This study purposes to estimate climate change effect on agriculture sector in ASEAN by using the copula-based stochastic frontier approach to evaluate the technical efficiency and factors that affect agriculture production. Panel data of land, labour, fertilizer, and temperature in seven countries in ASEAN including Thailand, Vietnam, Myanmar, Philippines, Indonesia, Cambodia, and Malaysia collected from 2002 - 2016 were used for estimating the model. The results presented that the land, labour, and fertilizer consumption according to the agriculture have positive and significant effects on agricultural production. The most interesting point from this study, found that there is a negative effect on agriculture production related by the climate change. Additionally, this study provides the most appropriate tools to analyse climate change impacts on ASEAN agriculture and the potential options for adaptation in the agriculture sector.
This study purposed to forecast the Chinese tourism demand for Thailand. The time series data of Chinese tourists arriving in Thailand were estimated by using MS-AR Model, the consumer price index of Thailand, and the Thai exchange rate (THB/RMP) based on a monthly basis ranged between 2014 and 2019 collected from Ministry of Tourism and Sports, Bank of Thailand, and Ministry of Commerce, respectively. The results showed that the consumer price index of Thailand and the Thai exchange rate had a significant effect on Chinese tourism demand for Thailand. The most crucial point of this study demonstrated that the CPI could stimulate the tourism industry during the low season, so that the government can utilize or put some policies in effect for stimulating the tourism industry by controlling the CPI. In addition, this study provides the most appropriate tools to forecast the demand of Chinese tourism in Thailand and the potential options for adaption in the tourism sector.
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