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Sparse Models and Methods for Optimal Instruments with an Application to Eminent Domain

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  1. 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.
  2. Ash, Elliott & MacLeod, W. Bentley, 2021. "Reducing partisanship in judicial elections can improve judge quality: Evidence from U.S. state supreme courts," Journal of Public Economics, Elsevier, vol. 201(C).
  3. Manudeep Bhuller & Gordon B. Dahl & Katrine V. Løken & Magne Mogstad, 2020. "Incarceration, Recidivism, and Employment," Journal of Political Economy, University of Chicago Press, vol. 128(4), pages 1269-1324.
  4. 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.
  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. 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.
  7. Alexandre Belloni & Victor Chernozhukov & Kengo Kato, 2019. "Valid Post-Selection Inference in High-Dimensional Approximately Sparse Quantile Regression Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 114(526), pages 749-758, April.
  8. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins, 2018. "Double/debiased machine learning for treatment and structural parameters," Econometrics Journal, Royal Economic Society, vol. 21(1), pages 1-68, February.
  9. Lu, Xun & Su, Liangjun, 2016. "Shrinkage estimation of dynamic panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 190(1), pages 148-175.
  10. 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.
  11. 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.
  12. Daniele Bianchi & Kenichiro McAlinn, 2018. "Large-Scale Dynamic Predictive Regressions," Papers 1803.06738, arXiv.org.
  13. Guanhao Feng & Stefano Giglio & Dacheng Xiu, 2020. "Taming the Factor Zoo: A Test of New Factors," Journal of Finance, American Finance Association, vol. 75(3), pages 1327-1370, June.
  14. 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.
  15. Stephen Coussens & Jann Spiess, 2021. "Improving Inference from Simple Instruments through Compliance Estimation," Papers 2108.03726, arXiv.org.
  16. 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.
  17. 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.
  18. 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.
  19. Chen, Daniel L. & Levonyan, Vardges & Yeh, Susan, 2016. "Policies Affect Preferences: Evidence from Random Variation in Abortion Jurisprudence," IAST Working Papers 16-58, Institute for Advanced Study in Toulouse (IAST).
  20. 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.
  21. Emily Cuddy & Janet Currie, 2020. "Rules vs. Discretion: Treatment of Mental Illness in U.S. Adolescents," NBER Working Papers 27890, National Bureau of Economic Research, Inc.
  22. Li, Qiang & An, Lian & Zhang, Ren, 2023. "Corruption drives brain drain: Cross-country evidence from machine learning," Economic Modelling, Elsevier, vol. 126(C).
  23. 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.
  24. Guilherme Lichand & Anandi Mani, 2020. "Cognitive Droughts," CSAE Working Paper Series 2020-02, Centre for the Study of African Economies, University of Oxford.
  25. 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," Discussion Paper 2019-008, Tilburg University, Tilburg Law and Economic Center.
  26. 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.
  27. Breunig, Christoph & Mammen, Enno & Simoni, Anna, 2020. "Ill-posed estimation in high-dimensional models with instrumental variables," Journal of Econometrics, Elsevier, vol. 219(1), pages 171-200.
  28. René Böheim & Philipp Stöllinger, 2021. "Decomposition of the gender wage gap using the LASSO estimator," Applied Economics Letters, Taylor & Francis Journals, vol. 28(10), pages 817-828, June.
  29. Chirinko, Robert S. & Wilson, Daniel J., 2017. "Tax competition among U.S. states: Racing to the bottom or riding on a seesaw?," Journal of Public Economics, Elsevier, vol. 155(C), pages 147-163.
  30. 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.
  31. 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.
  32. Wang, Steven Shuye & Xu, Kuan & Zhang, Hao, 2019. "A microstructure study of circuit breakers in the Chinese stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 57(C).
  33. 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.
  34. Frank Windmeijer & Helmut Farbmacher & Neil Davies & George Davey Smith, 2019. "On the Use of the Lasso for Instrumental Variables Estimation with Some Invalid Instruments," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 114(527), pages 1339-1350, July.
  35. 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.
  36. 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.
  37. Victor Chernozhukov & Juan Carlos Escanciano & Hidehiko Ichimura & Whitney K. Newey & James M. Robins, 2022. "Locally Robust Semiparametric Estimation," Econometrica, Econometric Society, vol. 90(4), pages 1501-1535, July.
  38. 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.
  39. 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.
  40. Daniel Paravisini & Veronica Rappoport & Philipp Schnabl & Daniel Wolfenzon, 2015. "Dissecting the Effect of Credit Supply on Trade: Evidence from Matched Credit-Export Data," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 82(1), pages 333-359.
  41. Matthias Westphal & Daniel A Kamhöfer & Hendrik Schmitz, 2022. "Marginal College Wage Premiums Under Selection Into Employment," The Economic Journal, Royal Economic Society, vol. 132(646), pages 2231-2272.
  42. Pierri, Nicola & Timmer, Yannick, 2022. "The importance of technology in banking during a crisis," Journal of Monetary Economics, Elsevier, vol. 128(C), pages 88-104.
  43. Strittmatter, Anthony & Wunsch, Conny, 2021. "The Gender Pay Gap Revisited with Big Data: Do Methodological Choices Matter?," Working papers 2021/05, Faculty of Business and Economics - University of Basel.
  44. Dennis Lim & Wenjie Wang & Yichong Zhang, 2022. "A Conditional Linear Combination Test with Many Weak Instruments," Papers 2207.11137, arXiv.org, revised Apr 2023.
  45. Dong, Chaohua & Gao, Jiti & Linton, Oliver, 2023. "High dimensional semiparametric moment restriction models," Journal of Econometrics, Elsevier, vol. 232(2), pages 320-345.
  46. Alain Hecq & Luca Margaritella & Stephan Smeekes, 2023. "Granger Causality Testing in High-Dimensional VARs: A Post-Double-Selection Procedure," Journal of Financial Econometrics, Oxford University Press, vol. 21(3), pages 915-958.
  47. 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.
  48. Neng-Chieh Chang, 2018. "Semiparametric Difference-in-Differences with Potentially Many Control Variables," Papers 1812.10846, arXiv.org, revised Jan 2019.
