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This study examines the decision process of household members in visiting local health care providers. It also explores the effect of various household level socioeconomic factors on motivating rural people to visit traditional versus modern health care providers in rural Bangladesh. I used the Population, Environment, and Poverty data collected from eight villages of rural Bangladesh in 1998 in addition to self-collected ethnographic survey information. The data suggest that a large majority of rural households attempt to visit locally available untrained health care providers first, and then trained doctors as the sickness worsens. The data also suggest that socio-cultural and economic factors are important in shaping their decision to visit traditional as opposed to modern health care providers. Training the traditional and untrained health care providers will be a wise option to ensure health care to the villagers.

Coffee producers typically sell raw coffee beans as the first step in a global value chain. Recently, groups of producers have formed coffee cooperatives that attempt to regain market power by integrating the other steps of the value chain. This study uses matching to estimate the effect of membership in one such cooperative on the household economy of indigenous coffee producers in the state of Chiapas, Mexico. It contributes to the literature by considering new determinants of participation and outcomes of interest. First, social capital at the individual and village level is correlated with cooperative membership more than other demographic factors. Second, cooperative members report an increase in the share of coffee sold and income from coffee sales but not in per-kilo price or total income. These two results reflect particular features of the Chiapas reality and the desires of the indigenous people the cooperative serves. Thus, they reiterate the importance for economic development projects to consider the context of their interventions.

Under the impetus of federal law, each state is required to develop Guidelines by which to determine presumptive child support awards following divorce. The key federal requirement is that during the specified quadrennial reviews of each state’s Guidelines, “a state must consider economic data on the cost of raising children.” Our purpose here is to compare presumptive child support awards provided in typical state Guidelines with the actual monetary costs of raising children.

To this end, we estimate these monetary costs from government data on consumer outlays in households with children as compared with substantially similar childless households. We review and reject current methods for determining child costs: both from income equivalence methods and those offered in annual government surveys; and provide quite different results despite using the same data employed by others.

Our econometric results indicate much lower monetary costs than reported for either of the two alternatives. Since presumptive child support awards in most states rely on current methods, these findings suggest that existing award structures should be re-evaluated.

Current award structures create a financial asset resulting from the gap between presumptive awards and monetary costs for custodial parents. This factor engenders resentment by support payers since it is his or her payments that fund this asset. And this resentment harms relationships between the parents. Increased willingness of non-custodial parents to make their assessed payments is an outcome promoted when payment amounts reflect the actual monetary costs of raising children.

In Bangladesh, girls’ ability to complete schooling is compromised by poverty and the practice of early marriage. Although most girls enroll in school, rates of dropping out are high around puberty. This paper uses a panel survey (2001 and 2003) of nearly 3,000 adolescent girls in rural Bangladesh to predict schooling outcomes. The analysis explores household and community factors to explain school enrollment, dropping out and marriage. Girls in poor households are more likely to drop out before reaching secondary school. Girls in wealthier households are more likely to drop out later, because of marriage, and having more siblings increases this possibility.

Micro hospitals are a new form of for-profit health-care facility with rapid expansion in some parts of the country. They continue to grow in Texas without in-depth public understanding or explicit policy guidance on their role in the health-care system. Our project aims to define socioeconomic and demographic characteristics of areas served by micro and regular hospitals, and by doing so help assess micro hospitals' impact in expanding health-care access for disadvantaged populations in Texas.

We (1) estimated hospital service areas (catchment areas) with a spatial model based on advanced Geographic Information System (GIS) methods using a proprietary ESRI traffic network; (2) assigned population socioeconomic measures to the catchment areas from the 2014–2018 American Community Survey 5-Year Estimates, weighted with an empirically tested Gaussian distribution; (3) used two-tailed t-tests to compare means of population characteristics between micro and regular hospital catchment areas; and (4) conducted logistic regressions to examine relationships between selected population variables and the associated odds of micro hospital presence.

We found micro hospitals in Texas tend to serve a population less stressed in health-care access compared to those who are more in need as measured by various dimensions of disadvantages.

Our analysis takes a cross sectional look at the population characteristics of micro hospital service areas. Even though the initial geographic choices of micro hospitals may not reflect the long-term population changes in specific neighborhoods, our analysis can provide policy makers a tool to examine health-care access for disadvantaged populations at given point in time. As the population socioeconomic characteristics have long been associated with health-care inequality, we hope our analysis will help foster structural policy considerations that balance growing health-care delivery innovations and their social accountability.

We used GIS based spatial modeling to dynamically capture the potential patient basis by travel time calculated with a street network dataset, rather than using the traditional static census tract to define hospital service areas. By integrating both spatial and nonspatial dimensions of healthcare access, we demonstrated that the policy considerations on the implications of equal opportunity for health-care access need to take into account the social realities and lived experiences of those experiencing the most vulnerability in our society, rather than a conceptual “equality” existing in the spatial and market abstraction.

This paper extends the behavioral ecology framework to predict how individuals perceive and evaluate risks. The perceptions of health and safety hazards for females, and how those perceptions relate to resource security and resource acquisition are examined. Poverty and inequality affect the constraints and opportunities available for Hispanic women working in apple packing warehouses in Eastern Washington. Warehouse workers see the health and safety risks inherent in their work and view the hazards from their positions of relative vulnerability with respect to resources. They are active agents who evaluate their situations and work to provide secure resources for themselves and their offspring within the local political and socioeconomic context.

We present a computable general equilibrium model of the interface between the Great Salt Lake (GSL) ecosystem and both the international and regional economy that impacts the ecosystem. International trade is accounted for in the simplest of terms, involving the export of each of the ecosystem's main commodities and importation of a composite good, as well as equilibrium balances in the savings-investment and current accounts. With respect to the ecosystem, the model treats the various representative species as net energy maximizers and bases population dynamics on the period-by-period sizes of surplus net energy. Energy markets – where predators and prey exchange biomass – determine equilibrium energy prices. With respect to the regional economy, we model five production sectors (at the aggregate industry level) – brine cyst harvesters, the mineral-extraction industry, agriculture, recreation, and a composite-good industry – as well as the household sector. By performing dynamic simulations of the joint ecosystem–regional economy model, we isolate the effects of period-by-period stochastic changes in salinity levels and an initial shock to species-population levels on the ecological and economic variables of the model.