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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. Achim Ahrens & Christian B. Hansen & Mark E. Schaffer & Thomas Wiemann, 2024. "Model Averaging and Double Machine Learning," Papers 2401.01645, arXiv.org.

  2. 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. 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.
    2. Chen, Guowen & Herrera, Ana María & Lugauer, Steven, 2022. "Policy and misallocation: Evidence from Chinese firm-level data," European Economic Review, Elsevier, vol. 149(C).
    3. Emaad Manzoor & Nikhil Malik, 2023. "Designing Effective Music Excerpts," Papers 2309.14475, arXiv.org.
    4. 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.
    5. Caglio, Ariela & Laffitte, Sebastien & Masciandaro, Donato & Ottaviano, Gianmarco Ireo Paolo, 2023. "Has financial fair play changed European football?," LSE Research Online Documents on Economics 121307, London School of Economics and Political Science, LSE Library.
    6. 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.
    7. 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.
    8. Calderón Cerbón Mariana & Cortés Espada Josué Fernando & Pérez Pérez Jorge & Salcedo Alejandrina, 2022. "Disentangling the Effects of Large Minimum Wage and VAT Changes on Prices: Evidence from Mexico," Working Papers 2022-13, Banco de México.
    9. 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.
    10. Luis Alvarez & Bruno Ferman, 2023. "Extensions for Inference in Difference-in-Differences with Few Treated Clusters," Papers 2302.03131, arXiv.org.
    11. Goyal, Raghav & Steinbach, Sandro, 2023. "Agricultural commodity markets in the wake of the black sea grain initiative," Economics Letters, Elsevier, vol. 231(C).
    12. Di, Wenhua & Pattison, Nathaniel, 2023. "Industry Specialization and Small Business Lending," Journal of Banking & Finance, Elsevier, vol. 149(C).
    13. Ander Iraizoz & José M Labeaga, 2022. "Incidence and Avoidance Effects of Spatial Fuel Tax Differentials: Evidence using Regional Tax Variation in Spain," Working Papers halshs-03789430, HAL.
    14. 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).
    15. 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".
    16. Ahn, Soojung & Kim, Dongin & Steinbach, Sandro, 2023. "Global Grain Trade Implications of the Russia-Ukraine War," 2023 Annual Meeting, July 23-25, Washington D.C. 335482, Agricultural and Applied Economics Association.
    17. Roth, Jonathan & Sant’Anna, Pedro H.C. & Bilinski, Alyssa & Poe, John, 2023. "What’s trending in difference-in-differences? A synthesis of the recent econometrics literature," Journal of Econometrics, Elsevier, vol. 235(2), pages 2218-2244.
    18. Shirin, Farzana, 2023. "Does Teacher Salary Support Improve Student Learning Outcomes," 2023 Annual Meeting, July 23-25, Washington D.C. 335793, Agricultural and Applied Economics Association.

  3. 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. 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.
    2. Achim Ahrens & Christian B. Hansen & Mark E. Schaffer & Thomas Wiemann, 2024. "Model Averaging and Double Machine Learning," Papers 2401.01645, arXiv.org.

  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. 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. 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.
    3. Wenjie Wang & Yichong Zhang, 2021. "Wild Bootstrap for Instrumental Variables Regressions with Weak and Few Clusters," Papers 2108.13707, arXiv.org, revised Jan 2024.
    4. 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.
    5. Javier Alejo & Antonio F Galvao & Gabriel Montes-Rojas, 2023. "A first-stage representation for instrumental variables quantile regression," The Econometrics Journal, Royal Economic Society, vol. 26(3), pages 350-377.
    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. Belaïd, Fateh & Rault, Christophe, 2021. "Energy Expenditure in Egypt: Empirical Evidence Based on a Quantile Regression Approach," IZA Discussion Papers 14011, Institute of Labor Economics (IZA).
    2. Arulsamy, Karen & Delaney, Liam, 2022. "The impact of automatic enrolment on the mental health gap in pension participation: evidence from the UK," LSE Research Online Documents on Economics 117274, London School of Economics and Political Science, LSE Library.
    3. Francesca Micocci & Armando Rungi, 2021. "Predicting Exporters with Machine Learning," Working Papers 03/2021, IMT School for Advanced Studies Lucca, revised Jul 2021.
    4. 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.
    5. 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).
    6. 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).
    7. Yun Qiu & Xi Chen & Wei Shi, 2020. "Impacts of social and economic factors on the transmission of coronavirus disease 2019 (COVID-19) in China," Journal of Population Economics, Springer;European Society for Population Economics, vol. 33(4), pages 1127-1172, October.
    8. Santos, Luca J. & Oliveira, Alessandro V.M. & Aldrighi, Dante Mendes, 2021. "Testing the differentiated impact of the COVID-19 pandemic on air travel demand considering social inclusion," Journal of Air Transport Management, Elsevier, vol. 94(C).
    9. 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.
    10. 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.
    11. Li, Qiang & An, Lian & Zhang, Ren, 2023. "Corruption drives brain drain: Cross-country evidence from machine learning," Economic Modelling, Elsevier, vol. 126(C).
    12. 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.
    13. 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.
    14. Theresa Graefe, 2023. "The effect of the Austrian-German bidding zone split on unplanned cross-border flows," Papers 2303.14182, arXiv.org.
    15. 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.
    16. Joshua D. Angrist & Brigham Frandsen, 2022. "Machine Labor," Journal of Labor Economics, University of Chicago Press, vol. 40(S1), pages 97-140.
    17. 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.
    18. Alain Naef & Jacob P. Weber, 2021. "Regional How Powerful is Unannounced, Sterilized Foreign Exchange Intervention?," Working papers 834, Banque de France.
    19. 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.
    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. 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.
    22. Ekaterina Oparina & Caspar Kaiser & Niccolo Gentile & Alexandre Tkatchenko & Andrew E. Clark & Jan-Emmanuel De Neve & Conchita D'Ambrosio, 2022. "Human wellbeing and machine learning," CEP Discussion Papers dp1863, Centre for Economic Performance, LSE.
    23. Yuriy Gorodnichenko & Tho Pham & Oleksandr Talavera, 2019. "Conference Presentations and Academic Publishing," NBER Working Papers 26240, National Bureau of Economic Research, Inc.
    24. Naef, Alain & Weber, Jacob, 2021. "How Powerful Is Unannounced, Sterilized Foreign Exchange Intervention?," SocArXiv bfehz, Center for Open Science.
    25. Collins, Alan & Fan, Jingwen & Mahabir, Aruneema, 2022. "Actual versus ‘natural’ rates of suicide: Evidence from the USA," Economic Modelling, Elsevier, vol. 106(C).
    26. 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.
    27. 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.
    28. 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.
    29. 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.
    30. 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.
    31. 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..
    32. 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).
    33. 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.
    34. 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).
    35. 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.
    36. 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).
    37. 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.
    38. 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).
    39. 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.
    40. 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.
    41. 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.
    42. Mariarosaria Comunale, 2020. "The persistently high rate of suicide in Lithuania: an updated view," Bank of Lithuania Discussion Paper Series 21, Bank of Lithuania.
    43. Yue Cai, 2021. "Measuring Market Power in the IPO Underwriter," Working Papers 2108, Waseda University, Faculty of Political Science and Economics.
    44. 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.
    45. 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).
    46. 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.
    47. 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).
    48. 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.
    49. Saha, Shree & Narayanan, Sudha, 2022. "A simplified measure of nutritional empowerment: Using machine learning to abbreviate the Women’s Empowerment in Nutrition Index (WENI)," World Development, Elsevier, vol. 154(C).
    50. 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.

  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. Yiren Wang & Liangjun Su & Yichong Zhang, 2022. "Low-rank Panel Quantile Regression: Estimation and Inference," Papers 2210.11062, arXiv.org.
    2. Ke Miao & Peter C.B. Phillips & Liangjun Su, 2020. "High-Dimensional VARs with Common Factors," Cowles Foundation Discussion Papers 2252, Cowles Foundation for Research in Economics, Yale University.
    3. Jianqing Fan & Kunpeng Li & Yuan Liao, 2020. "Recent Developments on Factor Models and its Applications in Econometric Learning," Papers 2009.10103, arXiv.org.
    4. Junlong Feng, 2019. "Regularized Quantile Regression with Interactive Fixed Effects," Papers 1911.00166, arXiv.org, revised Mar 2021.
    5. Alexandre Belloni & Mingli Chen & Oscar Hernan Madrid Padilla & Zixuan & Wang, 2019. "High Dimensional Latent Panel Quantile Regression with an Application to Asset Pricing," Papers 1912.02151, arXiv.org, revised Aug 2022.

  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. Simon Freyaldenhoven & Christian Hansen & Jorge Pérez Pérez & Jesse M. Shapiro, 2021. "Visualization, Identification, and Estimation in the Linear Panel Event-Study Design," NBER Working Papers 29170, National Bureau of Economic Research, Inc.
    2. Uehleke, Reinhard & Petrick, Martin & Hüttel, Silke, 2022. "Evaluations of agri-environmental schemes based on observational farm data: The importance of covariate selection," Land Use Policy, Elsevier, vol. 114(C).
    3. Aksoy, Cevat Giray & Carpenter, Christopher S. & De Haas, Ralph & Tran, Kevin, 2018. "Do Laws Shape Attitudes? Evidence from Same-Sex Relationship Recognition Policies in Europe," IZA Discussion Papers 11743, Institute of Labor Economics (IZA).
    4. Agyeman, Stephen Duah & Lin, Boqiang, 2023. "Electricity industry (de)regulation and innovation in negative-emission technologies: How do market liberalization influences climate change mitigation?," Energy, Elsevier, vol. 270(C).
    5. 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).
    6. Anderson, Michael L. & Davis, Lucas W., 2020. "An empirical test of hypercongestion in highway bottlenecks," Journal of Public Economics, Elsevier, vol. 187(C).
    7. Uchenna, Efobi & Joseph, Ajefu, 2024. "Exploring the Spillover Effects of Internally Displaced Settlements on the Wellbeing of Children of the Locales," GLO Discussion Paper Series 1381, Global Labor Organization (GLO).
    8. Tal Gross & Raymond Kluender & Feng Liu & Matthew J. Notowidigdo & Jialan Wang, 2019. "The Economic Consequences of Bankruptcy Reform," NBER Working Papers 26254, National Bureau of Economic Research, Inc.
    9. Perez Perez, Jorge, 2020. "City Minimum Wages and Spatial Equilibrium Effects," SocArXiv fpx9e, Center for Open Science.
    10. Ferentinos, Konstantinos & Gibberd, Alex & Guin, Benjamin, 2021. "Climate policy and transition risk in the housing market," Bank of England working papers 918, Bank of England.
    11. Daniel G. Garrett & Eric Ohrn & Juan Carlos Suárez Serrato, 2020. "Tax Policy and Local Labor Market Behavior," American Economic Review: Insights, American Economic Association, vol. 2(1), pages 83-100, March.
    12. Damian Clarke & Kathya Tapia Schythe, 2020. "Implementing the Panel Event Study," Working Papers wp497, University of Chile, Department of Economics.
    13. Sumit Agarwal & Slava Mikhed & Barry Scholnick & Man Zhang, 2022. "Reducing Strategic Default in a Financial Crisis," Working Papers 21-36, Federal Reserve Bank of Philadelphia.
    14. John McHale & Jason Harold & Jen-Chung Mei & Akhil Sasidharan & Anil Yadav, 2023. "Stars as catalysts: an event-study analysis of the impact of star-scientist recruitment on local research performance in a small open economy," Journal of Economic Geography, Oxford University Press, vol. 23(2), pages 343-369.
    15. Parra-Cely, Sergio & Zanoni, Wladimir, 2022. "The Labor Market Worsening Effects of a Resource Bust: Evidence from the Crude Oil Price Shock in Ecuador," IDB Publications (Working Papers) 12268, Inter-American Development Bank.
    16. Ferentinos, Konstantinos & Gibberd, Alex & Guin, Benjamin, 2023. "Stranded houses? The price effect of a minimum energy efficiency standard," Energy Economics, Elsevier, vol. 120(C).
    17. Sofiyandi, Yusuf & Kurniawan, Yusuf Reza & Yudhistira, Muhammad Halley, 2023. "The impact of maritime logistics subsidy on food prices: Evidence from Indonesia," Economic Analysis and Policy, Elsevier, vol. 79(C), pages 1026-1045.
    18. Li, Pei & Lu, Yi & Wang, Jin, 2020. "The effects of fuel standards on air pollution: Evidence from China," Journal of Development Economics, Elsevier, vol. 146(C).
    19. Clarke, Damian & Mühlrad, Hanna, 2018. "Abortion Laws and Women's Health," IZA Discussion Papers 11890, Institute of Labor Economics (IZA).
    20. Javorcik, Beata & Kett, Ben & Stapleton, Katherine & O'Kane, Layla, 2019. "Unravelling Trade Integration: Local Labour Market Effects of the Brexit Vote," CEPR Discussion Papers 14222, C.E.P.R. Discussion Papers.
    21. Vilma Todri, 2022. "Frontiers: The Impact of Ad-Blockers on Online Consumer Behavior," Marketing Science, INFORMS, vol. 41(1), pages 7-18, January.
    22. Myungkou Shin, 2022. "Finitely Heterogeneous Treatment Effect in Event-study," Papers 2204.02346, arXiv.org, revised Feb 2024.
    23. Ahn, Soojung & Steinbach, Sandro, 2022. "COVID-19 Trade Actions and Their Impact on the Agricultural and Food Sector," 2022 Allied Social Sciences Association (ASSA) Annual Meeting (Virtual), January 7-9, 2022 316789, Agricultural and Applied Economics Association.
    24. Torrini, Irene & Lucifora, Claudio & Russo, Antonio Giampiero, 2023. "The long-term effects of hospitalization on health care expenditures: An empirical analysis for the young-old population in Lombardy," Health Policy, Elsevier, vol. 132(C).
    25. Clément de Chaisemartin & Xavier D’haultfœuille, 2022. "Two-Way Fixed Effects and Differences-in-Differences with Heterogeneous Treatment Effects: A Survey," SciencePo Working papers Main hal-03873885, HAL.
    26. González-Pampillón, Nicolás, 2022. "Spillover effects from new housing supply," Regional Science and Urban Economics, Elsevier, vol. 92(C).
    27. Marco Francesconi & Jonathan James, 2021. "None for the Road? Stricter Drink Driving Laws and Road Accidents," CESifo Working Paper Series 9159, CESifo.
    28. Schmidheiny, Kurt & Siegloch, Sebastian, 2019. "On Event Study Designs and Distributed-Lag Models: Equivalence, Generalization and Practical Implications," IZA Discussion Papers 12079, Institute of Labor Economics (IZA).
    29. 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).
    30. Hui Chen & Zhuo Chen & Zhiguo He & Jinyu Liu & Rengming Xie, 2019. "Pledgeability and Asset Prices: Evidence from the Chinese Corporate Bond Markets," NBER Working Papers 26520, National Bureau of Economic Research, Inc.
    31. Rodrigo Adão & Martin Beraja & Nitya Pandalai-Nayar, 2020. "Technological Transitions with Skill Heterogeneity Across Generations," NBER Working Papers 26625, National Bureau of Economic Research, Inc.
    32. Fernando Díaz & Pablo A Henríquez, 2021. "Social sentiment segregation: Evidence from Twitter and Google Trends in Chile during the COVID-19 dynamic quarantine strategy," PLOS ONE, Public Library of Science, vol. 16(7), pages 1-29, July.
    33. Hanming Fang & Yongqin Wang & Xian Wu, 2020. "The Collateral Channel of Monetary Policy: Evidence from China," PIER Working Paper Archive 20-008, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    34. Jonathan Roth & Pedro H. C. Sant’Anna, 2023. "Efficient Estimation for Staggered Rollout Designs," Journal of Political Economy Microeconomics, University of Chicago Press, vol. 1(4), pages 669-709.
    35. Guzman, Jorge, 2020. "The Direct Effect of Corporate Law on Entrepreneurship," SocArXiv 967ph, Center for Open Science.
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    65. Salemi, Colette, 2021. "Refugee camps and deforestation in Sub-Saharan Africa," Journal of Development Economics, Elsevier, vol. 152(C).
    66. Nicolas Gonzalez-Pampillon & Gonzalo Nunez-Chaim & Henry G. Overman, 2022. "The economic impacts of the UK's eat out to help out scheme," CEP Discussion Papers dp1865, Centre for Economic Performance, LSE.
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    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," Economics Series Working Papers 984, University of Oxford, Department of Economics.
    2. 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.

  10. 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. Kea BARET, 2021. "Fiscal rules’ compliance and Social Welfare," Working Papers of BETA 2021-50, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    2. Baris Ata & Alexandre Belloni & Ozan Candogan, 2018. "Latent Agents in Networks: Estimation and Targeting," Papers 1808.04878, arXiv.org, revised Jan 2022.
    3. Victor Chernozhukov & Chen Huang & Weining Wang, 2021. "Uniform Inference on High-dimensional Spatial Panel Networks," Papers 2105.07424, arXiv.org, revised Sep 2023.
    4. 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.
    5. 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.
    6. Andrii Babii, 2022. "High-Dimensional Mixed-Frequency IV Regression," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(4), pages 1470-1483, October.
    7. Denis Chetverikov & Daniel Wilhelm & Dongwoo Kim, 2018. "An adaptive test of stochastic monotonicity," CeMMAP working papers CWP24/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    8. 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.
    9. Masayuki Sawada & Kohei Kawaguchi, 2020. "Estimating High-Dimensional Discrete Choice Model of Differentiated Products with Random Coefficients," Papers 2004.08791, arXiv.org.
    10. Kea BARET, 2021. "Fiscal rules’ compliance and Social Welfare," Working Papers of BETA 2021-38, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    11. Myung Hwan Seo & Yoichi Arai & Taisuke Otsu, 2021. "Regression Discontinuity Design with Potentially Many Covariates," Working Paper Series no142, Institute of Economic Research, Seoul National University.
    12. Manu Navjeevan, 2023. "An Identification and Dimensionality Robust Test for Instrumental Variables Models," Papers 2311.14892, arXiv.org.
    13. Adam Baybutt & Manu Navjeevan, 2023. "Doubly-Robust Inference for Conditional Average Treatment Effects with High-Dimensional Controls," Papers 2301.06283, arXiv.org.
    14. Saulius Jokubaitis & Remigijus Leipus, 2022. "Asymptotic Normality in Linear Regression with Approximately Sparse Structure," Mathematics, MDPI, vol. 10(10), pages 1-28, May.
    15. 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.
    16. Xinwei Ma & Jingshen Wang, 2018. "Robust Inference Using Inverse Probability Weighting," Papers 1810.11397, arXiv.org, revised May 2019.

