Economic theory states that the exchange rates influences movements in agricultural prices and are in an important determinant of the agricultural sector trade. This paper reviewed the theory and economic models under which exchange rate fluctuations create shifts in the excess supply and demand between countries in the international market along with a history of relations between the United States and the DR-CAFTA region. The theory is econometrically tested through the OLS method to examine to what extent the real exchange rates between the United States and less developed countries were constant with accepted theory. The agricultural trade movements were investigated by examining imports and export values between the United States and the selected counties and proposing the exchange rate as one of the explanatory variables in the econometric model. Given the interdependence of the trade flows within the region, the OLS equations were run as a system of equations under Seemingly Unrelated Regression estimation for annual exports and imports from 1976 to 2004. The exchange rate effect entered into the model was expressed as the foreign countries' currency value with respect to the U.S. dollar. The expectation was that depreciations in the U.S. dollar would have a positive effect on U.S. exports and a negative effect on U.S. imports from the DR-CAFTA region. There were some major concerns of this study in the underlying interdependence of the factors and their effects on trade. Among the results of this study, U.S. agricultural exports are given more emphasis, as the more stable and larger economy. The developed economy of the United exhibited behavior conforming to economic theory. The less developed Central American countries could not be expected to comply with economic theory when there are underlying socioeconomic factors affecting trade. The results, while inconclusive on the U.S. import side, show that exchange rates were important in explaining U.S. exports to the DR-CAFTA region.

This dissertation focuses on two research themes related to econometric estimation of linear almost ideal demand systems (LAIDS) for U.S. meats. The first theme addresses whether nonstationarity (unit-roots and cointegration) contributes to a dynamic specification of LAIDS models. The results of the effect of nonstationarity are reported in two case studies. The second theme explores the relationship between age and household size with budget shares to specify semiparametric LAIDS model. The results are reported in a third case study that compares parametric and semiparametric models estimates of price and expenditure elasticities. The first case study conducts a comparative analysis of elasticity estimates from static and dynamic LAIDS models. Historical meat consumption data (1975:1-2002:4) for beef, pork and poultry products were used. Hylleberg et al. (1990) seasonal unit roots tests were conducted. Unit roots and cointegration analysis lead to the specification of an ECM of the Engle-Granger type for the LAIDS model. Marshallian and compensated elasticities were generated from the static and dynamic LAIDS models. The study found some model differences in elasticity estimates and rejected homogeneity in the dynamic model. The second case study evaluates the forecasting performance of static and dynamic LAIDS models. Forecast evaluation was based on mean square error (MSE) criteria and recently developed MSE-tests. The study found ECM-LAIDS model performs uniformly better under all forecasting horizons for the beef equation. However, in the case of the pork equation the static model performed better in one-step-ahead and two-step-ahead forecasting horizons while the dynamic model was superior in the three-step-ahead and four-step-ahead forecasting horizons using MSE comparisons. In testing, only the two-steps ahead was superior for pork. The third case study specifies a semiparametric LAIDS model that maintains the linearity assumption of prices and total expenditures and allows nonparametric effects of age and household size. 2003 U.S. Consumer Expenditure Survey data for four meat products (beef, pork, poultry and seafood) were used in the study. Model fit and elasticity estimates revealed negligible differences exist between parametric and semiparametric models.

