Since the introduction of bootstrap DEA there is a growing literature on applications which use this method, mainly for hypothesis testing. It is therefore important to establish the consistency and evaluate the performance of bootstrap DEA. The few Monte Carlo experiments in the literature...

The ability of six alternative bootstrap methods to reduce the bias of GMM parameter estimates is examined in an instrumental variable framework using Monte Carlo analysis. Promising results were found for the two bootstrap estimators suggested in the paper.

We extend the method of indirect inference testing to data that is not filtered and so may be non-stationary. We apply the method to an open economy real businss cycle model on UK data. We review the method using a Monte Carlo experiment and find that it performs accurately and has good power.

Motivated by a recent study of Bao and Ullah (2007a) on finite sample properties of MLE in the pure SAR (spatial autoregressive) model, a general method for third-order bias and variance corrections on a nonlinear estimator is proposed based on stochastic expansion and bootstrap. Working with...

Our study analyses stochastic convergence of relative real GDP per capita in the West African Economic and Monetary Union (WAEMU) in the period 1960 to 2010. It highlights the importance of considering structural breaks and cross-section dependence in the panel unit root tests. Using the panel...

We extend the method of indirect inference testing to data that is not filtered and so may be non-stationary. We apply the method to an open economy real business cycle model on UK data. We review the method using a Monte Carlo experiment and find that it performs accurately and has good power.

In studying the asymptotic and finite-sample properties of quasi-maximum likelihood (QML) estimators for the spatial linear regression models, much attention has been paid to the spatial lag dependence (SLD) model; little has been given to its companion, the spatial error dependence (SED) model....

In this paper we define a set of Indirect Inference estimators based on moment approximations of the auxiliary ones. Their introduction is motivated by reasons of analytical and computational facilitation. Their definition provides an indirect inference framework for some "classical" bias...

Identification in the context of multivariate state space modelling involves the specification of the dimension of the state vector. One identification approach requires an estimate of the rank of a Hankel matrix. The most frequently used approaches of rank determination rely on information...

Five alternative techniques have been applied to measure the degree of uncertainty associated with the forecasts produced by a macro-model of the French economy, the Mini-DMS developed at INSEE. They are bootstrap, analytic simulation on coefficients, Monte Carlo on coefficients, parametric...