The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
권호 표지
DOI QR코드

DOI QR Code

Test of Model Specification in Panel Regression Model with Two Error Components

이원오차성분을 갖는 패널회귀모형의 모형식별검정

  • 송석헌 (고려대학교 통계학과) ;
  • 김영지 (LG화재 기업요율상품팀) ;
  • 황선영 (숙명여자대학교 통계학과)
  • Published : 2006.11.30
Download PDF
⟨ Previous Next ⟩

Abstract

This paper derives joint and conditional Lagrange multiplier tests based on Double-Length Artificial Regression(DLR) for testing functional form and/or the presence of individual(time) effect in a panel regression model. Small sample properties of these tests are assessed by Monte Carlo study, and comparisons are made with LM tests based on Outer Product Gradient(OPG). The results show that the proposed DLR based LM tests have the most appropriate finite sample performance.

본 논문에서는 이원오차성분을 갖는 패널회귀모형에서 모형식별을 위하여 LM 검정통계량을 유도하고 검정통계량의 연산을 위하여 인공회귀방법(Double-Length Artificial Regression, DLR)을 이용한다. 모의 실험 결과, 소표본의 경 우에는 Outer-Product Gradient(OPG)에 근거한 LM 검정통계량은 유위수준이 과대기각하는 경향을 보인 반면 DLR에 근거한 LM 검정통계량은 명목유의수준을 잘 유지하고 검정력도 높게 나타났다.

Keywords

References

  1. 송석헌, 최충돈 (2003). 패널회귀모형에서 선형성검정, <응용통계연구>, 16, 351-364
  2. Baltagi, B. H. (2002). Econometric Analysis of Panel Data, John Wiley, New York
  3. Baltagi, B. H., Song. S. H. and Jung. B. C. (2001). The unbalanced nested error component regression model, Journal of Econometrics, 101, 357-381 https://doi.org/10.1016/S0304-4076(00)00089-0
  4. Baltagi, B. H., Song. S. H. and Jung. B. C. (2002a). Simple LM tests for unbalanced nested error component regression model, Econometric Reviews, 21, 167-187 https://doi.org/10.1081/ETC-120014347
  5. Baltagi, B. H., Song. S. H. and Jung. B. C. (2002b). A comparative study of alterative estimators for the unbalanced two-way error component regression model, The Econometrics Journal, 5, 480-493 https://doi.org/10.1111/1368-423X.t01-1-00094
  6. Box, G. E. P. and Cox D. R. (1964). An analysis of transformations, Journal of The Royal Statistical Society Series, 26, 211-252
  7. Davidson, R. and MacKinnon, J. G. (1984). Model specification test based on artificial regression, International Economic Review, 25, 485-502 https://doi.org/10.2307/2526210
  8. Davidson, R. and MacKinnon, J. G. (1988). Double-Length artificial regression, Oxford Bulletin of Economics and Statistics, 50, 203-217 https://doi.org/10.1111/j.1468-0084.1988.mp50002008.x
  9. Davidson, R. and MacKinnon, J. G. (1990). Specification tests based on artificial regressions, Journal of the American Statistical Association, 85, 220-227 https://doi.org/10.2307/2289548
  10. Fuller, W. A. and Battese, G. E. (1974). Estimation of linear models with cross-error structure, Journal of Econometrics, 2, 67-68 https://doi.org/10.1016/0304-4076(74)90030-X
  11. Godfrey, L. G. and Wickens, M. R. (1981). Testing linear and log-linear regressions for functional form, Review of Economic Studies, 48, 487-496 https://doi.org/10.2307/2297160
  12. Nerlove, M. (1971). Further evidence on the estimation of dynamic economic relations from a time-series of cross-sections, Econometrica, 39, 359-382 https://doi.org/10.2307/1913350
  13. Yeo, I. K. and Johnson, R. A. (2000). A new family of power transformation to improve normality or symmetry, Biometrika, 87, 954-959 https://doi.org/10.1093/biomet/87.4.954