Simulation based selection of competing structural econometric models
This paper proposes a formal model selection test for choosing between two competing structural econometric models. The procedure is based on a novel lack-of-fit criterion, namely, the simulated mean squared error of predictions (SMSEP), taking into account the complexity of structural econometric models. It is asymptotically valid for any fixed number of simulations, and allows for any estimator which has a asymptotic normality or is n[alpha]-consistent for [alpha]>1/2. The test is bi-directional and applicable to non-nested models which are both possibly misspecified. The asymptotic distribution of the test statistic is derived. The proposed test is general, regardless of whether the optimization criteria for estimation of competing models are the same as the SMSEP criterion used for model selection. A Monte Carlo study demonstrates good power and size properties of the test. An empirical application using timber auction data from Oregon illustrates the usefulness and generality of the proposed testing procedure.
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