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This article quantifies the impact of civil wars on economic growth at home and in nearby countries. Three alternative measures of nearness-contiguity, length of contiguous borders, and distance of closest approach-are used to capture the spatial dispersion of civil war consequences. We present short-run panel estimates (at five-year intervals) and long-run (1961-95) panel estimates for the world. Generally, the distance measures, novel to this study, and not contiguity provides the most accurate measure of the diffusion of the negative economic consequences of civil wars on other countries. Unlike earlier studies, we also investigate the temporal influence of civil wars on growth at home and in nearby countries. Both the duration and the timing of civil wars have an economic impact.

A neoclassical growth model is used to empirically test for the influences of a civil war on steady-state income per capita both at home and in neighboring countries. This model provides the basis for measuring long-run and short-run effects of civil wars on income per capita growth in the host country and its neighbors. Evidence of significant collateral damage on economic growth in neighboring nations is uncovered. In addition, this damage is attributed to country-specific influences rather than to migration, human capital, or investment factors. As the intensity of the measure used to proxy the conflict increases, there are enhanced neighbor spillovers. Moreover, collateral damage from civil wars to growth is more pronounced in the short run.

There is a growing body of public health research documenting how characteristics of neighborhoods are associated with differences in the health status of residents. However, little is known about how the spatial resolution of neighborhood observational data or community audits affects the identification of neighborhood differences in health. We developed a systematic neighborhood observation instrument for collecting data at very high spatial resolution (we observe each parcel independently) and used it to collect data in a low-income minority neighborhood in Dallas, TX. In addition, we collected data on the health status of individuals residing in this neighborhood. We then assessed the inter-rater reliability of the instrument and compared the costs and benefits of using data at this high spatial resolution. Our instrument provides a reliable and cost-effect method for collecting neighborhood observational data at high spatial resolution, which then allows researchers to explore the impact of varying geographic aggregations. Furthermore, these data facilitate a demonstration of the predictive accuracy of self-reported health status. We find that ordered logit models of health status using observational data at different spatial resolution produce different results. This implies a need to analyze the variation in correlative relationships at different geographic resolutions when there is no solid theoretical rational for choosing a particular resolution. We argue that neighborhood data at high spatial resolution greatly facilitates the evaluation of alternative geographic specifications in studies of neighborhood and health.

Neighborhood quality is an important attribute of housing yet its value is rarely known to researchers. We argue that changes in nearby foreclosures reveal changes in neighborhood quality. Thus estimates of the hedonic price of nearby foreclosures provide a glimpse of values that people hold for local neighborhood quality. The empirical models include controls for both spatial dependence in housing prices and in the errors. The estimates indicate that nearby foreclosures produce externalities that are capitalized into home prices—an additional foreclosure within 250 feet of a sale negatively impacts selling price by approximately $1,666, ceteris paribus .

This paper develops a correlated probit model to describe dichotomous choices that may contain a public-goods component or some other forms of interdependency. The key contribution of the paper is to formulate tests for interdependent behavior among agents. In particular, we examine the decisions by nations whether or not to ratify the Montreal Protocol on Substances that Deplete the Ozone Layer. Specifically, we reject free riding as a motive for not ratifying the Protocol, and we find little evidence that individual nations were influenced by the behavior of their largest trading partners. Hence, the data suggest that, with respect to the Montreal Protocol, most nations acted without regard for the actions of other nations.

BACKGROUND:Researchers measuring relationships between neighborhoods and health have begun using property appraisal data as a source of information about neighborhoods. Economists have developed a rich tool kit to understand how neighborhood characteristics are quantified in appraisal values. This tool kit principally relies on hedonic (implicit) price models and has much to offer regarding the interpretation and operationalization of property appraisal data-derived neighborhood measures, which goes beyond the use of appraisal data as a measure of neighborhood socioeconomic status. METHODS:We develop a theoretically informed hedonic-based neighborhood measure using residuals of a hedonic price regression applied to appraisal data in a single metropolitan area. We describe its characteristics, reliability in different types of neighborhoods, and correlation with other neighborhood measures (i.e., raw neighborhood appraisal values, census block group poverty, and observed property characteristics). We examine the association between all neighborhood measures and body mass index. RESULTS:The hedonic-based neighborhood measure was correlated in the expected direction with block group poverty rate and observed property characteristics. The neighborhood measure and average raw neighborhood appraisal value, but not census block group poverty, were associated with individual body mass index. CONCLUSION:We draw theoretically consistent methodology from the economics literature on hedonic price models to demonstrate how to leverage the implicit valuation of neighborhoods contained in publicly available appraisal data. Consistent measurement and application of the hedonic-based neighborhood measures in epidemiology will improve understanding of the relationships between neighborhoods and health. Researchers should proceed with a careful use of appraisal values utilizing theoretically informed methods such as this one.

Down payment or closing cost assistance is an effective program in addressing the wealth constraints of low- and moderate-income homebuyers. However, the spillover effect of such programs on the neighborhood is unknown. This paper estimates the impact of the City of Dallas Mortgage Assistance Program (MAP) on nearby home values using a hedonic model of home sales from 1990 to 2006. We define neighborhoods of 1,000 feet around each sale and estimate the average differences in sales prices between neighborhoods with various numbers of MAP properties before and after their appearance. We find that MAP properties tend to locate in neighborhoods with lower property values; however, unless a concentration of MAP properties forms, the infusion of MAP properties has little detrimental impact on neighboring property values. Moreover, low concentration of MAP properties has a modest positive impact on surrounding property values.

Residential housing sales data from the San Francisco Bay area are merged with earthquake hazard measures, geologic measures, neighborhood quality measures, and community characteristics in order to estimate the hedonic price of earthquake risk before and after the October 17, 1989, Loma Prieta earthquake. The estimates suggest that the hedonic price fell after the earthquake, indicating that consumers had initially overestimated the earthquake hazard. This suggests that information about earthquake risks is imperfect and that some efficiency may be realized by devoting more resources to earthquake risk communication.

This article argues that the World Resources Institute (WRI) data are appropriate for our game-theoretic-based analysis of countries' CFC emission cutbacks prior to the ratification of the Protocol. Given the underlying game from which our reduced-form equations follow, the policymakers must be viewed as responding to contemporary information, which was the WRI dataset. The article also addresses the issue of an alleged perfect correlation being induced between CFC emission cutbacks and GNP due to the imputation process used by WRI. The article also raises concerns about inventory inclusion in the United Nations Environmental Programme data that could distort cutbacks for major producer countries that were likely to stockpile CFCs before production lines were shifted over to CFC substitutes.

This article investigates NATO burden sharing in the 1990s in light of strategic, technological, political and membership changes. Both an ability-to-pay and a benefits-received analysis of burden sharing are conducted. During 1990–99, there is no evidence of disproportionate burden sharing, where the large allies shoulder the burdens of the small. Nevertheless, the theoretical model predicts that this disproportionality will plague NATO in the near future. Thus far, there is still a significant concordance between benefits received and defence burdens carried. When alternative expansion scenarios are studied, the extent of disproportionality of burden sharing increases as NATO grows in size. A broader security burden-sharing measure is devised and tested; based on this broader measure, there is still no disproportionality evident in the recent past.