Damian Kozbur
Citations
Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.Working papers
- 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.
Cited by:
- Christian Hansen & Damian Kozbur & Sanjog Misra, 2016. "Targeted undersmoothing," ECON - Working Papers 282, Department of Economics - University of Zurich, revised Apr 2018.
- Damian Kozbur, 2015.
"Testing-Based Forward Model Selection,"
ECON - Working Papers
283, Department of Economics - University of Zurich, revised Apr 2018.
- Damian Kozbur, 2017. "Testing-Based Forward Model Selection," American Economic Review, American Economic Association, vol. 107(5), pages 266-269, May.
- Damian Kozbur, 2020. "Analysis of Testing‐Based Forward Model Selection," Econometrica, Econometric Society, vol. 88(5), pages 2147-2173, September.
- Shi, Zhentao & Huang, Jingyi, 2023. "Forward-selected panel data approach for program evaluation," Journal of Econometrics, Elsevier, vol. 234(2), pages 512-535.
- Christian Hansen & Damian Kozbur & Sanjog Misra, 2016.
"Targeted undersmoothing,"
ECON - Working Papers
282, Department of Economics - University of Zurich, revised Apr 2018.
Cited by:
- Victor Chernozhukov & Mert Demirer & Esther Duflo & Ivan Fernandez-Val, 2017.
"Generic machine learning inference on heterogenous treatment effects in randomized experiments,"
CeMMAP working papers
CWP61/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- 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.
- 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.
- Victor Chernozhukov & Mert Demirer & Esther Duflo & Iván Fernández‐Val, 2025. "Fisher–Schultz Lecture: Generic Machine Learning Inference on Heterogeneous Treatment Effects in Randomized Experiments, With an Application to Immunization in India," Econometrica, Econometric Society, vol. 93(4), pages 1121-1164, July.
- Victor Chernozhukov & Mert Demirer & Esther Duflo & Iván Fernández-Val, 2023. "Fischer-Schultz Lecture: Generic Machine Learning Inference on Heterogenous Treatment Effects in Randomized Experiments, with an Application to Immunization in India," Working Papers hal-04238425, HAL.
- Jean-Pierre Dubé & Sanjog Misra, 2017. "Personalized Pricing and Consumer Welfare," NBER Working Papers 23775, National Bureau of Economic Research, Inc.
- 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.
- Shi, Zhentao & Huang, Jingyi, 2023. "Forward-selected panel data approach for program evaluation," Journal of Econometrics, Elsevier, vol. 234(2), pages 512-535.
- Victor Chernozhukov & Mert Demirer & Esther Duflo & Ivan Fernandez-Val, 2017.
"Generic machine learning inference on heterogenous treatment effects in randomized experiments,"
CeMMAP working papers
CWP61/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Damian Kozbur, 2015.
"Testing-Based Forward Model Selection,"
ECON - Working Papers
283, Department of Economics - University of Zurich, revised Apr 2018.
- Damian Kozbur, 2017. "Testing-Based Forward Model Selection," American Economic Review, American Economic Association, vol. 107(5), pages 266-269, May.
Cited by:
- Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins, 2017.
"Double/Debiased Machine Learning for Treatment and Structural Parameters,"
NBER Working Papers
23564, National Bureau of Economic Research, Inc.
- 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.
- 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.
- 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.
- Sarra Houidi & Dominique Fourer & François Auger & Houda Ben Attia Sethom & Laurence Miègeville, 2021. "Comparative Evaluation of Non-Intrusive Load Monitoring Methods Using Relevant Features and Transfer Learning," Energies, MDPI, vol. 14(9), pages 1-28, May.
- 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.
- Peter C.B. Phillips & Zhentao Shi, 2019. "Boosting: Why you Can Use the HP Filter," Cowles Foundation Discussion Papers 2212, Cowles Foundation for Research in Economics, Yale University.
- Peter C. B. Phillips & Zhentao Shi, 2019. "Boosting: Why You Can Use the HP Filter," Papers 1905.00175, arXiv.org, revised Nov 2020.
- 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.
- 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.
- Hansen, Christian & Liao, Yuan, 2016. "The Factor-Lasso and K-Step Bootstrap Approach for Inference in High-Dimensional Economic Applications," MPRA Paper 75313, University Library of Munich, Germany.
- 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.
- Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins, 2016. "Double/Debiased Machine Learning for Treatment and Causal Parameters," Papers 1608.00060, arXiv.org, revised Nov 2024.
- Damian Kozbur, 2015.
"Testing-Based Forward Model Selection,"
ECON - Working Papers
283, Department of Economics - University of Zurich, revised Apr 2018.
- Damian Kozbur, 2017. "Testing-Based Forward Model Selection," American Economic Review, American Economic Association, vol. 107(5), pages 266-269, May.
