ENVIRONMENTAL POLICY AND NATURAL-RESOURCE-BASED ECONOMIC DEVELOPMENT

Environmental Economics and Policy,

COMMERCIAL AGRICULTURE AND THE ENVIRONMENT: AN EVOLUTIONARY PERSPECTIVE

Environmental Economics and Policy,

ACCUMULATION AND RENTAL BEHAVIOR IN THE MARKET FOR FARMLAND

A farmerÂ’s choices of tenure and farm size result from a complex interplay of economic factors technology, entrepreneurial ability, and personal preferences. This paper examines the qualitative effects of these factors on tenure and farm size in a dynamic optimization framework. One implication of the theoretical model is that changes in technology should cause systematic differences to be observed between rates of return on farmland and rates earned on comparable long-term assets. This implication is supported by an empirical test.Land Economics/Use,

FACTORS AFFECTING THE ADOPTION OF SUSTAINABLE AGRICULTURAL PRACTICES

The extent to which individual factors influence the adoption of sustainable agricultural practices is estimated using a logit model and data from a 1990 survey of West Virginia producers. The results are, as expected, different than those for conventional agricultural technologies. For example, the effects of human capital characteristics are significant, while those for structural and institutional characteristics are not. However, the likelihood of adoption of sustainable agricultural practices is affected most by the environmental characteristic of whether or not the producer is aware that ground water contamination exists on his farm. This creates an important "awareness effect" upon which policies to promote sustainable agriculture adoption can be formulated. It also implies the existence of a derived demand for sustainable agriculture.Farm Management,

STREAM WATER QUALITY MANAGEMENT: A STOCHASTIC MIXED-INTEGER PROGRAMMING MODEL

Water quality management under the watershed approach of Total Maximum Daily Load (TMDL) programs requires that water quality standards be maintained throughout the year. The main purpose of this research was to develop a methodology that incorporates inter-temporal variations in stream conditions through statistical distributions of pollution loading variables. This was demonstrated through a cost minimization mixed-integer linear programming (MIP) model that maintains the spatial integrity of the watershed problem. Traditional approaches for addressing variability in stream conditions are unlikely to satisfy the assumptions on which these methodologies are founded or are inadequate in addressing the problem correctly when distributions are not normal. The MIP model solves for the location and the maximum capacity of treatment plants to be built throughout the watershed which will provide the optimal level of treatment throughout the year. The proposed methodology involves estimation of parameters of the distribution of pollution loading variables from simulated data and use of those parameters to re-generate a suitable number of random observations in the optimization process such that the new data preserve the same distribution parameters. The objective of the empirical model was to minimize costs for implementing pH TMDLs for a watershed by determining the level of treatment required to attain water quality standards under stochastic stream conditions. The output of the model was total minimum costs for treatment and selection of the spatial pattern of the least-cost technologies for treatment. To minimize costs, the model utilized a spatial network of streams in the watershed, which provides opportunities for cost-reduction through trading of pollution among sources and/or least-cost treatment. The results were used to estimate the costs attributable to inter-temporal variations and the costs of different settings for the margin of safety. The methodology was tested with water quality data for the Paint Creek watershed in West Virginia. The stochastic model included nine streams in the optimal solution. An estimate of inter-temporal variations in stream conditions was calculated by comparing total costs under the stochastic model and a deterministic version of the stochastic model estimated with mean values of the loading variables. It was observed that the deterministic model underestimates total treatment cost by about 45 percent relative to the 97th percentile stochastic model. Estimates of different margin of safety were calculated by comparing total costs for the 99.9th percentile treatment (instead of an idealistic absolute treatment) with that of the 95th to 99th percentile treatment. The differential costs represent the savings due to the knowledge of the statistical distribution of pollution and an explicit margin of safety. Results indicate that treatment costs are about 7 percent lower when the level of assurance is reduced from 99.9 to 99 percent and 21 percent lower when 95 percent assurance is selected. The application of the methodology, however, is not limited to the estimation of TMDL implementation costs. For example, it could be utilized to estimate costs of anti-degradation policies for water quality management and other watershed management issues.Resource /Energy Economics and Policy,

A SPATIAL MODEL OF REGIONAL VARIATIONS IN EMPLOYMENT GROWTH IN APPALACHIA

In this study, a spatial equilibrium model of employment growth is developed and empirically estimated by Generalized Spatial Two-Stage Least Squares (GS2SLS) estimator using cross-sectional data from Appalachian counties for 1990-2000. Besides the existence of spatial spillover effects, the results suggest that agglomerative effects that arise from the demand and the supply side contribute to employment growth in the study area during the study period. The policy implications of the findings are: (1) Regional cooperation of counties and communities is advisable and may in fact be necessary to design effective policies to encourage employment growth; and (2) Policy makers at the county level may need to design policies that can attract people with high endowments of human capital and higher income into their respective counties.APPALACHIA, EMPLOYMENT GROWTH, SPATIAL MODEL

A Spatial Panel Simultaneous-Equations Model of Business Growth, Migration Behavior, Local Public Services and Household Income in Appalachia

