This study investigated the impact of climate change on yield, harvested area, and production of sugarcane in Thailand using spatial regression together with an instrumental variable approach to address the possible selection bias. The data were comprised of new fine-scale weather outcomes merged together with a provincial-level panel of crops that spanned all provinces in Thailand from 1989–2016. We found that in general climate variables, both mean and variability, statistically determined the yield and harvested area of sugarcane. Increased population density reduced the harvested area for non-agricultural use. Considering simultaneous changes in climate and demand of land for non-agricultural development, we reveal that the future sugarcane yield, harvested area, and production are projected to decrease by 23.95–33.26%, 1.29–2.49%, and 24.94–34.93% during 2046–2055 from the baseline, respectively. Sugarcane production is projected to have the largest drop in the eastern and lower section of the central regions. Given the role of Thailand as a global exporter of sugar and the importance of sugarcane production in Thai agriculture, the projected declines in the production could adversely affect the well-being of one million sugarcane growers and the stability of sugar price in the world market.

The authors estimate the market impact of media coverage related to the name “swine flu,” relabeled subsequently as “2009 H1N1 flu,” on the future prices of lean hogs, live cattle, corn, and soybeans. They then quantified the revenue loss, employing the subset vector autoregressive model. The results indicate that the media coverage was associated with a significant and temporary negative impact on the futures prices of lean hogs, but with little impact on the other futures prices. The impact persisted for about four months, yielding an April–December 2009 market revenue loss of about $200 million (about 2.51 percent).

This article examined the effect of climate change on land use, yield, and production of cassava in Thailand, employing the panel data analysis between 1989 and 2016. The spatial regression and the instrumental variable method with the generalized method of moment were employed to address the endogeneity problems with the unique climate dataset. The current article investigated that total rainfall and the La Niña event determined harvested area of cassava. In addition, the harvested area was decreased as the population density increased due to high demand for non-agricultural use. On the other hand, increased access to irrigation systems enhanced the harvested area of cassava. Considering the yield of cassava, we found an inverted U-shape relationship between yield and temperature. Moreover, this study revealed that climate variability, extreme events and technological progress statistically influenced cassava yields. By using the climate projections during 2046–2055, we found that harvested area and yield of cassava were projected to reduce 12.49–16.05% and 2.57–6.22% from the baseline. As a result, cassava production in Thailand was predicted to decline 14.74–21.26% from the baseline. The well-being of a half-million farmers in Thailand plus actors in the global supply chain of cassava will be vulnerable to climate change.