Efficiency Bounds for Semiparametric Regression

Citations

Cited by:

1. Chen, Xiaohong & Pouzo, Demian, 2009. "Efficient estimation of semiparametric conditional moment models with possibly nonsmooth residuals," Journal of Econometrics, Elsevier, vol. 152(1), pages 46-60, September.
   • Xiaohong Chen & Demian Pouzo, 2008. "Efficient Estimation of Semiparametric Conditional Moment Models with Possibly Nonsmooth Residuals," Cowles Foundation Discussion Papers 1640R, Cowles Foundation for Research in Economics, Yale University, revised Jul 2009.
   • Xiaohong Chen & Demian Pouzo, 2009. "Efficient estimation of semiparametric conditional moment models with possibly nonsmooth residuals," CeMMAP working papers CWP20/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
   • Chen, Xiaohong & Pouzo, Demian, 2008. "Efficient Estimation of Semiparametric Conditional Moment Models with Possibly Nonsmooth Residuals," Working Papers 38, Yale University, Department of Economics.
   • Xiaohong Chen & Demian Pouzo, 2008. "Efficient estimation of semiparametric conditional moment models with possibly nonsmooth residuals," CeMMAP working papers CWP09/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
2. 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 28/17, Institute for Fiscal Studies.
   • 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 CWP28/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
3. Xiaohong Chen & Andres Santos, 2018. "Overidentification in Regular Models," Econometrica, Econometric Society, vol. 86(5), pages 1771-1817, September.
   • Xiaohong Chen & Andres Santos, 2015. "Overidentification in Regular Models," Cowles Foundation Discussion Papers 1999, Cowles Foundation for Research in Economics, Yale University.
   • Xiaohong Chen & Andres Santos, 2015. "Overidentification in Regular Models," Cowles Foundation Discussion Papers 1999R, Cowles Foundation for Research in Economics, Yale University, revised Jun 2018.
4. So Im, Kyung & Ahn, Seung C. & Schmidt, Peter & Wooldridge, Jeffrey M., 1999. "Efficient estimation of panel data models with strictly exogenous explanatory variables," Journal of Econometrics, Elsevier, vol. 93(1), pages 177-201, November.
5. Yi Zhang & Kosuke Imai, 2023. "Individualized Policy Evaluation and Learning under Clustered Network Interference," Papers 2311.02467, arXiv.org, revised Feb 2024.
6. Severini, Thomas A. & Tripathi, Gautam, 2012. "Efficiency bounds for estimating linear functionals of nonparametric regression models with endogenous regressors," Journal of Econometrics, Elsevier, vol. 170(2), pages 491-498.
   • Thomas A. Severini & Gautam Tripathi, 2007. "Efficiency Bounds for Estimating Linear Functionals of Nonparametric Regression Models with Endogenous Regressors," Working papers 2007-18, University of Connecticut, Department of Economics.
   • Thomas A. Severini & Gautam Tripathi, 2007. "Efficiency bounds for estimating linear functionals of nonparametric regression models with endogenous regressors," CeMMAP working papers CWP13/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
7. Tadao Hoshino, 2014. "Quantile regression estimation of partially linear additive models," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 26(3), pages 509-536, September.
8. Li, Qi, 1996. "On the root-N-consistent semiparametric estimation of partially linear models," Economics Letters, Elsevier, vol. 51(3), pages 277-285, June.
9. A. Belloni & V. Chernozhukov & I. Fernández‐Val & C. Hansen, 2017. "Program Evaluation and Causal Inference With High‐Dimensional Data," Econometrica, Econometric Society, vol. 85, pages 233-298, January.
   • Alexandre Belloni & Victor Chernozhukov & Ivan Fern'andez-Val & Christian Hansen, 2013. "Program Evaluation and Causal Inference with High-Dimensional Data," Papers 1311.2645, arXiv.org, revised Jan 2018.
   • Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen, 2016. "Program evaluation and causal inference with high-dimensional data," CeMMAP working papers 13/16, Institute for Fiscal Studies.
   • Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen, 2016. "Program evaluation and causal inference with high-dimensional data," CeMMAP working papers CWP13/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
10. Dennis Kristensen, 2009. "Semiparametric modelling and estimation (in Russian)," Quantile, Quantile, issue 7, pages 53-83, September.
11. Hoderlein, Stefan & Holzmann, Hajo & Meister, Alexander, 2017. "The triangular model with random coefficients," Journal of Econometrics, Elsevier, vol. 201(1), pages 144-169.
    • Stefan Hoderlein & Hajo Holzmann & Alexander Meister, 2015. "The triangular model with random coefficients," CeMMAP working papers 33/15, Institute for Fiscal Studies.
    • Stefan Hoderlein & Hajo Holzmann & Alexander Meister, 2015. "The triangular model with random coefficients," CeMMAP working papers CWP33/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    • Stefan Hoderlein & Hajo Holzmann & Alexander Meister, 2015. "The Triangular Model with Random Coefficients," Boston College Working Papers in Economics 894, Boston College Department of Economics, revised 01 Feb 2016.
12. Kirill Borusyak & Peter Hull & Xavier Jaravel, 2023. "Design-Based Identification with Formula Instruments: A Review," NBER Working Papers 31393, National Bureau of Economic Research, Inc.