  11. 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. Henrika Langen & Martin Huber, 2022. "How causal machine learning can leverage marketing strategies: Assessing and improving the performance of a coupon campaign," Papers 2204.10820, arXiv.org, revised Jun 2022.
    2. Combes, Pierre-Philippe & Gobillon, Laurent & Zylberberg, Yanos, 2022. "Urban economics in a historical perspective: Recovering data with machine learning," Regional Science and Urban Economics, Elsevier, vol. 94(C).
    3. Amit Sharma & Emre Kiciman, 2020. "DoWhy: An End-to-End Library for Causal Inference," Papers 2011.04216, arXiv.org.
    4. William C. Horrace & Hyunseok Jung & Shane Sanders, 2020. "Network Competition and Team Chemistry in the NBA," Center for Policy Research Working Papers 226, Center for Policy Research, Maxwell School, Syracuse University.
    5. 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.
    6. Jeremiah Jones & Ashkan Ertefaie & Susan M. Shortreed, 2023. "Rejoinder to “Reader reaction to ‘Outcome‐adaptive Lasso: Variable selection for causal inference’ by Shortreed and Ertefaie (2017)”," Biometrics, The International Biometric Society, vol. 79(1), pages 521-525, March.
    7. Yu-Chin Hsu & Martin Huber & Ying-Ying Lee & Chu-An Liu, 2021. "Testing Monotonicity of Mean Potential Outcomes in a Continuous Treatment with High-Dimensional Data," Papers 2106.04237, arXiv.org, revised Aug 2022.
    8. 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).
    9. Elek, Péter & Bíró, Anikó, 2021. "Regional differences in diabetes across Europe – regression and causal forest analyses," Economics & Human Biology, Elsevier, vol. 40(C).
    10. 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," SciencePo Working papers Main hal-03813557, HAL.
    11. Jiabei Yang & Issa J. Dahabreh & Jon A. Steingrimsson, 2022. "Causal interaction trees: Finding subgroups with heterogeneous treatment effects in observational data," Biometrics, The International Biometric Society, vol. 78(2), pages 624-635, June.
    12. Victor Chernozhukov & Carlos Cinelli & Whitney Newey & Amit Sharma & Vasilis Syrgkanis, 2021. "Long Story Short: Omitted Variable Bias in Causal Machine Learning," Papers 2112.13398, arXiv.org, revised Nov 2023.
    13. Su, Miaomiao & Wang, Ruoyu & Wang, Qihua, 2022. "A two-stage optimal subsampling estimation for missing data problems with large-scale data," Computational Statistics & Data Analysis, Elsevier, vol. 173(C).
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    15. Victor Chernozhukov & Chen Huang & Weining Wang, 2021. "Uniform Inference on High-dimensional Spatial Panel Networks," Papers 2105.07424, arXiv.org, revised Sep 2023.
    16. Hidehiko Ichimura & Whitney K. Newey, 2022. "The influence function of semiparametric estimators," Quantitative Economics, Econometric Society, vol. 13(1), pages 29-61, January.
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    18. Giacomo De Giorgi & Costanza Naguib, 2022. "Life after Default: Credit Hardship and its Effects," Diskussionsschriften dp2206, Universitaet Bern, Departement Volkswirtschaft.
    19. Uehleke, Reinhard & Petrick, Martin & Hüttel, Silke, 2022. "Evaluations of agri-environmental schemes based on observational farm data: The importance of covariate selection," Land Use Policy, Elsevier, vol. 114(C).
    20. Masahiro Kato & Yusuke Kaneko, 2020. "Off-Policy Evaluation of Bandit Algorithm from Dependent Samples under Batch Update Policy," Papers 2010.13554, arXiv.org.
    21. Andrew B. Martinez, 2020. "Forecast Accuracy Matters for Hurricane Damages," Working Papers 2020-003, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    22. Riccardo Di Francesco, 2022. "Aggregation Trees," CEIS Research Paper 546, Tor Vergata University, CEIS, revised 20 Nov 2023.
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    24. Okyere, Charles Yaw & Kornher, Lukas, 2022. "Carbon Farming Training and Welfare: Evidence from Northern Ghana," Discussion Papers 324738, University of Bonn, Center for Development Research (ZEF).
    25. 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.
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    27. 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.
    28. Sören Blomquist & Anil Kumar & Che-Yuan Liang & Whitney Newey, 2023. "Nonlinear Budget Set Regressions for the Random Utility Model," NBER Working Papers 31194, National Bureau of Economic Research, Inc.
    29. Aur'elien Sallin, 2021. "Estimating returns to special education: combining machine learning and text analysis to address confounding," Papers 2110.08807, arXiv.org, revised Feb 2022.
    30. Pedro Carneiro & Sokbae Lee & Daniel Wilhelm, 2016. "Optimal Data Collection for Randomized Control Trials," Papers 1603.03675, arXiv.org, revised Aug 2016.
    31. Biewen, Martin & Fitzenberger, Bernd & Seckler, Matthias, 2020. "Counterfactual quantile decompositions with selection correction taking into account Huber/Melly (2015): An application to the German gender wage gap," Labour Economics, Elsevier, vol. 67(C).
    32. 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.
    33. 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.
    34. Juodis, Artūras & Sarafidis, Vasilis, 2022. "An incidental parameters free inference approach for panels with common shocks," Journal of Econometrics, Elsevier, vol. 229(1), pages 19-54.
    35. Jiafeng Chen & Daniel L. Chen & Greg Lewis, 2020. "Mostly Harmless Machine Learning: Learning Optimal Instruments in Linear IV Models," Papers 2011.06158, arXiv.org, revised Jun 2021.
    36. 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.
    37. Qingliang Fan & Zijian Guo & Ziwei Mei & Cun-Hui Zhang, 2023. "Uniform Inference for Nonlinear Endogenous Treatment Effects with High-Dimensional Covariates," Papers 2310.08063, arXiv.org, revised Oct 2023.
    38. Ying Liu & Haoran Zhao & Jieguang Sun & Yahui Tang, 2022. "Digital Inclusive Finance and Family Wealth: Evidence from LightGBM Approach," Sustainability, MDPI, vol. 14(22), pages 1-19, November.
    39. Philipp F. M. Baumann & Michael Schomaker & Enzo Rossi, 2020. "Estimating the Effect of Central Bank Independence on Inflation Using Longitudinal Targeted Maximum Likelihood Estimation," Papers 2003.02208, arXiv.org, revised May 2021.
    40. 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.
    41. 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.
    42. Sven Klaassen & Jannis Kuck & Martin Spindler & Victor Chernozhukov, 2018. "Uniform Inference in High-Dimensional Gaussian Graphical Models," Papers 1808.10532, arXiv.org, revised Dec 2018.
    43. Knaus, Michael C., 2020. "Double Machine Learning Based Program Evaluation under Unconfoundedness," IZA Discussion Papers 13051, Institute of Labor Economics (IZA).
    44. Giglio, Stefano & Feng, Guanhao & Xiu, Dacheng, 2020. "Taming the Factor Zoo: A Test of New Factors," CEPR Discussion Papers 14266, C.E.P.R. Discussion Papers.
    45. Huber Martin & Wüthrich Kaspar, 2019. "Local Average and Quantile Treatment Effects Under Endogeneity: A Review," Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-27, January.
    46. Helmut Farbmacher & Martin Huber & Luk'av{s} Laff'ers & Henrika Langen & Martin Spindler, 2020. "Causal mediation analysis with double machine learning," Papers 2002.12710, arXiv.org, revised Feb 2021.
    47. Miruna Oprescu & Vasilis Syrgkanis & Zhiwei Steven Wu, 2018. "Orthogonal Random Forest for Causal Inference," Papers 1806.03467, arXiv.org, revised Sep 2019.
    48. Kotlyarova, Yulia & Schafgans, Marcia M.A. & Zinde-Walsh, Victoria, 2021. "Rates of expansions for functional estimators," LSE Research Online Documents on Economics 113436, London School of Economics and Political Science, LSE Library.
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    50. Julia Hatamyar & Noemi Kreif, 2023. "Policy Learning with Rare Outcomes," Papers 2302.05260, arXiv.org, revised Oct 2023.
    51. Mats J. Stensrud & Miguel A. Hernán & Eric J Tchetgen Tchetgen & James M. Robins & Vanessa Didelez & Jessica G. Young, 2021. "A generalized theory of separable effects in competing event settings," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 27(4), pages 588-631, October.
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    53. 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.
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    57. 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.
    58. 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," IZA Discussion Papers 12526, Institute of Labor Economics (IZA).
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    60. Minkyung Kim & K. Sudhir & Kosuke Uetake, 2022. "A Structural Model of a Multitasking Salesforce: Incentives, Private Information, and Job Design," Management Science, INFORMS, vol. 68(6), pages 4602-4630, June.
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    399. Johann Pfitzinger, 2021. "An Interpretable Neural Network for Parameter Inference," Papers 2106.05536, arXiv.org.
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    402. Alejandro Sanchez-Becerra, 2023. "Robust inference for the treatment effect variance in experiments using machine learning," Papers 2306.03363, arXiv.org.
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    410. Martin Hodula & Milan Szabo & Lukas Pfeifer & Martin Melecky, 2022. "Cooling the Mortgage Loan Market: The Effect of Recommended Borrower-Based Limits on New Mortgage Lending," Working Papers 2022/3, Czech National Bank.
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    Cited by:

    1. Baris Ata & Alexandre Belloni & Ozan Candogan, 2018. "Latent Agents in Networks: Estimation and Targeting," Papers 1808.04878, arXiv.org, revised Jan 2022.
    2. Victor Chernozhukov & Chen Huang & Weining Wang, 2021. "Uniform Inference on High-dimensional Spatial Panel Networks," Papers 2105.07424, arXiv.org, revised Sep 2023.
    3. 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.
    4. Christoph Breunig & Enno Mammen & Anna Simoni, 2018. "Ill-posed Estimation in High-Dimensional Models with Instrumental Variables," Papers 1806.00666, arXiv.org, revised Aug 2020.
    5. Caner, Mehmet, 2023. "Generalized linear models with structured sparsity estimators," Journal of Econometrics, Elsevier, vol. 236(2).

  13. 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 Dec 2017.

    Cited by:

    1. Amit Sharma & Emre Kiciman, 2020. "DoWhy: An End-to-End Library for Causal Inference," Papers 2011.04216, arXiv.org.
    2. 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.
    3. 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," SciencePo Working papers Main hal-03813557, HAL.
    4. Victor Chernozhukov & Carlos Cinelli & Whitney Newey & Amit Sharma & Vasilis Syrgkanis, 2021. "Long Story Short: Omitted Variable Bias in Causal Machine Learning," Papers 2112.13398, arXiv.org, revised Nov 2023.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
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    12. Huber Martin & Wüthrich Kaspar, 2019. "Local Average and Quantile Treatment Effects Under Endogeneity: A Review," Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-27, January.
    13. Miruna Oprescu & Vasilis Syrgkanis & Zhiwei Steven Wu, 2018. "Orthogonal Random Forest for Causal Inference," Papers 1806.03467, arXiv.org, revised Sep 2019.
    14. Julia Hatamyar & Noemi Kreif, 2023. "Policy Learning with Rare Outcomes," Papers 2302.05260, arXiv.org, revised Oct 2023.
    15. Aristide Houndetoungan & Abdoul Haki Maoude, 2024. "Inference for Two-Stage Extremum Estimators," Papers 2402.05030, arXiv.org.
    16. 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.
    17. 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.
    18. 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.
    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. 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.
    21. 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.
    22. 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).
    23. 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.
    24. Jiaming Mao & Zhesheng Zheng, 2020. "Structural Regularization," Papers 2004.12601, arXiv.org, revised Jun 2020.
    25. Su, Liangjun & Ura, Takuya & Zhang, Yichong, 2019. "Non-separable models with high-dimensional data," Journal of Econometrics, Elsevier, vol. 212(2), pages 646-677.
    26. Yuya Sasaki & Takuya Ura & Yichong Zhang, 2020. "Unconditional Quantile Regression with High Dimensional Data," Papers 2007.13659, arXiv.org, revised Feb 2022.
    27. 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.
    28. 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).
    29. Sant’Anna, Pedro H.C. & Zhao, Jun, 2020. "Doubly robust difference-in-differences estimators," Journal of Econometrics, Elsevier, vol. 219(1), pages 101-122.
    30. 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).
    31. 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).
    32. Jiaming Mao & Jingzhi Xu, 2020. "Ensemble Learning with Statistical and Structural Models," Papers 2006.05308, arXiv.org.
    33. Ricardo P. Masini & Marcelo C. Medeiros & Eduardo F. Mendes, 2023. "Machine learning advances for time series forecasting," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 76-111, February.
    34. Jonas Metzger, 2022. "Adversarial Estimators," Papers 2204.10495, arXiv.org, revised Jun 2022.
    35. 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.
    36. 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.
    37. Ruoxuan Xiong & Allison Koenecke & Michael Powell & Zhu Shen & Joshua T. Vogelstein & Susan Athey, 2021. "Federated Causal Inference in Heterogeneous Observational Data," Papers 2107.11732, arXiv.org, revised Apr 2023.
    38. Anna Baiardi & Andrea A. Naghi, 2021. "The Value Added of Machine Learning to Causal Inference: Evidence from Revisited Studies," Papers 2101.00878, arXiv.org.
    39. Yong Bian & Xiqian Wang & Qin Zhang, 2023. "How Does China's Household Portfolio Selection Vary with Financial Inclusion?," Papers 2311.01206, arXiv.org.
    40. 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.
    41. 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.
    42. Phillip Heiler, 2020. "Efficient Covariate Balancing for the Local Average Treatment Effect," Papers 2007.04346, arXiv.org.
    43. Vira Semenova, 2018. "Machine Learning for Dynamic Discrete Choice," Papers 1808.02569, arXiv.org, revised Nov 2018.
    44. 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.
    45. Matt Goldman & Brian Quistorff, 2018. "Pricing Engine: Estimating Causal Impacts in Real World Business Settings," Papers 1806.03285, arXiv.org, revised Jun 2018.
    46. Victor Chernozhukov & Mert Demirer & Esther Duflo & Ivan Fernandez-Val, 2017. "Generic machine learning inference on heterogenous treatment effects in randomized experiments," CeMMAP working papers 61/17, Institute for Fiscal Studies.
    47. 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.
    48. 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.
    49. 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.
    50. 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.
    51. 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.
    52. Ziwei Mei & Zhentao Shi, 2022. "On LASSO for High Dimensional Predictive Regression," Papers 2212.07052, arXiv.org, revised Jan 2024.
    53. 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.
    54. Vira Semenova, 2017. "Debiased Machine Learning of Set-Identified Linear Models," Papers 1712.10024, arXiv.org, revised Dec 2022.
    55. 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.
    56. 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.
    57. 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.
    58. Victor Chernozhukov & Whitney Newey & Vira Semenova, 2019. "Inference on weighted average value function in high-dimensional state space," Papers 1908.09173, arXiv.org.
    59. Gazeaud, Jules & Khan, Nausheen & Mvukiyehe, Eric & Sterck, Olivier, 2023. "With or without him? Experimental evidence on cash grants and gender-sensitive trainings in Tunisia," Journal of Development Economics, Elsevier, vol. 165(C).
    60. 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.
    61. 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).
    62. Dmitry Arkhangelsky & Guido Imbens, 2023. "Causal Models for Longitudinal and Panel Data: A Survey," Papers 2311.15458, arXiv.org, revised Mar 2024.
    63. 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.
    64. Fernando Delbianco & Fernando Tohmé, 2023. "Individualized Conformal," Working Papers 247, Red Nacional de Investigadores en Economía (RedNIE).
    65. 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.
    66. Elliott Ash & Daniel L. Chen & Sergio Galletta, 2022. "Measuring Judicial Sentiment: Methods and Application to US Circuit Courts," Post-Print hal-03597819, HAL.
    67. 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.
    68. Dongcheng Zhang & Kunpeng Zhang, 2020. "Weighting-Based Treatment Effect Estimation via Distribution Learning," Papers 2012.13805, arXiv.org, revised May 2023.
    69. 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.
    70. 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.
    71. Marica Valente, 2021. "Policy Evaluation of Waste Pricing Programs Using Heterogeneous Causal Effect Estimation," Discussion Papers of DIW Berlin 1980, DIW Berlin, German Institute for Economic Research.
    72. 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.
    73. 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.
    74. 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.
    75. 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.
    76. Sven Klaassen & Jannis Kueck & Martin Spindler, 2017. "Transformation Models in High-Dimensions," Papers 1712.07364, arXiv.org.

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

    Cited by:

    1. Pawel Dlotko & Simon Rudkin & Wanling Qiu, 2019. "Topologically Mapping the Macroeconomy," Papers 1911.10476, arXiv.org.
    2. 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.
    3. 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.
    4. Huber, Martin & Imhof, David, 2019. "Machine learning with screens for detecting bid-rigging cartels," International Journal of Industrial Organization, Elsevier, vol. 65(C), pages 277-301.
    5. 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.
    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. Hannes Wallimann & David Imhof & Martin Huber, 2023. "A Machine Learning Approach for Flagging Incomplete Bid-Rigging Cartels," Computational Economics, Springer;Society for Computational Economics, vol. 62(4), pages 1669-1720, December.
    8. 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).
    9. 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.
    10. Altman, Edward I. & Balzano, Marco & Giannozzi, Alessandro & Srhoj, Stjepan, 2022. "Revisiting SME default predictors: The Omega Score," GLO Discussion Paper Series 1207, Global Labor Organization (GLO).
    11. 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.
    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. 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.
    14. 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.
    15. 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.
    16. 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.
    17. Marica Valente & Timm Gries & Lorenzo Trapani, 2023. "Informal employment from migration shocks," Working Papers 2023-09, Faculty of Economics and Statistics, Universität Innsbruck.
    18. Harold D. Chiang, 2018. "Many Average Partial Effects: with An Application to Text Regression," Papers 1812.09397, arXiv.org, revised Jan 2022.
    19. 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 Feb 2024.

  15. 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. 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.
    2. Shi, Zhentao & Huang, Jingyi, 2023. "Forward-selected panel data approach for program evaluation," Journal of Econometrics, Elsevier, vol. 234(2), pages 512-535.
    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 61/17, Institute for Fiscal Studies.
    4. Jean-Pierre Dubé & Sanjog Misra, 2017. "Personalized Pricing and Consumer Welfare," NBER Working Papers 23775, National Bureau of Economic Research, Inc.
    5. Victor Chernozhukov & Mert Demirer & Esther Duflo & Iv'an Fern'andez-Val, 2017. "Fisher-Schultz Lecture: Generic Machine Learning Inference on Heterogenous Treatment Effects in Randomized Experiments, with an Application to Immunization in India," Papers 1712.04802, arXiv.org, revised Oct 2023.

  16. 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.

    Cited by:

    1. 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.
    2. 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.
    3. Chernozhukov, Victor & Wüthrich, Kaspar & Zhu, Yinchu, 2021. "An Exact and Robust Conformal Inference Method for Counterfactual and Synthetic Controls," University of California at San Diego, Economics Working Paper Series qt90m9d66s, Department of Economics, UC San Diego.
    4. Philippe Goulet Coulombe, 2020. "The Macroeconomy as a Random Forest," Papers 2006.12724, arXiv.org, revised Mar 2021.
    5. Jad Beyhum & Jonas Striaukas, 2023. "Sparse plus dense MIDAS regressions and nowcasting during the COVID pandemic," Papers 2306.13362, arXiv.org, revised Dec 2023.
    6. Smeekes, Stephan & Wijler, Etienne, 2018. "Macroeconomic forecasting using penalized regression methods," International Journal of Forecasting, Elsevier, vol. 34(3), pages 408-430.
    7. Michael Vogt & Christopher Walsh & Oliver Linton, 2022. "CCE Estimation of High-Dimensional Panel Data Models with Interactive Fixed Effects," Papers 2206.12152, arXiv.org.
    8. 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.
    9. 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.
    10. 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.

  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. Alexei Alexandrov & Russell Pittman & Olga Ukhaneva, 2018. "Pricing of Complements in the U.S. Freight Railroads: Cournot Versus Coase," EAG Discussions Papers 201801, Department of Justice, Antitrust Division.
    2. 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.
    3. 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.
    4. Victor Chernozhukov & Wolfgang Härdle & Chen Huang & Weining Wang, 2019. "LASSO-Driven Inference in Time and Space," CeMMAP working papers CWP20/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Athey, Susan & Tibshirani, Julie & Wager, Stefan, 2017. "Generalized Random Forests," Research Papers 3575, Stanford University, Graduate School of Business.
    6. 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.
    7. Christian Hansen & Yuan Liao, 2016. "The Factor-Lasso and K-Step Bootstrap Approach for Inference in High-Dimensional Economic Applications," Departmental Working Papers 201610, Rutgers University, Department of Economics.
    8. 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.
    9. Victor Chernozhukov & Juan Carlos Escanciano & Hidehiko Ichimura & Whitney K. Newey & James M. Robins, 2018. "Locally robust semiparametric estimation," CeMMAP working papers CWP30/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. 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.
    11. Zhengyuan Zhou & Susan Athey & Stefan Wager, 2023. "Offline Multi-Action Policy Learning: Generalization and Optimization," Operations Research, INFORMS, vol. 71(1), pages 148-183, January.
    12. Jiaming Mao & Zhesheng Zheng, 2020. "Structural Regularization," Papers 2004.12601, arXiv.org, revised Jun 2020.
    13. Susan Athey & Stefan Wager, 2017. "Policy Learning with Observational Data," Papers 1702.02896, arXiv.org, revised Sep 2020.
    14. 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.
    15. Damian Kozbur, 2015. "Testing-Based Forward Model Selection," ECON - Working Papers 283, Department of Economics - University of Zurich, revised Apr 2018.
    16. Jiaming Mao & Jingzhi Xu, 2020. "Ensemble Learning with Statistical and Structural Models," Papers 2006.05308, arXiv.org.
    17. 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. Christian Hansen & Damian Kozbur & Sanjog Misra, 2016. "Targeted undersmoothing," ECON - Working Papers 282, Department of Economics - University of Zurich, revised Apr 2018.
    19. Dmitry Arkhangelsky & Guido W. Imbens, 2019. "The Role of the Propensity Score in Fixed Effect Models," Working Papers wp2019_1905, CEMFI.
    20. Mochen Yang & Edward McFowland III & Gordon Burtch & Gediminas Adomavicius, 2020. "Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem," Papers 2012.10790, arXiv.org.
    21. 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.
    22. Lester Mackey & Vasilis Syrgkanis & Ilias Zadik, 2017. "Orthogonal Machine Learning: Power and Limitations," Papers 1711.00342, arXiv.org, revised Aug 2018.
    23. Susan Athey & Guido W. Imbens, 2017. "The State of Applied Econometrics: Causality and Policy Evaluation," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 3-32, Spring.
    24. Jean-Pierre Dubé & Sanjog Misra, 2017. "Personalized Pricing and Consumer Welfare," NBER Working Papers 23775, National Bureau of Economic Research, Inc.
    25. 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.
    26. 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.
    27. 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.
    28. 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.
    29. 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.
    30. Khashayar Khosravi & Greg Lewis & Vasilis Syrgkanis, 2019. "Non-Parametric Inference Adaptive to Intrinsic Dimension," Papers 1901.03719, arXiv.org, revised Jun 2019.
    31. 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.

  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," Papers 1502.03155, arXiv.org, revised Mar 2015.

