Grandfathering

26 February 2025

• Overview
• Abstract
• Repository Structure
• Data Availability
• Computational requirements
• Code
• Instructions
• Citation
• References

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Overview

This GitHub repository contains the replication package for:

Bialek-Gregory, Sylwia, Jack Gregory, Bridget Pals, and Richard Revesz. Forthcoming. “Still your grandfather’s boiler: Estimating the effects of the Clean Air Act’s grandfathering provisions.” Journal of the Association of Environmental and Resource Economists.

It is a ‘first principles’ alternative to the official replication package available here. Both packages are fully self-contained; however, this repository endeavors wherever possible to provide code in lieu of data. For example, a major departure from the official replication package is the inclusion of the SQL code necessary to setup a MySQL CEMS¹ database.

The code in this replication package reproduces data collection, cleaning, and analysis for the paper using R, SQL, and Stata. The scripts in the build/05_analysis subfolder produce all tables and figures in the paper and appendices. The replicator should expect the code to run for about a week on a personal computer running Windows 10 Home on an Intel four-core CPU at 2.60GHz with 20GB of RAM.

The remainder of this readme file is organized as follows. First, we reproduce the paper’s abstract and provide the repository structure. Next, we discuss data availability, through the main data sources and all data files, and we list all computational requirements. We then provide a description of the code and instructions for how to reproduce our analysis. We suggest sample citations for the paper and repository. Finally, we list our references.

Abstract

While vintage differentiation is a highly prominent feature of various regulations, it can induce significant biases. We study these biases in the context of New Source Review—a program within the U.S. Clean Air Act imposing costly sulfur dioxide (SO$_2$) abatement requirements on new boilers but not existing ones. Leveraging a novel dataset covering state-level SO$_2$ regulations, we show that the regulatory differentiation decreased the probability of a grandfathered boiler retiring in a given year by 2.4 percentage points (i.e., 60 percent smaller) and increased their operations by around 1,150 hours annually. Conservative back-of-the-envelope calculations suggest annual societal damages of up to $2.5 billion associated with additional SO$_2$ emissions caused by delayed retirements, higher utilization, and higher emission rates in the years considered. The results imply that long after their passage and in presence of many subsequent, more stringent environmental policies, grandfathering provisions continued to have strong perverse impacts.

Repository Structure

The following table lists and describes the structure of the repository.

Folder	Description	Included
build	Contains all collection, cleaning, preprocessing, and analysis code.	Yes
build/01_eia	Contains all code related to EIA data collection and cleaning. Includes an automation script 01_eia/00_master.R, though the constituent scripts can be run independently and in any order.	Yes
build/02_boilers	Contains all code related to EIA boiler cleaning, with an automation script 02_boilers/00_master.R where order is important.	Yes
build/03_cems	Contains all code related to EPA CEMS data collection, ingestion, and cleaning. Note that order of the scripts is important.	Yes
build/04_preprocessing	Contains all code related to data preprocessing, with an automation script 04_preprocessing/00_master.R though the constituent scripts can be run independently and in any order.	Yes
build/05_analysis	Contains all code related to project analysis and produce all tables and figures within the paper. Includes an automation script 05_analysis/00_master.R where order is important.	Yes
data	Contains both raw and cleaned data. The latter is located in the root directory, while the former is stored by source among its subfolders.	Yes
lit	Contains a database and a companion script for generating an associated BibTex file.	Yes
out	Contains all project outputs arranged in subfolders by generation date. Folder is generated through the build code.	No
src	Contains all source code and functions.	Yes

Data Availability

All data used in the paper is from secondary sources. That is, it is either collected from publicly available sources or assembled manually.

See LICENSE.txt for details.

The following datasets are licensed under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0):

• State emission regulations $\longrightarrow$ so2_regulations_by_state_1976_to_2019.xlsx and data/regs/indiana.xlsx
• New Source Review grandfathering status $\longrightarrow$ data/regs/gf_status_born_around_1978.xlsx
• County attainment status 1978–1990 $\longrightarrow$ data/epa/phistory_1978_1990.csv

You may use, share, and adapt this data for non-commercial purposes with appropriate credit.

