Economics and Business Economics, Aarhus University.
    4. James Hansen & James McDonald & Panayiotis Theodossiou & Brad Larsen, 2010. "Partially Adaptive Econometric Methods For Regression and Classification," Computational Economics, Springer;Society for Computational Economics, vol. 36(2), pages 153-169, August.
    5. Hallin, Marc & La Vecchia, Davide, 2017. "R-estimation in semiparametric dynamic location-scale models," Journal of Econometrics, Elsevier, vol. 196(2), pages 233-247.
    6. Norman, Stephen & Phillips, Kerk L., 2009. "What is the Shape of Real Exchange Rate Nonlinearity?," MPRA Paper 23504, University Library of Munich, Germany.
    7. Joe Hirschberg & Jenny Lye, 2021. "Estimating risk premiums for regulated firms when accounting for reference-day variation and high-order moments of return volatility," Environment Systems and Decisions, Springer, vol. 41(3), pages 455-467, September.
    8. Yeliz Mert Kantar & Ilhan Usta & Şükrü Acıtaş, 2011. "A Monte Carlo simulation study on partially adaptive estimators of linear regression models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(8), pages 1681-1699, August.
    9. Sikora, Grzegorz & Michalak, Anna & Bielak, Łukasz & Miśta, Paweł & Wyłomańska, Agnieszka, 2019. "Stochastic modeling of currency exchange rates with novel validation techniques," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1202-1215.
    10. Szarek, Dawid & Bielak, Łukasz & Wyłomańska, Agnieszka, 2020. "Long-term prediction of the metals’ prices using non-Gaussian time-inhomogeneous stochastic process," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 555(C).
    11. Martin Browning & Lars Gårn Hansen & Sinne Smed, 2019. "Heterogeneous Consumer Reactions to Health News," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 101(2), pages 579-599.
    12. Martin Browning & Lars Gårn Hansen & Sinne Smed, 2013. "Rational inattention or rational overreaction? Consumer reactions to health news," IFRO Working Paper 2013/14, University of Copenhagen, Department of Food and Resource Economics.
    13. Sean C. Kerman & James B. McDonald, 2012. "Skewness-kurtosis bounds for the skewed generalized T and related distributions," BYU Macroeconomics and Computational Laboratory Working Paper Series 2012-10, Brigham Young University, Department of Economics, BYU Macroeconomics and Computational Laboratory.
    14. Monique Graf & J. Miguel Marín & Isabel Molina, 2019. "A generalized mixed model for skewed distributions applied to small area estimation," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(2), pages 565-597, June.
    15. Steven Caudill, 2012. "A partially adaptive estimator for the censored regression model based on a mixture of normal distributions," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 21(2), pages 121-137, June.
    16. Herrmann Klaus & Fischer Matthias, 2010. "An Alternative Maximum Entropy Model for Time-Varying Moments with Application to Financial Returns," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(3), pages 1-23, May.
    17. Randall A. Lewis & James B. McDonald, 2014. "Partially Adaptive Estimation of the Censored Regression Model," Econometric Reviews, Taylor & Francis Journals, vol. 33(7), pages 732-750, October.
    18. Higbee, Joshua D. & McDonald, James B., 2024. "A comparison of the GB2 and skewed generalized log-t distributions with an application in finance," Journal of Econometrics, Elsevier, vol. 240(2).

  33. Christian Hansen & James B. McDonald & Whitney K. Newey, 2007. "Instrumental variables estimation with flexible distribution," CeMMAP working papers CWP21/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Poirier, Alexandre, 2017. "Efficient estimation in models with independence restrictions," Journal of Econometrics, Elsevier, vol. 196(1), pages 1-22.
    2. Sølvsten, Mikkel, 2020. "Robust estimation with many instruments," Journal of Econometrics, Elsevier, vol. 214(2), pages 495-512.
    3. Jason Cook & James McDonald, 2013. "Partially Adaptive Estimation of Interval Censored Regression Models," Computational Economics, Springer;Society for Computational Economics, vol. 42(1), pages 119-131, June.
    4. James B. McDonald & Daniel B. Walton & Bryan Chia, 2020. "Distributional Assumptions and the Estimation of Contingent Valuation Models," Computational Economics, Springer;Society for Computational Economics, vol. 56(2), pages 431-460, August.
    5. Lee, Adam & Mesters, Geert, 2024. "Locally robust inference for non-Gaussian linear simultaneous equations models," Journal of Econometrics, Elsevier, vol. 240(1).
    6. Scott A. Carson & James B. McDonald, 2018. "Partially Adaptive Econometric Methods and the Modern Obesity Epidemic," CESifo Working Paper Series 7058, CESifo.
    7. Mamonov Mikhail E. & Parmeter Christopher F. & Prokhorov Artem B., 2022. "Dependence modeling in stochastic frontier analysis," Dependence Modeling, De Gruyter, vol. 10(1), pages 123-144, January.
    8. Sikora, Grzegorz & Michalak, Anna & Bielak, Łukasz & Miśta, Paweł & Wyłomańska, Agnieszka, 2019. "Stochastic modeling of currency exchange rates with novel validation techniques," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1202-1215.
    9. Szarek, Dawid & Bielak, Łukasz & Wyłomańska, Agnieszka, 2020. "Long-term prediction of the metals’ prices using non-Gaussian time-inhomogeneous stochastic process," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 555(C).
    10. Andrea Guizzardi & Luca Vincenzo Ballestra & Enzo D’Innocenzo, 2024. "Reverse engineering the last-minute on-line pricing practices: an application to hotels," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 33(3), pages 943-971, July.
    11. Amsler, Christine & Artem, Prokhorov & Peter, Schmidt, 2015. "Endogeneity in Stochastic Frontier Models," Working Papers 2015-01, University of Sydney Business School, Discipline of Business Analytics.
    12. Sean C. Kerman & James B. McDonald, 2012. "Skewness-kurtosis bounds for the skewed generalized T and related distributions," BYU Macroeconomics and Computational Laboratory Working Paper Series 2012-10, Brigham Young University, Department of Economics, BYU Macroeconomics and Computational Laboratory.
    13. Guizzardi, Andrea & Ballestra, Luca Vincenzo & D'Innocenzo, Enzo, 2022. "Hotel dynamic pricing, stochastic demand and covid-19," Annals of Tourism Research, Elsevier, vol. 97(C).
    14. Scott Alan Carson & Wael M. Al-Sawai & Scott A. Carson, 2023. "Partially Adaptive Econometric Methods and Vertically Integrated Majors in the Oil and Gas Industry," CESifo Working Paper Series 10733, CESifo.
    15. Zhi, Bangdong & Wang, Xiaojun & Xu, Fangming, 2020. "Impawn rate optimisation in inventory financing: A canonical vine copula-based approach," International Journal of Production Economics, Elsevier, vol. 227(C).
    16. McDonald, James & Stoddard, Olga & Walton, Daniel, 2018. "On using interval response data in experimental economics," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 72(C), pages 9-16.
    17. Tsionas, Efthymios G., 2013. "Bayesian inference in regression with Pearson disturbances," Economics Letters, Elsevier, vol. 118(1), pages 177-181.
    18. Siemsen, Thomas & Vilsmeier, Johannes, 2018. "On a quest for robustness: About model risk, randomness and discretion in credit risk stress tests," Discussion Papers 31/2018, Deutsche Bundesbank.
    19. Juraj Pekár & Mário Pčolár, 2022. "Empirical distribution of daily stock returns of selected developing and emerging markets with application to financial risk management," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(2), pages 699-731, June.
    20. Ng Serena & Bai Jushan, 2009. "Selecting Instrumental Variables in a Data Rich Environment," Journal of Time Series Econometrics, De Gruyter, vol. 1(1), pages 1-34, April.
    21. Oh Kang Kwon & Stephen Satchell, 2020. "The Distribution of Cross Sectional Momentum Returns When Underlying Asset Returns Are Student’s t Distributed," JRFM, MDPI, vol. 13(2), pages 1-19, February.
    22. John Deke & Mariel Finucane & Daniel Thal, "undated". "The BASIE (BAyeSian Interpretation of Estimates) Framework for Interpreting Findings from Impact Evaluations: A Practical Guide for Education Researchers," Mathematica Policy Research Reports 5a0d5dff375d42048799878be, Mathematica Policy Research.
    23. Shum, Wai Yan, 2020. "Modelling conditional skewness: Heterogeneous beliefs, short sale restrictions and market declines," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    24. Jetro Anttonen & Markku Lanne & Jani Luoto, 2024. "Statistically identified structural VAR model with potentially skewed and fat‐tailed errors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(3), pages 422-437, April.

  34. Christian Hansen & Jerry Hausman & Whitney K. Newey, 2006. "Estimation with many instrumental variables," CeMMAP working papers CWP19/06, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Gordon, Brett R. & Hartmann, Wesley R., 2011. "Advertising Effects in Presidential Elections," Research Papers 2080, Stanford University, Graduate School of Business.
    2. Doko Tchatoka, Firmin & Wang, Wenjie, 2021. "Size-corrected Bootstrap Test after Pretesting for Exogeneity with Heteroskedastic or Clustered Data," MPRA Paper 110899, University Library of Munich, Germany.
    3. Norman R. Swanson & John C. Chao & Jerry A. Hausman & Whitney K. Newey & Tiemen Woutersen, 2011. "Testing Overidentifying Restrictions with Many Instruments and Heteroskedasticity," Departmental Working Papers 201118, Rutgers University, Department of Economics.
    4. Jerry Hausman & Whitney K. Newey & Tiemen M. Woutersen & John Chao & Norman Swanson, 2007. "Instrumental variable estimation with heteroskedasticity and many instruments," CeMMAP working papers CWP22/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Firmin Doko Tchatoka, 2014. "Specification Tests with Weak and Invalid Instruments," School of Economics and Public Policy Working Papers 2014-05, University of Adelaide, School of Economics and Public Policy.
    6. Eric Gautier & Christiern Rose, 2022. "Fast, Robust Inference for Linear Instrumental Variables Models using Self-Normalized Moments," Papers 2211.02249, arXiv.org, revised Nov 2022.
    7. Hyunseok Jung & Xiaodong Liu, 2023. "Testing for Peer Effects without Specifying the Network Structure," Papers 2306.09806, arXiv.org, revised Jul 2024.
    8. Stanislav Anatolyev & Nikolay Gospodinov, 2008. "Specification Testing in Models with Many Instruments," Working Papers w0124, New Economic School (NES).
    9. John Gilbert & Reza Oladi, 2011. "Net Campaign Contributions, Agricultural Interests, and Votes on Liberalizing Trade with China," Working Papers 2011-02, Utah State University, Department of Economics.
    10. Antoine, Bertille & Lavergne, Pascal, 2023. "Identification-robust nonparametric inference in a linear IV model," Journal of Econometrics, Elsevier, vol. 235(1), pages 1-24.
    11. Hu, Zhining, 2021. "The effect of income inequality on human capital inequality: Evidence from China," Structural Change and Economic Dynamics, Elsevier, vol. 58(C), pages 471-489.
    12. Liu, Xiaodong & Patacchini, Eleonora & Zenou, Yves & Lee, Lung-Fei, 2012. "Criminal Networks: Who is the Key Player?," Climate Change and Sustainable Development 128707, Fondazione Eni Enrico Mattei (FEEM).
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Articles

  1. Achim Ahrens & Christian B. Hansen & Mark E. Schaffer & Thomas Wiemann, 2024. "ddml: Double/debiased machine learning in Stata," Stata Journal, StataCorp LP, vol. 24(1), pages 3-45, March.
    See citations under working paper version above.
  2. Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2023. "pystacked: Stacking generalization and machine learning in Stata," Stata Journal, StataCorp LP, vol. 23(4), pages 909-931, December.
    See citations under working paper version above.
  3. Belloni, Alexandre & Hansen, Christian & Newey, Whitney, 2022. "High-dimensional linear models with many endogenous variables," Journal of Econometrics, Elsevier, vol. 228(1), pages 4-26.

    Cited by:

    1. Santos, José Eusébio & Andini, Corrado, 2024. "Net privatisation prices in Brazil," Emerging Markets Review, Elsevier, vol. 60(C).
    2. Eric Gautier & Christiern Rose, 2022. "Fast, Robust Inference for Linear Instrumental Variables Models using Self-Normalized Moments," Papers 2211.02249, arXiv.org, revised Nov 2022.

  4. Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2020. "lassopack: Model selection and prediction with regularized regression in Stata," Stata Journal, StataCorp LP, vol. 20(1), pages 176-235, March.
    See citations under working paper version above.
  5. Hansen, Christian & Liao, Yuan, 2019. "The Factor-Lasso And K-Step Bootstrap Approach For Inference In High-Dimensional Economic Applications," Econometric Theory, Cambridge University Press, vol. 35(3), pages 465-509, June.
    See citations under working paper version above.
  6. Simon Freyaldenhoven & Christian Hansen & Jesse M. Shapiro, 2019. "Pre-event Trends in the Panel Event-Study Design," American Economic Review, American Economic Association, vol. 109(9), pages 3307-3338, September.
    See citations under working paper version above.
  7. Timothy Conley & Silvia Gonçalves & Christian Hansen, 2018. "Inference with Dependent Data in Accounting and Finance Applications," Journal of Accounting Research, Wiley Blackwell, vol. 56(4), pages 1139-1203, September.

    Cited by:

    1. Jinhwan Kim & Rodrigo S. Verdi & Benjamin P. Yost, 2020. "Do Firms Strategically Internalize Disclosure Spillovers? Evidence from Cash‐Financed M&As," Journal of Accounting Research, Wiley Blackwell, vol. 58(5), pages 1249-1297, December.
    2. James G. MacKinnon & Morten Ørregaard Nielsen & Matthew D. Webb, 2023. "Leverage, influence, and the jackknife in clustered regression models: Reliable inference using summclust," Stata Journal, StataCorp LP, vol. 23(4), pages 942-982, December.
    3. James G. MacKinnon & Morten Ørregaard Nielsen & Matthew D. Webb, 2022. "Fast and Reliable Jackknife and Bootstrap Methods for Cluster-Robust Inference," Working Paper 1485, Economics Department, Queen's University.
    4. James G. MacKinnon & Morten {O}rregaard Nielsen & Matthew D. Webb, 2023. "Testing for the appropriate level of clustering in linear regression models," Papers 2301.04522, arXiv.org, revised Mar 2023.
    5. James G. MacKinnon & Morten Ørregaard Nielsen & Matthew D. Webb, 2022. "Cluster-Robust Inference: A Guide to Empirical Practice," Working Paper 1456, Economics Department, Queen's University.
    6. Kris Hardies & Sarowar Hossain & Larelle (Ellie) Chapple, 2021. "Archival research on audit partners: assessing the research field and recommendations for future research," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(3), pages 4209-4256, September.
    7. Harakeh, Mostafa & El-Gammal, Walid & Matar, Ghida, 2019. "Female directors, earnings management, and CEO incentive compensation: UK evidence," Research in International Business and Finance, Elsevier, vol. 50(C), pages 153-170.
    8. Wessel M Badenhorst & Rieka von Well, 2023. "The Value‐relevance of Fair Value Measurement for Inventories," Australian Accounting Review, CPA Australia, vol. 33(2), pages 135-159, June.
    9. Michael P. Leung, 2021. "Network Cluster-Robust Inference," Papers 2103.01470, arXiv.org, revised Feb 2023.
    10. Balakrishnan, Karthik & De George, Emmanuel T. & Ertan, Aytekin & Scobie, Hannah, 2021. "Economic consequences of mandatory auditor reporting to bank regulators," Journal of Accounting and Economics, Elsevier, vol. 72(2).
    11. Harakeh, Mostafa, 2020. "Dividend policy and corporate investment under information shocks," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 65(C).
    12. Peter Fiechter & Jörg‐Markus Hitz & Nico Lehmann, 2022. "Real Effects of a Widespread CSR Reporting Mandate: Evidence from the European Union's CSR Directive," Journal of Accounting Research, Wiley Blackwell, vol. 60(4), pages 1499-1549, September.
    13. Nicholas M. Guest, 2021. "The Information Role of the Media in Earnings News," Journal of Accounting Research, Wiley Blackwell, vol. 59(3), pages 1021-1076, June.
    14. Dane M. Christensen & Hengda Jin & Suhas A. Sridharan & Laura A. Wellman, 2022. "Hedging on the Hill: Does Political Hedging Reduce Firm Risk?," Management Science, INFORMS, vol. 68(6), pages 4356-4379, June.
    15. James G. MacKinnon & Morten Ørregaard Nielsen & Matthew D. Webb, 2024. "Cluster-Robust Jackknife and Bootstrap Inference for Binary Response Models," Working Paper 1515, Economics Department, Queen's University.
    16. Fiechter, Peter & Landsman, Wayne R. & Peasnell, Kenneth & Renders, Annelies, 2024. "Do industry-specific accounting standards matter for capital allocation decisions?," Journal of Accounting and Economics, Elsevier, vol. 77(2).
    17. Miao Liu, 2022. "Assessing Human Information Processing in Lending Decisions: A Machine Learning Approach," Journal of Accounting Research, Wiley Blackwell, vol. 60(2), pages 607-651, May.
    18. Cao, Zhangfan & Chen, Steven Xianglong & Harakeh, Mostafa & Lee, Edward, 2022. "Do non-financial factors influence corporate dividend policies? Evidence from business strategy," International Review of Financial Analysis, Elsevier, vol. 82(C).
    19. Cai Yong & Canay Ivan A. & Kim Deborah & Shaikh Azeem M., 2023. "On the Implementation of Approximate Randomization Tests in Linear Models with a Small Number of Clusters," Journal of Econometric Methods, De Gruyter, vol. 12(1), pages 85-103, January.
    20. Abakah, Alex Annan & Kim, Gunchang & Somé, Hyacinthe Yirlier, 2024. "Social networks and start-up funding," Finance Research Letters, Elsevier, vol. 64(C).
    21. Kevin C. W. Chen & Tai‐Yuan Chen & Weifang Han & Hongqi Yuan, 2022. "Auditors Under Fire: The Association Between Audit Errors and the Career Setbacks of Individual Auditors," Journal of Accounting Research, Wiley Blackwell, vol. 60(3), pages 853-900, June.
    22. Huang, Yin-Siang & Lee, Cheng-Few & Lin, Chih-Yung, 2023. "Applications of fixed effect models to managerial risk-taking incentives," The Quarterly Review of Economics and Finance, Elsevier, vol. 92(C), pages 249-261.
    23. Darendeli, Alper & Fiechter, Peter & Hitz, Jörg-Markus & Lehmann, Nico, 2022. "The role of corporate social responsibility (CSR) information in supply-chain contracting: Evidence from the expansion of CSR rating coverage," Journal of Accounting and Economics, Elsevier, vol. 74(2).
    24. Frank S. Zhou & Yuqing Zhou, 2020. "The Dog that Did Not Bark: Limited Price Efficiency and Strategic Nondisclosure," Journal of Accounting Research, Wiley Blackwell, vol. 58(1), pages 155-197, March.
    25. Raphael Duguay, 2022. "The Economic Consequences of Financial Audit Regulation in the Charitable Sector," Journal of Accounting Research, Wiley Blackwell, vol. 60(4), pages 1463-1498, September.

