Nonparametric estimation in random coefficients binary choice models

Citations

Cited by:

1. Frédérique Fève & Jean-Pierre Florens, 2010. "The practice of non-parametric estimation by solving inverse problems: the example of transformation models," Econometrics Journal, Royal Economic Society, vol. 13(3), pages 1-27, October.
   • Fève, Frédérique & Florens, Jean-Pierre, 2009. "The Practice of Non Parametric Estimation by Solving Inverse Problems: The Example of Transformation Models," TSE Working Papers 10-169, Toulouse School of Economics (TSE).
   • Fève, Frédérique & Florens, Jean-Pierre, 2009. "The Practice of Non Parametric Estimation by Solving Inverse Problems: The Example of Transformation Models," IDEI Working Papers 615, Institut d'Économie Industrielle (IDEI), Toulouse.
2. Zhan Gao & M. Hashem Pesaran, 2023. "Identification and estimation of categorical random coefficient models," Empirical Economics, Springer, vol. 64(6), pages 2543-2588, June.
   • Gao, Z. & Pesaran, M. H., 2022. "Identification and Estimation of Categorical Random Coeficient Models," Cambridge Working Papers in Economics 2228, Faculty of Economics, University of Cambridge.
   • Zhan Gao & M. Hashem Pesaran, 2023. "Identification and Estimation of Categorical Random Coefficient Models," Papers 2302.14380, arXiv.org.
   • Zhan Gao & M. Hashem Pesaran, 2022. "Identification and Estimation of Categorical Random Coefficient Models," CESifo Working Paper Series 9714, CESifo.
3. Eric Gautier & Stefan Soderlein, 2011. "Estimating the Distribution of Treatment Effects," Working Papers 2011-25, Center for Research in Economics and Statistics.
4. Kasy, Maximilian, "undated". "Instrumental variables with unrestricted heterogeneity and continuous treatment - DON'T CITE! SEE ERRATUM BELOW," Working Paper 33257, Harvard University OpenScholar.
5. Klein, Tobias J., 2010. "Heterogeneous treatment effects: Instrumental variables without monotonicity?," Journal of Econometrics, Elsevier, vol. 155(2), pages 99-116, April.
   • Klein, Tobias J., 2007. "Heterogeneous Treatment Effects: Instrumental Variables without Monotonicity?," IZA Discussion Papers 2738, Institute of Labor Economics (IZA).
   • Klein, T.J., 2010. "Heterogeneous treatment effects : Instrumental variables without monotonicity?," Other publications TiSEM 0ec85b01-ab6a-4c2a-9e23-1, Tilburg University, School of Economics and Management.
   • Klein, T.J., 2008. "Heterogeneous Treatment Effects : Instrumental Variables Without Monotonicity?," Other publications TiSEM e015611a-6b97-4cd5-8dc8-7, Tilburg University, School of Economics and Management.
   • Klein, T.J., 2008. "Heterogeneous Treatment Effects : Instrumental Variables Without Monotonicity?," Discussion Paper 2008-45, Tilburg University, Center for Economic Research.
6. Antonio Merlo & Áureo de Paula, 2017. "Identification and Estimation of Preference Distributions When Voters Are Ideological," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 84(3), pages 1238-1263.
   • Antonio Merlo & Aureo de Paula, 2010. "Identification and Estimation of Preference Distributions When Voters Are Ideological," PIER Working Paper Archive 11-001, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
   • Antonio Merlo & Áureo de Paula, 2013. "Identification and estimation of preference distributions when voters are ideological," CeMMAP working papers CWP51/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
   • Merlo, Antonio & de Paula, Aureo, 2015. "Identification and Estimation of Preference Distributions When Voters Are Ideological," CEPR Discussion Papers 10821, C.E.P.R. Discussion Papers.
   • Antonio Merlo & Áureo de Paula, 2015. "Identification and estimation of preference distributions when voters are ideological," CeMMAP working papers CWP50/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
   • Antonio Merlo & Áureo de Paula, 2015. "Identification and estimation of preference distributions when voters are ideological," CeMMAP working papers 50/15, Institute for Fiscal Studies.