All other data are sourced from the U.S. federal government under the public domain. As such, these data are licensed under the Creative Commons Zero (CC0) License. You may use, share, and adapt this data without restriction. See LICENSE.md for further details.

Below we provide tables summarizing the data sources for the analysis and the data files within the repository.

Main data sources

The table below summarizes main data references necessary for the analysis.

Source	Dataset	Via	Description	Citation
Bureau of Transportation Statistics (BTS)	National Transportation Atlas Database (NTAD)	Download	The NTAD is a set of nationwide geographic databases of transportation facilities, transportation networks, and associated infrastructure. These datasets include spatial information for transportation modal networks and intermodal terminals, as well as the related attribute information for these features. The current project utilizes rail and marine geospatial datasets.	US DOT (2022)
Census Bureau (CB)	Geospatial data	Download	CB geospatial data including state shapefiles and geocodes.	N/A
Energy Information Administration (EIA)	EIA-423	Code	Historical survey Form EIA-423 collected monthly fuel receipts for plants with a fossil-fueled nameplate generating capacity of 50+ MW. It was discontinued in 2011; beginning in 2008, its information was transferred to Form EIA 923.	US EIA (2023)
	EIA-767	Code	Historical survey Form EIA-767 collected data from steam-electric plants with a generator nameplate rating of 10+ MW. It contains data on plant operations and equipment design, including boilers, generators, flue gas desulfurizations, flue gas particulate collectors, and stacks. EIA Form 767 was discontinued in 2005; beginning in 2007, its information was transferred to Forms EIA 860 and EIA 923.	US EIA (2005)
	EIA-860	Code	The survey Form EIA-860 collects generator-level data on existing and planned electric power plants with 1+ MW of combined nameplate capacity. The EIA-860 superseded the EIA-767.	US EIA (2019a)
	EIA-861	Code	The survey Form EIA-861 collects data from distribution utilities and power marketers of electricity.	US EIA (2021a)
	EIA-923	Code	The survey Form EIA-923 collects detailed electric power data on electricity generation, fuel consumption, and receipts at the power plant and prime mover level. The EIA-923 superseded the EIA-423, EIA-759, EIA-767, EIA-867, EIA-906, and EIA-920.	US EIA (2019b)
	Geospatial data	Download	EIA geospatial data including state and county shapefiles.	US EIA (2021b)
	State data	Code	EIA state-level summary data, primarily with respect to Form EIA-860.	US EIA (2019c)
Environmental Protection Agency (EPA)	Continuous Emission Monitoring System (CEMS)	Code	EPA CEMS data is available from the Clean Air Markets Program Data (CAMPD) website. It contains hourly resolution of plant utilization and emissions beginning in 1995 and containing nost coal plants.	US EPA (2021b)
Environmental Protection Agency (EPA)	EPA Green Book	Download	EPA nonattainment areas from 1992 to the present.	US EPA (2021a)
Environmental Protection Agency (EPA)	EPA-EIA Crosswalk	Code	A data crosswalk to integrate US power sector emission and operation data from the EPA and EIA.	Huetteman et al. (2021)
	Facility Attributes	Download	The EPA collects power plant data through its various programs. It synthesizes this information through an annual “facility attributes” dataset.	US EPA (2021b)

Data files

This repository represents a ‘first principles’ replication package, which means that it focuses on supplying all necessary code in lieu of data. Essentially, we aim to provide all collection and cleaning code for publicly available data instead of a preprocessed dataset ready for analysis.

If you would prefer a replication package which focuses on data provision, much of the data listed below is available through the official replication package.

There are two datasets of particular note which cover our universe of state regulations.

• <so2_regulations_by_state_1976_to_2019.xlxs> $\longrightarrow$ All state regulations except Indiana site-specific ones.
• <indiana.xlsx> $\longrightarrow$ Indiana site-specific regulations based on the boilers in our sample and as such is non-exhaustive.

