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Machine Learning: An Applied Econometric Approach

Citations

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Sam Watson’s journal round-up for 12th June 2017
    by Sam Watson in The Academic Health Economists' Blog on 2017-06-12 16:00:00

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
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Cited by:

  1. Baruník, Jozef & Hanus, Luboš, 2024. "Fan charts in era of big data and learning," Finance Research Letters, Elsevier, vol. 61(C).
  2. Lamperti, Francesco & Roventini, Andrea & Sani, Amir, 2018. "Agent-based model calibration using machine learning surrogates," Journal of Economic Dynamics and Control, Elsevier, vol. 90(C), pages 366-389.
  3. Blankenship, Brian & Aklin, Michaël & Urpelainen, Johannes & Nandan, Vagisha, 2022. "Jobs for a just transition: Evidence on coal job preferences from India," Energy Policy, Elsevier, vol. 165(C).
  4. Matthew A. Cole & Robert J R Elliott & Bowen Liu, 2020. "The Impact of the Wuhan Covid-19 Lockdown on Air Pollution and Health: A Machine Learning and Augmented Synthetic Control Approach," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 76(4), pages 553-580, August.
  5. Francesca Micocci & Armando Rungi, 2021. "Predicting Exporters with Machine Learning," Papers 2107.02512, arXiv.org, revised Sep 2022.
  6. Gerard Domènech-Arumí, 2022. "Neighborhoods, Perceived Inequality, and Preferences for Redistribution :Evidence from Barcelona," Working Papers ECARES 2022-09, ULB -- Universite Libre de Bruxelles.
  7. Tsang, Andrew, 2021. "Uncovering Heterogeneous Regional Impacts of Chinese Monetary Policy," MPRA Paper 110703, University Library of Munich, Germany.
  8. Sebastian Doerr & Leonardo Gambacorta & José María Serena Garralda, 2021. "Big data and machine learning in central banking," BIS Working Papers 930, Bank for International Settlements.
  9. 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.
  10. Chakraborty, Chiranjit & Joseph, Andreas, 2017. "Machine learning at central banks," Bank of England working papers 674, Bank of England.
  11. 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.
  12. Bertoli, Paola & Grembi, Veronica, 2021. "Territorial differences in access to prenatal care and health at birth," Health Policy, Elsevier, vol. 125(8), pages 1092-1099.
  13. repec:zbw:bofitp:2018_009 is not listed on IDEAS
  14. Thiemo Fetzer & Stephan Kyburz, 2024. "Cohesive Institutions and Political Violence," The Review of Economics and Statistics, MIT Press, vol. 106(1), pages 133-150, January.
  15. 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.
  16. Onder Ozgur & Erdal Tanas Karagol & Fatih Cemil Ozbugday, 2021. "Machine learning approach to drivers of bank lending: evidence from an emerging economy," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-29, December.
  17. Joshua S. Gans, 2023. "Artificial intelligence adoption in a competitive market," Economica, London School of Economics and Political Science, vol. 90(358), pages 690-705, April.
  18. Kristian Jönsson, 2020. "Machine Learning and Nowcasts of Swedish GDP," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 16(2), pages 123-134, November.
  19. Akash Malhotra, 2021. "A hybrid econometric–machine learning approach for relative importance analysis: prioritizing food policy," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 11(3), pages 549-581, September.
  20. Emily Cuddy & Janet Currie, 2020. "Rules vs. Discretion: Treatment of Mental Illness in U.S. Adolescents," NBER Working Papers 27890, National Bureau of Economic Research, Inc.
  21. Luca Grilli & Sergio Mariotti & Riccardo Marzano, 2024. "Artificial intelligence and shapeshifting capitalism," Journal of Evolutionary Economics, Springer, vol. 34(2), pages 303-318, April.
  22. Byron Botha & Rulof Burger & Kevin Kotzé & Neil Rankin & Daan Steenkamp, 2023. "Big data forecasting of South African inflation," Empirical Economics, Springer, vol. 65(1), pages 149-188, July.
