This paper studies the Hodges and Lehmann (1956) optimality of tests in a general setup. The tests are compared by the exponential rates of growth to one of the power functions evaluated at a fixed alternative while keeping the asymptotic sizes bounded by some constant. We present two sets of...

This paper proposes Pearson-type statistics based on implies probabilities to detect structural change. The class of generalized empirical likelihood estimators (see Smith (1997)) assigns a set of probabilities to each observation such that moment conditions are satisfied. These restricted...

This paper examines structural change tests based on generalized empirical likelihood methods in the time series context. Standard structural change tests for GMM with strongly identified parameters are adapted to the GEL context. We show that when moment conditions are properly smoothed, these...

This paper proposes Pearson-type statistics based on implied probabilities to detect structural change. The class of generalized empirical likelihood estimators (see Smith (1997)) assigns a set of implied probabilities to each observation such that moment conditions are satisfied. The proposed...

This paper proposes Pearson-type statistics based on implied probabilities to detect structural change. The class of generalized empirical likelihood estimators (see Smith, 1997) assigns a set of probabilities to each observation such that moment conditions are satisfied. These restricted...

Finite sample approximations for the distribution functions of Generalized Empirical Likelihood (GEL) are derived using Edgeworth expansions. The analytical results obtained are shown to apply to most of the common extremum estimators used in applied work in an i.i.d. sampling context. The GEL...

A simple saddlepoint (SP) approximation for the distribution of generalized empirical likelihood (GEL) estimators is derived. Simulations compare the performance of the SP and other methods such as the Edgeworth and the bootstrap for special cases of GEL: continuous updating, empirical...

This paper studies large deviation properties of the generalized method of moments and generalized empirical likelihood estimators for moment restriction models. We consider two cases for the data generating probability measure: the model assumption and local deviations from the model...

This paper studies moderate deviation behaviors of the generalized method of moments and generalized empirical likelihood estimators for generalized estimating equations, where the number of equations can be larger than the number of unknown parameters. We consider two cases for the data...

The maximum likelihood estimator (MLE) under the normality assumption of error terms is widely used to estimate the Box-Cox transformation model. However, since the error terms cannot be normally distributed, it is not a proper estimator. In other words, the estimator is inconsistent. In this...