  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. Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2019. "lassopack: Model selection and prediction with regularized regression in Stata," Papers 1901.05397, arXiv.org.
    2. 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.
    3. 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.
    4. Andreas Menzel & Christopher Woodruff, 2019. "Gender Wage Gaps and Worker Mobility: Evidence from the Garment Sector in Bangladesh," NBER Working Papers 25982, National Bureau of Economic Research, Inc.
    5. 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.
    6. 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.
    7. Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen, 2013. "Program evaluation with high-dimensional data," CeMMAP working papers 77/13, Institute for Fiscal Studies.
    8. Alexandre Belloni & Mingli Chen & Victor Chernozhukov, 2016. "Quantile Graphical Models: Prediction and Conditional Independence with Applications to Systemic Risk," Papers 1607.00286, arXiv.org, revised Oct 2019.
    9. 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.
    10. 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.
    11. Ofori, Isaac K. & Quaidoo, Christopher & Ofori, Pamela E., 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, issue forthcomi.
    12. Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Post-selection and post-regularization inference in linear models with many controls and instruments," CeMMAP working papers 02/15, Institute for Fiscal Studies.
    13. 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.
    14. 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.
    15. Santos, Luca J. & Oliveira, Alessandro V.M. & Aldrighi, Dante Mendes, 2021. "Testing the differentiated impact of the COVID-19 pandemic on air travel demand considering social inclusion," Journal of Air Transport Management, Elsevier, vol. 94(C).
    16. Christoph Breunig & Enno Mammen & Anna Simoni, 2018. "Ill-posed Estimation in High-Dimensional Models with Instrumental Variables," Papers 1806.00666, arXiv.org, revised Aug 2020.
    17. Steven Shuye Wang & Kuan Xu & Hao Zhang, 2019. "A Microstructure Study of Circuit Breakers in the Chinese Stock Markets," Working Papers daleconwp2019-02, Dalhousie University, Department of Economics.
    18. Gal Amedi, 2023. "The Determinants of the Transit Accessibility Premium," Bank of Israel Working Papers 2023.12, Bank of Israel.
    19. 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.
    20. 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.
    21. Samarth Gupta, 2023. "Model-Selection Inference for Causal Impact of Clusters and Collaboration on MSMEs in India," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 21(3), pages 641-662, September.
    22. Joshua D. Angrist & Brigham Frandsen, 2022. "Machine Labor," Journal of Labor Economics, University of Chicago Press, vol. 40(S1), pages 97-140.
    23. Su, Liangjun & Ura, Takuya & Zhang, Yichong, 2019. "Non-separable models with high-dimensional data," Journal of Econometrics, Elsevier, vol. 212(2), pages 646-677.
    24. 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.
    25. 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).
    26. 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).
    27. 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.
    28. Marianne BLÉHAUT & Xavier D'HAULTFOEUILLE & Jérémy L'HOUR & Alexandre B. TSYBAKOV, 2020. "An alternative to synthetic control for models with many covariates under sparsity," Working Papers 2020-17, Center for Research in Economics and Statistics.
    29. 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.
    30. 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.
    31. Seojeong Lee & Youngki Shin, 2018. "Optimal Estimation with Complete Subsets of Instruments," Department of Economics Working Papers 2018-15, McMaster University.
    32. 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.
    33. Ahrens, Achim & Hansen, Christian B. & Schaffer, Mark E & Wiemann, Thomas, 2023. "ddml: Double/Debiased Machine Learning in Stata," IZA Discussion Papers 15963, Institute of Labor Economics (IZA).
    34. 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.
    35. Seojeong Lee & Youngki Shin, 2021. "Complete subset averaging with many instruments," The Econometrics Journal, Royal Economic Society, vol. 24(2), pages 290-314.
    36. 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.
    37. Tomaso Duso & Claus Michelsen & Maximilian Schäfer & Kevin Ducbao Tran, 2021. "Airbnb and Rental Markets: Evidence from Berlin," CESifo Working Paper Series 9089, CESifo.
    38. 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.
    39. 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.
    40. 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," SPRU Working Paper Series 2020-13, SPRU - Science Policy Research Unit, University of Sussex Business School.
    41. Giuseppe De Luca & Jan R. Magnus & Franco Peracchi, 2017. "Weighted-average least squares estimation of generalized linear models," EIEF Working Papers Series 1711, Einaudi Institute for Economics and Finance (EIEF), revised Aug 2017.
    42. 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.
    43. Danquah, Michael & Iddrisu, Abdul Malik & Boakye, Ernest Owusu & Owusu, Solomon, 2021. "Do gender wage differences within households influence women's empowerment and welfare? Evidence from Ghana," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 916-932.
    44. 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.
    45. 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.
    46. 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).
    47. 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.
    48. 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).
    49. Lai Xinglin, 2021. "Modelling hetegeneous treatment effects by quantitle local polynomial decision tree and forest," Papers 2111.15320, arXiv.org, revised Mar 2022.
    50. 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).
    51. Bilgin, Rumeysa, 2023. "The Selection Of Control Variables In Capital Structure Research With Machine Learning," SocArXiv e26qf, Center for Open Science.
    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 Dec 2017.
    53. Susan Athey & Guido Imbens, 2016. "The Econometrics of Randomized Experiments," Papers 1607.00698, arXiv.org.
    54. 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.
    55. 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.
    56. Kyle Myers & Wei Yang Tham, 2023. "Money, Time, and Grant Design," Papers 2312.06479, arXiv.org.
    57. 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).
    58. Cocker Liu & Adam Nowak & Patrick Smith, 2017. "Some Remarks on Real Estate Pricing," Working Papers 17-20, Department of Economics, West Virginia University.
    59. 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.
    60. Christis Katsouris, 2023. "High Dimensional Time Series Regression Models: Applications to Statistical Learning Methods," Papers 2308.16192, arXiv.org.
    61. Kaila, Heidi & Azad, Abul, 2023. "The effects of crime and violence on food insecurity and consumption in Nigeria," Food Policy, Elsevier, vol. 115(C).
    62. 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.
    63. 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.
    64. 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.
    65. 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 Feb 2024.
    66. 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.

  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. Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2018. "Economic predictions with big data: the illusion of sparsity," Staff Reports 847, Federal Reserve Bank of New York.
    2. 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.
    3. Victor Chernozhukov & Christian Hansen & Kaspar Wuthrich, 2020. "Instrumental Variable Quantile Regression," Papers 2009.00436, arXiv.org.
    4. Ofori, Isaac K. & Quaidoo, Christopher & Ofori, Pamela E., 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, issue forthcomi.
    5. Aristide Houndetoungan & Abdoul Haki Maoude, 2024. "Inference for Two-Stage Extremum Estimators," Papers 2402.05030, arXiv.org.
    6. Rahul Singh, 2021. "Debiased Kernel Methods," Papers 2102.11076, arXiv.org, revised Mar 2021.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. Victor Chernozhukov & Juan Carlos Escanciano & Hidehiko Ichimura & Whitney K. Newey & James M. Robins, 2018. "Locally robust semiparametric estimation," CeMMAP working papers CWP30/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    12. 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.
    13. Su, Liangjun & Ura, Takuya & Zhang, Yichong, 2019. "Non-separable models with high-dimensional data," Journal of Econometrics, Elsevier, vol. 212(2), pages 646-677.
    14. Robert Adamek & Stephan Smeekes & Ines Wilms, 2020. "Lasso Inference for High-Dimensional Time Series," Papers 2007.10952, arXiv.org, revised Sep 2022.
    15. 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.
    16. 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).
    17. Ali Charkhi & Gerda Claeskens, 2018. "Asymptotic post-selection inference for the Akaike information criterion," Biometrika, Biometrika Trust, vol. 105(3), pages 645-664.
    18. Neng-Chieh Chang, 2018. "Semiparametric Difference-in-Differences with Potentially Many Control Variables," Papers 1812.10846, arXiv.org, revised Jan 2019.
    19. Christian Hansen & Damian Kozbur & Sanjog Misra, 2016. "Targeted undersmoothing," ECON - Working Papers 282, Department of Economics - University of Zurich, revised Apr 2018.
    20. Neng-Chieh Chang, 2020. "The Mode Treatment Effect," Papers 2007.11606, arXiv.org.
    21. 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.
    22. Markus Pelger & Jiacheng Zou, 2022. "Inference for Large Panel Data with Many Covariates," Papers 2301.00292, arXiv.org, revised Mar 2023.
    23. 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.
    24. Jelena Bradic & Victor Chernozhukov & Whitney K. Newey & Yinchu Zhu, 2019. "Minimax Semiparametric Learning With Approximate Sparsity," Papers 1912.12213, arXiv.org, revised Aug 2022.
    25. 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.
    26. 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.
    27. Qizhao Chen & Vasilis Syrgkanis & Morgane Austern, 2022. "Debiased Machine Learning without Sample-Splitting for Stable Estimators," Papers 2206.01825, arXiv.org, revised Nov 2022.
    28. 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.
    29. 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.
    30. Victor Chernozhukov & Whitney K Newey & Rahul Singh, 2022. "Debiased machine learning of global and local parameters using regularized Riesz representers [Semiparametric instrumental variable estimation of treatment response models]," The Econometrics Journal, Royal Economic Society, vol. 25(3), pages 576-601.
    31. Yanqin Fan & Fang Han & Wei Li & Xiao-Hua Zhou, 2019. "On rank estimators in increasing dimensions," Papers 1908.05255, arXiv.org.
    32. Yoshimasa Uematsu & Takashi Yamagata, 2020. "Inference in Weak Factor Models," ISER Discussion Paper 1080, Institute of Social and Economic Research, Osaka University.
    33. 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.
    34. Sandro Heiniger, 2024. "Data-driven model selection within the matrix completion method for causal panel data models," Papers 2402.01069, arXiv.org.
    35. Stephan Martin, 2022. "Estimation of Conditional Random Coefficient Models using Machine Learning Techniques," Papers 2201.08366, arXiv.org.
    36. 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.
    37. Helmut Wasserbacher & Martin Spindler, 2021. "Machine Learning for Financial Forecasting, Planning and Analysis: Recent Developments and Pitfalls," Papers 2107.04851, arXiv.org.
    38. 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.
    39. Victor Chernozhukov & Whitney Newey & Vira Semenova, 2019. "Inference on weighted average value function in high-dimensional state space," Papers 1908.09173, arXiv.org.
    40. 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.
    41. 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.
    42. Victor Chernozhukov & Whitney Newey & Rahul Singh & Vasilis Syrgkanis, 2020. "Adversarial Estimation of Riesz Representers," Papers 2101.00009, arXiv.org, revised Jan 2024.
    43. Kaila, Heidi & Azad, Abul, 2023. "The effects of crime and violence on food insecurity and consumption in Nigeria," Food Policy, Elsevier, vol. 115(C).
    44. Ghysels, Eric & Qian, Hang, 2019. "Estimating MIDAS regressions via OLS with polynomial parameter profiling," Econometrics and Statistics, Elsevier, vol. 9(C), pages 1-16.
    45. 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.
    46. Victor Chernozhukov & Whitney K. Newey & Rahul Singh, 2022. "Automatic Debiased Machine Learning of Causal and Structural Effects," Econometrica, Econometric Society, vol. 90(3), pages 967-1027, May.

  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. Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2019. "lassopack: Model selection and prediction with regularized regression in Stata," Papers 1901.05397, arXiv.org.
    2. Shapiro, Joseph S., 2020. "The Environmental Bias of Trade Policy," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt7jh2s7d6, Department of Agricultural & Resource Economics, UC Berkeley.
    3. 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.
    4. Francesca Micocci & Armando Rungi, 2021. "Predicting Exporters with Machine Learning," Working Papers 03/2021, IMT School for Advanced Studies Lucca, revised Jul 2021.
    5. J. Daniel Aromí & M. Paula Bonel & Julián Cristiá & Martín Llada, 2020. "Socio-economic status and mobility during the COVID-19 pandemic: An analysis of large Latin American urban areas," Asociación Argentina de Economía Política: Working Papers 4307, Asociación Argentina de Economía Política.
    6. 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.
    7. Harrison Fell & Melinda Sandler Morrill, 2024. "The Impact of Wind Energy on Air Pollution and Emergency Department Visits," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 87(1), pages 287-320, January.
    8. Andrii Babii & Ryan T. Ball & Eric Ghysels & Jonas Striaukas, 2020. "Machine Learning Panel Data Regressions with Heavy-tailed Dependent Data: Theory and Application," Papers 2008.03600, arXiv.org, revised Nov 2021.
    9. 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).
    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 02/15, Institute for Fiscal Studies.
    11. Aristide Houndetoungan & Abdoul Haki Maoude, 2024. "Inference for Two-Stage Extremum Estimators," Papers 2402.05030, arXiv.org.
    12. Yun Qiu & Xi Chen & Wei Shi, 2020. "Impacts of social and economic factors on the transmission of coronavirus disease 2019 (COVID-19) in China," Journal of Population Economics, Springer;European Society for Population Economics, vol. 33(4), pages 1127-1172, October.
    13. Luv Sharma & Aravind Chandrasekaran & Elliot Bendoly, 2020. "Does the Office of Patient Experience Matter in Improving Delivery of Care?," Production and Operations Management, Production and Operations Management Society, vol. 29(4), pages 833-855, April.
    14. 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.
    15. Holger Breinlich & Valentina Corradi & Nadia Rocha & Michele Ruta & Joao M.C. Santos Silva & Tom Zylkin, 2021. "Machine Learning in International Trade Research ?- Evaluating the Impact of Trade Agreements," School of Economics Discussion Papers 0521, School of Economics, University of Surrey.
    16. Duncan Sheppard Gilchrist & Emily Glassberg Sands, 2016. "Something to Talk About: Social Spillovers in Movie Consumption," Journal of Political Economy, University of Chicago Press, vol. 124(5), pages 1339-1382.
    17. 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.
    18. 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.
    19. Christian Hansen & Yuan Liao, 2016. "The Factor-Lasso and K-Step Bootstrap Approach for Inference in High-Dimensional Economic Applications," Departmental Working Papers 201610, Rutgers University, Department of Economics.
    20. Damian Kozbur, 2017. "Sharp convergence rates for forward regression in high-dimensional sparse linear models," ECON - Working Papers 253, Department of Economics - University of Zurich, revised Apr 2018.
    21. Sun, Yuying & Hong, Yongmiao & Wang, Shouyang & Zhang, Xinyu, 2023. "Penalized time-varying model averaging," Journal of Econometrics, Elsevier, vol. 235(2), pages 1355-1377.
    22. 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.
    23. Natalie Bau & Martin Rotemberg & Manisha Shah & Bryce Steinberg, 2020. "Human Capital Investment in the Presence of Child Labor," NBER Working Papers 27241, National Bureau of Economic Research, Inc.
    24. 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.
    25. Lamarche, Carlos & Parker, Thomas, 2023. "Wild bootstrap inference for penalized quantile regression for longitudinal data," Journal of Econometrics, Elsevier, vol. 235(2), pages 1799-1826.
    26. 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.
    27. Damian Kozbur, 2015. "Testing-Based Forward Model Selection," ECON - Working Papers 283, Department of Economics - University of Zurich, revised Apr 2018.
    28. Julián Caballero & Christian Upper, 2023. "What happens to EMEs when US yields go up?," BIS Working Papers 1081, Bank for International Settlements.
    29. 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.
    30. Caballero, Julián, 2021. "Corporate dollar debt and depreciations: All’s well that ends well?," Journal of Banking & Finance, Elsevier, vol. 130(C).
    31. Marta Serra-Garcia & Uri Gneezy, 2023. "Improving Human Deception Detection Using Algorithmic Feedback," CESifo Working Paper Series 10518, CESifo.
    32. Chiang, Harold D. & Rodrigue, Joel & Sasaki, Yuya, 2023. "Post-Selection Inference In Three-Dimensional Panel Data," Econometric Theory, Cambridge University Press, vol. 39(3), pages 623-658, June.
    33. Christian Hansen & Damian Kozbur & Sanjog Misra, 2016. "Targeted undersmoothing," ECON - Working Papers 282, Department of Economics - University of Zurich, revised Apr 2018.
    34. Borgschulte, Mark & Vogler, Jacob, 2019. "Did the ACA Medicaid Expansion Save Lives?," IZA Discussion Papers 12552, Institute of Labor Economics (IZA).
    35. Damian Kozbur, 2020. "Analysis of Testing‐Based Forward Model Selection," Econometrica, Econometric Society, vol. 88(5), pages 2147-2173, September.
    36. Xi Chen & Ye Luo & Martin Spindler, 2019. "Adaptive Discrete Smoothing for High-Dimensional and Nonlinear Panel Data," Papers 1912.12867, arXiv.org, revised Jan 2020.
    37. Anders Bredahl Kock & Haihan Tang, 2014. "Inference in High-dimensional Dynamic Panel Data Models," CREATES Research Papers 2014-58, Department of Economics and Business Economics, Aarhus University.
    38. Samuel Dodini, 2023. "Insurance Subsidies, the Affordable Care Act, and Financial Stability," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 42(1), pages 97-136, January.
    39. Rossmann, Tobias, 2019. "Does Experience Shape Subjective Expectations?," Rationality and Competition Discussion Paper Series 181, CRC TRR 190 Rationality and Competition.
    40. Collins, Alan & Fan, Jingwen & Mahabir, Aruneema, 2022. "Actual versus ‘natural’ rates of suicide: Evidence from the USA," Economic Modelling, Elsevier, vol. 106(C).
    41. 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.
    42. Brian Asquith, 2019. "Do Rent Increases Reduce the Housing Supply Under Rent Control? Evidence from Evictions in San Francisco," Upjohn Working Papers 19-296, W.E. Upjohn Institute for Employment Research.
    43. Michael Vogt & Christopher Walsh & Oliver Linton, 2022. "CCE Estimation of High-Dimensional Panel Data Models with Interactive Fixed Effects," Papers 2206.12152, arXiv.org.
    44. 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..
    45. 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.
    46. Wei Shi & Lung-fei Lee, 2018. "The effects of gun control on crimes: a spatial interactive fixed effects approach," Empirical Economics, Springer, vol. 55(1), pages 233-263, August.
    47. Danquah, Michael & Iddrisu, Abdul Malik & Boakye, Ernest Owusu & Owusu, Solomon, 2021. "Do gender wage differences within households influence women's empowerment and welfare? Evidence from Ghana," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 916-932.
    48. 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.
    49. Max Vilgalys, 2023. "A Machine Learning Approach to Measuring Climate Adaptation," Papers 2302.01236, arXiv.org.
    50. Yigit Aydede & Jan Ditzen, 2022. "Identifying the regional drivers of influenza-like illness in Nova Scotia with dominance analysis," Papers 2212.06684, arXiv.org.
    51. 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.
    52. 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).
    53. Raja, Akash, 2023. "The impact of changes in bank capital requirements," Bank of England working papers 1004, Bank of England.
    54. 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.
    55. 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.
    56. 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.
    57. Paul Clarke & Annalivia Polselli, 2023. "Double Machine Learning for Static Panel Models with Fixed Effects," Papers 2312.08174, arXiv.org, revised Dec 2023.
    58. 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.
    59. Harold D. Chiang, 2018. "Many Average Partial Effects: with An Application to Text Regression," Papers 1812.09397, arXiv.org, revised Jan 2022.
    60. 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.
    61. María Laura Alzua & Natalia Cantet & Ana C. Dammert & Damilola Olajide, 2023. "The Wellbeing Effects of an Old Age Pension: Experimental Evidence for Ekiti State in Nigeria," CEDLAS, Working Papers 0322, CEDLAS, Universidad Nacional de La Plata.
    62. 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).

  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. 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.
    2. Alexandre Belloni & Victor Chernozhukov & Kengo Kato, 2014. "Valid post-selection inference in high-dimensional approximately sparse quantile regression models," CeMMAP working papers 53/14, Institute for Fiscal Studies.
    3. 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.
    4. Athey, Susan & Tibshirani, Julie & Wager, Stefan, 2017. "Generalized Random Forests," Research Papers 3575, Stanford University, Graduate School of Business.
    5. Christian Hansen & Yuan Liao, 2016. "The Factor-Lasso and K-Step Bootstrap Approach for Inference in High-Dimensional Economic Applications," Departmental Working Papers 201610, Rutgers University, Department of Economics.
    6. Farrell, Max H., 2015. "Robust inference on average treatment effects with possibly more covariates than observations," Journal of Econometrics, Elsevier, vol. 189(1), pages 1-23.
    7. 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.
    8. 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.
    9. Damian Kozbur, 2015. "Testing-Based Forward Model Selection," ECON - Working Papers 283, Department of Economics - University of Zurich, revised Apr 2018.
    10. 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.
    11. Christian Hansen & Damian Kozbur & Sanjog Misra, 2016. "Targeted undersmoothing," ECON - Working Papers 282, Department of Economics - University of Zurich, revised Apr 2018.
    12. Ning Xu & Jian Hong & Timothy C. G. Fisher, 2016. "Finite-sample and asymptotic analysis of generalization ability with an application to penalized regression," Papers 1609.03344, arXiv.org, revised Sep 2016.
    13. Braverman, Mark & Chassang, Sylvain, 2022. "Data-driven incentive alignment in capitation schemes," Journal of Public Economics, Elsevier, vol. 207(C).
    14. Denis Chetverikov & . ., 2016. "On cross-validated Lasso," CeMMAP working papers CWP47/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    15. 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.
    16. Denis Chetverikov & . ., 2016. "On cross-validated Lasso," CeMMAP working papers 47/16, Institute for Fiscal Studies.
    17. 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.
    18. Susan Athey & Guido W. Imbens, 2017. "The State of Applied Econometrics: Causality and Policy Evaluation," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 3-32, Spring.
    19. Danquah, Michael & Iddrisu, Abdul Malik & Boakye, Ernest Owusu & Owusu, Solomon, 2021. "Do gender wage differences within households influence women's empowerment and welfare? Evidence from Ghana," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 916-932.
    20. Max H. Farrell, 2013. "Robust Inference on Average Treatment Effects with Possibly More Covariates than Observations," Papers 1309.4686, arXiv.org, revised Feb 2018.
    21. Kasy Maximilian, 2019. "Uniformity and the Delta Method," Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-19, January.
    22. Matias D. Cattaneo & Michael Jansson, 2014. "Bootstrapping Kernel-Based Semiparametric Estimators," CREATES Research Papers 2014-25, Department of Economics and Business Economics, Aarhus University.
    23. Kaspar W thrich, 2015. "Semiparametric estimation of quantile treatment effects with endogeneity," Diskussionsschriften dp1509, Universitaet Bern, Departement Volkswirtschaft.

  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.