Over the past decade, the peeling segment of the Louisiana crawfish industry has faced the challenge of remaining competitive in an increasingly global market. Since the mid-1990s, there has been escalated discussion among Louisiana crawfish processors on the need for a crawfish peeling machine. The International Trade Commission determined that the U.S. crawfish industry had been materially injured by the imported tailmeat and ruled China was, in fact, dumping crawfish in the U.S. by selling below fair market value in the host country. The development of a suitable crawfish peeling machine could potentially increase production and lower cost of production, therefore allowing the United States to be more competitive with the imported tailmeat from China. Using conjoint analysis, the preferences of Louisiana crawfish processors in adopting crawfish peeling machines are analyzed. Theses results were based on the various attributes a peeling machine would possess. According to the industry, whether the crawfish peeling machine deveins is viewed as being most important; devein constitutes 30.6% of the total importance. For this study, cluster analysis was used to categorize processors into homogenous groups to bring together crawfish processors with a relatively high similarity in attribute preference. The analysis suggests processors peeling a higher percentage of crawfish tailmeat tended to be grouped into cluster 2, which considered a machine that deveins and retains fat to be the most important. Thirty crawfish processors ex-ante adoption rates of hypothetical crawfish peeling machines are assessed using a polychotomous choice elicitation format. Adoption rates are estimated to range from 23 to 70 percent, depending upon the machine and whether it was purchased or leased. Processors most likely to adopt are determined using ordered probit analysis. Greater adopters would be larger and more diversified, have greater current resources, and have longer planning horizons. Early adopters of the machine would benefit from the reduced cost of production before the market becomes concentrated while late adopters would most likely experience lower profits or short-term losses prior to adoption.

This dissertation analyzed spatial agglomeration economies associated with the geographical distribution of the U.S. biotech industry. Three location issues associated with the biotech industry were addressed in the study. The first study utilized a Bayesian spatial tobit model and examined the overall and regional differences in factors affecting the location of the U.S. biotech industry. The second study examined the inter- and intra-industry spatial association of biotech related research and development (R&D) and testing facilities across all contiguous U.S. counties employing a Spatial Two-Stage Least Squares model. Finally, the interdependence between different subsectors of the U.S. biotech industry was analyzed using a Seemingly Unrelated Regression model. The first study confirmed the hypothesis of spatial agglomeration for the spatial structure of the biotech industry, indicating that biotech firms are positively correlated across counties, resulting in clustering of biotech production. Availability of venture capital firms, research institutions, and hospitals were found to have the most significant impact on the location of biotech firms. Results from regional models indicate that biotech firms willing to locate in the West prefer to establish in metro-counties with easy access to research institutes and skilled labor pool. Conversely, firms that are willing to locate in the Northeast prefer counties with easy access to funding sources and hospitals for research, testing and marketing of new biotech products. Spatial clustering of biotech research and testing activities was confirmed in the second study. Proximity to manufacturing firms and research universities, and availability of venture capital firms were found to have the most significant impact on the location of R&D and testing facilities. Results indicated that public as well as private spillovers are at work in the R&D and testing industry, resulting in their spatial clustering. Agricultural biotechnology firms preference to locate in counties with large farmland, low median housing values and average hourly wage, and a high unemployment rate was indicated in the third study. Conversely, results indicate that firms belonging to drug and pharmaceuticals, and medical devices and equipment subsectors prefer to locate in counties with high standards of living and in close proximity of research institutes and hospitals to access skilled-labor, and develop and test new drugs.

Fifty Louisiana dairy farmers were interviewed to gather production amounts, costs of production, management techniques, technologies adopted, and demographic information. These data were used to analyze what record-keeping systems the farmers were adopting and to what extent the systems were being used. Logit, ordered probit, negative binomial regression, OLS regression, and double hurdle models were used to determine adoption and intensity. In this study, age was found to decrease the probability that a farmer would believe their computer was not at all useful and also of limited usefulness, while increasing the probability that a farmer would believe the computer was very useful to the farm business. Older farmers were more likely to perceive the computer as more useful. Having a family successor to take over the dairy upon the operators retirement affected many things, including: decreasing experience with the internet; increasing the probability of a farmer perceiving the computer as of limited usefulness; decreasing the probability of a farmer perceiving the computer as very useful; increasing the hours spent per week reviewing DHIA output; increasing the number of financial measures tracked; increasing the intensity of use of DHIA after it has been adopted; and increasing the probability of adopting computerized record-keeping systems. If the operator himself kept the records for the farm, then fewer financial statements were generated and less time was spent updating computerized record-keeping systems. These farmers, however, devoted more time to reviewing DHIA output. When the farmer was a technology adopter he was more likely to have experience with the internet and to have adopted DHIA, but spend less time reviewing DHIA output. Also, technology adopters were more likely to view the computer as very useful and less likely to view the computer as not at all useful. The more statements a farmer generated for financial analysis, the more likely he was to adopt computerized record-keeping systems. Thus, farmers with a greater interest in record-keeping were likely to find the computer more useful because it can make financial analysis much easier compared to paper based records.

