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Lukas Laffers

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First Name:Lukas
Middle Name:
Last Name:Laffers
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RePEc Short-ID:pla1110
[This author has chosen not to make the email address public]
http://www.lukaslaffers.com
Terminal Degree:2014 Norges Handelshøyskole (NHH) (from RePEc Genealogy)

Research output

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Jump to: Working papers Articles

Working papers

  1. Martin Huber & Kevin Kloiber & Lukas Laffers, 2024. "Testing identification in mediation and dynamic treatment models," Papers 2406.13826, arXiv.org.
  2. Lafférs, Lukáš & Schmidpeter, Bernhard, 2021. "Mothers' Job Search after Childbirth," IZA Discussion Papers 14593, Institute of Labor Economics (IZA).
  3. Martin Kahanec & Lukáš Lafférs & Bernhard Schmidpeter, 2021. "The Impact of Mass Antigen Testing for COVID-19 on the Prevalence of the Disease," Discussion Papers 59, Central European Labour Studies Institute (CELSI).
  4. Lafférs, Lukáš & Mellace, Giovanni, 2020. "Identification of the average treatment effect when SUTVA is violated," Discussion Papers on Economics 3/2020, University of Southern Denmark, Department of Economics.
  5. Lafférs, Lukáš & Schmidpeter, Bernhard, 2020. "Early Child Development and Parents' Labor Supply," IZA Discussion Papers 13531, Institute of Labor Economics (IZA).
  6. Lukáš Lafférs, 2015. "Bounding average treatment effects using linear programming," CeMMAP working papers 70/15, Institute for Fiscal Studies.
  7. Laffers, Lukas & Mellace, Giovanni, 2015. "A Note on Testing the LATE Assumptions," Discussion Papers on Economics 4/2015, University of Southern Denmark, Department of Economics.
  8. Laffers, Lukas, 2013. "Identification in Models with Discrete Variables," Discussion Paper Series in Economics 1/2013, Norwegian School of Economics, Department of Economics.

Articles

  1. Štefánik, Miroslav & Lafférs, Lukáš, 2024. "Supporting the right workplace experience: a dynamic evaluation of three activation programmes for young job seekers in Slovakia," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 58, pages 1-16.
  2. Michela Bia & Martin Huber & Lukáš Lafférs, 2024. "Double Machine Learning for Sample Selection Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(3), pages 958-969, July.
  3. Martin Huber & Lukáš Lafférs, 2022. "Bounds on direct and indirect effects under treatment/mediator endogeneity and outcome attrition," Econometric Reviews, Taylor & Francis Journals, vol. 41(10), pages 1141-1163, November.
  4. Martin Kahanec & Lukáš Lafférs & Bernhard Schmidpeter, 2021. "The impact of repeated mass antigen testing for COVID-19 on the prevalence of the disease," Journal of Population Economics, Springer;European Society for Population Economics, vol. 34(4), pages 1105-1140, October.
  5. Lukáš Lafférs & Bernhard Schmidpeter, 2021. "Early child development and parents' labor supply," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(2), pages 190-208, March.
  6. Lukáš Lafférs, 2019. "Bounding average treatment effects using linear programming," Empirical Economics, Springer, vol. 57(3), pages 727-767, September.
  7. Lukáš Lafférs, 2019. "Identification in Models with Discrete Variables," Computational Economics, Springer;Society for Computational Economics, vol. 53(2), pages 657-696, February.
  8. Lafférs, Lukáš & Nedela, Roman, 2017. "Sensitivity of the bounds on the ATE in the presence of sample selection," Economics Letters, Elsevier, vol. 158(C), pages 84-87.
  9. Martin Huber & Lukas Laffers & Giovanni Mellace, 2017. "Sharp IV Bounds on Average Treatment Effects on the Treated and Other Populations Under Endogeneity and Noncompliance," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(1), pages 56-79, January.
  10. Lukas Laffers & Giovanni Mellace, 2017. "A note on testing instrument validity for the identification of LATE," Empirical Economics, Springer, vol. 53(3), pages 1281-1286, November.
  11. Lafférs, Lukáš, 2013. "A note on bounding average treatment effects," Economics Letters, Elsevier, vol. 120(3), pages 424-428.

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.

Working papers

  1. Martin Kahanec & Lukáš Lafférs & Bernhard Schmidpeter, 2021. "The Impact of Mass Antigen Testing for COVID-19 on the Prevalence of the Disease," Discussion Papers 59, Central European Labour Studies Institute (CELSI).