  49. Julián Caballero & Christian Upper, 2023. "What happens to EMEs when US yields go up?," BIS Working Papers 1081, Bank for International Settlements.
  50. 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).
  51. Onatski, Alexei, 2015. "Asymptotic analysis of the squared estimation error in misspecified factor models," Journal of Econometrics, Elsevier, vol. 186(2), pages 388-406.
  52. 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.
  53. Balima, Hippolyte W. & Sokolova, Anna, 2021. "IMF programs and economic growth: A meta-analysis," Journal of Development Economics, Elsevier, vol. 153(C).
  54. Belloni, Alexandre. & Chen, Mingli & Chernozhukov, Victor, 2016. "Quantile Graphical Models: Prediction and Conditional Independence with Applications to Financial Risk Management," The Warwick Economics Research Paper Series (TWERPS) 1125, University of Warwick, Department of Economics.
  55. Jonas Krampe & Luca Margaritella, 2021. "Factor Models with Sparse VAR Idiosyncratic Components," Papers 2112.07149, arXiv.org, revised May 2022.
  56. 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.
  57. 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.
  58. Halko, Marja-Liisa & Lappalainen, Olli & Sääksvuori, Lauri, 2021. "Do non-choice data reveal economic preferences? Evidence from biometric data and compensation-scheme choice," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 87-104.
  59. McIntosh, Craig & Zeitlin, Andrew, 2022. "Using household grants to benchmark the cost effectiveness of a USAID workforce readiness program," Journal of Development Economics, Elsevier, vol. 157(C).
  60. Neng-Chieh Chang, 2020. "The Mode Treatment Effect," Papers 2007.11606, arXiv.org.
  61. Marianne Bl'ehaut & Xavier D'Haultfoeuille & J'er'emy L'Hour & Alexandre B. Tsybakov, 2020. "An alternative to synthetic control for models with many covariates under sparsity," Papers 2005.12225, arXiv.org, revised Jun 2021.
  62. Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2011. "Estimation of treatment effects with high-dimensional controls," CeMMAP working papers CWP42/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  63. Prosper Donovon & Alastair R. Hall, 2015. "GMM and Indirect Inference: An appraisal of their connections and new results on their properties under second order identification," Economics Discussion Paper Series 1505, Economics, The University of Manchester.
  64. Collins, Alan & Fan, Jingwen & Mahabir, Aruneema, 2022. "Actual versus ‘natural’ rates of suicide: Evidence from the USA," Economic Modelling, Elsevier, vol. 106(C).
  65. Jelena Bradic & Victor Chernozhukov & Whitney K. Newey & Yinchu Zhu, 2019. "Minimax Semiparametric Learning With Approximate Sparsity," Papers 1912.12213, arXiv.org, revised Aug 2022.
  66. Linton, Oliver & Seo, Myung Hwan & Whang, Yoon-Jae, 2023. "Testing stochastic dominance with many conditioning variables," Journal of Econometrics, Elsevier, vol. 235(2), pages 507-527.
  67. Kristof Lommers & Ouns El Harzli & Jack Kim, 2021. "Confronting Machine Learning With Financial Research," Papers 2103.00366, arXiv.org, revised Mar 2021.
  68. Achim Ahrens & Arnab Bhattacharjee, 2015. "Two-Step Lasso Estimation of the Spatial Weights Matrix," Econometrics, MDPI, vol. 3(1), pages 1-28, March.
  69. 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.
  70. Seoyun Hong, 2023. "Censored Quantile Regression with Many Controls," Papers 2303.02784, arXiv.org.
  71. 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.
  72. Carlana, Michela & La Ferrara, Eliana, 2021. "Apart but Connected: Online Tutoring and Student Outcomes during the COVID-19 Pandemic," IZA Discussion Papers 14094, Institute of Labor Economics (IZA).
  73. 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.
  74. Lutz Bellmann & Olaf Hübler, 2022. "Personality traits, working conditions and health: an empirical analysis based on the German Linked Personnel Panel, 2013–2017," Review of Managerial Science, Springer, vol. 16(2), pages 283-318, February.
  75. 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.
  76. 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.
  77. Gyuhyeong Goh & Jisang Yu, 2022. "Causal inference with some invalid instrumental variables: A quasi‐Bayesian approach," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(6), pages 1432-1451, December.
  78. Pietro Bonaldi & Ali Hortaçsu & Jakub Kastl, 2015. "Empirical Analysis of Funding Cost Spillovers in the EURO Zone with Application to Systemic Risk," Working Papers 2015-5, Princeton University. Economics Department..
  79. Eric Gautier & Alexandre Tsybakov, 2013. "Pivotal estimation in high-dimensional regression via linear programming," Working Papers hal-00805556, HAL.
  80. Ahrens, Achim & Hansen, Christian B. & Schaffer, Mark E & Wiemann, Thomas, 2024. "Model Averaging and Double Machine Learning," IZA Discussion Papers 16714, Institute of Labor Economics (IZA).
  81. 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.
  82. Chen, Daniel L. & Yeh, Susan, 2022. "How do rights revolutions occur? Free speech and the first amendment," TSE Working Papers 22-1396, Toulouse School of Economics (TSE).
  83. Frank Windmeijer & Xiaoran Liang & Fernando P. Hartwig & Jack Bowden, 2021. "The confidence interval method for selecting valid instrumental variables," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(4), pages 752-776, September.
  84. Kasey Buckles & Daniel Hungerman & Steven Lugauer, 2021. "Is Fertility a Leading Economic Indicator?," The Economic Journal, Royal Economic Society, vol. 131(634), pages 541-565.
  85. 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.
  86. 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).
  87. 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.
  88. Jo Thori Lind & Daniel Chen, 2016. "The Political Economy Of Beliefs: Why Fiscal And Social Conservatives/Liberals Come Hand-In-Hand," 2016 Meeting Papers 606, Society for Economic Dynamics.
  89. 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.
  90. 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.
  91. Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2011. "Inference for High-Dimensional Sparse Econometric Models," Papers 1201.0220, arXiv.org.
  92. Gray, Rowena & Wright, Greg C., 2024. "A rising tide? The local incidence of the second wave of globalization," Journal of International Economics, Elsevier, vol. 148(C).