In this paper we develop a spatial panel simultaneous-equations model of business growth, migration behavior, local public services and median household income in a partial lag-adjustment growth-equilibrium framework and utilizing a one-way error component model for the disturbances. This model is an extension of the jobs follow people or people follow jobs literature and it improved previous models in the growth-equilibrium tradition by: (1) explicitly modeling local government and regional income in the growth process; (2) explicitly modeling gross in-migration and gross out-migration separately in order to spell out the differential effects, which used to be glossed over under net population change in previous studies; (3) explicitly incorporating both spatially lagged dependent variables and spatially lagged error terms to account for spatial spillover effects in the data set; and (4) extending and generalizing the modeling and estimation of simultaneous systems of spatially interrelated cross sectional equations into a panel data setting. To estimate the model, we develop a five-step new estimation strategy by generalizing the Generalized Spatial Three-Stage Least Squares (GS3SLS) approach outlined in Kelejian and Prucha (2004) into a panel data setting. The empirical implementation of the model uses county-level data from the 418 Appalachian counties for 1980-2000. Generally, the results from these model estimations are consistent with the theoretical expectations and empirical findings in the equilibrium growth literature and provide support to the basic hypotheses of this study. First, the estimates show the existence of feedback simultaneities among the endogenous variables of the model. Second, the results also show the existence of conditional convergence with respect to the respective endogenous variable of each equation of the model and the speed of adjustment parameters are generally comparable to those in literature. Third, the results from the parameter estimation of the model indicate the existence of spatial autoregressive lag effects and spatial cross-regressive lag effects with respect to the endogenous variables of the model. One of the key conclusions is that sector specific policies should be integrated and harmonized in order to give the desirable outcome. Besides, regionally focusing resources for development policy may yield greater returns than treating all locations the same.Community/Rural/Urban Development,

Global, regional, and national disability-adjusted life-years (DALYs) for 333 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

BACKGROUND: Measurement of changes in health across locations is useful to compare and contrast changing epidemiological patterns against health system performance and identify specific needs for resource allocation in research, policy development, and programme decision making. Using the Global Burden of Diseases, Injuries, and Risk Factors Study 2016, we drew from two widely used summary measures to monitor such changes in population health: disability-adjusted life-years (DALYs) and healthy life expectancy (HALE). We used these measures to track trends and benchmark progress compared with expected trends on the basis of the Socio-demographic Index (SDI). METHODS: We used results from the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 for all-cause mortality, cause-specific mortality, and non-fatal disease burden to derive HALE and DALYs by sex for 195 countries and territories from 1990 to 2016. We calculated DALYs by summing years of life lost and years of life lived with disability for each location, age group, sex, and year. We estimated HALE using age-specific death rates and years of life lived with disability per capita. We explored how DALYs and HALE differed from expected trends when compared with the SDI: the geometric mean of income per person, educational attainment in the population older than age 15 years, and total fertility rate. FINDINGS: The highest globally observed HALE at birth for both women and men was in Singapore, at 75·2 years (95% uncertainty interval 71·9-78·6) for females and 72·0 years (68·8-75·1) for males. The lowest for females was in the Central African Republic (45·6 years [42·0-49·5]) and for males was in Lesotho (41·5 years [39·0-44·0]). From 1990 to 2016, global HALE increased by an average of 6·24 years (5·97-6·48) for both sexes combined. Global HALE increased by 6·04 years (5·74-6·27) for males and 6·49 years (6·08-6·77) for females, whereas HALE at age 65 years increased by 1·78 years (1·61-1·93) for males and 1·96 years (1·69-2·13) for females. Total global DALYs remained largely unchanged from 1990 to 2016 (-2·3% [-5·9 to 0·9]), with decreases in communicable, maternal, neonatal, and nutritional (CMNN) disease DALYs offset by increased DALYs due to non-communicable diseases (NCDs). The exemplars, calculated as the five lowest ratios of observed to expected age-standardised DALY rates in 2016, were Nicaragua, Costa Rica, the Maldives, Peru, and Israel. The leading three causes of DALYs globally were ischaemic heart disease, cerebrovascular disease, and lower respiratory infections, comprising 16·1% of all DALYs. Total DALYs and age-standardised DALY rates due to most CMNN causes decreased from 1990 to 2016. Conversely, the total DALY burden rose for most NCDs; however, age-standardised DALY rates due to NCDs declined globally. INTERPRETATION: At a global level, DALYs and HALE continue to show improvements. At the same time, we observe that many populations are facing growing functional health loss. Rising SDI was associated with increases in cumulative years of life lived with disability and decreases in CMNN DALYs offset by increased NCD DALYs. Relative compression of morbidity highlights the importance of continued health interventions, which has changed in most locations in pace with the gross domestic product per person, education, and family planning. The analysis of DALYs and HALE and their relationship to SDI represents a robust framework with which to benchmark location-specific health performance. Country-specific drivers of disease burden, particularly for causes with higher-than-expected DALYs, should inform health policies, health system improvement initiatives, targeted prevention efforts, and development assistance for health, including financial and research investments for all countries, regardless of their level of sociodemographic development. The presence of countries that substantially outperform others suggests the need for increased scrutiny for proven examples of best practices, which can help to extend gains, whereas the presence of underperforming countries suggests the need for devotion of extra attention to health systems that need more robust support. FUNDING: Bill & Melinda Gates Foundation