Ramirez, Octavio A.
This study hypothetically analyzes the distribution of the premiums paid and thus the subsidies received by farmers participating in the Risk Management Agency (RMA) multi-peril crop insurance program. The results show a wide spread in the effective subsidy levels, to where some producers might not be receiving any subsidies at all (i.e., they actually pay close to their full actuarially fair premium), while others only pay a small fraction of their actuarially fair premium. More importantly, the results show that “shrinkage” estimators such as the one used by the RMA have the unintended negative consequence of disproportionally subsidizing farmers who are less effective in managing risk. Producers whose farms exhibit higher downside yield variability receive much more generous subsidies than those with lower levels of yield variability.
The relative importance of income earning potential versus consumptive values in setting ranchland prices is examined using a truncated hedonic model. The market value of New Mexico ranches is related to annual income earning potential and other ranch characteristics including ranch size, location, elevation, terrain, and the amount of deeded, public, and state trust land on the ranch. We found ranch income to be a statistically important determinant of land value, but yet a relatively small percentage of ranch value was explained by income earnings. Ranch location, scenic view, and the desirable lifestyle influenced ranch value more than ranch income.
The performance of a proposed asymmetric-error GARCH model is evaluated in comparison to the normal-error- and Student-t-GARCH models through three applications involving forecasts of U.S. soybean, sorghum, and wheat prices. The applications illustrate the relative advantages of the proposed model specification when the error term is asymmetrically distributed, and provide improved probabilistic forecasts for the prices of these commodities.
This study analyzes the risks of diversified tropical cropping systems that combine cocoa, plantain, and tree-crop components in different proportions versus traditional monocultures. A technique for modeling the expected values, variances, and covariances of correlated time-series variables that are autocorrelated and nonnormal (right or left skewed and kurtotic) is applied to simulate commodity prices. The importance of using simulated cumulative density functions (cdf's) which reflect the most important characteristics of the stochastic behavior of prices for analyzing risk and returns of diversified agricultural systems is demonstrated. The analysis priovides evidence in favor of diversified cocoa-plantain-Cordia agroforestry system technologies versus the traditional monocultures.
Recently developed techniques are adapted and combined for the modeling and simulation of crop yields and prices that can be mutually correlated, exhibit heteroskedasticity or autocorrelation, and follow nonnormal probability density functions. The techniques are applied to the modeling and simulation of probability distribution functions for the returns of three tropical agroforestry systems for coffee production. The importance of using distribution functions that can more closely reflect the statistical behavior of yields and prices for risk analysis is discussed and illustrated.