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Testing Cross-sectional Correlation in Large Panel Data Models with Serial Correlation

Listed author(s):
  • Badi H. Baltagi

    (Syracuse University)

  • Chihwa Kao

    (University of Connecticut)

  • Bin Peng

    (Huazhong University of Science and Technology)

This paper considers the problem of testing cross-sectional correlation in large panel data models with serially correlated errors. It finds that existing tests for cross-sectional correlation encounter size distortions with serial correlation in the errors. To control the size, this paper proposes a modification of Pesaran’s CD test to account for serial correlation of an unknown form in the error term. We derive the limiting distribution of this test as (N, T) → ∞. The test is distribution free and allows for unknown forms of serial correlation in the errors. Monte Carlo simulations show that the test has good size and power for large panels when serial correlation in the errors is present. JEL Classification: C13; C33 Key words: Cross-sectional Correlation Test; Serial Correlation; Large Panel Data Model

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File URL: http://web2.uconn.edu/economics/working/2016-32.pdf
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Paper provided by University of Connecticut, Department of Economics in its series Working papers with number 2016-32.

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Length: 24 pages
Date of creation: Oct 2016
Handle: RePEc:uct:uconnp:2016-32
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University of Connecticut 365 Fairfield Way, Unit 1063 Storrs, CT 06269-1063

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Fax: (860) 486-4463
Web page: http://www.econ.uconn.edu/

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  1. Baltagi, Badi H. & Feng, Qu & Kao, Chihwa, 2012. "A Lagrange Multiplier test for cross-sectional dependence in a fixed effects panel data model," Journal of Econometrics, Elsevier, vol. 170(1), pages 164-177.
  2. Donald W. K. Andrews, 2005. "Cross-Section Regression with Common Shocks," Econometrica, Econometric Society, vol. 73(5), pages 1551-1585, 09.
  3. T. S. Breusch & A. R. Pagan, 1980. "The Lagrange Multiplier Test and its Applications to Model Specification in Econometrics," Review of Economic Studies, Oxford University Press, vol. 47(1), pages 239-253.
  4. Baltagi, Badi H. & Song, Seuck Heun & Koh, Won, 2003. "Testing panel data regression models with spatial error correlation," Journal of Econometrics, Elsevier, vol. 117(1), pages 123-150, November.
  5. James R. Schott, 2005. "Testing for complete independence in high dimensions," Biometrika, Biometrika Trust, vol. 92(4), pages 951-956, December.
  6. M. Hashem Pesaran, 2015. "Testing Weak Cross-Sectional Dependence in Large Panels," Econometric Reviews, Taylor & Francis Journals, vol. 34(6-10), pages 1089-1117, December.
  7. Chen, Song Xi & Qin, Yingli, 2010. "A Two Sample Test for High Dimensional Data with Applications to Gene-set Testing," MPRA Paper 59642, University Library of Munich, Germany.
  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. Lee, Lung-Fei, 2002. "Consistency And Efficiency Of Least Squares Estimation For Mixed Regressive, Spatial Autoregressive Models," Econometric Theory, Cambridge University Press, vol. 18(02), pages 252-277, April.
  10. Badi H. Baltagi & Qu Feng & Chihwa Kao, 2011. "Testing for sphericity in a fixed effects panel data model," Econometrics Journal, Royal Economic Society, vol. 14(1), pages 25-47, February.
  11. Chen, Song Xi & Zhang, Li-Xin & Zhong, Ping-Shou, 2010. "Tests for High-Dimensional Covariance Matrices," Journal of the American Statistical Association, American Statistical Association, vol. 105(490), pages 810-819.
  12. Francesco Moscone & Elisa Tosetti, 2009. "A Review And Comparison Of Tests Of Cross-Section Independence In Panels," Journal of Economic Surveys, Wiley Blackwell, vol. 23(3), pages 528-561, 07.
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