The meat goat industry is one of the fastest growing agricultural sectors in the United States. However, there has been limited research on consumers preferences for goat meat; therefore, a choice experiment was used to assess consumer preferences for goat meat and/or live goats. A national online survey was conducted from April 27, 2012 to May 4, 2012. Respondents were asked to complete either the goat meat choice experiment, live goat choice experiment or both. In addition to the choice experiment, respondents answered a set of questions about goat meat consumption and purchasing behavior as well as demographics. The attributes that consumers evaluated for the goat meat choice experiment included, cut, color, source and price. The attributes that consumers evaluated for the live goat choice experiment included, age, sex, slaughter method, and price. The results revealed that goat meat consumers preferred chops and cubes over whole and half carcasses. The attribute, color, was not as important to consumers choice as hypothesized, in the estimated models the attribute was statistically insignificant or had a small effect on preference. Goat meat consumers valued domestic over imported goat meat. The random parameters logit model and latent class logit model revealed heterogeneous preferences. In the latent class model, age, gender, and consumption frequency did fairly well in defining the class; however, overall the demographic variables failed to distinctly characterize the classes. The results from the live goat choice experiment revealed that age and slaughter method were the most important attributes to consumers. These consumers valued younger goats and preferred to have the farmer to perform the slaughter.

Regional economists and policy makers are interested in forecasting economic changes that are likely to take place at local and state levels after exogenous shocks to an economy; that is, create disequilibrium conditions in terms of supply and demand. Impacts of such shocks could be observed at the level of employment, unemployment, commuting patterns, assessed property values, property and sales taxes and local level of expenditures in several categories. The objective of the first essay was to model the employment change decompositions of different effects in two major industries using a shift share analysis technique in context of Louisiana parishes before and after hurricanes Katrina and Rita. A correlation analysis test was performed to identify whether a distinct regional industry effect can be identified separately from a sub-region local effect in shift-share analysis. Results from the test indicated that the distinctiveness of spatial neighboring region effect and the localized effect was evaluated and they were two separate effects. The objective of my second essay was to model the Louisiana labor market for purposes of improving forecasting accuracy in regional economic modeling. Specifically, this was performed through the use of alternative regional econometric estimators in Community Policy Analysis System (COMPAS) models for Louisiana. Results suggested that panel data models increased forecasting performance compared to other models in the study, if measured in terms of traditional error measures. However, the mean comparison test suggested that panel models do not always display statistical improvement in forecasting. The third and final objective of my dissertation was to evaluate if a fiscal module under the COMPAS framework (an equilibrium model) fits better under a disequilibrium economic environment. I found that both a simple naïve model with one year lagged expenditure as well as a lagged expenditure model with revenue capacity variables significantly increased forecasting performance relative to the traditional supply/demand equilibrium model of the public sector. I also found weak evidence suggesting that in cases where the equilibrium model is used in a cross-sectional setting, quantile regression may improve forecasting performance given the attribute of lumpy public goods.

Agriculture can be defined as the domestication and farming of plant and animal species to produce food and fiber products. Our society is fundamentally dependent on agriculture as it is the primary source of nutrients essential to human activities. Historically, the introduction of agriculture and technological development thereafter drastically changed the way human civilization has evolved into what it is today. New technologies allow farmers to produce more outputs with fewer inputs. Saved resources from agricultural production, such as land, labor and time, were used elsewhere to produce other goods and services that enrich the quality of our life. The primary focus of my dissertation is how new agricultural technology is adopted by U.S. farmers in the face of risk and uncertainty surrounding todays agriculture. This dissertation contributes to the existing literature by reflecting the important recent trends in U.S. agriculture. In the first essay, I explore the implication of genetically modified crop varieties on farm households income from off-farm sources, which explains approximately 90% of total farm household income in the United States. The second essay studies the relationship between farm operators formal education and technology adoption. It reconsiders the conventional human capital theory and demonstrates that formal education can have a negative impact on technology adoption. The final essay focuses on the impact of farm producers attitude toward risk on their use of various risk management strategies.

