Neyman and Scott (1948) define the incidental parameter problem. In panel data with T observations per individual and unobservable individual-specific effects, the inconsistency of the maximum likelihood estimator of the common parameters is in general of the order 1/T. This paper considers the...

Neyman and Scott (1948) define the incidental parameter problem. In panel data with T observations per individual and unobservable individual-specific effects, the maximum likelihood estimator of the common parameters is in general inconsistent. This paper develops the integrated moment...

We reconsider the efficiency bound for the semi-parametric Mixed Proportional Hazard (MPH) model with parametric baseline hazard and regression function. This bound was first derived by Hahn (1994). One of his results is that if the baseline hazard is Weibull, the efficiency bound is singular,...

Using many moment conditions can improve efficiency but makes the usual generalized method of moments (GMM) inferences inaccurate. Two-step GMM is biased. Generalized empirical likelihood (GEL) has smaller bias, but the usual standard errors are too small in instrumental variable settings. In...

Properties of GMM estimators are sensitive to the choice of instruments. Usingmany instruments leads to high asymptotic asymptotic efficiency but can causehigh bias and/or variance in small samples. In this paper we develop and implementasymptotic mean square error (MSE) based criteria for...

The main objective of this paper is to propose a feasible, model free estimator of the predictive density of integrated volatility. In this sense, we extend recent papers by Andersen et a]. [Andersen, T.G., Bollerslev,T., Diebold, FX, Labys, P., 2003. Modelling and forecasting realized...

This article makes two contributions. First, we outline a simple simulation-based framework for constructing conditional distributions for multifactor and multidimensional diffusion processes, for the case where the functional form of the conditional density is unknown. The distributions can be...

This paper outlines a testing procedure for assessing the relative out-of-sample predictive accuracy of multiple conditional distribution models, and surveys existing related methods in the area of predictive density evaluation, including methods based on the probability integral transform and...