The Federal Water Pollution Control Act of 1972, PL92-500, established the goals of making the nation's streams and lakes swimmable and fishable by 1983 and eliminating both point and non-point pollution discharge by 1985. Implementation of this act, even if carried out uniformly and on the basis of scientifically determined information, could have far-reaching impacts on the agricultural sector.

The purpose of this article is to:

1. 1. Review the requirements of the legislation.

2. 2. Review selected research.

3. 3. Estimate the potential economic impact of proposed regulations on agriculture in Mississippi.

4. 4. Identify research needed to minimize the adverse economic impact of attaining the objectives of the regulations.

In view of the breadth of the topic, coverage is limited to identifying the events and commenting on the types of impacts on agriculture rather than stating specific empirical estimates of impacts. Numerous researchers in agricultural economics have examined the quantitative dimensions of impact from particular scenarios of future courses of some of the events identified here.

With only one or two notable exceptions, the current commodity output mix of southern agriculture is similar to that for U.S. agriculture as a whole. Ranking the top eight farm enterprises of the south in dollar value (1976) shows tobacco in the southern region replacing wheat in the national ranking; dairy, corn, and hogs are more important nationally and broilers and eggs are more important in the southern complex. Therefore, if those dimensions of agriculture associated with geographic location, such as population, climate, or transport net, are excluded, the major events affecting southern agriculture in the 1970s can be discussed in terms of U.S. agriculture.

The fundamental issue of the 1980s will be whether agriculture will preserve its identity. The 1980s will be the decade decision as to the structural organization of agriculture. It is not anticipated that the agricultural sector will be preserved intact, or, alternately, totally transformed by 1990, but by then the die will have been cast. In a different idiom, a point of no return will have been reached.

Structural questions touch virtually every policy issue in agriculture. Income tax, estate tax, environmental protection, availability of farm credit, terms of price and income support — these and other issues are interwoven. Agricultural economists relate to structural issues in two ways. We are concerned for our clients. The kind of agriculture to prevail makes a difference to farmers and their families, to rural communities, and to the citizenry of the South. It makes a difference also to agricultural economists professionally. In 1969 many of our analytical skills were developed for a dispersed market-oriented agriculture. If a different kind of agriculture materializes, the need for economic guidance will not end, but many of us will find ourselves technologically obsolescent.

One of the fundamental problems in applied econometric work is the choice of functional form. Economic theory is insufficient in suggesting the functional forms appropriate to the specification of economic relationships. Conventionally, the functional form of the regression equation is assumed a priori and parameter estimates are obtained according to certain desirable criteria, such as least squares. A wide variety of functional forms have been investigated empirically with respect to the demand function for food, yet no single functional form has been generally accepted among economists [2, 6, 7].

There is considerable overlap between events of lasting significance in the 1970s and policy issues of the 1980s, perhaps because of an implicit requirement (in my own mind at least) that policy implications are a prerequisite to significance. At any rate, past developments in their full dimensions seem closely interwoven with future events.

Repeated invitations to Harold Breimyer to “look ahead” are evidence of our profession's view of his ranking in the trade of seers. Because, at best, we can only “see through a glass darkly,” it may be a futile effort to forecast developments beyond a two- or three-year horizon. Yet several of the unexpected events within our individual spheres of existence might have been spotted on the more distant horizon if we had really strained a bit to peer through the fog. Even knowing that the forecasting balance is tilted heavily on the side of events that cannot be foreseen, we feel it beneficial to keep peering ahead. I believe that is why, in spite of records that do not sparkle with accuracy, Breimyer continues to prophesy and we continue to listen.

Currently the United States consumes an estimated 39 to 45 percent of its beef in the “ground” form [3, 7, 8]. As recently as 1972 the estimated percentage of beef consumed as ground was only 33 [3] and some industry leaders have estimated the proportion by 1985 to be from 50 to 65 percent [5, 8, 11, 12]. This increasing trend in the percentage of beef consumed in the ground form is often attributed to several factors including (1) an increase in the percentage of wives working away from home which results in more “eating out” and less home preparation of “traditional” meat dishes for those meals consumed at home, and (2) the continuing growth of the fast-food restaurants and their popular “hamburger” meals [5, 8, 11, 12].

The economic theory to be applied in optimizing feeding periods for finishing slaughter cattle is well developed both for cases in which only one group of cattle is finished and for cases in which each group of finished animals sold is replaced in the feedlot by another group of feeder animals [3, pp. 71–76; 4]. According to received theory the operator who plans to replace the finished animal with another feeder should feed to the point in time at which marginal net revenue equals average net revenue (maximizes returns to time). The operator who does not intend to replace the finished animal with another should continue feeding until marginal net revenue is zero (maximizes returns to the animal).

In the final year of an eventful decade, it is appropriate to take stock of where we are, what the events of this decade really mean, and what the next decade holds in store. What really happened in the 1970s? As for any other decade, that question is not easy to answer. It will be easier to answer a few decades hence when we are better able to see the events of lasting significance in historical perspective, and to distinguish them from the short-lived phenomena that cloud both our vision and our understanding because we are still too close to them. Furthermore, decades are simply 10-year units in a continuum of events and are not necessarily logical units of time to study.