Significant changes in attitudes toward farm policy and trade have occurred within the European Union and the United States in the past decade. Trade negotiations under the General Agreement on Tariff and Trade (GATT) specifically the Agreement on Agriculture (AoA) and later under the Doha Round of the World Trade Organization (WTO) have bought about considerable changes in the market structure in the cereals trade. Bilateral trade has further been impacted by the cessation of concession treaties like the Blair House Accord that expired at the end of the 2004 marketing year (WTO). Domestic budget pressures in the United States have lead to decreased support to farmers, making them more oriented to world market needs based on prevailing world prices (Daryll E. Ray). The European Union has introduced reforms in the Common Agricultural Policy as a consequence of high budgetary expenditure and the accession of the ten new central European nations into the European Union in the form of the Mac Sharry Reforms and the Agenda 2000 Reforms. These reforms are now aimed at decreasing the distortions caused due to the high amount of protection for farm income thus moving towards more targeted farm programs. These economy wise changes internal to each of these major players in agricultural trade in the world, coupled with transformed bilateral trade relations under the auspices of the WTO have had vital effects on bilateral transactions and world markets. These reforms may have had compelling economy wise effects on consumption, production, trade and world prices and could subsequently provoke trade liberalization in other sectors based on the quantification and prediction of welfare effects of such measures by the two trading partners. This study is aimed at reviewing policy changes in the European Union's Common Agricultural Policy and their effects on the cereal trade with the United States. The study contributes to estimating whether changes in the cereal policies of the EU have had a significant impact on the trade between the EU and the US. Further a forecast for the domestic prices for wheat in a free trade scenario is documented with an estimated trend for the exogenous variables. Results obtained from the suggest that the re-instrumentation of the Common Agricultural Policy (CAP) by the Mac Sharry Reforms of 1992 and the Agenda 2000 Reforms have had significant effects on trade between the U.S. and the fifteen member countries. The forecast for domestic prices in wheat for the EU suggest a period of decreased prices followed by an increased amount of imports of wheat.

This study is mainly intended to determine quantitatively the economic effects of crawfish imports on the domestic crawfish industry. Inverse demand systems are used to estimate the price and scale flexibility as an indicator for the effects of imports on crawfish domestic price. A variety of algebraic forms for empirical consumer allocation models have been developed. Economic theory, however, does not provide the necessary fundamental criteria to choose ex ante among the alternative specifications. Bartern (1993) and Brown, Lee, and Seale (1995) examined a family of inverse demand systems, showing that the integrated demand system, in its own right, has more parameters than any of the component systems, and is, therefore, more flexible. This study also finds that among the different type of inverse demand systems the generalized inverse demand model (GIDS) is a better fit for the data used in this study. As expected, the cross price flexibility of imported crawfish and scale flexibility in the domestic crawfish equation are shown to be negative, implying that crawfish imports have negative effect on domestic crawfish price and imports of aggregate fish also have a negative effect on the domestic crawfish price. At the same time, cross price flexibilities show either substitutability or complementarity. The Morishima elasticity of complementarity was used as a more adequate measure of interaction between commodities than the coefficients of the Antonelli matrix. The study showed that the elasticities of complementarity are all positive, implying both the tendency toward complementarity and the negativity of the own-quantity elasticities. As the negativity of cross price flexibility of imported crawfish indicates, domestic crawfish producers will suffer economic losses from increased imports of crawfish, while the domestic crawfish consumer will be better off. Even though the economic loss to the domestic crawfish producers resulting from increases in the imports of crawfish is relatively small compared with the gains to domestic crawfish consumer welfare, the impact of imports is serious to the domestic crawfish industry because the loss is accrued to a small number of domestic crawfish processors. This study however, shows a net social welfare gain from increasing crawfish imports.