    • Borusyak, Kirill & Hull, Peter & Jaravel, Xavier, 2024. "Design-based identification with formula instruments: a review," LSE Research Online Documents on Economics 123848, London School of Economics and Political Science, LSE Library.
    • Kirill Borusyak & Peter Hull & Xavier Jaravel, 2023. "Design-based identification with formula instruments: A review," CeMMAP working papers 12/23, Institute for Fiscal Studies.
13. Clément de Chaisemartin & Xavier D’Haultfœuille, 2023. "Two-way fixed effects and differences-in-differences with heterogeneous treatment effects: a survey," The Econometrics Journal, Royal Economic Society, vol. 26(3), pages 1-30.
    • Cl'ement de Chaisemartin & Xavier D'Haultf{oe}uille, 2021. "Two-Way Fixed Effects and Differences-in-Differences with Heterogeneous Treatment Effects: A Survey," Papers 2112.04565, arXiv.org, revised Jun 2022.
    • Clément de Chaisemartin & Xavier D’haultfœuille, 2022. "Two-Way Fixed Effects and Differences-in-Differences with Heterogeneous Treatment Effects: A Survey," Post-Print hal-03873885, HAL.
    • Clément de Chaisemartin & Xavier D'Haultfoeuille, 2022. "Two-Way Fixed Effects and Differences-in-Differences with Heterogeneous Treatment Effects: A Survey," NBER Working Papers 29734, National Bureau of Economic Research, Inc.
    • Clément de Chaisemartin & Xavier D'Haultfoeuille, 2022. "Two-Way Fixed Effects and Differences-in-Differences with Heterogeneous Treatment Effects: A Survey," NBER Working Papers 29691, National Bureau of Economic Research, Inc.
    • Xavier d'Haultfoeuille, 2022. "Two-way fixed effects and difference in differences with heterogeneous treatment effects: A survey," French Stata Users' Group Meetings 2022 01, Stata Users Group.
    • Clément de Chaisemartin & Xavier D’haultfœuille, 2022. "Two-Way Fixed Effects and Differences-in-Differences with Heterogeneous Treatment Effects: A Survey," SciencePo Working papers Main hal-03873885, HAL.
14. Xiaohong Chen & Demian Pouzo, 2012. "Estimation of Nonparametric Conditional Moment Models With Possibly Nonsmooth Generalized Residuals," Econometrica, Econometric Society, vol. 80(1), pages 277-321, January.
    • Xiaohong Chen & Demian Pouzo, 2008. "Estimation of Nonparametric Conditional Moment Models With Possibly Nonsmooth Generalized Residuals," Cowles Foundation Discussion Papers 1650R, Cowles Foundation for Research in Economics, Yale University, revised Jul 2009.
    • Xiaohong Chen & Demian Pouzo, 2008. "Estimation of Nonparametric Conditional Moment Models With Possibly Nonsmooth Generalized Residuals," Cowles Foundation Discussion Papers 1650RR, Cowles Foundation for Research in Economics, Yale University, revised Jan 2011.
15. Okui, Ryo & Yanagi, Takahide, 2019. "Panel data analysis with heterogeneous dynamics," Journal of Econometrics, Elsevier, vol. 212(2), pages 451-475.
    • Ryo Okui & Takahide Yanagi, 2014. "Panel Data Analysis with Heterogeneous Dynamics," KIER Working Papers 906, Kyoto University, Institute of Economic Research.
    • Ryo Okui & Takahide Yanagi, 2018. "Panel Data Analysis with Heterogeneous Dynamics," Papers 1803.09452, arXiv.org, revised Jan 2019.
16. Magnac, Thierry & Maurin, Eric, 2007. "Identification and information in monotone binary models," Journal of Econometrics, Elsevier, vol. 139(1), pages 76-104, July.
    • Magnac, Thierry & Maurin, Eric, 2003. "Identification and Information in Monotone Binary Models," IDEI Working Papers 180, Institut d'Économie Industrielle (IDEI), Toulouse, revised Oct 2004.
    • Thierry Magnac & Eric Maurin, 2007. "Identification and Information in Monotone Binary Models," PSE-Ecole d'économie de Paris (Postprint) halshs-00754218, HAL.
    • Thierry Magnac & Eric Maurin, 2007. "Identification and Information in Monotone Binary Models," Post-Print halshs-00754218, HAL.
17. Graham, Bryan S. & Hahn, Jinyong & Poirier, Alexandre & Powell, James L., 2018. "A quantile correlated random coefficients panel data model," Journal of Econometrics, Elsevier, vol. 206(2), pages 305-335.
    • Bryan S. Graham & Jinyong Hahn & Alexandre Poirier & James L. Powell, 2016. "A quantile correlated random coefficients panel data model," CeMMAP working papers CWP34/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    • Bryan S. Graham & Jinyong Hahn & Alexandre Poirier & James L. Powell, 2016. "A quantile correlated random coefficients panel data model," CeMMAP working papers 34/16, Institute for Fiscal Studies.
18. Xiaohong Chen & Victor Chernozhukov & Sokbae Lee & Whitney K. Newey, 2014. "Local Identification of Nonparametric and Semiparametric Models," Econometrica, Econometric Society, vol. 82(2), pages 785-809, March.
