Firm Relocation as Environmental Policy: Impacts on Agglomeration and the Environment

Project: Research project

Project Details

Description

As countries industrialize, trade-offs between promoting economic growth and negative environment effects such as pollution and emissions become more binding. Because environmental policies impact firm decisions, they provide a lens to test theories of firm interactions that contribute to our understanding of firm behavior. This research project will study the effects a policy which relocated firms located in densely urban areas to industrial locations outside the city. The goal was to move polluting firms out of high population density areas so that they would affect fewer people. Because random drawings were held to assign plots at the new location to firms as industrial plots became available, the randomization makes the firms that relocated earlier comparable to those that relocated later. This makes it possible to provide an improved understanding of how the presence of industrial activity at a variety of scales affects air quality and emissions in urban areas, workers' choices of where to live. Additionally, the proposal develops a new method of inferring air pollution levels from historical high-resolution satellite images which can be helpful whenever direct measurements are not available. This innovative design allows the researchers allows researchers to assess the impact of industrial policy on the environment. The results of this research will provide inputs into environmental policy and thus establish the US as the global leader in environment research and policy.

Understanding aggregate and distributional consequences of environmental policies is important to inform policies that balance the growth-pollution trade-off. We use the randomized removal of firms from city centers at different times to assess neighborhood-level policy impacts on a range of outcomes such as agglomeration, entry and exit, environmental quality, and land values. A key input to the analysis is fine resolution air quality measures spanning a fifteen year period. The proposed research will use deep learning methods applied to satellite imagery to create pollution measures at a fine spatial and temporal resolution. Furthermore, conditional on a firm's assigned plot being in one of four size categories, the specific plot that a firm allotted was also random. This generates random variation in firms' neighbors, as well as in location characteristics such as proximity to infrastructure like roads. The project will estimate how different aspects of firm location impact firm outcomes and how these effects are heterogeneous depending on neighbors' characteristics. In studies of agglomeration and density, truly experimental variation is almost entirely absent so that most identification is either quasi-experimental or model-based. This study is the first to conduct a joint experimental analysis of how firm density impacts environmental quality, firm outcomes, and agglomeration. The results of this research will provide inputs into environmental policy and thus establish the US as the global leader in environment research and policy.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

StatusActive
Effective start/end date6/1/215/31/22

Funding

  • National Science Foundation: $249,998.00

Fingerprint

Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.