  23. Alabrese, Eleonora & Becker, Sascha O. & Fetzer, Thiemo & Novy, Dennis, 2019. "Who voted for Brexit? Individual and regional data combined," European Journal of Political Economy, Elsevier, vol. 56(C), pages 132-150.
  24. Caferra, Rocco & Morone, Andrea, 2019. "Tax Morale and Perceived Intergenerational Mobility: a Machine Learning Predictive Approach," MPRA Paper 93171, University Library of Munich, Germany.
  25. Tobias Götze & Marc Gürtler & Eileen Witowski, 0. "Improving CAT bond pricing models via machine learning," Journal of Asset Management, Palgrave Macmillan, vol. 0, pages 1-19.
  26. de Blasio, Guido & D'Ignazio, Alessio & Letta, Marco, 2022. "Gotham city. Predicting ‘corrupted’ municipalities with machine learning," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
  27. Samuel Bazzi & Robert A. Blair & Christopher Blattman & Oeindrila Dube & Matthew Gudgeon & Richard Peck, 2022. "The Promise and Pitfalls of Conflict Prediction: Evidence from Colombia and Indonesia," The Review of Economics and Statistics, MIT Press, vol. 104(4), pages 764-779, October.
  28. Giri, Prashant & Sharma, Tarun, 2024. "Market instrument for the first fuel and its role in decarbonizing Indian industrial production," Energy Policy, Elsevier, vol. 190(C).
  29. Anja Lambrecht & Catherine Tucker, 2019. "Algorithmic Bias? An Empirical Study of Apparent Gender-Based Discrimination in the Display of STEM Career Ads," Management Science, INFORMS, vol. 65(7), pages 2966-2981, July.
  30. Breinlich, Holger & Corradi, Valentina & Rocha, Nadia & Ruta, Michele & Silva, J.M.C. Santos & Zylkin, Tom, 2021. "Machine learning in international trade research - evaluating the impact of trade agreements," LSE Research Online Documents on Economics 114379, London School of Economics and Political Science, LSE Library.
  31. Yusuke Narita & Kohei Yata, 2021. "Algorithm is Experiment: Machine Learning, Market Design, and Policy Eligibility Rules," Working Papers 2021-022, Human Capital and Economic Opportunity Working Group.
  32. LI Chao & MANAGI Shunsuke, 2022. "Impact of the Rapid Expansion of Renewable Energy on Electricity Market Price: Using machine learning and shapley additive explanation," Discussion papers 22093, Research Institute of Economy, Trade and Industry (RIETI).
  33. 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.
  34. Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2022. "How is machine learning useful for macroeconomic forecasting?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 920-964, August.
  35. Gert Bijnens & Shyngys Karimov & Jozef Konings, 2023. "Does Automatic Wage Indexation Destroy Jobs? A Machine Learning Approach," De Economist, Springer, vol. 171(1), pages 85-117, March.
  36. Petros Xepapadeas & Kostas Douvis & Ioannis Kapsomenakis & Anastasios Xepapadeas & Christos Zerefos, 2024. "Assessing the Link between Wildfires, Vulnerability, and Climate Change: Insights from the Regions of Greece," Sustainability, MDPI, vol. 16(11), pages 1-25, June.
  37. Jens Ludwig & Sendhil Mullainathan, 2021. "Fragile Algorithms and Fallible Decision-Makers: Lessons from the Justice System," Journal of Economic Perspectives, American Economic Association, vol. 35(4), pages 71-96, Fall.
  38. 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.
  39. MIYAKAWA Daisuke, 2019. "Shocks to Supply Chain Networks and Firm Dynamics: An Application of Double Machine Learning," Discussion papers 19100, Research Institute of Economy, Trade and Industry (RIETI).
  40. Bryan, Kevin A. & Ozcan, Yasin & Sampat, Bhaven, 2020. "In-text patent citations: A user's guide," Research Policy, Elsevier, vol. 49(4).