Each year, heads of agricultural economics departments meet to discuss mutual issues related to our teaching, extension, and research programs. A major continuing issue is our portion of research and extension funds— with a natural suspicion that we are not being allocated our “fair share.” An additional, and perhaps larger, concern has arisen in the last few years as we recognize the apparent movement toward increasing use of competitive grants for funding agricultural research. It is not the grants idea that concerns us as much as it is the research areas which have been developed and/or may be developed within which we must make our proposals.

Each department in a university draws its sustenance from the same pie. Each is concerned with the size of the pieces devoured by animal science, crop science, and the others. The following comments relate to both share and “pie enlargement.”

Cost and volume data used in long-run cost studies often are observations from a single cross-section on firms or the average of multiple observations for each firm [1, 3, 5]. Averaging costs and volume over a time series is designed to eliminate the effect of short-run disturbances on the estimated long-run cost function. This practice results in a loss of information on the cost effects of short-run disturbances and significantly reduces the potential degrees of freedom that could result from pooling cross-sectional time-series data. In order to pool data, binary variables for each firm previously have been used to account for short-run fixed firm effects [4].

Periods of reduced supplies due to exogenous shocks and subsequent high price levels have occurred for many agricultural commodities in the past decade. Consumers' adjustments to these events depend on the magnitude of the shocks and characteristics of the commodity. Understanding consumers' responses to these events requires recognition of rigidities that result in delays in consumer responses to prices.

Recognition of rigidities in consumption relationships by using dynamic stock and flow adjustment models was popularized by Houthakker and Taylor [2]. The models recognize the role of inventories and habits resulting from previous purchase patterns in determining current consumption decisions.

Commodity Credit Corporation (CCC) price support loan activity has important implications for U.S. Treasury outlays. In 1977, CCC purchases of agricultural commodities (the vast majority of which were in the form of support loans) amounted to $3.9 billion. In other words, roughly 25 percent of federal purchases of nondurable goods, or 2.7 percent of all federal purchases, arose from CCC commodity transactions. In 1976, CCC purchases were $900 million, only about 9.5 percent of federal purchases of nondurables and 0.7 percent of total federal purchases of goods and services. Furthermore, the quarterly pattern of the series is extremely volatile, with swings often exceeding $500 million in a single quarter. In the six years between 1972 and 1977, nominal CCC purchases were negative in each of the first three years and positive in the last three.

Farm firm growth has been an important topic for research and discussion since the 1950s. Incentives for farm growth have been and continue to be substantial. An agricultural economy characterized by technological improvement, decreasing costs, competition, and an inelastic demand for farm products leaves little alternative but growth for a commercial farm. Farm growth is stimulated by the need to achieve size economies that arises partly from new technology and partly from large investments in machinery and equipment. Growth is encouraged by the improving managerial ability of the operator as he matures and gains experience. Increased family living needs and the desire to overcome the adverse effects of inflation on purchasing power spur interest in improving the farm's earning potential. In addition, the operator's goals may include size aspirations to satisfy the desire for a large operation or to support the family of a son or daughter attempting to become established in farming. Because the pressures for growth, both internal and external to the firm, are long-run phenomena in agriculture, continued study and evaluation of the process of entry, firm growth, and exit coordination are essential.

Although American agriculture has been adopting new technology for more than 100 years, the rate of adoption has greatly accelerated in recent decades. This technological revolution has resulted in important changes in rural America. Mesthene [12] points out the impact of technological change on society; Donaldson and Mclnerney [6] examine the impact of machinery technology on agricultural adjustment.

When farms increase in size and decrease in number, employment opportunities in agriculture are reduced [1]. This change, in turn, affects the viability of towns in farming areas, as shown by Heady and Sonka [8] and by Hamilton, Peterson, and Reid [7]. Changes in agricultural technology, in farm size, and in farm-oriented towns have major economic and social effects on rural communities. Beale [2] documents recent demographic changes and Brinkman [3] discusses the impact on the rural sector of transition to an urban society.

A traditional approach to defining problems or needs is to compare a situation (what is) with objectives or valuations (what ought to be). A more elaborate version of this approach introduces some dynamics into the scheme by projecting current trends to determine how the expected situation some time in the future compares with what we would like the situation to be. One difficulty in such an approach is deciding what dimensions of the situation are important.

In considering the problems of small farms, do we primarily examine income and the measures of wellbeing — or emphasize the structure of agriculture and its implications for our society? Must we consider the extent to which concern for conservation of soil and energy resources is related to size of farms? Should we complicate the picture even more, as is often argued, by including the non-market-goods dimensions [18]? Some researchers would merely use a change in the number of small farms as indicative of a problem, but this is only symptomatic of more basic factors at work.

Modeling local and regional manufacturing activity is an important component of economic research. Models that explain the levels of local aggregates, such as employment, aid the efforts of state and local governments to influence the future course of economic activity. Such models also aid private decision makers in their efforts to develop feasibility studies of projects representing different investment alternatives. Input-output and economic base studies are the most common means of modeling local economic activity. These studies, though useful in assessing the multiplier effects of changes in local manufacturing activity, do not capture the temporal influence of national economic trends or the specific community characteristics responsible for varying levels of manufacturing activity. Econometric models, being more flexible and less expensive, may better serve the latter purposes.