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Using rank-ordered logit regression, researchers typically analyze consumer preference data collected with Best-Worst Scaling (BWS) surveys. We propose a generalized rank-ordered logit (GROL) model that allows flexibility in modeling preference heterogeneity. The GROL and mixed rank-ordered logit model (MROL) accommodate preference heterogeneity. However, the GROL also allows one to model heterogeneity as a function of demographic or environmental variables. A Monte Carlo experiment compares the estimates of accuracy and precision of the proposed GROL estimation with the MROL specification. Simulation results suggest that the GROL model performs comparatively well when the GROL or the MROL is the true data-generating process (dgp). Coefficient and willingness-to-pay estimates of the GROL are more precise and accurate compared to the MROL when the MROL is the true dgp. We surmise that the increased precision of the GROL estimator arises from the added flexibility for modeling different sources of heterogeneity. An empirical application analyzes a BWS survey on consumer preferences for single-use eating-ware (SUEW) products made from biobased materials. Findings suggest that consumers value most product degradability and using non-plastic materials to fabricate SUEW. Consumers also valued the rapidity of product degradability and using non-plastic materials to make SUEW plates. Respondent attentiveness also affected willingness-to-pay (WTP) estimates across attributes. Results suggest attentive respondents were about $3.00 more WTP for biodegradable SUEW than inattentive respondents. • A rank ordered logit model is usually used to analyze Best-Worst Scaling (BWS) survey data. • This study presents a new model – a Generalized Ranked Ordered Logit (GROL) model for BWS data. • A Monte Carlo simulation compares the small-sample properties of the GROL and mixed ranked ordered logit (MROL). • Simulation results show that the GROL model performs well when either the GROL or the MROL is the true dgp. • An empirical application using a BWS survey on consumer preferences for single-use eating-ware (SUEW) products is presented. [ABSTRACT FROM AUTHOR]

Mastitis is a worldwide problem in dairy cows and results in reduced milk production, the culling of cows, and other economic losses. Bulk tank somatic cell count (BTSCC) over 200,000 cells/mL often indicates underlying subclinical mastitis in dairy herds. Several preventative measures that can be implemented to help improve the incidence of mastitis exist, but surveys find these practices not fully adopted by producers. The goal of this research was to analyze the farm and operator characteristics associated with BTSCC in dairy herds by analyzing a survey of dairy producers in the southeastern United States. We examined this region because it has experienced a decline in the number of dairy farms, dairy cows, and milk production over the past 2 decades. The southeast region is also associated with higher BTSCC levels than the national average. Dairy farms in Georgia, Mississippi, Kentucky, North Carolina, South Carolina, Tennessee, and Virginia were surveyed. Producers were asked questions about the BTSCC at which they take action to address BTSCC, the information sources they use to learn about and manage BTSCC, farm structure and management characteristics, and attitudinal variables associated with profitability, managerial control, and planning horizon. Least squares regression was used to determine how these factors were associated with BTSCC levels across the 7-state region. Concern over mastitis, financial consequences of mastitis, and increased previous-year BTSCC were associated with higher current BTSCC levels. Obtaining information about mastitis from veterinarians and extension personnel, taking action against mastitis at a BTSCC less than 300,000 cells/mL, and perceived ability to control processes and mastitis incidence were associated with reduced BTSCC. We found average BTSCC was lower in North Carolina and Virginia. These results suggest that proactive producers (i.e., those that perceive they can control BTSCC and seek information from reliable sources), were more likely to report lower BTSCC. As a result, it may be possible to achieve improved milk quality, evident from lowered BTSCC, across the region. [ABSTRACT FROM AUTHOR]

United States Department of Agriculture (USDA) conservation policy has increasingly shifted from a traditional land-retirement focus to greater emphasis on producer adoption of working-land conservation practices. This research made use of USDA integrated field/farm surveys, the Conservation Effects Assessment Project (CEAP) and Agricultural Resources Management Survey (ARMS), to (1) enhance understanding of operator, field, farm, economic, and environmental characteristic differences between conservation program participants and non-participants across a farm typology, and (2) to enhance understanding of the relative importance of these factors on influencing farm stewardship intensity in corn and wheat production, i.e., how these factors influence differences in producer adoption of alternative levels of land and pest-management practices between conservation program participants and non-participants. The research used a cost-function acreage-based technology adoption model to examine farm stewardship differences. Results indicate that program non-participants invest more heavily in land conserving and pest-management practices than program participants. Relative prices, structural, and socio-environmental factors play significantly different roles across crops, and between conservation program participants and non-participants, in their influence on producer adoption decisions for land and pest-management intensity. The environmental effectiveness and cost efficiency of conservation programs will likely improve when their implementation more explicitly recognizes farm heterogeneity as well as differences in farmer motivations for stewardship investments. Recognizing these differences can help improve targeting of conservation incentive structures. [ABSTRACT FROM AUTHOR]

