The failure to allow for significant crop quality effects in a partial-equilibrium model can lead to misleading inferences about the price, output and welfare implications of air quality improvements. It has been observed that air pollutants such as ozone, sulphur dioxide, and nitrogen dioxide affect the yield and quality of many crops. The economic benefit from improving air quality in crop producing regions has been measured using a partial-equilibrium approach which accounts only for supply shifting yield effects. It is shown that a yield-effect only model will underestimate output increases and benefits from an air quality improvement when commodity quality improvements as well as yield increases are forthcoming.

The price and quantity effects of a forthcoming biotechnology product, bovine growth hormone (bGH), are explored in a simple partial equilibrium model. The model is based on previous theoretical work on technological change but is developed in terms of a sector output. A particular output curve is estimated using data from a random sample of New York State dairy farms. Information on the farm level production effects of bGH is used to shift the output curve and to solve for equilibrium levels of price and output. The model projects the bGH may lead to the exit of 5,400 New York dairy farms and a 20 percent reduction in herd size. Consumers will benefit from an approximately 30 percent drop in milk price. The effect on gradual diffusion of bGH on farm numbers is considered. To accommodate this technology policies encouraging an orderly transfer of resources out of the dairy sector should be examined.

Although energy substitution in U.S. manufacturing has been studied in great depth at the national level, little attention has been paid to the regional level. However, regions may differ in their use of energy for a variety of reasons. The main objective of this study is to estimate region-specific demands for energy using a dynamic model for two-digit SIC Code manufacturing sectors. We derive own and cross-price elasticities for energy for different regions and we compare them. We, thus, provide information which has implications for a region specific energy policy.

Assessments of the NJARE and other agricultural economic journals by faculty in the Northeast Region were contrasted to those made by faculty in other regions. Faculty in the Northeast judged the NJARE to be of high professional quality and personal usefulness and felt that the NJARE had made substantial quality improvements. A strong regional character in the NJARE was evidenced by low journal participation rates by faculty in other regions. Impacts of recent changes in the Journal and the need for future assessments were discussed.

Milk supply response was estimated for Pennsylvania using three different levels of structural aggregation. The base level involved the estimation of milk production in a single equation. Under the second method, production was the product of two equations: milk per cow and number of milk cows. The third method factored production into three equations: milk per cow, number of dairy farms, and number of cows per farm. As expected, the greater the degree of disaggregation the more was learned about the structural aspects of milk production. At the same time, predictive accuracy generally decreased, but the differences among models was slight.

An interregional competition model of the U.S. apple industry is constructed. This model includes the consumer products of fresh apples, applesauce and apple juice. The validation of the model showed that it did a good job of estimating consumer's quantity demanded and prices and a reasonable job of estimating utilization. This model was used to study the effects of transportation cost changes on the industry in the short- and intermediate run. The total production and consumption levels changed by moderate amounts with changing transport costs while the utilization of a region's crop was quite sensitive to such changes.

A dynamic (multi-period) linear programming model of a beef/sheep farm was used to evaluate the potential for increasing income and for maintaining a specified level of annual income during a cattle cycle. Results indicate that both objectives may be accomplished by adjusting animal numbers in response to changing price ratios: a higher proportion of cows should be kept during the accumulation phase of the cattle cycle, and a higher proportion of ewes should be kept during the liquidation phase.

A model analyzing household substitution of fuelwood for other heating fuels is needed to clarify the relationship between energy prices and patterns of forest resource utilization. This paper employs the household production methodology to model fuelwood demand in Rhode Island. Data from a cross-sectional survey of 515 households are employed to test a discrete-choice model of household participation in wood-burning and a four-equation system modeling household production of heat and aesthetic benefits from fuelwood and stove capital. Control of selection bias via inclusion of an appropriate instrument allows analysis of aggregate demands. Some broad policy prescriptions applicable to the Northeast generally are presented.

Commercial bank loans to New York farmers are significantly overestimated in the reported USDA statistics due to out-of-state lending and reporting of some agribusiness loans as agricultural loans by New York State banks. Correcting for this distortion lowers the 1978–84 average New York agricultural credit market share held by banks from 36 to 24 percent. As deregulation allows more interstate banking activity, the overestimate of agricultural loan volume in states with money center banks and the corresponding underestimate of loan levels and market shares in nonmoney center states could cause increased distortion of state level farm debt statistics.

An advertising-sales response model is extended to include the effects of demographic factors (age and race) as additional determinants of milk demand. Previous research indicates that the age structure of a population and its racial composition are primary factors influencing fluid milk sales. Failure to incorporate these factors in the milk demand model results in a 30 percent downward biased estimate of the advertising effect. Consequently, the economic effectiveness of milk advertising is understated when the effects of demographic variables are ignored. Changes in demographic factors (growing nonwhite population and shrinking teenage market) appear to explain the relatively flat trend in per capita milk sales in the New York City market over the period 1971–80—a period in which dairy producers spent $12 million on generic advertising of milk. Net returns to Federal Order 2 dairy farmers from generic advertising of fluid milk is estimated to average $6.07 per media dollar invested over the 1972–79 period.