    Cited by:

    1. Majerčák Jozef & Vakulenko Sergej Petrovich, 2023. "The Impact of COVID-19 Pandemic on Population Mobility in the Czech Republic and Slovakia," LOGI – Scientific Journal on Transport and Logistics, Sciendo, vol. 14(1), pages 158-168, January.
    2. David Turner & Balazs Egert & Yvan Guillemette & Jamila Botev, 2021. "The Tortoise and the Hare: The Race between Vaccine Rollout and New Covid Variants," CESifo Working Paper Series 9151, CESifo.
    3. Anna Adamecz-Völgyi & Ágnes Szabó-Morvai, 2021. "Confidence in public institutions is critical in containing the COVID-19 pandemic," CERS-IE WORKING PAPERS 2126, Institute of Economics, Centre for Economic and Regional Studies.
    4. Guilhem Cassan & Marc Sangnier, 2022. "The impact of 2020 French municipal elections on the spread of COVID-19," Journal of Population Economics, Springer;European Society for Population Economics, vol. 35(3), pages 963-988, July.
    5. Jeon, Jeonghwan & Suvitha, Krishnan & Arshad, Noreen Izza & Kalaiselvan, Samayan & Narayanamoorthy, Samayan & Ferrara, Massimiliano & Ahmadian, Ali, 2023. "A probabilistic hesitant fuzzy MCDM approach to evaluate India’s intervention strategies against the COVID-19 pandemic," Socio-Economic Planning Sciences, Elsevier, vol. 89(C).
    6. Phi-Hung Nguyen & Jung-Fa Tsai & Thanh-Tuan Dang & Ming-Hua Lin & Hong-Anh Pham & Kim-Anh Nguyen, 2021. "A Hybrid Spherical Fuzzy MCDM Approach to Prioritize Governmental Intervention Strategies against the COVID-19 Pandemic: A Case Study from Vietnam," Mathematics, MDPI, vol. 9(20), pages 1-26, October.
    7. Anna Godøy & Maja Weemes Grøtting & Rannveig Kaldager Hart, 2022. "Reopening schools in a context of low COVID-19 contagion: consequences for teachers, students and their parents," Journal of Population Economics, Springer;European Society for Population Economics, vol. 35(3), pages 935-961, July.

  2. Lafférs, Lukáš & Mellace, Giovanni, 2020. "Identification of the average treatment effect when SUTVA is violated," Discussion Papers on Economics 3/2020, University of Southern Denmark, Department of Economics.

    Cited by:

    1. Arthur Lewbel, 2018. "The Identification Zoo - Meanings of Identification in Econometrics," Boston College Working Papers in Economics 957, Boston College Department of Economics, revised 14 Dec 2019.

  3. Lafférs, Lukáš & Schmidpeter, Bernhard, 2020. "Early Child Development and Parents' Labor Supply," IZA Discussion Papers 13531, Institute of Labor Economics (IZA).

    Cited by:

    1. Kouki, Amairisa, 2023. "Beyond the “Comforts” of work from home: Child health and the female wage penalty," European Economic Review, Elsevier, vol. 157(C).
    2. Arenas-Arroyo, Esther & Schmidpeter, Bernhard, 2022. "Spillover Effects of Immigration Policies on Children's Human Capital," IZA Discussion Papers 15624, Institute of Labor Economics (IZA).
    3. Cho, Seungyeon, 2021. "Is handedness exogenously determined? Counterevidence from South Korea," Economics & Human Biology, Elsevier, vol. 43(C).
    4. Voit, Falk A. C., 2023. "Adverse birth outcomes and parental labor market participation after birth," Hannover Economic Papers (HEP) dp-710, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

  4. Lukáš Lafférs, 2015. "Bounding average treatment effects using linear programming," CeMMAP working papers 70/15, Institute for Fiscal Studies.

    Cited by:

    1. Laffers, Lukas, 2013. "Identification in Models with Discrete Variables," Discussion Paper Series in Economics 1/2013, Norwegian School of Economics, Department of Economics.

  5. Laffers, Lukas, 2013. "Identification in Models with Discrete Variables," Discussion Paper Series in Economics 1/2013, Norwegian School of Economics, Department of Economics.

    Cited by:

    1. Lukáš Lafférs, 2019. "Bounding average treatment effects using linear programming," Empirical Economics, Springer, vol. 57(3), pages 727-767, September.

Articles

  1. Martin Huber & Lukáš Lafférs, 2022. "Bounds on direct and indirect effects under treatment/mediator endogeneity and outcome attrition," Econometric Reviews, Taylor & Francis Journals, vol. 41(10), pages 1141-1163, November.

    Cited by:

    1. Daniel Kaliski, 2023. "Identifying the impact of health insurance on subgroups with changing rates of diagnosis," Health Economics, John Wiley & Sons, Ltd., vol. 32(9), pages 2098-2112, September.

  2. Martin Kahanec & Lukáš Lafférs & Bernhard Schmidpeter, 2021. "The impact of repeated mass antigen testing for COVID-19 on the prevalence of the disease," Journal of Population Economics, Springer;European Society for Population Economics, vol. 34(4), pages 1105-1140, October.