    • Xiaohong Chen & Victor Chernozhukov & Sokbae Lee & Whitney Newey, 2011. "Local Identification of Nonparametric and Semiparametric Models," Cowles Foundation Discussion Papers 1795, Cowles Foundation for Research in Economics, Yale University.
    • Xiaohong Chen & Victor Chernozhukov & Sokbae (Simon) Lee & Whitney K. Newey, 2012. "Local identification of nonparametric and semiparametric models," CeMMAP working papers 37/12, Institute for Fiscal Studies.
    • Xiaohong Chen & Victor Chernozhukov & Sokbae (Simon) Lee & Whitney K. Newey, 2011. "Local identification of nonparametric and semiparametric models," CeMMAP working papers 17/11, Institute for Fiscal Studies.
    • Xiaohong Chen & Victor Chernozhukov & Sokbae Lee & Whitney Newey, 2011. "Local Identification of Nonparametric and Semiparametric Models," Cowles Foundation Discussion Papers 1795R, Cowles Foundation for Research in Economics, Yale University, revised Nov 2012.
    • Xiaohong Chen & Victor Chernozhukov & Sokbae (Simon) Lee & Whitney K. Newey, 2011. "Local identification of nonparametric and semiparametric models," CeMMAP working papers CWP17/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    • Xiaohong Chen & Victor Chernozhukov & Sokbae (Simon) Lee & Whitney K. Newey, 2012. "Local identification of nonparametric and semiparametric models," CeMMAP working papers CWP37/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
19. Stephane Bonhomme & Angela Denis, 2024. "Estimating Heterogeneous Effects: Applications to Labor Economics," Papers 2404.01495, arXiv.org.
20. Alain-Philippe Fortin & Patrick Gagliardini & O. Scaillet, 2022. "Eigenvalue tests for the number of latent factors in short panels," Swiss Finance Institute Research Paper Series 22-81, Swiss Finance Institute.
    • Alain-Philippe Fortin & Patrick Gagliardini & Olivier Scaillet, 2022. "Eigenvalue tests for the number of latent factors in short panels," Papers 2210.16042, arXiv.org.
21. Alexandre Belloni & Victor Chernozhukov & Lie Wang, 2013. "Pivotal estimation via square-root lasso in nonparametric regression," CeMMAP working papers CWP62/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    • 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.
22. Alain Carpentier & Robert D. Weaver, 1996. "Assessment of producers' attitude toward risk and information using panel data : the example of pesticide use in the French crop sector," Post-Print hal-01931607, HAL.
23. Patrick Gagliardini & Elisa Ossola & O. Scaillet, 2019. "Estimation of Large Dimensional Conditional Factor Models in Finance," Swiss Finance Institute Research Paper Series 19-46, Swiss Finance Institute.
    • Gagliardini, Patrick & Ossola, Elisa & Scaillet, Olivier, 2019. "Estimation of large dimensional conditional factor models in finance," Working Papers unige:125031, University of Geneva, Geneva School of Economics and Management.
24. Xiaohong Chen & Demian Pouzo, 2015. "Sieve Wald and QLR Inferences on Semi/Nonparametric Conditional Moment Models," Econometrica, Econometric Society, vol. 83(3), pages 1013-1079, May.
    • Xiaohong Chen & Demian Pouzo, 2013. "Sieve Wald and QLR Inferences on Semi/nonparametric Conditional Moment Models," Cowles Foundation Discussion Papers 1897R, Cowles Foundation for Research in Economics, Yale University, revised Apr 2014.
    • Xiaohong Chen & Demian Pouzo, 2014. "Sieve Wald and QLR Inferences on Semi/nonparametric Conditional Moment Models," Papers 1411.1144, arXiv.org, revised Mar 2015.
    • Xiaohong Chen & Demian Pouzo, 2013. "Sieve Wald and QLR Inferences on Semi/nonparametric Conditional Moment Models," Cowles Foundation Discussion Papers 1897RR, Cowles Foundation for Research in Economics, Yale University, revised Nov 2014.
    • Xiaohong Chen & Demian Pouzo, 2014. "Sieve Wald and QLR Inferences on Semi/nonparametric Conditional Moment Models," CeMMAP working papers CWP38/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
25. 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.
    • Victor Chernozhukov & Juan Carlos Escanciano & Hidehiko Ichimura & Whitney K. Newey, 2016. "Locally robust semiparametric estimation," CeMMAP working papers CWP31/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    • Victor Chernozhukov & Juan Carlos Escanciano & Hidehiko Ichimura & Whitney K. Newey & James M. Robins, 2016. "Locally Robust Semiparametric Estimation," Papers 1608.00033, arXiv.org, revised Aug 2020.
    • Victor Chernozhukov & Juan Carlos Escanciano & Hidehiko Ichimura & Whitney K. Newey & James M. Robins, 2018. "Locally robust semiparametric estimation," CeMMAP working papers CWP30/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    • Victor Chernozhukov & Juan Carlos Escanciano & Hidehiko Ichimura & Whitney K. Newey, 2016. "Locally robust semiparametric estimation," CeMMAP working papers 31/16, Institute for Fiscal Studies.