  41. Bloise, Francesco & Tancioni, Massimiliano, 2021. "Predicting the spread of COVID-19 in Italy using machine learning: Do socio-economic factors matter?," Structural Change and Economic Dynamics, Elsevier, vol. 56(C), pages 310-329.
  42. Lundberg, Ian & Brand, Jennie E. & Jeon, Nanum, 2022. "Researcher reasoning meets computational capacity: Machine learning for social science," SocArXiv s5zc8, Center for Open Science.
  43. Matthias Westphal & Daniel A Kamhöfer & Hendrik Schmitz, 2022. "Marginal College Wage Premiums Under Selection Into Employment," The Economic Journal, Royal Economic Society, vol. 132(646), pages 2231-2272.
  44. von Essen, Emma & Jansson, Joakim, 2020. "Misogynistic and Xenophobic Hate Language Online: A Matter of Anonymity," Working Paper Series 1350, Research Institute of Industrial Economics.
  45. Dang, Hai-Anh H & Kilic, Talip & Hlasny, Vladimir & Abanokova, Kseniya & Carletto, Calogero, 2024. "Using Survey-to-Survey Imputation to Fill Poverty Data Gaps at a Low Cost: Evidence from a Randomized Survey Experiment," IZA Discussion Papers 16792, Institute of Labor Economics (IZA).
  46. Andrei Dubovik & Adam Elbourne & Bram Hendriks & Mark Kattenberg, 2022. "Forecasting World Trade Using Big Data and Machine Learning Techniques," CPB Discussion Paper 441, CPB Netherlands Bureau for Economic Policy Analysis.
  47. Stefania Albanesi & Domonkos F. Vamossy, 2019. "Predicting Consumer Default: A Deep Learning Approach," NBER Working Papers 26165, National Bureau of Economic Research, Inc.
  48. Jill Furzer & Maripier Isabelle & Boriana Miloucheva & Audrey Laporte, 2021. "Public drug insurance and children’s use of mental health medication: Risk-specific responses to lower out-of-pocket treatment costs," CIRANO Working Papers 2021s-34, CIRANO.
  49. 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.
  50. Chengyan Gu, 2023. "Market segmentation and dynamic price discrimination in the U.S. airline industry," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 22(5), pages 338-361, October.
  51. Jorge Mejia & Shawn Mankad & Anandasivam Gopal, 2019. "A for Effort? Using the Crowd to Identify Moral Hazard in New York City Restaurant Hygiene Inspections," Information Systems Research, INFORMS, vol. 30(4), pages 1363-1386, December.
  52. Barkan, Oren & Benchimol, Jonathan & Caspi, Itamar & Cohen, Eliya & Hammer, Allon & Koenigstein, Noam, 2023. "Forecasting CPI inflation components with Hierarchical Recurrent Neural Networks," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1145-1162.
  53. Colak, Gonul & Fu, Mengchuan & Hasan, Iftekhar, 2022. "On modeling IPO failure risk," Economic Modelling, Elsevier, vol. 109(C).
  54. Gavoille, Nicolas & Zasova, Anna, 2023. "What we pay in the shadows: Labor tax evasion, minimum wage hike and employment," Journal of Public Economics, Elsevier, vol. 228(C).
  55. 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).
  56. Costanza Naguib, 2023. "Is the Impact of Opening the Borders Heterogeneous?," Diskussionsschriften dp2312, Universitaet Bern, Departement Volkswirtschaft.
  57. Dang, Hai-Anh H. & Kilic, Talip & Abanokova, Kseniya & Carletto, Calogero, 2024. "Imputing Poverty Indicators without Consumption Data: An Exploratory Analysis," GLO Discussion Paper Series 1458, Global Labor Organization (GLO).
  58. Ahlfeldt, Gabriel M. & Heblich, Stephan & Seidel, Tobias, 2023. "Micro-geographic property price and rent indices," Regional Science and Urban Economics, Elsevier, vol. 98(C).
