Long-term Effect of Redlining Policy on Air Pollution Exposure

Shu Yang Co-Author
North Carolina State University, Department of Statistics
 
Brian Reich Co-Author
North Carolina State University
 
Xiaodan Zhou First Author
 
Xiaodan Zhou Presenting Author
 
Sunday, Aug 4: 4:20 PM - 4:35 PM
3048 
Contributed Papers 
Oregon Convention Center 
This study assesses the potential long-term environmental effects of redlining policies (1935-1974) on present-day PM2.5 air pollution levels. Enacted in the 1930s, there are only a few low-quality pre-treatment covariates recorded in survey. Consequently, traditional methods fails to sufficiently account for unmeasured confounders, potentially skewing causal interpretations. Moreover, the time lapse of 75 years between the policy action and the pollution measurement further obscures causal links. By integrating historical redlining data with 2010 PM2.5 levels, our study aims to discern whether a causal link exists. Our study addresses challenges with a novel spatial latent framework, using the income level and percentage of Black population in survey as proxies to reconstruct pre-treatment socio-economic factors. We establish identification of a causal effect under broad assumptions, and use Bayesian MCMC to quantify uncertainty. Our method promises to enhance the validity of causal claims by rigorously adjusting for confounders. Anticipated findings will illuminate the effects of redlining policy on contemporary air quality.

Keywords

Bayesian causal model

Spatial latent factor

proxy variable

Redlining policy

air pollution exposure 

Main Sponsor

Section on Statistics in Epidemiology