    Cited by:

    1. 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.
    2. Elena Esposito, 2022. "The Side Effects of Immunity: Malaria and African Slavery in the United States," American Economic Journal: Applied Economics, American Economic Association, vol. 14(3), pages 290-328, July.
    3. 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.
    4. Imke Reimers & Joel Waldfogel, 2021. "Digitization and Pre-purchase Information: The Causal and Welfare Impacts of Reviews and Crowd Ratings," American Economic Review, American Economic Association, vol. 111(6), pages 1944-1971, June.
    5. Pawel Dlotko & Simon Rudkin & Wanling Qiu, 2019. "Topologically Mapping the Macroeconomy," Papers 1911.10476, arXiv.org.
    6. Prem, Mounu & Purroy, Miguel E. & Vargas, Juan F., 2022. "Landmines: the Local Effects of Demining," IAST Working Papers 22-132, Institute for Advanced Study in Toulouse (IAST).
    7. Green, Gareth & Richards, Timothy, 2016. "Interpreting Results of Demand Estimation from Machine Learning Models," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 236147, Agricultural and Applied Economics Association.
    8. Rajeev Dehejia & Cristian Pop-Eleches & Cyrus Samii, 2021. "From Local to Global: External Validity in a Fertility Natural Experiment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(1), pages 217-243, January.
    9. Eli Ben-Michael & Avi Feller & Jesse Rothstein, 2018. "The Augmented Synthetic Control Method," Papers 1811.04170, arXiv.org, revised Jul 2020.
    10. Alain Hecq & Luca Margaritella & Stephan Smeekes, 2019. "Granger Causality Testing in High-Dimensional VARs: a Post-Double-Selection Procedure," Papers 1902.10991, arXiv.org, revised Dec 2020.
    11. Perilla, Sergio & Prem, Mounu & Purroy, Miguel E. & Vargas, Juan F., 2024. "How peace saves lives: Evidence from Colombia," World Development, Elsevier, vol. 176(C).
    12. 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.
    13. Mullally, Conner & Chakravarty, Shourish, 2018. "Are Matching Funds for Smallholder Irrigation Money Well Spent?," SocArXiv x5vmz, Center for Open Science.
    14. Karolis Matikonis & Matthew Gobey, 2024. "Small Business Property Tax Reductions and Firm Productivity," Small Business Economics, Springer, vol. 62(1), pages 307-324, January.
    15. 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.
    16. Francesca Micocci & Armando Rungi, 2021. "Predicting Exporters with Machine Learning," Working Papers 03/2021, IMT School for Advanced Studies Lucca, revised Jul 2021.
    17. 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.
    18. 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.
    19. Maria Angelica Bautista & Felipe Gonzalez & Luis R. Martınez & Pablo Munoz & Mounu Prem, 2019. "The Geography of Dictatorship and Support for Democracy," Empirical Studies of Conflict Project (ESOC) Working Papers 13, Empirical Studies of Conflict Project.
    20. Vegard H. Larsen & Leif Anders Thorsrud & Julia Zhulanova, 2019. "News-driven inflation expectations and information rigidities," Working Papers No 03/2019, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    21. Jakob Everding & Jan Marcus, 2020. "The effect of unemployment on the smoking behavior of couples," Health Economics, John Wiley & Sons, Ltd., vol. 29(2), pages 154-170, February.
    22. Arindrajit Dube & Attila S. Lindner, 2020. "City Limits: What do Local-Area Minimum Wages Do?," NBER Working Papers 27928, National Bureau of Economic Research, Inc.
    23. 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.
    24. Maffioli, Elisa M., 2021. "The political economy of health epidemics: Evidence from the Ebola outbreak," Journal of Development Economics, Elsevier, vol. 151(C).
    25. Guido De Blasio & Emanuele Ciani, 2015. "European Structural Funds During the Crisis: Evidence from Southern Italy," ERSA conference papers ersa15p435, European Regional Science Association.
    26. Gray, Colin, 2019. "Leaving benefits on the table: Evidence from SNAP," Journal of Public Economics, Elsevier, vol. 179(C).
    27. 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.
    28. Cobb-Clark, Deborah A. & Dahmann, Sarah C. & Kamhöfer, Daniel A. & Schildberg-Hörisch, Hannah, 2022. "The Predictive Power of Self-Control for Life Outcomes," Journal of Economic Behavior & Organization, Elsevier, vol. 197(C), pages 725-744.
    29. Ajay Agrawal & Joshua Gans & Avi Goldfarb, 2018. "Prediction, Judgment, and Complexity: A Theory of Decision-Making and Artificial Intelligence," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 89-110, National Bureau of Economic Research, Inc.
    30. 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.
    31. Pedro Carneiro & Sokbae Lee & Daniel Wilhelm, 2016. "Optimal Data Collection for Randomized Control Trials," Papers 1603.03675, arXiv.org, revised Aug 2016.
    32. Marcel Fafchamps & Julien Labonne, 2016. "Using Split Samples to Improve Inference about Causal Effects," NBER Working Papers 21842, National Bureau of Economic Research, Inc.
    33. Koning, Pierre & Muller, Paul & Prudon, Roger, 2022. "Why Do Temporary Workers Have Higher Disability Insurance Risks Than Permanent Workers?," IZA Discussion Papers 15173, Institute of Labor Economics (IZA).
    34. Dario Sansone & Anna Zhu, 2020. "Using Machine Learning to Create an Early Warning System for Welfare Recipients," Papers 2011.12057, arXiv.org, revised May 2021.
    35. Dmitry Arkhangelsky & Susan Athey & David A. Hirshberg & Guido W. Imbens & Stefan Wager, 2019. "Synthetic Difference In Differences," NBER Working Papers 25532, National Bureau of Economic Research, Inc.
    36. Daniel Mejía & Mounu Prem & Juan F. Vargas, 2019. "The Rise and Persistence of Illegal Crops: Evidence from a Naive Policy Announcement," Documentos CEDE 17535, Universidad de los Andes, Facultad de Economía, CEDE.
    37. Erica Field & Rohini Pande & Natalia Rigol & Simone Schaner & Charity Troyer Moore, 2021. "On Her Own Account: How Strengthening Women's Financial Control Impacts Labor Supply and Gender Norms," American Economic Review, American Economic Association, vol. 111(7), pages 2342-2375, July.
    38. 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.
    39. 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.
    40. Ofori, Isaac K. & Quaidoo, Christopher & Ofori, Pamela E., 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, issue forthcomi.
    41. Sokbae Lee & Yuan Liao & Myung Hwan Seo & Youngki Shin, 2022. "Fast Inference for Quantile Regression with Tens of Millions of Observations," Papers 2209.14502, arXiv.org, revised Oct 2023.
    42. Barboni, Giorgia & Cardenas, Juan Camilo & de Roux, Nicolas, 2022. "Behavioral Messages and Debt Repayment," CAGE Online Working Paper Series 633, Competitive Advantage in the Global Economy (CAGE).
    43. Levchenko, Andrei & Bartelme, Dominick & Lan, Ting, 2020. "Specialization, Market Access and Real Income," CEPR Discussion Papers 15604, C.E.P.R. Discussion Papers.
    44. Gonzalez, Felipe & Prem, Mounu & von Dessauer, Cristine, 2023. "Empowerment or Indoctrination? Women Centers Under Dictatorship," SocArXiv 64mf9, Center for Open Science.
    45. Gallego, J & Prem, M & Vargas, J. F., 2022. "Predicting Politicians Misconduct: Evidence From Colombia," Documentos de Trabajo 20504, Universidad del Rosario.
    46. 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.
    47. Olga Namen & Mounu Prem & Juan F. Vargas, 2019. "The human capital peace dividend," Documentos de Trabajo 17353, The Latin American and Caribbean Economic Association (LACEA).
    48. Santos, Luca J. & Oliveira, Alessandro V.M. & Aldrighi, Dante Mendes, 2021. "Testing the differentiated impact of the COVID-19 pandemic on air travel demand considering social inclusion," Journal of Air Transport Management, Elsevier, vol. 94(C).
    49. Michael Bailey & Drew Johnston & Theresa Kuchler & Johannes Stroebel & Arlene Wong, 2021. "Peer Effects in Product Adoption," Working Papers 2021-66, Princeton University. Economics Department..
    50. 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.
    51. Hector F. Calvo-Pardo & Tullio Mancini & Jose Olmo, 2020. "Neural Network Models for Empirical Finance," JRFM, MDPI, vol. 13(11), pages 1-22, October.
    52. 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.
    53. 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.
    54. Erica M. Field & Rohini Pande & Natalia Rigol & Simone G. Schaner & Charity Troyer Moore, 2019. "On Her Own Account: How Strengthening Women's Financial Control Affects Labor Supply and Gender Norms," NBER Working Papers 26294, National Bureau of Economic Research, Inc.
    55. Emily Cuddy & Janet Currie, 2020. "Rules vs. Discretion: Treatment of Mental Illness in U.S. Adolescents," Working Papers 2020-10, Princeton University. Economics Department..
    56. Dong, C. & Gao, J. & Linton, O., 2018. "High Dimensional Semiparametric Moment Restriction Models," Cambridge Working Papers in Economics 1881, Faculty of Economics, University of Cambridge.
    57. Stolbov, Mikhail & Shchepeleva, Maria, 2020. "What predicts the legal status of cryptocurrencies?," Economic Analysis and Policy, Elsevier, vol. 67(C), pages 273-291.
    58. 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.
    59. 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 e30db5a4-5c1c-450b-8f1d-6, Tilburg University, School of Economics and Management.
    60. Carolina Bernal & Mónica Ortiz & Mounu Prem & Juan F. Vargas, 2022. "Peaceful entry: Entrepreneurship dynamics during Colombia’s peace agreement," Documentos de Trabajo 19939, The Latin American and Caribbean Economic Association (LACEA).
    61. 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.
    62. Saavedra, Santiago & Romero, Mauricio, 2021. "Local incentives and national tax evasion: The response of illegal mining to a tax reform in Colombia," European Economic Review, Elsevier, vol. 138(C).
    63. Davide Viviano & Jelena Bradic, 2019. "Synthetic learner: model-free inference on treatments over time," Papers 1904.01490, arXiv.org, revised Aug 2022.
    64. Anastasiya-Mariya Asanov Noha & Igor Asanov & Guido Buenstorf, 2022. "Mental Health and Stress Level of Ukrainians Seeking Psychological Help Online," MAGKS Papers on Economics 202231, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    65. Harold D Chiang & Yukun Ma & Joel Rodrigue & Yuya Sasaki, 2021. "Dyadic double/debiased machine learning for analyzing determinants of free trade agreements," Papers 2110.04365, arXiv.org, revised Dec 2022.
    66. Jose E. Gomez-Gonzalez & Jorge M. Uribe & Oscar M. Valencia, 2023. "Sovereign Risk and Economic Complexity: Machine Learning Insights on Causality and Prediction," IREA Working Papers 202315, University of Barcelona, Research Institute of Applied Economics, revised Nov 2023.
    67. Luigi Guiso & Alexey Makarin, 2020. "Affinity, Trust, and Information," EIEF Working Papers Series 2020, Einaudi Institute for Economics and Finance (EIEF), revised Sep 2020.
    68. Joyce P Jacobsen & Laurence M Levin & Zachary Tausanovitch, 2016. "Comparing Standard Regression Modeling to Ensemble Modeling: How Data Mining Software Can Improve Economists’ Predictions," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 42(3), pages 387-398, June.
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    70. Faber, Marius, 2020. "Robots and reshoring: Evidence from Mexican labor markets," Journal of International Economics, Elsevier, vol. 127(C).
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    72. Anil Kumar, 2018. "Do Restrictions on Home Equity Extraction Contribute to Lower Mortgage Defaults? Evidence from a Policy Discontinuity at the Texas Border," American Economic Journal: Economic Policy, American Economic Association, vol. 10(1), pages 268-297, February.
    73. Li, Wenchao, 2021. "The “miseries” of sex imbalance: Evidence using subjective well-being data," Journal of Development Economics, Elsevier, vol. 151(C).
    74. 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.
    75. 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.
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    78. Simon Briole & Marc Gurgand & Eric Maurin & Sandra McNally & Jenifer Ruiz-Valenzuela & Daniel Santin, 2022. "The making of civic virtues: a school-based experiment in three countries," CEP Discussion Papers dp1830, Centre for Economic Performance, LSE.
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    82. Su, Liangjun & Ura, Takuya & Zhang, Yichong, 2019. "Non-separable models with high-dimensional data," Journal of Econometrics, Elsevier, vol. 212(2), pages 646-677.
    83. Gerald A. Carlino & Albert Saiz, 2019. "Beautiful city: Leisure amenities and urban growth," Journal of Regional Science, Wiley Blackwell, vol. 59(3), pages 369-408, June.
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    Cited by:

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    7. Stefano Cabras & J.D. Tena, 2022. "Implicit Institutional Incentives and Individual Decisions: Causal Inference with Deep Learning Models," Working Papers 202218, University of Liverpool, Department of Economics.
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  26. Victor Chernozhukov & Christian Hansen, 2013. "Quantile Models with Endogeneity," Papers 1303.7050, arXiv.org.

    Cited by:

    1. Xiaohong Chen & Demian Pouzo & James L. Powell, 2019. "Penalized Sieve GEL for Weighted Average Derivatives of Nonparametric Quantile IV Regressions," Papers 1902.10100, arXiv.org.
    2. 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.
    3. 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.
    4. Victor Chernozhukov & Christian Hansen & Kaspar Wuthrich, 2020. "Instrumental Variable Quantile Regression," Papers 2009.00436, arXiv.org.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. Hammoudeh, Shawkat & Nguyen, Duc Khuong & Sousa, Ricardo M., 2014. "Energy prices and CO2 emission allowance prices: A quantile regression approach," Energy Policy, Elsevier, vol. 70(C), pages 201-206.
    10. Victor Chernozhukov & Iv'an Fern'andez-Val & Whitney Newey & Sami Stouli & Francis Vella, 2017. "Semiparametric Estimation of Structural Functions in Nonseparable Triangular Models," Papers 1711.02184, arXiv.org, revised Oct 2019.
    11. 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.
    12. Chletsos, Michael & Roupakias, Stelios, 2018. "Education and wage inequality before and during the fiscal crisis: A quantile regression analysis for Greece 2006-2016," MPRA Paper 87633, University Library of Munich, Germany.
    13. Wüthrich, Kaspar, 2019. "A closed-form estimator for quantile treatment effects with endogeneity," Journal of Econometrics, Elsevier, vol. 210(2), pages 219-235.
    14. 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.
    15. 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.
    16. Pengzhou Wu & Kenji Fukumizu, 2021. "$\beta$-Intact-VAE: Identifying and Estimating Causal Effects under Limited Overlap," Papers 2110.05225, arXiv.org.
    17. 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.
    18. 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.
    19. 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.
    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. 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.
    22. 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.
    23. 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.
    24. Damian Clarke & Manuel Llorca Ja~na & Daniel Paila~nir, 2021. "The Use of Quantile Methods in Economic History," Papers 2108.06055, arXiv.org.
    25. Blaise Melly und Kaspar W thrich, 2016. "Local quantile treatment effects," Diskussionsschriften dp1605, Universitaet Bern, Departement Volkswirtschaft.
    26. 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.
    27. 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.
    28. 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.
    29. 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.
    30. 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.
    31. Kaspar W thrich, 2015. "Semiparametric estimation of quantile treatment effects with endogeneity," Diskussionsschriften dp1509, Universitaet Bern, Departement Volkswirtschaft.
    32. 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.

  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 46/15, Institute for Fiscal Studies.
    2. Anthony Strittmatter & Conny Wunsch, 2021. "The Gender Pay Gap Revisited with Big Data: Do Methodological Choices Matter?," Papers 2102.09207, arXiv.org, revised Feb 2021.
    3. Liran Einav & Jonathan Levin, 2013. "The Data Revolution and Economic Analysis," NBER Chapters, in: Innovation Policy and the Economy, Volume 14, pages 1-24, National Bureau of Economic Research, Inc.
    4. 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.
    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. 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.
    7. Aline Bütikofer & Rita Ginja & Fanny Landaud & Katrine Løken, 2020. "School Selectivity, Peers, and Mental Health," Working Papers 2020-074, Human Capital and Economic Opportunity Working Group.
    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. Stefano Cabras & J.D. Tena, 2022. "Implicit Institutional Incentives and Individual Decisions: Causal Inference with Deep Learning Models," Working Papers 202218, University of Liverpool, Department of Economics.
    10. 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.
    11. Gonzalez, Felipe & Muñoz, Pablo & Prem, Mounu, 2021. "Lost in transition? The persistence of dictatorship mayors," SocArXiv d6x54, Center for Open Science.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. Gabriel Okasa, 2022. "Meta-Learners for Estimation of Causal Effects: Finite Sample Cross-Fit Performance," Papers 2201.12692, arXiv.org.
    17. Caner, Mehmet & Kock, Anders Bredahl, 2018. "Asymptotically honest confidence regions for high dimensional parameters by the desparsified conservative Lasso," Journal of Econometrics, Elsevier, vol. 203(1), pages 143-168.
    18. Toru Kitagawa & Chris Muris, 2013. "Covariate selection and model averaging in semiparametric estimation of treatment effects," CeMMAP working papers 61/13, Institute for Fiscal Studies.
    19. 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.
    20. Alexandre Belloni & Victor Chernozhukov, 2015. "Comment," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(512), pages 1449-1451, December.
    21. 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.
    22. Clarke, Damian, 2023. "The Economics of Abortion Policy," IZA Discussion Papers 16395, Institute of Labor Economics (IZA).
    23. Sylvain Barde & Rowan Cherodian & Guy Tchuente, 2023. "Moran's I Lasso for models with spatially correlated data," Papers 2310.02773, arXiv.org.
    24. 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.
    25. 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).
    26. Angrist, Joshua & Rokkanen, Miikka, 2013. "Wanna Get Away? RD Identification Away from the Cutoff," IZA Discussion Papers 7429, Institute of Labor Economics (IZA).
    27. 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.
    28. Imbens, Guido W., 2014. "Matching Methods in Practice: Three Examples," IZA Discussion Papers 8049, Institute of Labor Economics (IZA).
    29. 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).
    30. 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.
    31. Knaus, Michael C. & Lechner, Michael & Strittmatter, Anthony, 2017. "Heterogeneous Employment Effects of Job Search Programmes: A Machine Learning Approach," Economics Working Paper Series 1711, University of St. Gallen, School of Economics and Political Science.
    32. 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.
    33. John List & Ian Muir & Gregory Sun, 2022. "Using Machine Learning for Efficient Flexible Regression Adjustment in Economic Experiments," Natural Field Experiments 00763, The Field Experiments Website.
    34. 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," The Warwick Economics Research Paper Series (TWERPS) 1361, University of Warwick, Department of Economics.
    35. Hensel, Lukas & Tekleselassie, Tsegay & Witte, Marc J, 2021. "Formalized Employee Search and Labor Demand," IZA Discussion Papers 14839, Institute of Labor Economics (IZA).
    36. 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.
    37. Chakravorty, Bhaskar & Bhatiya, Apurav Yash & Imbert, Clement & Lohnert, Maximilian & Panda, Poonam & Rathelot, Roland, 2022. "Impact of the COVID-19 Crisis on Indias Rural Youth : Evidence from a Panel Survey and an Experiment," CAGE Online Working Paper Series 634, Competitive Advantage in the Global Economy (CAGE).
    38. 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.
    39. Chen, Ya & Tsionas, Mike G. & Zelenyuk, Valentin, 2021. "LASSO+DEA for small and big wide data," Omega, Elsevier, vol. 102(C).
    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. 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.
    42. 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.
    43. 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.
    44. 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.
    45. 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.
    46. 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.
    47. 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).
    48. Alexander Krei{ss} & Christoph Rothe, 2021. "Inference in Regression Discontinuity Designs with High-Dimensional Covariates," Papers 2110.13725, arXiv.org, revised May 2022.
    49. 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.
    50. 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).
    51. Kaila, Heidi & Azad, Abul, 2023. "The effects of crime and violence on food insecurity and consumption in Nigeria," Food Policy, Elsevier, vol. 115(C).
    52. 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).
    53. 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.

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

    Cited by:

    1. Áureo de Paula & Imran Rasul & Pedro CL Souza, 2019. "Identifying network ties from panel data: theory and an application to tax competition," CeMMAP working papers CWP55/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Matthew Gentzkow & Bryan T. Kelly & Matt Taddy, 2017. "Text as Data," NBER Working Papers 23276, National Bureau of Economic Research, Inc.
    3. Alain Hecq & Luca Margaritella & Stephan Smeekes, 2019. "Granger Causality Testing in High-Dimensional VARs: a Post-Double-Selection Procedure," Papers 1902.10991, arXiv.org, revised Dec 2020.
    4. Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2018. "Economic predictions with big data: the illusion of sparsity," Staff Reports 847, Federal Reserve Bank of New York.
    5. 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.
    6. 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.
    7. 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.
    8. Alexandre Belloni & Mingli Chen & Victor Chernozhukov, 2016. "Quantile Graphical Models: Prediction and Conditional Independence with Applications to Systemic Risk," Papers 1607.00286, arXiv.org, revised Oct 2019.
    9. Victor Chernozhukov & Wolfgang Härdle & Chen Huang & Weining Wang, 2019. "LASSO-Driven Inference in Time and Space," CeMMAP working papers CWP20/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. 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.
    11. 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.
    12. Alexandre Belloni & Victor Chernozhukov & Kengo Kato, 2013. "Robust inference in high-dimensional approximately sparse quantile regression models," CeMMAP working papers 70/13, Institute for Fiscal Studies.
    13. 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.
    14. 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.
    15. Natalia Bailey & George Kapetanios & M. Hashem Pesaran, 2020. "Measurement of Factor Strenght: Theory and Practice," CESifo Working Paper Series 8146, CESifo.
    16. Demian Pouzo, 2015. "On the Non-Asymptotic Properties of Regularized M-estimators," Papers 1512.06290, arXiv.org, revised Oct 2016.
    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. 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.
    19. Caner, Mehmet & Kock, Anders Bredahl, 2018. "Asymptotically honest confidence regions for high dimensional parameters by the desparsified conservative Lasso," Journal of Econometrics, Elsevier, vol. 203(1), pages 143-168.
    20. 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.
    21. 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.
    22. Scoles, Brooke & Nicodemo, Catia, 2022. "Doctors’ attitudes toward specific medical conditions," Journal of Economic Behavior & Organization, Elsevier, vol. 204(C), pages 182-199.
    23. 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.
    24. Gold, David & Lederer, Johannes & Tao, Jing, 2020. "Inference for high-dimensional instrumental variables regression," Journal of Econometrics, Elsevier, vol. 217(1), pages 79-111.
    25. 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.
    26. Matteo Barigozzi & Christian T. Brownlees, 2013. "Nets: Network estimation for time series," Economics Working Papers 1391, Department of Economics and Business, Universitat Pompeu Fabra.
    27. 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.
    28. 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.
    29. 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.
    30. 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.
    31. 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.
    32. Mueller, Hannes & Rauh, Christopher, 2018. "Reading Between the Lines: Prediction of Political Violence Using Newspaper Text," American Political Science Review, Cambridge University Press, vol. 112(2), pages 358-375, May.
    33. 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.
    34. 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.
    35. 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.
    36. 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.
    37. 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.
    38. 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.
    39. Victor Chernozhukov & Chris Hansen & Martin Spindler, 2016. "High-Dimensional Metrics in R," Papers 1603.01700, arXiv.org, revised Aug 2016.
    40. 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.
    41. Riccardo Di Francesco, 2023. "Ordered Correlation Forest," Papers 2309.08755, arXiv.org.
    42. 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".
    43. Myrto Kalouptsidi, 2014. "Time to Build and Fluctuations in Bulk Shipping," American Economic Review, American Economic Association, vol. 104(2), pages 564-608, February.
    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 Dec 2017.
    45. 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).
    46. Florens, Jean-Pierre & Van Bellegem, Sébastien, 2015. "Instrumental variable estimation in functional linear models," Journal of Econometrics, Elsevier, vol. 186(2), pages 465-476.
    47. Song Song & Peter J. Bickel, 2011. "Large Vector Auto Regressions," SFB 649 Discussion Papers SFB649DP2011-048, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    48. 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.
    49. 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.
    50. Li, Zhaoyuan & Yao, Jianfeng, 2019. "Testing for heteroscedasticity in high-dimensional regressions," Econometrics and Statistics, Elsevier, vol. 9(C), pages 122-139.
    51. 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).
    52. 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).
    53. 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 Feb 2024.

  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. Chen, Daniel L., 2016. "Priming Ideology: Why Presidential Elections Affect U.S. Judges," IAST Working Papers 16-39, Institute for Advanced Study in Toulouse (IAST), revised Aug 2016.
    2. Chen, Daniel L. & Michaeli, Moti & Spiro, Daniel, 2016. "Ideological Perfectionism," TSE Working Papers 16-694, Toulouse School of Economics (TSE).
    3. Shi, Zhentao, 2016. "Econometric estimation with high-dimensional moment equalities," Journal of Econometrics, Elsevier, vol. 195(1), pages 104-119.

