AN EMPIRICAL INVESTIGATION OF THE DISTRIBUTION OF MODIFIED LIML ESTIMATORS FOR EQUATIONS WITH MORE THAN TWO ENDOGENOUS VARIABLES

SUMMARY. In this paper we consider the general problem of estimation and inference in stochastic simultaneous equations. We discuss a class of modified limited information max-imum likelihood estimators called scaled down LIML estimators. One of these estimators is asymptotically unbiased to order σ2 and a second one is minimum mean square to order σ4. Based on the unbiased estimator, asymptotic tests of hypotheses are proposed. Simulation results indicate that these tests perform better compared to traditional tests. In this paper we consider the general problem of estimating the coefficients of a structural equation and the associated problem of testing hypotheses concern-ing the coefficients. In most applications standardized statistics based on limited information maximum likelihood (LIML) or two stage least squares (TSLS) es