- 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.
- 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.
- Xiduo Chen & Xingdong Feng & Antonio F. Galvao & Yeheng Ge, 2025. "Treatment Effects Inference with High-Dimensional Instruments and Control Variables," Papers 2503.20149, arXiv.org, revised Oct 2025.
- 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.
- Zhentao Shi & Jingyi Huang, 2019. "Forward-Selected Panel Data Approach for Program Evaluation," Papers 1908.05894, arXiv.org, revised Apr 2021.
- Shi, Zhentao & Huang, Jingyi, 2023. "Forward-selected panel data approach for program evaluation," Journal of Econometrics, Elsevier, vol. 234(2), pages 512-535.
- Alexandre Belloni & Victor Chernozhukov & Christian Hansen & Damian Kozbur, 2014.
"Inference in high dimensional panel models with an application to gun control,"
CeMMAP working papers
CWP50/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- 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.
- Alexandre Belloni & Victor Chernozhukov & Christian Hansen & Damian Kozbur, 2014. "Inference in high dimensional panel models with an application to gun control," CeMMAP working papers 50/14, Institute for Fiscal Studies.
- 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:
- 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.
- Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Christian Hansen & Kengo Kato, 2018. "High-dimensional econometrics and regularized GMM," CeMMAP working papers CWP35/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- 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.
- María Hernández de Benito, 2022. "This Is a Man’s World: Crime and Intra-Household Resource Allocation," HiCN Working Papers 372, Households in Conflict Network.
- Julián Caballero & Christian Upper, 2023. "What happens to EMEs when US yields go up?," BIS Working Papers 1081, Bank for International Settlements.
- Bigerna, Simona & D’Errico, Maria Chiara & Polinori, Paolo, 2025. "Institutional variables and power firms’ productivity: Micro panel estimation with time-invariant variables," Socio-Economic Planning Sciences, Elsevier, vol. 102(C).
- 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.
- Meera Mahadevan, 2024. "The Price of Power: Costs of Political Corruption in Indian Electricity," American Economic Review, American Economic Association, vol. 114(10), pages 3314-3344, October.
- 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.
- Anna Baiardi & Paul S. Clarke & Andrea A. Naghi & Annalivia Polselli, 2026. "Double Machine Learning for Static Panel Data with Instrumental Variables: New Method and Applications," Papers 2603.20464, arXiv.org.
- Uckat, Hannah Irmela, 2023. "Leaning in at Home : Women's Promotions and Intra-household Bargaining in Bangladesh," Policy Research Working Paper Series 10370, The World Bank.
- Kaicheng Chen, 2025. "Inference in High-Dimensional Panel Models: Two-Way Dependence and Unobserved Heterogeneity," Papers 2504.18772, arXiv.org, revised Dec 2025.
- 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.
- 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, IZA Network @ LISER.
- Jonas Fluchtmann & Anita M. Glenny & Nikolaj A. Harmon & Jonas Maibom, 2024. "The Gender Application Gap: Do Men and Women Apply for the Same Jobs?," American Economic Journal: Economic Policy, American Economic Association, vol. 16(2), pages 182-219, May.
- Aristide Houndetoungan & Abdoul Haki Maoude, 2024.
"Inference for Two-Stage Extremum Estimators,"
Papers
2402.05030, arXiv.org, revised Nov 2024.
- Aristide Houndetoungan & Abdoul Haki Maoude, 2024. "Inference for Two-Stage Extremum Estimators," Thema Working Papers 2024-01, THEMA (Théorie Economique, Modélisation et Applications), CY Cergy-Paris University, ESSEC and CNRS.
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- Christian Hansen & Damian Kozbur & Sanjog Misra, 2016. "Targeted undersmoothing," ECON - Working Papers 282, Department of Economics - University of Zurich, revised Apr 2018.
- 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.
- Julián Caballero, 2020.
"Corporate dollar debt and depreciations: all's well that ends well?,"
BIS Working Papers
879, Bank for International Settlements.
- Caballero, Julián, 2021. "Corporate dollar debt and depreciations: All’s well that ends well?," Journal of Banking & Finance, Elsevier, vol. 130(C).
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- 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.
- 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.
- Hansen, Christian & Liao, Yuan, 2016. "The Factor-Lasso and K-Step Bootstrap Approach for Inference in High-Dimensional Economic Applications," MPRA Paper 75313, University Library of Munich, Germany.
- 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.
- Akash Raja, 2023. "The impact of changes in bank capital requirements," Bank of England working papers 1004, Bank of England.
- Paul S. Clarke & Annalivia Polselli, 2023. "Double Machine Learning for Static Panel Models with Fixed Effects," Papers 2312.08174, arXiv.org, revised Dec 2024.
- Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2019.
