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Testing for Breaks in Cointegrated Panels with Common and Idiosyncratic Stochastic Trends

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Abstract

In this paper, we develop tests for structural change in cointegrated panel regressions with common and idiosyncratic trends. We consider both the cases of observable and nonobservable common trends, deriving a Functional Central Limit Theorem for the partial sample estimators under the null of no break. We show that tests based on sup-Wald statistics are powerful versus breaks of size , also proving that power is present when the time of change differs across units and when only some units have a break. Our framework is extended to the case of cross correlated regressors and endogeneity. Monte Carlo evidence shows that the tests have the correct size and good power properties.

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Paper provided by Center for Policy Research, Maxwell School, Syracuse University in its series Center for Policy Research Working Papers with number 129.

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Length: 49 pages
Date of creation: Feb 2011
Date of revision:
Handle: RePEc:max:cprwps:129

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Keywords: Structural change; Panel cointegration; Common stochastic trends; Functional Central Limit Theorem.;

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