26. Patrick Gagliardini & Elisa Ossola & Olivier Scaillet, 2016. "Time‐Varying Risk Premium in Large Cross‐Sectional Equity Data Sets," Econometrica, Econometric Society, vol. 84, pages 985-1046, May.
    • Patrick GAGLIARDINI & Elisa OSSOLA & Olivier SCAILLET, 2011. "Time-Varying Risk Premium In Large Cross-Sectional Equidity Datasets," Swiss Finance Institute Research Paper Series 11-40, Swiss Finance Institute.
    • Ossola, Elisa & Gagilardini, Patrick & Scaillet, Olivier, 2015. "Time-varying risk premium in large cross-sectional equity datasets," Working Papers unige:76321, University of Geneva, Geneva School of Economics and Management.
    • Patrick GAGLIARDINI & Elisa OSSOLA & Olivier SCAILLET, 2011. "Time-Varying Risk Premium In Large Cross-Sectional Equidity Datasets," Swiss Finance Institute Research Paper Series 11-41, Swiss Finance Institute.
27. 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.
28. Park, Byeong U. & Sickles, Robin C. & Simar, Leopold, 2003. "Semiparametric-efficient estimation of AR(1) panel data models," Journal of Econometrics, Elsevier, vol. 117(2), pages 279-309, December.
    • Park, B.U. & Sickles, R.C. & Simar, L., 2000. "Semiparametric Efficient Estimation of AR(1) Panel Data Models," Papers 0020, Catholique de Louvain - Institut de statistique.
    • Byeong Park & Robin C. Sickles & Leopold Simar, 2000. "Semiparametric Efficient Estimation of AR(1) Panel Data Models," Econometric Society World Congress 2000 Contributed Papers 1510, Econometric Society.
29. Rosen, Adam M., 2012. "Set identification via quantile restrictions in short panels," Journal of Econometrics, Elsevier, vol. 166(1), pages 127-137.
    • Adam Rosen, 2009. "Set identification via quantile restrictions in short panels," CeMMAP working papers CWP26/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
30. Cheng Hsiao & Qi Li & Zhongwen Liang & Wei Xie, 2019. "Panel Data Estimation for Correlated Random Coefficients Models," Econometrics, MDPI, vol. 7(1), pages 1-18, February.
31. Joris Pinkse & Margaret Slade, 2007. "Semi-structural models of advertising competition," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(7), pages 1227-1246.
32. Chris Muris, 2020. "Efficient GMM Estimation with Incomplete Data," The Review of Economics and Statistics, MIT Press, vol. 102(3), pages 518-530, July.
33. Manzan, sebastiano & Zerom, Dawit, 2008. "A Semiparametric Analysis of Gasoline Demand in the US: Reexamining The Impact of Price," MPRA Paper 14386, University Library of Munich, Germany.
34. Mert Demirer & Vasilis Syrgkanis & Greg Lewis & Victor Chernozhukov, 2019. "Semi-Parametric Efficient Policy Learning with Continuous Actions," CeMMAP working papers CWP34/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    • Mert Demirer & Vasilis Syrgkanis & Greg Lewis & Victor Chernozhukov, 2019. "Semi-Parametric Efficient Policy Learning with Continuous Actions," Papers 1905.10116, arXiv.org, revised Jul 2019.
35. Xiaohong Chen & Demian Pouzo, 2014. "Sieve Wald and QLR Inferences on Semi/nonparametric Conditional Moment Models," CeMMAP working papers 38/14, Institute for Fiscal Studies.
36. Xin Geng & Carlos Martins-Filho & Feng Yao, 2015. "Estimation of a Partially Linear Regression in Triangular Systems," Working Papers 15-46, Department of Economics, West Virginia University.
    • Xin Geng & Carlos Martins-Filho & Feng Yao, 2018. "Estimation of a Partially Linear Regression in Triangular Systems," Working Papers 18-05, Department of Economics, West Virginia University.
37. Manuel Arellano & Stéphane Bonhomme, 2012. "Identifying Distributional Characteristics in Random Coefficients Panel Data Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 79(3), pages 987-1020.
    • Manuel Arellano & Stéphane Bonhomme, 2009. "Identifying Distributional Characteristics in Random Coefficients Panel Data Models," Working Papers wp2009_0904, CEMFI.
    • Manuel Arellano & Stéphane Bonhomme, 2009. "Identifying distributional characteristics in random coefficients panel data models," CeMMAP working papers CWP22/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
38. Miguel A. Delgado & Juan Mora, 1995. "On asymptotic inferences in non-parametric and semiparametric models with discrete and mixed regressors," Investigaciones Economicas, Fundación SEPI, vol. 19(3), pages 435-467, September.
39. Qi Li & Aman Ullha, 1998. "Estimating partially linear panel data models with one-way error components," Econometric Reviews, Taylor & Francis Journals, vol. 17(2), pages 145-166.
40. Blazsek, Szabolcs & Escribano, Alvaro, 2016. "Score-driven dynamic patent count panel data models," Economics Letters, Elsevier, vol. 149(C), pages 116-119.
    • Blazsek, Szabolcs, 2016. "Score-driven dynamic patent count panel data models," UC3M Working papers. Economics 23458, Universidad Carlos III de Madrid. Departamento de Economía.