   • Antonio Merlo & Áureo de Paula, 2013. "Identification and estimation of preference distributions when voters are ideological," CeMMAP working papers 51/13, Institute for Fiscal Studies.
   • Merlo, Antonio & de Paula, Aureo, 2015. "Identification and Estimation of Preference Distributions When Voters Are Ideological," Working Papers 15-007, Rice University, Department of Economics.
7. Fabian Dunker & Stefan Hoderlein & Hiroaki Kaido, 2017. "Nonparametric identification of random coefficients in endogenous and heterogeneous aggregate demand models," CeMMAP working papers 11/17, Institute for Fiscal Studies.
   • Fabian Dunker & Stefan Hoderlein & Hiroaki Kaido, 2022. "Nonparametric Identification of Random Coefficients in Endogenous and Heterogeneous Aggregate Demand Models," Papers 2201.06140, arXiv.org.
   • Fabian Dunker & Stefan Hoderlein & Hiroaki Kaido, 2017. "Nonparametric identification of random coefficients in endogenous and heterogeneous aggregate demand models," CeMMAP working papers CWP11/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
8. Stefano Lombardi & Gerard J. van den Berg & Johan Vikström, 2024. "Empirical Monte Carlo evidence on estimation of timing-of-events models," Econometric Reviews, Taylor & Francis Journals, vol. 44(1), pages 90-118, September.
   • Lombardi, Stefano & van den Berg, Gerard J. & Vikström, Johan, 2020. "Empirical Monte Carlo evidence on estimation of Timing-of-Events models," Working Paper Series 2020:26, IFAU - Institute for Evaluation of Labour Market and Education Policy, revised 05 Jan 2021.
   • Lombardi, Stefano & van den Berg, Gerard J. & Vikström, Johan, 2021. "Empirical Monte Carlo Evidence on Estimation of Timing-of-Events Models," IZA Discussion Papers 14015, Institute of Labor Economics (IZA).
9. Roy Allen & John Rehbeck, 2020. "Identification of Random Coefficient Latent Utility Models," Papers 2003.00276, arXiv.org.
10. Steven T. Berry & Philip A. Haile, 2014. "Identification in Differentiated Products Markets Using Market Level Data," Econometrica, Econometric Society, vol. 82, pages 1749-1797, September.
    • Steven T. Berry & Philip A. Haile, 2014. "Identification in Differentiated Products Markets Using Market Level Data," Econometrica, Econometric Society, vol. 82(5), pages 1749-1797, September.
    • Steven T. Berry & Philip Haile, 2010. "Identification in Differentiated Products Markets Using Market Level Data," Cowles Foundation Discussion Papers 1744R, Cowles Foundation for Research in Economics, Yale University, revised May 2012.
    • Steven T. Berry & Philip A. Haile, 2010. "Identification in Differentiated Products Markets Using Market Level Data," NBER Working Papers 15641, National Bureau of Economic Research, Inc.
    • Steven T. Berry & Philip Haile, 2010. "Identification in Differentiated Products Markets Using Market Level Data," Cowles Foundation Discussion Papers 1744, Cowles Foundation for Research in Economics, Yale University, revised Mar 2010.
11. Hoderlein, Stefan & Nesheim, Lars & Simoni, Anna, 2017. "Semiparametric Estimation Of Random Coefficients In Structural Economic Models," Econometric Theory, Cambridge University Press, vol. 33(6), pages 1265-1305, December.
    • Stefan Hoderlein & Lars Nesheim & Anna Simoni, 2012. "Semiparametric estimation of random coefficients in structural economic models," CeMMAP working papers 09/12, Institute for Fiscal Studies.
