Production Efficiency of Jasmine Rice Producers in Northern and North‐eastern Thailand

The paper jointly evaluates the determinants of switching to Jasmine rice and its productivity while allowing for production inefficiency at the level of individual producers. Model diagnostics reveal that serious selection bias exists, justifying use of a sample selection framework in stochastic frontier models. Results from the probit variety selection equation reveal that gross return (mainly powered by significantly higher Jasmine rice price), access to irrigation and education are the important determinants of choosing Jasmine rice. Results from the stochastic production frontier reveal that land, irrigation and fertilisers are the significant determinants of Jasmine rice productivity. Significantly lower productivity in Phitsanulok and Tung Gula Rong Hai provinces demonstrate the influence of biophysical and environmental factors on productivity performance. The mean level of technical efficiency is estimated at 0.63 suggesting that 59% [(100 ? 63)/63] of the productivity is lost due to technical inefficiency. Policy implications include measures to keep Jasmine rice price high, increase access to irrigation and fertiliser availability, as well as investment in education targeted to farm households which will synergistically increase adoption of Jasmine rice as well as farm productivity.     

An empirical study of inbound tourism demand in China: a copula-GARCH approach

This paper proposes new models for analyzing the volatility and dependence of monthly tourist arrivals to China applying a copula-GARCH approach. A desegregation of the top six origins of China inbound tourists from the period January 1994 to December 2013 is used in this study. The empirical results show that there is a strong seasonal effect in all cases and ?????? some habit persistence on monthly tourist arrival growth rate for South Korea, Russia, the United States (US), and Malaysia. Second, the volatilities of arrival growth rates to China are impacted significantly by their own short- and long-run effects, except for Russia and South Korea. Only short-run shock affects Russian arrivals while only long-run shocks are affecting South Korea arrivals. Third, the conditional dependence among different source countries is found to be positive and significant, but the conditional dependence for all considered pairs is low. Moreover, there is extreme co-movement (tail dependence) between the six major tourism source countries, suggesting the pairwise of international tourist arrivals shows a related increasing or decreasing pattern during extreme events. Implications are discussed and recommendations provided.     

Modelling dependence between tourism demand and exchange rate using the copula-based GARCH model

This paper investigates dependence between tourism demand and exchange rate, using the case of China, and from a new perspective by using copula–GARCH models. The empirical results show that the volatility of exchange rate is not a determinant factor in fluctuation of China's inbound tourism demand from the countries being studied. Furthermore, only Russia exhibits risk-adverse behaviour with extreme SUR depreciation, or CNY appreciation associated with an extreme decline in arrivals. Third, introducing the tail dependence and dynamic dependence between growth rates of tourism demand and exchange rate add much to the explanatory ability of the model. The findings of this study have important implications for destination manager and travel agent as it helps to understand the impact of exchange rates on China inbound tourism demand and provide a complementary academic approach on evaluating the role of exchange rates in the international tourism demand model.