This paper offers three different regional output-by-industry forecasting techniques (time series, Social Accounting Matrix (SAM)-based, and Computable General Equilibrium (CGE)-based) and two different occupation-by-industry matrices (national and state geographies) for use in the creation of industry/occupation employment forecasts. Estimates are compared to actual data from eight years from 2001 to 2010. OLS regressions are run to determine how well modeled employment estimates fit actual employment for the state of Louisiana. A meta-analysis style regression of the R-sqaured values on model characteristics (accounted for using Boolean dummy-variables) determines that industrial output forecasting techniques do not provide statistically different R-squared values, but that models which use the state level occupation-by-industry matrix constructed for this paper should expect a statistically higher (by about 3.5%) R-squared value.

The markets facing nursery producers have changed dramatically in the past decade. These changes in nursery markets have outdated previous research. New research into nursery marketing will assist nursery producers in making marketing decisions. Nursery producers can market their plants to five different marketing channels: Mass-merchandisers, garden centers, other retailers, landscapers and re-wholesalers. This study described the 1998 Louisiana nursery industry, analyzed nursery market changes over the past decade in Louisiana and the Southeast and analyzed characteristics of Louisiana and Southeastern nurseries to estimate marketing channel choice. Data was collected via mail using the third Trade Flows and Marketing Practices survey. Non-respondents to the mail survey were contacted by telephone to obtain survey information. The resulting data set was compiled and tabulated to form a description of the 1998 Louisiana nursery industry. Data from the 1998 TFMP survey was compared with data from the 1988 and 1993 surveys. An analysis of variance for each of the marketing channels was performed to determine if and how marketing channel use had changed over the decade. In order to estimate marketing channel use, a model was designed with the proportion of sales through each channel as a function of a set of market oriented variables such as sales, acreage, age, contract sales, transaction methods, in-state sales and sales to four or more marketing channels . A system of five equations was designed to estimate marketing channel use, one equation for each marketing channel. Analysis of the Louisiana nursery market over the past decade showed that Louisiana nurseries have increased sales to retailers and re-wholesalers at the expense of landscapers. Analysis of nursery marketing channel choice revealed that nurseries have little market power to make marketing decisions. It appears that the retailers and the market dictate marketing decisions in the nursery industry.

As a result of the Uruguay Round (UR), the impact on the international rice market is profound. In addition, another round of the WTO trade negotiations has started and the impacts of potential policy changes on rice trade are unknown. The major U.S. benefit of the UR has been the access to the Japanese market. However, the U.S. share of this import market has been unstable and the share of Korean rice market is zero percent. Therefore, this study attempts to analyze the potential implication of U.S. rice exports to Japan and Korea. The Japanese and Korean rice economies as well as U.S. export demand are analyzed using empirical supply and demand models. This study captures the dynamics inherent in supply and demand of the Japanese and Korean rice sectors. For the study, the supply parameters are estimated using two stage least squares (2SLS), and the demand equations are estimated using ordinary least squares (OLS). Since rice is a political commodity, this study incorporates the political influence of various interest groups in the policy-making process. The analysis measures the pattern of the implicit political weights given to the interest groups, considering a Political Preference Function (PPF). In the final stage, the estimated elasticities and political weights are incorporated in a noncooperative dynamic game framework to analyze the possible impacts of policy changes in the three countries. This study analyses various policies, including several reasonable scenarios regarding changes in Japanese and Korean tariff equivalents from 2% to 8% with respect to U.S. export programs, such as credit guarantee and market development programs. The results show that the best export policy option from the U.S. perspective is obtained at a 4% tariff reduction for Japan and Korea under a combination of U.S. market access program and foreign market development program. The results suggest that the U.S. policy makers might focus more on the U.S. export policy options than the tariff reduction of Japan and Korea. However, it depends on how the policies are implemented, given the state trading enterprises and implicit trade barriers in both countries.

The general objective of this research project was to study the consumption behavior of U.S. Hispanics for meat products. A comprehensive review of literature on the studies of U.S. Hispanic consumers was performed by means of a systematic survey; different sources of information useful in studying Hispanic consumers were documented. The simultaneous increase in population and income of Hispanics in the United States is attractive to food companies, and makes more relevant the study of their consumer behavior patterns for discovering future market opportunities. Censored incomplete demand systems of the LinQuad form were used for recognizing the consumption patterns by Hispanics with those of Whites, African Americans, and households of other minorities. The analyzed dataset was extracted from the Consumer Expenditures Survey released by the U.S. Bureau of Labor Statistics. The estimation of elasticities required two steps; in the first step, the decision to purchase was modeled and in the second step demand equations using instrumental variables were estimated to eliminate selectivity bias. Both steps used a concatenated forward stepwise modeling approach. It was found that Full Information Maximum Likelihood (FIML) under a high level of censoring produces inconsistent own price elasticities and bigger standard errors, due to violations of multivariate normality of the error terms and high level of censoring. The discussed results come from Iterative Seemingly Unrelated Regression since it was able to produce a greater number of significant parameters and more consistent elasticities compared to FIML. The role of ethnicity in the consumption of meat products in the U.S. marketplace was evaluated by means of a demand system that had dummy variables for comparing patterns of Hispanics with the rest of the ethnic groups. Hispanics on average allocated more for total food expenditures, consumed more at home, and spent 21.5%, 8.1%, 5.4% more on meat products than Whites, African Americans, and households of other minorities, respectively. Three sets of demand systems are presented. The first set includes elasticities from demand systems that only included prices and income; the second set is augmented with household size in Amsterdam scale; the third set uses the complete proposed set of demographics.

Farm firm decision making processes have long been of concern to agricultural economists. The concept of maximizing utility rather than profit is an important concept in multidimensional goal research. The prevalence of low or negative net returns in Louisiana beef and dairy production leads to the hypothesis that goals other than profit maximization compete strongly in producers' decisions. The objective of this study is to determine the hierarchy of goals that motivate beef and dairy producers and evaluate them in a multi-dimensional framework. Seven goals were evaluated in producer decision making: Maintain and Conserve Land, Maximize Profit, Increase Farm Size, Avoid Years of Loss / Low Profit, Increase Net Worth, Have Time for Other Activities, and Have Family Involved in Agriculture. Each goal's weight is its importance in the measurement of the farmer's utility. Weights were elicited using the fuzzy pair-wise comparison and simple rank ordering procedures. Using the fuzzy pair-wise comparison method, the goal weight ranged between 0 and 1 and the errors for each of the goal equations were contemporaneously correlated. Thus, logistic seemingly unrelated regression was appropriate to use in regressing the weights of goals on explanatory variables such as production characteristics, risk preference, social capital, environmental attitudes and others. Goal hierarchies of producers were elicited via mail survey. Of 13,100 Louisiana beef producers, 1,472 were surveyed. For producers with less than 100 animals, Maintain and Conserve Land and Increase Farm Size were the most and least important goals, respectively. Producers with more than 100 animals weighted Avoid Years of Loss / Low Profit as the most important goal and Increase Farm Size as the least important goal. The entire population of dairy producers (428) was surveyed. Avoid Years of Loss / Low Profit was slightly more important than Maximize Profit. Increase Farm Size was the least important goal. Overall, dairy producers placed more emphasis on profit related goals such as Maximize Profit, Avoid Years of Loss / Low Profit, and Increase Net Worth. The most important goal of beef producers was Maintain and Conserve Land.

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.