  8. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins, 2018. "Double/debiased machine learning for treatment and structural parameters," Econometrics Journal, Royal Economic Society, vol. 21(1), pages 1-68, February.
    See citations under working paper version above.
  9. A. Belloni & V. Chernozhukov & I. Fernández‐Val & C. Hansen, 2017. "Program Evaluation and Causal Inference With High‐Dimensional Data," Econometrica, Econometric Society, vol. 85, pages 233-298, January.
    See citations under working paper version above.
  10. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey, 2017. "Double/Debiased/Neyman Machine Learning of Treatment Effects," American Economic Review, American Economic Association, vol. 107(5), pages 261-265, May.

    Cited by:

    1. TELLO, Mario D., 2024. "Inversión Pública En Infraestructura Y Crecimiento Regional En Perú, 2005-2020: Un Análisis Basado En Técnicas De Aprendizaje Automático Causal," Regional and Sectoral Economic Studies, Euro-American Association of Economic Development, vol. 24(2), pages 195-222.
    2. Pedro H. C. Sant'Anna & Jun B. Zhao, 2018. "Doubly Robust Difference-in-Differences Estimators," Papers 1812.01723, arXiv.org, revised May 2020.
    3. Xiong, Ruoxuan & Koenecke, Allison & Powell, Michael & Shen, Zhu & Vogelstein, Joshua T. & Athey, Susan, 2021. "Federated Causal Inference in Heterogeneous Observational Data," Research Papers 3990, Stanford University, Graduate School of Business.
    4. Yoganathan, Vignesh & Osburg, Victoria-Sophie, 2024. "The mind in the machine: Estimating mind perception's effect on user satisfaction with voice-based conversational agents," Journal of Business Research, Elsevier, vol. 175(C).
    5. Maximilian Maurice Gail & Phil-Adrian Klotz, 2021. "The Impact of the Agency Model on E-book Prices: Evidence from the UK," MAGKS Papers on Economics 202111, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    6. Jong Hee Park & Byung Koo Kim, 2020. "Why your neighbor matters: Positions in preferential trade agreement networks and export growth in global value chains," Economics and Politics, Wiley Blackwell, vol. 32(3), pages 381-410, November.
    7. Ziwei Cong & Jia Liu & Puneet Manchanda, 2021. "The Role of "Live" in Livestreaming Markets: Evidence Using Orthogonal Random Forest," Papers 2107.01629, arXiv.org, revised Sep 2022.
    8. Susan Athey & Guido Imbens & Jonas Metzger & Evan Munro, 2019. "Using Wasserstein Generative Adversarial Networks for the Design of Monte Carlo Simulations," Papers 1909.02210, arXiv.org, revised Jul 2020.
    9. Miquel Oliu-Barton & Bary S R Pradelski & Nicolas Woloszko & Lionel Guetta-Jeanrenaud & Philippe Aghion & Patrick Artus & Arnaud Fontanet & Philippe Martin & Guntram B Wolff, 2022. "The Effect of COVID Certificates on Vaccine Uptake, Health Outcomes, and the Economy," Post-Print hal-03813557, HAL.
    10. Waverly Wei & Maya Petersen & Mark J van der Laan & Zeyu Zheng & Chong Wu & Jingshen Wang, 2023. "Efficient targeted learning of heterogeneous treatment effects for multiple subgroups," Biometrics, The International Biometric Society, vol. 79(3), pages 1934-1946, September.
    11. Jinyong Hahn & Jerry Hausman, 2021. "Problems with the Control Variable Approach in Achieving Unbiased Estimates in Nonlinear Models in the Presence of Many Instruments," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 39-58, December.
    12. Wang, Hongning & Ma, Sanjun, 2022. "Preventing crimes against public health with artificial intelligence and machine learning capabilities," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    13. Monica Andini & Emanuele Ciani & Guido de Blasio & Alessio D'Ignazio & Viola Salvestrini, 2017. "Targeting policy-compliers with machine learning: an application to a tax rebate programme in Italy," Temi di discussione (Economic working papers) 1158, Bank of Italy, Economic Research and International Relations Area.
    14. Francesco Decarolis & Cristina Giorgiantonio, 2020. "Corruption red flags in public procurement: new evidence from Italian calls for tenders," Questioni di Economia e Finanza (Occasional Papers) 544, Bank of Italy, Economic Research and International Relations Area.
    15. Hoang, Daniel & Wiegratz, Kevin, 2022. "Machine learning methods in finance: Recent applications and prospects," Working Paper Series in Economics 158, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    16. Huber, Martin & Wüthrich, Kaspar, 2019. "Local Average and Quantile Treatment Effects Under Endogeneity: A Review," University of California at San Diego, Economics Working Paper Series qt4j29d8sc, Department of Economics, UC San Diego.
    17. Valente, Marica, 2023. "Policy evaluation of waste pricing programs using heterogeneous causal effect estimation," Journal of Environmental Economics and Management, Elsevier, vol. 117(C).
    18. Laura Derksen & Jason Kerwin & Natalia Ordaz Reynoso & Olivier Sterck, 2021. "Appointments: A More Effective Commitment Device for Health Behaviors," Papers 2110.06876, arXiv.org.
    19. Anna Baiardi & Andrea A. Naghi, 2021. "The Value Added of Machine Learning to Causal Inference: Evidence from Revisited Studies," Papers 2101.00878, arXiv.org.
    20. Gustavo J. Bobonis & Paul J. Gertler & Marco Gonzalez-Navarro & Simeon Nichter, 2023. "Does Combating Corruption Reduce Clientelism?," Working Papers tecipa-752, University of Toronto, Department of Economics.
    21. Zhen Li & Jie Chen & Eric Laber & Fang Liu & Richard Baumgartner, 2023. "Optimal Treatment Regimes: A Review and Empirical Comparison," International Statistical Review, International Statistical Institute, vol. 91(3), pages 427-463, December.
    22. Ganesh Karapakula, 2023. "Stable Probability Weighting: Large-Sample and Finite-Sample Estimation and Inference Methods for Heterogeneous Causal Effects of Multivalued Treatments Under Limited Overlap," Papers 2301.05703, arXiv.org, revised Jan 2023.
    23. Wang, Xiqian & Bian, Yong & Zhang, Qin, 2023. "The effect of cooking fuel choice on the elderly’s well-being: Evidence from two non-parametric methods," Energy Economics, Elsevier, vol. 125(C).
    24. Elliott Ash & Daniel L. Chen & Sergio Galletta, 2022. "Measuring Judicial Sentiment: Methods and Application to US Circuit Courts," Economica, London School of Economics and Political Science, vol. 89(354), pages 362-376, April.
    25. Pradhi Aggarwal & Alec Brandon & Ariel Goldszmidt & Justin Holz & John List & Ian Muir & Gregory Sun & Thomas Yu, 2022. "High-frequency location data shows that race affects the likelihood of being stopped and fined for speeding," Natural Field Experiments 00764, The Field Experiments Website.
    26. Songul Cinaroglu, 2020. "Modelling unbalanced catastrophic health expenditure data by using machine‐learning methods," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 27(4), pages 168-181, October.
    27. Matt Goldman & Brian Quistorff, 2018. "Pricing Engine: Estimating Causal Impacts in Real World Business Settings," Papers 1806.03285, arXiv.org, revised Jun 2018.
    28. Nikolaos Ignatiadis & Wolfgang Huber, 2021. "Covariate powered cross‐weighted multiple testing," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(4), pages 720-751, September.
    29. Miruna Oprescu & Vasilis Syrgkanis & Zhiwei Steven Wu, 2018. "Orthogonal Random Forest for Causal Inference," Papers 1806.03467, arXiv.org, revised Sep 2019.
    30. Gareth Liu-Evans & Shalini Mitra, 2023. "Formal sector enforcement and welfare," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 30(3), pages 706-728, June.
    31. Jiaming Mao & Jingzhi Xu, 2020. "Ensemble Learning with Statistical and Structural Models," Papers 2006.05308, arXiv.org.
    32. Aristide Houndetoungan & Abdoul Haki Maoude, 2024. "Inference for Two-Stage Extremum Estimators," THEMA Working Papers 2024-01, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    33. Fernando Delbianco & Fernando Tohmé, 2023. "Individualized Conformal," Working Papers 247, Red Nacional de Investigadores en Economía (RedNIE).
    34. Sander Gerritsen & Mark Kattenberg & Sonny Kuijpers, 2019. "The impact of age at arrival on education and mental health," CPB Discussion Paper 389, CPB Netherlands Bureau for Economic Policy Analysis.
    35. Fukuyama, Hirofumi & Tsionas, Mike & Tan, Yong, 2023. "Dynamic network data envelopment analysis with a sequential structure and behavioural-causal analysis: Application to the Chinese banking industry," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1360-1373.
    36. Mark Kattenberg & Bas Scheer & Jurre Thiel, 2023. "Causal forests with fixed effects for treatment effect heterogeneity in difference-in-differences," CPB Discussion Paper 452, CPB Netherlands Bureau for Economic Policy Analysis.
    37. Jonas Metzger, 2022. "Adversarial Estimators," Papers 2204.10495, arXiv.org, revised Jun 2022.
    38. Yuya Sasaki & Takuya Ura & Yichong Zhang, 2022. "Unconditional quantile regression with high‐dimensional data," Quantitative Economics, Econometric Society, vol. 13(3), pages 955-978, July.
    39. Guido W. Imbens, 2020. "Potential Outcome and Directed Acyclic Graph Approaches to Causality: Relevance for Empirical Practice in Economics," Journal of Economic Literature, American Economic Association, vol. 58(4), pages 1129-1179, December.
    40. Alexander Buchholz & Vito Bellini & Giuseppe Di Benedetto & Yannik Stein & Matteo Ruffini & Fabian Moerchen, 2022. "Fair Effect Attribution in Parallel Online Experiments," Papers 2210.08338, arXiv.org.
    41. Andreas Fuster & Paul Goldsmith‐Pinkham & Tarun Ramadorai & Ansgar Walther, 2022. "Predictably Unequal? The Effects of Machine Learning on Credit Markets," Journal of Finance, American Finance Association, vol. 77(1), pages 5-47, February.
    42. Duncan Simester & Artem Timoshenko & Spyros I. Zoumpoulis, 2020. "Targeting Prospective Customers: Robustness of Machine-Learning Methods to Typical Data Challenges," Management Science, INFORMS, vol. 66(6), pages 2495-2522, June.
    43. Heigle, Julia & Pfeiffer, Friedhelm, 2019. "An analysis of selected labor market outcomes of college dropouts in Germany: A machine learning estimation approach. Research report," ZEW Expertises, ZEW - Leibniz Centre for European Economic Research, number 222378.
    44. Belloni, Alexandre & Hansen, Christian & Newey, Whitney, 2022. "High-dimensional linear models with many endogenous variables," Journal of Econometrics, Elsevier, vol. 228(1), pages 4-26.
    45. Sven Klaassen & Jannis Kück & Martin Spindler & Victor Chernozhukov, 2019. "Uniform inference in high-dimensional Gaussian graphical models," CeMMAP working papers CWP29/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    46. Ashkan Ertefaie & Nima S. Hejazi & Mark J. van der Laan, 2023. "Nonparametric inverse‐probability‐weighted estimators based on the highly adaptive lasso," Biometrics, The International Biometric Society, vol. 79(2), pages 1029-1041, June.
    47. Victor Chernozhukov & Carlos Cinelli & Whitney Newey & Amit Sharma & Vasilis Syrgkanis, 2022. "Long Story Short: Omitted Variable Bias in Causal Machine Learning," NBER Working Papers 30302, National Bureau of Economic Research, Inc.
    48. Jushan Bai & Sung Hoon Choi & Yuan Liao, 2019. "Feasible Generalized Least Squares for Panel Data with Cross-sectional and Serial Correlations," Papers 1910.09004, arXiv.org, revised Aug 2020.
    49. Esfandiar Maasoumi & Jianqiu Wang & Zhuo Wang & Ke Wu, 2024. "Identifying factors via automatic debiased machine learning," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(3), pages 438-461, April.
    50. Retsef Levi & Elisabeth Paulson & Georgia Perakis & Emily Zhang, 2024. "Heterogeneous Treatment Effects in Panel Data," Papers 2406.05633, arXiv.org.
    51. Betts, Alexander & Flinder Stierna, Maria & Omata, Naohiko & Sterck, Olivier, 2023. "Refugees welcome? Inter-group interaction and host community attitude formation," World Development, Elsevier, vol. 161(C).
    52. Abadie, Alberto & Gu, Jiaying & Shen, Shu, 2024. "Instrumental variable estimation with first-stage heterogeneity," Journal of Econometrics, Elsevier, vol. 240(2).
    53. Ke Sun & Linglong Kong & Hongtu Zhu & Chengchun Shi, 2024. "Optimal Treatment Allocation Strategies for A/B Testing in Partially Observable Time Series Experiments," Papers 2408.05342, arXiv.org, revised Oct 2024.
    54. Whitney K. Newey & James M. Robins, 2017. "Cross-fitting and fast remainder rates for semiparametric estimation," CeMMAP working papers 41/17, Institute for Fiscal Studies.
    55. Xing, Lu & Han, DongHao & Hui, Xie, 2023. "The impact of carbon policy on corporate risk-taking with a double/debiased machine learning based difference-in-differences approach," Finance Research Letters, Elsevier, vol. 58(PC).
    56. Delprato, Marcos & Frola, Alessia & Antequera, Germán, 2022. "Indigenous and non-Indigenous proficiency gaps for out-of-school and in-school populations: A machine learning approach," International Journal of Educational Development, Elsevier, vol. 93(C).
    57. Anna Baiardi & Andrea A. Naghi, 2021. "The Value Added of Machine Learning to Causal Inference: Evidence from Revisited Studies," Tinbergen Institute Discussion Papers 21-001/V, Tinbergen Institute.
    58. Aristide Houndetoungan & Abdoul Haki Maoude, 2024. "Inference for Two-Stage Extremum Estimators," Papers 2402.05030, arXiv.org, revised Nov 2024.
    59. Oliver Hines & Stijn Vansteelandt & Karla Diaz-Ordaz, 2021. "Robust Inference for Mediated Effects in Partially Linear Models," Psychometrika, Springer;The Psychometric Society, vol. 86(2), pages 595-618, June.
    60. Ziwei Mei & Zhentao Shi, 2022. "On LASSO for High Dimensional Predictive Regression," Papers 2212.07052, arXiv.org, revised Jan 2024.
    61. Vira Semenova, 2017. "Debiased Machine Learning of Set-Identified Linear Models," Papers 1712.10024, arXiv.org, revised Dec 2022.
    62. Amit Sharma & Emre Kiciman, 2020. "DoWhy: An End-to-End Library for Causal Inference," Papers 2011.04216, arXiv.org.
    63. Feng, Sanying & Kong, Kaidi & Kong, Yinfei & Li, Gaorong & Wang, Zhaoliang, 2022. "Statistical inference of heterogeneous treatment effect based on single-index model," Computational Statistics & Data Analysis, Elsevier, vol. 175(C).
    64. Victor Chernozhukov & Whitney Newey & Vira Semenova, 2019. "Welfare Analysis in Dynamic Models," Papers 1908.09173, arXiv.org, revised Nov 2024.
    65. Yong Bian & Xiqian Wang & Qin Zhang, 2023. "How Does China's Household Portfolio Selection Vary with Financial Inclusion?," Papers 2311.01206, arXiv.org.
    66. Betts,Alexander Milton Stedman & Stierna,Maria Flinder & Omata,Naohiko & Sterck,Olivier Christian Brigitte, 2022. "Social Cohesion and Refugee-Host Interactions : Evidence from East Africa," Policy Research Working Paper Series 9917, The World Bank.
    67. Ricardo P. Masini & Marcelo C. Medeiros & Eduardo F. Mendes, 2020. "Machine Learning Advances for Time Series Forecasting," Papers 2012.12802, arXiv.org, revised Apr 2021.
    68. Jules Gazeaud & Nausheen Khan & Eric Mvukiyehe & Olivier Sterck, 2023. "With or without him? Experimental evidence on cash grants and gender-sensitive trainings in Tunisia," Post-Print hal-04364356, HAL.
    69. Sven Klaassen & Jannis Kueck & Martin Spindler, 2017. "Transformation Models in High-Dimensions," Papers 1712.07364, arXiv.org.
    70. Helmut Wasserbacher & Martin Spindler, 2022. "Machine learning for financial forecasting, planning and analysis: recent developments and pitfalls," Digital Finance, Springer, vol. 4(1), pages 63-88, March.
    71. Jikai Jin & Vasilis Syrgkanis, 2024. "Structure-agnostic Optimality of Doubly Robust Learning for Treatment Effect Estimation," Papers 2402.14264, arXiv.org, revised Mar 2024.
    72. Andrew Bennett & Nathan Kallus & Xiaojie Mao & Whitney Newey & Vasilis Syrgkanis & Masatoshi Uehara, 2023. "Source Condition Double Robust Inference on Functionals of Inverse Problems," Papers 2307.13793, arXiv.org.
    73. Vira Semenova, 2018. "Machine Learning for Dynamic Discrete Choice," Papers 1808.02569, arXiv.org, revised Nov 2018.
    74. Carl Bonander & Mikael Svensson, 2021. "Using causal forests to assess heterogeneity in cost‐effectiveness analysis," Health Economics, John Wiley & Sons, Ltd., vol. 30(8), pages 1818-1832, August.
    75. Maria Cuellar & Edward H. Kennedy, 2020. "A non‐parametric projection‐based estimator for the probability of causation, with application to water sanitation in Kenya," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(4), pages 1793-1818, October.
    76. Paolo Libenzio Brignoli & Alessandro Varacca & Cornelis Gardebroek & Paolo Sckokai, 2024. "Machine learning to predict grains futures prices," Agricultural Economics, International Association of Agricultural Economists, vol. 55(3), pages 479-497, May.
    77. Su, Liangjun & Ura, Takuya & Zhang, Yichong, 2017. "Non-separable Models with High-dimensional Data," Economics and Statistics Working Papers 15-2017, Singapore Management University, School of Economics.
    78. Andres Algaba & David Ardia & Keven Bluteau & Samuel Borms & Kris Boudt, 2020. "Econometrics Meets Sentiment: An Overview Of Methodology And Applications," Journal of Economic Surveys, Wiley Blackwell, vol. 34(3), pages 512-547, July.
    79. Anna Baiardi & Andrea A Naghi, 2024. "The value added of machine learning to causal inference: evidence from revisited studies," The Econometrics Journal, Royal Economic Society, vol. 27(2), pages 213-234.
    80. Madadkhani, Shiva & Ikonnikova, Svetlana, 2024. "Toward high-resolution projection of electricity prices: A machine learning approach to quantifying the effects of high fuel and CO2 prices," Energy Economics, Elsevier, vol. 129(C).
    81. Whitney K. Newey & James M. Robins, 2017. "Cross-fitting and fast remainder rates for semiparametric estimation," CeMMAP working papers CWP41/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    82. Julia Hatamyar & Noemi Kreif, 2023. "Policy Learning with Rare Outcomes," Papers 2302.05260, arXiv.org, revised Oct 2023.
    83. Heiler, Phillip & Kazak, Ekaterina, 2021. "Valid inference for treatment effect parameters under irregular identification and many extreme propensity scores," Journal of Econometrics, Elsevier, vol. 222(2), pages 1083-1108.
    84. Jiaming Mao & Zhesheng Zheng, 2020. "Structural Regularization," Papers 2004.12601, arXiv.org, revised Jun 2020.
    85. Mochen Yang & Edward McFowland & Gordon Burtch & Gediminas Adomavicius, 2022. "Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem," INFORMS Joural on Data Science, INFORMS, vol. 1(2), pages 138-155, October.
    86. Dmitry Arkhangelsky & Guido Imbens, 2023. "Causal Models for Longitudinal and Panel Data: A Survey," Papers 2311.15458, arXiv.org, revised Jun 2024.
    87. Andrew Bennett & Nathan Kallus & Xiaojie Mao & Whitney Newey & Vasilis Syrgkanis & Masatoshi Uehara, 2022. "Inference on Strongly Identified Functionals of Weakly Identified Functions," Papers 2208.08291, arXiv.org, revised Jun 2023.
    88. Max Cytrynbaum, 2021. "Optimal Stratification of Survey Experiments," Papers 2111.08157, arXiv.org, revised Aug 2023.
    89. Dongcheng Zhang & Kunpeng Zhang, 2020. "Weighting-Based Treatment Effect Estimation via Distribution Learning," Papers 2012.13805, arXiv.org, revised May 2023.
    90. Stephan Martin, 2022. "Estimation of Conditional Random Coefficient Models using Machine Learning Techniques," Papers 2201.08366, arXiv.org.
    91. Falco J. Bargagli Stoffi & Kenneth De Beckker & Joana E. Maldonado & Kristof De Witte, 2021. "Assessing Sensitivity of Machine Learning Predictions.A Novel Toolbox with an Application to Financial Literacy," Papers 2102.04382, arXiv.org.
    92. Guber, Raphael, 2018. "Instrument Validity Tests with Causal Trees: With an Application to the Same-sex Instrument," MEA discussion paper series 201805, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
    93. Phillip Heiler, 2020. "Efficient Covariate Balancing for the Local Average Treatment Effect," Papers 2007.04346, arXiv.org.
    94. Johannes Jakubik & Stefan Feuerriegel, 2022. "Data‐driven allocation of development aid toward sustainable development goals: Evidence from HIV/AIDS," Production and Operations Management, Production and Operations Management Society, vol. 31(6), pages 2739-2756, June.