    • Stefan Hoderlein & Lars Nesheim & Anna Simoni, 2012. "Semiparametric estimation of random coefficients in structural economic models," CeMMAP working papers CWP09/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    • Stefan Hoderlein & Lars Nesheim & Anna Simoni, 2017. "Semiparametric Estimation Of Random Coefficients In Structural Economic Models," Post-Print hal-03089886, HAL.
    • Stefan Hoderlein & Lars Nesheim & Anna Simoni, 2015. "Semiparametric Estimation of Random Coefficients in Structural Economic Models," Boston College Working Papers in Economics 895, Boston College Department of Economics, revised 01 Feb 2016.
12. Fabian Dunker & Stefan Hoderlein & Hiroaki Kaido, 2014. "Nonparametric identification of endogenous and heterogeneous aggregate demand models: complements, bundles and the market level," CeMMAP working papers 23/14, Institute for Fiscal Studies.
    • Dunker, Fabian & Hoderlein, Stefan & Kaido, Hiroaki, 2014. "Nonparametric Identification of Endogenous and Heterogeneous Aggregate Demand Models: Complements, Bundles and the Market Level," Economics Series 307, Institute for Advanced Studies.
    • Fabian Dunker & Stefan Hoderlein & Hiroaki Kaido, 2014. "Nonparametric Identification of Endogenous and Heterogeneous Aggregate Demand Models: Complements, Bundles and the Market Level," Boston University - Department of Economics - Working Papers Series 2014-005, Boston University - Department of Economics.
    • Fabian Dunker & Stefan Hoderlein & Hiroaki Kaido, 2015. "Nonparametric identification of endogenous and heterogeneous aggregate demand models: complements, bundles and the market level," CeMMAP working papers CWP51/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    • Fabian Dunker & Stefan Hoderlein & Hiroaki Kaido, 2014. "Nonparametric identification of endogenous and heterogeneous aggregate demand models: complements, bundles and the market level," CeMMAP working papers CWP23/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    • Fabian Dunker & Stefan Hoderlein & Hiroaki Kaido, 2015. "Nonparametric identification of endogenous and heterogeneous aggregate demand models: complements, bundles and the market level," CeMMAP working papers 51/15, Institute for Fiscal Studies.
13. Browning, Martin & Carro, Jesus M., 2014. "Dynamic binary outcome models with maximal heterogeneity," Journal of Econometrics, Elsevier, vol. 178(2), pages 805-823.
    • Martin Browning & Jesus M. Carro, 2007. "Dynamic Binary Outcome Models with Maximal Heterogeneity," CAM Working Papers 2009-08, University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics, revised Feb 2009.
    • Martin Browning & Jesus M. Carro, 2009. "Dynamic binary outcome models with maximal heterogeneity," Economics Series Working Papers 426, University of Oxford, Department of Economics.
    • Browning, Martin, 2009. "Dynamic binary outcome models with maximal heterogeneity," UC3M Working papers. Economics we091710, Universidad Carlos III de Madrid. Departamento de Economía.
14. Florens, Jean-Pierre & Simoni, Anna, 2016. "Regularizing Priors For Linear Inverse Problems," Econometric Theory, Cambridge University Press, vol. 32(1), pages 71-121, February.
    • Florens, Jean-Pierre & Simoni, Anna, 2010. "Regularizing priors for linear inverse problems," TSE Working Papers 10-175, Toulouse School of Economics (TSE).
    • Florens, Jean-Pierre & Simoni, Anna, 2013. "Regularizing Priors for Linear Inverse Problems," IDEI Working Papers 767, Institut d'Économie Industrielle (IDEI), Toulouse.
    • Anna Simoni & Jean-Pierre Florens, 2013. "Regularizing Priors for Linear Inverse Problems," THEMA Working Papers 2013-32, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    • Jean-Pierre Florens & Anna Simoni, 2013. "Regularizing Priors for Linear Inverse Problems," Working Papers hal-00873180, HAL.
    • Jean-Pierre Florens & Anna Simoni, 2016. "Regularizing Priors For Linear Inverse Problems," Post-Print hal-03089887, HAL.
