Bai, Jushan and Li, Kunpeng (2010): Theory and methods of panel data models with interactive effects.
Preview |
PDF
MPRA_paper_43441.pdf Download (679kB) | Preview |
Abstract
This paper considers the maximum likelihood estimation of the panel data models with interactive effects. Motivated in economics and other social sciences, a notable feature of the model is that the explanatory variables are correlated with the unobserved effects. The usual within-group estimator is inconsistent. Existing methods for consistent estimation are either designed for panel data with short time periods or are less efficient. The maximum likelihood estimator has desirable properties and is easy to implement, as illustrated by the Monte Carlo simulations. This paper develops the inferential theory for the maximum likelihood estimator, including consistency, rate of convergence and the limiting distributions. We further extend the model to include time-invariant regressors and common regressors (cross-section invariant). The regression coefficients for the time-invariant regressors are time-varying, and the coefficients for the common regressors are cross-sectionally varying.
Item Type: | MPRA Paper |
---|---|
Original Title: | Theory and methods of panel data models with interactive effects |
Language: | English |
Keywords: | factor error structure; factors; factor loadings; maximum likelihood; principal components; within-group estimator; simultaneous equations; |
Subjects: | C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C33 - Panel Data Models ; Spatio-temporal Models |
Item ID: | 43441 |
Depositing User: | Kunpeng Li |
Date Deposited: | 29 Jan 2013 10:35 |
Last Modified: | 26 Sep 2019 21:29 |
References: | Ahn, S. G., Y. H. Lee and P. Schmidt (2001) GMM estimation of linear panel data models with time-varying Individual effects, \textit{Journal of Econometrics}, \textbf{101}, 219--255. Ahn, S. G., Y. H. Lee and P. Schmidt (2006) Panel data models with multiple time-varying effects, \textit{manuscript}, Arizona State University. Amemiya Y., W. A. Fuller and S. G. Pantula (1987) The asymptotic distributions of some estimators for a factor analysis model, \textit{Journal of Multivariate Analysis}, \textbf{22:1}, 51--64. Anderson, T.W. and Y. Amemiya (1988) The asymptotic normal distribution of estimators in factor analysis under general conditions, \textit{The Annals of Statistics}, \textbf{16:2}, 759--771. Anderson, T.W. and H. Rubin (1956) Statistical inference in factor analysis, In \textit{ Proceedings of the third Berkeley Symposium on Mathematical Statistics and Probability: Contributions to The Theory of Statistics}, University of California Press. Arellano, M. (2003) \textit{Panel Data Econometrics}, Oxford University Press. Bai, J. (2003) Inferential theory for factor models of large dimensions. \textit{Econometrica}, \textbf{71(1)}, 135--171. Bai, J. (2009a) Panel data models with interactive fixed effects. \textit{Econometrica}, \textbf{77(4)}, 1229--1279. Bai, J. (2009b) Likelihood approach to small T dynamic panel models with interactive effects. \textit{manuscript}, Columbia University. Bai, J. and K. Li (2012) Statistical analysis of factor models of high dimension. \textit{Annals of Statistics}, \textbf{40(1)}, 436--465. Bai, J. and S. Ng (2002) Determining the number of factors in approximate factor models,\textit{ Econometrica}, \textbf{70:1}, 191--221. Baltagi, B.H. (2005) \textit{Econometric Analysis of Panel Data}. Chichester: Wiley. Breitung, J. and J. Tenhofen (2011) GLS estimation of dynamic factor models, \textit{Journal of the American Statistical Association}, \textbf{106(3)}, 1150--1166. Chamberlain, G. (1984) Panel data, in Z. Griliches and M. Intriligator (eds.), \textit{in Handbook of Econometrics}, Vol.2, 1247--1318, Amsterdam: North-Holland. Chamberlain, G. and M. Rothschild (1983) Arbitrage, factor structure, and mean-variance analysis on large asset markets, \textit{Econometrica}, \textbf{51:5}, 1281--1304. Doz, C., D. Giannone and L. Reichlin (2012) A qausi-maximum likelihood approach for large approximate dynamic factor models, \textit{Review of Economics and Statistics}, \textbf{94(4)}, 1014--1024. Holtz-Eakin, D., W., Newey and H.S. Rosen (1988) Estimating vector autoregressions with panel data, \textit{Econometrica}, \textbf{56(6)}, 1371--1395. Hsiao, C. (2003) Analysis of Panel Data, \textit{NewYork: Cambridge University Press}. Jenrich, R.I. (1969) Asymptotic properties of non-linear least squares estimators, \textit{The Annals of Mathematical Statistics}, \textbf{40(2)}, 633--643. Kneip, A., R.C., Sickles and W. Song (2012) A new panel data treatment for heterogeneity in time trends, \textit{Econometric theory}, \textbf{28(3)}, 590--628. Lawley D. N. and A. E. Maxwell (1971) \textit{Factor Analysis as a Statistical Method}, New York: American Elsevier Publishing Company. Meng X.L. and D.B. Rubin (1993) Maximum likelihood estimation via the ECM algorithm: A general framework, \textit{Biometrika}, \textbf{80(2)}, 267--278. Moon, H. and M., Weidner (2009) Likelihood expansion for panel regression models with factors, \textit{manuscipt, University of Southern California}. Mundlak, Y. (1978): On the pooling of time series and cross section data, \textit{Econometrica}, \textbf{46(1)}, 69--85. Newey, W. and D. McFadden (1994) Large Sample Estimation and Hypothesis Testing, in Engle, R.F. and D. McFadden (eds.) {\em Handbook of Econometrics,} North Holland. Neyman, J. and E.L. Scott (1948) Consistent estimates based on partially consistent observations. \textit{Econometrica}, \textbf{16(1)}, 1-32. Pesaran, M.H. (2006) Estimation and inference in large heterogeneous panels with a multifactor error structure, \textit{Econometrica}, \textbf{74(4)}, 967--1012. Ross, S.A. (1976) The arbitrage theory of capital asset pricing, \textit{Journal of Economic Theory},\textbf{13(3)}, 341--360. Rubin, D.B. and D.T. Thayer (1982) EM algorithms for ML factor analysis, \textit{Psychometrika},\textbf{47(1)}, 69--76. Stock, J.H. and M.W. Watson (2002) Forecasting using principal components from a large number of predictors, {\em Journal of the American Statistical Association }, \textbf{97}, 1167--1179. Su, L., S., Jin and Y., Zhang (2012) Specification Test for Panel Data Models with Interactive Fixed Effects, \textit{manuscript}, Singapore Management University. Tucker, L.R. (1958) An inter-battery method of factor analysis, \textit{Psychometrika}, \textbf{23(2)}, 111--136. Wu, C.F.J. (1983) On the convergence properties of the EM algorithm, {\em The Annals of Statistics}, 95--103. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/43441 |