Short-run and long-run performance of international tourism: Evidence from Bayesian dynamic models |
| |
Affiliation: | 1. Isenberg School of Management, University of Massachusetts-Amherst, 90 Campus Center Way, 209A Flint Lab, Amherst, MA 01003, USA;2. Management School, University of Liverpool, L69 7ZH, UK;3. Lancaster University Management School, LA1 4YX, UK |
| |
Abstract: | Measuring the technical efficiency of the tourism industry is essential for evaluating tourism sustainability and reshaping tourism activities. This paper introduces for the first time a new dynamic stochastic frontier model to 1-measure and compare the short-run and long-run technical efficiencies of leading tourism destinations, and 2-provide impulse response functions and persistence measures to trace out the dynamic effect of shocks in technical inefficiency. We develop our model in a Bayesian framework using carefully constructed Markov Chain Monte Carlo (MCMC) techniques. We report efficiency results and persistence scores for individual destinations and discuss how different destinations recover from shocks in tourism performance. |
| |
Keywords: | Short-run technical efficiency Long-run technical efficiency Bayesian dynamic model Tourism destinations |
本文献已被 ScienceDirect 等数据库收录! |
|