Cointegrating Polynomial Regressions: Fully Modified OLS Estimation and Inference

Hong, Seung Hyun and Wagner, Martin (March 2011) Cointegrating Polynomial Regressions: Fully Modified OLS Estimation and Inference. IHS Economics Series 264

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Abstract or Table of Contents

Abstract: This paper develops a fully modified OLS estimator for cointegrating polynomial regressions, i.e. for regressions including deterministic variables, integrated processes and powers of integrated processes as explanatory variables and stationary errors. The errors are allowed to be serially correlated and the regressors are allowed to be endogenous. The paper thus extends the fully modified approach developed in Phillips and Hansen (1990). The FM-OLS estimator has a zero mean Gaussian mixture limiting distribution, which is the basis for standard asymptotic inference. In addition Wald and LM tests for specification as well as a KPSS-type test for cointegration are derived. The theoretical analysis is complemented by a simulation study which shows that the developed FM-OLS estimator and tests based upon it perform well in the sense that the performance advantages over OLS are by and large similar to the performance advantages of FM-OLS over OLS in cointegrating regressions.;

Item Type: IHS Series
Keywords: 'Cointegrating polynomial regression' 'Fully modified OLS estimation' 'Integrated process' 'Testing'
Classification Codes (e.g. JEL): C12, C13, C32
Status: Published
Date Deposited: 26 Sep 2014 10:39
Last Modified: 21 Jul 2017 08:27
URI: http://irihs.ihs.ac.at/id/eprint/2047

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