Abstract
This paper employs a smoothed homogenous bootstrapped frontier approach to obtain data envelopment analysis (DEA) efficiency estimates for a more reliable efficiency ranking of Asian container ports. The paper applies desirable statistical properties to DEA efficiency estimates pertaining to consistency, unbiasedness, and estimation of confidence intervals. The paper uses a three-pronged analysis, first by identifying outliers using the log-ratio analysis; second, testing hypothesis with regard to global returns to scale employing a bootstrap methodology; and third, implementing the smooth homogenous bootstrap method to derive bias-corrected DEA efficiency estimates and to build confidence intervals. The results of the study enable individual ports to assess whether their production is efficient compared to their counterparts and indicate strategies for efficiency improvement.
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