A Two Step Procedure for Testing Partial Parameter Stability in Cointegrated Regression Models

Mohitosh Kejriwal, Pierre Perron and Xuewen Yu ()
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Xuewen Yu: Purdue University

No WP2020-011, Boston University - Department of Economics - Working Papers Series from Boston University - Department of Economics

Abstract: Kejriwal and Perron (2010, KP) provided a comprehensive treatment for the problem of testing multiple structural changes in cointegrated regression models. A variety of models were considered depending on whether all regression coefficients are allowed to change (pure structural change) or a subset of the coefficients is held Öxed (partial structural change). In this note, we Örst show that the limit distributions of the test statistics in the latter case are not invariant to changes in the coe¢ cients not being tested; in fact, they diverge as the sample size increases. To address this issue, we propose a simple two step procedure to test for partial parameter stability. The Örst entails the application of a joint test of stability for all coe¢ cients as in KP. Upon a rejection, the second conducts a stability test on the subset of coe¢ cients of interest while allowing the other coe¢ cients to change at the estimated breakpoints. Its limit distribution is standard chi-square. The relevant asymptotic theory is provided along with simulations that illustrates the usefulness of the procedure in finite samples.

Keywords: cointegration; partial structural change; break date; sup-Wald tests; joint hypothesis testing (search for similar items in EconPapers)
JEL-codes: C22 (search for similar items in EconPapers)
Pages: 16 pages
Date: 2020-02
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-ore
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Journal Article: A two‐step procedure for testing partial parameter stability in cointegrated regression models (2022)
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