  93. Kilic, Gizem, 2021. "State-level Food Waste Policies In the U.S.: A Predictive Modelling," 2021 Annual Meeting, August 1-3, Austin, Texas 314091, Agricultural and Applied Economics Association.
  94. Saulius Jokubaitis & Remigijus Leipus, 2022. "Asymptotic Normality in Linear Regression with Approximately Sparse Structure," Mathematics, MDPI, vol. 10(10), pages 1-28, May.
  95. Guy Tchuente, 2016. "Estimation of social interaction models using regularization," Studies in Economics 1607, School of Economics, University of Kent.
  96. 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).
  97. Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen, 2013. "Program evaluation with high-dimensional data," CeMMAP working papers CWP57/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  98. Chen, Daniel L. & Ash, Elliott & Naidu, Suresh, 2022. "Ideas Have Consequences: The Impact of Law and Economics on American Justice," TSE Working Papers 22-1392, Toulouse School of Economics (TSE).
  99. 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.
  100. 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).
  101. 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.
  102. 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.
  103. 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.
  104. Elliott Ash & Daniel L. Chen & Sergio Galletta, 2022. "Measuring Judicial Sentiment: Methods and Application to US Circuit Courts," Economica, London School of Economics and Political Science, vol. 89(354), pages 362-376, April.
  105. 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.
  106. 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.
  107. Marit Hinnosaar & Elaine M. Liu, 2020. "Persistence in alcohol consumption: evidence from migrants," Carlo Alberto Notebooks 620, Collegio Carlo Alberto.
  108. Rebecca Brough & Matthew Freedman & David C. Phillips, 2021. "Understanding socioeconomic disparities in travel behavior during the COVID‐19 pandemic," Journal of Regional Science, Wiley Blackwell, vol. 61(4), pages 753-774, September.
  109. 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.
  110. Lee, Ji Hyung & Shi, Zhentao & Gao, Zhan, 2022. "On LASSO for predictive regression," Journal of Econometrics, Elsevier, vol. 229(2), pages 322-349.
  111. Bom, Judith & Bakx, Pieter & Schut, Frederik & van Doorslaer, Eddy, 2019. "Health effects of caring for and about parents and spouses," The Journal of the Economics of Ageing, Elsevier, vol. 14(C).
  112. Bellmann, Lutz & Hübler, Olaf, 2019. "Personal Attitudes, Job Characteristics and Health," IZA Discussion Papers 12597, Institute of Labor Economics (IZA).
  113. Harold D. Chiang, 2018. "Many Average Partial Effects: with An Application to Text Regression," Papers 1812.09397, arXiv.org, revised Jan 2022.
  114. Yue Cai, 2021. "Measuring Market Power in the IPO Underwriter," Working Papers 2108, Waseda University, Faculty of Political Science and Economics.
  115. Christian B. Hansen & Mark E. Schaffer & Thomas Wiemann & Achim Ahrens, 2022. "ddml: Double/debiased machine learning in Stata," Swiss Stata Conference 2022 02, Stata Users Group.
  116. 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.
  117. Miao, Ke & Phillips, Peter C.B. & Su, Liangjun, 2023. "High-dimensional VARs with common factors," Journal of Econometrics, Elsevier, vol. 233(1), pages 155-183.
  118. Alexandre Belloni & Victor Chernozhukov & Ying Wei, 2013. "Honest confidence regions for a regression parameter in logistic regression with a large number of controls," CeMMAP working papers 67/13, Institute for Fiscal Studies.
  119. Liran Einav & Jonathan Levin, 2014. "The Data Revolution and Economic Analysis," Innovation Policy and the Economy, University of Chicago Press, vol. 14(1), pages 1-24.
  120. Park, Sujeong & Powell, David, 2021. "Is the rise in illicit opioids affecting labor supply and disability claiming rates?," Journal of Health Economics, Elsevier, vol. 76(C).
  121. Mehmet Caner & Xu Han & Yoonseok Lee, 2018. "Adaptive Elastic Net GMM Estimation With Many Invalid Moment Conditions: Simultaneous Model and Moment Selection," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 24-46, January.
  122. 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.
  123. 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.
  124. 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.
  125. 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.
  126. 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.
  127. Michal Kolesár & Raj Chetty & John Friedman & Edward Glaeser & Guido W. Imbens, 2015. "Identification and Inference With Many Invalid Instruments," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(4), pages 474-484, October.
  128. Ivan A. Canay & Magne Mogstad & Jack Mountjoy, 2020. "On the Use of Outcome Tests for Detecting Bias in Decision Making," NBER Working Papers 27802, National Bureau of Economic Research, Inc.
  129. Achim Ahrens & Christian B. Hansen & Mark E. Schaffer & Thomas Wiemann, 2024. "ddml: Double/debiased machine learning in Stata," Stata Journal, StataCorp LP, vol. 24(1), pages 3-45, March.
  130. 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.
  131. 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.
  132. 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.
  133. Alexandre Belloni & Victor Chernozhukov & Kengo Kato, 2013. "Uniform post selection inference for LAD regression and other z-estimation problems," CeMMAP working papers CWP74/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  134. 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.
  135. 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.
  136. Mckenzie,David J. & Sansone,Dario & Mckenzie,David J. & Sansone,Dario, 2017. "Man vs. machine in predicting successful entrepreneurs : evidence from a business plan competition in Nigeria," Policy Research Working Paper Series 8271, The World Bank.
  137. 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.
  138. 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.
  139. 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.
  140. 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.
  141. Timothy B. Armstrong & Michal Koles'ar & Soonwoo Kwon, 2020. "Bias-Aware Inference in Regularized Regression Models," Papers 2012.14823, arXiv.org, revised Aug 2023.
  142. 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.
  143. 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.
  144. Marcelo C. Medeiros & Eduardo F. Mendes, 2012. "Estimating High-Dimensional Time Series Models," CREATES Research Papers 2012-37, Department of Economics and Business Economics, Aarhus University.
  145. 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.
  146. 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.