41. Muller, Ursula U. & Van Keilegom, Ingrid, 2011. "Efficient parameter estimation in regression with missing responses," LIDAM Discussion Papers ISBA 2011026, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
42. Dmitry Arkhangelsky & Guido W. Imbens, 2019. "Doubly Robust Identification for Causal Panel Data Models," Papers 1909.09412, arXiv.org, revised Feb 2022.
    • Dmitry Arkhangelsky & Guido W. Imbens, 2021. "Double-Robust Identification for Causal Panel Data Models," NBER Working Papers 28364, National Bureau of Economic Research, Inc.
43. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
    • M Arellano & O Bover, 1990. "Another Look at the Instrumental Variable Estimation of Error-Components Models," CEP Discussion Papers dp0007, Centre for Economic Performance, LSE.
44. Mora, Juan, 1993. "Inference on semiparametric models with discrete regressors," DES - Working Papers. Statistics and Econometrics. WS 3700, Universidad Carlos III de Madrid. Departamento de Estadística.
45. Alyssa Carlson & Riju Joshi, 2024. "Sample selection in linear panel data models with heterogeneous coefficients," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(2), pages 237-255, March.
    • Alyssa Carlson & Riju Joshi, 2021. "Sample Selection in Linear Panel Data Models with Heterogeneous Coefficients," Working Papers 2115, Department of Economics, University of Missouri.
    • Alyssa Carlson & Riju Joshi, 2023. "Sample Selection in Linear Panel Data Models with Heterogeneous Coefficients," Working Papers 2305, Department of Economics, University of Missouri.
    • Alyssa Carlson & Riju Joshi, 2022. "Sample Selection in Linear Panel Data Models with Heterogeneous Coefficients," Working Papers 2203, Department of Economics, University of Missouri.
    • Alyssa Carlson & Riju Joshi, 2021. "Sample Selection in Linear Panel Data Models with Heterogeneous Coefficients," Working Papers 2103, Department of Economics, University of Missouri.
    • Alyssa Carlson & Riju Joshi, 2023. "Sample Selection in Linear Panel Data Models with Heterogeneous Coefficients," Working Papers 2312, Department of Economics, University of Missouri.
46. Demian Pouzo & Zacharias Psaradakis & Martin Sola, 2022. "Maximum Likelihood Estimation in Markov Regime‐Switching Models With Covariate‐Dependent Transition Probabilities," Econometrica, Econometric Society, vol. 90(4), pages 1681-1710, July.
    • Demian Pouzo & Zacharias Psaradakis & Martin Sola, 2016. "Maximum Likelihood Estimation in Markov Regime-Switching Models with Covariate-Dependent Transition Probabilities," Papers 1612.04932, arXiv.org, revised Dec 2021.
    • Demian Pouzo & Zacharias Psaradakis & Martín Sola, 2021. "Maximum Likelihood Estimation in Markov Regime-Switching Models with Covariate-Dependent Transition Probabilities," Department of Economics Working Papers 2021_07, Universidad Torcuato Di Tella.
47. Bryan S. Graham, 2019. "Network Data," NBER Working Papers 26577, National Bureau of Economic Research, Inc.
    • Bryan S. Graham, 2019. "Network Data," Papers 1912.06346, arXiv.org.
48. Louise Laage, 2020. "A Correlated Random Coefficient Panel Model with Time-Varying Endogeneity," Papers 2003.09367, arXiv.org, revised Nov 2022.
49. Sebastiano Manzan & Dawit Zerom, 2010. "A Semiparametric Analysis of Gasoline Demand in the United States Reexamining The Impact of Price," Econometric Reviews, Taylor & Francis Journals, vol. 29(4), pages 439-468.
50. Emine Boz & Gita Gopinath & Mikkel Plagborg-Møller, 2017. "Global Trade and the Dollar," NBER Working Papers 23988, National Bureau of Economic Research, Inc.
    • Mikkel Plagborg-Moller & Gita Gopinath & Emine Boz, 2017. "Global Trade and the Dollar," 2017 Meeting Papers 1041, Society for Economic Dynamics.
    • Emine Boz & Gita Gopinath & Mikkel Plagborg-Møller, 2017. "Global Trade and the Dollar," Working Paper 489661, Harvard University OpenScholar.
    • Ms. Emine Boz & Ms. Gita Gopinath & Mikkel Plagborg-Møller, 2017. "Global Trade and the Dollar," IMF Working Papers 2017/239, International Monetary Fund.
51. Ai, Chunrong & Chen, Xiaohong, 2012. "The semiparametric efficiency bound for models of sequential moment restrictions containing unknown functions," Journal of Econometrics, Elsevier, vol. 170(2), pages 442-457.
    • Chunrong Ai & Xiaohong Chen, 2009. "Semiparametric Efficiency Bound for Models of Sequential Moment Restrictions Containing Unknown Functions," Cowles Foundation Discussion Papers 1731, Cowles Foundation for Research in Economics, Yale University.
    • Chunrong Ai & Xiaohong Chen, 2009. "Semiparametric efficiency bound for models of sequential moment restrictions containing unknown functions," CeMMAP working papers CWP28/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
52. Graham, Bryan S. & Pinto, Cristine Campos de Xavier, 2022. "Semiparametrically efficient estimation of the average linear regression function," Journal of Econometrics, Elsevier, vol. 226(1), pages 115-138.
