IDEAS home Printed from https://ideas.repec.org/r/ecm/emetrp/v80y2012i5p2105-2152.html
   My bibliography  Save this item

Identification and Estimation of Average Partial Effects in “Irregular” Correlated Random Coefficient Panel Data Models

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Hugo Freeman & Martin Weidner, 2021. "Low-rank approximations of nonseparable panel models," The Econometrics Journal, Royal Economic Society, vol. 24(2), pages 40-77.
  2. Jorge E. Galán, 2020. "The benefits are at the tail: uncovering the impact of macroprudential policy on growth-at-risk," Working Papers 2007, Banco de España.
  3. Pesaran, M. H. & Yang, L., 2023. "Trimmed Mean Group Estimation of Average Treatment Effects in Ultra Short T Panels under Correlated Heterogeneity," Cambridge Working Papers in Economics 2364, Faculty of Economics, University of Cambridge.
  4. Brantly Callaway & Tong Li, 2019. "Quantile treatment effects in difference in differences models with panel data," Quantitative Economics, Econometric Society, vol. 10(4), pages 1579-1618, November.
  5. Chernozhukov, Victor & Fernández-Val, Iván & Hoderlein, Stefan & Holzmann, Hajo & Newey, Whitney, 2015. "Nonparametric identification in panels using quantiles," Journal of Econometrics, Elsevier, vol. 188(2), pages 378-392.
  6. Jorge E. Galán & María Rodríguez Moreno, 2020. "At-risk measures and financial stability," Financial Stability Review, Banco de España, issue Autumn.
  7. Hoderlein, Stefan & Holzmann, Hajo & Meister, Alexander, 2017. "The triangular model with random coefficients," Journal of Econometrics, Elsevier, vol. 201(1), pages 144-169.
  8. 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.
  9. Ghanem, Dalia, 2017. "Testing identifying assumptions in nonseparable panel data models," Journal of Econometrics, Elsevier, vol. 197(2), pages 202-217.
  10. Xavier d'Haultfoeuille & Stefan Hoderlein & Yuya Sasaki, 2013. "Nonlinear difference-in-differences in repeated cross sections with continuous treatments," CeMMAP working papers 40/13, Institute for Fiscal Studies.
  11. Chen, Xiaohong & Liao, Zhipeng, 2014. "Sieve M inference on irregular parameters," Journal of Econometrics, Elsevier, vol. 182(1), pages 70-86.
  12. Okui, Ryo & Yanagi, Takahide, 2019. "Panel data analysis with heterogeneous dynamics," Journal of Econometrics, Elsevier, vol. 212(2), pages 451-475.
  13. 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.
  14. Khan, Shakeeb & Ponomareva, Maria & Tamer, Elie, 2016. "Identification of panel data models with endogenous censoring," Journal of Econometrics, Elsevier, vol. 194(1), pages 57-75.
  15. Dilek Uz & Steven Buck & David Sunding, 2022. "Fixed or mixed? Farmer‐level heterogeneity in response to changes in salinity," American Journal of Agricultural Economics, John Wiley & Sons, vol. 104(4), pages 1343-1363, August.
  16. 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.
  17. 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.
  18. Yingyao Hu & Ji‐Liang Shiu, 2018. "Identification and estimation of semi‐parametric censored dynamic panel data models of short time periods," Econometrics Journal, Royal Economic Society, vol. 21(1), pages 55-85, February.
  19. Dalia Ghanem & Pedro H. C. Sant'Anna & Kaspar Wüthrich, 2022. "Selection and Parallel Trends," CESifo Working Paper Series 9910, CESifo.
  20. 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.
  21. Patrick Kline & Raffaele Saggio & Mikkel Sølvsten, 2020. "Leave‐Out Estimation of Variance Components," Econometrica, Econometric Society, vol. 88(5), pages 1859-1898, September.
  22. Emmanouil Kitsios & Manasa Patnam, 2016. "Estimating Fiscal Multipliers with Correlated Heterogeneity," IMF Working Papers 2016/013, International Monetary Fund.
  23. 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.
  24. Louise Laage, 2020. "A Correlated Random Coefficient Panel Model with Time-Varying Endogeneity," Papers 2003.09367, arXiv.org, revised Nov 2022.
  25. Iv'an Fern'andez-Val & Hugo Freeman & Martin Weidner, 2020. "Low-Rank Approximations of Nonseparable Panel Models," Papers 2010.12439, arXiv.org, revised Mar 2021.
  26. 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.
  27. Jorge E. Galán & María Rodríguez Moreno, 2020. "At-risk measures and financial stability," Revista de Estabilidad Financiera, Banco de España, issue Autumn.
