Kevin Credit

Social services in the United States are delivered jointly by government and nonprofits. Prior research examines either the location or the resources of nonprofits; it rarely examines how these factors jointly influence social service availability or access. We leverage a unique dataset linking nonprofit headquarters and service site locations, along with organizational and neighborhood data. We find most nonprofits demonstrate neighborhood homophily, locating headquarters and service sites in demographically similar neighborhoods. However, we also find a distinctive set of nonprofits headquartered in affluent neighborhoods providing services in disadvantaged communities. Organizations serving neighborhoods with predominantly Black and Asian/immigrant populations are exposed to heightened fiscal vulnerability. Our study demonstrates how inequalities in access to nonprofit social services are shaped by the combination of where nonprofits provide services, the manner in which nonprofits spatially organize services across various sites, and the overall capacity of these organizations.

Employing a cutting-edge quasi-experimental event study estimator from de Chaisemartin and D’Haultfœuille, the results of this paper indicate that light rail construction has a significant impact on reducing regional CO ₂ emissions per capita, and that these effects change dynamically for at least 20 years after construction. The paper categorizes these long-run effects into four phases of light rail operational effectiveness: an early “establishment” phase where observed effects on per capita emissions are relatively small, an “early growth” phase of increasing effectiveness, a “stagnation” phase where the benefits plateau, and a “maturity” phase of renewed effectiveness.

This paper describes a straightforward method for calculating an open-source Walkable Accessibility Score (WAS) that measures walkability at the block group scale based on walking distance to business establishments, schools, and parks. Exploratory analysis of the WAS reveals high concentrations of walkable accessibility in the centres of the densest and/or largest cities. Our optimised specification ( decay = 0.008, upper = 800, k = 30) performs very well, achieving a Spearman rank correlation of 0.912 with proprietary Walk Score® values (for 2011). We provided pre-calculated data for each year from 1997 to 2019 and Python code for calculating the WAS at the project’s GitHub repository . The method is particularly useful in that it uses simple Euclidean distance calculations, and thus can be run at scale on a laptop or personal computer.

Employing a cutting-edge quasi-experimental event study estimator from de Chaisemartin and D’Haultfœuille (2024), the results of this paper indicate that light rail construction has a significant impact on reducing regional CO2 emissions per capita, and that these effects change dynamically for at least 20 years after construction. The paper categorizes these long-run effects into four phases of light rail operational effectiveness: an early “establishment” phase where observed effects on per capita emissions are relatively small, an “early growth” phase of increasing effectiveness, a “stagnation” phase where the benefits plateau, and a “maturity” phase of renewed effectiveness.

Using a multilevel modelling approach to analyse a novel dataset of academic publications at all business schools in 11 European countries, this paper finds that the influence of organisational- and country-level contextual factors on researchers varies considerably based on the type of institution and the development level of the country they are located in. At the organisational-level, we find that greater spatial connectivity–operationalised through proximity to nearby business schools, rail stations, and airports–is positively related to scientific research volume and public dissemination (news mentions). While this result is significant only for high-income countries (above EU-average 2018 GDP per capita), this is likely because the low-income countries (below EU-average 2018 GDP per capita) examined here lack a ‘critical mass’ of well-connected universities to generate observable agglomeration effects. At the country-level, the results indicate that in high-income countries, less prestigious schools benefit from higher rates of recent international immigration from any foreign country, providing a direct policy pathway for increasing research output for universities that aren’t already well-known enough to attract the most talented researchers. In low-income countries, recent immigration rates are even stronger predictors of research performance across all levels of institutional prestige; more open immigration policies would likely benefit research performance in these countries to an even greater extent. Finally, the paper’s results show that, in low-income countries, a composite measure of a country’s quality of life (including self-rated life satisfaction, health, working hours, and housing overcrowding) is positively related to research outcomes through its interaction with school prestige. This suggests that the lower a country’s quality of life, the more researchers are incentivised to produce higher levels of research output. While this may in part reflect the greater disparities inherent in these countries’ economic systems, it is noteworthy–and perhaps concerning–that we have observed a negative correlation between country-level quality of life and research performance in low-income countries, which is particularly felt by researchers at less prestigious institutions.