  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. Christoph Breunig & Enno Mammen & Anna Simoni, 2018. "Ill-posed Estimation in High-Dimensional Models with Instrumental Variables," Papers 1806.00666, arXiv.org, revised Aug 2020.
    2. Andrii Babii, 2022. "High-Dimensional Mixed-Frequency IV Regression," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(4), pages 1470-1483, October.
    3. 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.
    4. 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.
    5. 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.
    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. 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..
    9. 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.

  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. Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2019. "lassopack: Model selection and prediction with regularized regression in Stata," Papers 1901.05397, arXiv.org.
    2. 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.
    3. Barrera-Osorio, Felipe & Gertler,Paul J. & Nakajima,Nozomi & Patrinos,Harry Anthony, 2020. "Promoting Parental Involvement in Schools : Evidence from Two Randomized Experiments," Policy Research Working Paper Series 9462, The World Bank.
    4. Elliott Ash & W. Bentley MacLeod, 2016. "Reducing Partisanship in Judicial Elections Can Improve Judge Quality: Evidence from U.S. State Supreme Courts," NBER Working Papers 22071, National Bureau of Economic Research, Inc.
    5. 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.
    6. Manudeep, Bhuller & Dahl, Gordon B. & Løken, Katrine V. & Mogstad, Magne, 2016. "Incarceration, recidivism and employment," Working Papers in Economics 07/16, University of Bergen, Department of Economics.
    7. Anthony Strittmatter & Conny Wunsch, 2021. "The Gender Pay Gap Revisited with Big Data: Do Methodological Choices Matter?," Papers 2102.09207, arXiv.org, revised Feb 2021.
    8. Bonaccolto, Giovanni & Borri, Nicola & Consiglio, Andrea, 2023. "Breakup and default risks in the great lockdown," Journal of Banking & Finance, Elsevier, vol. 147(C).
    9. Alain Hecq & Luca Margaritella & Stephan Smeekes, 2019. "Granger Causality Testing in High-Dimensional VARs: a Post-Double-Selection Procedure," Papers 1902.10991, arXiv.org, revised Dec 2020.
    10. Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2018. "Economic predictions with big data: the illusion of sparsity," Staff Reports 847, Federal Reserve Bank of New York.
    11. Khan, Adnan & Nasim, Sanval & Shaukat, Mahvish & Stegmann, Andreas, 2021. "Building trust in the state with information: Evidence from urban Punjab," Journal of Public Economics, Elsevier, vol. 202(C).
    12. Adam B. Badawi & Daniel L. Chen, 2017. "The Shareholder Wealth Effects of Delaware Litigation," American Law and Economics Review, American Law and Economics Association, vol. 19(2), pages 287-326.
    13. 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.
    14. 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.
    15. Medeiros, Marcelo C. & Mendes, Eduardo F., 2016. "ℓ1-regularization of high-dimensional time-series models with non-Gaussian and heteroskedastic errors," Journal of Econometrics, Elsevier, vol. 191(1), pages 255-271.
    16. J. Daniel Aromí & M. Paula Bonel & Julián Cristiá & Martín Llada, 2020. "Socio-economic status and mobility during the COVID-19 pandemic: An analysis of large Latin American urban areas," Asociación Argentina de Economía Política: Working Papers 4307, Asociación Argentina de Economía Política.
    17. Liran Einav & Jonathan Levin, 2013. "The Data Revolution and Economic Analysis," NBER Chapters, in: Innovation Policy and the Economy, Volume 14, pages 1-24, National Bureau of Economic Research, Inc.
    18. Manudeep Bhuller & Gordon B. Dahl & Katrine V. Løken & Magne Mogstad, 2018. "Incarceration Spillovers in Criminal and Family Networks," NBER Working Papers 24878, National Bureau of Economic Research, Inc.
    19. Gautier, Eric & Rose, Christiern & Tsybakov, Alexandre, 2018. "High-dimensional instrumental variables regression and confidence sets," TSE Working Papers 18-930, Toulouse School of Economics (TSE), revised Nov 2019.
    20. 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.
    21. Jooyoung Cha & Harold D. Chiang & Yuya Sasaki, 2021. "Inference in high-dimensional regression models without the exact or $L^p$ sparsity," Papers 2108.09520, arXiv.org, revised Dec 2022.
    22. Alexandre Belloni & Victor Chernozhukov & Kengo Kato, 2014. "Valid post-selection inference in high-dimensional approximately sparse quantile regression models," CeMMAP working papers 53/14, Institute for Fiscal Studies.
    23. Jakob Everding & Jan Marcus, 2020. "The effect of unemployment on the smoking behavior of couples," Health Economics, John Wiley & Sons, Ltd., vol. 29(2), pages 154-170, February.
    24. 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.
    25. Mehmet Caner & Kfir Eliaz, 2021. "Shoiuld Humans Lie to Machines: The Incentive Compatibility of Lasso and General Weighted Lasso," Papers 2101.01144, arXiv.org, revised Sep 2021.
    26. Michal Kolesár & Raj Chetty & John N. Friedman & Edward L. Glaeser & Guido W. Imbens, 2011. "Identification and Inference with Many Invalid Instruments," NBER Working Papers 17519, National Bureau of Economic Research, Inc.
    27. Zhu, Ying, 2015. "Sparse Linear Models and l1−Regularized 2SLS with High-Dimensional Endogenous Regressors and Instruments," MPRA Paper 81217, University Library of Munich, Germany.
    28. Xun Lu & Su Liangjun, 2015. "Shrinkage Estimation of Dynamic Panel Data Models with Interactive Fixed Effects," Working Papers 02-2015, Singapore Management University, School of Economics.
    29. 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.
    30. Tomohiro Ando & Naoya Sueishi, 2019. "On the Convergence Rate of the SCAD-Penalized Empirical Likelihood Estimator," Econometrics, MDPI, vol. 7(1), pages 1-14, March.
    31. Ivan A. Canay & Magne Mogstad & Jack Mountjoy, 2020. "On the Use of Outcome Tests for Detecting Bias in Decision Making," Working Papers 2020-125, Becker Friedman Institute for Research In Economics.
    32. 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.
    33. Marine Carrasco & Guy Tchuente, 2015. "Regularized LIML for many instruments," Studies in Economics 1515, School of Economics, University of Kent.
    34. Colin F. Camerer & Gideon Nave & Alec Smith, 2019. "Dynamic Unstructured Bargaining with Private Information: Theory, Experiment, and Outcome Prediction via Machine Learning," Management Science, INFORMS, vol. 65(4), pages 1867-1890, April.
    35. Jiafeng Chen & Daniel L. Chen & Greg Lewis, 2020. "Mostly Harmless Machine Learning: Learning Optimal Instruments in Linear IV Models," Papers 2011.06158, arXiv.org, revised Jun 2021.
    36. Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen, 2013. "Program evaluation with high-dimensional data," CeMMAP working papers 77/13, Institute for Fiscal Studies.
    37. Embaye, Weldensie T. & Zereyesus, Yacob A., 2017. "Measuring the value of housing services in household surveys: an application of machine learning approach," 2017 Annual Meeting, February 4-7, 2017, Mobile, Alabama 252851, Southern Agricultural Economics Association.
    38. Alexandre Belloni & Mingli Chen & Victor Chernozhukov, 2016. "Quantile Graphical Models: Prediction and Conditional Independence with Applications to Systemic Risk," Papers 1607.00286, arXiv.org, revised Oct 2019.
    39. 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.
    40. Yoonseok Lee & Yu Zhou, 2015. "Averaged Instrumental Variables Estimators," Center for Policy Research Working Papers 180, Center for Policy Research, Maxwell School, Syracuse University.
    41. Alexandre Belloni & Victor Chernozhukov, 2011. "High Dimensional Sparse Econometric Models: An Introduction," Papers 1106.5242, arXiv.org, revised Sep 2011.
    42. Chen, D.L. & Levonyan, V. & Reinhart, S.E. & Taksler, G., 2014. "Do Payment Disclosure Laws Affect Industry-Physician Relationships?," Health, Econometrics and Data Group (HEDG) Working Papers 14/24, HEDG, c/o Department of Economics, University of York.
    43. Mr. Anil Ari & Sophia Chen & Mr. Lev Ratnovski, 2019. "The Dynamics of Non-Performing Loans during Banking Crises: A New Database," IMF Working Papers 2019/272, International Monetary Fund.
    44. Serkan Aglasan & Barry K. Goodwin & Roderick M. Rejesus, 2023. "Risk effects of GM corn: Evidence from crop insurance outcomes and high‐dimensional methods," Agricultural Economics, International Association of Agricultural Economists, vol. 54(1), pages 110-126, January.
    45. Daniel Lewis & Davide Melcangi & Laura Pilossoph, 2019. "Latent Heterogeneity in the Marginal Propensity to Consume," 2019 Meeting Papers 519, Society for Economic Dynamics.
    46. Daniele Bianchi & Kenichiro McAlinn, 2018. "Large-Scale Dynamic Predictive Regressions," Papers 1803.06738, arXiv.org.
    47. Giglio, Stefano & Feng, Guanhao & Xiu, Dacheng, 2020. "Taming the Factor Zoo: A Test of New Factors," CEPR Discussion Papers 14266, C.E.P.R. Discussion Papers.
    48. 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.
    49. 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.
    50. Andrii Babii & Eric Ghysels & Jonas Striaukas, 2022. "Machine Learning Time Series Regressions With an Application to Nowcasting," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 1094-1106, June.
    51. Alexandre Belloni & Victor Chernozhukov & Kengo Kato, 2013. "Uniform Post Selection Inference for LAD Regression and Other Z-estimation problems," Papers 1304.0282, arXiv.org, revised Oct 2020.
    52. 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.
    53. Stephen Coussens & Jann Spiess, 2021. "Improving Inference from Simple Instruments through Compliance Estimation," Papers 2108.03726, arXiv.org.
    54. Athey, Susan & Tibshirani, Julie & Wager, Stefan, 2017. "Generalized Random Forests," Research Papers 3575, Stanford University, Graduate School of Business.
    55. Ofori, Isaac K. & Quaidoo, Christopher & Ofori, Pamela E., 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, issue forthcomi.
    56. Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Post-selection and post-regularization inference in linear models with many controls and instruments," CeMMAP working papers 02/15, Institute for Fiscal Studies.
    57. Levchenko, Andrei & Bartelme, Dominick & Lan, Ting, 2020. "Specialization, Market Access and Real Income," CEPR Discussion Papers 15604, C.E.P.R. Discussion Papers.
    58. 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.
    59. Luv Sharma & Aravind Chandrasekaran & Elliot Bendoly, 2020. "Does the Office of Patient Experience Matter in Improving Delivery of Care?," Production and Operations Management, Production and Operations Management Society, vol. 29(4), pages 833-855, April.
    60. 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.
    61. 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.
    62. Santos, Luca J. & Oliveira, Alessandro V.M. & Aldrighi, Dante Mendes, 2021. "Testing the differentiated impact of the COVID-19 pandemic on air travel demand considering social inclusion," Journal of Air Transport Management, Elsevier, vol. 94(C).
    63. Marine Carrasco & Guy Tchuente, 2016. "Efficient Estimation with Many Weak Instruments Using Regularization Techniques," Econometric Reviews, Taylor & Francis Journals, vol. 35(8-10), pages 1609-1637, December.
    64. Holger Breinlich & Valentina Corradi & Nadia Rocha & Michele Ruta & Joao M.C. Santos Silva & Tom Zylkin, 2021. "Machine Learning in International Trade Research ?- Evaluating the Impact of Trade Agreements," School of Economics Discussion Papers 0521, School of Economics, University of Surrey.
    65. Undral Byambadalai, 2022. "Identification and Inference for Welfare Gains without Unconfoundedness," Papers 2207.04314, arXiv.org.
    66. 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.
    67. Chen, Daniel L. & Levonyan, Vardges & Yeh, Susan, 2016. "Policies Affect Preferences: Evidence from Random Variation in Abortion Jurisprudence," TSE Working Papers 16-723, Toulouse School of Economics (TSE).
    68. Brett R. Gordon & Florian Zettelmeyer & Neha Bhargava & Dan Chapsky, 2019. "A Comparison of Approaches to Advertising Measurement: Evidence from Big Field Experiments at Facebook," Marketing Science, INFORMS, vol. 38(2), pages 193-225, March.
    69. Alexandre Belloni & Victor Chernozhukov & Kengo Kato, 2013. "Robust inference in high-dimensional approximately sparse quantile regression models," CeMMAP working papers 70/13, Institute for Fiscal Studies.
    70. Sonin, Konstantin & Milosh, Maria & Painter, Marcus & Van Dijcke, David & Wright, Austin L., 2020. "Unmasking Partisanship: Polarization Undermines Public Response to Collective Risk," CEPR Discussion Papers 15464, C.E.P.R. Discussion Papers.
    71. Li, Qiang & An, Lian & Zhang, Ren, 2023. "Corruption drives brain drain: Cross-country evidence from machine learning," Economic Modelling, Elsevier, vol. 126(C).
    72. Emily Cuddy & Janet Currie, 2020. "Rules vs. Discretion: Treatment of Mental Illness in U.S. Adolescents," Working Papers 2020-10, Princeton University. Economics Department..
    73. Brian Quistorff & Gentry Johnson, 2020. "Machine Learning for Experimental Design: Methods for Improved Blocking," Papers 2010.15966, arXiv.org.
    74. 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.
    75. 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.
    76. Dong, C. & Gao, J. & Linton, O., 2018. "High Dimensional Semiparametric Moment Restriction Models," Cambridge Working Papers in Economics 1881, Faculty of Economics, University of Cambridge.
    77. Christoph Breunig & Enno Mammen & Anna Simoni, 2018. "Ill-posed Estimation in High-Dimensional Models with Instrumental Variables," Papers 1806.00666, arXiv.org, revised Aug 2020.
    78. Chen, Daniel L. & Sethi, Jasmin, 2016. "Insiders, Outsiders, and Involuntary Unemployment: Sexual Harrassment Exacerbates Gender Inequality," TSE Working Papers 16-687, Toulouse School of Economics (TSE).
    79. Colin Gray & Adam Leive & Elena Prager & Kelsey B. Pukelis & Mary Zaki, 2021. "Employed in a SNAP? The Impact of Work Requirements on Program Participation and Labor Supply," NBER Working Papers 28877, National Bureau of Economic Research, Inc.
    80. 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.
    81. Max H. Farrell & Tengyuan Liang & Sanjog Misra, 2018. "Deep Neural Networks for Estimation and Inference," Papers 1809.09953, arXiv.org, revised Sep 2019.
    82. Christian Hansen & Yuan Liao, 2016. "The Factor-Lasso and K-Step Bootstrap Approach for Inference in High-Dimensional Economic Applications," Departmental Working Papers 201610, Rutgers University, Department of Economics.
    83. Guilherme Lichand & Anandi Mani, 2020. "Cognitive Droughts," CSAE Working Paper Series 2020-02, Centre for the Study of African Economies, University of Oxford.
    84. Mitchell J. Lovett & Renana Peres & Linli Xu, 2019. "Can your advertising really buy earned impressions? The effect of brand advertising on word of mouth," Quantitative Marketing and Economics (QME), Springer, vol. 17(3), pages 215-255, September.
    85. Philipp Kugler, 2022. "The role of wage beliefs in the decision to become a nurse," Health Economics, John Wiley & Sons, Ltd., vol. 31(1), pages 94-111, January.
    86. Damian Kozbur, 2017. "Sharp convergence rates for forward regression in high-dimensional sparse linear models," ECON - Working Papers 253, Department of Economics - University of Zurich, revised Apr 2018.
    87. 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 e30db5a4-5c1c-450b-8f1d-6, Tilburg University, School of Economics and Management.
    88. 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.
    89. Hippolyte Balima & Anna Sokolova, 2020. "IMF Programs And Economic Growth: A Meta-Analysis," HSE Working papers WP BRP 241/EC/2020, National Research University Higher School of Economics.
    90. Brian J. Asquith & Judith K. Hellerstein & Mark J. Kutzbach & David Neumark, 2017. "Social Capital and Labor Market Networks," NBER Working Papers 23959, National Bureau of Economic Research, Inc.
    91. Ismir Mulalic & Ninette Pilegaard & Jan Rouwendal, 2015. "Does improving Public Transport decrease Car Ownership? Evidence from the Copenhagen Metropolitan Area," Tinbergen Institute Discussion Papers 15-139/VIII, Tinbergen Institute.
    92. René Böheim & Philipp Stöllinger, 2020. "Decomposition of the Gender Wage Gap using the LASSO Estimator," Economics working papers 2020-03, Department of Economics, Johannes Kepler University Linz, Austria.
    93. Robert S. Chirinko & Daniel J. Wilson, 2017. "Tax competition among U.S. States: racing to the bottom or riding on a seesaw?," Working Papers 3, Department of the Treasury, Ministry of the Economy and of Finance.
    94. Victor Chernozhukov & Jerry Hausman & Whitney K. Newey, 2019. "Demand analysis with many prices," CeMMAP working papers CWP59/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    95. Zhang, Han, 2021. "How Using Machine Learning Classification as a Variable in Regression Leads to Attenuation Bias and What to Do About It," SocArXiv 453jk, Center for Open Science.
    96. Yuehao Bai & Liang Jiang & Joseph P. Romano & Azeem M. Shaikh & Yichong Zhang, 2023. "Covariate Adjustment in Experiments with Matched Pairs," Papers 2302.04380, arXiv.org, revised Oct 2023.
    97. Steven Shuye Wang & Kuan Xu & Hao Zhang, 2019. "A Microstructure Study of Circuit Breakers in the Chinese Stock Markets," Working Papers daleconwp2019-02, Dalhousie University, Department of Economics.
    98. Victor Chernozhukov & Juan Carlos Escanciano & Hidehiko Ichimura & Whitney K. Newey & James M. Robins, 2018. "Locally robust semiparametric estimation," CeMMAP working papers CWP30/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    99. Marit Hinnosaar & Elaine Liu, 2022. "Malleability of Alcohol Consumption: Evidence from Migrants," Working Papers 2022-020, Human Capital and Economic Opportunity Working Group.
    100. Ke Miao & Peter C.B. Phillips & Liangjun Su, 2020. "High-Dimensional VARs with Common Factors," Cowles Foundation Discussion Papers 2252, Cowles Foundation for Research in Economics, Yale University.
    101. Shana Kushner Gadarian & Sara Wallace Goodman & Thomas B Pepinsky, 2021. "Partisanship, health behavior, and policy attitudes in the early stages of the COVID-19 pandemic," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-13, April.
    102. Anil Kumar, 2018. "Do Restrictions on Home Equity Extraction Contribute to Lower Mortgage Defaults? Evidence from a Policy Discontinuity at the Texas Border," American Economic Journal: Economic Policy, American Economic Association, vol. 10(1), pages 268-297, February.
    103. Liu, Chu-An & Tao, Jing, 2016. "Model selection and model averaging in nonparametric instrumental variables models," MPRA Paper 69492, University Library of Munich, Germany.
    104. Farrell, Max H., 2015. "Robust inference on average treatment effects with possibly more covariates than observations," Journal of Econometrics, Elsevier, vol. 189(1), pages 1-23.
    105. 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.
    106. 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.
    107. 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.
    108. Sheldon, Tamara L. & DeShazo, J.R., 2017. "How does the presence of HOV lanes affect plug-in electric vehicle adoption in California? A generalized propensity score approach," Journal of Environmental Economics and Management, Elsevier, vol. 85(C), pages 146-170.
    109. Gordon Burtch & Edward McFowland III & Mochen Yang & Gediminas Adomavicius, 2023. "EnsembleIV: Creating Instrumental Variables from Ensemble Learners for Robust Statistical Inference," Papers 2303.02820, arXiv.org.
    110. Timothy B. Armstrong & Michal Kolesár & Soonwoo Kwon, 2020. "Bias-Aware Inference in Regularized Regression Models," Working Papers 2020-2, Princeton University. Economics Department..
    111. Adam D. Nowak & Bradley S. Price & Patrick S. Smith, 2021. "Real Estate Dictionaries Across Space and Time," The Journal of Real Estate Finance and Economics, Springer, vol. 62(1), pages 139-163, January.
    112. Cheng, Xu & Liao, Zhipeng, 2015. "Select the valid and relevant moments: An information-based LASSO for GMM with many moments," Journal of Econometrics, Elsevier, vol. 186(2), pages 443-464.
    113. Ash, Elliott & Chen, Daniel L. & Lu, Wei, 2018. "Motivated Reasoning in the Field: Partisanship in Precedent, Prose, Vote, and Retirement in U.S. Circuit Courts, 1800-2013," IAST Working Papers 18-89, Institute for Advanced Study in Toulouse (IAST).
    114. Caner, Mehmet & Kock, Anders Bredahl, 2018. "Asymptotically honest confidence regions for high dimensional parameters by the desparsified conservative Lasso," Journal of Econometrics, Elsevier, vol. 203(1), pages 143-168.
    115. Guilherme Lichand & Anandi Mani, 2020. "Cognitive droughts," ECON - Working Papers 341, Department of Economics - University of Zurich.
    116. MArcelo C. Medeiros & Eduardo F.Mendes, 2012. "Estimating High-Dimensional Time Series Models," Textos para discussão 602, Department of Economics PUC-Rio (Brazil).
    117. 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.
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    302. Brett R. Gordon & Mitchell J. Lovett & Bowen Luo & James C. Reeder, 2023. "Disentangling the Effects of Ad Tone on Voter Turnout and Candidate Choice in Presidential Elections," Management Science, INFORMS, vol. 69(1), pages 220-243, January.
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    304. Renan P. de Oliveira & Alessandro V. M. Oliveira & Gui Lohmann, 2021. "A Network-Design Analysis of Airline Business Model Adaptation in the Face of Competition and Consolidation," Transportation Science, INFORMS, vol. 55(2), pages 532-548, March.
    305. Mr. Andrew J Tiffin, 2019. "Machine Learning and Causality: The Impact of Financial Crises on Growth," IMF Working Papers 2019/228, International Monetary Fund.
    306. Fan, Jianqing & Guo, Yongyi & Jiang, Bai, 2022. "Adaptive Huber regression on Markov-dependent data," Stochastic Processes and their Applications, Elsevier, vol. 150(C), pages 802-818.
    307. 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.
    308. Pieter Bakx & Bram Wouterse & Eddy (E.K.A.) van Doorslaer & Albert Wong, 2018. "Better off at home? Effects of a nursing home admission on costs, hospitalizations and survival," Tinbergen Institute Discussion Papers 18-060/V, Tinbergen Institute.
    309. 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.
    310. Djenontin, Ida Nadia S. & Zulu, Leo C. & Richardson, Robert B., 2022. "Smallholder farmers and forest landscape restoration in sub-Saharan Africa: Evidence from Central Malawi," Land Use Policy, Elsevier, vol. 122(C).
    311. Elliott Ash & Daniel L. Chen & Sergio Galletta, 2022. "Measuring Judicial Sentiment: Methods and Application to US Circuit Courts," Post-Print hal-03597819, HAL.
    312. Vira Semenova & Matt Goldman & Victor Chernozhukov & Matt Taddy, 2023. "Inference on heterogeneous treatment effects in high‐dimensional dynamic panels under weak dependence," Quantitative Economics, Econometric Society, vol. 14(2), pages 471-510, May.
    313. Hübler, Olaf, 2021. "COVID-19 Spread in Germany from a Regional Perspective," IZA Discussion Papers 14669, Institute of Labor Economics (IZA).
    314. Brieland, Stephanie & Töpfer, Marina, 2020. "The gender pay gap revisited: Does machine learning offer new insights?," Discussion Papers 111, Friedrich-Alexander University Erlangen-Nuremberg, Chair of Labour and Regional Economics.
    315. Harold D. Chiang, 2018. "Many Average Partial Effects: with An Application to Text Regression," Papers 1812.09397, arXiv.org, revised Jan 2022.
    316. Anna Mikusheva & Liyang Sun, 2023. "Weak Identification with Many Instruments," Papers 2308.09535, arXiv.org, revised Jan 2024.
    317. Giulia Brancaccio & Myrto Kalouptsidi & Theodore Papageorgiou & Nicola Rosaia, 2020. "Search Frictions and Efficiency in Decentralized Transportation Markets," NBER Working Papers 27300, National Bureau of Economic Research, Inc.
    318. Kaila, Heidi & Azad, Abul, 2023. "The effects of crime and violence on food insecurity and consumption in Nigeria," Food Policy, Elsevier, vol. 115(C).
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    320. 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.
    321. Li, Zhaoyuan & Yao, Jianfeng, 2019. "Testing for heteroscedasticity in high-dimensional regressions," Econometrics and Statistics, Elsevier, vol. 9(C), pages 122-139.
    322. Agboola, Oluwagbenga David & Yu, Han, 2023. "Neighborhood-based cross fitting approach to treatment effects with high-dimensional data," Computational Statistics & Data Analysis, Elsevier, vol. 186(C).
    323. Bellmann, Lutz & Hübler, Olaf, 2019. "Personal Attitudes, Job Characteristics and Health," IZA Discussion Papers 12597, Institute of Labor Economics (IZA).
    324. Yue Cai, 2021. "Measuring Market Power in the IPO Underwriter," Working Papers 2108, Waseda University, Faculty of Political Science and Economics.
    325. Arthur Charpentier & Emmanuel Flachaire & Antoine Ly, 2017. "Econom\'etrie et Machine Learning," Papers 1708.06992, arXiv.org, revised Mar 2018.
    326. Shi, Zhentao, 2016. "Econometric estimation with high-dimensional moment equalities," Journal of Econometrics, Elsevier, vol. 195(1), pages 104-119.
    327. 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.
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    329. Lan, Wei & Zhong, Ping-Shou & Li, Runze & Wang, Hansheng & Tsai, Chih-Ling, 2016. "Testing a single regression coefficient in high dimensional linear models," Journal of Econometrics, Elsevier, vol. 195(1), pages 154-168.
    330. Mehmet Caner, 2021. "A Starting Note: A Historical Perspective in Lasso," International Econometric Review (IER), Econometric Research Association, vol. 13(1), pages 1-3, March.
    331. Sølvsten, Mikkel, 2020. "Robust estimation with many instruments," Journal of Econometrics, Elsevier, vol. 214(2), pages 495-512.
    332. Victor Chernozhukov & Whitney K. Newey & Rahul Singh, 2022. "Automatic Debiased Machine Learning of Causal and Structural Effects," Econometrica, Econometric Society, vol. 90(3), pages 967-1027, May.
    333. 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.
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    336. 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).
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    338. Mitchell J. Lovett, 2019. "Empirical Research on Political Marketing: a Selected Review," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 6(3), pages 49-56, December.
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    344. Thomas Wiemann, 2023. "Optimal Categorical Instrumental Variables," Papers 2311.17021, arXiv.org.
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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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. Hallin, Marc & La Vecchia, Davide, 2017. "R-estimation in semiparametric dynamic location-scale models," Journal of Econometrics, Elsevier, vol. 196(2), pages 233-247.
    9. 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.
    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. 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.
    12. Norman, Stephen & Phillips, Kerk L., 2009. "What is the Shape of Real Exchange Rate Nonlinearity?," MPRA Paper 23504, University Library of Munich, Germany.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.

