Environment Cleanup Incentives as Place-Based Redistribution
The Inflation Reduction Act (IRA) unlocked multiple financial incentives for renewable energy projects and redevelopment of brownfields — land that is abandoned or underused due to a risk of pollution or contamination. Given the recency of the policy, the redistributive effects of the funds provided by the IRA for brownfield redevelopment are unclear. Environmental Protection Agency (EPA) grant awards for brownfield cleanup proposals surged from $18 million in 2022 to $117 million in 2024.
The goal of this project is to provide a comprehensive analysis of the nationwide economic impact and redistributive consequences of EPA grants, and how these incentives interact with recent tax credits for renewable energy investment. For instance, do rural areas benefit more than urban areas? Who are the residents who move into newly rehabilitated sites? We will focus on two major components of household wealth, namely, housing wealth and business creation. We will work with data on business establishments, real estate transactions, liens, and rental listings.
I am seeking a team of RAs to work on the creation of a database recording public and private funding sources for local environmental cleanup efforts and clean energy investments. The bulk of the RA work involves web scraping, submitting written data requests to governmental offices, and formatting property addresses across different databases to track new businesses and property development over time.
Requisite Skills and Qualifications
The data acquisition portion of this project involves compiling records from municipal tax authorities and related government websites. This may require a large number of web searches, web scraping (i.e. batch downloading files and text, or converting PDFs to tabular format in Excel), submitting written data requests via email to the relevant public official(s), and cleaning the raw data to ensure consistency across jurisdictions. Therefore, attention to detail and professional writing skills are crucial to the execution of the research.
Prior experience with web scraping is preferred. I am especially interested in candidates who have experience geo-locating data points using tools such as Google Maps API and software packages like tigris in R. However, familiarity with these tools is not a requirement.
Basic proficiency in statistical/econometric software packages such as R/Python/Stata is required for aspects of the project which involve cleaning the source data collected. I welcome applicants with interests in other fields besides economics – including but not limited to – finance, urban studies, computer science, mathematics/statistics, and physics.