Efficient information theoretic inference for conditional moment restrictions

Richard Smith ()
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Richard Smith: Institute for Fiscal Studies and University of Cambridge

No CWP14/05, CeMMAP working papers from Centre for Microdata Methods and Practice, Institute for Fiscal Studies

Abstract: The generalized method of moments estimator may be substantially biased in finite samples, especially so when there are large numbers of unconditional moment conditions. This paper develops a class of first order equivalent semi-parametric efficient estimators and tests for conditional moment restrictions models based on a local or kernel-weighted version of the Cressie-Read power divergence family of discrepancies. This approach is similar in spirit to the empirical likelihood methods of Kitamura, Tripathi and Ahn (2004) and Tripathi and Kitamura (2003). These efficient local methods avoid the necessity of explicit estimation of the conditional Jacobian and variance matrices of the conditional moment restrictions and provide empirical conditional probabilities for the observations.

Keywords: Conditional Moment Restrictions; Local Cressie-Read Minimum Discrepancy; GMM; Semi-Parametric Efficiency (search for similar items in EconPapers)
JEL-codes: C12 C13 C14 C20 C30 (search for similar items in EconPapers)
Pages: 40 pp.
Date: 2005-10-31
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (1)

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Related works:
Journal Article: Efficient information theoretic inference for conditional moment restrictions (2007)
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