Bayesian inference in moment condition models is difficult to implement. For these models, a posterior distribution cannot be calculated because the likelihood function has not been fully specified. In this paper, we obtain a class of likelihoods by formal Bayesian calculations that take into...

This article reviews a number of recent contributions to estimation and inference for models defined by moment condition restrictions. The particular emphasis is on the generalized empirical likelihood class of estimators as an alternative to the generalized method of moments. Estimation methods...

This paper proposes a GMM-based method for asymptotic confidence interval construction in stationary autoregressive models, which is robust to the presence of conditional heteroskedasticity of unknown form. The confidence regions are obtained by inverting the asymptotic acceptance region of the...

This paper studies the Minimum Divergence (MD) class of estimators for econometric models specified through moment restrictions. We show that MD estimators can be obtained as solutions to a computationally tractable optimization problem. This problem is similar to the one solved by the...

Abstract In many spatial applications, agents make discrete choices (e.g. operating or product-line decisions), and applied researchers need econometric techniques that enable them to model such situations. Unfortunately, however, most discrete-choice estimators are invalid when variables and/or...

It is now widely recognized that the most commonly used efficient two-step GMM estimator may have large bias in small samples. In this paper we analyze by simulation the finite sample bias of two classes of alternative estimators. The first includes estimators which are asymptotically...

This paper proposes novel methods for the construction of tests for models specified by unconditional moment restrictions. It exploits the classical-like nature of generalized empirical likelihood (GEL) to define Pearson-type statistics for over-identifying moment conditions and parametric...

We re-examine the empirical relevance of the cost channel of monetary policy (e.g. Ravenna and Walsh, 2006), employing recently developed moment-conditions inference methods, including identification-robust procedures. Using US data, our results suggest that the cost channel effect is poorly...

We re-examine the empirical relevance of the cost channel of monetary policy (e.g. Ravenna and Walsh, 2006), employing recently developed moment-conditions inference methods, including identiÂ…cation-robust procedures. Using US data, our results suggest that the cost channel effect is poorly...

GEL methods which generalize and extend previous contributions are defined and analysed for moment condition models specified in terms of weakly dependent data. These procedures offer alternative one-step estimators and tests that are asymptotically equivalent to their efficient two-step GMM...