Economic assurance region in the evaluation of agricultural production systems

Abstract

Probability models are fit to productivity measures of rice, beans, milk, corn, soybeans and wheat using Brazilian time series data. In this exercise it is investigated the fit of the gamma, beta and normal truncated densities. The distributions suggested from this analysis are refit using the one step ahead confidence limits of the productivity measures and the 5% and 95% quantiles associated with the corresponding densities are determined. International market prices time series data are analyzed assuming stochastic trend and seasonality. The analysis is used to characterize financial risk limits for the commercialization of the commodities. The limits are adjusted locally and used in the economic risk evaluation of different production systems. Considering the six products and their production systems distribution among municipalities, 83% are potential candidates for insurance. There is no evidence that a given probability family is flexible. Each case demands a specific analysis.