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Panel Data Models with Multiple Time-Varying Individual Effects

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Author Info

  • Seung C. Ahn

    () (Dept. of Economics, W.P. Carey School of Business, Arizona State University, Tempe, AZ 85287)

  • Young H. Lee

    (Hansung University)

  • Peter Schmidt

    (Michigan State University)

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 factors. We propose a generalized methods of moments procedure by which both the number of factors 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

Paper provided by University of Crete, Department of Economics in its series Working Papers with number 0702.

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Length: 43 pages
Date of creation: 00 Oct 2006
Date of revision:
Handle: RePEc:crt:wpaper:0702

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Keywords: panel data; time-varying individual effects; factor models;

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References

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  1. Cragg, John G. & Donald, Stephen G., 1997. "Inferring the rank of a matrix," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 223-250.
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Citations

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Cited by:
  1. 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.
  2. 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.
  3. Sarafidis, Vasilis & Wansbeek, Tom, 2010. "Cross-sectional Dependence in Panel Data Analysis," MPRA Paper 20367, University Library of Munich, Germany.
  4. 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.
  5. 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.
  6. Perez, Marcos & Ahn, Seung Chan, 2007. "GMM Estimation of the Number of Latent Factors," MPRA Paper 4862, University Library of Munich, Germany.
  7. Robertson, Donald & Sarafidis, Vasilis & Symons, James, 2010. "IV Estimation of Panels with Factor Residuals," MPRA Paper 26166, University Library of Munich, Germany.

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