Testing Linearity in Cointegrating Relations With an Application to Purchasing Power Parity

By Seung-Hyun Hong, Peter C. B. Phillips. 2010

59 citations recorded by the source corpus.

This article shows that when applied to nonstationary time series, the conventional Regression Error Specification Test (RESET) leads to severe size distortion and its asymptotic distribution involves a mixture of noncentral χ2 distributions. Nonstationarity introduces bias terms in the limit distribution, and appropriate corrections for the bias are presented leading to a modified RESET test that has a central χ2 limit distribution. In simulations, this modified test is shown to have power not only against nonlinear cointegration but also against the absence of cointegration. In an empirical illustration, the linear purchasing power parity (PPP) specification is tested using five Organization for Economic Cooperation and Development (OECD) countries.

Subfields: Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/acd5970848788b604ab6873d01a9e858a46f025e

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In Economics and Econometrics

Citations in the corpus

COINTEGRATING POLYNOMIAL REGRESSIONS: FULLY MODIFIED OLS ESTIMATION AND INFERENCE (2011, methodology): “With respect to specification testing, amongst other things, this paper extends Hong and Phillips (2010) – who consider LM-type specification testing based on the OLS residuals of a linear cointegrating relationship with one integrated regressor – in several ways.”
Estimating Smooth Structural Change in Cointegration Models (2017, unknown): “However, parameter instability and functional form misspeciﬁ-cation may limit the performance of such nonlinear parametric cointegration models in empirical applications (Hong and Phillips, 2010; Kasparis and Phillips, 2012; Kasparis et al , 2013).”