An online survey was used to collect data on specialty crop farms in 2010 in Louisiana. The objectives included evaluation of familiarity with the Louisiana Food MarketMaker website and the All about Blueberries website, about marketing channels used, and the adoption of electronic and Internet based technologies to assist with marketing of differentiated products. Variables included use and effectiveness of marketing channels, level of use and quality of internet service, use of Internet-based functions and applications, barriers to internet use, frequency of use and usefulness of social media and smart phones, effectiveness of and familiarity with MarketMaker and All about Blueberries websites and specific application. Generally, despite small sample size, farmer characteristics from the Louisiana survey were reasonably consistent with results from the Census of Agriculture 2007. Descriptive analysis and Logit model were used for data analysis. Results from this study can provide useful information about these new (to many farmers) technologies for marketing. Familiarity with MarketMaker was strongly associated with share of total sales from vegetable crops, farmer occupation, Internet speed as a barrier, Internet use in farming and finding markets through MarketMaker in 5 percent significant level. Social media use in farming was statistically significant in explaining familiarity with All about Blueberries website. Internet use and specialty crop acreage also were significant. In addition, large impacts on the odds ratios were found. When speed of internet service was rated as not a barrier, familiarity with MarketMaker was higher. Significant impact of coefficients on odds ratios were found for both websites. Future questionnaires could segment users based on level of activity such as initial and intermediate involvement, improved ability to use the site for partners and for research, to manage risk, and for feedback for further development of the program. Length of the survey questionnaire was a limitation.

Regional classification and labor market study form an important part of any regional development efforts. Successful formation and implementation of developmental policies for a region requires a sound knowledge of the labor market situation and socioeconomic background of the region, which in turn leads ultimately to regional welfare. We find literature in the area of regional classification to be very inadequate. This study classifies Louisiana using a clustering approach in two different ways. First of all, Wards method has been used to classify Louisiana into labor markets based on two-way commuting flow between the parishes. Eight geographical clusters are formed and compared with eight Metropolitan Statistical Areas in Louisiana. Secondly, a regional classification for Louisiana is delineated based on four socioeconomic variables using K-means clustering method. Based on goodness-of-fit criteria, nine regional clusters have been formed.

The Critical Access Hospital (CAH) Program was created in response to the dramatic deterioration of financial conditions and the potential threat of closure of small rural hospitals under the Prospective Payment System (PPS). CAHs receive cost-based reimbursement for services provided to Medicare patients in exchange for accepting a number of restrictions. The PPS, which pays a fixed price per case, provides an incentive for hospitals to reduce costs and increase efficiency. In the first essay, I examine the impact of conversion to CAH status on hospital efficiency. The estimated results show that CAHs are less cost and allocatively efficient than non-converting, PPS rural hospitals, without being less technically efficient. Relative to their pre-conversion selves, CAHs appear to be slightly less allocatively efficient, while they are slightly more technically efficient, and no less cost efficient. The second essay examines cost efficiency differences between CAHs and non-converting, PPS rural hospitals using quality controls and alternative methods of efficiency analysis. The results show that CAHs are, on average, less cost efficient than non-converting, PPS rural hospitals. The third essay estimates the marginal effects of environmental variables on the technical efficiency of CAHs. The results suggest that enhanced Medicare reimbursement may not have had a detrimental effect on the technical efficiency of CAHs. Overall, the results of this dissertation have important policy implications. First, they show that cost-based reimbursed CAHs are, on average, between 4.5 and 6.7 percentage points less cost efficient than non-converting, PPS rural hospitals. This can be translated in a cost per CAH between $751,000 and $1.12 million (in 2005 dollars) higher than the cost that would have been under the PPS. Second, the results show that the technical efficiency of CAHs improved relative to the pre-conversion period and that CAHs are as technically efficient as non-converting, PPS rural hospitals. It may be the case that the CAH Programs requirements have resulted in technical efficiency improvements comparable to the PPS. Third, improved technical efficiency of CAHs in conjunction with their decreased cost efficiency suggest that reductions in CAHs cost efficiency may not be a function of direct overconsumption of physical inputs. Rather, decreased cost efficiency of CAHs may be driven by allocative inefficiency generated by the inability of these hospitals to substitute to lower input cost combinations in the production process.

