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Panel data models with multiple time-varying individual effects

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  • Ahn, Seung C.
  • Lee, Young H.
  • Schmidt, Peter

Abstract

This paper considers a panel data model with time-varying individual effects. The data are assumed to contain a large number of cross-sectional units repeatedly observed over a fixed number of time periods. The model has a feature of the fixed-effects model in that the effects are assumed to be correlated with the regressors. The unobservable individual effects are assumed to have a factor structure. For consistent estimation of the model, it is important to estimate the true number of individual effects. We propose a generalized methods of moments procedure by which both the number of individual effects and the regression coefficients can be consistently estimated. Some important identification issues are also discussed. Our simulation results indicate that the proposed methods produce reliable estimates.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 174 (2013)
Issue (Month): 1 ()
Pages: 1-14

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Handle: RePEc:eee:econom:v:174:y:2013:i:1:p:1-14

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Web page: http://www.elsevier.com/locate/jeconom

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Keywords: Panel data; Time-varying individual effects; Factor models;

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  1. Campbell, John Y., 1987. "Stock returns and the term structure," Journal of Financial Economics, Elsevier, vol. 18(2), pages 373-399, June.
  2. Satchachai, Panutat & Schmidt, Peter, 2008. "GMM with more moment conditions than observations," Economics Letters, Elsevier, vol. 99(2), pages 252-255, May.
  3. Chamberlain, Gary, 1992. "Efficiency Bounds for Semiparametric Regression," Econometrica, Econometric Society, vol. 60(3), pages 567-96, May.
  4. Cornwell, Christopher & Rupert, Peter, 1988. "Efficient Estimation with Panel Data: An Empirical Comparison of Instrumental Variables Estimators," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 3(2), pages 149-55, April.
  5. Donald W.K. Andrews, 2004. "Cross-section Regression with Common Shocks," Yale School of Management Working Papers ysm401, Yale School of Management.
  6. Pischke, Jörn-Steffen, 1991. "Individual income, incomplete information, and aggregate consumption," ZEW Discussion Papers 91-07, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
  7. Sumru Altug & Robert Miller, . "Household Choices in Equilibrium," University of Chicago - Population Research Center 87-8, Chicago - Population Research Center.
  8. Fuller, Wayne A. & Battese, George E., 1974. "Estimation of linear models with crossed-error structure," Journal of Econometrics, Elsevier, vol. 2(1), pages 67-78, May.
  9. Arellano, Manuel & Bond, Stephen, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Wiley Blackwell, vol. 58(2), pages 277-97, April.
  10. Baltagi, Badi H. & Chang, Young-Jae & Li, Qi, 1992. "Monte Carlo evidence on panel data regressions with AR(1) disturbances and an arbitrary variance on the initial observations," Journal of Econometrics, Elsevier, vol. 52(3), pages 371-380, June.
  11. Whitney K. Newey & Frank Windmeijer, 2009. "Generalized Method of Moments With Many Weak Moment Conditions," Econometrica, Econometric Society, vol. 77(3), pages 687-719, 05.
  12. Seung Ahn & Young Lee & Peter Schmidt, 2007. "Stochastic frontier models with multiple time-varying individual effects," Journal of Productivity Analysis, Springer, vol. 27(1), pages 1-12, February.
  13. Jagannathan, Ravi & Wang, Zhenyu, 1996. " The Conditional CAPM and the Cross-Section of Expected Returns," Journal of Finance, American Finance Association, vol. 51(1), pages 3-53, March.
  14. 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.
  15. Conley, T. G., 1999. "GMM estimation with cross sectional dependence," Journal of Econometrics, Elsevier, vol. 92(1), pages 1-45, September.
  16. Amemiya, Takeshi, 1971. "The Estimation of the Variances in a Variance-Components Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 12(1), pages 1-13, February.
  17. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
  18. Caselli, Francesco & Esquivel, Gerardo & Lefort, Fernando, 1996. " Reopening the Convergence Debate: A New Look at Cross-Country Growth Empirics," Journal of Economic Growth, Springer, vol. 1(3), pages 363-89, September.
  19. Anderson, T.W., 2005. "Origins of the limited information maximum likelihood and two-stage least squares estimators," Journal of Econometrics, Elsevier, vol. 127(1), pages 1-16, July.
  20. J. A. Hausman & W. E. Taylor, 1980. "Panel Data and Unobservable Individual Effects," Working papers 255, Massachusetts Institute of Technology (MIT), Department of Economics.
