The effects of individual crop payments on the cost of food

Abstract

This thesis focuses on the question of the effect of commodity pricing and Federal programs on the cost of food in the United States. For many decades the debate around subsidy payments has been argued in the halls of Congress and in farm fields across the country. Corn, wheat, and soybeans are the three largest crops subsidized in the United States today; arguably, the prices of these crops are influenced by subsidy payments. The goal of this thesis is to determine the effects of the prices of the top three subsidized crops on the thrifty market basket for families for four published by the USDA, factoring in transportation costs, market spread, agricultural technology advancements, and market value share. Previous studies have focused on direct subsidy payments as a whole and their aggregate influence on the price of food. This paper builds on the past studies by evaluating the effects of crop-specific programs on the cost of food. Econometric regression analysis was used to analyze the data gathered to support or refute the hypothesis that commodity prices and Federal payments do influence the cost of food. Initially data were gathered from January 1960 to December 2012. The data were adjusted for inflation using the Producer Price Index and Consumer Price Index where appropriate. After multiple attempts of modeling it was discovered that data from 1960 to 1970 needed to be discarded due to the difference in the market basket price calculations from the rest of the series. Furthermore, the model was adjusted based on the presence of multicollinearity, and the Hildreth-Lu Method was utilized to correct for the autocorrelation in error. The regression results illustrated that the only commodity of the three considered in the study that had a positive and statistically significant impact on the cost of food over the sample period was corn (p-value = 0.005). The coefficients on wheat and soybean prices were statistically insignificant. The historical fuel price had the expected positive sign and was statistically significant. The agricultural technology factor was not significant. The results also suggested that the cereal grains supply chain has significantly increased the cost of food. Both the cereal grain farm value share and the retail-to-farm spread for cereal grains were statistically significant (p-value < 0.000) with positive coefficients. The price spread of fruit was statistically significant, (p-value = 0.000), but the farm value was not. The regression results were initially surprising for the crop price variables. The overall analysis supports previous studies that crop subsidies alone may not have impacted food prices per se, but biofuel policies may have had unintended consequences. Crop-specific results provide more information to consider when discussing The Farm Bill and the implications of such a complicated and omnibus piece of legislation.