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Title: Estimation of error correction model with measurement errors Authors:  Sung Ahn - Washington State University (United States) [presenting]
Abstract: Effects of measurement errors on the analysis of error correction models (ECMs) of vector processes observed with measurement errors were studied previously. It was found that statistically undesirable effects on the analysis attributable to endogeneity in the ECM induced by measurement errors, even in their simplest form. Therefore, we propose a method using instrumental variables and derive the asymptotic distributions of the reduced rank estimator that eliminate the undesirable effect of endogeneity. We also propose a method of using a moving-average term to deal with endogeneity. These methods yield estimators that are consistent and asymptotically unbiased. We investigate the effects of the measurement errors on the proposed methods through a Monte Carlo simulation study.