  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. 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).
    2. 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.
    3. 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.
    4. Amsler, Christine & Prokhorov, Artem & Schmidt, Peter, 2016. "Endogeneity in stochastic frontier models," Journal of Econometrics, Elsevier, vol. 190(2), pages 280-288.
    5. 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).
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. Poirier, Alexandre, 2017. "Efficient estimation in models with independence restrictions," Journal of Econometrics, Elsevier, vol. 196(1), pages 1-22.
    11. 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).
    12. 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).
    13. 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.
    14. 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.
    15. 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.
    16. Tsionas, Efthymios G., 2013. "Bayesian inference in regression with Pearson disturbances," Economics Letters, Elsevier, vol. 118(1), pages 177-181.
    17. 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.
    18. Scott A. Carson & James B. McDonald, 2018. "Partially Adaptive Econometric Methods and the Modern Obesity Epidemic," CESifo Working Paper Series 7058, CESifo.
    19. Sølvsten, Mikkel, 2020. "Robust estimation with many instruments," Journal of Econometrics, Elsevier, vol. 214(2), pages 495-512.
    20. 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.
    21. 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.

  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. Cássio Roberto de Andrade Alves & Márcio Laurini, 2023. "Estimating the Capital Asset Pricing Model with Many Instruments: A Bayesian Shrinkage Approach," Mathematics, MDPI, vol. 11(17), pages 1-20, September.
    2. Yukitoshi Matsushita & Taisuke Otsu, 2020. "Jackknife Lagrange multiplier test with many weak instruments," STICERD - Econometrics Paper Series 613, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    3. Herbst, Chris M., 2012. "The Impact of Non-Parental Child Care on Child Development: Evidence from the Summer Participation "Dip"," IZA Discussion Papers 7039, Institute of Labor Economics (IZA).
    4. Murray Michael P., 2017. "Linear Model IV Estimation When Instruments Are Many or Weak," Journal of Econometric Methods, De Gruyter, vol. 6(1), pages 1-22, January.
    5. 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.
    6. Karol Szafranek, 2016. "Linking excessive disinflation and output movements in an emerging, small open economy A hybrid New Keynesian Phillips Curve perspective," NBP Working Papers 239, Narodowy Bank Polski.
    7. Besfamille, Martín & Jorrat, Diego A. & Manzano, Osmel & Quiroga, Bernardo F. & Sanguinetti, Pablo, 2023. "How do subnational governments react to shocks to different revenue sources? Evidence from hydrocarbon-producing provinces in Argentina," Journal of Urban Economics, Elsevier, vol. 136(C).
    8. Bertille Antoine & Pascal Lavergne, 2020. "Identification-Robust Nonparametric Interference in a Linear IV Model," Discussion Papers dp20-03, Department of Economics, Simon Fraser University.
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Articles

  1. 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.
  2. 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. 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.

  3. 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.
  4. 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.
  5. 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.
  6. 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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. Michael P. Leung, 2023. "Network Cluster‐Robust Inference," Econometrica, Econometric Society, vol. 91(2), pages 641-667, March.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. James G. MacKinnon & Morten Ørregaard Nielsen & Matthew D. Webb, 2023. "Fast and reliable jackknife and bootstrap methods for cluster‐robust inference," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(5), pages 671-694, August.
    11. 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).
    12. 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.
    13. Harakeh, Mostafa, 2020. "Dividend policy and corporate investment under information shocks," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 65(C).
    14. Yong Cai & Ivan A. Canay & Deborah Kim & Azeem M. Shaikh, 2021. "On the implementation of Approximate Randomization Tests in Linear Models with a Small Number of Clusters," Papers 2102.09058, arXiv.org, revised Mar 2022.
    15. 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.
    16. 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.
    17. 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).
    18. 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).
    19. 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.
    20. 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.
    21. 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.

  7. 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.
  8. 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. Amit Sharma & Emre Kiciman, 2020. "DoWhy: An End-to-End Library for Causal Inference," Papers 2011.04216, arXiv.org.
    2. 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.
    3. 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," SciencePo Working papers Main hal-03813557, HAL.
    4. Victor Chernozhukov & Carlos Cinelli & Whitney Newey & Amit Sharma & Vasilis Syrgkanis, 2021. "Long Story Short: Omitted Variable Bias in Causal Machine Learning," Papers 2112.13398, arXiv.org, revised Nov 2023.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. Sven Klaassen & Jannis Kuck & Martin Spindler & Victor Chernozhukov, 2018. "Uniform Inference in High-Dimensional Gaussian Graphical Models," Papers 1808.10532, arXiv.org, revised Dec 2018.
    12. Huber Martin & Wüthrich Kaspar, 2019. "Local Average and Quantile Treatment Effects Under Endogeneity: A Review," Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-27, January.
    13. Miruna Oprescu & Vasilis Syrgkanis & Zhiwei Steven Wu, 2018. "Orthogonal Random Forest for Causal Inference," Papers 1806.03467, arXiv.org, revised Sep 2019.
    14. Julia Hatamyar & Noemi Kreif, 2023. "Policy Learning with Rare Outcomes," Papers 2302.05260, arXiv.org, revised Oct 2023.
    15. Aristide Houndetoungan & Abdoul Haki Maoude, 2024. "Inference for Two-Stage Extremum Estimators," Papers 2402.05030, arXiv.org.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. 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).
    22. 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.
    23. Jiaming Mao & Zhesheng Zheng, 2020. "Structural Regularization," Papers 2004.12601, arXiv.org, revised Jun 2020.
    24. Su, Liangjun & Ura, Takuya & Zhang, Yichong, 2019. "Non-separable models with high-dimensional data," Journal of Econometrics, Elsevier, vol. 212(2), pages 646-677.
    25. Yuya Sasaki & Takuya Ura & Yichong Zhang, 2020. "Unconditional Quantile Regression with High Dimensional Data," Papers 2007.13659, arXiv.org, revised Feb 2022.
    26. 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.
    27. 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).
    28. Sant’Anna, Pedro H.C. & Zhao, Jun, 2020. "Doubly robust difference-in-differences estimators," Journal of Econometrics, Elsevier, vol. 219(1), pages 101-122.
    29. 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).
    30. 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).
    31. Jiaming Mao & Jingzhi Xu, 2020. "Ensemble Learning with Statistical and Structural Models," Papers 2006.05308, arXiv.org.
    32. Ricardo P. Masini & Marcelo C. Medeiros & Eduardo F. Mendes, 2023. "Machine learning advances for time series forecasting," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 76-111, February.
    33. Jonas Metzger, 2022. "Adversarial Estimators," Papers 2204.10495, arXiv.org, revised Jun 2022.
    34. Laura Derksen & Jason Kerwin & Natalia Ordaz Reynoso & Olivier Sterck, 2021. "Appointments: A More Effective Commitment Device for Health Behaviors," Papers 2110.06876, arXiv.org.
    35. 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.
    36. 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.
    37. Ruoxuan Xiong & Allison Koenecke & Michael Powell & Zhu Shen & Joshua T. Vogelstein & Susan Athey, 2021. "Federated Causal Inference in Heterogeneous Observational Data," Papers 2107.11732, arXiv.org, revised Apr 2023.
    38. Anna Baiardi & Andrea A. Naghi, 2021. "The Value Added of Machine Learning to Causal Inference: Evidence from Revisited Studies," Papers 2101.00878, arXiv.org.
    39. Yong Bian & Xiqian Wang & Qin Zhang, 2023. "How Does China's Household Portfolio Selection Vary with Financial Inclusion?," Papers 2311.01206, arXiv.org.
    40. 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.
    41. Gustavo J. Bobonis & Paul Gertler & Marco Gonzalez-Navarro & Simeon Nichter, 2023. "Does Combating Corruption Reduce Clientelism?," NBER Working Papers 31266, National Bureau of Economic Research, Inc.
    42. 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.
    43. 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.
    44. Phillip Heiler, 2020. "Efficient Covariate Balancing for the Local Average Treatment Effect," Papers 2007.04346, arXiv.org.
    45. 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.
    46. Vira Semenova, 2018. "Machine Learning for Dynamic Discrete Choice," Papers 1808.02569, arXiv.org, revised Nov 2018.
    47. 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.
    48. Matt Goldman & Brian Quistorff, 2018. "Pricing Engine: Estimating Causal Impacts in Real World Business Settings," Papers 1806.03285, arXiv.org, revised Jun 2018.
    49. 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.
    50. 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.
    51. 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.
    52. Stephan Martin, 2022. "Estimation of Conditional Random Coefficient Models using Machine Learning Techniques," Papers 2201.08366, arXiv.org.
    53. 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.
    54. 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.
    55. Ziwei Mei & Zhentao Shi, 2022. "On LASSO for High Dimensional Predictive Regression," Papers 2212.07052, arXiv.org, revised Jan 2024.
    56. 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.
    57. Vira Semenova, 2017. "Debiased Machine Learning of Set-Identified Linear Models," Papers 1712.10024, arXiv.org, revised Dec 2022.
    58. 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.
    59. 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.
    60. 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.
    61. Victor Chernozhukov & Whitney Newey & Vira Semenova, 2019. "Inference on weighted average value function in high-dimensional state space," Papers 1908.09173, arXiv.org.
    62. Gazeaud, Jules & Khan, Nausheen & Mvukiyehe, Eric & Sterck, Olivier, 2023. "With or without him? Experimental evidence on cash grants and gender-sensitive trainings in Tunisia," Journal of Development Economics, Elsevier, vol. 165(C).
    63. 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.
    64. 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).
    65. Dmitry Arkhangelsky & Guido Imbens, 2023. "Causal Models for Longitudinal and Panel Data: A Survey," Papers 2311.15458, arXiv.org, revised Mar 2024.
    66. Max Cytrynbaum, 2021. "Optimal Stratification of Survey Experiments," Papers 2111.08157, arXiv.org, revised Aug 2023.
    67. 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.
    68. 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.
    69. Fernando Delbianco & Fernando Tohmé, 2023. "Individualized Conformal," Working Papers 247, Red Nacional de Investigadores en Economía (RedNIE).
    70. Elliott Ash & Daniel L. Chen & Sergio Galletta, 2022. "Measuring Judicial Sentiment: Methods and Application to US Circuit Courts," Post-Print hal-03597819, HAL.
    71. 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.
    72. Dongcheng Zhang & Kunpeng Zhang, 2020. "Weighting-Based Treatment Effect Estimation via Distribution Learning," Papers 2012.13805, arXiv.org, revised May 2023.
    73. 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.
    74. 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.
    75. 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).
    76. Marica Valente, 2021. "Policy Evaluation of Waste Pricing Programs Using Heterogeneous Causal Effect Estimation," Discussion Papers of DIW Berlin 1980, DIW Berlin, German Institute for Economic Research.
    77. 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.
    78. 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.
    79. 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.
    80. 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.
    81. Sven Klaassen & Jannis Kueck & Martin Spindler, 2017. "Transformation Models in High-Dimensions," Papers 1712.07364, arXiv.org.

  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. 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. 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.
    2. Gupta, Abhimanyu & Hidalgo, Javier, 2022. "Nonparametric prediction with spatial data," LSE Research Online Documents on Economics 115292, London School of Economics and Political Science, LSE Library.
    3. 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, Ryerson University, Department of Economics.
    4. Kaicheng Chen & Timothy J. Vogelsang, 2023. "Fixed-b Asymptotics for Panel Models with Two-Way Clustering," Papers 2309.08707, arXiv.org, revised Oct 2023.
    5. Ulrich K. Muller & Mark W. Watson, 2021. "Spatial Correlation Robust Inference," Papers 2102.09353, arXiv.org.
    6. Timothy G. Conley & Sílvia Gonçalves & Min Seong Kim & Benoit Perron, 2023. "Bootstrap inference under cross‐sectional dependence," Quantitative Economics, Econometric Society, vol. 14(2), pages 511-569, May.
    7. 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.
    8. J. Hidalgo & M. Schafgans, 2020. "Inference without smoothing for large panels with cross-sectional and temporal dependence," Papers 2006.14409, arXiv.org.
    9. David Powell, 2017. "Inference with Correlated Clusters," Working Papers WR-1137-1, RAND Corporation.
    10. Bartalotti Otávio, 2019. "Regression Discontinuity and Heteroskedasticity Robust Standard Errors: Evidence from a Fixed-Bandwidth Approximation," Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-26, January.
    11. Gupta, Abhimanyu, 2018. "Autoregressive spatial spectral estimates," Journal of Econometrics, Elsevier, vol. 203(1), pages 80-95.
    12. Ulrich K. Müller & Mark W. Watson, 2021. "Spatial Correlation Robust Inference," Working Papers 2021-61, Princeton University. Economics Department..
    13. 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.
    14. Eduardo A. Souza-Rodrigues, 2016. "Nonparametric Regression with Common Shocks," Econometrics, MDPI, vol. 4(3), pages 1-17, September.
    15. Ye, Xiaoqing & Sun, Yixiao, 2018. "Heteroscedasticity and Autocorrelation Robust F and t Tests in Stata," University of California at San Diego, Economics Working Paper Series qt0bb8d0s9, Department of Economics, UC San Diego.
    16. 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. 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. Boyuan Zhang, 2020. "Forecasting with Bayesian Grouped Random Effects in Panel Data," Papers 2007.02435, arXiv.org, revised Oct 2020.
    2. 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.
    3. 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.
    4. 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.
    5. Arsham Reisinezhad, 2018. "Economic Growth and Income Inequality in Resource Countries: Theory and Evidence," PSE Working Papers halshs-01707976, HAL.
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    23. 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.
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  13. 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.
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    See citations under working paper version above.
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    3. 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.
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    6. 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.
    7. Athey, Susan & Bergstrom, Katy & Hadad, Vitor & Jamison, Julian C. & Ozler, Berk & Parisotto, Luca & Sama, Julius Dohbit, 2021. "Shared Decision-Making: Can Improved Counseling Increase Willingness to Pay for Modern Contraceptives?," Research Papers 3987, Stanford University, Graduate School of Business.
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    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.
    3. Alena Skolkova, 2023. "Model Averaging with Ridge Regularization," CERGE-EI Working Papers wp758, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    4. Marine Carrasco & Guy Tchuente, 2015. "Regularized LIML for many instruments," Studies in Economics 1515, School of Economics, University of Kent.
    5. Jiafeng Chen & Daniel L. Chen & Greg Lewis, 2020. "Mostly Harmless Machine Learning: Learning Optimal Instruments in Linear IV Models," Papers 2011.06158, arXiv.org, revised Jun 2021.
    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. Stephen Coussens & Jann Spiess, 2021. "Improving Inference from Simple Instruments through Compliance Estimation," Papers 2108.03726, arXiv.org.
    8. Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Post-selection and post-regularization inference in linear models with many controls and instruments," CeMMAP working papers 02/15, Institute for Fiscal Studies.
    9. Marine Carrasco & Guy Tchuente, 2016. "Efficient Estimation with Many Weak Instruments Using Regularization Techniques," Econometric Reviews, Taylor & Francis Journals, vol. 35(8-10), pages 1609-1637, December.
    10. Emmanuel Selorm Tsyawo, 2023. "Feasible IV regression without excluded instruments," The Econometrics Journal, Royal Economic Society, vol. 26(2), pages 235-256.
    11. 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.
    12. Christoph Breunig & Enno Mammen & Anna Simoni, 2018. "Ill-posed Estimation in High-Dimensional Models with Instrumental Variables," Papers 1806.00666, arXiv.org, revised Aug 2020.
    13. Joshua D. Angrist & Brigham Frandsen, 2022. "Machine Labor," Journal of Labor Economics, University of Chicago Press, vol. 40(S1), pages 97-140.
    14. Qingliang Fan & Yaqian Wu, 2020. "Endogenous Treatment Effect Estimation with some Invalid and Irrelevant Instruments," Papers 2006.14998, arXiv.org.
    15. 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.
    16. Dennis Lim & Wenjie Wang & Yichong Zhang, 2022. "A Conditional Linear Combination Test with Many Weak Instruments," Papers 2207.11137, arXiv.org, revised Apr 2023.
    17. Damian Kozbur, 2015. "Testing-Based Forward Model Selection," ECON - Working Papers 283, Department of Economics - University of Zurich, revised Apr 2018.
    18. Cheng Hsiao & Qiankun Zhou, 2017. "JIVE for Panel Dynamic Simultaneous Equations Models," Departmental Working Papers 2017-10, Department of Economics, Louisiana State University.
    19. 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.
    20. Gold, David & Lederer, Johannes & Tao, Jing, 2020. "Inference for high-dimensional instrumental variables regression," Journal of Econometrics, Elsevier, vol. 217(1), pages 79-111.
    21. Jinyuan Chang & Zhentao Shi & Jia Zhang, 2021. "Culling the herd of moments with penalized empirical likelihood," Papers 2108.03382, arXiv.org, revised May 2022.
    22. Victor Chernozhukov & Christian Hansen & Martin Spindler, 2016. "Valid post-selection and post-regularization inference: An elementary, general approach," CeMMAP working papers 36/16, Institute for Fiscal Studies.
    23. Qingliang Fan & Zijian Guo & Ziwei Mei, 2022. "A Heteroskedasticity-Robust Overidentifying Restriction Test with High-Dimensional Covariates," Papers 2205.00171, arXiv.org, revised Mar 2023.
    24. Christian Hansen & Damian Kozbur & Sanjog Misra, 2016. "Targeted undersmoothing," ECON - Working Papers 282, Department of Economics - University of Zurich, revised Apr 2018.
    25. Abdul-Nasah Soale & Emmanuel Selorm Tsyawo, 2023. "Clustered Covariate Regression," Papers 2302.09255, arXiv.org, revised Jul 2023.
    26. Max-Sebastian Dov`i & Anders Bredahl Kock & Sophocles Mavroeidis, 2022. "A Ridge-Regularised Jackknifed Anderson-Rubin Test," Papers 2209.03259, arXiv.org, revised Nov 2023.
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    Cited by:

    1. Bertille Antoine & Pascal Lavergne, 2020. "Identification-Robust Nonparametric Interference in a Linear IV Model," Discussion Papers dp20-03, Department of Economics, Simon Fraser University.
    2. Barnichon, Regis & Mesters, Geert, 2019. "Identifying Modern Macro Equations with Old Shocks," CEPR Discussion Papers 13765, C.E.P.R. Discussion Papers.
    3. Kleibergen, Frank, 2021. "Efficient size correct subset inference in homoskedastic linear instrumental variables regression," Journal of Econometrics, Elsevier, vol. 221(1), pages 78-96.
    4. Bertille Antoine & Pascal Lavergne, 2019. "Identification-Robust Nonparametric Inference in a Linear IV Model," Discussion Papers dp19-02, Department of Economics, Simon Fraser University.
    5. 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.
    6. Donald W. K. Andrews & Patrik Guggenberger, 2015. "Identification- and Singularity-Robust Inference for Moment Condition," Cowles Foundation Discussion Papers 1978R2, Cowles Foundation for Research in Economics, Yale University, revised Jan 2019.
    7. Giuseppe Cavaliere & Zeng-Hua Lu & Anders Rahbek & Yuhong Yang, 2021. "MinP Score Tests with an Inequality Constrained Parameter Space," Papers 2107.06089, arXiv.org.
    8. 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.
    9. 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.
    10. 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).
    11. Tetsuya Kaji, 2019. "Theory of Weak Identification in Semiparametric Models," Papers 1908.10478, arXiv.org, revised Aug 2020.
    12. 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).