  59. Arno Parolini & Wei Wu Tan & Aron Shlonsky, 2019. "Decision-based models of the implementation of interventions in systems of healthcare: Implementation outcomes and intervention effectiveness in complex service environments," PLOS ONE, Public Library of Science, vol. 14(10), pages 1-17, October.
  60. Antonio Pacifico, 2022. "Structural Compressed Panel VAR with Stochastic Volatility: A Robust Bayesian Model Averaging Procedure," Econometrics, MDPI, vol. 10(3), pages 1-24, July.
  61. Jo~ao B. Assunc{c}~ao & Pedro Afonso Fernandes, 2024. "The Surprising Robustness of Partial Least Squares," Papers 2409.05713, arXiv.org.
  62. Igor Sadoune & Andrea Lodi & Marcelin Joanis, 2022. "Implementing a Hierarchical Deep Learning Approach for Simulating Multi-Level Auction Data," Papers 2207.12255, arXiv.org, revised Feb 2024.
  63. 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.
  64. Rachidi Kotchoni & Maxime Leroux & Dalibor Stevanovic, 2019. "Macroeconomic forecast accuracy in a data‐rich environment," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(7), pages 1050-1072, November.
  65. Stefania Albanesi & Domonkos F. Vamossy, 2024. "Credit Scores: Performance and Equity," NBER Working Papers 32917, National Bureau of Economic Research, Inc.
  66. Christensen, Peter & Francisco, Paul & Myers, Erica & Shao, Hansen & Souza, Mateus, 2024. "Energy efficiency can deliver for climate policy: Evidence from machine learning-based targeting," Journal of Public Economics, Elsevier, vol. 234(C).
  67. Achten, Sandra & Lessmann, Christian, 2020. "Spatial inequality, geography and economic activity," World Development, Elsevier, vol. 136(C).
  68. Chaney, Eric, 2020. "Modern Library Holdings and Historic City Growth," CEPR Discussion Papers 14686, C.E.P.R. Discussion Papers.
  69. Michael Pollmann, 2020. "Causal Inference for Spatial Treatments," Papers 2011.00373, arXiv.org, revised Jan 2023.
  70. Lucas, Benjamin & Francu, R. Elena & Goulding, James & Harvey, John & Nica-Avram, Georgiana & Perrat, Bertrand, 2021. "A Note on Data-driven Actor-differentiation and SDGs 2 and 12: Insights from a Food-sharing App," Research Policy, Elsevier, vol. 50(6).
  71. Halko, Marja-Liisa & Lappalainen, Olli & Sääksvuori, Lauri, 2021. "Do non-choice data reveal economic preferences? Evidence from biometric data and compensation-scheme choice," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 87-104.
  72. Chuandi Fang & Jinhua Cheng & Zhe You & Jiahao Chen & Jing Peng, 2023. "A Detailed Examination of China’s Clean Energy Mineral Consumption: Footprints, Trends, and Drivers," Sustainability, MDPI, vol. 15(23), pages 1-26, November.
  73. Feras A. Batarseh & Munisamy Gopinath & Anderson Monken & Zhengrong Gu, 2021. "Public Policymaking for International Agricultural Trade using Association Rules and Ensemble Machine Learning," Papers 2111.07508, arXiv.org.
  74. Suriyan Jomthanachai & Wai Peng Wong & Khai Wah Khaw, 2024. "An Application of Machine Learning to Logistics Performance Prediction: An Economics Attribute-Based of Collective Instance," Computational Economics, Springer;Society for Computational Economics, vol. 63(2), pages 741-792, February.
  75. Li, Zheng & Zhou, Bo & Hensher, David A., 2022. "Forecasting automobile gasoline demand in Australia using machine learning-based regression," Energy, Elsevier, vol. 239(PD).
  76. Michael Bailey & Drew Johnston & Theresa Kuchler & Johannes Stroebel & Arlene Wong, 2022. "Peer Effects in Product Adoption," American Economic Journal: Applied Economics, American Economic Association, vol. 14(3), pages 488-526, July.
