Empirical Evidence Concerning the Finite Sample Performance of EL-Type Structural Equation Estimation and Inference Methods

Ron Mittelhammer (), George Judge () and Ron Schoenberg

No 25090, CUDARE Working Papers from University of California, Berkeley, Department of Agricultural and Resource Economics

Abstract: This paper presents empirical evidence concerning the finite sample performance of conventional and generalized empirical likelihood-type estimators that utilize instruments in the context of linear structural models characterized by endogenous explanatory variables. There are suggestions in the literature that traditional and non-traditional asymptotically efficient estimators based on moment equations may, for the relatively small sample sizes usually encountered in econometric practice, have relatively large biases and/or variances and provide an inadequate basis for estimation and inference. Given this uncertainty we use a range of data sampling processes and Monte Carlo sampling procedures to accumulate finite sample empirical evidence concerning these questions for a family of generalized empirical likelihood-type estimators in comparison to conventional 2SLS and GMM estimators. Solutions to EL-type empirical moment-constrained optimization problems present formidable numerical challenges. We identify effective optimization algorithms for meeting these challenges.

Keywords: Research; Methods/; Statistical; Methods (search for similar items in EconPapers)
Pages: 36
Date: 2003
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Citations: View citations in EconPapers (5)

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Working Paper: Empirical Evidence Concerning the Finite Sample Performance of EL-Type Structural Equation Estimation and Inference Methods (2003)
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Persistent link: https://EconPapers.repec.org/RePEc:ags:ucbecw:25090

DOI: 10.22004/ag.econ.25090

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