Cointegrating Polynomial Regressions: Fully Modified OLS Estimation and Inference

Wagner, Martin and Hong, Seung Hyun (2015) Cointegrating Polynomial Regressions: Fully Modified OLS Estimation and Inference. Econometric Theory.

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Abstract or Table of Contents

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

Item Type: Article in Academic Journal
Status: Published
Date Deposited: 09 Dec 2015 08:53
Last Modified: 01 Apr 2016 14:20
Identification Number or DOI: 10.1017/S0266466615000213
ISSN: 0266-4666

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