# Estimating the causal effect of redlining on present-day air pollution

## TL;DR

This study investigates how historical redlining policies caused long-term air pollution disparities in present-day neighborhoods.

## Contribution

The paper introduces a novel spatial and non-spatial latent factor framework to estimate the causal effects of redlining on air pollution.

## Key findings

- Historically redlined neighborhoods are exposed to notably higher NO₂ concentrations.
- Disparities in PM₂.₅ between redlined and non-redlined neighborhoods are less pronounced.
- Los Angeles and Atlanta show the most significant pollution effects for both NO₂ and PM₂.₅.

## Abstract

Recent studies have shown associations between redlining policies (1935–1974) and present-day fine particulate matter (PM\documentclass[12pt]{minimal}
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$_2$\end{document}) air pollution concentrations. In this paper, we move beyond associations and investigate the causal effects of redlining using spatial causal inference. Redlining policies were enacted in the 1930s, so there is very limited documentation of pre-treatment covariates. Consequently, traditional methods failed to sufficiently account for unmeasured confounders, potentially biasing causal interpretations. By integrating historical redlining data with 2010 PM\documentclass[12pt]{minimal}
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