What’s Missing in Environmental Self-Monitoring: Evidence from Strategic Shutdowns of Pollution Monitors

Abstract Regulators often rely on regulated entities to self-monitor compliance, creating strategic incentives for endogenous monitoring. This paper builds a framework to detect whether local governments skip air pollution monitoring when they expect air quality to deteriorate. The core of our method tests whether the timing of monitor shutdowns coincides with the counties’ air quality alerts—public advisories based on local governments’ own pollution forecasts. Applying the method to a monitor in Jersey City, New Jersey, suspected of a deliberate shutdown during the 2013 “Bridgegate” traffic jam, we find a 33% reduction of this monitor's sampling rate on pollution-alert days. Building on large-scale inference tools, we then apply the method to test more than 1,300 monitors across the United States, finding fourteen metropolitan areas with clusters of monitors showing similar strategic behavior. We assess geometric imputation and remote-sensing technologies as potential solutions to deter future strategic monitoring.

Authors

Institutions

Publication Details

Journal
The Review of Economics and Statistics
Published
2024-08-26
DOI
https://doi.org/10.1162/rest_a_01477
Citations
4
Primary Topic
Air Quality and Health Impacts
Type
article
Field-Weighted Citation Impact
1.26
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

What’s Missing in Environmental Self-Monitoring: Evidence from Strategic Shutdowns of Pollution Monitors

Yingfei Mu, Edward S. Rubin, Eric Zou
4 citations
The Review of Economics and Statistics
Air Quality and Health Impacts
1.26
article

What’s Missing in Environmental Self-Monitoring: Evidence from Strategic Shutdowns of Pollution Monitors

Yingfei Mu, Edward S. Rubin, Eric Zou
article en
4 citations

Abstract

Abstract Regulators often rely on regulated entities to self-monitor compliance, creating strategic incentives for endogenous monitoring. This paper builds a framework to detect whether local governments skip air pollution monitoring when they expect air quality to deteriorate. The core of our method tests whether the timing of monitor shutdowns coincides with the counties’ air quality alerts—public advisories based on local governments’ own pollution forecasts. Applying the method to a monitor in Jersey City, New Jersey, suspected of a deliberate shutdown during the 2013 “Bridgegate” traffic jam, we find a 33% reduction of this monitor's sampling rate on pollution-alert days. Building on large-scale inference tools, we then apply the method to test more than 1,300 monitors across the United States, finding fourteen metropolitan areas with clusters of monitors showing similar strategic behavior. We assess geometric imputation and remote-sensing technologies as potential solutions to deter future strategic monitoring.

The Review of Economics and Statistics
Johns Hopkins University (US), University of Oregon (US), University of Michigan (US)
Openalex Percentile: Top 21%
Air Quality and Health Impacts
1.26
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.