/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 …

We use a subsample bootstrap method to get a consistent estimate of the asymptotically optimal choice of the …

determined with a permutation procedure and a parametric bootstrap in the testsfor serial independence and linearity …

transmission modelling framework. In addressing this issue, this paper introduces and applies parametric bootstrap techniques to … alternative asymmetric price transmission models under various error and sample size conditions. The results of the bootstrap … simulations indicate that model selection performance depends on bootstrap sample size and the amount of noise in the data …

.S., using the bootstrap Granger (temporal) non-causality test and a fixed-size rolling-window estimation approach. We use … full-sample bootstrap non-Granger causality test result suggests the existence of a unidirectional causality running from … cannot rely on the full-sample causality tests and, hence, this warrants a time-varying (bootstrap) rolling-window approach …

.S., using the bootstrap Granger (temporal) non-causality test and a fixed-size rolling-window estimation approach. We use … full-sample bootstrap non-Granger causality test result suggests the existence of a unidirectional causality running from … cannot rely on the full-sample causality tests and, hence, this warrants a time-varying (bootstrap) rolling-window approach …

positive efficiency and technology change. The bootstrap analysis reveals that these improvements are ascribed to 50% of the …

-optimally weighted SQLR statistic; (5) the consistency of the nonparametric bootstrap and the weighted bootstrap (possibly non …