    • Florens, Jean-Pierre & Simoni, Anna, 2010. "Regularizing priors for linear inverse problems," IDEI Working Papers 621, Institut d'Économie Industrielle (IDEI), Toulouse.
    • Florens, Jean-Pierre & Simoni, Anna, 2013. "Regularizing Priors for Linear Inverse Problems," TSE Working Papers 13-384, Toulouse School of Economics (TSE).
15. Wang, Ao, 2020. "Identifying the Distribution of Random Coefficients in BLP Demand Models Using One Single Variation in Product Characteristics," The Warwick Economics Research Paper Series (TWERPS) 1304, University of Warwick, Department of Economics.
16. Éric Gautier, 2021. "Relaxing Monotonicity in Endogenous Selection Models and Application to Surveys," Post-Print hal-03306234, HAL.
17. Babii, Andrii, 2020. "Honest Confidence Sets In Nonparametric Iv Regression And Other Ill-Posed Models," Econometric Theory, Cambridge University Press, vol. 36(4), pages 658-706, August.
    • Andrii Babii, 2016. "Honest Confidence Sets in Nonparametric IV Regression and Other Ill-Posed Models," Papers 1611.03015, arXiv.org, revised Dec 2020.
    • Babii, Andrii, 2017. "Honest confidence sets in nonparametric IV regression and other ill-posed models," TSE Working Papers 17-803, Toulouse School of Economics (TSE).
18. Juan Carlos Escanciano & Wei Li, 2013. "On the identification of structural linear functionals," CeMMAP working papers CWP48/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    • Juan Carlos Escanciano & Wei Li, 2013. "On the identification of structural linear functionals," CeMMAP working papers 48/13, Institute for Fiscal Studies.
19. Amit Gandhi & Jeremy T. Fox, 2009. "Identifying Heterogeneity in Economic Choice and Selection Models Using Mixtures," 2009 Meeting Papers 165, Society for Economic Dynamics.
20. Tsionas, Mike, 2012. "Simple techniques for likelihood analysis of univariate and multivariate stable distributions: with extensions to multivariate stochastic volatility and dynamic factor models," MPRA Paper 40966, University Library of Munich, Germany, revised 20 Aug 2012.
21. Joel L. Horowitz, 2013. "Ill-posed inverse problems in economics," CeMMAP working papers CWP37/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
22. Steven T. Berry & Philip A. Haile, 2009. "Nonparametric Identification of Multinomial Choice Demand Models with Heterogeneous Consumers," NBER Working Papers 15276, National Bureau of Economic Research, Inc.
    • Steven T. Berry & Philip A. Haile, 2009. "Nonparametric Identification of Multinomial Choice Demand Models with Heterogeneous Consumers," Cowles Foundation Discussion Papers 1718, Cowles Foundation for Research in Economics, Yale University, revised Mar 2010.
23. Hoderlein, Stefan & Sherman, Robert, 2015. "Identification and estimation in a correlated random coefficients binary response model," Journal of Econometrics, Elsevier, vol. 188(1), pages 135-149.
    • Stefan Hoderlein & Robert Sherman, 2012. "Identification And Estimation In A Correlated Random Coefficients Binary Response Model," Boston College Working Papers in Economics 837, Boston College Department of Economics.
    • Stefan Hoderlein & Robert Sherman, 2012. "Identification and estimation in a correlated random coefficients binary response model," CeMMAP working papers CWP42/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    • Stefan Hoderlein & Robert Sherman, 2012. "Identification and estimation in a correlated random coefficients binary response model," CeMMAP working papers 42/12, Institute for Fiscal Studies.
24. Andrew Chesher & Adam M. Rosen, 2014. "An instrumental variable random‐coefficients model for binary outcomes," Econometrics Journal, Royal Economic Society, vol. 17(2), pages 1-19, June.
    • Andrew Chesher & Adam Rosen, 2012. "An instrumental variable random coefficients model for binary outcomes," CeMMAP working papers 34/12, Institute for Fiscal Studies.
