Resumen
Price volatility is a significant risk factor affecting the income of farmers in the agriculture sector, especially for international trade in products such as coffee in Thailand. This study proposes an alternative model to analyze the major factors in terms of internal and external factors, which are expected to affect price volatility simultaneously, by applying multiple exogenous Bayesian GARCH-X models. The empirical results of the comparison between the multiple exogenous Bayesian GARCH-X model and the standard Bayesian GARCH-X model, which estimated the impact of individual exogenous variables separately, show that the standard error of the first model is the smallest compared to the others, which means the multiple exogenous Bayesian GARCH-X model is more fitted to the data than the others. The results indicate that the increase in demand for manufactories for coffee beans in Thailand (TDD) and coffee bean export volume in Indonesia (INEX) leads to an increase in the volatility of raw coffee prices. On the other hand, if coffee bean export volume in Brazil (BEX) increases, this will cause a decrease in the volatility of raw coffee bean prices. Therefore, the Thai government should carefully consider the changes in the production and marketing policies of those countries in the formulation of the coffee policy. The appropriate policy on coffee price volatility in Thailand should not concern only reduce the uncertainty in the coffee bean market but also consider the impact on the long-term income and livelihoods of coffee growers. Therefore, external factors of the competing countries should be taken into account in the coffee production policy.