  11. Alexandre Belloni & Victor Chernozhukov & Christian Hansen & Damian Kozbur, 2016. "Inference in High-Dimensional Panel Models With an Application to Gun Control," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 590-605, October.
    See citations under working paper version above.
  12. Bester, C. Alan & Hansen, Christian B., 2016. "Grouped effects estimators in fixed effects models," Journal of Econometrics, Elsevier, vol. 190(1), pages 197-208.

    Cited by:

    1. Nibbering, D. & Paap, R., 2019. "Panel Forecasting with Asymmetric Grouping," Econometric Institute Research Papers EI-2019-30, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Malmendier, Ulrike M. & Pezone, Vincenzo & Zheng, Hui, 2020. "Managerial Duties and Managerial Biases," CEPR Discussion Papers 14929, C.E.P.R. Discussion Papers.
    3. Levent Kutlu & Robin C. Sickles & Mike G. Tsionas & Emmanuel Mamatzakis, 2022. "Heterogeneous decision-making and market power: an application to Eurozone banks," Empirical Economics, Springer, vol. 63(6), pages 3061-3092, December.
    4. Yann Bramoull'e & Kenan Huremovi'c, 2017. "Promotion through Connections: Favors or Information?," Papers 1708.07723, arXiv.org, revised May 2024.
    5. Parlasca, Martin C. & Mußhoff, Oliver & Qaim, Matin, 2018. "How mobile phones can improve nutrition among pastoral communities: Panel data evidence from Northern Kenya," GlobalFood Discussion Papers 274651, Georg-August-Universitaet Goettingen, GlobalFood, Department of Agricultural Economics and Rural Development.
    6. Santiago Pereda-Fernández, 2021. "Copula-Based Random Effects Models for Clustered Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(2), pages 575-588, March.
    7. Liu, Ruiqi & Shang, Zuofeng & Zhang, Yonghui & Zhou, Qiankun, 2020. "Identification and estimation in panel models with overspecified number of groups," Journal of Econometrics, Elsevier, vol. 215(2), pages 574-590.
    8. Jiaying Gu & Stanislav Volgushev, 2018. "Panel Data Quantile Regression with Grouped Fixed Effects," Papers 1801.05041, arXiv.org, revised Aug 2018.
    9. Okui, Ryo & Wang, Wendun, 2021. "Heterogeneous structural breaks in panel data models," Journal of Econometrics, Elsevier, vol. 220(2), pages 447-473.
    10. Claudia Pigini & Alessandro Pionati & Francesco Valentini, 2023. "Specification testing with grouped fixed effects," Papers 2310.01950, arXiv.org.
    11. Arsham Reisinezhad, 2018. "Economic Growth and Income Inequality in Resource Countries: Theory and Evidence," Working Papers halshs-01707976, HAL.
    12. Didier Nibbering & Richard Paap, 2024. "Forecasting carbon emissions using asymmetric grouping," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 2228-2256, September.
    13. Boyuan Zhang, 2020. "Forecasting with Bayesian Grouped Random Effects in Panel Data," Papers 2007.02435, arXiv.org, revised Oct 2020.
    14. Martin C. Parlasca & Oliver Mußhoff & Matin Qaim, 2020. "Can mobile phones improve nutrition among pastoral communities? Panel data evidence from Northern Kenya," Agricultural Economics, International Association of Agricultural Economists, vol. 51(3), pages 475-488, May.
    15. Wang, Wuyi & Su, Liangjun, 2021. "Identifying latent group structures in nonlinear panels," Journal of Econometrics, Elsevier, vol. 220(2), pages 272-295.
    16. Bennedsen, Mikkel & Hillebrand, Eric & Jensen, Sebastian, 2023. "A neural network approach to the environmental Kuznets curve," Energy Economics, Elsevier, vol. 126(C).
    17. Su, Liangjun & Ju, Gaosheng, 2018. "Identifying latent grouped patterns in panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 206(2), pages 554-573.
    18. Jorge A. Rivero, 2023. "Unobserved Grouped Heteroskedasticity and Fixed Effects," Papers 2310.14068, arXiv.org, revised Oct 2023.
    19. Zhangqi Zhong & Yiqin Hu & Lei Jiang, 2019. "Impact of Climate Change on Agricultural Total Factor Productivity Based on Spatial Panel Data Model: Evidence from China," Sustainability, MDPI, vol. 11(6), pages 1-17, March.
    20. Mehrabani, Ali, 2023. "Estimation and identification of latent group structures in panel data," Journal of Econometrics, Elsevier, vol. 235(2), pages 1464-1482.
    21. Sophie Therese Schneider & Konstantin M. Wacker, 2022. "Explaining the global landscape of foreign direct investment: Knowledge capital, gravity, and the role of culture and institutions," The World Economy, Wiley Blackwell, vol. 45(10), pages 3080-3108, October.
    22. Chu, Ba, 2017. "Composite Quasi-Maximum Likelihood Estimation of Dynamic Panels with Group-Specific Heterogeneity and Spatially Dependent Errors," MPRA Paper 79709, University Library of Munich, Germany.
    23. Thomas Wiemann, 2023. "Optimal Categorical Instrumental Variables," Papers 2311.17021, arXiv.org, revised May 2024.
    24. Platoni, Silvia & Barbieri, Laura & Moro, Daniele & Sckokai, Paolo, 2020. "Heteroscedastic stratified two-way EC models of single equations and SUR systems," Econometrics and Statistics, Elsevier, vol. 15(C), pages 46-66.
    25. Chihwa Kao & Min Seong Kim & Zhonghui Zhang, 2021. "Mahalanobis Metric Based Clustering for Fixed Effects Model," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(2), pages 493-506, November.
    26. Katerina Chrysikou & George Kapetanios, 2024. "Heterogeneous Grouping Structures in Panel Data," Papers 2407.19509, arXiv.org.
    27. Ogasawara, Kota, 2018. "Health and education during industrialization: Evidence from early twentieth century Japan," International Journal of Educational Development, Elsevier, vol. 61(C), pages 40-54.
    28. Oh, Dong Hwan & Patton, Andrew J., 2023. "Dynamic factor copula models with estimated cluster assignments," Journal of Econometrics, Elsevier, vol. 237(2).
    29. Alejandro Sanchez-Becerra, 2022. "The Network Propensity Score: Spillovers, Homophily, and Selection into Treatment," Papers 2209.14391, arXiv.org.
    30. Chenggang Wang & Danli Du & Tiansen Liu & Yue Zhu & Dongxue Yang & Yuan Huang & Fan Meng, 2024. "Impact of Green Technology Innovation on Green Economy: Evidence from China," Sustainability, MDPI, vol. 16(19), pages 1-23, October.
    31. Gu, Jiaying & Volgushev, Stanislav, 2019. "Panel data quantile regression with grouped fixed effects," Journal of Econometrics, Elsevier, vol. 213(1), pages 68-91.

  13. Bester, C. Alan & Conley, Timothy G. & Hansen, Christian B. & Vogelsang, Timothy J., 2016. "FIXED-b ASYMPTOTICS FOR SPATIALLY DEPENDENT ROBUST NONPARAMETRIC COVARIANCE MATRIX ESTIMATORS," Econometric Theory, Cambridge University Press, vol. 32(1), pages 154-186, February.

    Cited by:

    1. Gupta, A, 2015. "Autoregressive Spatial Spectral Estimates," Economics Discussion Papers 23825, University of Essex, Department of Economics.
    2. Hwang, Jungbin & Sun, Yixiao, 2018. "Should we go one step further? An accurate comparison of one-step and two-step procedures in a generalized method of moments framework," Journal of Econometrics, Elsevier, vol. 207(2), pages 381-405.
    3. Eyal Frank & Anant Sudarshan, 2024. "The Social Costs of Keystone Species Collapse: Evidence from the Decline of Vultures in India," American Economic Review, American Economic Association, vol. 114(10), pages 3007-3040, October.
    4. Abhimanyu Gupta & Javier Hidalgo, 2022. "Nonparametric prediction with spatial data," STICERD - Econometrics Paper Series 621, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    5. Xiaoqing Ye & Yixiao Sun, 2018. "Heteroskedasticity- and autocorrelation-robust F and t tests in Stata," Stata Journal, StataCorp LP, vol. 18(4), pages 951-980, December.
    6. Bartalotti, Otávio, 2018. "Regression Discontinuity and Heteroskedasticity Robust Standard Errors: Evidence from a Fixed-Bandwidth Approximation," ISU General Staff Papers 201802010800001586, Iowa State University, Department of Economics.
    7. Ulrich K. Muller & Mark W. Watson, 2021. "Spatial Correlation Robust Inference," Papers 2102.09353, arXiv.org.
    8. Timothy Conley & Sílvia Gonçalves & Min Seong Kim & Benoit Perron, 2022. "Bootstrap Inference Under Cross Sectional Dependence," Working papers 2022-14, University of Connecticut, Department of Economics.
    9. Min Seong Kim & Yixiao Sun & Jingjing Yang, 2015. "A Fixed-bandwidth View of the Pre-asymptotic Inference for Kernel Smoothing with Time Series Data," Working Papers 049, Toronto Metropolitan University, Department of Economics.
    10. Carolina Caetano & Gregorio Caetano & Hao Fe & Eric R. Nielsen, 2021. "A Dummy Test of Identification in Models with Bunching," Finance and Economics Discussion Series 2021-068, Board of Governors of the Federal Reserve System (U.S.).
    11. Ulrich K. Müller & Mark W. Watson, 2021. "Spatial Correlation Robust Inference," Working Papers 2021-61, Princeton University. Economics Department..
    12. J. Hidalgo & M. Schafgans, 2020. "Inference without smoothing for large panels with cross-sectional and temporal dependence," Papers 2006.14409, arXiv.org.
    13. Hwang, Jungbin & Sun, Yixiao, 2015. "Asymptotic F and t Tests in an Efficient GMM Setting," University of California at San Diego, Economics Working Paper Series qt1c62d8xf, Department of Economics, UC San Diego.
    14. David Powell, 2017. "Inference with Correlated Clusters," Working Papers WR-1137-1, RAND Corporation.
    15. Kaicheng Chen & Timothy J. Vogelsang, 2023. "Fixed-b Asymptotics for Panel Models with Two-Way Clustering," Papers 2309.08707, arXiv.org, revised Aug 2024.
    16. Hanan G. Jacoby, 2016. "Food Prices, Wages, And Welfare In Rural India," Economic Inquiry, Western Economic Association International, vol. 54(1), pages 159-176, January.
    17. Min Seong Kim, 2021. "Robust Inference for Diffusion-Index Forecasts with Cross-Sectionally Dependent Data," Working papers 2021-04, University of Connecticut, Department of Economics.
    18. Eduardo A. Souza-Rodrigues, 2016. "Nonparametric Regression with Common Shocks," Econometrics, MDPI, vol. 4(3), pages 1-17, September.

