Nonparametric Detection and Estimation of Structural Change

Dennis Kristensen

CREATES Research Papers from Department of Economics and Business Economics, Aarhus University

Abstract: We propose a nonparametric approach to the estimation and testing of structural change in time series regression models. Under the null of a given set of the coefficients being constant, we develop estimators of both the nonparametric and parametric components. Given the estimators under null and alternative, generalized F and Wald tests are developed. The asymptotic distributions of the estimators and test statistics are derived. A simulation study examines the fi?nite-sample performance of the estimators and tests. The techniques are employed in the analysis of structural change in US productivity and the Eurodollar term structure.

Keywords: structural change; regression; nonparametric; estimation; testing; generalized likelihood ratio; time-varying; locally stationary. (search for similar items in EconPapers)
JEL-codes: C12 C13 C14 C22 (search for similar items in EconPapers)
Pages: 60
Date: 2011-04-18
New Economics Papers: this item is included in nep-ets
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Citations: View citations in EconPapers (2)

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Related works:
Journal Article: Non‐parametric detection and estimation of structural change (2012)
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Persistent link: https://EconPapers.repec.org/RePEc:aah:create:2011-13

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