    • Andrew Chesher & Adam Rosen, 2012. "An instrumental variable random coefficients model for binary outcomes," CeMMAP working papers CWP34/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
25. Jeremy T. Fox & David H. Hsu & Chenyu Yang, 2012. "Unobserved Heterogeneity in Matching Games with an Application to Venture Capital," NBER Working Papers 18168, National Bureau of Economic Research, Inc.
26. 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.
27. Chernozhukov, Victor & Fernández-Val, Iván & Newey, Whitney K., 2019. "Nonseparable multinomial choice models in cross-section and panel data," Journal of Econometrics, Elsevier, vol. 211(1), pages 104-116.
    • Victor Chernozhukov & Iv'an Fern'andez-Val & Whitney Newey, 2017. "Nonseparable Multinomial Choice Models in Cross-Section and Panel Data," Papers 1706.08418, arXiv.org, revised May 2018.
    • Victor Chernozhukov & Ivan Fernandez-Val & Whitney K. Newey, 2017. "Nonseparable multinomial choice models in cross-section and panel data," CeMMAP working papers 33/17, Institute for Fiscal Studies.
    • Victor Chernozhukov & Ivan Fernandez-Val & Whitney K. Newey, 2017. "Nonseparable multinomial choice models in cross-section and panel data," CeMMAP working papers CWP33/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
28. Christoph Breunig & Stefan Hoderlein, 2018. "Specification testing in random coefficient models," Quantitative Economics, Econometric Society, vol. 9(3), pages 1371-1417, November.
    • Breunig, Christoph & Hoderlein, Stefan, 2016. "Specification testing in random coefficient models," SFB 649 Discussion Papers 2015-053, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    • Breunig, Christoph & Hoderlein, Stefan, 2018. "Specification Testing in Random Coefficient Models," Rationality and Competition Discussion Paper Series 77, CRC TRR 190 Rationality and Competition.
29. Eric Gautier & Erwann Le Pennec, 2011. "Adaptive Estimation in the Nonparametric Random Coefficients Binary Choice Model by Needlet Thresholding," Working Papers 2011-20, Center for Research in Economics and Statistics.
    • Gautier, Eric & Le Pennec, Erwan, 2016. "Adaptive estimation in the nonparametric random coefficients binary choice model by needlet thresholding," TSE Working Papers 16-713, Toulouse School of Economics (TSE).
    • Eric Gautier & Erwan Le Pennec, 2017. "Adaptive estimation in the nonparametric random coefficients binary choice model by needlet thresholding," Working Papers inria-00601274, HAL.
30. Tadao Hoshino & Daichi Shimamoto & Yasuyuki Todo, 2020. "Accounting for Heterogeneity in Network Formation Behaviour: An Application to Vietnamese SMEs," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(5), pages 1042-1067, October.
    • HOSHINO Tadao & SHIMAMOTO Daichi & TODO Yasuyuki, 2017. "Accounting for Heterogeneity in Network Formation Behavior: An application to Vietnamese SMEs," Discussion papers 17023, Research Institute of Economy, Trade and Industry (RIETI).
31. Arthur Lewbel, 2019. "The Identification Zoo: Meanings of Identification in Econometrics," Journal of Economic Literature, American Economic Association, vol. 57(4), pages 835-903, December.
    • Arthur Lewbel, 2018. "The Identification Zoo - Meanings of Identification in Econometrics," Boston College Working Papers in Economics 957, Boston College Department of Economics, revised 14 Dec 2019.
32. Fabian Dunker & Konstantin Eckle & Katharina Proksch & Johannes Schmidt-Hieber, 2017. "Tests for qualitative features in the random coefficients model," Papers 1704.01066, arXiv.org, revised Mar 2018.
    • Fabian Dunker & Konstantin Eckle & Katharina Proksch & Johannes Schmidt-Hieber, 2017. "Tests for qualitative features in the random coefficients model," Courant Research Centre: Poverty, Equity and Growth - Discussion Papers 225, Courant Research Centre PEG.