  24. Bester, C. Alan & Hansen, Christian, 2009. "Identification of Marginal Effects in a Nonparametric Correlated Random Effects Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(2), pages 235-250.

    Cited by:

    1. 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.
    2. Chernozhukov, Victor & Fernández-Val, Iván & Hoderlein, Stefan & Holzmann, Hajo & Newey, Whitney, 2015. "Nonparametric identification in panels using quantiles," Journal of Econometrics, Elsevier, vol. 188(2), pages 378-392.
    3. 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 Dec 2023.
    4. 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.
    5. Čížek, Pavel & Lei, Jinghua, 2018. "Identification and estimation of nonseparable single-index models in panel data with correlated random effects," Journal of Econometrics, Elsevier, vol. 203(1), pages 113-128.
    6. Stefan Hoderlein & Halbert White, 2009. "Nonparametric identification in nonseparable panel data models with generalized fixed effects," CeMMAP working papers CWP33/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    7. Bester, C. Alan & Hansen, Christian B., 2016. "Grouped effects estimators in fixed effects models," Journal of Econometrics, Elsevier, vol. 190(1), pages 197-208.
    8. Connor, Gregory & Hagmann, Matthias & Linton, Oliver, 2007. "Efficient estimation of a semiparametric characteristic-based factor model of security returns," LSE Research Online Documents on Economics 24504, London School of Economics and Political Science, LSE Library.
    9. Shakeeb Khan & Maria Ponomareva & Elie Tamer, 2011. "Identification of Panel Data Models with Endogenous Censoring," Working Papers 11-07, Duke University, Department of Economics.
    10. Sarojini Hirshleifer & Dalia Ghanem & Karen Ortiz-Becerra, 2019. "Testing for Attrition Bias in Field Experiments," Working Papers 201919, University of California at Riverside, Department of Economics, revised Aug 2019.
    11. Dalia Ghanem & Pedro H. C. Sant'Anna & Kaspar Wuthrich, 2022. "Selection and parallel trends," Papers 2203.09001, arXiv.org, revised Mar 2024.
    12. 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.
    13. Lu, Xun & White, Halbert, 2014. "Testing for separability in structural equations," Journal of Econometrics, Elsevier, vol. 182(1), pages 14-26.
    14. Chen, Mingli, 2016. "Estimation of Nonlinear Panel Models with Multiple Unobserved Effects," Economic Research Papers 269326, University of Warwick - Department of Economics.
    15. 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.
    16. 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.
    17. Sadikoglu, Serhan, 2019. "Essays in econometric theory," Other publications TiSEM 99d83644-f9dc-49e3-a4e1-5, Tilburg University, School of Economics and Management.
    18. 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.
    19. Amaresh K Tiwari, 2021. "A Control Function Approach to Estimate Panel Data Binary Response Model," Papers 2102.12927, arXiv.org, revised Sep 2021.
    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. Irene Botosaru & Chris Muris, 2022. "Identification of time-varying counterfactual parameters in nonlinear panel models," Papers 2212.09193, arXiv.org, revised Nov 2023.
    23. 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.
    24. 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.
    25. Cavit Pakel & Martin Weidner, 2023. "Bounds on Average Effects in Discrete Choice Panel Data Models," Papers 2309.09299, arXiv.org, revised Dec 2023.
    26. Louise Laage, 2020. "A Correlated Random Coefficient Panel Model with Time-Varying Endogeneity," Papers 2003.09367, arXiv.org, revised Nov 2022.
    27. Ghanem, Dalia & Hirshleifer, Sarojini & Ortiz-Becerra, Karen, 2019. "Testing Attrition Bias in Field Experiments," 2019 Annual Meeting, July 21-23, Atlanta, Georgia 291215, Agricultural and Applied Economics Association.
    28. Ghanem, Dalia, 2017. "Testing identifying assumptions in nonseparable panel data models," Journal of Econometrics, Elsevier, vol. 197(2), pages 202-217.

  25. 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. 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.
    2. 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.
    3. 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.
    4. Victor Chernozhukov & Christian Hansen & Kaspar Wuthrich, 2020. "Instrumental Variable Quantile Regression," Papers 2009.00436, arXiv.org.
    5. Purevdorj Tuvaandorj, 2021. "Robust Permutation Tests in Linear Instrumental Variables Regression," Papers 2111.13774, arXiv.org, revised Jun 2023.
    6. 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.
    7. 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.
    8. David M. Kaplan, 2023. "Smoothed instrumental variables quantile regression," Papers 2310.09013, arXiv.org.
    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. 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.
    11. Luciano de Castro & Antonio F. Galvao & David M. Kaplan, 2017. "Smoothed instrumental variables quantile regression, with estimation of quantile Euler equations," Working Papers 1710, Department of Economics, University of Missouri, revised 28 Feb 2018.
    12. Wüthrich, Kaspar, 2019. "A closed-form estimator for quantile treatment effects with endogeneity," Journal of Econometrics, Elsevier, vol. 210(2), pages 219-235.
    13. 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.
    14. Joel L. Horowitz, 2017. "Non-asymptotic inference in instrumental variables estimation," CeMMAP working papers 46/17, Institute for Fiscal Studies.
    15. 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.
    16. Zhongjun Qu & Jungmo Yoon, 2019. "Uniform Inference on Quantile Effects under Sharp Regression Discontinuity Designs," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(4), pages 625-647, October.
    17. Zhongjun Qu & Jungmo Yoon, 2011. "Nonparametric Estimation and Inference on Conditional Quantile Processes," Boston University - Department of Economics - Working Papers Series WP2011-059, Boston University - Department of Economics.
    18. Olivier Gossner & Karl H. Schlag, 2013. "Finite-sample exact tests for linear regressions with bounded dependent variables," Post-Print halshs-00879792, HAL.
    19. 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).
    20. Otsu, Taisuke, 2008. "Conditional empirical likelihood estimation and inference for quantile regression models," Journal of Econometrics, Elsevier, vol. 142(1), pages 508-538, January.
    21. David M. Kaplan & Yixiao Sun, 2013. "Smoothed Estimating Equations for Instrumental Variables Quantile Regression," Working Papers 1314, Department of Economics, University of Missouri.
    22. Javier Alejo & Antonio F Galvao & Gabriel Montes-Rojas, 2023. "A first-stage representation for instrumental variables quantile regression," The Econometrics Journal, Royal Economic Society, vol. 26(3), pages 350-377.
    23. Lukáš Lafférs, 2019. "Identification in Models with Discrete Variables," Computational Economics, Springer;Society for Computational Economics, vol. 53(2), pages 657-696, February.
    24. Adam Rosen & Takuya Ura, 2020. "Finite Sample Inference for the Maximum Score Estimand," CeMMAP working papers CWP22/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    25. 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.
    26. David M. Kaplan, 2020. "sivqr: Smoothed IV quantile regression," Working Papers 2009, Department of Economics, University of Missouri.
    27. Christis Katsouris, 2023. "Quantile Time Series Regression Models Revisited," Papers 2308.06617, arXiv.org, revised Aug 2023.
    28. Joel L. Horowitz, 2018. "Non-Asymptotic Inference in Instrumental Variables Estimation," Papers 1809.03600, arXiv.org.
    29. Isaiah Andrews & Anna Mikusheva, 2022. "Optimal Decision Rules for Weak GMM," Econometrica, Econometric Society, vol. 90(2), pages 715-748, March.
    30. Jun, Sung Jae, 2008. "Weak identification robust tests in an instrumental quantile model," Journal of Econometrics, Elsevier, vol. 144(1), pages 118-138, May.
    31. V. Chernozhukov & C. Hansen, 2013. "Quantile Models with Endogeneity," Annual Review of Economics, Annual Reviews, vol. 5(1), pages 57-81, May.
    32. 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.
    33. 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.
    34. 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.
    35. 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.
    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. Kaspar W thrich, 2015. "Semiparametric estimation of quantile treatment effects with endogeneity," Diskussionsschriften dp1509, Universitaet Bern, Departement Volkswirtschaft.

  26. 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. Johannes S. Kunz & Kevin E. Staub & Rainer Winkelmann, 2021. "Predicting Individual Effects in Fixed Effects Panel Probit Models," SoDa Laboratories Working Paper Series 2021-05, Monash University, SoDa Laboratories.
    2. 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.
    3. Galvao, Antonio F. & Kato, Kengo, 2016. "Smoothed quantile regression for panel data," Journal of Econometrics, Elsevier, vol. 193(1), pages 92-112.
    4. 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.
    5. Geert Dhaene & Koen Jochmans, 2014. "Split-Panel Jackknife Estimation of Fixed-Effect Models," Sciences Po Economics Discussion Papers 2014-03, Sciences Po Departement of Economics.
    6. 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).
    7. 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.
    8. Yoonseok Lee & Peter C.B. Phillips, 2013. "Model Selection in the Presence of Incidental Parameters," Cowles Foundation Discussion Papers 1919, Cowles Foundation for Research in Economics, Yale University.
    9. 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.
    10. Čížek, Pavel & Lei, Jinghua, 2018. "Identification and estimation of nonseparable single-index models in panel data with correlated random effects," Journal of Econometrics, Elsevier, vol. 203(1), pages 113-128.
    11. Geert Dhaene & Koen Jochmans, 2011. "Profile-score Adjustements for Nonlinearfixed-effect Models," SciencePo Working papers Main hal-01073733, HAL.
    12. Johannes S. Kunz & Kevin E. Staub & Rainer Winkelmann, 2019. "Predicting fixed effects in panel probit models," Monash Economics Working Papers 10-19, Monash University, Department of Economics.
    13. Geert Dhaene & Koen Jochmans, 2013. "Likelihood inference in an Autoregression with fixed effects," SciencePo Working papers Main hal-01070434, HAL.
    14. 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).
    15. Laura Hospido, 2007. "Modelling heterogeneity and dynamics in the volatility of individual wages," Working Papers 0738, Banco de España.
    16. 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.
    17. Schumann, Martin & Severini, Thomas A. & Tripathi, Gautam, 2021. "Integrated likelihood based inference for nonlinear panel data models with unobserved effects," Journal of Econometrics, Elsevier, vol. 223(1), pages 73-95.
    18. Bester, C. Alan & Hansen, Christian B., 2016. "Grouped effects estimators in fixed effects models," Journal of Econometrics, Elsevier, vol. 190(1), pages 197-208.
    19. 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.
    20. Laura Hospido, 2012. "Estimating Nonlinear Models with Multiple Fixed Effects: A Computational Note," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 74(5), pages 760-775, October.
    21. Jesus M. Carro & Alejandra Traferri, 2014. "State Dependence And Heterogeneity In Health Using A Bias‐Corrected Fixed‐Effects Estimator," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(2), pages 181-207, March.
    22. Patrick GAGLIARDINI & Christian GOURIEROUX, 2009. "Efficiency in Large Dynamic Panel Models with Common Factor," Swiss Finance Institute Research Paper Series 09-12, Swiss Finance Institute.
    23. Lamarche, Carlos & Parker, Thomas, 2023. "Wild bootstrap inference for penalized quantile regression for longitudinal data," Journal of Econometrics, Elsevier, vol. 235(2), pages 1799-1826.
    24. 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.
    25. Manuel Arellano & Stéphane Bonhomme, 2006. "Robust Priors in Nonlinear Panel Data Models," Working Papers wp2006_0614, CEMFI.
    26. 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.
    27. Albarrán, Pedro & Carrasco, Raquel & Carro, Jesús M., 2015. "Estimation of Dynamic Nonlinear Random Effects Models with Unbalanced Panels," UC3M Working papers. Economics we1503, Universidad Carlos III de Madrid. Departamento de Economía.
    28. Iván Fernández-Val & Martin Weidner, 2018. "Fixed Effects Estimation of Large-TPanel Data Models," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 109-138, August.
    29. 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.
    30. 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.
    31. 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.
    32. Lee, Yoonseok, 2012. "Bias in dynamic panel models under time series misspecification," Journal of Econometrics, Elsevier, vol. 169(1), pages 54-60.
    33. Maurice J.G. Bun & Martin A. Carree & Arturas Juodis, 2014. "On Maximum Likelihood estimation of dynamic panel data models," UvA-Econometrics Working Papers 14-04, Universiteit van Amsterdam, Dept. of Econometrics.
    34. 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.
    35. 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.
    36. 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.
    37. Amrei Stammann, 2023. "Debiased Fixed Effects Estimation of Binary Logit Models with Three-Dimensional Panel Data," Papers 2311.04073, arXiv.org.
    38. 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.
    39. Yoshitsugu Kitazawa, 2013. "Exploration of dynamic fixed effects logit models from a traditional angle," Discussion Papers 60, Kyushu Sangyo University, Faculty of Economics.
    40. 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.
    41. Carro, Jesús M. & 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.
    42. 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.
    43. 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.
    44. 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).
    45. 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.

  27. Conley, Timothy G. & Hansen, Christian B. & McCulloch, Robert E. & Rossi, Peter E., 2008. "A semi-parametric Bayesian approach to the instrumental variable problem," Journal of Econometrics, Elsevier, vol. 144(1), pages 276-305, May.

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    1. Dyevre, Arthur & Lampach, Nicolas, 2018. "The origins of regional integration: Untangling the effect of trade on judicial cooperation," International Review of Law and Economics, Elsevier, vol. 56(C), pages 122-133.
    2. Sudhir Voleti & Pulak Ghosh, 2013. "A robust approach to measure latent, time-varying equity in hierarchical branding structures," Quantitative Marketing and Economics (QME), Springer, vol. 11(3), pages 289-319, September.
    3. Yang Li & Asim Ansari, 2014. "A Bayesian Semiparametric Approach for Endogeneity and Heterogeneity in Choice Models," Management Science, INFORMS, vol. 60(5), pages 1161-1179, May.
    4. Sjoerd van den Hauwe & Richard Paap & Dick J.C. van Dijk, 2011. "An Alternative Bayesian Approach to Structural Breaks in Time Series Models," Tinbergen Institute Discussion Papers 11-023/4, Tinbergen Institute.
    5. Jiang, Renna & Manchanda, Puneet & Rossi, Peter E., 2009. "Bayesian analysis of random coefficient logit models using aggregate data," Journal of Econometrics, Elsevier, vol. 149(2), pages 136-148, April.
    6. Sylvia Frühwirth-Schnatter & Martin Halla & Alexandra Posekany & Gerald J. Pruckner & Thomas Schober, 2014. "The Quantity and Quality of Children: A Semi-Parametric Bayesian IV Approach," Economics working papers 2014-03, Department of Economics, Johannes Kepler University Linz, Austria.
    7. Mark J. Jensen & John M. Maheu, 2008. "Bayesian semiparametric stochastic volatility modeling," FRB Atlanta Working Paper 2008-15, Federal Reserve Bank of Atlanta.
    8. Martin Halla & Martina Zweimüller, 2014. "Parental Response to Early Human Capital Shocks: Evidence from the Chernobyl Accident," NRN working papers 2014-01, The Austrian Center for Labor Economics and the Analysis of the Welfare State, Johannes Kepler University Linz, Austria.
    9. Manuel Wiesenfarth & Carlos Matías Hisgen & Thomas Kneib & Carmen Cadarso-Suarez, 2014. "Bayesian Nonparametric Instrumental Variables Regression Based on Penalized Splines and Dirichlet Process Mixtures," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(3), pages 468-482, July.
    10. Jin, Xin & Maheu, John M, 2014. "Bayesian Semiparametric Modeling of Realized Covariance Matrices," MPRA Paper 60102, University Library of Munich, Germany.
    11. Nomen Nescio, 2013. "Nomen Nescio," Tinbergen Institute Discussion Papers 12-095 not issued, Tinbergen Institute.
    12. Marcus L. Nascimento & Kelly C. M. Gonçalves & Mario Jorge Mendonça, 2023. "Spatio-Temporal Instrumental Variables Regression with Missing Data: A Bayesian Approach," Computational Economics, Springer;Society for Computational Economics, vol. 62(1), pages 29-47, June.
    13. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2013. "Historical Developments in Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 13-191/III, Tinbergen Institute.
    14. Pelenis, Justinas, 2012. "Bayesian Semiparametric Regression," Economics Series 285, Institute for Advanced Studies.
    15. Ryo Kato & Takahiro Hoshino, 2020. "Semiparametric Bayesian Instrumental Variables Estimation for Nonignorable Missing Instruments," Discussion Paper Series DP2020-06, Research Institute for Economics & Business Administration, Kobe University.
    16. Anupriya & Daniel J. Graham & Daniel Horcher & Prateek Bansal, 2021. "Revisiting the empirical fundamental relationship of traffic flow for highways using a causal econometric approach," Papers 2104.02399, arXiv.org.
    17. Martin Burda & Artem Prokhorov, 2012. "Copula Based Factorization in Bayesian Multivariate Infinite Mixture Models," Working Papers 12012, Concordia University, Department of Economics.
    18. Jean-Pierre H. Dubé, 2018. "Microeconometric Models of Consumer Demand," NBER Working Papers 25215, National Bureau of Economic Research, Inc.
    19. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2014. "On the Rise of Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 14-085/III, Tinbergen Institute, revised 04 Sep 2014.
    20. Bradlow, Eric T. & Gangwar, Manish & Kopalle, Praveen & Voleti, Sudhir, 2017. "The Role of Big Data and Predictive Analytics in Retailing," Journal of Retailing, Elsevier, vol. 93(1), pages 79-95.
    21. Nascimento, Marcus Gerardus Lavagnole & Abanto-Valle, Carlos Antonio & Mendonça, Mario Jorge, 2019. "Multivariate Spatial IV Regression," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 38(2), January.
    22. Ruochen Wu & Melvyn Weeks, 2020. "A Semi-Parametric Bayesian Generalized Least Squares Estimator," Papers 2011.10252, arXiv.org, revised Jan 2023.
    23. Cem Çakmakli, 2012. "Bayesian Semiparametric Dynamic Nelson-Siegel Model," Working Paper series 59_12, Rimini Centre for Economic Analysis, revised Sep 2012.
    24. Pogonyi, Csaba G. & Graham, Daniel J. & Carbo, Jose M., 2021. "Metros, agglomeration and displacement. Evidence from London," Regional Science and Urban Economics, Elsevier, vol. 90(C).
    25. Haoyan Sun & Jianqing Chen & Ming Fan, 2021. "Effect of Live Chat on Traffic‐to‐Sales Conversion: Evidence from an Online Marketplace," Production and Operations Management, Production and Operations Management Society, vol. 30(5), pages 1201-1219, May.
    26. Njuki, Eric & Bravo-Ureta, Boris, 2014. "A Bayesian Approach to Analyzing the Economic Costs of Environmental Regulation in U.S. Dairy Farming," Working Papers 33, University of Connecticut, Department of Agricultural and Resource Economics, Charles J. Zwick Center for Food and Resource Policy.
    27. Ben Deaner, 2019. "Nonparametric Instrumental Variables Estimation Under Misspecification," Papers 1901.01241, arXiv.org, revised Dec 2022.
    28. Andros Kourtellos & Alex Lenkoski & Kyriakos Petrou, 2017. "Measuring the Strength of the Theories of Government Size," University of Cyprus Working Papers in Economics 11-2017, University of Cyprus Department of Economics.
    29. Ryo Kato & Takahiro Hoshino, 2018. "Semiparametric Bayes Instrumental Variable Estimation with Many Weak Instruments," Discussion Paper Series DP2018-14, Research Institute for Economics & Business Administration, Kobe University.
    30. Han, Yufeng, 2012. "State uncertainty in stock markets: How big is the impact on the cost of equity?," Journal of Banking & Finance, Elsevier, vol. 36(9), pages 2575-2592.
    31. Li, Mingliang & Tobias, Justin L., 2011. "Bayesian inference in a correlated random coefficients model: Modeling causal effect heterogeneity with an application to heterogeneous returns to schooling," Journal of Econometrics, Elsevier, vol. 162(2), pages 345-361, June.
    32. Andr'es Ram'irez-Hassan & Alejandro L'opez-Vera, 2021. "Semi-parametric estimation of the EASI model: Welfare implications of taxes identifying clusters due to unobserved preference heterogeneity," Papers 2109.07646, arXiv.org.
    33. Martin Burda & Matthew C. Harding & Jerry Hausman, 2008. "A Bayesian mixed logit-probit model for multinomial choice," CeMMAP working papers CWP23/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    34. Didier Nibbering, 2023. "A High-dimensional Multinomial Logit Model," Monash Econometrics and Business Statistics Working Papers 19/23, Monash University, Department of Econometrics and Business Statistics.
    35. Matthew J. Salois & Kelvin G. Balcombe, 2015. "A Generalized Bayesian Instrumental Variable Approach under Student t-distributed Errors with Application," Manchester School, University of Manchester, vol. 83(5), pages 499-522, September.
    36. Didier Nibbering, 2019. "A High-dimensional Multinomial Choice Model," Monash Econometrics and Business Statistics Working Papers 19/19, Monash University, Department of Econometrics and Business Statistics.
    37. Sudhir Voleti & Praveen K. Kopalle & Pulak Ghosh, 2015. "An Interproduct Competition Model Incorporating Branding Hierarchy and Product Similarities Using Store-Level Data," Management Science, INFORMS, vol. 61(11), pages 2720-2738, November.
    38. Mark J. Jensen & John M. Maheu, 2018. "Risk, Return and Volatility Feedback: A Bayesian Nonparametric Analysis," JRFM, MDPI, vol. 11(3), pages 1-29, September.
    39. Pelenis, Justinas, 2014. "Bayesian regression with heteroscedastic error density and parametric mean function," Journal of Econometrics, Elsevier, vol. 178(P3), pages 624-638.
    40. Chuanming Gao & Kajal Lahiri, 2019. "A Comparison of Some Bayesian and Classical Procedures for Simultaneous Equation Models with Weak Instruments," Econometrics, MDPI, vol. 7(3), pages 1-28, July.
    41. Cameron McIntosh, 2014. "The presence of an error term does not preclude causal inference in regression: a comment on Krause (2012)," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(1), pages 243-250, January.
    42. van Hasselt, Martijn, 2011. "Bayesian inference in a sample selection model," Journal of Econometrics, Elsevier, vol. 165(2), pages 221-232.
    43. Arnold Zellner (posthumously) & Tomohiro Ando & Nalan Basturk & Lennart Hoogerheide & Herman K. van Dijk, 2012. "Bayesian Analysis of Instrumental Variable Models: Acceptance-Rejection within Direct Monte Carlo," Tinbergen Institute Discussion Papers 12-098/III, Tinbergen Institute.
    44. Eoghan O'Neill, 2022. "Type I Tobit Bayesian Additive Regression Trees for Censored Outcome Regression," Papers 2211.07506, arXiv.org, revised Feb 2024.
    45. Cogley, Timothy & Startz, Richard, 2012. "Bayesian IV: the normal case with multiple endogenous variables," University of California at Santa Barbara, Economics Working Paper Series qt40v0x246, Department of Economics, UC Santa Barbara.