    • Bryan S. Graham & Cristine Campos de Xavier Pinto, 2018. "Semiparametrically Efficient Estimation of the Average Linear Regression Function," NBER Working Papers 25234, National Bureau of Economic Research, Inc.
    • Bryan S. Graham & Cristine Campos de Xavier Pinto, 2018. "Semiparametrically efficient estimation of the average linear regression function," Papers 1810.12511, arXiv.org.
    • Bryan S. Graham & Cristine Campos de Xavier Pinto, 2018. "Semiparametrically efficient estimation of the average linear regression function," CeMMAP working papers CWP62/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
53. Michael Bates & Seolah Kim, 2019. "Per-Cluster Instrumental Variables Estimation: Uncovering the Price Elasticity of the Demand for Gasoline," Working Papers 202003, University of California at Riverside, Department of Economics.
54. Bent Jesper Christensen & Michael Sørensen, 2008. "Optimal inference in dynamic models with conditional moment restrictions," CREATES Research Papers 2008-51, Department of Economics and Business Economics, Aarhus University.
55. Jelena Bradic & Victor Chernozhukov & Whitney K. Newey & Yinchu Zhu, 2019. "Minimax Semiparametric Learning With Approximate Sparsity," Papers 1912.12213, arXiv.org, revised Aug 2022.
56. Ahn, Seung C. & Lee, Young H. & Schmidt, Peter, 2013. "Panel data models with multiple time-varying individual effects," Journal of Econometrics, Elsevier, vol. 174(1), pages 1-14.
    • Seung C. Ahn & Young H. Lee & Peter Schmidt, 2007. "Panel Data Models with Multiple Time-Varying Individual Effects," Working Papers 0702, University of Crete, Department of Economics.
57. Bryan S. Graham & James Powell, 2008. "Identification and Estimation of 'Irregular' Correlated Random Coefficient Models," NBER Working Papers 14469, National Bureau of Economic Research, Inc.
58. Park, Sangin, 2003. "Semiparametric instrumental variables estimation," Journal of Econometrics, Elsevier, vol. 112(2), pages 381-399, February.
59. Hansen, Lars Peter & Scheinkman, Jose Alexandre, 1995. "Back to the Future: Generating Moment Implications for Continuous-Time Markov Processes," Econometrica, Econometric Society, vol. 63(4), pages 767-804, July.
    • Lars Peter Hansen & Jose Alexandre Scheinkman, 1993. "Back to the Future: Generating Moment Implications for Continuous-Time Markov Processes," NBER Technical Working Papers 0141, National Bureau of Economic Research, Inc.
60. Chirok Han & Goeun Lee, 2017. "Efficient Estimation of Linear Panel Data Models with Sample Selection and Fixed Effects," Discussion Paper Series 1707, Institute of Economic Research, Korea University.
61. Bartolucci, Francesco & Belotti, Federico & Peracchi, Franco, 2015. "Testing for time-invariant unobserved heterogeneity in generalized linear models for panel data," Journal of Econometrics, Elsevier, vol. 184(1), pages 111-123.
    • Francesco Bartolucci & Federico Belotti & Franco Peracchi, 2013. "Testing for Time-Invariant Unobserved Heterogeneity in Generalized Linear Models for Panel Data," EIEF Working Papers Series 1312, Einaudi Institute for Economics and Finance (EIEF), revised May 2013.
62. Feng Yao & Junsen Zhang, 2015. "Efficient kernel-based semiparametric IV estimation with an application to resolving a puzzle on the estimates of the return to schooling," Empirical Economics, Springer, vol. 48(1), pages 253-281, February.
    • Feng Yao & Junsen Zhang, 2013. "Efficient Kernel-Based Semiparametric IV Estimation with an Application to Resolving a Puzzle on the Estimates of the Return to Schooling," Working Papers 13-01, Department of Economics, West Virginia University.
63. Gibbons Charles E. & Suárez Serrato Juan Carlos & Urbancic Michael B., 2019. "Broken or Fixed Effects?," Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-12, January.
    • Charles E. Gibbons & Juan Carlos Suárez Serrato & Michael B. Urbancic, 2014. "Broken or Fixed Effects?," NBER Working Papers 20342, National Bureau of Economic Research, Inc.
64. Manzan, Sebastiano & Zerom, Dawit, 2005. "Kernel estimation of a partially linear additive model," Statistics & Probability Letters, Elsevier, vol. 72(4), pages 313-322, May.
65. Ben Deaner, 2018. "Proxy Controls and Panel Data," Papers 1810.00283, arXiv.org, revised Nov 2023.
66. Chen, Xiaohong, 2007. "Large Sample Sieve Estimation of Semi-Nonparametric Models," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 76, Elsevier.
67. Bryan S. Graham & Jinyong Hahn & Alexandre Poirier & James L. Powell, 2015. "Quantile regression with panel data," CeMMAP working papers CWP12/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    • Bryan S. Graham & Jinyong Hahn & Alexandre Poirier & James L. Powell, 2015. "Quantile Regression with Panel Data," NBER Working Papers 21034, National Bureau of Economic Research, Inc.
