Regional Science and Urban Economics最新文献

In our evaluation of the housing expenditure share cap, a macroprudential policy, we discover the importance of modeling space. In a spatial model, the equilibrium features income-based spatial sorting where a household competes with households of their own income type for residential space. As a result, the cap policy causes a larger drop in housing demand, and consequently a larger reduction in equilibrium housing prices, for constrained low-income families than for unconstrained high-income families. Depending on the assumption on households’ preference, this mechanism leads to a smaller increase or even a modest decrease in welfare inequality in a spatial model than in a spaceless model.

We discuss two approaches to estimating the air quality impacts of public transit projects, focusing on Metro projects in the context of developing countries: air quality modeling and reduced-form econometric methods. As we illustrate, pollution reductions due to Metro projects implied by pollutant chemistry, vehicle emissions factors, and modal shifts may differ from econometric estimates of the impact of transit projects on ambient pollution concentrations. We discuss both approaches and illustrate how economics researchers can use estimated emissions reductions associated with a transit project and pollutant chemistry as a check on their estimates of changes in ambient concentrations.

We consider the implications of unifying the distinct literatures on residential sorting and human capital dynamics. We argue that integrating insights from recent work in both areas has important implications for future research at the intersection of environmental and urban economics. To focus attention on these implications, we summarize stylized facts from recent empirical work on residential sorting and on the effects of exposures to environmental factors on human capital. Then we outline a simple overlapping generations model that reproduces these stylized facts and use it to guide our discussion on directions for future research.

Do environmental conditions pose greater health risks to individuals living in urban or rural areas? The answer is theoretically ambiguous: while urban areas have traditionally been associated with heightened exposure to environmental pollutants, the economies of scale and density inherent to urban environments offer unique opportunities for mitigating or adapting to these harmful exposures. To make progress on this question, we focus on the United States and consider how exposures – to air pollution, drinking water pollution, and extreme temperatures – and the response to those exposures differ across urban and rural settings. While prior studies have addressed some aspects of these issues, substantial gaps in knowledge remain, in large part due to historical deficiencies in monitoring and reporting, especially in rural areas. As a step toward closing these gaps, we present new evidence on urban–rural differences in air quality and population sensitivity to air pollution, leveraging recent advances in remote sensing measurement and machine learning. We find that the urban–rural gap in fine particulate matter (PM_2.5) has converged over the last two decades and the remaining gap is small relative to the overall declines. Furthermore, we find that residents of urban counties are, on average, less vulnerable to the mortality effects of PM_2.5 exposure. We also discuss promising areas for future research.

This paper investigates how the local COVID-19 outbreak, acting as a sudden negative shock to mobility and accessibility, led to a significant generational disparity, with younger people benefiting disproportionately from the ability to transition to online consumption. Employing credit card transaction data linked to cardholders’ demographic characteristics, we construct online spending shares by age group to study the generational disparity in online consumption when consumer mobility was constrained. We estimate a difference-in-difference model based on an exogenous regional outbreak of COVID-19 in South Korea. Our results show that when the mobility costs to offline stores unexpectedly increased due to the pandemic, middle-aged and older adults (aged 45 and above) were less likely to shift their spending online than younger adults (aged 20–44). The limited shift to the online consumption of older people resulted in decreases in their total consumption, while that of younger ones changed little, thereby increasing generational consumption inequality. With the rising trend in e-commerce, our findings emphasize the growing importance of generational differences in adapting to new shopping technologies.

Lack of access to affordable transportation has been hypothesized to be a barrier to employment among low-wage workers. We build a structural job search model to investigate how commuting costs influence the employment decisions of low-wage workers in the United States, and whether differences in commuting by race and education can explain observed disparities in employment. We find that commuting itself poses a significant barrier to overall low-wage employment, as the associated costs are high relative to potential wages. However, we find that inter-group differences in commuting costs account for a much smaller fraction of inter-group employment disparities than do differences in other labor market factors such as the wage offer distribution and offer arrival rates.

To what extent do highways increase income in the European Union? To answer the question, this paper uses detailed data on the expansion of highways in Europe between 1990 and 2020 combined with time-invariant data on more than 2.3 million roads and 1400 ferry connections. I construct a new network database of highways, roads and ferries depicting a 31-year evolution of the lowest travel times along 51 000 region-to-region routes. To tackle endogeneity, I use non-local highway improvements as a source of exogenous variation. Reduced-form estimations suggest that, through decreasing transportation costs, highways increase aggregate regional income and economic cohesion. The study determines that transportation infrastructure policies can generate substantial economic benefits and reduce income disparities between poor and rich European regions.

The world has pledged to protect 30 percent of its land and waters by 2030 to halt the rapid deterioration of critical ecosystems. We summarize the state of knowledge about the impacts of protected area policies, with a focus on deforestation and vegetation cover. We discuss critical issues around data and measurement, identify the most commonly-used empirical methods, and summarize empirical evidence across multiple regions of the world. In most cases, protection has had at most a modest impact on forest cover, with stronger effects in areas that face pressure of economic development. We then identify several open areas for research to advance our understanding of the effectiveness of protected area policies: the use of promising recent econometric advancements, shifting focus to direct measures of biodiversity, filling the knowledge gap on the effect of protected area policy in advanced economies, investigating the long-run impacts of protection, and understanding its equilibrium effects.

During a time of rising concern about climate change, the urban public transit sector has not significantly reduced its carbon footprint. Using data from the nation's transit agencies over the years 2002–2019, we document that the energy efficiency gains of US public transit lagged the gains of European public transit and the US private transportation. The carbon footprint of a transportation provider depends on scale, composition, and technique effects. We use this accounting framework to explore several possible explanations for our findings. We contrast the incentive effects that a private entity versus a public transit agency faces in decarbonizing.

An emerging labor economics literature examines the consequences of firms exercising market power in local labor markets. The extent of this market power is likely to vary across local labor markets. In choosing what local labor market to live and work in, workers tradeoff wages, house prices and local amenities. Building on the Rosen/Roback spatial equilibrium model, we investigate how the existence of local monopsony power affects the cross-sectional spatial distribution of house prices across cities. We find that house prices decline with increases in the employment concentration in the local market. For renters, this offsets roughly 70 percent of the estimated monopsony wage effect and shifts part of the costs of monopsony to homeowners. We find evidence that collective bargaining and minimum wages limit the extent of capitalization of monopsony power into house prices.