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

Timothy Vogelsang and Martin Wagner

No 263, Economics Series from Institute for Advanced Studies

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.

Keywords: Bandwidth; cointegration; fixed-b asymptotics; Fully Modified OLS; IM-OLS; kernel (search for similar items in EconPapers)
JEL-codes: C31 C32 (search for similar items in EconPapers)
Pages: 43 pages
Date: 2011-01
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 (2)

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https://irihs.ihs.ac.at/id/eprint/2037 First version, 2011 (application/pdf)

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Journal Article: Integrated modified OLS estimation and fixed-b inference for cointegrating regressions (2014)
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