(AIC) is used for model selection. Moreover, a likelihood ratio test is performed for the nested models. A bootstrap …

find that, by using the bootstrap technique to estimate confidence intervals, we can point at the uncertainty of the …

also significant. Additionally, bootstrap method is applied to explore the contextual factors influencing the efficiency …

requirements that are not always obvious to the non-expert user. Bootstrap DEA is a significant development of the past decade …, which could be extended to test almost any hypothesis in bootstrap DEA. Moreover, it enhances the intuition behind bootstrap …

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 … coverage probabilities are not a good tool of assessment. In our study we evaluate the performance of bootstrap DEA using the …

/methodology/approach – A bootstrap method is used to provide statistical precision of the DEA estimator. Technical efficiency is modeled as a … operation. Originality/value – The study is among the first that employ a bootstrap method and compare estimates from both Data …

analysis and a Malmquist productivity index. The estimates are bias-corrected using a bootstrap approach recently developed for …

This paper demonstrates that the bootstrap procedure suggested by Ferrier and Hirschberg (1997) gives inconsistent …

This paper considers the provision of some important municipal services and applies the non-parametric double bootstrap … inference are invalid, and they develop a bootstrap approach that yields valid inference in second stage regressions when these …