The purpose of this research is to investigate the implications of tobacco control policies and measure how these have brought about structural changes in Thailand’s tobacco leaf exports. The methodology involved employing secondary data to estimate the econometrics model and then utilizing the Chow test. The findings showed that the estimates from the econometrics model reflect the income elasticity of the real export value of 6.621. In the Chow test, a statistically significant (at 0.05) structural change in Thailand’s tobacco leaf export was apparent when comparing the results before and after the first quarter of 2010. Furthermore, since 2010 the exports have shifted from the old market to other ASEAN countries, namely Indonesia, the Philippines, Malaysia, and Lao PDR. Concerning the practical implications, from a public health perspective, the results provide evidence for the efficiency of tobacco control policies and measures in European countries, the US, and Australia. On the other hand, they also pinpoint an area of improvement for tobacco control policies in ASEAN countries, and further investigation is required. From an economic perspective, Thai tobacco farmers need to be supported by the government during the transition period.
The real business cycles in ASEAN-5 countries namely Indonesia, Malaysia, the Philippines, Thailand, and Vietnam over 1971-2015 fluctuated more than their agricultural business cycles. This research utilized the two-sector real business cycle model developed by Da-Rocha and Restuccia (2002) to stimulate such a stylized fact. The model assumes that a social planner makes a decision in an initial period to choose the consumption, capital stock, and working hours in the agricultural and non-agricultural sectors. This will enable a representative agent to attain optimum utility for the entire life under certain economic restrictions and subject to technology shocks occurring in both sectors. The mathematical methods applied to solve this decision-making problem for the social planner includes linear quadratic approximations and stochastic dynamic programming methods. The simulation results suggest that the applied model could reasonably well replicate the fluctuations of the real business cycle, agricultural business cycle, and the non-agricultural business cycle. This reflects the situation where technology shocks in the agricultural and non-agricultural sectors are related to each other and influence the volatility of these two economies.This suggest that the governments should encourage research and development activities in both agricultural and non-agricultural sectors to develop new technology that can generate technology shock to promote greater economic strength.
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