These were manually compiled by examining EPA historical documents, state administrative codes, entries in the Federal Register, and other resources. Further details are included in the paper. Each file contains a data dictionary, while they also contain references to the relevant data sources used to identify each regulation. Moreover, the official replication package contains a zip folder with references that are more challenging to locate.

Additional documentation—including data dictionaries—are typically included directly in the code.

File	Location	Code	Source	Description	Included
1989_1998_Nonutility_Power_Producer.zip	data/eia	NA	EIA	data from EIA-867 available for years 1989–1998 on independent power producers	Yes
ARP_power_plants.csv	data/regs	NA	Federal Register	Plants participating in Phase I of the Acid Rain Program (ARP) based on Table 1 in Subpart B 58 FR 3687.	Yes
ARP_prices.xlsx	data/regs	NA	EPA	Data on annual ARP auction permit prices.	Yes
EIA electricity demand data.zip	data/eia	NA	EIA	State-by-year panel of electricity demand.	Yes
Facility_Attributes.zip	data/epa	NA	EPA	EPA power plant data from 2021 synthesized through its various programs.	Yes
Marine_Highways.zip	data/bts	NA	BTS	The Marine Highways dataset was updated on October 31, 2023 and is part of the NTAD. The dataset contains the locations of all 28 maritime routes that have been designated as Marine Highways by the US Department of Transportation.	Yes
North_American_Rail_Network_Lines.zip	data/bts	NA	BTS	The North American Rail Network (NARN) Rail Lines dataset was updated on October 12, 2023 and is part of the NTAD. Among other variables, the dataset provides rail ownership, trackage rights, and type.	Yes
USA_Counties_(Generalized).zip	data/eia/shp	NA	EIA	EIA geospatial data for the 2020 US Census County boundaries including 2020 US Census codes.	Yes
USA_States_(Generalized).zip	data/eia/shp	NA	EIA	EIA geospatial data for the 2020 US Census State boundaries including 2020 US Census codes.	Yes
all-geocodes-v2020.xlsx	data/cb	NA	CB	The CB provides a list of all geocodes from the 2020 US Census.	Yes
all_fuel_1970_2018.csv	data	build/02_boilers/05_fuel_and_fuel_comp_1970_2018.R	Internal	Plant-by-year panel of EIA-759 and EIA-923 coal data between 1970 and 2018.	No
all_years_all_plants_and_features.csv	data	build/02_boilers/08_feature_generation.R	Internal	Draft synthesized boiler data.	No
aqcrs_to_cty_xwalk.csv	data/xwalk	NA	Internal	Crosswalk from Air Quality Control Regions (ACQRs) to counties.	Yes
boilers_1985_2005.csv	data	build/02_boilers/02_eia767_1985-2005.R	Internal	Boiler-by-year panel of EIA-767 data between 1985 and 2005.	No
boilers_1985_2018.csv	data	build/02_boilers/04_merge_eia767_and_eia860.R	Internal	Boiler-by-year panel of EIA-767 and EIA-860 data between 1985 and 2018.	No
boilers_2007_2018.csv	data	build/02_boilers/03_eia860_2007-2018.R	Internal	Boiler-by-year panel of EIA-860 data between 2007 and 2018.	No
boilers_fuel_comp_1985_2018.csv	data	build/02_boilers/05_fuel_and_fuel_comp_1970_2018.R	Internal	Boiler-by-year panel of EIA-767 and EIA-923 coal data between 1985 and 2018.	No
cb_2018_us_county_500k.zip	data/cb	NA	CB	CB geospatial data of US counties.	Yes