  14. Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Post-Selection and Post-Regularization Inference in Linear Models with Many Controls and Instruments," American Economic Review, American Economic Association, vol. 105(5), pages 486-490, May.
    See citations under working paper version above.
  15. Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Valid Post-Selection and Post-Regularization Inference: An Elementary, General Approach," Annual Review of Economics, Annual Reviews, vol. 7(1), pages 649-688, August.
    See citations under working paper version above.
  16. Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2014. "Inference on Treatment Effects after Selection among High-Dimensional Controlsâ€," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 81(2), pages 608-650.

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    1. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Christian Hansen & Kengo Kato, 2018. "High-Dimensional Econometrics and Regularized GMM," Papers 1806.01888, arXiv.org, revised Jun 2018.
    2. Alexandre Belloni & Victor Chernozhukov & Kengo Kato, 2019. "Valid Post-Selection Inference in High-Dimensional Approximately Sparse Quantile Regression Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 114(526), pages 749-758, April.
    3. Joel L. Horowitz & Ahnaf Rafi, 2023. "Bootstrap based asymptotic refinements for high-dimensional nonlinear models," Papers 2303.09680, arXiv.org, revised Feb 2024.
    4. TELLO, Mario D., 2024. "Inversión Pública En Infraestructura Y Crecimiento Regional En Perú, 2005-2020: Un Análisis Basado En Técnicas De Aprendizaje Automático Causal," Regional and Sectoral Economic Studies, Euro-American Association of Economic Development, vol. 24(2), pages 195-222.
    5. Kyle Colangelo & Ying-Ying Lee, 2019. "Double debiased machine learning nonparametric inference with continuous treatments," CeMMAP working papers CWP72/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Julián Caballero & Christian Upper, 2023. "What happens to EMEs when US yields go up?," BIS Working Papers 1081, Bank for International Settlements.
    7. Belloni, Alexandre & Chen, Mingli & Chernozhukov, Victor, 2016. "Quantile Graphical Models : Prediction and Conditional Independence with Applications to Financial Risk Management," Economic Research Papers 269321, University of Warwick - Department of Economics.
    8. Meles, Tensay Hadush & Lokina, Razack & Mtenga, Erica Louis & Tibanywana, Julieth Julius, 2023. "Stated preferences with survey consequentiality and outcome uncertainty: A split sample discrete choice experiment," EfD Discussion Paper 23-16, Environment for Development, University of Gothenburg.
    9. Pedro H. C. Sant'Anna & Jun B. Zhao, 2018. "Doubly Robust Difference-in-Differences Estimators," Papers 1812.01723, arXiv.org, revised May 2020.
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    11. Huber, Martin, 2019. "An introduction to flexible methods for policy evaluation," FSES Working Papers 504, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    12. Davies,Elwyn Adriaan Robin & Deffebach,Peter William & Iacovone,Leonardo & Mckenzie,David J., 2023. "Training Microentrepreneurs over Zoom : Experimental Evidence from Mexico," Policy Research Working Paper Series 10574, The World Bank.
    13. Victor Chernozhukov & Mert Demirer & Esther Duflo & Ivan Fernandez-Val, 2017. "Generic machine learning inference on heterogenous treatment effects in randomized experiments," CeMMAP working papers CWP61/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    14. Olaf J de Groot & Carlos Bozzoli & Anousheh Alamir & Tilman Brück, 2022. "The global economic burden of violent conflict," Journal of Peace Research, Peace Research Institute Oslo, vol. 59(2), pages 259-276, March.
    15. Franz Huber & Alan Ponce & Francesco Rentocchini & Thomas Wainwright, 2020. "The Wealth of (Open Data) Nations? Examining the interplay of open government data and country-level institutions for entrepreneurial activity at the country-level," SEEDS Working Papers 1120, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Nov 2020.
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    369. Eufrásio, Ana Beatriz R. & Eller, Rogéria A.G. & Oliveira, Alessandro V.M., 2021. "Are on-time performance statistics worthless? An empirical study of the flight scheduling strategies of Brazilian airlines," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
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    372. Netta Barak‐Corren & Yoav Kan‐Tor & Nelson Tebbe, 2022. "Examining the effects of antidiscrimination laws on children in the foster care and adoption systems," Journal of Empirical Legal Studies, John Wiley & Sons, vol. 19(4), pages 1003-1066, December.
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  17. Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2014. "High-Dimensional Methods and Inference on Structural and Treatment Effects," Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 29-50, Spring.
    See citations under working paper version above.
  18. Hansen, Christian & Kozbur, Damian, 2014. "Instrumental variables estimation with many weak instruments using regularized JIVE," Journal of Econometrics, Elsevier, vol. 182(2), pages 290-308.

    Cited by:

    1. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Christian Hansen & Kengo Kato, 2018. "High-Dimensional Econometrics and Regularized GMM," Papers 1806.01888, arXiv.org, revised Jun 2018.
    2. Cheng Hsiao & Qiankun Zhou, 2017. "JIVE for Panel Dynamic Simultaneous Equations Models," Departmental Working Papers 2017-10, Department of Economics, Louisiana State University.
    3. Eric Gautier & Christiern Rose, 2022. "Fast, Robust Inference for Linear Instrumental Variables Models using Self-Normalized Moments," Papers 2211.02249, arXiv.org, revised Nov 2022.
    4. Christian Hansen & Damian Kozbur & Sanjog Misra, 2016. "Targeted undersmoothing," ECON - Working Papers 282, Department of Economics - University of Zurich, revised Apr 2018.
    5. Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2019. "lassopack: Model selection and prediction with regularized regression in Stata," Papers 1901.05397, arXiv.org.
    6. Alexandre Belloni & Victor Chernozhukov & Christian Hansen & Damian Kozbur, 2014. "Inference in High Dimensional Panel Models with an Application to Gun Control," Papers 1411.6507, arXiv.org.
    7. Damian Kozbur, 2015. "Testing-Based Forward Model Selection," ECON - Working Papers 283, Department of Economics - University of Zurich, revised Apr 2018.
    8. Shi, Zhentao, 2016. "Econometric estimation with high-dimensional moment equalities," Journal of Econometrics, Elsevier, vol. 195(1), pages 104-119.
    9. Victor Chernozhukov & Christian Hansen & Martin Spindler, 2016. "Valid post-selection and post-regularization inference: An elementary, general approach," CeMMAP working papers CWP36/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Post-selection and post-regularization inference in linear models with many controls and instruments," CeMMAP working papers CWP02/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    11. Lonjezo Sithole, 2024. "A Locally Robust Semiparametric Approach to Examiner IV Designs," Papers 2404.19144, arXiv.org.
    12. Matsushita, Yukitoshi & Otsu, Taisuke, 2024. "A jackknife Lagrange multiplier test with many weak instruments," LSE Research Online Documents on Economics 116392, London School of Economics and Political Science, LSE Library.
    13. Hoang, Daniel & Wiegratz, Kevin, 2022. "Machine learning methods in finance: Recent applications and prospects," Working Paper Series in Economics 158, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
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    16. Anna Mikusheva & Liyang Sun, 2024. "Weak identification with many instruments," The Econometrics Journal, Royal Economic Society, vol. 27(2), pages -28.
    17. Qingliang Fan & Zijian Guo & Ziwei Mei, 2022. "A Heteroskedasticity-Robust Overidentifying Restriction Test with High-Dimensional Covariates," Papers 2205.00171, arXiv.org, revised May 2024.
    18. Helmut Farbmacher & Rebecca Groh & Michael Muhlegger & Gabriel Vollert, 2024. "Revisiting the Many Instruments Problem using Random Matrix Theory," Papers 2408.08580, arXiv.org.
    19. Sølvsten, Mikkel, 2020. "Robust estimation with many instruments," Journal of Econometrics, Elsevier, vol. 214(2), pages 495-512.
    20. Emmanuel Selorm Tsyawo, 2021. "Feasible IV Regression without Excluded Instruments," Papers 2103.09621, arXiv.org, revised Nov 2022.
    21. Guy Tchuente, 2016. "Estimation of social interaction models using regularization," Studies in Economics 1607, School of Economics, University of Kent.
    22. Joshua D. Angrist & Brigham Frandsen, 2022. "Machine Labor," Journal of Labor Economics, University of Chicago Press, vol. 40(S1), pages 97-140.
    23. Marine Carrasco & Guy Tchuente, 2015. "Efficient estimation with many weak instruments using regularization techniques," Studies in Economics 1517, School of Economics, University of Kent.
    24. Fan, Jianqing & Gong, Wenyan & Zhu, Ziwei, 2019. "Generalized high-dimensional trace regression via nuclear norm regularization," Journal of Econometrics, Elsevier, vol. 212(1), pages 177-202.
    25. Guy Tchuente, 2019. "Weak Identification and Estimation of Social Interaction Models," Papers 1902.06143, arXiv.org.
    26. Guy Tchuente & Marine Carrasco, 2013. "Regularized LIML for many instruments," CIRANO Working Papers 2013s-20, CIRANO.
    27. Abdul-Nasah Soale & Emmanuel Selorm Tsyawo, 2023. "Clustered Covariate Regression," Papers 2302.09255, arXiv.org, revised Jul 2023.
    28. Dakyung Seong, 2022. "Binary response model with many weak instruments," Papers 2201.04811, arXiv.org, revised Jun 2024.
    29. Alena Skolkova, 2023. "Model Averaging with Ridge Regularization," CERGE-EI Working Papers wp758, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
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    31. Dennis Lim & Wenjie Wang & Yichong Zhang, 2022. "A Conditional Linear Combination Test with Many Weak Instruments," Papers 2207.11137, arXiv.org, revised Apr 2023.
    32. Xuemei Fan & Ziyue Nan & Yuanhang Ma & Yingdan Zhang & Fei Han, 2021. "Research on the Spatio-Temporal Impacts of Environmental Factors on the Fresh Agricultural Product Supply Chain and the Spatial Differentiation Issue—An Empirical Research on 31 Chinese Provinces," IJERPH, MDPI, vol. 18(22), pages 1-26, November.
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    36. Callaway, Brantly & Karami, Sonia, 2023. "Treatment effects in interactive fixed effects models with a small number of time periods," Journal of Econometrics, Elsevier, vol. 233(1), pages 184-208.
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    38. Max-Sebastian Dov`i, 2021. "Inference on the New Keynesian Phillips Curve with Very Many Instrumental Variables," Papers 2101.09543, arXiv.org, revised Mar 2021.
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    41. Kiyotaka Nakashima & Masahiko Shibamoto & Koji Takahashi, 2017. "Risk-Taking Channel of Unconventional Monetary Policies in Bank Lending," Discussion Paper Series DP2017-24, Research Institute for Economics & Business Administration, Kobe University, revised Apr 2019.
    42. Alena Skolkova, 2023. "Instrumental Variable Estimation with Many Instruments Using Elastic-Net IV," CERGE-EI Working Papers wp759, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    43. Stephen Coussens & Jann Spiess, 2021. "Improving Inference from Simple Instruments through Compliance Estimation," Papers 2108.03726, arXiv.org.
    44. Bohacek, Radim & Myck, Michal, 2017. "Economic Consequences of Political Persecution," IZA Discussion Papers 11136, Institute of Labor Economics (IZA).
    45. Yiqi Lin & Frank Windmeijer & Xinyuan Song & Qingliang Fan, 2022. "On the instrumental variable estimation with many weak and invalid instruments," Papers 2207.03035, arXiv.org, revised Dec 2023.
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  19. V. Chernozhukov & C. Hansen, 2013. "Quantile Models with Endogeneity," Annual Review of Economics, Annual Reviews, vol. 5(1), pages 57-81, May.
    See citations under working paper version above.
  20. Timothy G. Conley & Christian B. Hansen & Peter E. Rossi, 2012. "Plausibly Exogenous," The Review of Economics and Statistics, MIT Press, vol. 94(1), pages 260-272, February.

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    6. Miyamoto, Wataru & Nguyen, Thuy Lan & Sheremirov, Viacheslav, 2019. "The effects of government spending on real exchange rates: Evidence from military spending panel data," Journal of International Economics, Elsevier, vol. 116(C), pages 144-157.
    7. Jumrani, Jaya, 2023. "How responsive are nutrients in India? Some recent evidence," Food Policy, Elsevier, vol. 114(C).
    8. Martin-Shields, Charles P. & Stojetz, Wolfgang, 2019. "Food security and conflict: Empirical challenges and future opportunities for research and policy making on food security and conflict," World Development, Elsevier, vol. 119(C), pages 150-164.
    9. Kalb, G. & van Ours, J.C., 2013. "Reading to Young Children : A Head-Start in Life?," Other publications TiSEM 70d95193-c085-4001-a660-8, Tilburg University, School of Economics and Management.
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    41. Wang, Ling, 2022. "The dynamics of money supply determination under asset purchase programs: A market-based versus a bank-based financial system," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
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    3. James G. MacKinnon, 2014. "Wild Cluster Bootstrap Confidence Intervals," Working Paper 1329, Economics Department, Queen's University.
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    8. Pesaran, M. Hashem & Tosetti, Elisa, 2007. "Large Panels with Common Factors and Spatial Correlations," IZA Discussion Papers 3032, Institute of Labor Economics (IZA).
    9. James G. MacKinnon & Morten Ørregaard Nielsen & Matthew D. Webb, 2023. "Leverage, influence, and the jackknife in clustered regression models: Reliable inference using summclust," Stata Journal, StataCorp LP, vol. 23(4), pages 942-982, December.
    10. Maurer, Stephan & Potlogea, Andrei, 2017. "Male-biased Demand Shocks and Women’s Labor Force Participation: Evidence from Large Oil Field Discoveries," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168143, Verein für Socialpolitik / German Economic Association.
    11. Javier Hidalgo & Marcia M Schafgans, 2015. "Inference and Testing Breaks in Large Dynamic Panels with Strong Cross Sectional Dependence," STICERD - Econometrics Paper Series /2015/583, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    12. James G. MacKinnon & Matthew D. Webb & Morten Ø. Nielsen, 2017. "Bootstrap And Asymptotic Inference With Multiway Clustering," Working Paper 1386, Economics Department, Queen's University.
    13. Sun, Yu & Yan, Karen X., 2019. "Inference on Difference-in-Differences average treatment effects: A fixed-b approach," Journal of Econometrics, Elsevier, vol. 211(2), pages 560-588.
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    Cited by:

    1. Victor Chernozhukov & Ivan Fernandez-Val & Stefan Hoderlein & Hajo Holzmann & Whitney K. Newey, 2013. "Nonparametric identification in panels using quantiles," CeMMAP working papers 66/13, Institute for Fiscal Studies.
    2. Botosaru, Irene & Muris, Chris & Pendakur, Krishna, 2023. "Identification of time-varying transformation models with fixed effects, with an application to unobserved heterogeneity in resource shares," Journal of Econometrics, Elsevier, vol. 232(2), pages 576-597.
    3. Ghanem, Dalia, 2017. "Testing identifying assumptions in nonseparable panel data models," Journal of Econometrics, Elsevier, vol. 197(2), pages 202-217.
    4. Hoderlein, Stefan & White, Halbert, 2012. "Nonparametric identification in nonseparable panel data models with generalized fixed effects," Journal of Econometrics, Elsevier, vol. 168(2), pages 300-314.
    5. Alexandre Belloni & Victor Chernozhukov & Christian Hansen & Damian Kozbur, 2014. "Inference in High Dimensional Panel Models with an Application to Gun Control," Papers 1411.6507, arXiv.org.
    6. Stefan Hoderlein & Yuya Sasaki, 2011. "On the role of time in nonseparable panel data models," CeMMAP working papers CWP15/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    7. Dalia Ghanem & Pedro H. C. Sant'Anna & Kaspar Wuthrich, 2022. "Selection and parallel trends," Papers 2203.09001, arXiv.org, revised Mar 2024.
    8. Louise Laage, 2020. "A Correlated Random Coefficient Panel Model with Time-Varying Endogeneity," Papers 2003.09367, arXiv.org, revised Nov 2022.
    9. Dalia Ghanem & Sarojini Hirshleifer & Karen Ortiz-Becerra, 2019. "Testing for Attrition Bias in Field Experiments," Working Papers 202010, University of California at Riverside, Department of Economics, revised Mar 2020.
    10. Cizek, P. & Lei, J., 2013. "Identification and Estimation of Nonseparable Single-Index Models in Panel Data with Correlated Random Effects," Other publications TiSEM 73e394eb-6799-4c79-af23-8, Tilburg University, School of Economics and Management.
    11. Irene Botosaru & Chris Muris, 2017. "Binarization for panel models with fixed effects," CeMMAP working papers CWP31/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    12. Chen, Songnian & Wang, Xi, 2018. "Semiparametric estimation of panel data models without monotonicity or separability," Journal of Econometrics, Elsevier, vol. 206(2), pages 515-530.
    13. Chen, Mingli, 2016. "Estimation of Nonlinear Panel Models with Multiple Unobserved Effects," The Warwick Economics Research Paper Series (TWERPS) 1120, University of Warwick, Department of Economics.
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    15. Laura Liu & Alexandre Poirier & Ji-Liang Shiu, 2021. "Identification and Estimation of Partial Effects in Nonlinear Semiparametric Panel Models," Papers 2105.12891, arXiv.org, revised Jul 2024.
    16. Shakeeb Khan & Maria Ponomareva & Elie Tamer, 2011. "Identification of Panel Data Models with Endogenous Censoring," Working Papers 11-07, Duke University, Department of Economics.
    17. Lu, Xun & White, Halbert, 2014. "Testing for separability in structural equations," Journal of Econometrics, Elsevier, vol. 182(1), pages 14-26.
    18. Brantly Callaway & Tong Li, 2019. "Quantile treatment effects in difference in differences models with panel data," Quantitative Economics, Econometric Society, vol. 10(4), pages 1579-1618, November.
    19. Juan Rodriguez-Poo & Alexandra Soberón, 2015. "Differencing techniques in semi-parametric panel data varying coefficient models with fixed effects: a Monte Carlo study," Computational Statistics, Springer, vol. 30(3), pages 885-906, September.
    20. Bryan S. Graham & James Powell, 2008. "Identification and Estimation of 'Irregular' Correlated Random Coefficient Models," NBER Working Papers 14469, National Bureau of Economic Research, Inc.
    21. Lu, Xun & White, Habert, 2015. "Testing For Treatment Dependence Of Effects Of A Continuous Treatment," Econometric Theory, Cambridge University Press, vol. 31(5), pages 1016-1053, October.
    22. Evgeniy M. Ozhegov & Daria Teterina, 2018. "The Ensemble Method For Censored Demand Prediction," HSE Working papers WP BRP 200/EC/2018, National Research University Higher School of Economics.
    23. Sadikoglu, Serhan, 2019. "Essays in econometric theory," Other publications TiSEM 99d83644-f9dc-49e3-a4e1-5, Tilburg University, School of Economics and Management.
    24. Cavit Pakel & Martin Weidner, 2023. "Bounds on Average Effects in Discrete Choice Panel Data Models," Papers 2309.09299, arXiv.org, revised May 2024.
    25. Bester, C. Alan & Hansen, Christian B., 2016. "Grouped effects estimators in fixed effects models," Journal of Econometrics, Elsevier, vol. 190(1), pages 197-208.
    26. Amaresh K Tiwari, 2021. "A Control Function Approach to Estimate Panel Data Binary Response Model," Papers 2102.12927, arXiv.org, revised Sep 2021.
    27. Irene Botosaru & Chris Muris, 2022. "Identification of time-varying counterfactual parameters in nonlinear panel models," Papers 2212.09193, arXiv.org, revised Nov 2023.