  147. Milosh, Maria & Painter, Marcus & Sonin, Konstantin & Van Dijcke, David & Wright, Austin L., 2021. "Unmasking partisanship: Polarization undermines public response to collective risk," Journal of Public Economics, Elsevier, vol. 204(C).
  148. Adamek, Robert & Smeekes, Stephan & Wilms, Ines, 2023. "Lasso inference for high-dimensional time series," Journal of Econometrics, Elsevier, vol. 235(2), pages 1114-1143.
  149. Kopp, Daniel, 2024. "Do Recruiters Penalize Men Who Prefer Low Hours? Evidence from Online Labor Market Data," IZA Discussion Papers 16845, Institute of Labor Economics (IZA).
  150. 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.
  151. 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 of the African Governance and Development Institute. 22/061, African Governance and Development Institute..
  152. Carrasco, Marine & Tchuente, Guy, 2015. "Regularized LIML for many instruments," Journal of Econometrics, Elsevier, vol. 186(2), pages 427-442.
  153. 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.
  154. 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.
  155. van Duijn, Mark & Rouwendal, Jan, 2021. "Sorting based on urban heritage and income: Evidence from the Amsterdam metropolitan area," Regional Science and Urban Economics, Elsevier, vol. 90(C).
  156. Fan, Jianqing & Jiang, Bai & Sun, Qiang, 2022. "Bayesian factor-adjusted sparse regression," Journal of Econometrics, Elsevier, vol. 230(1), pages 3-19.
  157. Kazuhiko Shinoda & Takahiro Hoshino, 2022. "Orthogonal Series Estimation for the Ratio of Conditional Expectation Functions," Papers 2212.13145, arXiv.org.
  158. Ye Luo & Martin Spindler & Jannis Kuck, 2016. "High-Dimensional $L_2$Boosting: Rate of Convergence," Papers 1602.08927, arXiv.org, revised Jul 2022.
  159. 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.
  160. Alexandre Belloni & Victor Chernozhukov & Kengo Kato, 2013. "Uniform post selection inference for LAD regression models," CeMMAP working papers CWP24/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  161. Stelios Michalopoulos & Melanie Meng Xue, 2019. "Folklore," NBER Working Papers 25430, National Bureau of Economic Research, Inc.
  162. Christian Hansen & Damian Kozbur & Sanjog Misra, 2016. "Targeted undersmoothing," ECON - Working Papers 282, Department of Economics - University of Zurich, revised Apr 2018.
  163. 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.
  164. Jin Li & Ye Luo & Xiaowei Zhang, 2021. "Causal Reinforcement Learning: An Instrumental Variable Approach," Papers 2103.04021, arXiv.org, revised Sep 2022.
  165. Zhentao Shi & Jingyi Huang, 2019. "Forward-Selected Panel Data Approach for Program Evaluation," Papers 1908.05894, arXiv.org, revised Apr 2021.
  166. 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.
  167. Caballero, Julián, 2021. "Corporate dollar debt and depreciations: All’s well that ends well?," Journal of Banking & Finance, Elsevier, vol. 130(C).
  168. Fu Ouyang & Thomas Tao Yang, 2023. "High Dimensional Binary Choice Model with Unknown Heteroskedasticity or Instrumental Variables," Papers 2311.07067, arXiv.org.
  169. 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).
  170. Rossmann, Tobias, 2019. "Does Experience Shape Subjective Expectations?," Rationality and Competition Discussion Paper Series 181, CRC TRR 190 Rationality and Competition.
  171. 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.
  172. Marc Arnold & Dustin Schuette & Alexander Wagner, 2021. "Neglected Risk in Financial Innovation: Evidence from Structured Product Counterparty Exposure," European Financial Management, European Financial Management Association, vol. 27(2), pages 287-325, March.
  173. Ye Luo & Martin Spindler, 2017. "$L_2$Boosting for Economic Applications," Papers 1702.03244, arXiv.org.
  174. Joshua D. Angrist, 2022. "Empirical Strategies in Economics: Illuminating the Path From Cause to Effect," Econometrica, Econometric Society, vol. 90(6), pages 2509-2539, November.
  175. Ho-Chang Chae, 2024. "In search of gazelles: machine learning prediction for Korean high-growth firms," Small Business Economics, Springer, vol. 62(1), pages 243-284, January.
  176. Bonaccolto-Töpfer, Marina & Briel, Stephanie, 2022. "The gender pay gap revisited: Does machine learning offer new insights?," Labour Economics, Elsevier, vol. 78(C).
  177. Fang, Tong & Lee, Tae-Hwy & Su, Zhi, 2020. "Predicting the long-term stock market volatility: A GARCH-MIDAS model with variable selection," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 36-49.
  178. 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.
  179. Jun Li & Serguei Netessine & Sergei Koulayev, 2018. "Price to Compete … with Many: How to Identify Price Competition in High-Dimensional Space," Management Science, INFORMS, vol. 64(9), pages 4118-4136, September.
  180. Shi, Zhentao & Huang, Jingyi, 2023. "Forward-selected panel data approach for program evaluation," Journal of Econometrics, Elsevier, vol. 234(2), pages 512-535.
  181. Bryan T. Kelly & Asaf Manela & Alan Moreira, 2019. "Text Selection," NBER Working Papers 26517, National Bureau of Economic Research, Inc.
  182. 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.
  183. Hao Hao & Bai Huang & Tae-Hwy Lee, 2022. "Model Averaging Estimation of Panel Data Models with Many Instruments and Boosting," Working Papers 202212, University of California at Riverside, Department of Economics.
  184. Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2021. "Economic Predictions With Big Data: The Illusion of Sparsity," Econometrica, Econometric Society, vol. 89(5), pages 2409-2437, September.
  185. 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.
  186. Qinqin Hu & Lu Lin, 2022. "Feature Screening in High Dimensional Regression with Endogenous Covariates," Computational Economics, Springer;Society for Computational Economics, vol. 60(3), pages 949-969, October.
  187. 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.
  188. 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).
  189. James Archsmith & Kenneth T. Gillingham & Christopher R. Knittel & David S. Rapson, 2020. "Attribute substitution in household vehicle portfolios," RAND Journal of Economics, RAND Corporation, vol. 51(4), pages 1162-1196, December.
