This paper illustrates the use of Kullback-Leibler Information (KLI) measure for assessing the relative quality of two approximations to an unknown distribution from which we ca obtain simple random drawings.

This paper presents a new simulated maximum-likelihood method that rests on estimating the likelihood nonparametrically on a simulated sample. We prove that this method, which can be used on very general models, is consistent and asymptotically efficient.

The generalised method of moments (GMM) is combined with the nonparametric estimation of the instrument matrix to obtain an easily computable estimator for the panel probit model. It is based on the specification of the conditional mean of the binary dependent variable in each period, and...

In competing risks model, several failure times arise potentially. The smallest failure time and its index only are observed. In this paper, nonparametric kernel estimators of the joint distribution function of failure times conditional on the covariates are proposed. Their weak or strong...

In this paper we describe a solution to the problem of controlling the size of homoskedasticity tests in linear regression contexts.

In this paper we present a test statistic, which will be used to test for significant differences between generating processes of two time series that may be logically connected. The test statistic is based on the differences between estimated parameters of the autoregressive models which are...

Policy evaluation based on the estimation of dynamic stochastic general equilibrium models with aggregate macroeconomic time series rests on the assumption that a representative agent can be identified, whose behavioural parameters are independent of the policy rules. Building on earlier work by...

In this paper, the authors provide some asymptotic results for the J-type test on non-nested hypotheses proposed by Davidson and MacKinnon (1981), in the context of I(1) time series.