  25. Bester, C. Alan & Hansen, Christian, 2009. "A Penalty Function Approach to Bias Reduction in Nonlinear Panel Models with Fixed Effects," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(2), pages 131-148.

    Cited by:

    1. Geert Dhaene & Koen Jochmans, 2011. "Profile-score Adjustements for Nonlinearfixed-effect Models," SciencePo Working papers Main hal-01073733, HAL.
    2. Ivan Fernandez-Val & Martin Weidner, 2018. "Fixed effect estimation of large T panel data models," CeMMAP working papers CWP22/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Kunz, Johannes S. & Staub, Kevin E. & Winkelmann, Rainer, 2017. "Estimating Fixed Effects: Perfect Prediction and Bias in Binary Response Panel Models, with an Application to the Hospital Readmissions Reduction Program," IZA Discussion Papers 11182, Institute of Labor Economics (IZA).
    4. DHAENE, Geert & JOCHMANS, Koen, 2010. "Split-panel jackknife estimation of fixed-effect models," LIDAM Discussion Papers CORE 2010003, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. Sun, Yixiao & Kim, Min Seong, 2009. "k-step Bootstrap Bias Correction for Fixed Effects Estimators in Nonlinear Panel Models," University of California at San Diego, Economics Working Paper Series qt9gn6n5mr, Department of Economics, UC San Diego.
    6. Manuel Arellano & Stéphane Bonhomme, 2007. "Robust priors in nonlinear panel data models," CeMMAP working papers CWP07/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    7. Yongsung Chang & Sunoong Hwang, 2011. "Asymmetric Phase Shifts in the U.S. Industrial Production Cycles," RCER Working Papers 564, University of Rochester - Center for Economic Research (RCER).
    8. Albarrán, Pedro, 2015. "Estimation of Dynamic Nonlinear Random Effects Models with Unbalanced Panels," UC3M Working papers. Economics we1503, Universidad Carlos III de Madrid. Departamento de Economía.
    9. Laura Hospido, 2011. "Estimating non-linear models with multiple fixed effects:a computational note," Working Papers 1114, Banco de España.
    10. Maurice J.G. Bun & Martin A. Carree & Artūras Juodis, 2017. "On Maximum Likelihood Estimation of Dynamic Panel Data Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(4), pages 463-494, August.
    11. Hospido, Laura, 2010. "Modelling Heterogeneity and Dynamics in the Volatility of Individual Wages," IZA Discussion Papers 4712, Institute of Labor Economics (IZA).
    12. Jesus M. Carro & Alejandra Traferri, 2011. "State Dependence and Heterogeneity in Health Using a Bias Corrected Fixed Effects Estimator," Documentos de Trabajo 402, Instituto de Economia. Pontificia Universidad Católica de Chile..
    13. Johannes S. Kunz & Kevin E. Staub & Rainer Winkelmann, 2021. "Predicting individual effects in fixed effects panel probit models," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(3), pages 1109-1145, July.
    14. Geert Dhaene & Koen Jochmans, 2013. "Likelihood inference in an Autoregression with fixed effects," Working Papers hal-01070434, HAL.
    15. Martin Schumann & Thomas A. Severini & Gautam Tripathi, 2017. "Integrated Likelihood Based Inference for Nonlinear Panel Data Models with Unobserved Effects," DEM Discussion Paper Series 17-01, Department of Economics at the University of Luxembourg.
    16. Lee, Yoonseok, 2012. "Bias in dynamic panel models under time series misspecification," Journal of Econometrics, Elsevier, vol. 169(1), pages 54-60.
    17. Buchmueller, Thomas C. & Cheng, Terence C. & Pham, Ngoc T.A. & Staub, Kevin E., 2021. "The effect of income-based mandates on the demand for private hospital insurance and its dynamics," Journal of Health Economics, Elsevier, vol. 75(C).
    18. Nini, Greg & Smith, David C. & Sufi, Amir, 2009. "Creditor control rights and firm investment policy," Journal of Financial Economics, Elsevier, vol. 92(3), pages 400-420, June.
    19. Cizek, P. & Lei, J., 2013. "Identification and Estimation of Nonseparable Single-Index Models in Panel Data with Correlated Random Effects," Other publications TiSEM 73e394eb-6799-4c79-af23-8, Tilburg University, School of Economics and Management.
    20. Pakel, Cavit, 2019. "Bias reduction in nonlinear and dynamic panels in the presence of cross-section dependence," Journal of Econometrics, Elsevier, vol. 213(2), pages 459-492.
    21. Vasilis Sarafidis & Tom Wansbeek, 2020. "Celebrating 40 Years of Panel Data Analysis: Past, Present and Future," Monash Econometrics and Business Statistics Working Papers 6/20, Monash University, Department of Econometrics and Business Statistics.
    22. Dhaene, Geert & Sun, Yutao, 2021. "Second-order corrected likelihood for nonlinear panel models with fixed effects," Journal of Econometrics, Elsevier, vol. 220(2), pages 227-252.
    23. Patrick GAGLIARDINI & Christian GOURIEROUX, 2010. "Efficiency in Large Dynamic Panel Models with Common Factor," Working Papers 2010-05, Center for Research in Economics and Statistics.
    24. Amrei Stammann, 2023. "Debiased Fixed Effects Estimation of Binary Logit Models with Three-Dimensional Panel Data," Papers 2311.04073, arXiv.org.
    25. Carlos Lamarche & Thomas Parker, 2020. "Wild Bootstrap Inference for Penalized Quantile Regression for Longitudinal Data," Papers 2004.05127, arXiv.org, revised May 2022.
    26. Galvao, Antonio F. & Kato, Kengo, 2016. "Smoothed quantile regression for panel data," Journal of Econometrics, Elsevier, vol. 193(1), pages 92-112.
    27. Alexander Chudik & M. Hashem Pesaran & Jui‐Chung Yang, 2018. "Half‐panel jackknife fixed‐effects estimation of linear panels with weakly exogenous regressors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(6), pages 816-836, September.
    28. Xiaokun Wang & Kara M. Kockelman, 2009. "Baysian Inference For Ordered Response Data With A Dynamic Spatial‐Ordered Probit Model," Journal of Regional Science, Wiley Blackwell, vol. 49(5), pages 877-913, December.
    29. Vladimir Filimonov & Guilherme Demos & Didier Sornette, 2016. "Modified Profile Likelihood Inference and Interval Forecast of the Burst of Financial Bubbles," Swiss Finance Institute Research Paper Series 16-12, Swiss Finance Institute.
    30. Kunz, J.S.; & Staub, K.E.; & Winkelmann, R.;, 2018. "Predicting fixed effects in panel probit models," Health, Econometrics and Data Group (HEDG) Working Papers 18/23, HEDG, c/o Department of Economics, University of York.
    31. Trushin, Eshref & Ugur, Mehmet, 2018. "Ecosystem complexity, firm learning and survival: UK evidence on intra-industry age and size diversity as exit hazards," Greenwich Papers in Political Economy 19095, University of Greenwich, Greenwich Political Economy Research Centre.
    32. Lee, Yoonseok & Phillips, Peter C.B., 2015. "Model selection in the presence of incidental parameters," Journal of Econometrics, Elsevier, vol. 188(2), pages 474-489.
    33. Yoshitsugu Kitazawa, 2017. "DFEL-RTN, a set of TSP programs for root-N consistent estimations of dynamic fixed effects logit models," Discussion Papers 81, Kyushu Sangyo University, Faculty of Economics.
    34. Galvao Jr., Antonio F., 2011. "Quantile regression for dynamic panel data with fixed effects," Journal of Econometrics, Elsevier, vol. 164(1), pages 142-157, September.
    35. Antonio F. Galvao & Jiaying Gu & Stanislav Volgushev, 2018. "On the Unbiased Asymptotic Normality of Quantile Regression with Fixed Effects," Papers 1807.11863, arXiv.org, revised Feb 2020.
    36. Galvao Jr, A. F. & Montes-Rojas, G., 2009. "Instrumental variables quantile regression for panel data with measurement errors," Working Papers 09/06, Department of Economics, City University London.
    37. Guangjie Li, 2015. "Consistency in Estimation and Model Selection of Dynamic Panel Data Models with Fixed Effects," Econometrics, MDPI, vol. 3(3), pages 1-31, July.
    38. Bartolucci, Francesco & Pigini, Claudia & Valentini, Francesco, 2021. "Conditional inference and bias reduction for partial effects estimation of fixed-effects logit models," MPRA Paper 110031, University Library of Munich, Germany.
    39. Amaresh Tiwari & Franz Palm, 2011. "Nonlinear Panel Data Models with Expected a Posteriori Values of Correlated Random Effects," CREPP Working Papers 1113, Centre de Recherche en Economie Publique et de la Population (CREPP) (Research Center on Public and Population Economics) HEC-Management School, University of Liège.
    40. F. Bartolucci & R. Bellio & A. Salvan & N. Sartori, 2016. "Modified Profile Likelihood for Fixed-Effects Panel Data Models," Econometric Reviews, Taylor & Francis Journals, vol. 35(7), pages 1271-1289, August.
    41. Francesco Bartolucci & Francesco Valentini & Claudia Pigini, 2023. "Recursive Computation of the Conditional Probability Function of the Quadratic Exponential Model for Binary Panel Data," Computational Economics, Springer;Society for Computational Economics, vol. 61(2), pages 529-557, February.
    42. William Greene, 2014. "Models for ordered choices," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 15, pages 333-362, Edward Elgar Publishing.
    43. Bester, C. Alan & Hansen, Christian B., 2016. "Grouped effects estimators in fixed effects models," Journal of Econometrics, Elsevier, vol. 190(1), pages 197-208.
    44. Traferri, Alejandra, 2009. "Correcting the bias in the estimation of a dynamic ordered probit with fixed effects of self-assessed health status," UC3M Working papers. Economics we094021, Universidad Carlos III de Madrid. Departamento de Economía.
    45. Yoshitsugu Kitazawa, 2013. "Exploration of dynamic fixed effects logit models from a traditional angle," Discussion Papers 60, Kyushu Sangyo University, Faculty of Economics.

  26. Chernozhukov, Victor & Hansen, Christian & Jansson, Michael, 2009. "Admissible Invariant Similar Tests For Instrumental Variables Regression," Econometric Theory, Cambridge University Press, vol. 25(3), pages 806-818, June.

    Cited by:

    1. Antoine, Bertille & Lavergne, Pascal, 2023. "Identification-robust nonparametric inference in a linear IV model," Journal of Econometrics, Elsevier, vol. 235(1), pages 1-24.
    2. Donald W. K. Andrews & Patrik Guggenberger, 2015. "Identification- and Singularity-Robust Inference for Moment Condition," Cowles Foundation Discussion Papers 1978, Cowles Foundation for Research in Economics, Yale University.
    3. Régis Barnichon & Geert Mesters, 2019. "Identifying Modern Macro Equations with Old Shocks," Working Papers 1097, Barcelona School of Economics.
    4. Marmer, Vadim & Yu, Zhengfei, 2015. "Efficient Inference in the Classical IV Regression Model with Weak Identification: Asymptotic Power Against Arbitrarily Large Deviations from the Null Hypothesis," Microeconomics.ca working papers vadim_marmer-2015-17, Vancouver School of Economics, revised 02 Sep 2015.
    5. Bertille Antoine & Pascal Lavergne, 2020. "Identification-Robust Nonparametric Interference in a Linear IV Model," Discussion Papers dp20-03, Department of Economics, Simon Fraser University.
    6. Kleibergen, Frank, 2021. "Efficient size correct subset inference in homoskedastic linear instrumental variables regression," Journal of Econometrics, Elsevier, vol. 221(1), pages 78-96.
    7. Moreira, Humberto Ataíde & Moreira, Marcelo J., 2013. "Contributions to the Theory of Optimal Tests," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 747, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    8. Tetsuya Kaji, 2019. "Theory of Weak Identification in Semiparametric Models," Papers 1908.10478, arXiv.org, revised Aug 2020.
    9. Mills, Benjamin & Moreira, Marcelo J. & Vilela, Lucas P., 2014. "Tests based on t-statistics for IV regression with weak instruments," Journal of Econometrics, Elsevier, vol. 182(2), pages 351-363.
    10. Dong Jin Lee, 2020. "Optimal tests for parameter breaking process in conditional quantile models," The Japanese Economic Review, Springer, vol. 71(3), pages 479-510, July.
    11. Giuseppe Cavaliere & Zeng-Hua Lu & Anders Rahbek & Yuhong Yang, 2021. "MinP Score Tests with an Inequality Constrained Parameter Space," Papers 2107.06089, arXiv.org.
    12. Aragón, Edilean Kleber da Silva Bejarano & Galvão, Ana Beatriz, 2023. "Shock-based inference on the Phillips curve with the cost channel," Economic Modelling, Elsevier, vol. 126(C).

  27. Chernozhukov, Victor & Hansen, Christian & Jansson, Michael, 2009. "Finite sample inference for quantile regression models," Journal of Econometrics, Elsevier, vol. 152(2), pages 93-103, October.