"lassopack: Model selection and prediction with regularized regression in Stata,"
Papers
1901.05397, arXiv.org.
- Ahrens, Achim & Hansen, Christian B. & Schaffer, Mark E, 2019. "lassopack: Model Selection and Prediction with Regularized Regression in Stata," IZA Discussion Papers 12081, IZA Network @ LISER.
- Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2020. "lassopack: Model selection and prediction with regularized regression in Stata," Stata Journal, StataCorp LLC, vol. 20(1), pages 176-235, March.
- Damian Kozbur, 2015.
"Testing-Based Forward Model Selection,"
ECON - Working Papers
283, Department of Economics - University of Zurich, revised Apr 2018.
- Damian Kozbur, 2017. "Testing-Based Forward Model Selection," American Economic Review, American Economic Association, vol. 107(5), pages 266-269, May.
- Marta Serra-Garcia & Uri Gneezy, 2023.
"Improving Human Deception Detection Using Algorithmic Feedback,"
CESifo Working Paper Series
10518, CESifo.
- Marta Serra-Garcia & Uri Gneezy, 2025. "Improving Human Deception Detection Using Algorithmic Feedback," Management Science, INFORMS, vol. 71(12), pages 10289-10307, December.
- 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.
- Szabó-Morvai Ágnes & Hubert János Kiss, 2020. "Locus of control and Human Capital Investment Decisions: The Role of Effort, Parental Preferences and Financial Constraints," KRTK-KTI WORKING PAPERS 2055, Institute of Economics, Centre for Economic and Regional Studies.
- 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.
- 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.
- Achim Ahrens & Alessandra Stampi‐Bombelli & Selina Kurer & Dominik Hangartner, 2024. "Optimal multi‐action treatment allocation: A two‐phase field experiment to boost immigrant naturalization," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(7), pages 1379-1395, November.
- 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.
- 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.
- Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Post-selection and post-regularization inference in linear models with many controls and instruments," CeMMAP working papers CWP02/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- 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.
- Francesca Micocci & Armando Rungi, 2021.
"Predicting Exporters with Machine Learning,"
Papers
2107.02512, arXiv.org, revised Sep 2022.
- Francesca Micocci & Armando Rungi, 2021. "Predicting Exporters with Machine Learning," Working Papers 03/2021, IMT School for Advanced Studies Lucca, revised Jul 2021.
- Micocci, Francesca & Rungi, Armando, 2023. "Predicting Exporters with Machine Learning," World Trade Review, Cambridge University Press, vol. 22(5), pages 584-607, December.
- Borgschulte, Mark & Vogler, Jacob, 2019.
"Did the ACA Medicaid Expansion Save Lives?,"
IZA Discussion Papers
12552, IZA Network @ LISER.
- Borgschulte, Mark & Vogler, Jacob, 2020. "Did the ACA Medicaid expansion save lives?," Journal of Health Economics, Elsevier, vol. 72(C).
- Qiu, Yun & Chen, Xi & Shi, Wei, 2020.
"Impacts of Social and Economic Factors on the Transmission of Coronavirus Disease 2019 (COVID-19) in China,"
GLO Discussion Paper Series
494 [pre.], Global Labor Organization (GLO).
- Qiu, Yun & Chen, Xi & Shi, Wei, 2020. "Impacts of Social and Economic Factors on the Transmission of Coronavirus Disease 2019 (COVID-19) in China," IZA Discussion Papers 13165, IZA Network @ LISER.
- 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.
- Qiu, Yun & Chen, Xi & Shi, Wei, 2020. "Impacts of Social and Economic Factors on the Transmission of Coronavirus Disease 2019 (COVID-19) in China," GLO Discussion Paper Series 494, Global Labor Organization (GLO).
- Jonathan Fuhr & Philipp Berens & Dominik Papies, 2024. "Estimating Causal Effects with Double Machine Learning -- A Method Evaluation," Papers 2403.14385, arXiv.org, revised Apr 2024.
- Caballero, Julián & Upper, Christian, 2026. "What happens to emerging market economies when US yields go up?," Journal of International Money and Finance, Elsevier, vol. 160(C).
- 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.
- Maria Laura Alzua & Natalia Cantet & Ana C Dammert & Damilola Olajide, 2024. "The Well-being Effects of an Old-Age Pension: Experimental Evidence for Ekiti State in Nigeria," Journal of African Economies, Centre for the Study of African Economies, vol. 33(3), pages 240-270.
- Jonathan Fuhr & Dominik Papies, 2024. "Double Machine Learning meets Panel Data -- Promises, Pitfalls, and Potential Solutions," Papers 2409.01266, arXiv.org.
- Maximilian Rücker & Michael Vogt & Oliver Linton & Christopher Walsh, 2025.