    • Bryan S. Graham & Jinyong Hahn & Alexandre Poirier & James L. Powell, 2015. "Quantile regression with panel data," CeMMAP working papers 12/15, Institute for Fiscal Studies.
68. repec:gnv:wpaper:unige:76321 is not listed on IDEAS
69. Han, Chirok & Orea, Luis & Schmidt, Peter, 2005. "Estimation of a panel data model with parametric temporal variation in individual effects," Journal of Econometrics, Elsevier, vol. 126(2), pages 241-267, June.
    • Han, Chirok & Orea, Luis & Schmidt, Peter, 2002. "Estimation of a Panel Data Model with Parametric Temporal Variation in Individual Effects," Efficiency Series Papers 2002/05, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    • Peter Schmidt & Chirok Han & Luis Orea, 2004. "Estimation of a Panel Data Model with Parametric Temporal Variation in Individual Effects," Econometric Society 2004 Far Eastern Meetings 519, Econometric Society.
70. Blazsek, Szabolcs, 2015. "Dynamic conditional score patent count panel data models," UC3M Working papers. Economics we1510, Universidad Carlos III de Madrid. Departamento de Economía.
71. Song Nian Chen, 2000. "Semiparametric Estimation of Heteroscedastic Binary Sample Selection Model," Econometric Society World Congress 2000 Contributed Papers 0263, Econometric Society.
72. Subbotin, Viktor, 2008. "Essays on the econometric theory of rank regressions," MPRA Paper 14086, University Library of Munich, Germany.
73. Lee, Sungwon, 2023. "Efficient estimation of a triangular system of equations for quantile regression," Economics Letters, Elsevier, vol. 226(C).
74. Joshua D. Angrist & Jinyong Hahn, 1999. "When to Control for Covariates? Panel-Asymptotic Results for Estimates of Treatment Effects," NBER Technical Working Papers 0241, National Bureau of Economic Research, Inc.
75. Valentin Verdier, 2020. "Average treatment effects for stayers with correlated random coefficient models of panel data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(7), pages 917-939, November.
76. Escanciano, Juan Carlos, 2023. "Irregular identification of structural models with nonparametric unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 234(1), pages 106-127.
    • Juan Carlos Escanciano, 2020. "Irregular Identification of Structural Models with Nonparametric Unobserved Heterogeneity," Papers 2005.08611, arXiv.org.
77. Breitung, Jörg & Salish, Nazarii, 2021. "Estimation of heterogeneous panels with systematic slope variations," Journal of Econometrics, Elsevier, vol. 220(2), pages 399-415.
78. Irene Botosaru & Chris Muris, 2017. "Binarization for panel models with fixed effects," CeMMAP working papers 31/17, Institute for Fiscal Studies.
    • Irene Botosaru & Chris Muris, 2017. "Binarization for panel models with fixed effects," CeMMAP working papers CWP31/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
79. Zhang, Zhengyu & He, Xiaobo, 2012. "Estimation of a heteroscedastic binary choice model with an endogenous dummy regressor," Economics Letters, Elsevier, vol. 117(3), pages 753-757.
80. Song, Suyong, 2015. "Semiparametric estimation of models with conditional moment restrictions in the presence of nonclassical measurement errors," Journal of Econometrics, Elsevier, vol. 185(1), pages 95-109.
81. Robinson, Peter M. & Thawornkaiwong, Supachoke, 2012. "Statistical inference on regression with spatial dependence," Journal of Econometrics, Elsevier, vol. 167(2), pages 521-542.
82. Ahn, Seung Chan & Hoon Lee, Young & Schmidt, Peter, 2001. "GMM estimation of linear panel data models with time-varying individual effects," Journal of Econometrics, Elsevier, vol. 101(2), pages 219-255, April.
83. Demian Pouzo & Zacharias Psaradakis & Martin Sola, 2016. "Maximum Likelihood Estimation in Possibly Misspeci ed Dynamic Models with Time-Inhomogeneous Markov Regimes," Department of Economics Working Papers 2016_04, Universidad Torcuato Di Tella.
84. Michael Bates & Seolah Kim, 2024. "Estimating the price elasticity of gasoline demand in correlated random coefficient models with endogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(4), pages 679-696, June.
    • Michael Bates & Seolah Kim, 2019. "Estimating the Price Elasticity of Gasoline Demand in Correlated Random Coefficient Models with Endogeneity," Working Papers 202304, University of California at Riverside, Department of Economics, revised Aug 2023.
    • Michael Bates & Seolah Kim, 2023. "Estimating the price elasticity of gasoline demand in correlated random coefficient models with endogeneity," German Stata Conference 2023 04, Stata Users Group.
    • Michael Bates & Seolah Kim, 2019. "Estimating the Price Elasticity of Gasoline Demand in Correlated Random Coefficient Models with Endogeneity," Working Papers 202021, University of California at Riverside, Department of Economics, revised Jul 2020.
85. 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.
    • 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 CWP49/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
86. Nicholas Brown & Jeffrey Wooldridge, 2023. "More Efficient Estimation of Multiplicative Panel Data Models in the Presence of Serial Correlation," Working Paper 1497, Economics Department, Queen's University.