  28. Chernozhukov, Victor & Hansen, Christian, 2008. "The reduced form: A simple approach to inference with weak instruments," Economics Letters, Elsevier, vol. 100(1), pages 68-71, July.

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    1. Bauernschuster, Stefan & Falck, Oliver & Woessmann, Ludger, 2014. "Surfing alone? The internet and social capital: Evidence from an unforeseeable technological mistake," Journal of Public Economics, Elsevier, vol. 117(C), pages 73-89.
    2. 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.
    3. Fatemi, Ali & Glaum, Martin & Kaiser, Stefanie, 2018. "ESG performance and firm value: The moderating role of disclosure," Global Finance Journal, Elsevier, vol. 38(C), pages 45-64.
    4. Apoorva Lal & Mac Lockhart & Yiqing Xu & Ziwen Zu, 2023. "How Much Should We Trust Instrumental Variable Estimates in Political Science? Practical Advice Based on Over 60 Replicated Studies," Papers 2303.11399, arXiv.org, revised Nov 2023.
    5. Murray Michael P., 2017. "Linear Model IV Estimation When Instruments Are Many or Weak," Journal of Econometric Methods, De Gruyter, vol. 6(1), pages 1-22, January.
    6. Bertille Antoine & Pascal Lavergne, 2020. "Identification-Robust Nonparametric Interference in a Linear IV Model," Discussion Papers dp20-03, Department of Economics, Simon Fraser University.
    7. Nathalie Ferrière, 2016. "To give or not to give? How do donors react to European food aid allocation?," PSE Working Papers halshs-01405130, HAL.
    8. Ernesto Dal Bó & Pedro Dal Bó & Erik Eyster, 2016. "The Demand for Bad Policy when Voters Underappreciate Equilibrium Effects," NBER Working Papers 22916, National Bureau of Economic Research, Inc.
    9. Kanika Mahajan & Bharat Ramaswami, 2015. "Caste, female labor supply and the gender wage gap in India: Boserup revisited," Discussion Papers 15-02, Indian Statistical Institute, Delhi.
    10. Tito Boeri & Marta De Philippis & Eleonora Patacchini & Michele Pellizzari, 2015. "Immigration, Housing Discrimination and Employment," Economic Journal, Royal Economic Society, vol. 125(586), pages 82-114, August.
    11. Barnichon, Regis & Mesters, Geert, 2019. "Identifying Modern Macro Equations with Old Shocks," CEPR Discussion Papers 13765, C.E.P.R. Discussion Papers.
    12. P. Dorian Owen, 2017. "Evaluating Ingenious Instruments for Fundamental Determinants of Long-Run Economic Growth and Development," Econometrics, MDPI, vol. 5(3), pages 1-33, September.
    13. Bensch, Gunther & Gotz, Gunnar & Peters, Jörg, 2020. "Effects of Rural Electrification on Employment: A Comment on Dinkelman (2011)," MetaArXiv zhn9b, Center for Open Science.
    14. Emma Hooper & Sanjay Peters & Patrick A. Pintus, 2020. "The Impact of Infrastructure Investments on Income Inequality: Evidence from US States," AMSE Working Papers 2019, Aix-Marseille School of Economics, France, revised Sep 2020.
    15. Bertille Antoine & Pascal Lavergne, 2019. "Identification-Robust Nonparametric Inference in a Linear IV Model," Discussion Papers dp19-02, Department of Economics, Simon Fraser University.
    16. Joshua Blonz & Brigitte Roth Tran & Erin Troland, 2023. "The Canary in the Coal Decline: Appalachian Household Finance and the Transition from Fossil Fuels," Working Paper Series 2023-09, Federal Reserve Bank of San Francisco.
    17. 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.
    18. Eve Caroli & Mathilde Godard, 2016. "Does job insecurity deteriorate health?," Health Economics, John Wiley & Sons, Ltd., vol. 25(2), pages 131-147, February.
    19. Ellis, Jimmy R. & Gershenson, Seth, 2016. "LATE for the Meeting: Gender, Peer Advising, and College Success," IZA Discussion Papers 9956, Institute of Labor Economics (IZA).
    20. 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.
    21. Emran, Shahe & Shilpi, Forhad, 2014. "Agricultural productivity, hired labor, wages and poverty : evidence from Bangladesh," Policy Research Working Paper Series 7056, The World Bank.
    22. 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.
    23. Konstantinos Angelopoulos & George Economides, 2008. "Fiscal policy, rent seeking, and growth under electoral uncertainty: theory and evidence from the OECD," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 41(4), pages 1375-1405, November.
    24. Itay Saporta-Eksten & Ity Shurtz & Sarit Weisburd, 2021. "Social Security, Labor Supply, and Health of Older Workers: Quasi-Experimental Evidence from a Large Reform [Identification and Estimation of Local Average Treatment Effects]," Journal of the European Economic Association, European Economic Association, vol. 19(4), pages 2168-2208.
    25. Christian Hansen & Yuan Liao, 2016. "The Factor-Lasso and K-Step Bootstrap Approach for Inference in High-Dimensional Economic Applications," Departmental Working Papers 201610, Rutgers University, Department of Economics.
    26. Joshua Angrist & Michal Koles'ar, 2021. "One Instrument to Rule Them All: The Bias and Coverage of Just-ID IV," Papers 2110.10556, arXiv.org, revised Dec 2022.
    27. Junxue Jia & Yongzheng Liu & Jorge Martinez-Vazquez & Kewei Zhang, 2017. "Vertical Fiscal Imbalance and Local Fiscal Discipline: Empirical Evidence from China," International Center for Public Policy Working Paper Series, at AYSPS, GSU paper1717, International Center for Public Policy, Andrew Young School of Policy Studies, Georgia State University.
    28. Joe Hirschberg & Jenny Lye, 2017. "Alternative Graphical Representations of the Confidence Intervals for the Structural Coefficient from Exactly Identified Two-Stage Least Squares," Department of Economics - Working Papers Series 2026, The University of Melbourne.
    29. Ongena, Steven & Gropp, Reint & Rocholl, Jörg & Saadi, Vahid, 2020. "The Cleansing Effect of Banking Crises," CEPR Discussion Papers 15025, C.E.P.R. Discussion Papers.
    30. 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.
    31. Hack, Lukas & Istrefi, Klodiana & Meier, Matthias, 2023. "Identification of systematic monetary policy," Working Paper Series 2851, European Central Bank.
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    33. Jeremy Edwards, 2012. "Does Culture Cause Economic Development? A Reassessment of the Evidence from European Regions," CESifo Working Paper Series 4015, CESifo.
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    36. Neha Deopa & Daniele Rinaldo, 2023. "Sacred Ecology: The Environmental Impact of African Traditional Religions," Papers 2401.13673, arXiv.org.
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    41. Buono, Ines & Formai, Sara, 2018. "The heterogeneous response of domestic sales and exports to bank credit shocks," Journal of International Economics, Elsevier, vol. 113(C), pages 55-73.
    42. 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).
    43. Keith Finlay & David Neumark, 2010. "Is Marriage Always Good for Children?: Evidence from Families Affected by Incarceration," Journal of Human Resources, University of Wisconsin Press, vol. 45(4), pages 1046-1088.
    44. So Yoon Ahn & Yu Kyung Koh, 2022. "Spousal Bargaining Power and Consumption of Married Couples in the US: Evidence from Scanner Data," Working Papers 2022-010, Human Capital and Economic Opportunity Working Group.
    45. Masakure, Oliver, 2016. "The effect of employee loyalty on wages," Journal of Economic Psychology, Elsevier, vol. 56(C), pages 274-298.
    46. Andersson, Christian & Johansson, Per & Waldenström, Nina, 2011. "Do you want your child to have a certified teacher?," Economics of Education Review, Elsevier, vol. 30(1), pages 65-78, February.
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    50. Wayne Yuan Gao & Peter C.B. Phillips, 2016. "Structural Inference from Reduced Forms with Many Instruments," Cowles Foundation Discussion Papers 2062, Cowles Foundation for Research in Economics, Yale University.
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    53. 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.
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    2. Mr. Serhan Cevik & Fedor Miryugin, 2022. "Rogue Waves: Climate Change and Firm Performance," IMF Working Papers 2022/102, International Monetary Fund.
    3. Jeremy G. Weber & Erin O. Sills & Simone Bauch & Subhrendu K. Pattanayak, 2011. "Do ICDPs Work? An Empirical Evaluation of Forest-Based Microenterprises in the Brazilian Amazon," Land Economics, University of Wisconsin Press, vol. 87(4), pages 661-681.
    4. Jushan Bai & Sung Hoon Choi & Yuan Liao, 2019. "Standard Errors for Panel Data Models with Unknown Clusters," Papers 1910.07406, arXiv.org, revised May 2020.
    5. Denis Chetverikov & Elena Manresa, 2022. "Spectral and post-spectral estimators for grouped panel data models," Papers 2212.13324, arXiv.org, revised Dec 2022.
    6. Bluhm, Benjamin & Cutura, Jannic, 2020. "Econometrics at scale: Spark up big data in economics," SAFE Working Paper Series 266, Leibniz Institute for Financial Research SAFE.
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    Cited by:

    1. Elliott Fan, 2010. "Does Public Income Induce More Consumption?," The Economic Record, The Economic Society of Australia, vol. 86(272), pages 15-27, March.
    2. Advani, Arun & Sloczynski, Tymon, 2013. "Mostly Harmless Simulations? On the Internal Validity of Empirical Monte Carlo Studies," IZA Discussion Papers 7874, Institute of Labor Economics (IZA).
    3. 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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  33. 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. WenShwo Fang & Stephen Miller & Chih-Chuan Yeh, 2010. "Does a threshold inflation rate exist? Quantile inferences for inflation and its variability," Empirical Economics, Springer, vol. 39(3), pages 619-641, December.
    2. 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.
    3. 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.
    4. Andini, Corrado & Andini, Monica, 2015. "A Note on Unemployment Persistence and Quantile Parameter Heterogeneity," IZA Discussion Papers 8819, Institute of Labor Economics (IZA).
    5. Le-Yu Chen & Yu-Min Yen, 2021. "Estimations of the Conditional Tail Average Treatment Effect," Papers 2109.08793, arXiv.org, revised Sep 2021.
    6. Wüthrich, Kaspar, 2019. "A closed-form estimator for quantile treatment effects with endogeneity," Journal of Econometrics, Elsevier, vol. 210(2), pages 219-235.
    7. 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.
    8. Le‐Yu Chen & Sokbae Lee, 2018. "Exact computation of GMM estimators for instrumental variable quantile regression models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(4), pages 553-567, June.
    9. Andini, Corrado, 2017. "Tertiary Education for All and Wage Inequality: Policy Insights from Quantile Regression," IZA Policy Papers 132, Institute of Labor Economics (IZA).
    10. Wang, Le, 2011. "How Does Education Affect the Earnings Distribution in Urban China?," IZA Discussion Papers 6173, Institute of Labor Economics (IZA).
    11. Domenico Depalo & Raffaela Giordano, 2011. "The public-private pay gap: a robust quantile approach," Temi di discussione (Economic working papers) 824, Bank of Italy, Economic Research and International Relations Area.
    12. 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).
    13. 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.
    14. Jean-Jacques Forneron, 2019. "Detecting Identification Failure in Moment Condition Models," Papers 1907.13093, arXiv.org, revised Oct 2023.
    15. 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.
    16. 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.
    17. Budria, Santiago, 2010. "Are educational mismatches responsible for the ‘inequality increasing effect’ of education?," MPRA Paper 23420, University Library of Munich, Germany.
    18. Oliver Himmler, 2009. "The Effects of School Competition on Academic Achievement and Grading Standards," CESifo Working Paper Series 2676, CESifo.
    19. 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(2), pages 1-60, December.
    20. Kaspar W thrich, 2015. "Semiparametric estimation of quantile treatment effects with endogeneity," Diskussionsschriften dp1509, Universitaet Bern, Departement Volkswirtschaft.
    21. 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.

  34. Theodossiou, Panayiotis & McDonald, James B. & Hansen, Christian B., 2007. "Some Flexible Parametric Models for Partially Adaptive Estimators of Econometric Models," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 1, pages 1-20.
    See citations under working paper version above.
  35. 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.

    Cited by:

    1. Tae-Hwan Kim & Christophe Muller, 2015. "A Particular Form of Non-Constant Effect in Two-Stage Quantile Regression," AMSE Working Papers 1522, Aix-Marseille School of Economics, France, revised May 2015.
    2. Massimiliano Caporin & Loriana Pelizzon & Francesco Ravazzolo & Roberto Rigobon, 2013. "Measuring Sovereign Contagion in Europe," NBER Working Papers 18741, National Bureau of Economic Research, Inc.
    3. Victor Ginsburgh & Juan Prieto-Rodriguez, 2013. "Is there a Gender Bias in the Use of Foreign Languages in Europe?," Kyklos, Wiley Blackwell, vol. 66(4), pages 552-566, November.
    4. Zhang, Lei & Leonard, Tammy, 2014. "Neighborhood impact of foreclosure: A quantile regression approach," Regional Science and Urban Economics, Elsevier, vol. 48(C), pages 133-143.
    5. Imai, Susumu & Katayama, Hajime & Krishna, Kala, 2013. "A quantile-based test of protection for sale model," Journal of International Economics, Elsevier, vol. 91(1), pages 40-52.
    6. WenShwo Fang & Stephen Miller & Chih-Chuan Yeh, 2010. "Does a threshold inflation rate exist? Quantile inferences for inflation and its variability," Empirical Economics, Springer, vol. 39(3), pages 619-641, December.
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    2. Victor Ginsburgh & Juan Prieto-Rodriguez, 2013. "Is there a Gender Bias in the Use of Foreign Languages in Europe?," Kyklos, Wiley Blackwell, vol. 66(4), pages 552-566, November.
    3. Timmins, Christopher & Murdock, Jennifer, 2007. "A revealed preference approach to the measurement of congestion in travel cost models," Journal of Environmental Economics and Management, Elsevier, vol. 53(2), pages 230-249, March.
    4. Manuel Arellano & Stéphane Bonhomme, 2016. "Nonlinear panel data methods for dynamic heterogeneous agent models," CeMMAP working papers CWP51/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Xiaohong Chen & Demian Pouzo & James L. Powell, 2019. "Penalized Sieve GEL for Weighted Average Derivatives of Nonparametric Quantile IV Regressions," Papers 1902.10100, arXiv.org.
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    27. Nathan Kallus & Miruna Oprescu, 2022. "Robust and Agnostic Learning of Conditional Distributional Treatment Effects," Papers 2205.11486, arXiv.org, revised Feb 2023.
    28. Le‐Yu Chen & Sokbae Lee, 2018. "Exact computation of GMM estimators for instrumental variable quantile regression models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(4), pages 553-567, June.
    29. Adam M. Lavecchia, 2024. "Family‐level responses to the introduction of Tax‐Free Savings Accounts," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 57(1), pages 108-139, February.
    30. 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.
    31. Takuya Ishihara, 2020. "Panel Data Quantile Regression for Treatment Effect Models," Papers 2001.04324, arXiv.org, revised Nov 2021.
    32. 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.
    33. Wenjie Wang & Yichong Zhang, 2021. "Wild Bootstrap for Instrumental Variables Regressions with Weak and Few Clusters," Papers 2108.13707, arXiv.org, revised Jan 2024.
    34. Edward L. Glaeser & Sari Pekkala Kerr & William R. Kerr, 2012. "Entrepreneurship and Urban Growth: An Empirical Assessment with Historical Mines," Harvard Business School Working Papers 13-015, Harvard Business School, revised Oct 2015.
    35. Kazuhiko Shinoda & Takahiro Hoshino, 2022. "Orthogonal Series Estimation for the Ratio of Conditional Expectation Functions," Papers 2212.13145, arXiv.org.
    36. Galina Besstremyannaya, 2015. "The adverse effects of incentives regulation in health care: a comparative analysis with the U.S. and Japanese hospital data," Working Papers w0218, Center for Economic and Financial Research (CEFIR).
    37. Abrevaya, Jason & Xu, Haiqing, 2023. "Estimation of treatment effects under endogenous heteroskedasticity," Journal of Econometrics, Elsevier, vol. 234(2), pages 451-478.
    38. 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.
    39. Daniel Jacob, 2021. "CATE meets ML," Digital Finance, Springer, vol. 3(2), pages 99-148, June.
    40. 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.
    41. 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.
    42. 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.
    43. 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.
    44. Blaise Melly und Kaspar W thrich, 2016. "Local quantile treatment effects," Diskussionsschriften dp1605, Universitaet Bern, Departement Volkswirtschaft.
    45. George Wehby & Charles J. Courtemanche, 2012. "The Heterogeneity of the Cigarette Price Effect on Body Mass Index," NBER Working Papers 18087, National Bureau of Economic Research, Inc.
    46. Armstrong, Christopher S. & Blouin, Jennifer L. & Jagolinzer, Alan D. & Larcker, David F., 2015. "Corporate governance, incentives, and tax avoidance," Journal of Accounting and Economics, Elsevier, vol. 60(1), pages 1-17.
    47. Seoyun Hong, 2023. "Censored Quantile Regression with Many Controls," Papers 2303.02784, arXiv.org.
    48. Phillip Heiler, 2020. "Efficient Covariate Balancing for the Local Average Treatment Effect," Papers 2007.04346, arXiv.org.
    49. Hernæs, Øystein M., 2020. "Distributional effects of welfare reform for young adults: An unconditional quantile regression approach," Labour Economics, Elsevier, vol. 65(C).
    50. 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.
    51. 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.
    52. Daniel Jacob, 2021. "CATE meets ML -- The Conditional Average Treatment Effect and Machine Learning," Papers 2104.09935, arXiv.org, revised Apr 2021.
    53. 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.
    54. 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).
    55. 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.
    56. Marc Chan & Cain Polidano & Ha Vu & Roger Wilkins & Andrew Carter & Hang To, 2020. "How effective are Matching Schemes in enticing low-income earners to save more for retirement? Evidence from a national scheme," Melbourne Institute Working Paper Series wp2020n27, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    57. Ping Yu & Peter C.B. Phillips, 2014. "Threshold Regression with Endogeneity," Cowles Foundation Discussion Papers 1966, Cowles Foundation for Research in Economics, Yale University.
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    63. 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 Dec 2017.
    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. 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.
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Software components

  1. 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 24 Jan 2019.

    Cited by:

    1. Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2019. "lassopack: Model selection and prediction with regularized regression in Stata," Papers 1901.05397, arXiv.org.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. Laura Derksen & Jason Kerwin & Natalia Ordaz Reynoso & Olivier Sterck, 2021. "Appointments: A More Effective Commitment Device for Health Behaviors," Papers 2110.06876, arXiv.org.
    7. Amanda Y. Agan & Jennifer L. Doleac & Anna Harvey, 2021. "Misdemeanor Prosecution," NBER Working Papers 28600, National Bureau of Economic Research, Inc.
    8. Tomaso Duso & Claus Michelsen & Maximilian Schäfer & Kevin Ducbao Tran, 2021. "Airbnb and Rental Markets: Evidence from Berlin," CESifo Working Paper Series 9089, CESifo.
    9. Jessica Goldberg & Mario Macis & Pradeep Chintagunta, 2023. "Incentivized Peer Referrals for Tuberculosis Screening: Evidence from India," American Economic Journal: Applied Economics, American Economic Association, vol. 15(1), pages 259-291, January.
    10. 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..
    11. 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).
    12. 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, 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 09 Jan 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. Gerhard Toews & Pierre-Louis Vezina, 2020. "Enemies of the people," Working Papers w0279, New Economic School (NES).
    3. Caglayan, Mustafa & Talavera, Oleksandr & Xiong, Lin, 2022. "Female small business owners in China: Discouraged, not discriminated," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
    4. Lunn, Pete & Lyons, Seán & Murphy, Martin, 2019. "Predicting farms’ noncompliance with regulations on nitrate pollution," Papers WP609, Economic and Social Research Institute (ESRI).
    5. 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.
    6. 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.
    7. 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.
    8. Rossmann, Tobias, 2019. "Does Experience Shape Subjective Expectations?," Rationality and Competition Discussion Paper Series 181, CRC TRR 190 Rationality and Competition.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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).
    14. 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.
    15. Joana Cardim & Teresa Molina-Millán & Pedro C. Vicente, 2021. "Can technology improve the classroom experience in primary education? An African experiment on a worldwide program," NOVAFRICA Working Paper Series wp2101, Universidade Nova de Lisboa, Nova School of Business and Economics, NOVAFRICA.

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