With an overall lack of economic information available on energy cane production, the aim of this research has been to provide some insight on the economic feasibility of producing energy cane in Louisiana as a feedstock for cellulosic ethanol production. When dealing with a non-traditional crop such as energy cane, increased uncertainty surrounding potential costs and returns can make the crop seem much less appealing to potential producers. As a high-fiber hybrid of traditionally produced sugarcane, energy cane production costs have been estimated using a standard enterprise budgeting approach developed for sugarcane, along with actual yield and fiber data from energy cane field trials. Monte Carlo simulation was performed in order to estimate energy cane costs and yields under stochastic input prices and yield levels. Breakeven yields for third through sixth stubble were calculated in order to determine the potential optimal crop cycle length that would maximize an energy cane producers net returns. Delivered feedstock costs to an ethanol producer were estimated along with potential processing costs in order to assess the total cost of producing cellulosic ethanol from energy cane. Overall, the average variable cost of energy cane production was about $14 per wet ton and the average total cost of producing energy cane was approximately $23 per wet ton. Energy cane yield estimates ranged from 36 to 68 tons per acre and results suggest that the optimal crop cycle length for energy cane is production through sixth stubble, or 8 years. Compared to similar economic studies for other energy crops, the findings of this study indicate that energy cane is capable of producing higher biomass yields at a lower cost. Furthermore, the results suggest that cellulosic ethanol producers utilizing energy cane as a feedstock can attain a minimum ethanol selling price between $2.00 and $2.30 if processing costs remain below $0.90 per gallon and the energy cane supply is sourced from farms within a 40 mile radius of the processing facility.

The research problem of this thesis was to compare strategies and costs of protecting impatiens in greenhouse culture from western flower thrips that would provide a plant of acceptable quality to the market and would address the issue of development of resistance to commonly used pesticides by evaluating biopesticides. Partial budgets based on alternative strategies were identified. Six control strategies were identified from a combination of commercial growers, research experts and biopesticide recommendations from product distributors. The research-recommended strategy 6 had the highest total production cost ($197.44), while one of the grower strategies based on conventional pesticides had the lowest total cost ($153.28). The second growers strategy had the second lowest total cost by relying on scouting and pesticide application as needed. This strategy used the smallest quantity of pesticides, and was expected to reduce or prevent resistance and minimize environmental impacts. Biopesticides had higher prices than conventional pesticides. Three biopesticide recommendation strategies (3, 4 and 5) were in the midrange of production cost. The treatments containing biopesticides usually had higher product and production cost than treatments that included only nonbiopesticides. An integer linear programming model was developed to determine the optimal WFT control program for impatiens. Constraints included pesticide mortality and label limits on consecutive or total applications per crop cycle. All pesticides in the linear programming solution were conventional. Biopesticides were not included in the solution because mortalities of biopesticides were far below the threshold, according to research reported through the IR4 program. The costs of using pesticides include economic product costs and environmental costs. Using biopesticides to replace conventional pesticides in a rotation scheme of conventional ones with different modes of action could reduce water and soil pollution while maintaining crop quality.