cems_YYYY.rds	data/epa	build/03_cems/03_cems_query.R	Internal	Yearly CEMS data restricted to the grandfathering sample consisting of gross load, SO$_2$ emissions, etc. by plant and unit.	No
cems_hrHH.rds	data/epa	build/03_cems/03_cems_query.R	Internal	Hourly CEMS data restricted to the grandfathering sample consisting of gross load, SO$_2$ emissions, etc. by plant and unit.	No
cems_yr.dta	data	build/03_cems/03_cems_query.R	Internal	Yearly CEMS data restricted to the grandfathering sample consisting of gross load, SO$_2$ emissions, etc. by plant and unit.	No
coal_char_data_by_plant_year.csv	data	build/02_boilers/06_coal_mine_data_eia923.R	Internal	Plant-by-year panel of EIA-423 and EIA-923 coal data.	No
ctrpoints_counties.csv	data	build/02_boilers/01_county_level_data.R	Internal	Cross-section of county centerpoints.	No
eia860_file_structure.xlsx	data/xwalk	NA	Internal	Description of the Form EIA-860 file structure, which changes in minor ways from year to year, to make the files easier to import.	Yes
eia923_fuel_dictionary.csv	data/xwalk	NA	Internal	Fuel definitions and codes across EIA-923 and its predecessors sourced from the included dataset notes.	Yes
eia_capacity.csv	data	build/01_eia/EIA_capacity.Rmd	Internal	State-by-fuel-by-year panel of electricity capacities.	No
eia_fuel.xlsx	data	build/01_eia/EIA_423923.Rmd	Internal	Plant- and state-by-month panels of fuel prices.	No
eia_netgen.csv	data	build/01_eia/EIA_906923.Rmd	Internal	Plant-by-month panel of net generation.	No
eia_netgen_unit.csv	data	build/01_eia/EIA_906923.Rmd	Internal	Boiler-by-month panel of net generation.	No
eia_plant.csv	data	NA	Internal	Plant-by-year panel of Form EIA-923 reporting frequency data from sheet “Page 6 Plant Frame”.	Yes
eia_sales.csv	data	build/01_eia/EIA_861.Rmd	Internal	Utility-by-year panel of electricity sales.	No
eia_sulfur.csv	data	build/01_eia/EIA_423923.Rmd	Internal	Mine, county, and state cross-section of sulfur contents.	No
epa.cems	MySQL	build/03_cems/02_cems_ingestion.R	EPA	Table populated with cleaned EPA CEMS data.	No
epa.filelog	MySQL	build/03_cems/02_cems_ingestion.R	Internal	Metadata table populated with EPA CEMS raw data files which have been ingested successfully into the MySQL database.	No
epa.xwalk	MySQL	build/03_cems/02_cems_ingestion.R	EPA	Table populated with EPA and EIA power plant crosswalk data synthesized from the EPA-EIA crosswalk and the CEMS database.	No
epa_eia_crosswalk.csv	data/epa	build/03_cems/02_cems_ingestion.R	EPA	Crosswalk mapping EPA and EIA power sector emission and operation data, authored by the EPA’s Clean Air Markets Division (CAMD).	Yes
existcapacity_annual.xlsx	data/eia	build/01_eia/EIA_capacity.Rmd	EIA	“Existing Nameplate and Net Summer Capacity by Energy Source, Producer Type and State” table based on annual data reported in form EIA-860.	No
f423_YYYY.zip	data/eia/f923	build/01_eia/EIA_423923.Rmd	EIA	Form EIA-423 collected monthly fuel receipts for plants with a fossil-fueled nameplate generating capacity of 50+ MW, where the data are available from 1972 to 2011.	No
f759_YYYY.zip	data/eia/f923	build/01_eia/EIA_759.Rmd	EIA	Historical form EIA-759 “Monthly power plant report”, where the data are available from 1970 to 2000.	No
