In this paper, I develop a quasi empirical likelihood estimator that has good finite-sample properties when there are many moment conditions. I show that the quasi empirical likelihood estimator, which uses semiparametric efficient estimation, is an approximation to the empirical likelihood...

Finite-sample inference methods are developed for quantile regression models. The methods are conservative in that (i) they apply to arbitrary sample sizes without the liberal assumption that sample sizes approach infinity, (ii) they apply when the quantiles are partially or set identified,...

We propose a novel statistic to test the rank of a matrix. The rank statistic overcomes deficiencies of existing rank statistics, like: necessity of a Kronecker covariance matrix for the canonical correlation rank statistic of Anderson (1951), sensitivity to the ordering of the variables for the...

In this paper we extend the setting analysed in Hahn and Hausman (2002a) by allowing for conditionally heteroscedastic disturbances. We start by considering the type of conditional variance-covariance matrices proposed by Engle and Kroner (1995) and we show that, when we impose a GARCH...

In this paper we extend the setting analysed in Hahn and Hausman (2002a) by allowing for conditionally heteroscedastic disturbances. We start by considering the type of conditional variance-covariance matrices proposed by Engle and Kroner (1995) and we show that, when we impose a GARCH...

We show that the higher order biases of instrumental variable statistics in the strong instrument case indicate the degeneracy of the first order asymptotic distributions of these statistics under weak or many instrument asymptotics. We express the higher order approximations using an estimator...

We construct higher order expressions for Wald and Lagrange multiplier (LM) GMM statistics that are based on 2step and continuous updating estimators (CUE). We show that the sensitivity of the limit distribution to weak and many instruments results from superfluous elements in the higher order...

This paper is concerned with Bayesian reduced rank regression when instruments are weak. There have been a number of studies on weak identification problem with the application of reduced rank regression combined with singular value decomposition (SVD) method in the Bayesian framework, see...

A new model is developed that augments a structural VAR specification with a GARCH covariance matrix. The model is utilised to study time series dependencies between three size-sorted portfolios from the Australian Stock Exchange. Even after accounting for contemporaneous correlations the...