Rising production costs, primarily associated with increasing fuel and fertilizer prices, combined with a relatively flat to slightly declining market price trend, have significantly reduced profit margins from sugarcane production in Louisiana over the past few years. Harvest operations are one area in which growers can have considerable influence on costs per unit. Estimation of current sugarcane harvest costs as well as economic evaluation of the impact of various factors on the performance and cost of this production phase are important to growers in conducting these harvest operations as efficiently and cost effectively as possible. The general objective of this research project was to estimate the current fixed and variable costs of harvesting sugarcane in Louisiana with combine harvest units and to determine optimal harvest schedules for groups of farms delivering sugarcane to a common mill. Using 2004 input prices, average estimated harvest costs were calculated to be $2.41 per ton for fixed expenses and $2.79 per ton for variable expenses, resulting in a total harvest cost of $5.20 per ton. A cost analysis conducted to evaluate the impact of increased truck waiting time at the mill on farm level harvest costs found that for every one minute of waiting time at the farm during harvest operations, the total harvest fuel and labor costs were increased by approximately $1.30 per acre. An integer linear programming model was developed which simulated the daily delivery of approximately 10,000 tons of harvested sugarcane with the goal of scheduling harvest operations of all farms to better coordinate trucking operations. Results of the linear programming analysis demonstrated that transport operations between farm and mill, which impacts harvest operation efficiency, could be improved with better coordination of harvest operation scheduling across a large group of farms.

Louisiana is the beneficiary of more than 30% of the U.S. coastal wetlands, but the states wetland loss accounts for about 90% of the total throughout the continental United States. The Coastal Wetlands Planning, Protection and Restoration Act of 1990 and the $1.9 billion that has recently been dedicated by Congress for coastal restoration activities will certainly aid in restoration efforts. However, these dedicated funds are but a small fraction of the total monies that will be required to maintain/restore Louisianas degraded wetlands. Recent estimates suggest restoration activities will cost, at a minimum, about $14 billion. The research, based on 119 wetland property transactions throughout Southwest Louisiana, develops an hedonic model which relates price to various property characteristics. These characteristics include type of property (i.e., fresh marsh, intermediate marsh, brackish and saline marsh, open water, and other property), distance from the nearest road, distance from the coast, and whether the property is in an area where projected wetland loss during the next 50 years is anticipated. Results indicate that fresh marsh and other land (this is a catchall category for property that is not specifically delineated as wetlands or open water) is valued more than open water (on a per acre basis) in the private market. However, intermediate marsh is valued less than open water in the private market. Depending upon the model specification, brackish and saline marsh is valued in the private market as either higher than open water or the same as open water (in a statistical sense). Results further suggest that buyers will, at least to some extent, discount properties in those areas where future wetland loss is anticipated (i.e., prices of properties in these areas are less after controlling for the influence of all other factors). This discounting increases as the rate of projected loss increases. Whether this discounting of future losses reflects previous losses remains untested.

This study uses a translog cost function to investigate the technical and economic relationships present among a sample of Florida grouper longline vessels. The existence of jointness-in-inputs and non-separability between inputs and outputs suggests that resource management should be based on multiproduct production theory, and that explicit recognition of the economic interactions among species should be incorporated in any regulatory process. The cross-price elasticities of input demands showed substitution relationships between input pairs, implying that imposed regulation on the single input will be compensated for by increases in the other inputs. Furthermore, model results showed apparently substantial economies of scope, especially between red grouper and most of the other species in the grouper fishery, product specific economies of scale and multiproduct economies of scale. The technical and economic interrelationships inferred from this study suggest that individual species regulation can generate economic inefficiency by inducing nonoptimal input and output mixes.