f767_YYYY.zip	data/eia/f767	build/01_eia/EIA_767.Rmd	EIA	Historical form EIA-767 “Steam-electric plant operation and design report”, where the data are available from 1985 to 2005.	No
f860_YYYY.zip	data/eia/f860	build/01_eia/EIA_860.Rmd	EIA	Form EIA-860 “Electric generators”, where the data are available from 1990 to the present.	No
f861_YYYY.zip	data/eia/f861	build/01_eia/EIA_861.Rmd	EIA	Form EIA-861 a census of all electric utilities, where the data are available from 1990 to the present.	No
f906920_YYYY.zip	data/eia/f923	build/01_eia/EIA_906923.Rmd	EIA	Predecessor to Form EIA-923, where the data are available from 1998 to 2007.	No
f906_YYYY.zip	data/eia/f923	build/01_eia/EIA_906923.Rmd	EIA	Predecessor to Form EIA-923, where the data are available from 1998 to 2007.	No
f923_YYYY.zip	data/eia/f923	build/01_eia/EIA_423923.Rmd	EIA	Form EIA-923 collects electric power data on electricity generation, fuel consumption, fossil fuel stocks, and receipts at the power plant and prime mover level, where the data are available from 1989 to the present through historical forms, including EIA-867, EIA-906, and EIA-920.	No
fgds_1985_2005.csv	data	build/02_boilers/02_eia767_1985-2005.R	Internal	Flue-gas-desulfurization-by-year panel of EIA-767 data between 1985 and 2005.	No
fgds_1985_2018.csv	data	build/02_boilers/04_merge_eia767_and_eia860.R	Internal	Flue-gas-desulfurization-by-year panel of EIA-767 and EIA-860 data between 1985 and 2018.	No
fgds_2007_2018.csv	data	build/02_boilers/03_eia860_2007-2018.R	Internal	Flue-gas-desulfurization-by-year panel of EIA-860 data between 2007 and 2018.	No
generators_1985_2005.csv	data	build/02_boilers/02_eia767_1985-2005.R	Internal	Generator-by-year panel of EIA-767 data between 1985 and 2005.	No
generators_1985_2018.csv	data	build/02_boilers/04_merge_eia767_and_eia860.R	Internal	Generator-by-year panel of EIA-767 and EIA-860 data between 1985 and 2018.	No
generators_2007_2018.csv	data	build/02_boilers/03_eia860_2007-2018.R	Internal	Generator-by-year panel of EIA-860 data between 2007 and 2018.	No
gf_cems_xwalk.dta	data/xwalk	build/03_cems/03_cems_query.R	Internal	Final crosswalk on ORISPL and boiler codes between the boiler dataset regression_vars.csv and CEMS data.	Yes
gf_matches_full.csv	data	build/03_cems/03_cems_query.R	Internal	Draft crosswalk on ORISPL and boiler codes between the boiler dataset regression_vars.csv, the EPA-EIA crosswalk, and CEMS data, used to generate manual matches for the gf_cems_xwalk.dta.	No
gf_status_born_around_1978.xlsx	data/regs	NA	Internal	Boiler NSR-grandfathering status for those that commenced operations soon after 1978. The data are based on calls, news search, etc.	Yes
handmatched_pa_maine_nm_mass.csv	data/xwalk	build/02_boilers/07_merge_boilers_to_regulations.R	Internal	Crosswalk matching boilers in states with irregular geographical boundaries for air quality regions/basins (e.g., not defined by county) to the correct geographical location. It was compiled by comparing plant location with a map of air basins available here.	Yes
indiana.xlsx	data/regs	NA	Internal	Indiana site-specific regulations limited to boilers in our sample.	Yes
merged_regs_and_plants.csv	data	build/02_boilers/07_merge_boilers_to_regulations.R	Internal	Plant-by-year panel of regulations.	No
