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County-level data combining U.S. EPA Environmental Quality Index (EQI) summary scores with the count of EPA enforcement penalties levied against regulated facilities in each county over a multi-year window. Used in glmOJ's vignette to demonstrate Poisson and negative-binomial count regression with continuous EQI exposure and categorical region covariates.

Usage

Greenberg26.dat

Format

A data frame with 3,139 rows and 27 columns:

countyname

County name (character).

statename

State name (character).

fips_1

County FIPS code (integer).

sociod_eqi_2jan2018_vc

Sociodemographic EQI summary score (z-scored).

air_eqi_2jan2018_vc

Air-quality EQI summary score (z-scored).

land_eqi_2jan2018_vc

Land EQI summary score (z-scored).

water_eqi_2jan2018_vc

Water EQI summary score (z-scored).

eqi_2jan2018_vc

Overall EPA Environmental Quality Index (z-scored).

pctnonwhite10

Percent non-white population (2010 census).

gdp2017b

County GDP, 2017 (billions of USD).

metro

Factor: 0 non-metropolitan, 1 metropolitan.

fac_penalty_count

Integer count of facility-level EPA penalties (the response used in the vignette).

CIDDist

Distance to the nearest community-information district.

FinalEC

Final environmental-compliance indicator (binary).

estab

Number of regulated establishments in the county.

EPAregion

Factor with 10 levels (EPA administrative regions 1-10).

cases_2011

Year-2011 case count.

cases_2012

Year-2012 case count.

cases_2013

Year-2013 case count.

cases_2014

Year-2014 case count.

cases_2015

Year-2015 case count.

cases_2016

Year-2016 case count.

cases_2017

Year-2017 case count.

cases_2018

Year-2018 case count.

cases_2019

Year-2019 case count.

cases_2020

Year-2020 case count.

proportionObama

Indicator / proportion of Obama vote at the county level (binary in this extract).

Source

Compiled from the U.S. EPA Environmental Quality Index and the ECHO enforcement database; see Greenberg (2026).