GMM Estimation with Noncausal Instruments
AbstractLagged variables are often used as instruments when the generalized method of moments (GMM) is applied to time series data. We show that if these variables follow noncausal autoregressive processes, their lags are not valid instruments and the GMM estimator is inconsistent. Moreover, in this case, endogeneity of the instruments may not be revealed by the J-test of overidentifying restrictions that may be inconsistent and, as shown by simulations, its finite-sample power is, in general, low. Although our explicit results pertain to a simple linear regression, they can be easily generalized. Our empirical results indicate that noncausality is quite common among economic variables, making these problems highly relevant.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 23649.
Date of creation: Sep 2009
Date of revision:
Noncausal autoregression; instrumental variables; test of overidentifying restrictions;
Other versions of this item:
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-07-17 (All new papers)
- NEP-ECM-2010-07-17 (Econometrics)
- NEP-ETS-2010-07-17 (Econometric Time Series)
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