China's regional tourism efficiency: A two-stage double bootstrap data envelopment analysis

This paper investigates tourism efficiency and its determinants using a two-stage double bootstrap approach for a global panel of 31 Chinese provinces over the period 2008-2013. Bias-corrected data envelopment analysis (DEA) efficiency scores were first calculated by employing the smoothed homogeneous bootstrapped procedure (Simar & Wilson, 2000). They were then regressed on a set of explanatory variables using the double-truncated regression approach. The results show that the tourism efficiency in China was low over the sample period. At the regional level, the average tourism efficiency in the east China was higher than central and west. The results also indicate that trade openness, climate change and intensity of market competition increase tourism efficiency. The study reveals several interesting and useful managerial insights and implications for tourism sector.