The topic of this address may seem somewhat remote from the traditional interests of agricultural economists. Yet it has been of central concern to those of us involved in natural resource and environmental issues. Given the direction in which agricultural economics is currently moving, it may soon prove to be as perplexing a problem in that arena as well.

This paper is divided into two parts which are somewhat independent. The first part of this paper discusses certain properties of a general autonomous control model that appears promising for the analysis of general dynamic supply response models in agricultural economics, resource economics, and related fields. The second part of the paper, which can be read somewhat independently of the first, emphasizes the potential empirical applications of special cases of the general model discussed in the first part. In what follows, we always deal with continuous time and infinite horizon models because of their analytical tractability. Extension and modification of our results for discrete-time, finite-horizon problems should be fairly obvious and are left to the interested reader.

The practice of econometrics entails choosing which equations to include in a system, and which equations to inclue in a system, and what restrictions to impose on the parameters. There is a widespread, but not universally held, preference for making these choices on the basis of theory. Until recently, this theory has rested on the hypothesis that agents solve static optimization problems. For agents’ behavior to be consistent with this story, certain restrictions must hold. These restrictions are used in econometric models as maintained or testable hypotheses.

Given the stable position in applied literature now held by static, duality models of choice, the focus of innovation has shifted to development of models of dynamic economic behavior. However, before jumping into this stream it is important to assess 1) the objectives and empirical relevance of study of such behavior, and 2) the characteristics of observed behavior which might help us resolve the specification of such models. The objective of empirical study of dynamic behavior seems clear. An accurate descriptive model is desired which could provide the basis for prediction and comparative analysis of behavior. The relevance of any such study is limited, as usual, by the accuracy and consistency with which the theory of behavior upon which the model is based simulates observed behavior. A prerequisite of relevance is an understanding of the elemental characteristics of observed dynamic behavior which might suggest the primitive elements of a theory of behavior and motivate model specification.

Problems of aggregation plague applications of microeconomics. The theory is derived from postulates of behavior of individuals, but we often have data only for groups of individuals. The economics of outdoor recreation is no exception. This paper addresses the aggregation issue for estimating the demand for outdoor recreation. What are the estimation and welfare implications of using individual vs. aggregated observations, if the latter is all we have?

This paper compares three recreation valuation techniques—the travel cost (TC), the hedonic travel cost (HTC), and the household production (HP) techniques—on the basis of their theoretical underpinnings, econometric and data considerations, and policy considerations. The major focus is on how these techniques can be used to evaluate the benefits to recreationists of changes in the quality of recreation sites. Bockstael and McConnell's (1981) formulation of the HP model for sport fishing is used in the following discussion. Other variants, such as the model used by Smith et al. (1983), are only briefly mentioned.

The current issues of landfill bans, groundwater contamination, waste-end taxes and source reduction of hazardous wastes have rekindled interest in a systems view of environmental management. While this recent interest is new, the basic concept is not. The physical Law of Conservation of Mass as embodied in materials or mass balance has underlain most residuals management research (e.g. Ayres and Kneese [1969]; Kneese and Bower [1979]). As society grapples with the complex problem of toxic and hazardous chemical residues and their distribution in the environment, mass balance is receiving renewed attention in the form of cross-media transfers. The focus of this renewed interest is the movement and transformation of residuals among environmental media (soil, air and water) after discharge. Our early public lessons in applied ecology taught us that the environment is a single integrated system and that there are frequently unintended consequences associated with the human use of that environment. The contemporary lessons from the identification and cleanup of uncontrolled hazardous waste sites under the “Superfund” program lends a new impetus to our reconsideration of these concepts.

Economists since Pigou have advocated the use of economic incentives for controlling environmental degradation. In a similar vein, environmental economists have long lamented a near unanimous reliance of environmental policy on the use of direct regulation. However, several pieces of legislation, as well as common law doctrine, provide strict liability for damages from a variety of pollution incidents. The term strict liability means that a polluter is liable for the penalty imposed for a pollution incident irrespective of intent, fault, or even knowledge of the pollution incident. Negligence need not be proved, thus strict liability allows for no defense of due care or conformance with common practice.

Potatoes have been grown continuously on many Long Island (New York) fields. Environmental concerns have raised questions about the continued usage of this practice. A farm-level linear programming model was used to investigate the economic impacts of crop rotations which result in reduced potato acreage. Crop rotations (an Integrated Pest Management tactic) reduced total pesticide use, but also reduced returns above variable costs as successively stringent rotation requirements were forced into the solution. The crop rotations which caused the least effect on income were identified.

The increased variability of interest rates experienced during the early 1980s led many commercial banks to shift the interest rate they charge on farm loans from a fixed to a variable rate (Zook and LaDue). Although the Farm Credit System had used variable rates for a number of years, the index for their rate was the average cost of funds, which is less volatile than some of the rate indices used by commercial banks. Further, in contrast to the situation when the Farm Credit Service switched to variable rates, the shift of commercial banks to variable rates left most farmers with no fixed rate general credit source, no matter how important a fixed debt service commitment might be to their business.

A translog cost function was estimated using pooled time series-cross section data from five Northeastern States to study structural changes in the dairy industry. The approach given in the duality theory was found useful in estimating the input demand structure under changing input prices and technology conditions. The estimated Allen partial elasticities of substitution show the existence of substitution between energy and non-energy inputs in dairy farming. Despite input price increases the dairy industry maintained competitiveness as seen by the returns to scale parameters.

The production structure of a selected cross-section sample of family owner-operated dairy farms is investigated using a translog variable cost function. Elasticities of scale, input substitution, and input own- and cross-price elasticities are estimated. At the sample mean herd size of 67 cows producing at 15,173 pounds of milk per cow, the elasticity of scale parameter was 1.00, implying constant returns to scale. The elasticities of substitution between feeds and hired labor and the own- and cross-price elasticities were inelastic.

This paper compares two alternative estimates of agricultural use values in New York, one based on comparable sales information and the other on capitalized yearly income. Emphasis is placed on the variability of the values over the 1973–83 period and its implications for taxpayer equity and the financing of local governments.

Forecasts made by econometricians are typically conditioned on actual values of explanatory variables, even when at the time of the forecast, such variables might not be available. As a first step, one might test the adequacy of econometric specification by comparing conditional post sample forecasts with those of a univariate ARIMA model. Second, when explanatory variables must themselves be forecast, those for which this can be done only badly, should be omitted from the final model. A better forecast will result. An example of screening out badly forecasted explanatory variables is presented.