"Estimation and inference in high‐dimensional panel data models with interactive fixed effects,"
Quantitative Economics, Econometric Society, vol. 16(4), pages 1457-1509, November.
- Maximilian Ruecker & Michael Vogt & Oliver Linton & Christopher Walsh, 2022. "Estimation and Inference in High-Dimensional Panel Data Models with Interactive Fixed Effects," Papers 2206.12152, arXiv.org, revised Aug 2025.
- Linton, O. B. & Rücker, M. & Vogt, M. & Walsh, C., 2024. "Estimation and Inference in High-Dimensional Panel Data Models with Interactive Fixed Effects," Cambridge Working Papers in Economics 2467, Faculty of Economics, University of Cambridge.
- 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.
- 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.
- Facundo Arga~naraz, 2025. "Automatic Debiased Machine Learning of Structural Parameters with General Conditional Moments," Papers 2512.08423, arXiv.org.
- 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.
- Zehranur Sanioğlu-Tanış & Duygu Dündar-Öztaşçı & İbrahim Özmen, 2025. "Fertility and women unemployment: new evidence from Türkiye," Economic Change and Restructuring, Springer, vol. 58(6), pages 1-39, December.
- 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.
- Babii, Andrii & Ball, Ryan T. & Ghysels, Eric & Striaukas, Jonas, 2023. "Machine learning panel data regressions with heavy-tailed dependent data: Theory and application," Journal of Econometrics, Elsevier, vol. 237(2).
- Jan Ditzen & Erkal Ersoy & Haoyang Li & Francesco Ravazzolo, 2026. "Forecasting Oil Consumption: The Statistical Review of World Energy Meets Machine Learning," Papers 2602.01963, arXiv.org.
- Breinlich, Holger & Corradi, Valentina & Rocha, Nadia & Ruta, Michele & Silva, J.M.C. Santos & Zylkin, Tom, 2021.
"Machine learning in international trade research - evaluating the impact of trade agreements,"
LSE Research Online Documents on Economics
114379, London School of Economics and Political Science, LSE Library.
- Holger Breinlich & Valentina Corradi & Nadia Rocha & Michele Ruta & J.M.C. Santos Silva & Tom Zylkin, 2021. "Machine learning in international trade research - evaluating the impact of trade agreements," CEP Discussion Papers dp1776, Centre for Economic Performance, LSE.
- Breinlich, Holger & Corradi, Valentina & Rocha, Nadia & Ruta, Michele & Santos Silva, JMC & Zylkin, Thomas, 2022. "Machine Learning in International Trade Research - Evaluating the Impact of Trade Agreements," CEPR Discussion Papers 17325, Centre for Economic Policy Research.
- Breinlich,Holger & Corradi,Valentina & Rocha,Nadia & Ruta,Michele & Santos Silva,J.M.C. & Zylkin,Tom, 2021. "Machine Learning in International Trade Research : Evaluating the Impact of Trade Agreements," Policy Research Working Paper Series 9629, The World Bank.
- 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.
- Damian Kozbur, 2020. "Analysis of Testing‐Based Forward Model Selection," Econometrica, Econometric Society, vol. 88(5), pages 2147-2173, September.
- 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.
- Michael Danquah & Abdul Malik Iddrisu & Ernest Owusu Boakye & Solomon Owusu, 2021. "Do gender wage differences within households influence women's empowerment and welfare?: Evidence from Ghana," WIDER Working Paper Series wp-2021-40, World Institute for Development Economic Research (UNU-WIDER).
- WANG, Hongming, 2025. "Quantifying the Mortality Consequences of Climate Change : Evidence from Japan," Discussion paper series HIAS-E-143, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
- Max Vilgalys, 2023. "A Machine Learning Approach to Measuring Climate Adaptation," Papers 2302.01236, arXiv.org.
- 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.
- 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.
- Carlos Lamarche & Thomas Parker, 2022. "Wild Bootstrap Inference For Penalized Quantile Regression For Longitudinal Data," Working Papers 22003 Classification-C15,, University of Waterloo, Department of Economics.
- Carlos Lamarche & Thomas Parker, 2020. "Wild Bootstrap Inference for Penalized Quantile Regression for Longitudinal Data," Papers 2004.05127, arXiv.org, revised May 2022.
- 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.
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- 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.
- Harold D. Chiang & Kengo Kato & Yukun Ma & Yuya Sasaki, 2019.
"Multiway Cluster Robust Double/Debiased Machine Learning,"
Papers
1909.03489, arXiv.org, revised Mar 2020.
- 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.
- 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.
- Muhammad Ramzan & Hong Li, 2025. "An analytical framework to link factors affecting agricultural trade intensity in the world: pathways to sustainable agricultural development 2030 agenda," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 27(1), pages 1223-1272, January.
- 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
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