Abstract: Information about soil nutrient carryover dynamics can assist cotton producers with the optimal management of potassium (K) fertilizer. Optimal K management promotes cotton plant health, may decrease input costs, and increases cotton lint yields. A dynamic programming model was developed to determine optimal K application rates and economic returns under different soil information scenarios based on cotton yield response to K fertilizer and fertilizer carryover estimates from a multi-year field trial. A Monte Carlo analysis was conducted to simulate the impact of stochastic input and lint prices and cotton yield on K management over a five-period planning horizon. Results suggest that soil test data could provide important information about K carryover potential, which may lead to more efficient fertilizer use and higher profit margins for cotton producers. [Copyright &y& Elsevier]

The Grassland Conservation Initiative (GCI) was introduced under the United States 2018 Agricultural Improvement Act. The goal of the GCI is to conserve pasture and grassland. This study analyzes the ex - ante impacts of the GCI on crop returns and land-use acreage for Oklahoma farmers and ranchers. Oklahoma's agricultural landscape is diverse. As with most agricultural policies focusing on land use, the distributional effects of GCI program will be conditional upon dominant land use types and grassland/pasture resources. Regions endowed with relatively more land resources in pasture and grassland are more likely to have more eligible acres, thereby potentially signaling to landowners in those regions opportunities to accrue land-holding rents. Land-use dynamics are estimated as a first-order Markov process. Not all regions benefit from this program. Findings suggest that aggregate net returns to cropland decrease. However, locations with above average pasture and grassland acreage experience gains in returns under certain policy assumptions. Counties experiencing gains from the GCI policy could experience higher returns to cattle and wheat compared to other counties with limited grassland and pasture acreage. • The distributional effects of the Grassland Conservation Initiative (GCI) is analyzed • Land in wheat is likely to transition into pasture and grassland • Eligible landowners in counties with greater grassland and pasture land resources most likely benefit [ABSTRACT FROM AUTHOR]

Abstract: The empirical evidence is mixed on whether urban growth boundaries (UGB) effectively moderate urbanization. The spatially varying effects of a UGB on land development patterns and land value in Eastern Tennessee, USA, were estimated to examine the impacts of the UGB in different submarkets. A simultaneous-equation model was used with an endogenous binary variable to reflect the parcel''s state of development and an endogenous continuous variable measuring parcel land value. Submarkets were identified using cluster analysis. The results suggest that the UGB slowed down development in urban submarkets but development accelerated in rural–urban submarket interfaces where the UGB did not play a role in land values. [Copyright &y& Elsevier]

Abstract: In recent years, the United States (US) government has put increasing emphasis on conservation programs geared toward rewarding good stewardship on working farmland. And, while the United States Department of Agriculture''s (USDA) farmland retirement programs continue to command the lion''s share of the conservation budget, roughly 80 percent of current land retirement contracts are due to expire before the end of the decade. With the 2007 US farm bill debate underway, policy makers will be making decisions about the future direction of farm conservation efforts. This paper examines the business, operator, and household characteristics of farms that have chosen to adopt conservation-compatible practices, with and without financial assistance from conservation programs. It sheds light on the relationship between adoption of conservation-compatible practices and conservation behavior, and how this relationship varies between farm business, operator, and household characteristics. Findings indicate that farm operator and household attributes, and farm business characteristics, affect the likelihood that a farmer adopts certain kinds of conservation-compatible practices. [Copyright &y& Elsevier]

This study analyzed differences between dairies that have closed compared with dairies still operating in the southeastern United States. Significant changes have occurred in the US dairy industry in the last decade, involving the number of dairy farms, herd size, milk quality, and management practices, yet the dairy industry remains the fourth leading agricultural sector in the United States, with $38 billion of milk sales in 2017. Although the number of dairy cows in the United States has remained relatively constant over the past decade, at approximately 9 million head, the number of dairy operations has decreased by 30%, resulting in larger dairies. This trend is even more prevalent in the southeastern United States, where the number of dairies has decreased by 39% from 5,315 in 2008 to only 3,235 in 2017. Additionally, downward pressure on bulk tank somatic cell count, which is used as a milk quality metric and has implications regarding animal health, intensified with US processors' introduction of incentive and penalty systems for quality milk production, necessitating better management of mastitis in dairy herds. In this context, this study examines factors that affect southeastern US dairy farms' persistence in the industry by using primary survey data collected in 2013 through a mail survey of Grade A dairies in Georgia, Mississippi, Kentucky, North Carolina, South Carolina, Tennessee, and Virginia. Dairies that were no longer operational had exited the industry from 2007 through 2014. A probit regression was used to determine which farm and operator characteristics were associated with the dairy's operational status. Dairy farms with more cows and higher average milk production per cow were more likely to be operational. For an additional 10 kg/d of milk production per cow, the dairy was 1.5% more likely to be operational. For each 100 additional cows a dairy had, it was 4% more likely to be operational. The analysis also identifies nonpecuniary determinants of operational status for southeastern US dairies, such as mastitis management practices. Findings suggest that operations capable of leveraging scale effects are more likely to remain operational, with results affirming the consolidation of the US dairy industry and demonstrating that more productive farms are more likely to stay in operation. Results also suggest that factors other than farm size affect a dairy's operational status. [ABSTRACT FROM AUTHOR]