mine_data_long.csv	data	build/02_boilers/06_coal_mine_data_eia923.R	Internal	Coal mine-by-plant-by-year panel of EIA-423 and EIA-923 coal mine data.	No
mine_var_names.csv	data/xwalk	build/02_boilers/06_coal_mine_data_eia923.R	Internal	Crosswalk to account for small changes in field names over time in EIA-423 and EIA-923 coal mine data.	Yes
nonattainment_by_cty_year.csv	data	build/02_boilers/01_county_level_data.R	Internal	County-by-year panel of nonattainment status.	No
phistory.csv	data/epa	NA	EPA	County attainment status from 1992 onwards sourced from the EPA Green Book. Note that coverage between 1978 to 1990 is included in <phistory_1978_1990.csv>.	Yes
phistory_1978_1990.csv	data/epa	NA	EPA	County attainment status from 1978 to 1990 based upon work by Randy A. Becker, PhD, at the Center for Economic Studies, US Census Bureau and synthesized at the State and Local Programs Group Air Quality Policy Division Office of the EPA.	Yes
plants_1985_2005.csv	data	build/02_boilers/02_eia767_1985-2005.R	Internal	Plant-by-year panel of EIA-767 data between 1985 and 2005.	No
plants_1985_2018.csv	data	build/02_boilers/04_merge_eia767_and_eia860.R	Internal	Plant-by-year panel of EIA-767 and EIA-860 data between 1985 and 2018.	No
plants_2007_2018.csv	data	build/02_boilers/03_eia860_2007-2018.R	Internal	Plant-by-year panel of EIA-860 data between 2007 and 2018.	No
plants_fuel_1970_2000.csv	data	build/02_boilers/05_fuel_and_fuel_comp_1970_2018.R	Internal	Plant-by-year panel of EIA-759 coal data between 1970 and 2000.	No
readme.xlsx	data	NA	Internal	Tabular data for the README.md file.	Yes
regression_vars.csv	data	build/02_boilers/09_generate_regression_vars.R	Internal	Final synthesized boiler data.	No
regressions_ready_data.dta	data	build/04_preprocessing/02_regression_data.do	Internal	Final synthesized boiler data preprocessed for analysis.	No
so2_regulations_by_state_1976_to_2019.xlsx	data/regs	NA	Internal	State-by-year panel of regulations except Indiana site-specific regulations, which are located in <indiana.xlsx>. These data were manually collected.	Yes
stackflues_1985_2005.csv	data	build/02_boilers/02_eia767_1985-2005.R	Internal	Stackflue-by-year panel of EIA-767 data between 1985 and 2005.	No
stackflues_1985_2018.csv	data	build/02_boilers/04_merge_eia767_and_eia860.R	Internal	Stackflue-by-year panel of EIA-767 and EIA-860 data between 1985 and 2018.	No
stackflues_2007_2018.csv	data	build/02_boilers/03_eia860_2007-2018.R	Internal	Stackflue-by-year panel of EIA-860 data between 2007 and 2018.	No
state_code_xwalk.csv	data/xwalk	NA	Internal	Crosswalk from state name to state two-letter code.	Yes
state_fips_xwalk.csv	data/xwalk	NA	Internal	Crosswalk from state name to FIPS code.	Yes
sulfur_iv.csv	data	build/04_preprocessing/01_sulfur.Rmd	Internal	Plant-by-year panel of sulfur instrumental variables based on EIA-423 and EIA-923 coal data, and NTAD network data.	No
utilities_in_1996-97.csv	data	build/02_boilers/08_feature_generation.R	Internal	Utility-by-year panel of EIA-860 data between 1996 and 1997.	No
utils_2007_2018.csv	data	build/02_boilers/03_eia860_2007-2018.R	Internal	Utility-by-year panel of EIA-860 data between 2007 and 2018.	No
varname_xwalks.xlsx	data/xwalk	NA	Internal	Crosswalk to account for small changes in field names over times in EIA form data.	Yes

