Integrated Modified OLS Estimation and Fixed-b Inference for Cointegrating Regressions

Vogelsang, Timothy J. and Wagner, MartinORCID: https://orcid.org/0000-0002-6123-4797 (January 2011) Integrated Modified OLS Estimation and Fixed-b Inference for Cointegrating Regressions. Former Series > Working Paper Series > IHS Economics Series 263

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Abstract

Abstract: This paper is concerned with parameter estimation and inference in a cointegrating regression, where as usual endogenous regressors as well as serially correlated errors are considered. We propose a simple, new estimation method based on an augmented partial sum (integration) transformation of the regression model. The new estimator is labeled Integrated Modified Ordinary Least Squares (IM-OLS). IM-OLS is similar in spirit to the fully modified approach of Phillips and Hansen (1990) with the key difference that IM-OLS does not require estimation of long run variance matrices and avoids the need to choose tuning parameters (kernels, bandwidths, lags). Inference does require that a long run variance be scaled out, and we propose traditional and fixed-b methods for obtaining critical values for test statistics. The properties of IM-OLS are analyzed using asymptotic theory and finite sample simulations. IM-OLS performs well relative to other approaches in the literature.;

Item Type: IHS Series
Keywords: 'Bandwidth' 'Cointegration' 'Fixed-b asymptotics' 'Fully Modified OLS' 'IM-OLS' 'Kernel'
Classification Codes (e.g. JEL): C31, C32
Date Deposited: 26 Sep 2014 10:39
Last Modified: 03 Dec 2024 07:00
ISBN: 1605-7996
URI: https://irihs.ihs.ac.at/id/eprint/2037

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