33. Gu, Jiaying & Russell, Thomas M., 2023. "Partial identification in nonseparable binary response models with endogenous regressors," Journal of Econometrics, Elsevier, vol. 235(2), pages 528-562.
34. Fabian Dunker & Stefan Hoderlein & Hiroaki Kaido, 2023. "Nonparametric identification of random coefficients in aggregate demand models for differentiated products," The Econometrics Journal, Royal Economic Society, vol. 26(2), pages 279-306.
35. Hall, Peter & Yatchew, Adonis, 2010. "Nonparametric least squares estimation in derivative families," Journal of Econometrics, Elsevier, vol. 157(2), pages 362-374, August.
36. Arthur Lewbel & Krishna Pendakur, 2017. "Unobserved Preference Heterogeneity in Demand Using Generalized Random Coefficients," Journal of Political Economy, University of Chicago Press, vol. 125(4), pages 1100-1148.
    • Arthur Lewbel & Krishna Pendakur, 2012. "Unobserved Preference Heterogeneity in Demand Using Generalized Random Coefficients," Boston College Working Papers in Economics 791, Boston College Department of Economics, revised 01 Jul 2013.
    • Arthur Lewbel & Krishna Pendakur, 2015. "Unobserved Preference Heterogeneity in Demand Using Generalized Random Coefficients," Discussion Papers dp16-03, Department of Economics, Simon Fraser University.
    • Arthur Lewbel & Krishna Pendakur, 2015. "Unobserved Preference Heterogeneity in Demand Using Generalized Random Coefficients," Discussion Papers dp15-12, Department of Economics, Simon Fraser University.
37. Jeremy T. Fox & Amit Gandhi, 2009. "Identifying Heterogeneity in Economic Choice Models," NBER Working Papers 15147, National Bureau of Economic Research, Inc.
38. Fox, Jeremy T. & Kim, Kyoo il & Ryan, Stephen P. & Bajari, Patrick, 2012. "The random coefficients logit model is identified," Journal of Econometrics, Elsevier, vol. 166(2), pages 204-212.
    • Patrick Bajari & Jeremy Fox & Kyoo il Kim & Stephen P. Ryan, 2009. "The Random Coefficients Logit Model Is Identified," NBER Working Papers 14934, National Bureau of Economic Research, Inc.
39. Giovanni Compiani & Yuichi Kitamura, 2016. "Using mixtures in econometric models: a brief review and some new results," Econometrics Journal, Royal Economic Society, vol. 19(3), pages 95-127, October.
40. Arthur Lewbel, 2012. "An Overview of the Special Regressor Method," Boston College Working Papers in Economics 810, Boston College Department of Economics.
41. Gautier, Eric & Hoderlein, Stefan, 2011. "A triangular treatment effect model with random coefficients in the selection equation," TSE Working Papers 15-598, Toulouse School of Economics (TSE), revised 25 Aug 2015.
    • Eric Gautier & Stefan Hoderlein, 2012. "A triangular treatment effect model with random coefficients in the selection equation," CeMMAP working papers CWP39/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    • Eric Gautier & Stefan Hoderlein, 2012. "A triangular treatment effect model with random coefficients in the selection equation," CeMMAP working papers 39/12, Institute for Fiscal Studies.
    • Eric Gautier & Stefan Hoderlein, 2012. "A Triangular Treatment Effect Model With Random Coefficients In The Selection Equation," Boston College Working Papers in Economics 838, Boston College Department of Economics, revised 15 Sep 2015.
42. Jackson Bunting, 2022. "Continuous permanent unobserved heterogeneity in dynamic discrete choice models," Papers 2202.03960, arXiv.org, revised Feb 2024.
43. Jiaying Gu & Roger Koenker, 2018. "Nonparametric maximum likelihood methods for binary response models with random coefficients," Papers 1811.03329, arXiv.org, revised Jan 2020.
44. Carrasco, Marine & Florens, Jean-Pierre, 2011. "A Spectral Method For Deconvolving A Density," Econometric Theory, Cambridge University Press, vol. 27(3), pages 546-581, June.