  190. Nicolas Apfel, 2019. "Relaxing the Exclusion Restriction in Shift-Share Instrumental Variable Estimation," Papers 1907.00222, arXiv.org, revised Jul 2022.
  191. Stojčić, Nebojša & Matić, Matija, 2024. "A journey toward global value chain upgrading: Exploring the transition from backward to forward integration," Technology in Society, Elsevier, vol. 76(C).
  192. Bilgin, Rumeysa, 2023. "The Selection Of Control Variables In Capital Structure Research With Machine Learning," SocArXiv e26qf, Center for Open Science.
  193. Cho, Hyunkeun, 2016. "The analysis of multivariate longitudinal data using multivariate marginal models," Journal of Multivariate Analysis, Elsevier, vol. 143(C), pages 481-491.
  194. Qiu, Chen & Otsu, Taisuke, 2022. "Information theoretic approach to high dimensional multiplicative models: stochastic discount factor and treatment effect," LSE Research Online Documents on Economics 110494, London School of Economics and Political Science, LSE Library.
  195. Adam Baybutt & Manu Navjeevan, 2023. "Doubly-Robust Inference for Conditional Average Treatment Effects with High-Dimensional Controls," Papers 2301.06283, arXiv.org.
  196. 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.
  197. Chaohua Dong & Jiti Gao & Oliver Linton, 2017. "High dimensional semiparametric moment restriction models," Monash Econometrics and Business Statistics Working Papers 17/17, Monash University, Department of Econometrics and Business Statistics.
  198. 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.
  199. Anthony Bald & Eric Chyn & Justine Hastings & Margarita Machelett, 2022. "The Causal Impact of Removing Children from Abusive and Neglectful Homes," Journal of Political Economy, University of Chicago Press, vol. 130(7), pages 1919-1962.
  200. 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.
  201. Hinnosaar, Marit & Liu, Elaine M., 2022. "Malleability of Alcohol Consumption: Evidence from Migrants," Journal of Health Economics, Elsevier, vol. 85(C).
  202. Su, Liangjun & Ura, Takuya & Zhang, Yichong, 2019. "Non-separable models with high-dimensional data," Journal of Econometrics, Elsevier, vol. 212(2), pages 646-677.
  203. 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.
  204. 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.
  205. Eric Gautier & Alexandre Tsybakov, 2011. "High-Dimensional Instrumental Variables Regression and Confidence Sets," Working Papers 2011-13, Center for Research in Economics and Statistics.
  206. 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.
  207. 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.
  208. 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.
  209. 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.
  210. Prosper Dovonon & Firmin Doko Tchatoka & Michael Aguessy, 2019. "Relevant moment selection under mixed identification strength," School of Economics and Public Policy Working Papers 2019-04, University of Adelaide, School of Economics and Public Policy.
  211. 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).
  212. Sarah Moshary & Bradley T. Shapiro & Jihong Song, 2020. "How and When to Use the Political Cycle to Identify Advertising Effects," NBER Working Papers 27349, National Bureau of Economic Research, Inc.
  213. Benjamin G. Hyman, 2022. "Can Displaced Labor Be Retrained? Evidence from Quasi-Random Assignment to Trade Adjustment Assistance," Working Papers 22-05, Center for Economic Studies, U.S. Census Bureau.
  214. 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.
  215. 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.
  216. Alexandre Belloni & Victor Chernozhukov, 2011. "High Dimensional Sparse Econometric Models: An Introduction," Papers 1106.5242, arXiv.org, revised Sep 2011.
  217. 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.
  218. Ning Xu & Jian Hong & Timothy C. G. Fisher, 2016. "Model selection consistency from the perspective of generalization ability and VC theory with an application to Lasso," Papers 1606.00142, arXiv.org.
  219. Undral Byambadalai, 2022. "Identification and Inference for Welfare Gains without Unconfoundedness," Papers 2207.04314, arXiv.org.
  220. Brian Quistorff & Gentry Johnson, 2020. "Machine Learning for Experimental Design: Methods for Improved Blocking," Papers 2010.15966, arXiv.org.
  221. 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.
  222. Max H. Farrell & Tengyuan Liang & Sanjog Misra, 2018. "Deep Neural Networks for Estimation and Inference," Papers 1809.09953, arXiv.org, revised Sep 2019.
  223. 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.
  224. Mulalic, Ismir & Rouwendal, Jan, 2020. "Does improving public transport decrease car ownership? Evidence from a residential sorting model for the Copenhagen metropolitan area," Regional Science and Urban Economics, Elsevier, vol. 83(C).
  225. Dominick Bartelme & Ting Ting & Andrei A. Levchenko, 2020. "Specialization, Market Access and Real Income," Working Papers 679, Research Seminar in International Economics, University of Michigan.
  226. Liu, Chu-An & Tao, Jing, 2016. "Model selection and model averaging in nonparametric instrumental variables models," MPRA Paper 69492, University Library of Munich, Germany.
  227. 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," TSE Working Papers 18-976, Toulouse School of Economics (TSE).
  228. Kanaya, Shin & Taylor, Luke, 2020. "Type I and Type II Error Probabilities in the Courtroom," MPRA Paper 100217, University Library of Munich, Germany.
  229. 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.
  230. Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2010. "LASSO Methods for Gaussian Instrumental Variables Models," Papers 1012.1297, arXiv.org, revised Feb 2011.
  231. Patrick Bajari & Denis Nekipelov & Stephen P. Ryan & Miaoyu Yang, 2015. "Demand Estimation with Machine Learning and Model Combination," NBER Working Papers 20955, National Bureau of Economic Research, Inc.
  232. 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.
  233. Damian Kozbur, 2017. "Testing-Based Forward Model Selection," American Economic Review, American Economic Association, vol. 107(5), pages 266-269, May.
  234. Fišera, Boris & Horváth, Roman, 2022. "Are exchange rates less important for trade in a more globalized world? Evidence for the new EU members," Economic Systems, Elsevier, vol. 46(1).
  235. Sharadendu Sharma & Yadnesh P. Mundhada & Rahul Arora, 2023. "Which Combination of Trade Provisions Promotes Trade in Value‐Added? An Application of Machine Learning to Cross‐Country Data," Economic Papers, The Economic Society of Australia, vol. 42(4), pages 332-346, December.
