A Dynamic Analysis Of Sustainable Farming Systems In California Agriculture

The economic viability of alternative and more sustainable agriculture farming systems depend on the value of farm profits. These values may be estimated through short or long-run of profit maximization, but there is a difference in these methods. In short-run profit maximization the instantaneous marginal benefits are equated to the marginal costs of production. Where as in the long-run maximization of profits the capital value of soil resources are quantify in addition to the direct revenues and costs of each system over time. A long-run approach is fundamental to capture the value of capital improvements in soil resources. In this study we use short-run experimental data from SAFS's rotations to calibrate the crop simulation model EPIC, and obtain a time series cross-sectional data set for developing the dynamic bioeconomic models. With data from EPIC we are able to expand the existing short-run analysis, to estimate the long-run profitability and ecological benefits of alternative sustainable farming systems in comparison to conventional systems. Profit maximizing farmers who may not adopt sustainable methods based on short-run returns may well adopt them when long-run capital values are included. Finally, when environmental constraints are imposed on agricultural technology, for example to reduce non-point source pollution, results from our bioeconomic models are expected to show that sustainable technologies are more valuable.