Doctoral Dissertations

Date of Award

12-1991

Degree Type

Dissertation

Degree Name

Doctor of Philosophy

Major

Agricultural Economics

Major Professor

Burton C. English

Committee Members

Luther H. Keller, William M. Park, Alan Schlottmann

Abstract

Agricultural topsoil is one of the critical natural resources of a civilization. This delicate layer of our planet is the primary source of sustenance for human and animal populations. Arable soil is necessary to feed, clothe, and shelter human beings and is a prerequisite for achieving the aspirations of a society. Without adequate arable land, a civilization will find it difficult to thrive, or even survive (Browning; Napier and Forster). Thus, the potential of a society is largely dependent upon the topsoil of its agricultural lands (Napier and Forster).

While the importance of topsoil and the problem of topsoil loss have long been recognized, over 40 years of cooperative efforts between farmers and the federal government have done little to check the erosion of our farmland (McConnell; Napier and Forster; Rasmussen, 1982; Walker). One-third of U.S. cropland topsoil has been lost in the last 200 years (Walker), and sheet and rill erosion on U.S. cropland continues at a rate of 1.6 billion tons annually (USDA/SCS, 1990).

Increased public awareness of these issues continues to put significant pressure on policymakers to solve our environmental problems while maintaining an abundant, inexpensive food supply. Policy debates, past and present, have focused primarily on physical actions to be taken rather than upon policy goals (Robinson, K.). The primary target for such policy is the “T" level, the "maximum annual number of tons of soil an acre of land can lose indefinitely without impairing the agricultural productivity of the soil" (Crosson, p. 34).

Yet the use of physical goals of soil loss is often challenged by economists who argue that it is not the physical loss from the farm that is important, but the costs incurred by loss of topsoil and offsite damages from agriculturally-generated sedimentation (Robinson, K.). Of the two, offsite sediment damages are far greater than onsite productivity damages. After modeling onsite damages of soil erosion, McConnell (p. 88) concluded "the major impact of soil erosion is water pollution," and "the problem of water pollution is paramount, not agriculture's future productive capacity." Similarly, Swanson's research in Illinois indicated that the impact of soil erosion on agricultural productive capacity is small.

The costs to society of offsite damages, however, are significant. Sediment is the largest polluter of ponds, streams, rivers and reservoirs (Clark, et al.; Miller and Everett; Wade and Heady, Water Resources Council). Sediment trapped in ditches and lakes reduces water holding capacity and increases the likelihood of flooding. It increases dredging costs of rivers and harbors, fills reservoirs, damages wildlife habitats and diminishes the recreational enjoyment of water resources. The annual offsite cost of erosion in the United States is estimated to be $6.2 billion (Clark, et al.).

Kenneth Robinson (p. 153) states "a shift away from emphasizing physical targets to the use of economic criteria (or some combination of the two) probably would lead to greater returns to society from the dollars currently invested in conservation activities." This study focuses on combining economic and physical relationships to develop a workable policy model to optimize both agricultural revenues and environmental quality.

The specific objective of this study is to develop a soil conservation policy model that incorporates both physical and economic criteria, and that includes the objectives of both producers and policymakers. The model used is an adaptation of the multi-level programming model developed by Candler and Norton and extended by Sylvia and Anderson. A multi-level optimal control model is developed which optimizes the producer's dynamic problem in the first stage, then uses the producer's optimal decision paths in the second stage as components of the policymakers' dynamic problem. The second stage problem utilizes weights indicating the relative importance of the policymaker's competing goals. Those weights are used to construct a dynamic policy frontier demonstrating the relationships between various policy goals and the resulting optimal solution paths.

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