  236. Byunghoon Kang, 2018. "Higher Order Approximation of IV Estimators with Invalid Instruments," Working Papers 257105320, Lancaster University Management School, Economics Department.
  237. Gold, David & Lederer, Johannes & Tao, Jing, 2020. "Inference for high-dimensional instrumental variables regression," Journal of Econometrics, Elsevier, vol. 217(1), pages 79-111.
  238. 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.
  239. Taisuke Otsu & Myung Hwan Seo, 2014. "Asymptotics for maximum score method under general conditions," STICERD - Econometrics Paper Series 571, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  240. Alex Coad & Stjepan Srhoj, 2020. "Catching Gazelles with a Lasso: Big data techniques for the prediction of high-growth firms," Small Business Economics, Springer, vol. 55(3), pages 541-565, October.
  241. Daniel L. Chen & Susan Yeh, 2023. "How do rights revolutions occur? Free speech and the first amendment," Working Papers hal-03921964, HAL.
  242. Hao Hao & Tae-Hwy Lee, 2023. "Boosting GMM with Many Instruments When Some Are Invalid or Irrelevant," Working Papers 202309, University of California at Riverside, Department of Economics.
  243. 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.
  244. Härdle, Wolfgang Karl & Chen, Shi & Liang, Chong & Schienle, Melanie, 2018. "Time-varying Limit Order Book Networks," IRTG 1792 Discussion Papers 2018-016, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
  245. Lukas Kiessling & Jonathan Norris, 2020. "The long-run effects of peers on mental health," Working Papers 2006, University of Strathclyde Business School, Department of Economics.
  246. Damian Kozbur, 2020. "Analysis of Testing‐Based Forward Model Selection," Econometrica, Econometric Society, vol. 88(5), pages 2147-2173, September.
  247. Nelson, Kelly P. & Parton, Lee C. & Brown, Zachary S., 2022. "Biofuels policy and innovation impacts: Evidence from biofuels and agricultural patent indicators," Energy Policy, Elsevier, vol. 162(C).
  248. Yiqi Lin & Frank Windmeijer & Xinyuan Song & Qingliang Fan, 2022. "On the instrumental variable estimation with many weak and invalid instruments," Papers 2207.03035, arXiv.org, revised Dec 2023.
  249. Andrii Babii & Eric Ghysels & Jonas Striaukas, 2019. "High-Dimensional Granger Causality Tests with an Application to VIX and News," Papers 1912.06307, arXiv.org, revised Feb 2021.
  250. Dakyung Seong, 2022. "Binary response model with many weak instruments," Papers 2201.04811, arXiv.org, revised May 2023.
  251. Victor Chernozhukov & Iv'an Fern'andez-Val & Chen Huang & Weining Wang, 2024. "Arellano-Bond LASSO Estimator for Dynamic Linear Panel Models," Papers 2402.00584, arXiv.org, revised Apr 2024.
  252. 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.
  253. Manu Navjeevan, 2023. "An Identification and Dimensionality Robust Test for Instrumental Variables Models," Papers 2311.14892, arXiv.org.
  254. Pietro Bonaldi & Ali Hortaçsu & Jakub Kastl, 2015. "An Empirical Analysis of Funding Costs Spillovers in the EURO-zone with Application to Systemic Risk," NBER Working Papers 21462, National Bureau of Economic Research, Inc.
  255. 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.
  256. Khai Xiang Chiong & Matthew Shum, 2019. "Random Projection Estimation of Discrete-Choice Models with Large Choice Sets," Management Science, INFORMS, vol. 65(1), pages 256-271, January.
  257. 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.
  258. Kalouptsidi, Myrto & Brancaccio, Giulia & Papageorgiou, Theodore & Rosaia, Nicola, 2020. "Search Frictions and Efficiency in Decentralized Transport Markets," CEPR Discussion Papers 14827, C.E.P.R. Discussion Papers.
  259. Max H. Farrell, 2013. "Robust Inference on Average Treatment Effects with Possibly More Covariates than Observations," Papers 1309.4686, arXiv.org, revised Feb 2018.
  260. Matthew Backus & Christopher Conlon & Michael Sinkinson, 2021. "Common Ownership and Competition in the Ready-to-Eat Cereal Industry," NBER Working Papers 28350, National Bureau of Economic Research, Inc.
  261. Sander Gerritsen & Mark Kattenberg & Sonny Kuijpers, 2019. "The impact of age at arrival on education and mental health," CPB Discussion Paper 389.rdf, CPB Netherlands Bureau for Economic Policy Analysis.
  262. Qian, Junhui & Su, Liangjun, 2016. "Shrinkage estimation of common breaks in panel data models via adaptive group fused Lasso," Journal of Econometrics, Elsevier, vol. 191(1), pages 86-109.
  263. Michael Zimmert, 2018. "Efficient Difference-in-Differences Estimation with High-Dimensional Common Trend Confounding," Papers 1809.01643, arXiv.org, revised Aug 2020.
  264. Chen, Daniel L., 2018. "Judicial Analytics and the Great Transformation of American Law," TSE Working Papers 18-974, Toulouse School of Economics (TSE).
  265. Arthur Charpentier & Emmanuel Flachaire & Antoine Ly, 2018. "Économétrie & Machine Learning," Working Papers hal-01568851, HAL.
  266. Kumari, Meena & Bao, Yanchun & S. Clarke, Paul & Smart, Melissa, 2018. "A comparison of robust methods for Mendelian randomization using multiple genetic variants," ISER Working Paper Series 2018-08, Institute for Social and Economic Research.
  267. Michael Lechner, 2023. "Causal Machine Learning and its use for public policy," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 159(1), pages 1-15, December.
  268. Daniel L. Chen, 2015. "Can markets stimulate rights? On the alienability of legal claims," RAND Journal of Economics, RAND Corporation, vol. 46(1), pages 23-65, March.
  269. Chen, Daniel L. & Halberstam, Yosh & Yu, Alan, 2016. "Covering: Mutable Characteristics and Perceptions of Voice in the U.S. Supreme Court," TSE Working Papers 16-680, Toulouse School of Economics (TSE), revised Feb 2020.