This research combines Geographic Information Systems (GIS) and Mixed Integer Programming (MIP) model to determine feedstock supply, preprocessing facility, and biorefinery locations at a highly resolved spatial scale with the objective of meeting a large-scale annual biofuel production and demand goal for Tennessee, USA. Simultaneous determination of this supply chain network using MIP is computationally expensive. Memory limitation of typical personal computers constrain the network problem. High Performance Computing environments may require days to solve, and without any assurance of a feasible solution. This paper proposes a two-stage optimization procedure to overcome these computational challenges while maintaining theoretical consistency with conventional firm location theory paradigms. The two-stage procedure assumes that firms first identify biorefinery locations with comparative advantage in terms of supplying biomass. Step two entails determining if costs can be lowered with the addition of preprocessing facilities, and their optimal location relative to the biorefinery sites. In contrast, a single step optimization procedure siting multiple biorefineries and concomitantly preprocessing units and biomass supply areas assumes a different strategy for a single firm. Results suggest that the two-stage optimization approach is able to identify a feasible solution of multiple feedstock areas, feedstock preprocessing and fuel production locations using high-resolution spatial layers over a relatively large geographic region in a fraction of the computer resources required to solve a single, simultaneous location problem. The optimal supply chain network solutions generated from the two-stage and single simultaneous approaches are different. The absolute difference in the smaller scaled models’ objective values is less than 1%. [ABSTRACT FROM AUTHOR]

The objective of this paper is to design two types of subsidies for biofuel feedstock production and water quality improvement and to analyze how each subsidy affects biomass supply and the abatement of nutrient runoff associated with the conversion of cropland to biomass production. Per-hectare (per-ha) subsidy was designed as a system that pays producers for each ha of cropland converted to switchgrass production and per-megagram (per-Mg) subsidy was a system that pays producers for each Mg of switchgrass produced. This study focuses on Oostanaula Creek watershed in East Tennessee. The analysis used a dynamic programming model coupled with a Soil and Water Assessment Tool (SWAT) simulation model to predict profit-maximizing fertilizer application rates, crop yields, and nitrogen (N) runoff for a biofuel feedstock (switchgrass) and a conventional crop (corn) across 28 different landscapes in the watershed. A Monte Carlo analysis was conducted to simulate the impact of stochastic N fertilizer and corn prices and yields on subsidies over a ten-year planning horizon. A per-ha subsidy system is more cost effective and feasible than a per-Mg system because the former has significantly lower subsidy than the latter for each kilogram (kg) of N reduction and for each Mg of switchgrass harvested. Converting all of the cropland from corn to switchgrass over ten years results in 124,084 dry Mg of switchgrass and 23% reduction in nitrogen runoff for the per-ha system and 122,347 dry Mg of switchgrass and 3% reduction for the per-Mg subsidy system. [ABSTRACT FROM AUTHOR]

The cattle industry contributes to U.S. agricultural greenhouse gas (GHG) emissions. Prescribed grazing can help reduce GHG emissions. We examine a hypothetical third party certified labeling program for beef from livestock operations using prescribed grazing. Willingness to support and pay for beef with the label is estimated using data from a survey of U.S. consumers. The findings are encouraging for producers and retailers pursuing niche markets for beef products. Estimated annual household willingness to pay is $306 among program supporters and $64 among all beef-consuming households. Support and willingness to pay are influenced by demographics, attitudes toward the environment and food production-distribution system, as well as perceived policy consequences of their survey responses. [ABSTRACT FROM AUTHOR]

Future bioenergy demand will likely result in the conversion of significant amounts of crop and pasture/hay lands in the mid-south of US. The objective of this research is to analyze the effects of the large-scale land use conversion to switchgrass as a bioenergy feedstock on water quality and economic feasibility in Oostanaula Creek watershed in East Tennessee. The soil and water assessment tool (SWAT) model was first used to simulate nutrient loadings of current land use in the watershed. Statistical criteria such as Nash–Suttcliffe efficiency (E) and R 2 were calculated for model calibration and validation. The calibrated SWAT model was then used to simulate the effect of the land use conversion from the entire current crop and pasture/hay lands to switchgrass production. Results show that the conversion reduces average annual watershed loadings of sediment, nitrate (NO 3 ), total nitrogen (TN), and total phosphorous (TP) by an estimated 77%, 62%, 34%, and 46%, respectively. Analysis of net present values of ten years of farm profits and cost-effectiveness ratios for abatement of nutrient loadings indicates that the land use conversion is economically feasible. [ABSTRACT FROM AUTHOR]