    • Carrasco, Marine & Florens, Jean-Pierre, 2002. "Spectral Method for Deconvolving a Density," IDEI Working Papers 138, Institut d'Économie Industrielle (IDEI), Toulouse, revised 2009.
45. Santiago Pereda-Fernández, 2021. "Copula-Based Random Effects Models for Clustered Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(2), pages 575-588, March.
    • Santiago Pereda Fernández, 2016. "Copula-based random effects models for clustered data," Temi di discussione (Economic working papers) 1092, Bank of Italy, Economic Research and International Relations Area.
46. Joel L. Horowitz, 2013. "Ill-posed inverse problems in economics," CeMMAP working papers 37/13, Institute for Fiscal Studies.
47. Gao, Yichen & Li, Cong & Liang, Zhongwen, 2015. "Binary response correlated random coefficient panel data models," Journal of Econometrics, Elsevier, vol. 188(2), pages 421-434.
48. Fabian Dunker & Stefan Hoderlein & Hiroaki Kaido, 2013. "Random Coefficients in Static Games of Complete Information," Boston College Working Papers in Economics 835, Boston College Department of Economics.
    • Fabian Dunker & Stefan Hoderlein & Hiroaki Kaido, 2013. "Random coefficients in static games of complete information," CeMMAP working papers CWP12/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    • Fabian Dunker & Stefan Hoderlein & Hiroaki Kaido, 2013. "Random coefficients in static games of complete information," CeMMAP working papers 12/13, Institute for Fiscal Studies.
49. Xiyuan Ren & Joseph Y. J. Chow & Prateek Bansal, 2023. "Estimating a k-modal nonparametric mixed logit model with market-level data," Papers 2309.13159, arXiv.org, revised Aug 2024.
50. Manuel Arellano & Stéphane Bonhomme, 2023. "Recovering Latent Variables by Matching," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 118(541), pages 693-706, January.
    • Manuel Arellano & Stephane Bonhomme, 2019. "Recovering Latent Variables by Matching," Papers 1912.13081, arXiv.org.
    • Manuel Arellano & Stéphane Bonhomme, 2020. "Recovering Latent Variables by Matching," CeMMAP working papers CWP2/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    • Manuel Arellano & Stéphane Bonhomme, 2019. "Recovering Latent Variables by Matching," Working Papers wp2019_1914, CEMFI.
51. Jeremy T. Fox, 2021. "A Note on Nonparametric Identification of Distributions of Random Coefficients in Multinomial Choice Models," Annals of Economics and Statistics, GENES, issue 142, pages 305-310.
    • Jeremy T. Fox, 2017. "A Note on Nonparametric Identification of Distributions of Random Coefficients in Multinomial Choice Models," NBER Working Papers 23621, National Bureau of Economic Research, Inc.
52. 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.
53. Christophe Gaillac & Eric Gautier, 2021. "Nonparametric classes for identification in random coefficients models when regressors have limited variation," Working Papers hal-03231392, HAL.
    • Gaillac, Christophe & Gautier, Eric, 2021. "Non Parametric Classes for Identification in Random Coefficients Models when Regressors have Limited Variation," TSE Working Papers 21-1218, Toulouse School of Economics (TSE).
54. Patrick Bajari & Jeremy T. Fox & Kyoo il Kim & Stephen P. Ryan, 2009. "A Simple Nonparametric Estimator for the Distribution of Random Coefficients," NBER Working Papers 15210, National Bureau of Economic Research, Inc.
55. Christoph Breunig & Stefan Hoderlein, 2016. "Nonparametric Specification Testing in Random Parameter Models," Boston College Working Papers in Economics 897, Boston College Department of Economics.
56. Pierre‐André Chiappori & Bernard Salanié & François Salanié & Amit Gandhi, 2019. "From Aggregate Betting Data to Individual Risk Preferences," Econometrica, Econometric Society, vol. 87(1), pages 1-36, January.
