It is well known that an amenity is a key driving engine to regional economic growth. However, the site-specific nature of an amenity can characterize them as public goods. Due to this characteristic, local governments have difficulty optimally supplying amenities. This dissertation tries to find relationships between an amenity and economic growth. Three empirical papers comprise the original research in this dissertation. The findings of the meta-analysis in the first essay suggest little methodological diversity exists among researchers linking amenities to economic growth., I do find that employment growth is more likely related to man-made amenities even in research on rural areas than natural amenities. Further, incorporating spatial estimators into amenity research improves modeling performance while reducing the net impact of amenities on economic growth. The second essay indicates a distinctive distribution between man-made amenities and natural amenities over counties of the United States. While man-made amenities are agglomerated in urban areas, natural amenities show heterogeneous dispersion. Both agricultural land and conservation land show an inverse relationship to man-made amenities across space. From an analysis using a local governments public policy along with an areas physical attributes, I find government tax policy having the greatest effect on film location decisions with natural amenities having little impact. The third essay analyzed the impact of a tax incentive program targeted to film industries on local economies using a quasi-experimental approach. This last essay provided three findings. First, this chapter found meaningful methodological specifications that should be considered in regional studies using a quasi-experimental approach. They are appropriate consideration of control periods, spatial units of comparison, and validities of dummy variables representing extraneous shocks. Second, the impact of the film industry tax program on local economies is insignificant for most industries. Third, the influence of tax subsidy policy on local economies is limited to a central area but is not beneficial to its adjacent areas.

The state of Louisiana has been hit by several severe hurricanes in recent years, and these disaster events have placed a financial burden on parish budgets. As such, local governments have been compelled to bear various cleanup and recovery costs in the short and long term. Therefore, this research sought to evaluate the factors that drive the variation in the financial health of local governments in Louisiana. This research made two contributions. The first contribution sought to develop a comprehensive measure of economic activity at the county level, and the second contribution used econometric methods to estimate the effect of selected macroeconomic indicators on the financial health of local governments. Gross domestic product (GDP) was selected as the economic activity metric because it was found to be a more comprehensive economic activity metric than the other economic metrics historically applied to measure the size and scope of a region. Three methods to estimate GDP at the county level were developed, and a systematic approach was used to select the best method. Whenever earnings data were fully disclosed, this research used a ratio of state earnings to state GDP to estimate GDP at the county level. When earnings data were not fully disclosed, however, a ratio of state employment to state GDP was used. To examine the effect macroeconomic indicators of local government financial health, nine financial ratios were generated using data from county financial statements. These ratios came from the categories of profitability, liquidity, capital structure, and performance. Two methods were developed to regress each of these ratios against selected economic and demographic indicators, including GDP, assessed valuation, hurricane damage, and lagged or initial values of the ratio being examined. The first method was a double-log random effects model, and the second method was an ordinary least squares model, which used the change over time in each of the variables as the parameters. Both methods found the damage variable to have a significant negative effect on county government financial health, supporting our hypothesis.

Field studies were conducted in Crowley, Louisiana and Stoneville, Mississippi in drill seeded rice to evaluate weed control, yield, and economical returns with imazethapyr programs. Red rice (Oryza sativa) and barnyardgrass (Echinochloa crus-galli) was evaluated with imazethapyr applied alone at various rates and application timings. Imazethapyr, averaged across rate, controlled red rice 89% and barnyardgrass 90% when the initial application of imazethapyr was applied at emergence followed by (fb) a second application of imazethapyr two weeks after the initial application. While imazethapyr, averaged across timing, showed no differences for red rice and barnyardgrass control. Yield and economical returns were maximized when the initial application of imazethapyr was applied at rice emergence fb a second application of imazethapyr two weeks later. Research was conducted in Crowley, Louisiana in 2008 and 2009 to evaluate the addition of different propanil formulations in mixture with a standard imazethapyr program of 70 g/ha early postemergence fb 70 g/ha late postemergence. Weeds evaluated included red rice, barnyardgrass, Texasweed (Caperonia palustris), and alligatorweed (Althernanthera philoxeroides). Weed control of all weeds evaluated with treatments consisting of a propanil formulation in mixture with imazethapyr was equivalent to, or higher, than the standard imazethapyr program. Yield and economical returns were maximized when the propanil formulation of RiceShot® or Stam M4® was in mixture with imazethapyr in the initial application. The addition of propanil in mixture with imazethapyr increased rough rice yield and economical returns due to the increased weed control Research was conducted in Crowley, Louisiana in 2008 and 2009 to evaluate the addition of a herbicide with soil residual activity in mixture with imazethapyr applied very-early postemergence fb an application of imazethapyr or imazamox two weeks after the initial application. Weeds evaluated included red rice, barnyardgrass, Texasweed, and alligatorweed. Weed control with treatments including a herbicide with soil residual activity was equivalent to or higher than imazethapyr applied alone fb imazethapyr or imazamox. Yield and economical returns were maximized with quinclorac or penoxsulam mixed with imazethapyr fb imazethapyr or imazamox. The addition of quinclorac or penoxsulam proved to be beneficial in a total weed management program.

