Testing Linearity in Cointegrating Relations With an Application to Purchasing Power Parity
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 chi(2) distributions. Nonstationarity introduces bias terms in the limit di...
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| Main Authors: | , |
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| Format: | text |
| Language: | English |
| Published: |
Institutional Knowledge at Singapore Management University
2010
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| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/soe_research/1812 https://ink.library.smu.edu.sg/context/soe_research/article/2811/viewcontent/Testing_Linearity_Cointegrating_PPP_av.pdf |
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| Institution: | Singapore Management University |
| Language: | English |
| Summary: | 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 chi(2) 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 chi(2) 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. |
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