The ever increasing demand for the shrimp products in the 1980s and 1990s caused the volume of shrimp imports to increase. The import of shrimp has had an upward trend, from 847 million pounds in 1997 to 1,636 million pounds in 2010.The imports price has declined since 1997. Along with the decrease in imports price, the U.S. domestic shrimp price has also declined. However, the annual production of shrimp from the Gulf of Mexico has, in the long-run, remained relatively stable. These facts indicate that there is not the same quantity-price relation between the U.S. domestic shrimp market and shrimp imports market. Therefore, an ordinary demand or an inverse demand can only demonstrate one aspect of demand behavior either the quantities consumed are a function of prices or the prices are a function of quantities demanded, and are not able to respond in a more complicated system of demand. The basic objective of this dissertation is to determine a closer approximation of the effects of events in the real U.S. shrimp demand market. To accomplish this objective, a mixed demand system was adopted. A mixed set of demand functions contains both coefficients of a regular demand system and of an inverse demand system (Barton, 1989). This study adopts the Brown and Lee parameterization (2006), known as the mixed Rotterdam demand system. The shrimp products were divided into two subgroups: 1) shrimp imports (group a); and 2) Gulf of Mexico shrimp landings (group b). Countries considered in the analysis include China, Ecuador, India, Indonesia, Mexico, Thailand, Vietnam, and a final category includes all other exporting countries ans named as Other Countries. Demand for Gulf shrimp is specified by size of shrimp with three sizes: Large, Medium, and Small. The U.S. imports from these countries were modeled in a quantity dependent framework, while demands for domestic shrimp products were modeled in a price dependent framework. The summary statistics and estimated results for the model parameters indicate that Thailand has the largest share and largest marginal share among all exporting countries and Gulf shrimp landings. As theoretically expected, all own-price elastisities of regular demand are negative, implying an inverse relation between the quantity of imports from a selected country and its price of imports. Among all countries, China, India, Mexico, and Vietnam have the largest and almost the same own-price elasticities (-0.40). Thailands own-price elasticity is smaller than these countries, although it has the largest share in U.S. total expenditure on shrimp products. This means that there are fewer substitutes for Thailands shrimp than these countries shrimp in the U.S. shrimp market. Cross-price elastisities of regular demand were positive, indicating that the price of a selected countrys shrimp has a direct effect on the quantity of other countries shrimp exports. The positive cross-price elastisities also indicate that the U.S. shrimp imports from different countries are substitutes for each other, as expected. Thailands export prices have the largest cross-price elastisities. This means that other countries quantities of exports are more sensitive to a change in Thailands export prices than the other countries prices and their own prices. The price elasticity/flexibility of inverse demand illustrates that no countrys export prices have a substantial effect on any size of Gulf landings. The most effect is associated with about 0.02% on the price of small size Gulf landings for a 1% change in the price of Thailands exports to the United States. Vietnam, India, Mexico, China, and Thailands income elasticities are greater than one. Therefore, one can conclude that a change in U.S. expenditure on shrimp products not only increases the consumption of these countries shrimp products but that the proportion (share) of these products also goes up in U.S. total expenditure on shrimp. Income elasticities for inverse demand represent the Gulf dockside price sensitivities relative to a change in U.S. expenditure on shrimp. Results illustrate that if U.S. expenditure on shrimp products increases 100%, the Gulf large, medium, and small size shrimp prices will increase 12%, 15%, and 19%, respectively. All of these elasticity estimates are statistically significant at 1% and 5% levels.

As a consequence of the growing concerns about human health and the environment, consumers are becoming more interested in grass-fed beef than conventional grain-fed beef. Therefore, the study of consumers preference towards grass-fed versus grain-fed beef steak is the focus of research. In this paper, 2,000 respondents who indicate they have eaten grass fed beef in the past years and 2,000 respondents that complete a nationally representative sample is the general population. Conjoint analysis is utilized to analyze the preference of consumers. Participants are presented ten hypothetical beef steaks to rate. All steaks are identical excluding their product type, source of production, grade and price. Respondents were asked to rate each product from 1 to 10. Results show that for both grass-fed beef eaters and the general population, the target market has a higher demand for local prime grass-fed beef with a USDA certification with a relatively lower price. Consumers who live in the west tend to purchase more grass-fed beef with USDA certification. The research also suggests among the four attributes, product type is the most essential attribute, followed by source as the second most important attribute for both groups. The highest utility rank for grass-fed eaters comes from the combination of grass-fed beef with USDA certification, local, prime, and $2.99 per pound; for general population, the highest utility rank is the combination of grass-fed product with USDA certification, local, choice, and $2.99 per pound. These results will help to reallocate input and resources as well as target and develop a market for grass-fed beef. Limitations to this research still exist because more interaction effect should be studied. Future research may focus on an increased number of variable samples in order to provide realistic assessments of the market allocation.