Forecasts of economic time series are often evaluated according to their accuracy as measured by either quantitative precision or qualitative reliability. We argue that consumers purchase forecasts for the potential utility gains from utilizing them, not for their accuracy. Using Monte Carlo...

Resurgent cotton production compels better acreage forecasts for planning seed, chemical, and other input requirements. Structural models describe leading acreage response indicators, and forecasts are compared to time-series models. Cotton price, loan rate, deficiency payments, lagged corn...

An adaptive regression model is employed for estimating pre- and post-boll weevil eradication cotton-acreage response. Results indicate cotton acreage becoming more inelastic to own- and cross-price changes. As a result of this shift in acreage response and yield increases from eradication, net...

Forecast users and market analysts need quality forecast information to improve their decision-making abilities. When more than one forecast is available, the analyst can improve forecast accuracy by using a composite forecast. One of several approaches to forming composite forecasts is a...

A restricted profit function model of California agriculture is specified and estimated subject to prior information provided by economic theory. Symmetry, homogeneity, and convexity of the profit function are maintained in the estimation. Parameter estimates and elasticities are presented for...

Resurging southeastern cotton production compels better cotton acreage forecasts for planning seed, chemical, and other input requirements. Structural models describe leading acreage response indicators, and forecasts are compared time-series models. Cotton price, loan rate, deficiency payments,...