  77. Ahmet Murat Ozbayoglu & Mehmet Ugur Gudelek & Omer Berat Sezer, 2020. "Deep Learning for Financial Applications : A Survey," Papers 2002.05786, arXiv.org.
  78. Yeomans, Michael, 2021. "A concrete example of construct construction in natural language," Organizational Behavior and Human Decision Processes, Elsevier, vol. 162(C), pages 81-94.
  79. Rubesam, Alexandre, 2022. "Machine learning portfolios with equal risk contributions: Evidence from the Brazilian market," Emerging Markets Review, Elsevier, vol. 51(PB).
  80. Rocco, Salvatore, 2022. "Implementing and managing Algorithmic Decision-Making in the public sector," SocArXiv ex93w, Center for Open Science.
  81. Peter Leopold S. Bergman & Elizabeth Kopko & Julio Rodriguez, 2021. "Using Predictive Analytics to Track Students: Evidence from a Seven-College Experiment," CESifo Working Paper Series 9157, CESifo.
  82. Kristof Lommers & Ouns El Harzli & Jack Kim, 2021. "Confronting Machine Learning With Financial Research," Papers 2103.00366, arXiv.org, revised Mar 2021.
  83. 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.
  84. Bryan, Gharad & Karlan, Dean & Osman, Adam, 2024. "Big loans to small businesses: predicting winners and losers in an entrepreneurial lending experiment," LSE Research Online Documents on Economics 120637, London School of Economics and Political Science, LSE Library.
  85. Micevska, Maja, 2021. "Revisiting forced migration: A machine learning perspective," European Journal of Political Economy, Elsevier, vol. 70(C).
  86. Sarr, Ibrahima & Dang, Hai-Anh H. & Guzman Gutierrez, Carlos Santiago & Beltramo, Theresa & Verme, Paolo, 2024. "Using Cross-Survey Imputation to Estimate Poverty for Venezuelan Refugees in Colombia," GLO Discussion Paper Series 1534, Global Labor Organization (GLO).
  87. Prüfer, Jens & Prüfer, Patricia, 2019. "Data Science for Entrepreneurship Research : Studying Demand Dynamics for Entrepreneurial Skills in the Netherlands," Other publications TiSEM 83a4ca9e-c0cd-4786-ac8c-9, Tilburg University, School of Economics and Management.
  88. Omid Rafieian, 2023. "Optimizing User Engagement Through Adaptive Ad Sequencing," Marketing Science, INFORMS, vol. 42(5), pages 910-933, September.
  89. Christophe Hurlin & Christophe Perignon & Sébastien Saurin, 2021. "The Fairness of Credit Scoring Models," Working Papers hal-03501452, HAL.
  90. Pan, Shuiyang & Long, Suwan(Cheng) & Wang, Yiming & Xie, Ying, 2023. "Nonlinear asset pricing in Chinese stock market: A deep learning approach," International Review of Financial Analysis, Elsevier, vol. 87(C).
  91. Becker, Sascha O. & Fetzer, Thiemo, 2018. "Has Eastern European Migration Impacted UK-born Workers?," The Warwick Economics Research Paper Series (TWERPS) 1165, University of Warwick, Department of Economics.
  92. Paul Geertsema & Helen Lu, 2023. "Relative Valuation with Machine Learning," Journal of Accounting Research, Wiley Blackwell, vol. 61(1), pages 329-376, March.
  93. McKenzie, David & Sansone, Dario, 2019. "Predicting entrepreneurial success is hard: Evidence from a business plan competition in Nigeria," Journal of Development Economics, Elsevier, vol. 141(C).
  94. Oz Shy, 2020. "Alternative Methods for Studying Consumer Payment Choice," FRB Atlanta Working Paper 2020-8, Federal Reserve Bank of Atlanta.
  95. 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.
