U.S. consumption of fresh tomatoes and cucumbers during the winter season (defined herein as November through May) is typically about 1,300 million and 370 million pounds, respectively. Florida has long been the major domestic supplier, and other states, principally Texas, California, and South Carolina, provide the remaining domestic winter season production. Mexico also is a major supplier of tomatoes and cucumbers in the U.S. during the winter. Before the 1962 embargo on Cuban-U.S. trade, Cuba, too, was an important source.

The analytical framework of international trade and industrial organization is used to review and test some new hypotheses about the effect of foreign trade, protection, and foreign direct investment on domestic profitability of U.S. food processing industries. Though several studies have examined the relationship between market structure and performance in food processing [7, 10], they are based on an implicit assumption that the economy is closed. The extensive multinational expansion of American food processors, documented by Horst [8], and their growing dependence on foreign trade suggest that this assumption has become untenable and that the proper identification of industrial structure must account for these foreign factors.

Cow-calf operations dominate cattle production in the Southeast. The 1978 January 1 U.S. cattle inventory report shows that breeding cows make up 45 percent of the total inventory in Region 41 compared with 33.3 percent nationally [3]. Further, in 1977 cow slaughter accounted for 64.8 percent of federally inspected cattle slaughter in Region 4 compared with 23.6 percent nationally [8].

Credit availability and use have been identified as crucial factors affecting success or failure for many farm operations [1, 2]. The increased level of uncertainty affecting agriculture in the 1970s has intensified the importance of credit use by farmers. Indeed, maintaining financial liquidity often is cited as a strategy to counter increasing farm risks [6, 12]. Farmers view credit as a crucial variable and, as shown by Barry and Baker [3], farmer borrowing patterns can be related to the level of unused credit those farmers maintain.

Recent increases in the number of resource and industrial developments in rural areas [10] have led to the creation of a large number of comprehensive planning models usually identified as “economic-demographic” projection models [see for example 1, 3, 4, 5]. These models are used to delineate systematically the interrelationships among various economic, demographic, and social factors. They differ in their basic model structure, their degrees of flexibility, and range of user input options, and in terms of the geographic and governmental units for which projections are made. Each, however, includes a basic economic module, a demographic module, and a module for interrelating or interfacing the economic and demographic modules. Additional modules, such as fiscal impact, settlement allocation, public service, and housing demand modules, also may be included but they tend to operate directly on the outputs of one of the other three basic components and are thus largely addendums to the economic, demographic, or interface modules of such models.

The improvement of economic and social conditions in rural areas has long been a special goal in our nation's history. Rural development is a broad-scale effort encompassing the many dimensions or conditions which determine the quality of life, such as access to public services and facilities, economic development, and the protection or enhancement of natural and environmental resources. As suggested by this diversity of programs, numerous government agencies and academic disciplines are involved in the process of rural development.

This article presents a model of the Florida watermelon industry that quantifies aggregate entry and exit decisions and the effect of interregional competition on prices received by Florida growers. The model development is presented first and is followed by estimation of the model's parameters. Policy implications from the model are then developed.

Surface mining, until recent years, concentrated on the recovery of the minerals rather than the recovery of the land. From 1870 to 1930 more than 1.3 billion tons of coal were mined and roughly 250,000 acres were disturbed. In the period 1930-1971, 3,357,000 acres of land were disturbed by surface mining. Approximately 43 percent of this total (1,436,000 acres) was partially or totally reclaimed. Since 1971 most surface-mined land has undergone at least partial reclamation, depending on the state where mining took place. If the nation's estimated 1 trillion tons of coal reserves were developed, approximately 200 million acres would be disturbed by surface mining in the three major coal producing regions (Appalachia, Midwest, and the Mountain West; Figure 1). Evaluation of the economic cost of reclamation to meet these laws, and (3) to analyze the effects of these costs on different coal producing regions.

Public spending in government programs to control animal and plant diseases, parasites, and other pests that reduce agricultural production amounts to more than $150 million annually [3]. These programs and activities are administered by the Animal and Plant Health Inspection Service (APHIS), U.S. Department of Agriculture. In recent years, program costs have increased rapidly and USDA officials have been asked many questions by the Congress, the Office of Management and Budget, and others about the need for certain programs. Because of steadily increasing pressure to reduce federal spending, public decision makers urgently need reliable aggregate measures of the performance of their programs.

Currently developments in two bodies of literature address the determination of optimum levels of storage. One approach, the use of inventory models, has developed as a generalization of the familiar lot size problem in management science models [9, 17]. The decision unit in these models is the firm or frequently a decentralized management unit or authority [4, 12, 15].