Computational requirements

The analysis for the paper can be performed on a personal computer. The software and hardware requirements are summarised below.

Software

We use R as the backbone of our workflow. Stata and MySQL serve specific but limited roles within our project.

All utilized software and packages are summarized in the table below.

Software	Purpose	Packages
R 4.3.1	Data collection, cleaning, and analysis	assertr [2.8]
		data.table [1.15.4]
		foreign [0.8-82]
		fs [1.6.2]
		geofacet [0.2.1]
		ggrepel [0.9.1]
		glue [1.6.2]
		haven [2.5.2]
		here [1.0.1]
		Hmisc [5.2-0]
		httr [1.4.6]
		knitr [1.48]
		lmtest [0.9-40]
		plotly [4.10.4]
		readxl [1.4.2]
		reshape2 [1.4.4]
		rmarkdown [2.29]
		RStata [1.1.1]
		rvest [1.0.3]
		sandwich [3.0-2]
		scales [1.2.1]
		sf [1.0-15]
		sfnetworks [0.6.3]
		stargazer [5.2.3]
		tidygraph [1.3.0]
		tidyverse [2.0.0]
		writexl [1.4.0]
		zip [2.2.0]
		zoo [1.8-11]
Stata SE 16.1	Regressions	grc1leg
		regsave
MySQL 8.0	CEMS data storage	NA

Hardware

The most recent run took about a week on a personal laptop running Windows 10 Home with an Intel four-core CPU at 2.60GHz, 20GB of RAM, and 50GB of free space.

Approximate storage space required for the repository is about 3GB once all public data has been collected. The CEMS SQL database requires approximately 30GB of storage, due to the hourly resolution of the data. In the official replication package, we instead provide synthesized CEMS datasets.

While most scripts run in a matter of minutes to hours, there are a few which require days to complete. These time-intensive scripts include:

• build/03_cems;
• build/04_preprocessing/01_sulfur.Rmd; and,
• build/05_analysis/08_plot_coefyr.R.

Code

Below we provide a high-level overview of the code along with a file-by-file description of their purpose.

The code in this repository is licensed under the GNU General Public License v3.0 (GPL-3.0). You may use, share, and adapt all code with appropriate credit and with derivations under the same license. See LICENSE.md for details.

The main code folders can be summarized as follows:

• Programs in build/01_eia collect and clean EIA data, including but not limited to Forms EIA-767, EIA-860, EIA-861, and EIA-923. The automation script 01_eia/00_master.R will run them all, where order is not important. Alternatively, all constituent programs can be run independently
• Programs in build/02_boilers synthesize the boiler dataset, primarily based on EIA data. The automation script 02_boilers/00_master.R will run them all where order is important.
• Programs in build/03_cems collect, ingest, and clean EPA CEMS data, where order is important.
• Programs in build/04_preprocessing prepare the sulfur instrumental variables as well as the final regression dataset. The automation script 04_preprocessing/00_master.R will run them both, where order is not important. Alternatively, all constituent programs can be run independently.
• Programs in build/05_analysis perform the analysis and output all tables and figures. The automation script 05_analysis/00_master.R will run them all. Order is important for programs 04_regs_data.R through 08_plot_coefyr.R; otherwise, the remaining programs are independent and order is not essential.
• Functions in src assist the build programs to complete their tasks.

The following table describes the code within the build and src folders. Further details are provided within the scripts themselves.

