Conference Agenda

We study the welfare effects of public transport infrastructure investments in the Paris region, highlighting the role of local air quality improvements typically omitted by standard quantitative urban models (QUMs). We first provide reduced-form evidence that tramway expansions improve local air quality. We then develop a QUM with endogenous worker and firm location choice, transport mode choice, and local air pollution affecting amenities and productivity. Applying the model to the Grand Paris Express metro project, we find welfare gains of around 1.5%. We show that omitting the air quality channel leads to a severe underestimation of welfare gains and spatial skill sorting, given the substantial heterogeneity in pollution exposure and its valuation across skill groups.

Place-based environmental regulations target pollution-intensive sectors in polluted areas. These regulations can improve local quality of life by reducing air pollution, while simultaneously reducing labor demand. I develop a framework to study the heterogeneous effects on worker welfare, considering changes in pollution exposure, sectoral and spatial labor distribution, and unemployment. I focus on the U.S. Environmental Protection Agency’s regulation of ozone and fine particulate air pollution during the 2000’s. First, I develop a triple-difference estimator to measure the employment effects on college-educated and non-college-educated workers. I find that, on average, regulation decreased employment by 7.6% among non-college-educated workers and by 3.6% among college-educated workers. However, these average treatment effects vary substantially depending on the intensity and type of regulation. I use this causal evidence to develop empirical moments that serve to identify key parameters of a new general equilibrium search and matching model with endogenous worker location choice and pollution exposure. I use the model to evaluate the welfare effects of regulation in North Carolina. I find the effects differ by worker skill level and geographic location. Low-skill workers in regulated areas experience notable welfare losses. I show these losses can be mitigated by improving labor mobility across

sectors and areas.

Why do individuals raised in environmentally disadvantaged areas often remain in similar conditions as adults? We propose a behavioral mechanism of environmental anchoring, where past lived experiences serve as a reference point for future residential choices. We develop a discrete choice model of residential sorting that incorporates reference-dependent preferences, positing that individuals discount the utility of amenities, such as air quality or climate, when they diverge substantially from their formative baseline. This framework offers a micro-foundation for the intergenerational persistence of environmental exposure: individuals from low-amenity origins may undervalue improvements in environmental quality, leading them to self-sort into similarly disadvantaged locations. We test this theory

empirically using an augmented gravity model of U.S. county-to-county migration flows from 2013 to 2017. By constructing a measure of environmental distance between origin and destination, we isolate the role of environmental anchoring in migration decisions. We find robust evidence that migration flows are significantly larger between counties with similar

environmental and socioeconomic pro les, even after controlling for physical distance and economic opportunities. These findings suggest that spatial inequality is reinforced not only by structural constraints but by internalized preferences, implying that policies aiming to promote intergenerational mobility must account for the behavioral stickiness of past

environmental exposure.

Industrial structure optimization (ISO) is often regarded as having complex potential to enhance the collaborative performance of carbon mitigation and air pollution control (CPCA). Based on panel data from 282 Chinese cities spanning from 2006 to 2020, this study evaluates the CPCA of Chinese cities and investigates the impact of ISO on it. Applying the STIRPAT model, panel regression, and spatial Durbin model (SDM), this research analyzes the effects of industrial structure upgrading (UP), industrial structure rationalization (RA), and industrial structure ecologization (EC) on CPCA, and conducts heterogeneity analysis and mechanism analysis based on the spatial spillover effects of ISO. The results reveal that the spatial distribution of CPCA in Chinese cities exhibits a gradient pattern with higher values in the southeast and lower values in the northwest, and presents positive spatial correlation over time. There is a complex nonlinear relationship between ISO and CPCA, where UP and RA exhibit a U-shaped relationship with CPCA, while EC demonstrates a positive linear effect on CPCA. Heterogeneity analysis unveils the differential impacts of ISO on CPCA across various regions and city sizes, and mechanism analysis further distinguishes its influences on carbon emission performance and air pollution control performance respectively. This study enriches the traditional core–periphery framework and ecological unequal exchange theory by incorporating the environmental and economic consequences of industrial restructuring, and provides both theoretical insights and empirical evidence to inform strategic industrial policies and support sustainable development not only in China but also in other emerging and transitional economies.