    Cited by:

    1. Kaplan, David M. & Sun, Yixiao, 2012. "Smoothed Estimating Equations For Instrumental Variables Quantile Regression," University of California at San Diego, Economics Working Paper Series qt888657tp, Department of Economics, UC San Diego.
    2. Fan, Yanqin & Liu, Ruixuan, 2016. "A direct approach to inference in nonparametric and semiparametric quantile models," Journal of Econometrics, Elsevier, vol. 191(1), pages 196-216.
    3. Jun, Sung Jae, 2008. "Weak identification robust tests in an instrumental quantile model," Journal of Econometrics, Elsevier, vol. 144(1), pages 118-138, May.
    4. Luger, Richard, 2012. "Finite-sample bootstrap inference in GARCH models with heavy-tailed innovations," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3198-3211.
    5. David M. Kaplan & Matt Goldman, 2013. "IDEAL Quantile Inference via Interpolated Duals of Exact Analytic L-statistics," Working Papers 1315, Department of Economics, University of Missouri.
    6. Biying Yu & Junyi Zhang & Akimasa Fujiwara, 2016. "Who rebounds in the private transport sector? A comparative analysis between Beijing and Tokyo," Environment and Planning B, , vol. 43(3), pages 561-579, May.
    7. Qu, Zhongjun & Yoon, Jungmo, 2015. "Nonparametric estimation and inference on conditional quantile processes," Journal of Econometrics, Elsevier, vol. 185(1), pages 1-19.
    8. de Castro, Luciano & Galvao, Antonio F. & Kaplan, David M. & Liu, Xin, 2019. "Smoothed GMM for quantile models," Journal of Econometrics, Elsevier, vol. 213(1), pages 121-144.
    9. Su Liangjun & Tadao Hoshino, 2015. "Sieve Instrumental Variable Quantile Regression Estimation of Functional Coefficient Models," Working Papers 01-2015, Singapore Management University, School of Economics.
    10. David M. Kaplan, 2020. "sivqr: Smoothed IV quantile regression," Working Papers 2009, Department of Economics, University of Missouri.
    11. David M. Kaplan, 2022. "Smoothed instrumental variables quantile regression," Stata Journal, StataCorp LP, vol. 22(2), pages 379-403, June.
    12. Adam M. Rosen & Takuya Ura, 2019. "Finite Sample Inference for the Maximum Score Estimand," Papers 1903.01511, arXiv.org, revised May 2020.
    13. Matt Goldman & David M. Kaplan, 2018. "Non‐parametric inference on (conditional) quantile differences and interquantile ranges, using L‐statistics," Econometrics Journal, Royal Economic Society, vol. 21(2), pages 136-169, June.
    14. Hiroaki Kaido & Kaspar Wüthrich, 2018. "Decentralization estimators for instrumental variable quantile regression models," CeMMAP working papers CWP72/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    15. Wüthrich, Kaspar, 2020. "A Comparison of Two Quantile Models With Endogeneity," University of California at San Diego, Economics Working Paper Series qt0q43931f, Department of Economics, UC San Diego.
    16. Purevdorj Tuvaandorj, 2021. "Robust Permutation Tests in Linear Instrumental Variables Regression," Papers 2111.13774, arXiv.org, revised Jul 2024.
    17. Joel L. Horowitz, 2018. "Non-Asymptotic Inference in Instrumental Variables Estimation," Papers 1809.03600, arXiv.org.
    18. Victor Chernozhukov & Christian Hansen, 2013. "Quantile Models with Endogeneity," Papers 1303.7050, arXiv.org.
    19. Horowitz, Joel L., 2021. "Bounding the difference between true and nominal rejection probabilities in tests of hypotheses about instrumental variables models," Journal of Econometrics, Elsevier, vol. 222(2), pages 1057-1082.
    20. Kaspar W thrich, 2015. "Semiparametric estimation of quantile treatment effects with endogeneity," Diskussionsschriften dp1509, Universitaet Bern, Departement Volkswirtschaft.
    21. Javier Alejo & Antonio F. Galvao & Gabriel Montes-Rojas, 2021. "A first-stage representation for instrumental variables quantile regression," Papers 2102.01212, arXiv.org, revised Feb 2022.
    22. Laffers, Lukas, 2013. "Identification in Models with Discrete Variables," Discussion Paper Series in Economics 1/2013, Norwegian School of Economics, Department of Economics.
    23. David M. Kaplan, 2013. "IDEAL Inference on Conditional Quantiles via Interpolated Duals of Exact Analytic L-statistics," Working Papers 1316, Department of Economics, University of Missouri.
    24. Chung, Ray S.W. & So, Mike K.P. & Chu, Amanda M.Y. & Chan, Thomas W.C., 2020. "Regularization of Bayesian quasi-likelihoods constructed from complex estimating functions," Computational Statistics & Data Analysis, Elsevier, vol. 150(C).
    25. Christis Katsouris, 2023. "Quantile Time Series Regression Models Revisited," Papers 2308.06617, arXiv.org, revised Aug 2023.
    26. Joel L. Horowitz, 2017. "Non-asymptotic inference in instrumental variables estimation," CeMMAP working papers CWP46/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    27. Olivier Gossner & Karl H. Schlag, 2013. "Finite-sample exact tests for linear regressions with bounded dependent variables," Post-Print halshs-00879792, HAL.
    28. Victor Chernozhukov & Christian Hansen & Kaspar Wuthrich, 2020. "Instrumental Variable Quantile Regression," Papers 2009.00436, arXiv.org.
    29. Elise Coudin & Jean-Marie Dufour, 2010. "Finite and Large Sample Distribution-Free Inference in Median Regressions with Instrumental Variables," Working Papers 2010-56, Center for Research in Economics and Statistics.
    30. Wüthrich, Kaspar, 2019. "A closed-form estimator for quantile treatment effects with endogeneity," Journal of Econometrics, Elsevier, vol. 210(2), pages 219-235.
    31. Otsu, Taisuke, 2008. "Conditional empirical likelihood estimation and inference for quantile regression models," Journal of Econometrics, Elsevier, vol. 142(1), pages 508-538, January.
    32. Zhongjun Qu & Jungmo Yoon, 2015. "Uniform Inference on Quantile Effects under Sharp Regression Discontinuity Designs," Boston University - Department of Economics - Working Papers Series wp2015-009, Boston University - Department of Economics.
    33. David M. Kaplan & Matt Goldman, 2016. "Nonparametric inference on conditional quantile differences and linear combinations, using L-statistics," Working Papers 1620, Department of Economics, University of Missouri.
    34. Joel L. Horowitz, 2017. "Non-asymptotic inference in instrumental variables estimation," CeMMAP working papers 46/17, Institute for Fiscal Studies.
    35. Marina Dias & Demian Pouzo, 2021. "Inference for multi-valued heterogeneous treatment effects when the number of treated units is small," Papers 2105.10965, arXiv.org.
    36. Joel L. Horowitz, 2018. "Non-asymptotic inference in instrumental variables estimation," CeMMAP working papers CWP52/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    37. Isaiah Andrews & Anna Mikusheva, 2022. "Optimal Decision Rules for Weak GMM," Econometrica, Econometric Society, vol. 90(2), pages 715-748, March.

  28. Hansen, Christian & Hausman, Jerry & Newey, Whitney, 2008. "Estimation With Many Instrumental Variables," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 398-422.
    See citations under working paper version above.
  29. Chernozhukov, Victor & Hansen, Christian, 2008. "Instrumental variable quantile regression: A robust inference approach," Journal of Econometrics, Elsevier, vol. 142(1), pages 379-398, January.

    Cited by:

    1. Raghuram G. Rajan & Rodney Ramcharan, 2009. "Land and Credit: A Study of the Political Economy of Banking in the United States in the Early 20th Century," NBER Working Papers 15083, National Bureau of Economic Research, Inc.
    2. Xu, Xiu & Wang, Weining & Shin, Yongcheol, 2020. "Dynamic Spatial Network Quantile Autoregression," IRTG 1792 Discussion Papers 2020-024, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    3. Alexandre Belloni & Victor Chernozhukov & Kengo Kato, 2019. "Valid Post-Selection Inference in High-Dimensional Approximately Sparse Quantile Regression Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 114(526), pages 749-758, April.
    4. Luciano de Castro & Antonio F. Galvao & David M. Kaplan & Xin Liu, 2017. "Smoothed GMM for quantile models," Papers 1707.03436, arXiv.org, revised Feb 2018.
    5. Ozan Bakis & Nurhan Davutyan & Haluk Levent & Sezgin Polat, 2010. "External Returns to Higher Education in Turkey," Working Papers 517, Economic Research Forum, revised 04 Jan 2010.
    6. Erik Figueiredo & Luiz Renato Lima & Gianluca Orefice, 2016. "Migration and Regional Trade Agreements: A (New) Gravity Estimation," Review of International Economics, Wiley Blackwell, vol. 24(1), pages 99-125, February.
    7. Cizek, P., 2009. "Generalized Methods of Trimmed Moments," Other publications TiSEM 46607f30-95c0-430a-8ef9-2, Tilburg University, School of Economics and Management.
    8. Kaplan, David M. & Sun, Yixiao, 2012. "Smoothed Estimating Equations For Instrumental Variables Quantile Regression," University of California at San Diego, Economics Working Paper Series qt888657tp, Department of Economics, UC San Diego.
    9. Dambala Gelo & Steven F. Koch & Edwin Muchapondwah, 2013. "Do the Poor Benefit from Devolution Policies? Evidences from Quantile Treatment Effect Evaluation of Joint Forest Management," Working Papers 201388, University of Pretoria, Department of Economics.
    10. Muller, Christophe, 2018. "Heterogeneity and nonconstant effect in two-stage quantile regression," Econometrics and Statistics, Elsevier, vol. 8(C), pages 3-12.
    11. Barceló, Cristina & Villanueva, Ernesto, 2016. "The response of household wealth to the risk of job loss: Evidence from differences in severance payments," Labour Economics, Elsevier, vol. 39(C), pages 35-54.
    12. Alessia Matano & Paolo Naticchioni, 2017. "The Extent of Rent Sharing along the Wage Distribution," IREA Working Papers 201704, University of Barcelona, Research Institute of Applied Economics, revised Feb 2017.
    13. Nguyen, Quang Khai, 2022. "Audit committee structure, institutional quality, and bank stability: evidence from ASEAN countries," Finance Research Letters, Elsevier, vol. 46(PA).
    14. Ardizzi, Guerino, 2013. "Card versus cash: empirical evidence of the impact of payment card interchange fees on end users’ choice of payment methods," MPRA Paper 48088, University Library of Munich, Germany, revised 25 May 2013.
    15. Tae-Hwan Kim & Christophe Muller, 2017. "A Robust Test of Exogeneity Based on Quantile Regressions," AMSE Working Papers 1716, Aix-Marseille School of Economics, France.
    16. David Powell, 2013. "A New Framework for Estimation of Quantile Treatment Effects Nonseparable Disturbance in the Presence of Covariates," Working Papers WR-824-1, RAND Corporation.
    17. Jun, Sung Jae, 2008. "Weak identification robust tests in an instrumental quantile model," Journal of Econometrics, Elsevier, vol. 144(1), pages 118-138, May.
    18. Hammoudeh, Shawkat & Tiwari, Aviral Kumar & Abakah, Emmanuel Joel Aikins & Adeabah, David, 2023. "Global value chains in sub-Saharan Africa: The role of business regulations, policies and institutions," Emerging Markets Review, Elsevier, vol. 57(C).
    19. Alessie, R.J.M. & Angelini, V. & van Santen, P.C., 2012. "Pension wealth and household savings in Europe," Research Report 12012-EEF, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
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    1. Emma Hooper & Sanjay Peters & Patrick A. Pintus, 2018. "The Causal Effect of Infrastructure Investments on Income Inequality: Evidence from US States," AMSE Working Papers 1801, Aix-Marseille School of Economics, France, revised May 2018.
    2. Hack, Lukas & Istrefi, Klodiana & Meier, Matthias, 2023. "Identification of systematic monetary policy," Working Paper Series 2851, European Central Bank.
    3. Enikolopov, Ruben & Makarin, Alexey & Petrova, Maria, 2016. "Social Media and Protest Participation: Evidence from Russia," CEPR Discussion Papers 11254, C.E.P.R. Discussion Papers.
    4. Frank Windmeijer, 2018. "Testing Over- and Underidentification in Linear Models, with Applications to Dynamic Panel Data and Asset-Pricing Models," Bristol Economics Discussion Papers 18/696, School of Economics, University of Bristol, UK.
    5. Athias, Laure & Macina, Moudo, 2020. "The Legacy of the Slave Trade: Towards Identifying the Causal Impact of Mistrust in Medicine on Demand for Vaccination in Sub-Saharan Africa," MPRA Paper 102968, University Library of Munich, Germany.
    6. Julian Costas-Fernandez & Simon Lodato, 2023. "Distributional effects of immigration and imperfect labour markets," RF Berlin - CReAM Discussion Paper Series 2301, Rockwool Foundation Berlin (RF Berlin) - Centre for Research and Analysis of Migration (CReAM).
    7. Antoine, Bertille & Lavergne, Pascal, 2023. "Identification-robust nonparametric inference in a linear IV model," Journal of Econometrics, Elsevier, vol. 235(1), pages 1-24.
    8. So Yoon Ahn & Meiqing Ren, 2022. "Gender Wage Gap, Bargaining Power, and Charitable Giving of Households," Working Papers 2022-033, Human Capital and Economic Opportunity Working Group.
    9. Julia Fonseca, 2023. "Less Mainstream Credit, More Payday Borrowing? Evidence from Debt Collection Restrictions," Journal of Finance, American Finance Association, vol. 78(1), pages 63-103, February.
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    13. A. Colin Cameron & Douglas L. Miller, 2015. "A Practitioner’s Guide to Cluster-Robust Inference," Journal of Human Resources, University of Wisconsin Press, vol. 50(2), pages 317-372.
    14. Emran, M. Shahe & Shilpi, Forhad, 2014. "Agricultural Productivity, Hired Labor, Wages and Poverty: Evidence from Bangladesh," MPRA Paper 58099, University Library of Munich, Germany.
    15. Spring, Eva & Grossmann, Volker, 2013. "Does Bilateral Trust Affect International Movement of Goods and Labor?," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79956, Verein für Socialpolitik / German Economic Association.
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    44. Matilde Giaccherini & Joanna Kopinska & Alessandro Palma, 2019. "When Particulate Matter Strikes Cities: Social Disparities and Health Costs of Air Pollution," CEIS Research Paper 467, Tor Vergata University, CEIS, revised 04 Aug 2020.
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    49. Luca Citino & Andrea Linarello, 2022. "The impact of Chinese import competition on Italian manufacturing," Review of International Economics, Wiley Blackwell, vol. 30(3), pages 702-731, August.
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    67. Katrina Kosec & Jie Song, 2021. "The effects of income fluctuations on undernutrition and overnutrition across the lifecycle," Health Economics, John Wiley & Sons, Ltd., vol. 30(10), pages 2487-2509, September.
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    94. George L. Wehby & Jeffrey C. Murray & Eduardo E. Castilla & Jorge S. Lopez‐Camelo & Robert L. Ohsfeldt, 2009. "Quantile effects of prenatal care utilization on birth weight in Argentina," Health Economics, John Wiley & Sons, Ltd., vol. 18(11), pages 1307-1321, November.
    95. Hirschberg, Joe & Lye, Jenny, 2017. "Inverting the indirect—The ellipse and the boomerang: Visualizing the confidence intervals of the structural coefficient from two-stage least squares," Journal of Econometrics, Elsevier, vol. 199(2), pages 173-183.
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  32. Chernozhukov, Victor & Hansen, Christian & Jansson, Michael, 2007. "Inference approaches for instrumental variable quantile regression," Economics Letters, Elsevier, vol. 95(2), pages 272-277, May.

    Cited by:

    1. Andini, Corrado, 2017. "Tertiary Education for All and Wage Inequality: Policy Insights from Quantile Regression," IZA Policy Papers 132, Institute of Labor Economics (IZA).
    2. Le-Yu Chen & Sokbae (Simon) Lee, 2017. "Exact computation of GMM estimators for instrumental variable quantile regression models," CeMMAP working papers CWP52/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Bryan S. Graham & Jinyong Hahn & Alexandre Poirier & James L. Powell, 2016. "A quantile correlated random coefficients panel data model," CeMMAP working papers 34/16, Institute for Fiscal Studies.
    4. Domenico Depalo & Raffaella Giordano, 2011. "The public-private pay gap: a robust quantile approach," Giornale degli Economisti, GDE (Giornale degli Economisti e Annali di Economia), Bocconi University, vol. 70(1), pages 25-64, January.
    5. Jean-Jacques Forneron, 2019. "Detecting Identification Failure in Moment Condition Models," Papers 1907.13093, arXiv.org, revised Oct 2023.
    6. Le-Yu Chen & Yu-Min Yen, 2021. "Estimations of the Local Conditional Tail Average Treatment Effect," Papers 2109.08793, arXiv.org, revised May 2024.
    7. Wehby George L. & McCarthy Ann Marie & Castilla Eduardo & Murray Jeffrey C., 2011. "The Impact of Household Investments on Early Child Neurodevelopment and on Racial and Socioeconomic Developmental Gaps: Evidence from South America," Forum for Health Economics & Policy, De Gruyter, vol. 14(1), pages 1-60, December.
    8. Wang, Le, 2011. "How Does Education Affect the Earnings Distribution in Urban China?," IZA Discussion Papers 6173, Institute of Labor Economics (IZA).
    9. Wüthrich, Kaspar, 2020. "A Comparison of Two Quantile Models With Endogeneity," University of California at San Diego, Economics Working Paper Series qt0q43931f, Department of Economics, UC San Diego.
    10. Luis Gamboa & Mauricio Rodríguez & Andrés García, 2013. "Differences in motivations and academic achievement," Lecturas de Economía, Universidad de Antioquia, Departamento de Economía, issue 78, pages 9-44.
    11. Oliver Himmler, 2009. "The Effects of School Competition on Academic Achievement and Grading Standards," CESifo Working Paper Series 2676, CESifo.
    12. Kaspar W thrich, 2015. "Semiparametric estimation of quantile treatment effects with endogeneity," Diskussionsschriften dp1509, Universitaet Bern, Departement Volkswirtschaft.
    13. Javier Alejo & Antonio F. Galvao & Gabriel Montes-Rojas, 2021. "A first-stage representation for instrumental variables quantile regression," Papers 2102.01212, arXiv.org, revised Feb 2022.
    14. WenShwo Fang & Stephen M. Miller & Chih-Chuan Yeh, 2009. "Does a Threshold Inflation Rate Exist? Quantile Inferences for Inflation and Its Variability," Working Papers 0921, University of Nevada, Las Vegas , Department of Economics, revised Dec 2009.
    15. Santiago Budría, 2011. "Are Educational Mismatches Responsible for the ‘Inequality Increasing Effect’ of Education?," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 102(3), pages 409-437, July.
    16. Marilena Furno, 2020. "Returns to Education and Gender Wage Gap Across Quantiles in Italy," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 12(2), pages 145-169, June.
    17. Arabsheibani, Reza & Staneva, Anita, 2012. "Returns to Education in Russia: Where There Is Risky Sexual Behaviour There Is Also an Instrument," IZA Discussion Papers 6726, Institute of Labor Economics (IZA).
    18. Wüthrich, Kaspar, 2019. "A closed-form estimator for quantile treatment effects with endogeneity," Journal of Econometrics, Elsevier, vol. 210(2), pages 219-235.
    19. Wehby, George L. & Murray, Jeffrey C. & Wilcox, Allen & Lie, Rolv T., 2012. "Smoking and body weight: Evidence using genetic instruments," Economics & Human Biology, Elsevier, vol. 10(2), pages 113-126.
    20. George L. Wehby & Jeffrey C. Murray & Eduardo E. Castilla & Jorge S. Lopez‐Camelo & Robert L. Ohsfeldt, 2009. "Quantile effects of prenatal care utilization on birth weight in Argentina," Health Economics, John Wiley & Sons, Ltd., vol. 18(11), pages 1307-1321, November.
    21. Morra, Wayne & Hearn, Gail & Buck, Andrew J., 2009. "The market for bushmeat: Colobus Satanas on Bioko Island," Ecological Economics, Elsevier, vol. 68(10), pages 2619-2626, August.
    22. Andini, Corrado & Andini, Monica, 2015. "A Note on Unemployment Persistence and Quantile Parameter Heterogeneity," IZA Discussion Papers 8819, Institute of Labor Economics (IZA).

