Sarafidis, Vasilis and Wansbeek, Tom (2010): Cross-sectional Dependence in Panel Data Analysis.
This is the latest version of this item.
Preview |
PDF
MPRA_paper_20815.pdf Download (492kB) | Preview |
Abstract
This paper provides an overview of the existing literature on panel data models with error cross-sectional dependence. We distinguish between spatial dependence and factor structure dependence and we analyse the implications of weak and strong cross-sectional dependence on the properties of the estimators. We consider estimation under strong and weak exogeneity of the regressors for both T fixed and T large cases. Available tests for error cross-sectional dependence and methods for determining the number of factors are discussed in detail. The finite-sample properties of some estimators and statistics are investigated using Monte Carlo experiments.
Item Type: | MPRA Paper |
---|---|
Original Title: | Cross-sectional Dependence in Panel Data Analysis |
Language: | English |
Keywords: | Panel data, Cross-sectional dependence, Spatial dependence, Factor structure, Strong/Weak exogeneity |
Subjects: | C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C50 - General C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C33 - Panel Data Models ; Spatio-temporal Models |
Item ID: | 20815 |
Depositing User: | Vasilis Sarafidis |
Date Deposited: | 21 Feb 2010 18:26 |
Last Modified: | 26 Sep 2019 09:05 |
References: | Ahn, S.C. and Schmidt, P. 1995. Efficient Estimations of Models for Dynamic Panel Data. Journal of Econometrics, 68, 5-28. Ahn, S. C. and Horenstein, A. 2008. Eigenvalue ratio test for the number of factors. Mimeo. Ahn, S. C., Y. H. Lee and P. Schmidt. 2006. GMM estimation of linear panel data models with time-varying individual effects. Journal of Econometrics, 101, 219-255. Ahn, S. C., Y. H. Lee and P. Schmidt. 2006. Panel Data Models with Multiple Time-Varying Individual Effects. Mimeo. Amengual, D. and Watson, M. W. 2007. Consistent estimation of the number of dynamic factors in a large N and T panels. Journal of Business & Economic Statistics, 25(1), 91-96. Anderson, T.W. and Hsiao, C. 1981. Estimation of Dynamic Models with Error Components. Journal of the American Statistical Association, 76, 598-606. Arellano, M. 2003. Panel Data Econometrics. Oxford University Press, Oxford. Arellano, M. and Bond S. 1991. Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations. Review of Economic Studies, 58, 277-297. Arellano, M. and Bover, O. 1995. Another Look at the Instrumental Variable Estimation of Error-Component Models. Journal of Econometrics, 68, 29-51. Bai, J. 2009. Panel Data Models with Interactive Fixed Effects. Econometrica, 77, 1229-1279. Bai, J. 2010. Likelihood approach to small T dynamic panel models with interactive effects. Mimeo. Bai, J. and Ng, S. 2002. Determining the Number of Factors in Approximate Factor Models. Econometrica, 70, 191-22. Bai, J. and Ng, S. 2002. A PANIC Attack on Unit Roots and Cointegration. Eco- nometrica, 72(4), 1127-1177. Baltagi, B. 2008. Econometric Analysis of Panel Data, 4th ed. John Willey & Sons, West Sussex. Baltagi B. H. and Pesaran M. H. 2007. Heterogeneity and cross section dependence in panel data models: theory and applications - Introduction. Journal of Applied Econometrics, 22(2), 229-232. Bekker, P.A. 1994. Alternative Approximations to the Distributions of Instrumental Variable Estimators. Econometrica, 62, 657-681. Blundell, R. and Bond, S. 1998. Initial Conditions and Moment Restrictions in Dynamic Panel Data Models. Journal of Econometrics, 87, 115-143. Breitung, J. and Pesaran, M.H. 2008. Unit Roots and Cointegration in Panels, in L. Matyas and Sevestre P. (eds.) The Econometrics of Panel Data: Fundamentals and Recent Developments in Theory and Practice, Kluwer Academic Publishers. Breusch, T. and A. Pagan. 