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Nonstationary Nonlinear Heteroskedasticity in Regression

Joon Park and Heetaik Chung

No 508, Econometric Society 2004 Far Eastern Meetings from Econometric Society

Abstract: This paper considers the regression with errors having nonstationary nonlinear heteroskedasticity. For both the usual stationary regression and the nonstationary cointegrating regression, we develop the asymptotic theories for the least squares methods in the presence of conditional heterogeneity given as a nonlinear function of an integrated process. In particular, it is shown that the nonstationarity of volatility in the regression errors may induce spuriousness of the underlying regression. This is true for both the usual stationary regression and the nonstationary cointegrating regression, if excessive nonstationary volatility is present in the errors. Mild nonstationary volatilities do not render the underlying regression spurious. However, their presence makes the least squares estimator asymptotically biased and inefficient and the usual chi-square test invalid. In the paper, we develop an unbiased and efficient method of estimation and a chi-square test applicable for the regression with mild nonstationary volatilities in the errors. We provide some illustrations to demonstrate the empirical relevancy of the model and theory developed in the paper. For this purpose, examined are US consumption function, EURO/USD forward-spot spreads and capital-asset pricing models for some major NYSE stocks

Keywords: volatility; nonstationary nonlinear heteroskedasticity; regression with heteroskedastic errors; spurious regression; cointegration (search for similar items in EconPapers)
JEL-codes: C22 (search for similar items in EconPapers)
Date: 2004-08-11
New Economics Papers: this item is included in nep-ecm and nep-ets
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Related works:
Journal Article: Nonstationary nonlinear heteroskedasticity in regression (2007) Downloads
Working Paper: Nonstationary Nonlinear Heteroskedasticity in Regression (2005) Downloads
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