  33. Hansen, Christian B., 2007. "Asymptotic properties of a robust variance matrix estimator for panel data when T is large," Journal of Econometrics, Elsevier, vol. 141(2), pages 597-620, December.

    Cited by:

    1. Breinlich, Holger & Corradi, Valentina & Rocha, Nadia & Ruta, Michele & Santos Silva, JMC & Zylkin, Thomas, 2022. "Machine Learning in International Trade Research - Evaluating the Impact of Trade Agreements," CEPR Discussion Papers 17325, C.E.P.R. Discussion Papers.
    2. Christopher L. Foote, 2007. "Space and time in macroeconomic panel data: young workers and state-level unemployment revisited," Working Papers 07-10, Federal Reserve Bank of Boston.
    3. Martin Weidner & Thomas Zylkin, 2021. "Bias and consistency in three-way gravity models," CeMMAP working papers CWP11/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Nikolov, Plamen & Adelman, Alan, 2019. "Do Private Household Transfers to the Elderly Respond to Public Pension Benefits? Evidence from Rural China," IZA Discussion Papers 12532, Institute of Labor Economics (IZA).
    5. Ildefonso Mendez & Gema Zamarro, 2018. "The intergenerational transmission of noncognitive skills and their effect on education and employment outcomes," Journal of Population Economics, Springer;European Society for Population Economics, vol. 31(2), pages 521-560, April.
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    1. Jerry Hausman & Guido Kuersteiner, 2005. "Difference in Difference Meets Generalized Least Squares: Higher Order Properties of Hypotheses Tests," Boston University - Department of Economics - Working Papers Series WP2005-010, Boston University - Department of Economics.
    2. Christopher L. Foote, 2007. "Space and time in macroeconomic panel data: young workers and state-level unemployment revisited," Working Papers 07-10, Federal Reserve Bank of Boston.
    3. Mike Brewer & Thomas Crossley & Federico Zilio, 2019. "What do we really know about the employment effects of the UK’s National Minimum Wage?," IFS Working Papers W19/14, Institute for Fiscal Studies.
    4. Davide Dottori & Giacinto Micucci & Laura Sigalotti, 2022. "Trade debts and bank lending in years of crisis," Questioni di Economia e Finanza (Occasional Papers) 695, Bank of Italy, Economic Research and International Relations Area.
    5. Lin, Tsung-Xian & Gozgor, Giray & Rather, Kashif Nesar & Mahalik, Mantu Kumar & Lau, Chi Keung Marco, 2024. "How do natural resource rents and productive capacity affect carbon emissions? Evidence from developed and developing countries," Resources Policy, Elsevier, vol. 93(C).
    6. Ana Inés Balsa & Patricia Triunfo, 2015. "Aseguramiento público, provisión privada: Impacto en el acceso a servicios perinatales y en la salud del recién nacido," Documentos de Trabajo (working papers) 0415, Department of Economics - dECON.
    7. Elliott Fan, 2010. "Does Public Income Induce More Consumption?," The Economic Record, The Economic Society of Australia, vol. 86(272), pages 15-27, March.
    8. Abay, Kibrom A. & Kahsay, Goytom Abraha, 2018. "Long-term effects of alternative deterrence policies: Panel data evidence from traffic punishments in Denmark," Transportation Research Part A: Policy and Practice, Elsevier, vol. 113(C), pages 1-19.
    9. Even, William E. & Macpherson, David A., 2015. "The Affordable Care Act and the Growth of Involuntary Part-Time Employment," IZA Discussion Papers 9324, Institute of Labor Economics (IZA).
    10. Andrea Bernini, 2023. "The voice of radio in the battle for equal rights: Evidence from the U.S. South," Economics and Politics, Wiley Blackwell, vol. 35(1), pages 163-226, March.
    11. Stanislao Maldonado, 2018. "The Non-Monotonic Political Effects of Resource Booms," Working Papers 121, Peruvian Economic Association.
    12. J. Vernon Henderson & Adam Storeygard & David N. Weil, 2009. "Measuring Economic Growth from Outer Space," NBER Working Papers 15199, National Bureau of Economic Research, Inc.
    13. Mikosch, Heiner & Sturm, Jan-Egbert, 2012. "Has the EMU reduced wage growth and unemployment? Testing a model of trade union behavior," European Journal of Political Economy, Elsevier, vol. 28(1), pages 27-37.
    14. Simon Hartmann & Rok Spruk, 2023. "The impact of unilateral BIT terminations on FDI: Quasi-experimental evidence from India," The Review of International Organizations, Springer, vol. 18(2), pages 259-296, April.
    15. Zhiyuan Gao & Zhiling Guo & Qian Tang, 2022. "How do monetary incentives influence giving? An empirical investigation of matching subsidies on kiva," Information Systems and e-Business Management, Springer, vol. 20(2), pages 303-324, June.
    16. Yan Song & Douglas Barthold, 2018. "The effects of state‐level pharmacist regulations on generic substitution of prescription drugs," Health Economics, John Wiley & Sons, Ltd., vol. 27(11), pages 1717-1737, November.
    17. Christine Neill, 2015. "Rising student employment: the role of tuition fees," Education Economics, Taylor & Francis Journals, vol. 23(1), pages 101-121, February.
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    19. Li, Shanjun & Liu, Yanyan & Purevjav, Avralt-Od & Yang, Lin, 2019. "Does subway expansion improve air quality?," Journal of Environmental Economics and Management, Elsevier, vol. 96(C), pages 213-235.
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    21. Guy David & Philip Saynisch & Spencer Luster & Aaron Smith‐McLallen & Ravi Chawla, 2018. "The impact of patient‐centered medical homes on medication adherence?," Health Economics, John Wiley & Sons, Ltd., vol. 27(11), pages 1805-1820, November.
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    47. Li, Haizheng & Ma, Mingyu & Liu, Qinyi, 2022. "How the COVID-19 pandemic affects job sentiments of rural teachers," China Economic Review, Elsevier, vol. 72(C).
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    51. Peterson K. Ozili & Paul Terhemba Iorember, 2024. "Financial stability and sustainable development," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(3), pages 2620-2646, July.
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    55. Olarte Bacares, Carlos Augusto, 2013. "Impact of urban public transport enhancements on crime rate: a diff-diff analysis for the case of Transmilenio," MPRA Paper 53967, University Library of Munich, Germany, revised 10 Jan 2014.
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    72. Andrea Bernini, 2020. "The Voice of Radio in the Battle for Equal Rights: Evidence from the U.S. South," Oxford Economic and Social History Working Papers _181, University of Oxford, Department of Economics.
    73. David A. Matsa, 2007. "Does Malpractice Liability Keep the Doctor Away? Evidence from Tort Reform Damage Caps," The Journal of Legal Studies, University of Chicago Press, vol. 36(S2), pages 143-182, June.
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    81. Alexander Whalley, 2013. "Elected versus Appointed Policy Makers: Evidence from City Treasurers," Journal of Law and Economics, University of Chicago Press, vol. 56(1), pages 39-81.
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    85. John O'Trakoun, 2018. "The impact of trade on growth in the Great Lakes states," Economics Bulletin, AccessEcon, vol. 38(4), pages 1845-1856.
    86. Korkeamäki, Ossi, 2011. "The Finnish payroll tax cut experiment revisited," Working Papers 22, VATT Institute for Economic Research.
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    88. Armstrong, Christopher & Kepler, John D. & Samuels, Delphine & Taylor, Daniel, 2022. "Causality redux: The evolution of empirical methods in accounting research and the growth of quasi-experiments," Journal of Accounting and Economics, Elsevier, vol. 74(2).
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    91. Constantino Carreto & Simon Freyaldenhoven & Christian Hansen & Jorge Perez Perez & Jesse Shapiro, 2024. "xtevent: Estimation and Visualization in the Linear Panel Event-Study Design," Working Papers 24-15, Federal Reserve Bank of Philadelphia.
    92. Li, Haizheng & Liu, Qinyi & Ma, Mingyu, 2021. "How the COVID-19 Pandemic Affects Job Stress of Rural Teachers," IZA Discussion Papers 14366, Institute of Labor Economics (IZA).
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    1. Frölich, Markus & Melly, Blaise, 2008. "Unconditional Quantile Treatment Effects under Endogeneity," IZA Discussion Papers 3288, Institute of Labor Economics (IZA).
    2. Javier Alejo & Nicolás Badaracco, 2015. "Counterfactual Distributions in Bivariate Models—A Conditional Quantile Approach," Econometrics, MDPI, vol. 3(4), pages 1-14, November.
    3. Xu, Xiu & Wang, Weining & Shin, Yongcheol, 2020. "Dynamic Spatial Network Quantile Autoregression," IRTG 1792 Discussion Papers 2020-024, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    4. Alberto Díaz Dapena & Esteban Fernández Vázquez & Fernando Rubiera Morollón, 2015. "Estimating agglomeration economies in Spain: evidence from geographically disaggregated data," ERSA conference papers ersa15p285, European Regional Science Association.
    5. Andini, Corrado, 2017. "Tertiary Education for All and Wage Inequality: Policy Insights from Quantile Regression," IZA Policy Papers 132, Institute of Labor Economics (IZA).
    6. Victor Chernozhukov & Ivan Fernandez-Val & Whitney K. Newey & Sami Stouli & Francis Vella, 2017. "Semiparametric estimation of structural functions in nonseparable triangular models," CeMMAP working papers CWP48/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
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    415. Halbert White & Karim Chalak, 2008. "Identifying Structural Effects in Nonseparable Systems Using Covariates," Boston College Working Papers in Economics 734, Boston College Department of Economics.
    416. de Castro, Luciano & Galvao, Antonio F. & Montes-Rojas, Gabriel, 2020. "Quantile selection in non-linear GMM quantile models," Economics Letters, Elsevier, vol. 195(C).
    417. Juan Carlos Escanciano & Chuan Goh, 2010. "Specification Analysis of Structural Quantile Regression Models," Working Papers tecipa-415, University of Toronto, Department of Economics.
    418. Lamarche, Carlos, 2008. "Private school vouchers and student achievement: A fixed effects quantile regression evaluation," Labour Economics, Elsevier, vol. 15(4), pages 575-590, August.
    419. Gabriela Bezerra De Medeiros & Marcelo Savino Portugal & Edilean Kleber Da Silva Bejarano Aragon, 2016. "Endogeneity And Nonlinearities In Central Bank Of Brazil’S Reaction Functions: An Inverse Quantile Regression Approach," Anais do XLIII Encontro Nacional de Economia [Proceedings of the 43rd Brazilian Economics Meeting] 061, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    420. Shengfang Tang & Zongwu Cai & Ying Fang & Ming Lin, 2020. "A New Quantile Treatment Effect Model for Studying Smoking Effect on Birth Weight During Mother's Pregnancy," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202003, University of Kansas, Department of Economics, revised Feb 2020.
    421. Sung Jae Jun & Joris Pinkse & Haiqing Xu & Neşe Yıldız, 2016. "Multiple Discrete Endogenous Variables in Weakly-Separable Triangular Models," Econometrics, MDPI, vol. 4(1), pages 1-21, February.
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    425. Bang, James T. & Mitra, Aniruddha & Wunnava, Phanindra V., 2016. "Do remittances improve income inequality? An instrumental variable quantile analysis of the Kenyan case," Economic Modelling, Elsevier, vol. 58(C), pages 394-402.
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  38. Victor Chernozhukov & Christian Hansen, 2004. "The Effects of 401(K) Participation on the Wealth Distribution: An Instrumental Quantile Regression Analysis," The Review of Economics and Statistics, MIT Press, vol. 86(3), pages 735-751, August.

