Efficient information theoretic inference for conditional moment restrictions

Abstract

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may AbstractThe 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. JEL Classification: C12, C13, C14, C20, C30.

Maximum Entropy Empirical Likelihood Methods Based on Laplace Transforms for Nonnegative Continuous Distribution with Actuarial Applications

“…Within this framework, MEEL estimators A. Luong are shown to be asymptotically first order equivalent to QL estimators using the same base. For the first and higher order properties of empirical likelihood estimators, see Newey and Smith [18], Smith [19].…”

Local GEL Methods for Conditional Moment Restrictions

“…See also Bonnal and Renault (2003) and Smith (2003) for analogous results for local CUE and efficient information theoretic estimators respectively.…”

“…Bonnal and Renault (2003) and Smith (2003), is readily seen to be a local GEL estimator when ρ(v) is quadratic; cf. NS, Theorem 2.1, which demonstrates an analogous result for unconditional moment restrictions.…”

“…2 An alternative local CUE more in the spirit of Hansen, Heaton, and Yaron (1996) would minimize Bonnal and Renault (2003) and Smith (2003). In contrast to the unconditional moment case, see NS, fn.1, the resultant CUE does not coincide withβ CUE .…”

“…In contrast, the empirical conditional probabilitiesπ ij employ the differential data-determined kernel weights w ij , (j = 1, ..., n), rather than equal weights 1/n resulting from the unconditional empirical distribution function. Kitamura and Stutzer (1997), and for quadratic ρ(v) or CUE, see Bonnal and Renault (2003) Back and Brown (1993) and Smith (2003). See also Brown and Newey (1992, 2002) and Smith (1997.…”