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How informative is the initial condition in the dynamic panel model with fixed effects?

Citations

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Cited by:

  1. Binder, Michael & Hsiao, Cheng & Pesaran, M. Hashem, 2005. "Estimation And Inference In Short Panel Vector Autoregressions With Unit Roots And Cointegration," Econometric Theory, Cambridge University Press, vol. 21(4), pages 795-837, August.
  2. Mavroeidis, Sophocles & Sasaki, Yuya & Welch, Ivo, 2015. "Estimation of heterogeneous autoregressive parameters with short panel data," Journal of Econometrics, Elsevier, vol. 188(1), pages 219-235.
  3. In Choi & Sanghyun Jung, 2021. "Cross-sectional quasi-maximum likelihood and bias-corrected pooled least squares estimators for short dynamic panels," Empirical Economics, Springer, vol. 60(1), pages 177-203, January.
  4. Chirok Han & Hyelim Lee, 2013. "Dependence Of Economic Growth On Co2 Emissions," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 38(1), pages 47-57, March.
  5. Barbosa, José Diogo & Moreira, Marcelo J., 2021. "Likelihood inference and the role of initial conditions for the dynamic panel data model," Journal of Econometrics, Elsevier, vol. 221(1), pages 160-179.
  6. Gareth M. Thomas & Seung C. Ahn, 2004. "Likelihood Based Inference for amic Panel Data Models," Econometric Society 2004 Far Eastern Meetings 669, Econometric Society.
  7. Jinyong Hahn & Jerry Hausman & Guido Kuersteiner, 2005. "Bias Corrected Instrumental Variables Estimation for Dynamic Panel Models with Fixed E¤ects," Boston University - Department of Economics - Working Papers Series WP2005-024, Boston University - Department of Economics.
  8. Jerry A. Hausman & Maxim L. Pinkovskiy, 2017. "Estimating dynamic panel models: backing out the Nickell Bias," Staff Reports 824, Federal Reserve Bank of New York.
  9. 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.
  10. Hahn, Jinyong & Hausman, Jerry & Kuersteiner, Guido, 2007. "Long difference instrumental variables estimation for dynamic panel models with fixed effects," Journal of Econometrics, Elsevier, vol. 140(2), pages 574-617, October.
  11. Richiardi Matteo & Poggi Ambra, 2012. "Imputing Individual Effects in Dynamic Microsimulation Models. An application of the Rank Method," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201213, University of Turin.
  12. Giorgio Calzolari & Laura Magazzini, 2014. "Improving GMM efficiency in dynamic models for panel data with mean stationarity," Working Papers 12/2014, University of Verona, Department of Economics.
  13. Majid M. Al-Sadoon & Tong Li & M. Hashem Pesaran, 2017. "Exponential class of dynamic binary choice panel data models with fixed effects," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 898-927, October.
  14. Burak Dindaroglu, 2010. "Intra-Industry Knowledge Spillovers and Scientific Labor Mobility," Discussion Papers 10-01, University at Albany, SUNY, Department of Economics.
  15. Badi H. Baltagi & Chihwa Kao, 2000. "Nonstationary Panels, Cointegration in Panels and Dynamic Panels: A Survey," Center for Policy Research Working Papers 16, Center for Policy Research, Maxwell School, Syracuse University.
  16. Sasaki, Yuya, 2015. "Heterogeneity and selection in dynamic panel data," Journal of Econometrics, Elsevier, vol. 188(1), pages 236-249.
  17. Michael Funke & Ralf Ruhwedel, 2002. "Export variety and export performance: Empirical evidence for the OECD countries," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 138(1), pages 97-114, March.
  18. Sasaki, Yuya & Xin, Yi, 2017. "Unequal spacing in dynamic panel data: Identification and estimation," Journal of Econometrics, Elsevier, vol. 196(2), pages 320-330.
  19. Hsiao, Cheng & Hashem Pesaran, M. & Kamil Tahmiscioglu, A., 2002. "Maximum likelihood estimation of fixed effects dynamic panel data models covering short time periods," Journal of Econometrics, Elsevier, vol. 109(1), pages 107-150, July.
  20. Jeffrey M. Wooldridge, 2005. "Simple solutions to the initial conditions problem in dynamic, nonlinear panel data models with unobserved heterogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(1), pages 39-54, January.
  21. Elhorst, J. Paul, 2003. "Unconditional maximum likelihood estimation of dynamic models for spatial panels," Research Report 03C27, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
  22. Ambra Poggi, 2007. "Does persistence of social exclusion exist in Spain?," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 5(1), pages 53-72, April.
  23. Ambra Poggi & Matteo Richiardi, 2012. "Accounting for Unobserved Heterogeneity in Discrete-time, Discrete-choice Dynamic Microsimulation Models. An application to Labor Supply and Household Formation in Italy," LABORatorio R. Revelli Working Papers Series 117, LABORatorio R. Revelli, Centre for Employment Studies.
  24. Martin A. Carree, 2002. "Nearly Unbiased Estimation in Dynamic Panel Data Models with Exogenous Variables," Tinbergen Institute Discussion Papers 02-007/2, Tinbergen Institute.
  25. Fajnzylber, Pablo & Maloney, William F., 2001. "How comparable are labor demand elasticities across countries?," Policy Research Working Paper Series 2658, The World Bank.
  26. Matteo Richiardi & Ambra Poggi, 2014. "Imputing Individual Effects in Dynamic Microsimulation Models. An application to household formation and labour market participation in Italy," International Journal of Microsimulation, International Microsimulation Association, vol. 7(2), pages 3-39.
  27. Khalaf, Lynda & Saunders, Charles J., 2020. "Monte Carlo two-stage indirect inference (2SIF) for autoregressive panels," Journal of Econometrics, Elsevier, vol. 218(2), pages 419-434.
  28. Giorgio Calzolari & Laura Magazzini, 2013. "A powerful test of mean stationarity in dynamic models for panel data: Monte Carlo evidence," Working Papers 14/2013, University of Verona, Department of Economics.
  29. Arvid Raknerud, 2002. "Identification, Estimation and Testing in Panel Data Models with Attrition: The Role of the Missing at Random Assumption," Discussion Papers 330, Statistics Norway, Research Department.
  30. Tong Li & Xiaoyong Zheng, 2008. "Semiparametric Bayesian inference for dynamic Tobit panel data models with unobserved heterogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(6), pages 699-728.
  31. Zongwu Cai & Linna Chen & Ying Fang, 2015. "Semiparametric Estimation of Partially Varying-Coefficient Dynamic Panel Data Models," Econometric Reviews, Taylor & Francis Journals, vol. 34(6-10), pages 695-719, December.
  32. Jerry Hausman & Maxim L. Pinkovskiy, 2017. "Estimating dynamic panel models: backing out the Nickell Bias," CeMMAP working papers 53/17, Institute for Fiscal Studies.
  33. Maria Elena Bontempi & Jan Ditzen, 2023. "GMM-lev estimation and individual heterogeneity: Monte Carlo evidence and empirical applications," Papers 2312.00399, arXiv.org, revised Dec 2023.
  34. repec:dgr:rugsom:03c27 is not listed on IDEAS
  35. Jerry Hausman & Maxim L. Pinkovskiy, 2017. "Estimating dynamic panel models: backing out the Nickell Bias," CeMMAP working papers CWP53/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  36. In Choi, 2016. "Cross-sectional maximum likelihood and bias-corrected pooled least squares estimators for dynamic panels with short T," Working Papers 1610, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
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