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    1. Kaspar Wuthrich & Ying Zhu, 2019. "Omitted variable bias of Lasso-based inference methods: A finite sample analysis," Papers 1903.08704, arXiv.org, revised Sep 2021.
    2. Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen, 2016. "Program evaluation and causal inference with high-dimensional data," CeMMAP working papers 13/16, Institute for Fiscal Studies.
    3. Le-Yu Chen & Sokbae (Simon) Lee, 2017. "Exact computation of GMM estimators for instrumental variable quantile regression models," CeMMAP working papers CWP52/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Wehby, George L. & Courtemanche, Charles J., 2012. "The heterogeneity of the cigarette price effect on body mass index," Journal of Health Economics, Elsevier, vol. 31(5), pages 719-729.
    5. Susumu Imai & Hajime Katayama & Kala Krishna, 2008. "A Quantile-based Test of Protection for Sale Model," NBER Working Papers 13900, National Bureau of Economic Research, Inc.
    6. Hafemann, Lucas, 2023. "A house prices at risk approach for the German residential real estate market," Technical Papers 07/2023, Deutsche Bundesbank.
    7. Barceló, Cristina & Villanueva, Ernesto, 2016. "The response of household wealth to the risk of job loss: Evidence from differences in severance payments," Labour Economics, Elsevier, vol. 39(C), pages 35-54.
    8. Daniel Jacob, 2021. "CATE meets ML," Digital Finance, Springer, vol. 3(2), pages 99-148, June.
    9. Blaise Melly und Kaspar W thrich, 2016. "Local quantile treatment effects," Diskussionsschriften dp1605, Universitaet Bern, Departement Volkswirtschaft.
    10. Besley, Tim & Surico, Paolo & Meads, Neil, 2010. "Risk Heterogeneity and Credit Supply: Evidence from the Mortgage Market," CEPR Discussion Papers 7633, C.E.P.R. Discussion Papers.
    11. Haiyang Lu & Ivan T. Kandilov, 2021. "Does Mobile Internet Use Affect the Subjective Well-being of Older Chinese Adults? An Instrumental Variable Quantile Analysis," Journal of Happiness Studies, Springer, vol. 22(7), pages 3137-3156, October.
    12. Leo Kaas & Georgi Kocharkov & Edgar Preugschat, 2019. "Wealth Inequality and Homeownership in Europe," Annals of Economics and Statistics, GENES, issue 136, pages 27-54.
    13. Corneo, Giacomo & Keese, Matthias & Schröder, Carsten, 2010. "The Effect of Saving Subsidies on Household Saving – Evidence from Germanys," Ruhr Economic Papers 170, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    14. Xiao, Zhijie & Xu, Lan, 2019. "What do mean impacts miss? Distributional effects of corporate diversification," Journal of Econometrics, Elsevier, vol. 213(1), pages 92-120.
    15. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney K. Newey & James Robins, 2017. "Double/debiased machine learning for treatment and structural parameters," CeMMAP working papers CWP28/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    16. Jau-er Chen & Chen-Wei Hsiang, 2019. "Causal Random Forests Model Using Instrumental Variable Quantile Regression," Econometrics, MDPI, vol. 7(4), pages 1-22, December.
    17. Hernæs, Øystein M., 2020. "Distributional effects of welfare reform for young adults: An unconditional quantile regression approach," Labour Economics, Elsevier, vol. 65(C).
    18. Suphi Sen & Herman R. J. Vollebergh, 2016. "The Effectiveness of Taxing Carbon Content of Energy Consumption," CESifo Working Paper Series 6003, CESifo.
    19. Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen, 2014. "Program evaluation with high-dimensional data," CeMMAP working papers CWP33/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    20. Jia-Young Michael Fu & Joel L. Horowitz & Matthias Parey, 2015. "Testing exogeneity in nonparametric instrumental variables identified by conditional quantile restrictions," CeMMAP working papers CWP68/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    21. Wenjie Wang & Yichong Zhang, 2021. "Wild Bootstrap for Instrumental Variables Regressions with Weak and Few Clusters," Papers 2108.13707, arXiv.org, revised Jan 2024.
    22. Jau-er Chen & Chien-Hsun Huang & Jia-Jyun Tien, 2019. "Debiased/Double Machine Learning for Instrumental Variable Quantile Regressions," Papers 1909.12592, arXiv.org, revised Feb 2021.
    23. Edward L. Glaeser & Sari Pekkala Kerr & William R. Kerr, 2013. "Entrepreneurship And Urban Growth:An Empirical Assessment With Historical Mines," Working Papers 13-15, Center for Economic Studies, U.S. Census Bureau.
    24. Rowena Crawford & Richard Disney & Carl Emmerson, 2012. "Do up-front tax incentives affect private pension saving in the United Kingdom?," IFS Working Papers W12/05, Institute for Fiscal Studies.
    25. Andr'es Ram'irez-Hassan & Raquel Vargas-Correa & Gustavo Garc'ia & Daniel Londo~no, 2020. "Optimal selection of the number of control units in kNN algorithm to estimate average treatment effects," Papers 2008.06564, arXiv.org.
    26. Chenhong Peng & Paul Siu Fai Yip & Yik Wa Law, 2019. "Intergenerational Earnings Mobility and Returns to Education in Hong Kong: A Developed Society with High Economic Inequality," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 143(1), pages 133-156, May.
    27. Chang, Huibin & Indra, Debarshi & Maiti, Abhradeep, 2023. "Metropolitan area heterogeneity and the impact of road infrastructure improvements on VMT," Transportation Research Part A: Policy and Practice, Elsevier, vol. 175(C).
    28. Wehby George L. & McCarthy Ann Marie & Castilla Eduardo & Murray Jeffrey C., 2011. "The Impact of Household Investments on Early Child Neurodevelopment and on Racial and Socioeconomic Developmental Gaps: Evidence from South America," Forum for Health Economics & Policy, De Gruyter, vol. 14(1), pages 1-60, December.
    29. Jarkko Harju, 2013. "Voluntary Pension Savings and Tax Incentives: Evidence from Finland," FinanzArchiv: Public Finance Analysis, Mohr Siebeck, Tübingen, vol. 69(1), pages 3-29, March.
    30. GINSBURGH, Victor & PRIETO-RODRIGUEZ, Juan, 2013. "Is there a gender bias in the use of foreign languages in Europe?," LIDAM Reprints CORE 2573, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    31. Ping Yu & Peter C.B. Phillips, 2014. "Threshold Regression with Endogeneity," Cowles Foundation Discussion Papers 1966, Cowles Foundation for Research in Economics, Yale University.
    32. DePaula, Guilherme, 2020. "The distributional effect of climate change on agriculture: Evidence from a Ricardian quantile analysis of Brazilian census data," Journal of Environmental Economics and Management, Elsevier, vol. 104(C).
    33. Edney, L.C. & Haji Ali Afzali, H. & Cheng, T.C. & Karnon, J., 2018. "Mortality reductions from marginal increases in public spending on health," Health Policy, Elsevier, vol. 122(8), pages 892-899.
    34. Hiroaki Kaido & Kaspar Wüthrich, 2018. "Decentralization estimators for instrumental variable quantile regression models," CeMMAP working papers CWP72/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    35. Ming-Chi Chen & Chi-Lu Peng & So-De Shyu & Jhih-Hong Zeng, 2012. "Market States and the Effect on Equity REIT Returns due to Changes in Monetary Policy Stance," The Journal of Real Estate Finance and Economics, Springer, vol. 45(2), pages 364-382, August.
    36. Wüthrich, Kaspar, 2020. "A Comparison of Two Quantile Models With Endogeneity," University of California at San Diego, Economics Working Paper Series qt0q43931f, Department of Economics, UC San Diego.
    37. Takuya Ishihara, 2020. "Panel Data Quantile Regression for Treatment Effect Models," Papers 2001.04324, arXiv.org, revised Nov 2021.
    38. Nathan Kallus & Miruna Oprescu, 2022. "Robust and Agnostic Learning of Conditional Distributional Treatment Effects," Papers 2205.11486, arXiv.org, revised Feb 2023.
    39. Wei, Shang-Jin & Wu, Weixing & Zhang, Linwan, 2019. "Portfolio choices, Asset returns and wealth inequality: evidence from China," Emerging Markets Review, Elsevier, vol. 38(C), pages 423-437.
    40. Abrevaya, Jason & Xu, Haiqing, 2023. "Estimation of treatment effects under endogenous heteroskedasticity," Journal of Econometrics, Elsevier, vol. 234(2), pages 451-478.
    41. Bola Amoke Awotide & Adebayo Ogunniyi & Kehinde Oluseyi Olagunju & Lateef Olalekan Bello & Amadou Youssouf Coulibaly & Alexander Nimo Wiredu & Bourémo Kone & Aly Ahamadou & Victor Manyong & Tahirou Ab, 2022. "Evaluating the Heterogeneous Impacts of Adoption of Climate-Smart Agricultural Technologies on Rural Households’ Welfare in Mali," Agriculture, MDPI, vol. 12(11), pages 1-16, November.
    42. Victor Chernozhukov & Christian Hansen, 2013. "Quantile Models with Endogeneity," Papers 1303.7050, arXiv.org.
    43. Sanglestsawai, Santi & Rejesus, Roderick M. & Yorobe, Jose M., 2014. "Do lower yielding farmers benefit from Bt corn? Evidence from instrumental variable quantile regressions," Food Policy, Elsevier, vol. 44(C), pages 285-296.
    44. Ramnath, Shanthi, 2013. "Taxpayers' responses to tax-based incentives for retirement savings: Evidence from the Saver's Credit notch," Journal of Public Economics, Elsevier, vol. 101(C), pages 77-93.
    45. Meliyanni Johar & Hajime Katayama, 2012. "Quantile regression analysis of body mass and wages," Health Economics, John Wiley & Sons, Ltd., vol. 21(5), pages 597-611, May.
    46. Chan, Marc K. & Polidano, Cain & Vu, Ha & Wilkins, Roger & Carter, Andrew & To, Hang, 2020. "How Effective are Matching Schemes in Enticing Low-income Earners to Save More for Retirement? Evidence from a National Scheme," IZA Discussion Papers 13939, Institute of Labor Economics (IZA).
    47. Wehby, George L. & Murray, Jeffrey C. & Castilla, Eduardo E. & Lopez-Camelo, Jorge S. & Ohsfeldt, Robert L., 2009. "Prenatal care demand and its effects on birth outcomes by birth defect status in Argentina," Economics & Human Biology, Elsevier, vol. 7(1), pages 84-95, March.
    48. Javier Alejo & Antonio F. Galvao & Gabriel Montes-Rojas, 2021. "A first-stage representation for instrumental variables quantile regression," Papers 2102.01212, arXiv.org, revised Feb 2022.
    49. Sungwon Lee, 2024. "Partial identification and inference for conditional distributions of treatment effects," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(1), pages 107-127, January.
    50. Horowitz, Joel L. & Lee, Sokbae, 2009. "Testing a parametric quantile-regression model with an endogenous explanatory variable against a nonparametric alternative," Journal of Econometrics, Elsevier, vol. 152(2), pages 141-152, October.
    51. Lin, Wei & Cai, Zongwu & Li, Zheng & Su, Li, 2015. "Optimal smoothing in nonparametric conditional quantile derivative function estimation," Journal of Econometrics, Elsevier, vol. 188(2), pages 502-513.
    52. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins, 2016. "Double/Debiased Machine Learning for Treatment and Causal Parameters," Papers 1608.00060, arXiv.org, revised Nov 2024.
    53. Daniel Jacob, 2021. "CATE meets ML -- The Conditional Average Treatment Effect and Machine Learning," Papers 2104.09935, arXiv.org, revised Apr 2021.
    54. Victor Chernozhukov & Christian Hansen & Kaspar Wuthrich, 2020. "Instrumental Variable Quantile Regression," Papers 2009.00436, arXiv.org.
    55. Chernozhukov, Victor & Hansen, Christian, 2006. "Instrumental quantile regression inference for structural and treatment effect models," Journal of Econometrics, Elsevier, vol. 132(2), pages 491-525, June.
    56. Hajime Katayama & Susumu Imai & Kala Krishna, 2006. "Protection For Sale Or Surge Protection?," Working Paper 1114, Economics Department, Queen's University.
    57. Bruna, Maria Giuseppina & Đặng, Rey & Ammari, Aymen & Houanti, L'Hocine, 2021. "The effect of board gender diversity on corporate social performance: An instrumental variable quantile regression approach," Finance Research Letters, Elsevier, vol. 40(C).
    58. Harding, Matthew & Lamarche, Carlos, 2009. "A quantile regression approach for estimating panel data models using instrumental variables," Economics Letters, Elsevier, vol. 104(3), pages 133-135, September.
    59. Wüthrich, Kaspar, 2019. "A closed-form estimator for quantile treatment effects with endogeneity," Journal of Econometrics, Elsevier, vol. 210(2), pages 219-235.
    60. Maria Giuseppina Bruna & Rey Đặng & Aymen Ammari & L'Hocine Houanti, 2021. "The effect of board gender diversity on corporate social performance: An instrumental variable quantile regression approach," Post-Print hal-04455603, HAL.
    61. Seoyun Hong, 2023. "Censored Quantile Regression with Many Controls," Papers 2303.02784, arXiv.org.
    62. Wehby, George L. & Murray, Jeffrey C. & Wilcox, Allen & Lie, Rolv T., 2012. "Smoking and body weight: Evidence using genetic instruments," Economics & Human Biology, Elsevier, vol. 10(2), pages 113-126.
    63. Kazuhiko Shinoda & Takahiro Hoshino, 2022. "Orthogonal Series Estimation for the Ratio of Conditional Expectation Functions," Papers 2212.13145, arXiv.org.
    64. Martin Jacob, 2013. "Capital Gains Taxes and the Realization of Capital Gains and Losses - Evidence from German Income Tax Data," FinanzArchiv: Public Finance Analysis, Mohr Siebeck, Tübingen, vol. 69(1), pages 30-56, March.
    65. George L. Wehby & Kwame A. Nyarko & Jorge S. Lopez‐Camelo, 2014. "Fetal Health Shocks And Early Inequalities In Health Capital Accumulation," Health Economics, John Wiley & Sons, Ltd., vol. 23(1), pages 69-92, January.
    66. George L. Wehby & Jeffrey C. Murray & Eduardo E. Castilla & Jorge S. Lopez‐Camelo & Robert L. Ohsfeldt, 2009. "Quantile effects of prenatal care utilization on birth weight in Argentina," Health Economics, John Wiley & Sons, Ltd., vol. 18(11), pages 1307-1321, November.
    67. Chernozhukov, Victor & Hansen, Christian, 2008. "Instrumental variable quantile regression: A robust inference approach," Journal of Econometrics, Elsevier, vol. 142(1), pages 379-398, January.
    68. Rahul Singh & Liyang Sun, 2019. "Double Robustness for Complier Parameters and a Semiparametric Test for Complier Characteristics," Papers 1909.05244, arXiv.org, revised Dec 2022.
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Software components

  1. Achim Ahrens & Christian B. Hansen & Mark E Schaffer, 2018. "LASSOPACK: Stata module for lasso, square-root lasso, elastic net, ridge, adaptive lasso estimation and cross-validation," Statistical Software Components S458458, Boston College Department of Economics, revised 18 Sep 2024.

    Cited by:

    1. Szabó-Morvai Ágnes & Hubert János Kiss, 2020. "Locus of control and Human Capital Investment Decisions: The Role of Effort, Parental Preferences and Financial Constraints," CERS-IE WORKING PAPERS 2055, Institute of Economics, Centre for Economic and Regional Studies.
    2. Mert Hakan Hekimoğlu & Burak Kazaz, 2020. "Analytics for Wine Futures: Realistic Prices," Production and Operations Management, Production and Operations Management Society, vol. 29(9), pages 2096-2120, September.
    3. Ladina Knapp & David Wuepper & Robert Finger, 2021. "Preferences, personality, aspirations, and farmer behavior," Agricultural Economics, International Association of Agricultural Economists, vol. 52(6), pages 901-913, November.
    4. Cardim, Joana & Molina-Millán, Teresa & Vicente, Pedro C., 2023. "Can technology improve the classroom experience in primary education? An African experiment on a worldwide program," Journal of Development Economics, Elsevier, vol. 164(C).
    5. Sander Gerritsen & Mark Kattenberg & Sonny Kuijpers, 2019. "The impact of age at arrival on education and mental health," CPB Discussion Paper 389, CPB Netherlands Bureau for Economic Policy Analysis.
    6. Gerhard Toews & Pierre-Louis Vezina, 2020. "Enemies of the people," Working Papers w0279, New Economic School (NES).
    7. Sujeong Park & David Powell, 2020. "Is the Rise in Illicit Opioids Affecting Labor Supply and Disability Claiming Rates?," NBER Working Papers 27804, National Bureau of Economic Research, Inc.
    8. Bertrand, Marianne & Crépon, Bruno, 2020. "Teaching Labor Laws: Evidence From a Randomized Control Trial in South Africa," IZA Discussion Papers 13513, Institute of Labor Economics (IZA).
    9. Mustafa Caglayan & Oleksandr Talavera & Lin Xiong, 2020. "Female Small Business Owners in China: Discouraged, not Discriminated," Discussion Papers 20-04, Department of Economics, University of Birmingham.
    10. Peter D. Lunn & Seán Lyons & Martin Murphy, 2020. "Predicting farms’ noncompliance with regulations on nitrate pollution," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 63(13), pages 2313-2333, November.
    11. Börschlein, Benjamin & Bossler, Mario, 2021. "A new machine learning-based treatment bite for long run minimum wage evaluations," VfS Annual Conference 2021 (Virtual Conference): Climate Economics 242441, Verein für Socialpolitik / German Economic Association.
    12. Oleksandr Faryna & Tho Pham & Oleksandr Talavera & Andriy Tsapin, 2020. "Wage Setting and Unemployment: Evidence from Online Job Vacancy Data," Economics Discussion Papers em-dp2020-02, Department of Economics, University of Reading.
    13. Mustafa Caglayan & Tho Pham & Oleksandr Talavera & Xiong Xiong, 2019. "Asset mispricing in loan secondary markets," Discussion Papers 19-07, Department of Economics, University of Birmingham.
    14. Luis Aguiar Wicht & Joel Waldfogel & Sarah Waldfogel, 2018. "Playlisting Favorites: Is Spotify Gender-Biased?," JRC Working Papers on Digital Economy 2018-07, Joint Research Centre.
    15. Rossmann, Tobias, 2019. "Does Experience Shape Subjective Expectations?," Rationality and Competition Discussion Paper Series 181, CRC TRR 190 Rationality and Competition.

  2. Achim Ahrens & Christian B. Hansen & Mark E Schaffer, 2018. "PDSLASSO: Stata module for post-selection and post-regularization OLS or IV estimation and inference," Statistical Software Components S458459, Boston College Department of Economics, revised 06 Aug 2024.

    Cited by:

    1. Falch, Ranveig, 2021. "How Do People Trade Off Resources Between Quick and Slow Learners?," Discussion Paper Series in Economics 5/2021, Norwegian School of Economics, Department of Economics.
    2. Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2019. "lassopack: Model selection and prediction with regularized regression in Stata," Papers 1901.05397, arXiv.org.
    3. Peter Eibich, 2021. "Care or self-care? The impact of informal care provision on health behaviour," MPIDR Working Papers WP-2021-005, Max Planck Institute for Demographic Research, Rostock, Germany.
    4. Laura Derksen & Jason Kerwin & Natalia Ordaz Reynoso & Olivier Sterck, 2021. "Appointments: A More Effective Commitment Device for Health Behaviors," Papers 2110.06876, arXiv.org.
    5. Tomaso Duso & Claus Michelsen & Maximilian Schäfer & Kevin Ducbao Tran, 2021. "Airbnb and Rental Markets: Evidence from Berlin," CESifo Working Paper Series 9089, CESifo.
    6. Felipe González & Magdalena Larreboure, 2021. "The Impact of the Women’s March on the U.S. House Election," Documentos de Trabajo 560, Instituto de Economia. Pontificia Universidad Católica de Chile..
    7. Simon B chler, Maximilian v. Ehrlich, 2021. "Quantifying Land Use Regulation and its Determinants - Ease of Residential Development across Swiss Municipalities," Diskussionsschriften credresearchpaper32, Universitaet Bern, Departement Volkswirtschaft - CRED.
    8. Agan, Amanda & Doleac, Jennifer & Harvey, Anna, 2021. "Misdemeanor Prosecution," IZA Discussion Papers 14234, Institute of Labor Economics (IZA).
    9. J. Goldberg & M. Macis & P. Chintagunta, 2019. "Incentivized Peer Referrals for Tuberculosis Screening: Evidence from India," Working Paper CRENoS 201911, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    10. Michael Danquah & Solomon Owusu, 2021. "Digital technology and productivity of informal enterprises: Empirical evidence from Nigeria," WIDER Working Paper Series wp-2021-114, World Institute for Development Economic Research (UNU-WIDER).
    11. Achim Ahrens & Sean Lyons, 2021. "Do rising rents lead to longer commutes? A gravity model of commuting flows in Ireland," Urban Studies, Urban Studies Journal Limited, vol. 58(2), pages 264-279, February.
    12. Do,Quy-Toan & Jacoby,Hanan G., 2020. "Sophisticated Policy with Naive Agents : Habit Formation and Piped Water in Vietnam," Policy Research Working Paper Series 9207, The World Bank.

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