The economic question this study seeks to answer is why healthier food products are less expensive in some stores than in others and in some neighborhoods than others. The analysis builds upon the precedent of past retail food pricing studies that have been conducted in Southeastern Louisiana and in other parts of the country, by further examining disparities of retail food costs across store formats and neighborhoods with different demographic compositions. It utilizes a comparison of a general market basket of food items used in past studies and a "representative" market basket that is regionally specific to Southeastern Louisiana to see if the composition of a selected market basket of goods impacts results. Specifically, the objectives of this study are to: 1. Determine whether the cost of a market basket that is composed of more representative regional food items that meet the 2005 Dietary Guidelines for Americans (DGA) differs from that of a general market basket developed by Pennsylvania State University researchers to meet the Thrifty Food Plan menu based on the 1995 DGA. 2. Determine whether demographic characteristics of a neighborhood have an influence on the cost of a healthy market basket of foods in that neighborhood. 3. Determine whether demographic characteristics of a neighborhood have an influence on the competition of supermarkets in that neighborhood. 4. Determine whether store size, type, and competition influence the cost of a healthy market basket in Baton Rouge, LA. The results of the study show that neither the TFP nor the 2005 DGA market basket of food items cost more, on average, at stores that are located in lower income areas in the Baton Rouge, LA, metropolitan area. The composition of the market basket including more representative, regionally-specific food items does not notably impact results. It can be concluded that food costs are significantly influenced by the management structure and store format, with chain stores and supercenters having the lowest market basket costs. A visual inspection of the distribution of large grocery stores suggests that some areas are more disadvantaged than others, especially rural areas.

A survey data by Singer et al. (2007) was used to study the factors affecting the adoption of cover crops by the producers at the Corn Belt area of the United States. Data was collected from four states: Illinois, Indiana, Iowa, and Minnesota. Two binomial logit models were used for the econometric analysis. The first logit model was used to observe the factors affecting the adoption of cover crops by the producers. The second logit model was used to analyze the factors affecting the adoption of cover crops by producers in recent years, specifically, in past five years. The result of the study suggested that access to proper information about use and management of cover crops has positive and significant effect on adoption of cover crops. The results also suggest that producers who grow small grains like wheat and oats and producers who grow both crops and livestock are more likely to use cover crops. In recent periods, i.e., the past five years, the results suggest that number of acres farmed have a positive and significant effect on the adoption of cover crops. Also, in recent years, university extension programs did not have significant effect on the adoption of cover crops in the Corn Belt region of the United States.

This thesis studies the off-farm labor supply decision of farm operators and their spouses in the United States. The data used in this study is from the Agricultural Resource Management survey, 2006. The objective of this study is twofold. First, to identify those factors that affect off-farm labor supply of farm operators and their spouses. In particular, this study investigates the impact of human capital of farm operators and spouses, personal, family, farm and location characteristics on labor allocation for on- and off-farm work. Empirical results indicate that farm operators and their spouses human capital are positively correlated with off-farm labor supply. In addition, the number of children in a household is inversely related to a spouses off-farm employment. Similarly, a households net worth and farm size have a negative impact on off-farm labor allocation decisions by both farm operators and their spouses. Payments from government programs have a negative effect on labor allocation for non-farm work. The availability of health insurance to farm operators and their spouses from off-farm employment has a positive effect on labor supply for off-farm work. The second objective of this study is to compare results obtained from a parametric probit model and a semiparametric additive probit model of off-farm labor supply by farm operators and spouses. One of the most important aspects of semiparametric analysis is to identify smoothing or nonparametric variables in a regression model. The Blundell and Duncan (1998) approach shows that farm size is such a smoothing variable in the off-farm labor supply model. A semiparametric additive regression model identifies a few significant covariates as compared to a parametric probit model; however, the Hong and White (1995) specification test and likelihood ratio test favor a semiparametric model in this study. In particular, the graphical plots of fitted values from parametric and semiparametric models also show that a semiparametric model is preferred. The semiparametric model helps to formulate appropriate functional form of off-farm labor supply in the United States, which might be the subject of further study of this research.

A national web survey was used to collected data from 253 households in the United States. Choice-based conjoint analysis was used to investigate which packaging and labeling attributes U.S. consumers consider important when choosing 100% fruit juices, and to estimate their willingness-to-pay. The attributes were packaging material, nutritional and health claims, presence of organic ingredients and whether the product was produced locally. Factor analysis, cluster analysis and a median split technique were used to identify market segments based on consumer preferences, behavior, and lifestyles. Differences between the segments were analyzed. A conditional logit model was used to estimate relative of importance and willingness-to-pay for the different attributes. Results from the study show that consumers place positive values on, and are willing to pay a premium of ($1.04) for the Polyethylene Terephthalate (PET) bottle, and ($0.29) more for the no sugar added claim. Consumers with high environmental interests were more likely to pay a premium for a fruit juice with organic ingredients and a nutritional index on the label. High information seekers are willing to pay ($0.13) more for the nutritional index, compared to ($0.05) that low information seeker will pay. Younger people are willing to pay more for local products and more than double ($1.41) of what older people will pay ($0.67) for a PET bottle.

