This study identifies alternative occupations for heavy truck drivers and evaluates the relative attractiveness of these alternatives in terms of compensation, ease of entry and future job growth. We also evaluate the geographic correspondence between truck driving jobs and available alternatives within the same state given research evidence about geographic rigidities in job seekers. We develop two strategies for identifying alternative occupations. One approach suggests that there may not be sufficient job alternatives for a displacement of 35% or more of the truck-driving workforce. The second alternative suggests insufficient job alternatives when displacement levels exceed 50%. Despite these varied pictures, our results present some important trends among job alternatives. Most alternatives were in Job Zones 1 and 2 which require little additional training and/or education for displaced drivers. Unfortunately, the identified alternatives paid lower wages than truck-driving jobs, indicating a potential loss of income. The projected demand for alternative jobs also varied by occupation. Some alternatives are projected to have employment growth, while others are projected to have job losses. Lastly, there were geographic trends in states projected to experience greater losses of driving jobs, and that do not have sufficient alternative jobs for workers. Our findings indicate that this is particularly true for states located in Middle America. Proactive labor policies that are tailored to the regional labor market and available job alternatives will be needed to help truck drivers transition into new occupations. These policies should be particularly mindful of the specific characteristics of the truck-driving workforce.

Research analyzing perceptions of water services has focused on water quality, water safety, and the propensity to consume water from different sources. It has not assessed perceptions of water costs. To address this knowledge gap, this study collected nationally representative survey data from households in the United States about water issues and incorporated these data into logistic regression models. In doing so, our study advances the water and public policy literature in three ways. One, it addresses the need for household resolution information about water issues given the absence of data at this scale in the United States. Two, it creates and utilizes one-of-a-kind survey data to understand the perceptions of household water bills and the drivers of these perceptions. Three, we assess the impact of proposed solutions to improve water affordability on household perceptions of water costs. Model results indicate low-income and households in underrepresented groups were more likely to perceive their water bills to be too high. The perception of water costs also varied geographically. From a policy perspective, model results indicate utilities can positively affect perceptions of water bills via the frequency of water billing and provision of payment assistance programs.

Rising infrastructure costs for water providers and the rising cost of water for households pose several challenges for water providers, policy makers, and the research community. Consumers may utilize several strategies for coping with rising water costs including reduced water use or spending reductions on other household goods and services. To provide a first glance at the link between rising water bills and consumer spending, this study analyzes data from a household survey in the United States to understand how consumers may change spending behavior given various water bill increase scenarios. Results of this analysis provide insights into the demographics of households likely to be affected, the industries that could be affected, and at what bill increase levels these trends are most pronounced. While additional research on this topic is needed, these results suggest a stronger emphasis on long-term water management planning and allocation of resources to building and maintaining water infrastructure may be required. For utilities, this means a consideration of nonrevenue sources of funds to pay for rising water costs and strategies for making water more affordable for customers without deferring infrastructure improvements.

Research on producer willingness to adopt individual best pasture management practices (BMPs) is extensive, but less attention has been paid to producers simultaneously adopting multiple, complementary BMPs. Applications linking primary survey data on BMP adoption to water quality biophysical models are also limited. A choice-experiment survey of livestock producers is analyzed to determine willingness to adopt pasture BMPs. Sediment abatement curves are derived by linking estimates of producer responsiveness to incentives to adopt rotational grazing with a biophysical simulation model. Current cost share rates of $24/acre should yield a 12% decrease in sediment loading from pastures.

Government subsidy programs incentivize livestock managers to adopt best management practices (BMPs), such as rotational grazing, water tank systems, stream crossings, and pasture improvement to prevent or reduce soil erosion. This paper addresses the challenge of integrating socio-economic data on BMP adoption behavior with hydrologic/biophysical models to analyze the association between incentives, BMP adoption, and changes in soil erosion rates. Using primary survey data of livestock producers in an East Tennessee watershed, this research estimates willingness to adopt BMPs among livestock producers. The propensity to adopt one or multiple management technologies, given an incentive, is estimated with a multivariate probit regression. The likelihood producers adopt one or a combination of practices is then integrated into the Soil and Water Assessment Tool (SWAT) hydrologic model to generate soil loss abatement curves for the watershed. Abatement curves specific to each hydrologic response unit (HRU) comprising the watershed are estimated and then aggregated to determine an aggregate abatement curve for the watershed. Based on the abatement curves, HRU are ranked according to cost efficiency.

Extensive beef cattle farming in the ridge and valley region of East Tennessee suggests that cattle producers could play an important role in improving water quality through the adoption of livestock best management practices (BMPs). This study examines factors influencing willingness to adopt four BMPs—rotational grazing, pasture improvement, stream water crossing, and water tank systems—by beef cattle operations in a southeast Tennessee watershed. Factors examined include farm and farmer characteristics, farmer attitudes, and a hypothetical incentive program encouraging adoption of these practices. Data was collected through a mail survey of 5,150 farmland owners in McMinn, Bradley, and Monroe Counties. Respondents were asked if they would be willing to adopt each of the four BMPs at a given cost share, with the cost share amounts ranging from 50% to 125% of the expected out-of-pocket costs of installation/annual management, and how many acres/units of the practice they would implement. Younger, more educated producers with higher income levels were more willing to adopt one or more of the BMPs. Higher cost share amounts appeared to have greater influence on adoption of stream crossings than on rotational grazing, water tanks, and pasture improvement. Pasture improvement showed the greatest level of overall adoption interest, although many would-be adopters had already taken steps to improve their pastures. Analysis suggests producers have the most interest in a bundle of BMPs that include rotational grazing, water tanks, and pasture improvements. The analysis also suggests a preference away from stream crossings and BMP bundles that included stream crossings, unless all four BMPs were concomitantly implemented. Factors influencing willingness to adopt were analyzed along with factors influencing adoption intensity using regression analysis. Cost-share incentives did not play a substantial role in explaining adoption, but the influence of other explanatory factors was similar to other results found in the BMP adoption literature.