  96. Kota Sugimoto, 2024. "Competitive effects of implicit auction on interconnectors: evidence from Japan," Journal of Regulatory Economics, Springer, vol. 66(1), pages 95-134, August.
  97. Sugiawan, Yogi & Managi, Shunsuke, 2019. "New evidence of energy-growth nexus from inclusive wealth," Renewable and Sustainable Energy Reviews, Elsevier, vol. 103(C), pages 40-48.
  98. Khudri, Md Mohsan & Hussey, Andrew, 2024. "Breastfeeding and Child Development Outcomes across Early Childhood and Adolescence: Doubly Robust Estimation with Machine Learning," IZA Discussion Papers 17080, Institute of Labor Economics (IZA).
  99. Jiang, Wen & Xing, Xianjun & Zhang, Xianwen & Mi, Mengxing, 2019. "Prediction of combustion activation energy of NaOH/KOH catalyzed straw pyrolytic carbon based on machine learning," Renewable Energy, Elsevier, vol. 130(C), pages 1216-1225.
  100. Colak, Gonul & Fu, Mengchuan & Hasan, Iftekhar, 2020. "Why are some Chinese firms failing in the US capital markets? A machine learning approach," Pacific-Basin Finance Journal, Elsevier, vol. 61(C).
  101. Breunig, Christoph & Grabova, Iuliia & Haan, Peter & Weinhardt, Felix & Weizsäcker, Georg, 2021. "Long-run expectations of households," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 31, pages 1-1.
  102. Byun, Suk-Joon & Cho, Sangheum & Kim, Da-Hea, 2024. "Can a machine learn from behavioral biases? Evidence from stock return predictability of deep learning models," Journal of Behavioral and Experimental Finance, Elsevier, vol. 41(C).
  103. Emanuel Kohlscheen, 2022. "Quantifying the role of interest rates, the Dollar and Covid in oil prices," BIS Working Papers 1040, Bank for International Settlements.
  104. Zhang, Jianhong & van Witteloostuijn, Arjen & Zhou, Chaohong & Zhou, Shengyang, 2024. "Cross-border acquisition completion by emerging market MNEs revisited: Inductive evidence from a machine learning analysis," Journal of World Business, Elsevier, vol. 59(2).
  105. Can Verberi & Muhittin Kaplan, 2024. "Exploring the Impact of Behavioural Factors and Personality Traits on Private Pension System Participation: A Machine Learning Approach," Istanbul Journal of Economics-Istanbul Iktisat Dergisi, Istanbul University, Faculty of Economics, vol. 73(74-1), pages 281-314, June.
  106. Williams, Austin M., 2019. "Understanding the micro-determinants of defensive behaviors against pollution," Ecological Economics, Elsevier, vol. 163(C), pages 42-51.
  107. Paolo Brunori & Vito Peragine & Laura Serlenga, 2019. "Upward and downward bias when measuring inequality of opportunity," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 52(4), pages 635-661, April.
  108. Mueller, Andreas I. & Spinnewijn, Johannes, 2023. "The Nature of Long-Term Unemployment: Predictability, Heterogeneity and Selection," CEPR Discussion Papers 17913, C.E.P.R. Discussion Papers.
  109. Steve J. Bickley & Ho Fai Chan & Benno Torgler, 2022. "Artificial intelligence in the field of economics," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(4), pages 2055-2084, April.
  110. Mehmet Güney Celbiş & Pui-Hang Wong & Karima Kourtit & Peter Nijkamp, 2021. "Innovativeness, Work Flexibility, and Place Characteristics: A Spatial Econometric and Machine Learning Approach," Sustainability, MDPI, vol. 13(23), pages 1-29, December.
  111. David Mayer-Foulkes, 2018. "Efficient Urbanization for Mexican Development," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 10(10), pages 1-1, October.
  112. Manav Raj & Robert Seamans, 2019. "Primer on artificial intelligence and robotics," Journal of Organization Design, Springer;Organizational Design Community, vol. 8(1), pages 1-14, December.
  113. 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.