  270. Tsionas, Mike G., 2023. "Combining data envelopment analysis and stochastic frontiers via a LASSO prior," European Journal of Operational Research, Elsevier, vol. 304(3), pages 1158-1166.
  271. 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.
  272. 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.
  273. Sauvenier, Mathieu & Van Bellegem, Sébastien, 2023. "Direction Identification and Minimax Estimation by Generalized Eigenvalue Problem in High Dimensional Sparse Regression," LIDAM Discussion Papers CORE 2023005, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  274. 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.
  275. Hübler, Olaf, 2021. "COVID-19 Spread in Germany from a Regional Perspective," IZA Discussion Papers 14669, Institute of Labor Economics (IZA).
  276. 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.
  277. Douglas Lehmann & Yun Li & Rajiv Saran & Yi Li, 2017. "Strengthening Instrumental Variables Through Weighting," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 9(2), pages 320-338, December.
  278. Li, Zhaoyuan & Yao, Jianfeng, 2019. "Testing for heteroscedasticity in high-dimensional regressions," Econometrics and Statistics, Elsevier, vol. 9(C), pages 122-139.
  279. 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).
  280. Arthur Charpentier & Emmanuel Flachaire & Antoine Ly, 2017. "Econom\'etrie et Machine Learning," Papers 1708.06992, arXiv.org, revised Mar 2018.
  281. Shi, Zhentao, 2016. "Econometric estimation with high-dimensional moment equalities," Journal of Econometrics, Elsevier, vol. 195(1), pages 104-119.
  282. Dominick Bartelme & Andrei Levchenko & Ting Lan, 2019. "Specialization, Market Access and Medium-Term Growth," 2019 Meeting Papers 999, Society for Economic Dynamics.
  283. Kock, Anders Bredahl & Callot, Laurent, 2015. "Oracle inequalities for high dimensional vector autoregressions," Journal of Econometrics, Elsevier, vol. 186(2), pages 325-344.
  284. Craig McIntosh & Andrew Zeitlin, 2021. "Cash versus Kind: Benchmarking a Child Nutrition Program against Unconditional Cash Transfers in Rwanda," Papers 2106.00213, arXiv.org.
  285. 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.
  286. Meijer, Erik & Spierdijk, Laura & Wansbeek, Tom, 2017. "Consistent estimation of linear panel data models with measurement error," Journal of Econometrics, Elsevier, vol. 200(2), pages 169-180.
  287. 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.
  288. Felipe Barrera-Osorio & Paul Gertler & Nozomi Nakajima & Harry Patrinos, 2020. "Promoting Parental Involvement in Schools: Evidence From Two Randomized Experiments," NBER Working Papers 28040, National Bureau of Economic Research, Inc.
  289. Bonaccolto, Giovanni & Borri, Nicola & Consiglio, Andrea, 2023. "Breakup and default risks in the great lockdown," Journal of Banking & Finance, Elsevier, vol. 147(C).
  290. 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.
  291. 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.
  292. 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.
  293. 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.
  294. Yoonseok Lee & Yu Zhou, 2015. "Averaged Instrumental Variables Estimators," Center for Policy Research Working Papers 180, Center for Policy Research, Maxwell School, Syracuse University.
  295. Daniel J. Lewis & Davide Melcangi & Laura Pilossoph, 2019. "Latent Heterogeneity in the Marginal Propensity to Consume," Staff Reports 902, Federal Reserve Bank of New York.
  296. Susan Athey & Julie Tibshirani & Stefan Wager, 2016. "Generalized Random Forests," Papers 1610.01271, arXiv.org, revised Apr 2018.
  297. 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.
  298. Chen, Daniel L. & Sethi, Jasmin, 2016. "Insiders, Outsiders, and Involuntary Unemployment: Sexual Harrassment Exacerbates Gender Inequality," IAST Working Papers 16-44, Institute for Advanced Study in Toulouse (IAST).
  299. 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.
  300. 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.
  301. 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.
  302. 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.
  303. Sarah Moshary & Bradley T. Shapiro & Jihong Song, 2021. "How and When to Use the Political Cycle to Identify Advertising Effects," Marketing Science, INFORMS, vol. 40(2), pages 283-304, March.
  304. 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.
  305. Guilherme Lichand & Anandi Mani, 2020. "Cognitive droughts," ECON - Working Papers 341, Department of Economics - University of Zurich.
  306. Qingliang Fan & Yaqian Wu, 2020. "Endogenous Treatment Effect Estimation with some Invalid and Irrelevant Instruments," Papers 2006.14998, arXiv.org.
  307. Ari, Anil & Chen, Sophia & Ratnovski, Lev, 2021. "The dynamics of non-performing loans during banking crises: A new database with post-COVID-19 implications," Journal of Banking & Finance, Elsevier, vol. 133(C).
  308. 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.
  309. Chen, Daniel L. & Yeh, Susan, 2016. "Government Expropriation Increases Economic Growth and Racial Inequality: Evidence from Eminent Domain," TSE Working Papers 16-693, Toulouse School of Economics (TSE).
  310. Hamsa Bastani, 2021. "Predicting with Proxies: Transfer Learning in High Dimension," Management Science, INFORMS, vol. 67(5), pages 2964-2984, May.
  311. 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.
  312. Chen, Daniel L., 2018. "Judicial Analytics and the Great Transformation of American Law," IAST Working Papers 18-87, Institute for Advanced Study in Toulouse (IAST).
  313. Xu Cheng & Zhipeng Liao, 2012. "Select the Valid and Relevant Moments: A One-Step Procedure for GMM with Many Moments," PIER Working Paper Archive 12-045, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  314. Guy Tchuente, 2021. "A Note on the Topology of the First Stage of 2SLS with Many Instruments," Papers 2106.15003, arXiv.org.
  315. 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.
  316. Pietro Bonaldi & Ali Hortaçsu & Jakub Kastl, 2015. "Empirical Analysis of Funding Cost Spillovers in the EURO Zone with Application to Systemic Risk," Working Papers 2015-4, Princeton University. Economics Department..