1980. The Lagrange multiplier test and its application to model specification in econometrics. Review of Economic Studies 47, 239-253. Chen, J., Gao, J. and Li, D. 2009. A New Diagnostic Test for Cross Section Independence in Nonparametric Panel Data Models. Mimeo. Chudik, A. Pesaran, M. H. and Tosetti, E. 2009. Weak and Strong Cross Section Dependence and Estimation of Large Panels. Mimeo. Coakley, J., A. Fuertes and R. Smith (2002). A Principal Components Approach to Cross-Section Dependence in Panels. Working paper, Birckbeck College, University of London. Conley, T.G. 1999. GMM Estimation with Cross Sectional Dependence. Journal of Econometrics, 92,1-45. Conley, T.G., and Topa, G. 2002. Socio-economic Distance and Spatial Patterns in Unemployment. Journal of Applied Econometrics, 17, 303-327. de Hoyos, R. E. and Sarafidis, V. 2006. Testing for Cross-sectional Dependence in Panel Data Models. The Stata Journal 6(4): 482-496. Driscoll, J.C., and Kraay, A.C. 1998. Consistent Covariance Matrix Estimation with Spatially Dependent Data. The Review of Economics and Statistics, 80, 549-560. Fiebig, D. G. 2001. Seemingly Unrelated Regression, in Baltagi, B. eds, A Companion to Theoretical Econometrics, Backwell Publishers, 101-121. Fisher, R.A. 1935. The Design of Experiments. Oliver and Boyd, Edinburgh. Forni, M. and Lippi, M. 2001. The Generalized Dynamic Factor Model: Representation Theory. Econometric Theory 17, 1113-1141. Forni, M., M. Hallin, M. Lippi, and L. Reichlin (2000). The generalized factor model: identification and estimation. The Review of Economics and Statistics, 82, 540-554. Frees, E. W. 1995. Assessing Cross-sectional Correlation in Panel Data. Journal of Econometrics, 69, 393-414. Friedman, M. 1937. The use of ranks to avoid the assumption of normality implicit in the analysis of variance. Journal of the American Statistical Association 32, 675-701. Goldberger, A. 1972. Structural equation methods in the social sciences. Econometrica 40 (6), 979-1001. Greenaway-McGrevy, R. Han, C. and Sul, D. 2009. Estimating the Number of Common Factors in Serially Dependent Approximate Factor Models. Mimeo. Hallin, M. and Liöka, R. 2007. Determining the number of factors in the general dynamic factor model. Journal of the American Statistical Association, 102(478), 603-617. Hansen, L. P. 1982. Large Sample Properties of Generalized Method of Moments Estimators, Econometrica, 50, 1029-1054. Hayakawa, K. 2009. Bias Corrected Estimation of Dynamic Panel Data Models with Interactive Fixed Effects. Mimeo. Holtz-Eakin D, Newey W. and Rosen H. 1988. Estimating Vector Autoregressions with Panel Data. Econometrica, 56, 1371-1395. Hurlin, C., Mignon, V. 2004. Second generation panel unit root tests. Mimeo. Hsiao, C. Analysis of Panel Data. 2nd ed. Cambridge University Press, Cambridge. 41 Hsiao, C. 2007. Panel Data Analysis - Advantages and Challenges. TEST. Vol. 16, pp. 1-22. Hsiao, C., Pesaran, M. H. and Pick, A. 2009. Diagnostic Tests of Cross Section Independence for Nonlinear Panel Data Models. Mimeo. Joreskog, K. G. and Goldberger, A. S. 1975. Estimation of a model with multiple indicators and multiple causes of a single latent variable. Journal of the American Statistical Association, 70, 631-639. Kapetanios, G. An Alternative Method for Determining the Number of Factors in Factor Models with Large Data Sets. Kapetanios G. Journal of Business and Economic Statistics, forthcoming. Kapetanios, G., and Pesaran, M. H. 2007. Small Sample Properties of Cross Section Augmented Estimators for Panel Data Models with Residual Multi-factor Structures; with M. H. Pesaran. In The Refinement of Econometric Estimation and Test Procedures: Finite Sample and Asymptotic Analysis, Garry Phillips and Elias Tzavalis (eds.), Cambridge University Press, Cambridge. Kapetanios, G., Pesaran, M. H. and Yamagata, T. 2009. Panels with Nonstationary Multifactor Error Structures. Mimeo. Kapoor, M., Kelejian, H. and Prucha, I. 2007. Panel Data Models with Spatially Correlated Error Components. Journal of Econometrics, 140, 97-130. Kelejian, H. and Prucha, I. 2010. Specification and Estimation of Spatial Autoregressive Models with Autoregressive and Heteroskedastic Disturbances. Journal of Econometrics, forthcoming. Kiviet, J. and Sarafidis, V. 2000. Cross-sectional Correlation in Panel Data Relationships. Mimeo. Kontoghiorghes, E. J. and Clarke, M. R. B. 1995. An alternative approach for the numerical solution of seemingly unrelated regression equations models. Computational Statistics & Data Analysis, 19(4), 369-377. Lee, L. F. 2004. Asymptotic Distributions of Quasi-Maximum Likelihood Estimators for Spatial Autoregressive Models. Econometrica, 72, 1899-1925. Lee, L. F. 2007. GMM and 2SLS estimation of mixed regressive, spatial autoregressive models. Journal of Econometrics, 137, 489-514. Lawley, D.N. and Maxwell A.E. 1971. Factor Analysis