  28. Denis Chetverikov & Bradley Larsen & Christopher Palmer, 2016. "IV Quantile Regression for Group‐Level Treatments, With an Application to the Distributional Effects of Trade," Econometrica, Econometric Society, vol. 84, pages 809-833, March.
  29. 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.
  30. Hugo Padrón-Ávila & Raúl Hernández-Martín, 2019. "Preventing Overtourism by Identifying the Determinants of Tourists’ Choice of Attractions," Sustainability, MDPI, vol. 11(19), pages 1-17, September.
  31. 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.
  32. 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.
  33. Oliver Linton & Ji-Liang Shiu, 2018. "Semiparametric nonlinear panel data models with measurement error," CeMMAP working papers CWP09/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  34. Ben-Moshe, Dan, 2018. "Identification Of Joint Distributions In Dependent Factor Models," Econometric Theory, Cambridge University Press, vol. 34(1), pages 134-165, February.
  35. Cl'ement de Chaisemartin & Xavier D'Haultfoeuille & F'elix Pasquier & Gonzalo Vazquez-Bare, 2022. "Difference-in-Differences Estimators for Treatments Continuously Distributed at Every Period," Papers 2201.06898, arXiv.org, revised Dec 2023.
  36. 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.
  37. Juan Carlos Escanciano, 2020. "Irregular Identification of Structural Models with Nonparametric Unobserved Heterogeneity," Papers 2005.08611, arXiv.org.
  38. 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.
  39. Peter Hull, 2018. "Estimating Treatment Effects in Mover Designs," Papers 1804.06721, arXiv.org.
  40. Irene Botosaru & Chris Muris, 2017. "Binarization for panel models with fixed effects," CeMMAP working papers 31/17, Institute for Fiscal Studies.
  41. Vasilis Sarafidis & Tom Wansbeek, 2020. "Celebrating 40 Years of Panel Data Analysis: Past, Present and Future," Monash Econometrics and Business Statistics Working Papers 6/20, Monash University, Department of Econometrics and Business Statistics.
  42. Cavit Pakel & Martin Weidner, 2023. "Bounds on Average Effects in Discrete Choice Panel Data Models," Papers 2309.09299, arXiv.org, revised Dec 2023.
  43. 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.
  44. Jorge E. Galán & María Rodríguez Moreno, 2020. "At-risk measures and financial stability," Revista de Estabilidad Financiera, Banco de España, issue NOV.
  45. 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.
  46. 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.
  47. Ming Li, 2021. "A Time-Varying Endogenous Random Coefficient Model with an Application to Production Functions," Papers 2110.00982, arXiv.org.
  48. Kasy, Maximilian, 2022. "Who wins, who loses? Identification of conditional causal effects, and the welfare impact of changing wages," Journal of Econometrics, Elsevier, vol. 226(1), pages 155-170.
  49. 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.
  50. Shosei Sakaguchi, 2017. "Estimation of Average Treatment Effects Using Panel Data when Treatment Effects Are Heterogeneous by Unobserved Fixed Effects," KIER Working Papers 970, Kyoto University, Institute of Economic Research.
  51. Dmitry Arkhangelsky & Guido Imbens, 2023. "Causal Models for Longitudinal and Panel Data: A Survey," Papers 2311.15458, arXiv.org, revised Mar 2024.
  52. 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.
  53. Cl'ement de Chaisemartin & Ziteng Lei, 2021. "More Robust Estimators for Instrumental-Variable Panel Designs, With An Application to the Effect of Imports from China on US Employment," Papers 2103.06437, arXiv.org, revised Sep 2023.
  54. Ishihara, Takuya, 2020. "Identification and estimation of time-varying nonseparable panel data models without stayers," Journal of Econometrics, Elsevier, vol. 215(1), pages 184-208.
  55. D’Haultfœuille, Xavier & Hoderlein, Stefan & Sasaki, Yuya, 2023. "Nonparametric difference-in-differences in repeated cross-sections with continuous treatments," Journal of Econometrics, Elsevier, vol. 234(2), pages 664-690.
  56. 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.
  57. Takuya Ishihara, 2020. "Panel Data Quantile Regression for Treatment Effect Models," Papers 2001.04324, arXiv.org, revised Nov 2021.
  58. 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.
  59. Yuya Sasaki & Takuya Ura, 2021. "Slow Movers in Panel Data," Papers 2110.12041, arXiv.org.
  60. Sungwon Lee, 2020. "Nonparametric Identification and Estimation of Panel Quantile Models with Sample Selection," Working Papers 2012, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
  61. Escanciano, Juan Carlos, 2023. "Irregular identification of structural models with nonparametric unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 234(1), pages 106-127.
  62. Irene Botosaru & Chris Muris, 2022. "Identification of time-varying counterfactual parameters in nonlinear panel models," Papers 2212.09193, arXiv.org, revised Nov 2023.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.