    Cited by:

    1. Majerčák Jozef & Vakulenko Sergej Petrovich, 2023. "The Impact of COVID-19 Pandemic on Population Mobility in the Czech Republic and Slovakia," LOGI – Scientific Journal on Transport and Logistics, Sciendo, vol. 14(1), pages 158-168, January.
    2. Anna Adamecz-Völgyi & Ágnes Szabó-Morvai, 2021. "Confidence in public institutions is critical in containing the COVID-19 pandemic," CERS-IE WORKING PAPERS 2126, Institute of Economics, Centre for Economic and Regional Studies.
    3. Guilhem Cassan & Marc Sangnier, 2022. "The impact of 2020 French municipal elections on the spread of COVID-19," Journal of Population Economics, Springer;European Society for Population Economics, vol. 35(3), pages 963-988, July.
    4. Jeon, Jeonghwan & Suvitha, Krishnan & Arshad, Noreen Izza & Kalaiselvan, Samayan & Narayanamoorthy, Samayan & Ferrara, Massimiliano & Ahmadian, Ali, 2023. "A probabilistic hesitant fuzzy MCDM approach to evaluate India’s intervention strategies against the COVID-19 pandemic," Socio-Economic Planning Sciences, Elsevier, vol. 89(C).
    5. Phi-Hung Nguyen & Jung-Fa Tsai & Thanh-Tuan Dang & Ming-Hua Lin & Hong-Anh Pham & Kim-Anh Nguyen, 2021. "A Hybrid Spherical Fuzzy MCDM Approach to Prioritize Governmental Intervention Strategies against the COVID-19 Pandemic: A Case Study from Vietnam," Mathematics, MDPI, vol. 9(20), pages 1-26, October.
    6. Anna Godøy & Maja Weemes Grøtting & Rannveig Kaldager Hart, 2022. "Reopening schools in a context of low COVID-19 contagion: consequences for teachers, students and their parents," Journal of Population Economics, Springer;European Society for Population Economics, vol. 35(3), pages 935-961, July.

  3. Lukáš Lafférs & Bernhard Schmidpeter, 2021. "Early child development and parents' labor supply," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(2), pages 190-208, March.
    See citations under working paper version above.
  4. Lukáš Lafférs, 2019. "Bounding average treatment effects using linear programming," Empirical Economics, Springer, vol. 57(3), pages 727-767, September.
    See citations under working paper version above.
  5. Lukáš Lafférs, 2019. "Identification in Models with Discrete Variables," Computational Economics, Springer;Society for Computational Economics, vol. 53(2), pages 657-696, February.
    See citations under working paper version above.
  6. Lafférs, Lukáš & Nedela, Roman, 2017. "Sensitivity of the bounds on the ATE in the presence of sample selection," Economics Letters, Elsevier, vol. 158(C), pages 84-87.

    Cited by:

    1. Huber, Martin & Laffers, Lukáš, 2020. "Bounds on direct and indirect effects under treatment/mediator endogeneity and outcome attrition," FSES Working Papers 514, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.

  7. Martin Huber & Lukas Laffers & Giovanni Mellace, 2017. "Sharp IV Bounds on Average Treatment Effects on the Treated and Other Populations Under Endogeneity and Noncompliance," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(1), pages 56-79, January.

    Cited by:

