Effects of climate change on agricultural production and agricultural production and inflation: A panel data analysis

The aim of this study is to examine the effects of climate change on agricultural production by using panel data on a global scale. The study also aims to point out the significant impact of climate change on inflation by demonstrating the relationship between agricultural production and inflation with a simple regression model. Data concerning climate, agricultural production, land quality, land use, natural disasters and socioeconomic variables for 49 countries between 1961-2013 were compiled by using the annual data found from various sources such as the Climate Research Unit (CRU), the British Atmospheric Data Center (BADC), the Food and Agriculture Organization (FAO), the Emergency Events Database (EM-DAT), the National Aeronautics and Space Administration (NASA) and the World Development Index (WDI) and a panel data set was created. First, the structural breaks in climate variables were determined for these countries between 1901 and 2013, by using the Bai-Perron Multiple Structural Break Test. An increase was seen in the average temperatures of all countries without exception; whereas the diurnal temperatures, number of ground frost days, wet day frequency and potential evapotranspiration changes were found to vary from country to country. Secondly, the impact of climate on agricultural production was estimated with the aid of regression analysis. It was determined that variations in temperature and other variables affect the global agricultural production, which is limited by the sample, in a positive way; while precipitation and diurnal temperature changes have a negative effect. Finally, the Threshold Regression Model was used to analyze in which latitudes the effect differs. The model demonstrated that changes in precipitation affect the agricultural sector positively at low latitudes, and negatively at high degree latitudes. On the whole, the simple relationship between agricultural production and inflation exemplifies the potential and indirect impact of climate change on inflation. This study is one of the few studies which examines the effects of climate change on agricultural production by using panel data. Among these studies, it is the first one to apply the threshold value regression model which helps to determine the original break points by representing climate change most extensively. Keywords: Climate Change, Agricultural Production, Inflation, Bai-Perron Multiple Structural Break Test, Threshold Regression Model