    • Chiappori, Pierre-André & Gandhi, Amit & Salanié, Bernard & Salanié, François, 2012. "From Aggregate Betting Data to Individual Risk Preferences," TSE Working Papers 13-453, Toulouse School of Economics (TSE).
    • Pierre-Andre Chiappori & Bernard Salanie & Francois Salanie & Amit Gandhi, 2019. "From aggregate betting data to individual risk preferences," Post-Print hal-02121859, HAL.
    • Chiappori, Pierre-André & Gandhi, Amit & Salanié, Bernard & Salanié, François, 2012. "From Aggregate Betting Data to Individual Risk Preferences," IDEI Working Papers 810, Institut d'Économie Industrielle (IDEI), Toulouse.
57. Gautier, Eric & Gaillac, Christophe, 2019. "Adaptive estimation in the linear random coefficients model when regressors have limited variation," TSE Working Papers 19-1026, Toulouse School of Economics (TSE).
    • Christophe Gaillac & Eric Gautier, 2021. "Adaptive estimation in the linear random coefficients model when regressors have limited variation," Post-Print hal-03374805, HAL.
    • Christophe Gaillac & Eric Gautier, 2020. "Adaptive estimation in the linear random coefficients model when regressors have limited variation," Working Papers hal-02130472, HAL.
58. Matzkin, Rosa L., 2019. "Constructive identification in some nonseparable discrete choice models," Journal of Econometrics, Elsevier, vol. 211(1), pages 83-103.
59. Antonio Merlo & Aureo de Paula, 2010. "Identification and Estimation of Preference Distributions When Voters Are Ideological, Second Version," PIER Working Paper Archive 13-055, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 13 Oct 2013.
60. Wang, Ao, 2023. "Sieve BLP: A semi-nonparametric model of demand for differentiated products," Journal of Econometrics, Elsevier, vol. 235(2), pages 325-351.
61. 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.
62. Steven T. Berry & Philip A. Haile, 2009. "Identification of a Heterogeneous Generalized Regression Model with Group Effects," Cowles Foundation Discussion Papers 1732, Cowles Foundation for Research in Economics, Yale University.
63. Matzkin, Rosa L., 2012. "Identification in nonparametric limited dependent variable models with simultaneity and unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 166(1), pages 106-115.
64. Jiaying Gu & Thomas M. Russell, 2021. "Partial Identification in Nonseparable Binary Response Models with Endogenous Regressors," Papers 2101.01254, arXiv.org, revised Jul 2022.
65. Dunker, Fabian & Hoderlein, Stefan & Kaido, Hiroaki & Sherman, Robert, 2018. "Nonparametric identification of the distribution of random coefficients in binary response static games of complete information," Journal of Econometrics, Elsevier, vol. 206(1), pages 83-102.
66. Haikady N Nagaraja & Shane Sanders, 2020. "The aggregation paradox for statistical rankings and nonparametric tests," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-21, March.
67. Nail Kashaev, 2018. "Identification and estimation of multinomial choice models with latent special covariates," Papers 1811.05555, arXiv.org, revised Mar 2022.
    • Nail Kashaev, 2022. "Identification and Estimation of Multinomial Choice Models with Latent Special Covariates," University of Western Ontario, Departmental Research Report Series 20224, University of Western Ontario, Department of Economics.
68. Victor H. Aguiar & Nail Kashaev, 2019. "Identification and Estimation of Discrete Choice Models with Unobserved Choice Sets," Papers 1907.04853, arXiv.org, revised Jun 2021.
69. Junpei Komiyama & Hajime Shimao, 2018. "Cross Validation Based Model Selection via Generalized Method of Moments," Papers 1807.06993, arXiv.org.
70. repec:hum:wpaper:sfb649dp2015-053 is not listed on IDEAS
71. Jiaying Gu & Roger Koenker, 2018. "Nonparametric maximum likelihood methods for binary response models with random coefficients," CeMMAP working papers CWP65/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.