  317. 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.
  318. Crocker H. Liu & Adam Nowak & Patrick S. Smith, 2018. "Does the Asset Pricing Premium Reflect Asymmetric or Incomplete Information?," Working Papers 18-06, Department of Economics, West Virginia University.
  319. Chandio, Rabail & Katchova, Ani & Giri, Anil K. & Subedi, Dipak, 2023. "Impact of interest rate changes and government payments on farm operation's debt," 2023 Annual Meeting, July 23-25, Washington D.C. 335958, Agricultural and Applied Economics Association.
  320. 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.
  321. Luis Antonio Fantozzi Alvarez & Rodrigo Toneto, 2024. "The interpretation of 2SLS with a continuous instrument: a weighted LATE representation," Working Papers, Department of Economics 2024_11, University of São Paulo (FEA-USP).
  322. Alastair R. Hall, 2015. "Econometricians Have Their Moments: GMM at 32," The Economic Record, The Economic Society of Australia, vol. 91(S1), pages 1-24, June.
  323. Mehmet Caner & Anders Bredahl Kock, 2016. "Oracle Inequalities for Convex Loss Functions with Nonlinear Targets," Econometric Reviews, Taylor & Francis Journals, vol. 35(8-10), pages 1377-1411, December.
  324. Jianqing Fan & Kunpeng Li & Yuan Liao, 2020. "Recent Developments on Factor Models and its Applications in Econometric Learning," Papers 2009.10103, arXiv.org.
  325. Guy Tchuente, 2019. "Weak Identification and Estimation of Social Interaction Models," Papers 1902.06143, arXiv.org.
  326. Chen, Daniel L. & Yeh, Susan, 2016. "How Do Rights Revolutions Occur? Free Speech and the First Amendment," IAST Working Papers 16-51, Institute for Advanced Study in Toulouse (IAST).
  327. Chen, Ya & Tsionas, Mike G. & Zelenyuk, Valentin, 2021. "LASSO+DEA for small and big wide data," Omega, Elsevier, vol. 102(C).
  328. Victor Chernozhukov & Chris Hansen & Martin Spindler, 2016. "High-Dimensional Metrics in R," Papers 1603.01700, arXiv.org, revised Aug 2016.
  329. 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.
  330. Kolesár, Michal, 2018. "Minimum distance approach to inference with many instruments," Journal of Econometrics, Elsevier, vol. 204(1), pages 86-100.
  331. Chen, Shi & Härdle, Wolfgang & Schienle, Melanie, 2021. "High-dimensional statistical learning techniques for time-varying limit order book networks," IRTG 1792 Discussion Papers 2021-015, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
  332. Robert Brooks & Brandon N. Cline & Pavel Teterin & Yu You, 2022. "The information in global interest rate futures contracts," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(6), pages 1135-1166, June.
  333. Caro Navarro, Ángela & Peña, Daniel, 2018. "Estimation of the common component in Dynamic Factor Models," DES - Working Papers. Statistics and Econometrics. WS 27047, Universidad Carlos III de Madrid. Departamento de Estadística.
  334. Helmut Wasserbacher & Martin Spindler, 2021. "Machine Learning for Financial Forecasting, Planning and Analysis: Recent Developments and Pitfalls," Papers 2107.04851, arXiv.org.
  335. Matthew Harding & Carlos Lamarche & Chris Muris, 2022. "Estimation of a Factor-Augmented Linear Model with Applications Using Student Achievement Data," Papers 2203.03051, arXiv.org.
  336. 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.
  337. Pedro I. Hancevic & Hector H. Sandoval, 2023. "Solar Panel Adoption in SMEs in Emerging Countries," Working Papers 222, Red Nacional de Investigadores en Economía (RedNIE).
  338. Dimic, Nebojsa & Goodell, John W. & Piljak, Vanja & Vulanovic, Milos, 2023. "Acquisition determinants of energy SPACs: Reflecting a closed group?," Finance Research Letters, Elsevier, vol. 55(PB).
  339. 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).
  340. Zhentao Shi & Liangjun Su & Tian Xie, 2020. "L2-Relaxation: With Applications to Forecast Combination and Portfolio Analysis," Papers 2010.09477, arXiv.org, revised Aug 2022.
  341. Giulia Brancaccio & Myrto Kalouptsidi & Theodore Papageorgiou & Nicola Rosaia, 2020. "Search Frictions and Efficiency in Decentralized Transport Markets," Boston College Working Papers in Economics 1010, Boston College Department of Economics.
  342. Mr. Andrew J Tiffin, 2019. "Machine Learning and Causality: The Impact of Financial Crises on Growth," IMF Working Papers 2019/228, International Monetary Fund.
  343. 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).
  344. Anna Mikusheva & Liyang Sun, 2023. "Weak Identification with Many Instruments," Papers 2308.09535, arXiv.org, revised Jan 2024.
  345. Kaila, Heidi & Azad, Abul, 2023. "The effects of crime and violence on food insecurity and consumption in Nigeria," Food Policy, Elsevier, vol. 115(C).
  346. Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2013. "Supplementary Appendix for "Inference on Treatment Effects After Selection Amongst High-Dimensional Controls"," Papers 1305.6099, arXiv.org, revised Jun 2013.
  347. Sølvsten, Mikkel, 2020. "Robust estimation with many instruments," Journal of Econometrics, Elsevier, vol. 214(2), pages 495-512.
  348. Ya Chen & Mike Tsionas & Valentin Zelenyuk, 2020. "LASSO DEA for small and big data," CEPA Working Papers Series WP092020, School of Economics, University of Queensland, Australia.
  349. 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.
  350. Tianxi Cai & T. Tony Cai & Zijian Guo, 2021. "Optimal statistical inference for individualized treatment effects in high‐dimensional models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(4), pages 669-719, September.
  351. Mardi Dungey & Vitali Alexeev & Jing Tian & Alastair R. Hall, 2015. "Econometricians Have Their Moments: GMM at 32," The Economic Record, The Economic Society of Australia, vol. 91, pages 1-24, June.
  352. Thomas Wiemann, 2023. "Optimal Categorical Instrumental Variables," Papers 2311.17021, arXiv.org.
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