  21. Chamberlain, Gary & Rothschild, Michael, 1982. "Arbitrage, Factor Structure, and Mean-Variance Analysis on Large Asset Markets," Scholarly Articles 3230355, Harvard University Department of Economics.
  22. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
  23. Whitney K. Newey & Richard J. Smith, 2004. "Higher Order Properties of Gmm and Generalized Empirical Likelihood Estimators," Econometrica, Econometric Society, vol. 72(1), pages 219-255, 01.
  24. Richard Blundell & Steve Bond, 1995. "Initial conditions and moment restrictions in dynamic panel data models," IFS Working Papers W95/17, Institute for Fiscal Studies.
  25. Islam, Nazrul, 1995. "Growth Empirics: A Panel Data Approach," The Quarterly Journal of Economics, MIT Press, vol. 110(4), pages 1127-70, November.
  26. Pesaran, M.H. & Smith, R., 1992. "Estimating Long-Run Relationships From Dynamic Heterogeneous Panels," Cambridge Working Papers in Economics 9215, Faculty of Economics, University of Cambridge.
  27. Baltagi, Badi H., 1986. "Pooling Under Misspecification: Some Monte Carlo Evidence on the Kmenta and the Error Components Techniques," Econometric Theory, Cambridge University Press, vol. 2(03), pages 429-440, December.
  28. K. Jöreskog, 1967. "Some contributions to maximum likelihood factor analysis," Psychometrika, Springer, vol. 32(4), pages 443-482, December.
  29. Cragg, John G. & Donald, Stephen G., 1997. "Inferring the rank of a matrix," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 223-250.
  30. Ahn, Seung C. & Schmidt, Peter, 1995. "Efficient estimation of models for dynamic panel data," Journal of Econometrics, Elsevier, vol. 68(1), pages 5-27, July.
  31. N. Gregory Mankiw & David Romer & David N. Weil, 1990. "A Contribution to the Empirics of Economic Growth," NBER Working Papers 3541, National Bureau of Economic Research, Inc.
  32. Holtz-Eakin, Douglas & Newey, Whitney & Rosen, Harvey S, 1988. "Estimating Vector Autoregressions with Panel Data," Econometrica, Econometric Society, vol. 56(6), pages 1371-95, November.
  33. Jushan Bai, 2003. "Inferential Theory for Factor Models of Large Dimensions," Econometrica, Econometric Society, vol. 71(1), pages 135-171, January.
  34. Amemiya, Takeshi & MaCurdy, Thomas E, 1986. "Instrumental-Variable Estimation of an Error-Components Model," Econometrica, Econometric Society, vol. 54(4), pages 869-80, July.
  35. Zhou, Guofu, 1994. "Analytical GMM Tests: Asset Pricing with Time-Varying Risk Premiums," Review of Financial Studies, Society for Financial Studies, vol. 7(4), pages 687-709.
  36. Keane, Michael P & Runkle, David E, 1992. "On the Estimation of Panel-Data Models with Serial Correlation When Instruments Are Not Strictly Exogenous," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(1), pages 1-9, January.
  37. Kelejian, Harry H & Prucha, Ingmar R, 1999. "A Generalized Moments Estimator for the Autoregressive Parameter in a Spatial Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 40(2), pages 509-33, May.
  38. Wallace, T D & Hussain, Ashiq, 1969. "The Use of Error Components Models in Combining Cross Section with Time Series Data," Econometrica, Econometric Society, vol. 37(1), pages 55-72, January.
  39. Connor, Gregory & Korajczyk, Robert A, 1993. " A Test for the Number of Factors in an Approximate Factor Model," Journal of Finance, American Finance Association, vol. 48(4), pages 1263-91, September.
  40. Breusch, Trevor S & Mizon, Grayham E & Schmidt, Peter, 1989. "Efficient Estimation Using Panel Data," Econometrica, Econometric Society, vol. 57(3), pages 695-700, May.
  41. Jushan Bai, 2009. "Panel Data Models With Interactive Fixed Effects," Econometrica, Econometric Society, vol. 77(4), pages 1229-1279, 07.
  42. Donald W.K. Andrews, 1997. "Consistent Moment Selection Procedures for Generalized Method of Moments Estimation," Cowles Foundation Discussion Papers 1146R, Cowles Foundation for Research in Economics, Yale University.
  43. Hayashi, Fumio & Sims, Christopher A, 1983. "Nearly Efficient Estimation of Time Series Models with Predetermined, but Not Exogenous, Instruments," Econometrica, Econometric Society, vol. 51(3), pages 783-98, May.
  44. Mundlak, Yair, 1978. "On the Pooling of Time Series and Cross Section Data," Econometrica, Econometric Society, vol. 46(1), pages 69-85, January.
  45. Wooldridge, Jeffrey M., 1996. "Estimating systems of equations with different instruments for different equations," Journal of Econometrics, Elsevier, vol. 74(2), pages 387-405, October.
  46. Keane, Michael P & Runkle, David E, 1992. "On the Estimation of Panel-Data Models with Serial Correlation When Instruments Are Not Strictly Exogenous: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(1), pages 26-29, January.
  47. Hansen, Lars Peter & Heaton, John & Yaron, Amir, 1996. "Finite-Sample Properties of Some Alternative GMM Estimators," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 262-80, July.
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Citations