87. Harrison H. Li & Art B. Owen, 2023. "Double machine learning and design in batch adaptive experiments," Papers 2309.15297, arXiv.org.
88. Chamberlain, Gary, 2022. "Feedback in panel data models," Journal of Econometrics, Elsevier, vol. 226(1), pages 4-20.
    • Chamberlain, G., 1993. "Feedback in Panel Data Medels," Harvard Institute of Economic Research Working Papers 1656, Harvard - Institute of Economic Research.
89. Dmitry Arkhangelsky & Guido Imbens, 2023. "Causal Models for Longitudinal and Panel Data: A Survey," Papers 2311.15458, arXiv.org, revised Jun 2024.
90. Alain-Philippe Fortin & Patrick Gagliardini & Olivier Scaillet, 2023. "Latent Factor Analysis in Short Panels," Swiss Finance Institute Research Paper Series 23-44, Swiss Finance Institute.
    • Alain-Philippe Fortin & Patrick Gagliardini & Olivier Scaillet, 2023. "Latent Factor Analysis in Short Panels," Papers 2306.14004, arXiv.org, revised May 2024.
91. Georg Keilbar & Juan M. Rodriguez-Poo & Alexandra Soberon & Weining Wang, 2022. "A semiparametric approach for interactive fixed effects panel data models," Papers 2201.11482, arXiv.org, revised Mar 2023.
92. Gagliardini, Patrick & Gouriéroux, Christian, 2019. "Identification by Laplace transforms in nonlinear time series and panel models with unobserved stochastic dynamic effects," Journal of Econometrics, Elsevier, vol. 208(2), pages 613-637.
93. Wooldridge, Jeffrey M., 1999. "Distribution-free estimation of some nonlinear panel data models," Journal of Econometrics, Elsevier, vol. 90(1), pages 77-97, May.
    • Wooldridge, J.M., 1990. "Distribution-Free Estimation Of Some Nonlinear Panel Data Models," Working papers 564, Massachusetts Institute of Technology (MIT), Department of Economics.
94. Rodriguez Poo, Juan M. & Vieu, Philippe, 2000. "Semiparametric estimation of weak and strong separable models," DES - Working Papers. Statistics and Econometrics. WS 10064, Universidad Carlos III de Madrid. Departamento de Estadística.
95. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
96. 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.
    • Victor Chernozhukov & Whitney K Newey & Rahul Singh, 2018. "Automatic Debiased Machine Learning of Causal and Structural Effects," Papers 1809.05224, arXiv.org, revised Oct 2022.
97. Chen, Songnian & Zhou, Yahong, 2010. "Semiparametric and nonparametric estimation of sample selection models under symmetry," Journal of Econometrics, Elsevier, vol. 157(1), pages 143-150, July.
98. St'ephane Bonhomme & Kevin Dano, 2023. "Functional Differencing in Networks," Papers 2307.11484, arXiv.org.
99. Dmitry Arkhangelsky & Aleksei Samkov, 2024. "Sequential Synthetic Difference in Differences," Papers 2404.00164, arXiv.org.
100. Henderson, Daniel J. & Carroll, Raymond J. & Li, Qi, 2008. "Nonparametric estimation and testing of fixed effects panel data models," Journal of Econometrics, Elsevier, vol. 144(1), pages 257-275, May.
101. repec:wvu:wpaper:10-11 is not listed on IDEAS
102. Sangin Park, 2000. "Semiparametric Instrumental Variables Estimation and Its Application to Dynamic Oligopoly," Econometric Society World Congress 2000 Contributed Papers 0432, Econometric Society.
103. Nathan Kallus & Miruna Oprescu, 2022. "Robust and Agnostic Learning of Conditional Distributional Treatment Effects," Papers 2205.11486, arXiv.org, revised Feb 2023.
104. Detemple, Jerome & Garcia, Rene & Rindisbacher, Marcel, 2006. "Asymptotic properties of Monte Carlo estimators of diffusion processes," Journal of Econometrics, Elsevier, vol. 134(1), pages 1-68, September.
     • Jérôme Detemple & René Garcia & Marcel Rindisbacher, 2003. "Asymptotic Properties of Monte Carlo Estimators of Diffusion Processes," CIRANO Working Papers 2003s-11, CIRANO.
     • Marcel Rindisbacher & Jérôme Detemple & René Garcia, 2004. "Asymptotic Properties of Monte Carlo Estimators of Diffusion Processes," Econometric Society 2004 North American Winter Meetings 483, Econometric Society.
105. Mijeong Kim & Yanyuan Ma, 2012. "The efficiency of the second-order nonlinear least squares estimator and its extension," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 64(4), pages 751-764, August.
106. Dennis Kristensen, 2009. "Semiparametric Modelling and Estimation: A Selective Overview," CREATES Research Papers 2009-44, Department of Economics and Business Economics, Aarhus University.
107. 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).
108. Christopher D. Walker, 2023. "Parametrization, Prior Independence, and the Semiparametric Bernstein-von Mises Theorem for the Partially Linear Model," Papers 2306.03816, arXiv.org, revised Feb 2024.
109. Long, Wei & Ouyang, Min & Shang, Ying, 2013. "Efficient estimation of partially linear varying coefficient models," Economics Letters, Elsevier, vol. 121(1), pages 79-81.