The search for improved methods of estimating crop yield density functions has been a theme of recurrent research interest in agricultural economics. Crop yield density functions are the statistical instrument that generates probability estimates of yield risk, and risk is an important decision variable in production agriculture. Recent research in crop yield density estimation suggests that yield probability estimates can be sensitive to the way yield data are filtered, and if true, then the search for an adequate filter is warranted. Such a quest is pursued in this study. It is proposed that unit-root tests can be used to identify the time-series properties of yields and that the outcome of these tests makes the choice of an appropriate filter trivial. Once a filter has been chosen, then nonparametric methods can be used to more flexibly fit a crop yield density function. The study uses state and county level (aggregated) yield data for corn and soybeans in Arkansas and Louisiana for the period 1960-2008, comprising 121 yield series. The results identify three main types of yield processes (and filters), namely, a unit-root (first differences), a trend stationary process (detrending), and stationary (remove the mean). More specifically, the study finds that for Louisiana soybeans, for example, 73% of the county yields studied can be represented by a unit-root process, 12% followed a trend stationary process, and the remaining 15% were stationary. One important implication of this finding is that the use of a universal yield filter may generate inaccurate yield probability estimates, which translates into inaccurate estimates of crop insurance risk premia. To shed light into relevance of these findings, yield density functions were estimated under alternative filtering scenarios and pairwise probability estimates compared. In particular, the results suggest sizeable differences in the two estimates, which at times can reach -1,153.65%. In addition to providing a detailed analysis of the findings, the study assessed the relevance of the findings in the context of two current risk management programs, namely a group risk plan (GRP) and average crop revenue election (ACRE) program. Limitations of the study are also highlighted.

Current trends in the U. S. dairy industry show an increase in milk cows per farm and milk production per cow, though the total number of milk cows in the industry is declining. This increase in productivity is attributed to advancements and adoption of modern dairy technologies. Breeding technologies are one of the important components of this structural change. This study analyzed the factors affecting the adoption of modern breeding technologies such as artificial insemination, embryo transplants, and sexed semen, and the impact of these technologies on farm productivity and profitability. Results of a bivariate probit model with selection showed that the adoption decision is affected by different farm and farmer attributes such as age, education, off-farm work, farm size, and specialization. The embryo transplants and/or sexed semen technology adoption decision was also influenced by the farmers planning horizon. Farm impact was assessed by estimating net returns and cost measures using ordinary least squares methods. Endogeneity and self-selection bias issues were also tested and corrected for in the impact models. Both artificial insemination (AI) and embryo transplants and/or sexed semen (ETSS) technologies are found to have significant and positive influences on net returns over total and net returns over operating costs per hundredweight of milk produced. Results also suggest that a higher allocated cost is associated with ETSS adoption. Relatively younger, more highly educated farmers and larger and more specialized farms received higher net returns. Since some part of the costs involved in ETSS may be for conducting artificial insemination, larger farms that had already adopted AI may consider ETSS adoption. Adoption decisions on a farm, however, would be based on the added advantages of ETSS adoption versus the additional costs of adopting these.

The development of an efficient biomass supply chain is pivotal for the cellulosic ethanol industry. The Louisiana Sugarcane Belt, and energy cane are the focus of this study. From both the producer and processor perspectives, cost of production, competitiveness of cellulosic ethanol, biomass pricing, changes in crop mix, and the optimal location for cellulosic ethanol processing facilities are the critical factors evaluated. Educating potential energy cane producers on production costs and agronomic practices is the first step in the biomass supply chain. This study finds that for energy cane producers to breakeven, processors need to pay producers at least $30 per ton of biomass. The breakeven price producers require, decreases if new varieties with higher yields and for a longer sustained production cycle are developed. These new varieties also help to increase the competitiveness of the cellulosic ethanol industry relative to the corn ethanol industry by driving down feedstock and transportation costs. For processors to induce the production of energy cane they have to provide producers with expected net returns per acre that are at least equivalent to that of sugarcane. Numerous methods on pricing biomass exist but this study investigates variable pricing strategies, based on corn, crude oil, and ethanol prices, and a two-tiered hybrid strategy that guarantees a portion of production cost plus a fixed amount per ton of biomass production. Results indicated that none of the pricing strategies induce the production of energy cane relative to sugarcane, but minor adjustments to the ethanol and hybrid strategies makes them viable options for processors. Depending upon the pricing strategy implemented, producers alter crop allocation decisions to maximize net returns per acre. Primarily rice and soybean acres in the region decline allowing for the production of energy cane. As the crop mix changes in the region, the cost minimizing location for a cellulosic ethanol plant changes. Results indicate that for a single processor operating Belt the optimal location is St. Landry Parish. Increasing the number of processors in the region to two, decreases total transportation costs decrease and the optimal locations for the plants are Acadia and Pointe Coupee Parishes.