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Heteroskedasticity-Robust Tests for Structural Change

  • MacKinnon, J G

It is remarkably easy to test for structural change, of the type that the classic F or "Chow" test is designed to detect, in a manner that is robust to heteroskedasticity of possibly unknown form. This paper first discusses how to test for structural change in nonlinear regression models by using a variant of the Gauss-Newton regression. It then shows how to make these tests robust to heteroskedasticity of unknown form, and discusses several related procedures for doing so. Finally, it presents the results of a number of Monte Carlo experiments designed to see how well the new tests perform in finite samples.

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Article provided by Springer in its journal Empirical Economics.

Volume (Year): 14 (1989)
Issue (Month): 2 ()
Pages: 77-92

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Handle: RePEc:spr:empeco:v:14:y:1989:i:2:p:77-92
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  1. Toyoda, Toshihisa, 1974. "Use of the Chow Test under Heteroscedasticity," Econometrica, Econometric Society, vol. 42(3), pages 601-08, May.
  2. DAVIDSON, Russel & MACKINNON, James G., . "Heteroskedastcity-robust tests in regressions directions," CORE Discussion Papers RP -678, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  3. Engle, Robert F., 1982. "A general approach to lagrange multiplier model diagnostics," Journal of Econometrics, Elsevier, vol. 20(1), pages 83-104, October.
  4. Watt, P A, 1979. "Tests of Equality between Sets of Coefficients in Two Linear Regressions When Disturbance Variances Are Unequal: Some Small Sample Properties," The Manchester School of Economic & Social Studies, University of Manchester, vol. 47(4), pages 391-96, December.
  5. Davidson, Russell & MacKinnon, James G, 1984. "Model Specification Tests Based on Artificial Linear Regressions," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 25(2), pages 485-502, June.
  6. Phillips, G. D. A. & McCabe, B. P., 1983. "The independence of tests for structural change in regression models," Economics Letters, Elsevier, vol. 12(3-4), pages 283-287.
  7. Toyoda, Toshihisa & Ohtani, Kazuhiro, 1986. "Testing equality between sets of coefficients after a preliminary test for equality of disturbance variances in two linear regressions," Journal of Econometrics, Elsevier, vol. 31(1), pages 67-80, February.
  8. Chesher, Andrew & Jewitt, Ian, 1987. "The Bias of a Heteroskedasticity Consistent Covariance Matrix Estimator," Econometrica, Econometric Society, vol. 55(5), pages 1217-22, September.
  9. Honda, Yuzo, 1982. "On Tests of Equality between Sets of Coefficients in Two Linear Regressions When Disturbance Variances Are Unequal," The Manchester School of Economic & Social Studies, University of Manchester, vol. 50(2), pages 116-25, June.
  10. James G. MacKinnon & Halbert White, 1983. "Some Heteroskedasticity Consistent Covariance Matrix Estimators with Improved Finite Sample Properties," Working Papers 537, Queen's University, Department of Economics.
  11. Schmidt, Peter & Sickles, Robin, 1977. "Some Further Evidence on the Use of the Chow Test under Heteroskedasticity," Econometrica, Econometric Society, vol. 45(5), pages 1293-98, July.
  12. Weerahandi, Samaradasa, 1987. "Testing Regression Equality with Unequal Variances," Econometrica, Econometric Society, vol. 55(5), pages 1211-15, September.
  13. Jayatissa, W A, 1977. "Tests of Equality between Sets of Coefficients in Two Linear Regressions when Disturbance Variances Are Unequal," Econometrica, Econometric Society, vol. 45(5), pages 1291-92, July.
  14. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-38, May.
  15. Ohtani, Kazuhiro & Toyoda, Toshihisa, 1985. "Small Sample Properties of Tests of Equality between Sets of Coefficients in Two Linear Regressions under Heteroscedasticity," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 26(1), pages 37-44, February.
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