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Cited by:
  1. Robertson, Donald & Sarafidis, Vasilis & Symons, James, 2010. "IV Estimation of Panels with Factor Residuals," MPRA Paper 26166, University Library of Munich, Germany.
  2. Westerlund, Joakim & Norkute, Milda, 2014. "A Factor Analytical Method to Interactive Effects Dynamic Panel Models with or without Unit Root," Working Papers 2014:12, Lund University, Department of Economics.
  3. Ahn, Seung C. & Perez, M. Fabricio, 2010. "GMM estimation of the number of latent factors: With application to international stock markets," Journal of Empirical Finance, Elsevier, vol. 17(4), pages 783-802, September.
  4. Greenaway-McGrevy, Ryan & Han, Chirok & Sul, Donggyu, 2012. "Asymptotic distribution of factor augmented estimators for panel regression," Journal of Econometrics, Elsevier, vol. 169(1), pages 48-53.
  5. Bada, Oualid & Kneip, Alois, 2014. "Parameter cascading for panel models with unknown number of unobserved factors: An application to the credit spread puzzle," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 95-115.
  6. KiHoon Jimmy Hong & Bin Peng & Xiaohui Zhang, 2014. "Capturing the Impact of Latent Industry-Wide Shocks with Dynamic Panel Model," Research Paper Series 347, Quantitative Finance Research Centre, University of Technology, Sydney.
  7. Yongcheol Shin, 2007. "Comments on: Panel data analysis—advantages and challenges," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer, vol. 16(1), pages 52-55, May.
  8. Vasilis Sarafidis & Tom Wansbeek, 2012. "Cross-Sectional Dependence in Panel Data Analysis," Econometric Reviews, Taylor & Francis Journals, vol. 31(5), pages 483-531, September.
  9. Kazuhiko Hayakawa & Vanessa Smith & Hashem Pesaran, 2014. "Transformed Maximum Likelihood Estimation of Short Dynamic Panel Data Models with interactive effects," Cambridge Working Papers in Economics 1412, Faculty of Economics, University of Cambridge.
  10. Castagnetti, Carolina & Rossi, Eduardo, 2008. "Estimation methods in panel data models with observed and unobserved components: a Monte Carlo study," MPRA Paper 26196, University Library of Munich, Germany.
  11. Shanti Gamper-Rabindran & Shakeeb Khan & Christopher Timmins, 2008. "The Impact of Piped Water Provision on Infant Mortality in Brazil: A Quantile Panel Data Approach," NBER Working Papers 14365, National Bureau of Economic Research, Inc.
  12. Bin Peng & Giovanni Forchini, 2014. "Consistent Estimation of Panel Data Models with a Multifactor Error Structure when the Cross Section Dimension is Large," Working Paper Series 20, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
  13. Bai, Jushan, 2013. "Likelihood approach to dynamic panel models with interactive effects," MPRA Paper 50267, University Library of Munich, Germany.
  14. Bai, Jushan & Li, Kunpeng, 2013. "Spatial panel data models with common shocks," MPRA Paper 52786, University Library of Munich, Germany, revised 09 Mar 2014.
  15. Perez, Marcos & Ahn, Seung Chan, 2007. "GMM Estimation of the Number of Latent Factors," MPRA Paper 4862, University Library of Munich, Germany.
  16. Kuersteiner, Guido M. & Prucha, Ingmar R., 2013. "Limit theory for panel data models with cross sectional dependence and sequential exogeneity," Journal of Econometrics, Elsevier, vol. 174(2), pages 107-126.

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