    1. Federico A. Bugni & Mengsi Gao & Filip Obradovic & Amilcar Velez, 2024. "Identification and Inference on Treatment Effects under Covariate-Adaptive Randomization and Imperfect Compliance," Papers 2406.08419, arXiv.org, revised Jun 2024.
    2. Laffers, Lukas, 2013. "Identification in Models with Discrete Variables," Discussion Paper Series in Economics 1/2013, Norwegian School of Economics, Department of Economics.
    3. Nadja van 't Hoff, 2023. "Identifying Causal Effects of Discrete, Ordered and ContinuousTreatments using Multiple Instrumental Variables," Papers 2311.17575, arXiv.org, revised Oct 2024.
    4. Xiaolin Sun & Xueyan Zhao & D. S. Poskitt, 2024. "Partially Identified Heterogeneous Treatment Effect with Selection: An Application to Gender Gaps," Papers 2410.01159, arXiv.org, revised Oct 2024.
    5. 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.
    6. Xintong Wang & Alfonso Flores-Lagunes, 2022. "Conscription and Military Service: Do They Result in Future Violent and Nonviolent Incarcerations and Recidivism?," Journal of Human Resources, University of Wisconsin Press, vol. 57(5), pages 1715-1757.
    7. Lukas Laffers & Giovanni Mellace, 2017. "A note on testing instrument validity for the identification of LATE," Empirical Economics, Springer, vol. 53(3), pages 1281-1286, November.
    8. Christelis, Dimitris & Messina, Julián, 2019. "Partial Identification of Population Average and Quantile Treatment Effects in Observational Data under Sample Selection," IDB Publications (Working Papers) 9520, Inter-American Development Bank.
    9. Michela Bia & German Blanco & Marie Valentova, 2021. "The Causal Impact of Taking Parental Leave on Wages: Evidence from 2005 to 2015," LISER Working Paper Series 2021-08, Luxembourg Institute of Socio-Economic Research (LISER).
    10. Chen, Xuan & Flores, Carlos A. & Flores-Lagunes, Alfonso, 2017. "Going beyond LATE: Bounding Average Treatment Effects of Job Corps Training," GLO Discussion Paper Series 93, Global Labor Organization (GLO).
    11. Kedagni, Desire, 2018. "Identifying Treatment Effects in the Presence of Confounded Types," ISU General Staff Papers 201809110700001056, Iowa State University, Department of Economics.
    12. Bartalotti, Otávio & Kédagni, Désiré & Possebom, Vitor, 2023. "Identifying marginal treatment effects in the presence of sample selection," Journal of Econometrics, Elsevier, vol. 234(2), pages 565-584.
    13. Amanda E. Kowalski, 2018. "Extrapolation using Selection and Moral Hazard Heterogeneity from within the Oregon Health Insurance Experiment," Cowles Foundation Discussion Papers 2135, Cowles Foundation for Research in Economics, Yale University.
    14. Kitagawa, Toru, 2021. "The identification region of the potential outcome distributions under instrument independence," Journal of Econometrics, Elsevier, vol. 225(2), pages 231-253.
    15. Kory Kroft & Ismael Mourifi'e & Atom Vayalinkal, 2024. "Lee Bounds with Multilayered Sample Selection," Papers 2409.04589, arXiv.org.
    16. Marx, Philip, 2024. "Sharp bounds in the latent index selection model," Journal of Econometrics, Elsevier, vol. 238(2).
    17. Possebom, Vitor, 2018. "Sharp bounds on the MTE with sample selection," MPRA Paper 89785, University Library of Munich, Germany.
    18. Aizawa, T.;, 2019. "Reviewing the Existing Evidence of the Conditional Cash Transfer in India through the Partial Identification Approach," Health, Econometrics and Data Group (HEDG) Working Papers 19/24, HEDG, c/o Department of Economics, University of York.
    19. Claudia Noack, 2021. "Sensitivity of LATE Estimates to Violations of the Monotonicity Assumption," Papers 2106.06421, arXiv.org.

  8. Lukas Laffers & Giovanni Mellace, 2017. "A note on testing instrument validity for the identification of LATE," Empirical Economics, Springer, vol. 53(3), pages 1281-1286, November.

    Cited by:

    1. Thomas Carr & Toru Kitagawa, 2021. "Testing Instrument Validity with Covariates," Papers 2112.08092, arXiv.org, revised Sep 2023.
    2. Yu-Chin Hsu & Ji-Liang Shiu & Yuanyuan Wan, 2023. "Testing Identification Conditions of LATE in Fuzzy Regression Discontinuity Designs," Working Papers tecipa-761, University of Toronto, Department of Economics.
    3. Bartalotti, Otávio & Kédagni, Désiré & Possebom, Vitor, 2023. "Identifying marginal treatment effects in the presence of sample selection," Journal of Econometrics, Elsevier, vol. 234(2), pages 565-584.
    4. 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.

  9. Lafférs, Lukáš, 2013. "A note on bounding average treatment effects," Economics Letters, Elsevier, vol. 120(3), pages 424-428.

    Cited by:

    1. Laffers, Lukas, 2013. "Identification in Models with Discrete Variables," Discussion Paper Series in Economics 1/2013, Norwegian School of Economics, Department of Economics.

More information

Research fields, statistics, top rankings, if available.

Statistics

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NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 12 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ECM: Econometrics (5) 2013-03-09 2015-03-13 2016-07-02 2020-03-16 2024-07-22. Author is listed
  2. NEP-HEA: Health Economics (3) 2021-02-22 2021-03-22 2021-04-12
  3. NEP-EUR: Microeconomic European Issues (2) 2021-08-09 2021-08-09
  4. NEP-LAB: Labour Economics (2) 2021-08-09 2021-08-23
  5. NEP-TRA: Transition Economics (2) 2021-04-12 2024-07-22
  6. NEP-BIG: Big Data (1) 2024-07-22
  7. NEP-DCM: Discrete Choice Models (1) 2013-03-09
  8. NEP-INV: Investment (1) 2024-07-22
  9. NEP-ISF: Islamic Finance (1) 2021-08-23
  10. NEP-LMA: Labor Markets - Supply, Demand, and Wages (1) 2020-09-14

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