Testing for parameter stability in quantile regression models
We propose a test for structural change of conditional distribution in dynamic regression models. The test is constructed based on time series regression quantile estimates and complements conventional parameter instability tests in least-square type regression models. Asymptotic distribution for our test under the null hypothesis is derived.
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Volume (Year): 78 (2008)
Issue (Month): 16 (November)
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- Bai, Jushan, 1996. "Testing for Parameter Constancy in Linear Regressions: An Empirical Distribution Function Approach," Econometrica, Econometric Society, vol. 64(3), pages 597-622, May.
- Diebold, Francis X & Gunther, Todd A & Tay, Anthony S, 1998. "Evaluating Density Forecasts with Applications to Financial Risk Management," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 863-83, November.
- Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
- Lee, Sangyeol & Na, Seongryong, 2004. "A nonparametric test for the change of the density function in strong mixing processes," Statistics & Probability Letters, Elsevier, vol. 66(1), pages 25-34, January.
- Koenker, Roger & Zhao, Quanshui, 1996. "Conditional Quantile Estimation and Inference for Arch Models," Econometric Theory, Cambridge University Press, vol. 12(05), pages 793-813, December.
- Inoue, Atsushi, 2001. "Testing For Distributional Change In Time Series," Econometric Theory, Cambridge University Press, vol. 17(01), pages 156-187, February.
- Koenker, Roger & Xiao, Zhijie, 2006. "Quantile Autoregression," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 980-990, September.
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