Crop biotechnology, structure of primary production and socioeconomic changes in rural communities

Lower production costs, higher productivity, and reduced chemical requirements are generally claimed as attributes of biotechnology in crop production. These claims are not substantiated through the analysis of the changes in production structure. The changes in the structure of production are manifested in farm structural changes in the long-run. It is often argued that farm structural changes affect rural socioeconomic conditions. Hence, the relevant policy questions are what changes in the structure of crop production are caused by biotechnology, and how those changes can potentially affect farm-based rural economies. In order to generate empirical answers to these questions, this study investigates the impacts of crop biotechnology on the structure of production and their implications for socioeconomic changes in rural communities. Specifically, this study estimates the changes in the structure of production of corn and soybeans attributable to biotechnology, and the impacts of changes in overall structure of production on rural socioeconomic changes in Southern Ontario.; First, an index for crop biotechnology is developed on the basis of the rates of adoption and translog variable cost models are estimated employing the index along with a time trend. As evident in the results, the index explains about 2% of the total factor productivity growth. The results also indicate that the technology has contributed to an increase in the total production costs, increases in the costs of seed and custom work, and decreases in the costs of fertilizer, chemicals and the use of machinery. At the second stage, a model for population and employment changes in rural communities is developed and estimated by incorporating measures of relative changes in the structure of sectoral production in the region. The results indicate that the long-run impact of regional employment growth in the primary sector on local population change is negative, while that in the tertiary sector is positive. The results also suggest that the impacts of regional income in the primary sector and agglomeration of production on local employment growth are positive.