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Testing for Parameter Constancy in Linear Regressions: An Empirical Distribution Function Approach

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Bai, Jushan

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Abstract

This paper proposes some tests for parameter constancy in linear regressions. The tests use weighted empirical distribution functions of estimated residuals and are asymptotically distribution free. The proposed tests have nontrivial local power against a wide range of alternatives. In particular, the tests are capable of detecting error heterogeneity that is not necessarily manifested in the form of changing variances. The model allows for both dynamic and trending regressors. As an intermediate result, some weak convergence for (stochastically) weighted sequential empirical processes is established. Copyright 1996 by The Econometric Society.

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Publisher Info
Article provided by Econometric Society in its journal Econometrica.

Volume (Year): 64 (1996)
Issue (Month): 3 (May)
Pages: 597-622
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Handle: RePEc:ecm:emetrp:v:64:y:1996:i:3:p:597-622

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  1. Jamie Emerson & Chihwa Kao, 2000. "Testing for Structural Change of a Time Trend Regression in Panel Data," Center for Policy Research Working Papers 15, Center for Policy Research, Maxwell School, Syracuse University. [Downloadable!]
  2. repec:att:wimass:19199827 is not listed on IDEAS
  3. Bruce E. Hansen & Mehmet Caner, 1997. "Threshold Autoregressions with a Unit Root," Boston College Working Papers in Economics 381, Boston College Department of Economics. [Downloadable!]
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