This brief note serves as a companion paper to Klein (2014). Small multiples incorporate graphical frameworks such as P value plots with ease, and thus facilitate visualizing quantitative data that record parameter change from simulation experiments. Pitfalls in layout may be avoided when...

Gravity type models are widely used in international economics. In these models the inclusion of time-fi0xed regressors like geographical or cultural distance, language and institutional (dummy) variables is often of vital importance e.g. to analyse the impact of trade costs on...

Cet article illustre l’applicabilité des méthodes de rééchantillonnage dans le cadre des tests multiples (simultanés), pour divers problèmes économétriques. Les hypothèses simultanées sont une conséquence habituelle de la théorie économique, de sorte que le contrôle de la...

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...

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...

We develop extensions of the variance-ratio statistic for testing the hypothesis a time series is uncorrelated and investigate their finite-sample performance. The tests employ an estimator of the asymptotic covariance matrix of the sample autocorrelations that is consistent under the null for...

This paper shows how a high level matrix programming language may be used to perform Monte Carlo simulation, bootstrapping, estimation by maximum likelihood and GMM, and kernel regression in parallel on symmetric multiprocessor computers or clusters of workstations. The implementation of...

Propensity score matching is a widely-used method to measure the effect of a treatment in social as well as health sciences. An important issue in propensity score matching is how to select conditioning variables in estimation of the propensity score. It is commonly mentioned that only variables...

In panel data the interest is often in slope estimation while taking account of the unobserved cross sectional heterogeneity. This paper proposes two nonparametric slope estimation where the unobserved effect is treated as fixed across cross section. The first estimator uses first-differencing...

This paper elaborates on the deleterious effects of outliers and corruption of dataset on estimation of linear regression coefficients by the Ordinary Least Squares method. Motivated to ameliorate the estimation procedure, we have introduced the robust regression estimators based on Campbell’s...