Three Essays on the Economics of Climate Impacts on Agriculture

Abstract

Global warming has been a hot issue lately all around world not only because it has been in increasing trend since 1980s but also affects many economic sectors as well as different aspect of human life. The three essays of this dissertation investigate the impacts of climate change on the agricultural sectors of the United States and the selected Asian countries using the pooled cross-section model and the panel analysis. The first essay analyzes the impact of climate change on agricultural production in 13 Asian countries from 1998 and 2007. This study estimates a country-level fixed effect (FE) panel model for agricultural production using seasonal and annual climate variables as well as production input variables. According to Mendelsohn et al., (2000; 2004), high latitude countries that are currently cool will likely benefit from warming. However, regions those are already hot such as low latitude countries will be vulnerable to climate change. The results in this study show that higher summer temperatures and more precipitations increase agricultural production while higher fall temperature is harmful in South and Southeast Asia. On the other hand, higher annual temperature decreases agricultural production in Asian countries. The second essay estimates the climate change effects on the U.S. agriculture using the pooled cross-section farm profit model mainly using the annual Agricultural Resource Management Survey (ARMS) data from USDA for the time period between 2000 and 2009 in the 48 contiguous States. For climate measure, growing season drought indices (the Palmer Drought Severity Index (PDSI) and Crop Moisture Index (CMI)) are applied to the analysis and both indices have a negative relationship with temperature. The estimates indicate that one unit increase in PDSI (CMI) leads to 5.5% (13.9%), 4% (9%), and 5% (14%) increase in farm profits for all farms, crop farms, and livestock farms. In the third essay, I use a static labor supply model to estimate the impact of weather on the farmers’ on-farm labor supply directly unlike the previous literature. The results suggest that there is an inverse U-shape relationship between temperature and farmers’ labor supply. Farmers’ labor supply is minimized between 50-70 degrees Fahrenheit. Consequently, it can be concluded that temperature is a substitute for labor until around 60 degrees. However, more labor is required after the temperature passes that threshold. Unlike temperature, the relationship between precipitation and labor supply is linear. The more precipitation a farm gets throughout the year, the more labor is supplied by the farmer. This is maybe because of the possibility that in my data set the observed precipitation may be already in the optimal range. The results show that precipitation and labor are complements.