as a Statistical Method. Butterworth, London. Moon, R. G. and Perron, B. 2004. Efficient Estimation of the SUR Cointegrating Regression Model and Testing for Purchasing Power Parity. Econometric Reviews, 23, 293-323. Moon, H. R. and Perron, B. 2006. Seemingly Unrelated Regressions. Mimeo. Mundlak, Y. 1978. On the pooling of time series and cross section data. Econometrica, 46, 69-85. Nauges, C. and Thomas, A. 2003. Consistent estimation of dynamic panel data models with time-varying individual effects. Annales de Economie et de Statistique, 70, 53-74. Neprash, J.A. 1934. Some Problems in the Correlation of Spatially Distributed Variables. Journal of the American Statistical Association, 29, 167-168. Newey, W. and West, K. 1987. A Simple, Positive Semi-definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix. Econometrica, 55(3), 703-708. Nickell, S. 1981. Biases in Dynamic Models with Fixed Effects. Econometrica, 49, 1417-1426. Onatski, A. 2007. A formal statistical test for the number of factors in the approximate factor models. Mimeo Pesaran, M. H. 2002. Estimation and Inference in Large Heterogenous Panels with Cross Section Dependence. Mimeo. Pesaran, M. H. 2004. General diagnostic tests for cross section dependence in panels. University of Cambridge, Faculty of Economics, Cambridge Working Papers in Economics No. 0435. Pesaran, M. H. 2006. Estimation And Inference In Large Heterogeneous Panels With A Multifactor Error Structure. Econometrica, 74(4), 967-1012. Pesaran, M. H. and Tosetti, E. 2009. Large panels with common factors and spatial correlations. Mimeo. Pesaran, M. H., A. Ullah, and Yamagata, T. 2008. A bias-adjusted test of error cross section dependence. The Econometrics Journal, 11, 105-127. Phillips, P. and Sul, D. 2003. Dynamic Panel Estimation and Homogeneity Testing under cross-sectional Dependence. Econometrics Journal 6, 217-259. Phillips, P. and Sul, D. 2007. Bias in Dynamic Panel Estimation with Fixed Effects, Incidental Trends and cross-sectional Dependence. Journal of Econometrics 137, 162-188. Robertson, D. and Symons. J. 2007. Maximum Likelihood Factor Analysis with Rank Deficient Sample Covariance Matrices. Journal of Multivariate Analysis, 98(4), 813-828. Robertson, D., V. Sarafidis, and J. Symons (2010). IV Estimation of Panels with Factor Residuals. mimeo. Sarafidis, V. 2009. GMM Estimation of Short Dynamic Panel Data Models with Error Cross-sectional Dependence. Mimeo. Sarafidis, V. and Robertson, D. 2009. On the Impact of Error Cross-sectional Dependence in Short Dynamic Panel Estimation. The Econometrics Journal, 12(1), 62-81. Sarafidis, V., Yamagata, T. and Robertson, D. 2009. A Test of Cross Section Dependence for a Linear Dynamic Panel Model with Regressors. Journal of Econometrics, 148(2), 149-161. Sargan, J.D. 1958. The Estimation of Economic Relationships Using Instrumental Variables. Econometrica, 26, 393-495. Stephan, F.F. 1934. Sampling Errors and Interpretations of Social Data Ordered in Time and Space. Journal of the American Statistical Association, 29, 165-166. Srivastava, V. K. and Dwivedi, T. D. 1979. Estimation of seemingly unrelated regression equations: a brief survey. Journal of Econometrics, 10, 15-32. Srivastava. S. and Giles, D. 1987. Seemingly Unrelated Regression Equations Models. Marcel Dekker, New York. Tobler, W. 1970. A Computer Movie Simulating Urban Growth in the Detroit Region. Economic Geography, 46, 234-240. Yamagata, T. 2008. A Joint Serial Correlation Test for Linear Panel Data Models. Journal of Econometrics 146, 13-145. Wansbeek, T., and Knaap, T. 1999. Estimating a Dynamic Panel Data Model with Heterogenous Trends. Annales de Economie et de Statistique, 55-56, 331-349. Wansbeek, T., and E. Meijer. 2000. Measurement Error and Latent Variables in Econometrics. Amsterdam, Elsevier. Wansbeek, T., and E. Meijer. 2007. Comments on; Panel data Analysis - Advantages and Challenges. TEST. Vol. 16, pp. 33-36. Zellner, A. 1962. An E¢ cient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias. Journal of the American Statistical Association, 57, 348-368. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/20815 |
Available Versions of this Item
-
Cross-sectional Dependence in Panel Data Analysis. (deposited 03 Feb 2010 00:23)
- Cross-sectional Dependence in Panel Data Analysis. (deposited 21 Feb 2010 18:26) [Currently Displayed]