  114. Hirche, Martin & Farris, Paul W. & Greenacre, Luke & Quan, Yiran & Wei, Susan, 2021. "Predicting Under- and Overperforming SKUs within the Distribution–Market Share Relationship," Journal of Retailing, Elsevier, vol. 97(4), pages 697-714.
  115. Michael C. Knaus & Michael Lechner & Anthony Strittmatter, 2022. "Heterogeneous Employment Effects of Job Search Programs: A Machine Learning Approach," Journal of Human Resources, University of Wisconsin Press, vol. 57(2), pages 597-636.
  116. Sun-Youn Shin & Han-Gyun Woo, 2022. "Energy Consumption Forecasting in Korea Using Machine Learning Algorithms," Energies, MDPI, vol. 15(13), pages 1-20, July.
  117. Leuz, Christian, 2022. "Towards a design-based approach to accounting research," Journal of Accounting and Economics, Elsevier, vol. 74(2).
  118. Rama K. Malladi, 2024. "Benchmark Analysis of Machine Learning Methods to Forecast the U.S. Annual Inflation Rate During a High-Decile Inflation Period," Computational Economics, Springer;Society for Computational Economics, vol. 64(1), pages 335-375, July.
  119. 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.
  120. Marianne Bertrand & Emir Kamenica, 2023. "Coming Apart? Cultural Distances in the United States over Time," American Economic Journal: Applied Economics, American Economic Association, vol. 15(4), pages 100-141, October.
  121. Disa M. Hynsjö & Luca Perdoni, 2024. "Mapping Out Institutional Discrimination: The Economic Effects of Federal “Redlining”," CESifo Working Paper Series 11098, CESifo.
  122. Gonzalo, Jesús & Pitarakis, Jean-Yves, 2021. "Spurious relationships in high-dimensional systems with strong or mild persistence," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1480-1497.
  123. Sandrine Mesplé-Somps and & Björn Nilsson, 2020. "Role models and migration intentions," Working Paper 519bfbde-8d2e-4e86-bd62-0, Agence française de développement.
  124. 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.
  125. Masci, Chiara & Johnes, Geraint & Agasisti, Tommaso, 2018. "Student and school performance across countries: A machine learning approach," European Journal of Operational Research, Elsevier, vol. 269(3), pages 1072-1085.
  126. Pablo Picardo, 2019. "Predicción de precios de vivienda: Aprendizaje estadístico con datos de oferta y transacciones para la ciudad de Montevideo," Documentos de trabajo 2019002, Banco Central del Uruguay.
  127. Galdo, Virgilio & Li, Yue & Rama, Martin, 2021. "Identifying urban areas by combining human judgment and machine learning: An application to India," Journal of Urban Economics, Elsevier, vol. 125(C).
  128. Jill Furzer & Maripier Isabelle & Boriana Miloucheva & Audrey Laporte, 2023. "Public drug insurance, moral hazard and children's use of mental health medication: Latent mental health risk‐specific responses to lower out‐of‐pocket treatment costs," Health Economics, John Wiley & Sons, Ltd., vol. 32(2), pages 518-538, February.
  129. Shoshan, Vered & Hazan, Tamir & Plonsky, Ori, 2023. "BEAST-Net: Learning novel behavioral insights using a neural network adaptation of a behavioral model," OSF Preprints kaeny, Center for Open Science.
  130. Evaggelia Siopi & Thomas Poufinas & James Ming Chen & Charalampos Agiropoulos, 2023. "Can Regulation Affect the Solvency of Insurers? New Evidence from European Insurers," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 29(1), pages 15-30, May.
  131. Mari O. Mamre & Dag Einar Sommervoll, 2024. "Coming of Age: Renovation Premiums in Housing Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 69(2), pages 307-342, August.
  132. Donna B. Gilleskie, 2021. "In sickness and in health, until death do us part: A case for theory," Southern Economic Journal, John Wiley & Sons, vol. 87(3), pages 753-768, January.
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