File	Location	Description
EIA_423923.Rmd	build/01_eia	This workbook is a part of the data cleaning process. It downloads and cleans data from EIA-923 and its predecessor, EIA-423. The forms contain monthly fuel receipts for plants with a fossil-fueled nameplate generating capacity of 50+ MW. It returns <eia_fuel.xlsx> and <eia_sulfur.csv>, which contain plant- and state-by-month panels of fuel prices and mine and county cross-section of sulfur contents, respectively.
EIA_759.Rmd	build/01_eia	This workbook is part of the data cleaning process. It downloads data from EIA-759, a predecessor to EIA-923. The forms contain monthly power plant data. It forms part of the <regression_vars.csv> dataset which contains a boiler-by-year panel.
EIA_767.Rmd	build/01_eia	This workbook is part of the data cleaning process. It downloads data from EIA-767, a predecessor to EIA-923. The forms contain plant operations and equipment design data. It forms part of the <regression_vars.csv> dataset which contains a boiler-by-year panel.
EIA_860.Rmd	build/01_eia	This workbook is part of the data cleaning process. It downloads data from EIA-860. The forms contain electric generator data. It forms part of the <regression_vars.csv> dataset which contains a boiler-by-year panel.
EIA_861.Rmd	build/01_eia	This workbook is part of the data cleaning process. It downloads and cleans annual sales by utility from the EIA. Specifically, it utilizes the “Sales to Ultimate Customers” table reported in form EIA-861. It returns <eia_sales.csv> which contains a utility-by-year panel of electricity sales.
EIA_906923.Rmd	build/01_eia	This workbook is a part of the data cleaning process. It downloads and cleans data from EIA-923 and its predecessors, EIA-906 and EIA-920. The forms provide monthly and annual data on generation and fuel consumption at the power plant and prime mover level. A subset of plants – steam-electric plants 10 MW and above – also provide boiler level and generator level data. It returns <eia_netgen.csv> and <eia_netgen_unit.csv>, which contain plant- and boiler-by-month panels of net generation, respectively.
EIA_capacity.Rmd	build/01_eia	This workbook is a part of the data cleaning process. It downloads and cleans annual capacity by state and fuel source from the EIA. Specifically, it utilizes the “Existing Nameplate and Net Summer Capacity by Energy Source, Producer Type and State” table based on annual data reported in form EIA-860. It returns <eia_capacity.csv>, which contains a state-by-fuel-by-year panel of electricity capacities.
00_master.R	build/02_boilers	This program provides a preamble and automates the other scripts in the build/02_boilers subfolder with the aim of performing boiler data cleaning for the Grandfathering project.
01_county_level_data.R	build/02_boilers	This program This script synthesizes county centerpoints and county non-attainment by year, returning <ctrpoints_counties.csv> and <nonattainment_by_cty_year.csv>, respectively.
02_eia767_1985-2005.R	build/02_boilers	This program creates the boiler sample from 1985 to 2005. It combines data from Form EIA-767 on coal plants, in particular location, heat rate, nameplate, and scrubbers. It returns <boilers_1985_2005.csv>, <fgds_1985_2005.csv>, <plants_1985_2005.csv>, <generators_1985_2005.csv>, and <stackflues_1985_2005.csv>.
03_eia860_2007-2018.R	build/02_boilers	This program creates the boiler sample from 2007 to 2018, where it synthesizes data from Form EIA-860. It returns <boilers_2007_2018.csv>, <fgds_2007_2018.csv>, <generators_2007_2018.csv>, <plants_2007_2018.csv>, <stackflues_2007_2018.csv>, and <utils_2007_2018.csv>.
04_merge_eia767_and_eia860.R	build/02_boilers	This program merges Forms EIA-767 and EIA-860, which contain most of the relevant boiler data from different time periods. It returns <boilers_1985_2018.csv>, <fgds_1985_2018.csv>, <plants_1985_2018.csv>, <generators_1985_2018.csv>, and <stackflues_1985_2018.csv>.
05_fuel_and_fuel_comp_1970_2018.R	build/02_boilers	This program merges fuel data from Forms EIA-767, EIA-923, and EIA-867 between 1970 and 2018. It synthesizes coal plant location, heat rate, nameplate, and scrubber information. It returns <plants_fuel_1970_2000.csv>, <all_fuel_1970_2018.csv>, and <boilers_fuel_comp_1985_2018.csv>.
06_coal_mine_data_eia923.R	build/02_boilers	This program merges coal mine data from Forms EIA-423 and EIA-923 between 1970 and 2018. It returns <coal_char_data_by_plant_year.csv> and <mine_data_long.csv>.
07_merge_boilers_to_regulations.R	build/02_boilers	This program merges boiler and regulation data. It returns <merged_regs_and_plants.csv>.
08_feature_generation.R	build/02_boilers	This program merges all data, generates additional useful features, eliminates unnecessary variables, and conducts additional data cleaning. It returns <utilities_in_1996-97.csv> and <all_years_all_plants_and_features.csv>.
09_generate_regression_vars.R	build/02_boilers	This program among other things generates a variable to indicate boiler modification, creates rolling variables for generation and sulfur content, and performs additional data cleaning. It returns <regression_vars.csv>.
01_cems_scrape.R	build/03_cems	This program is the first in a series related to EPA CEMS data; it scrapes CEMS data from the EPA FTP website.
02_cems_ingestion.R	build/03_cems	This program is the second in a series related to EPA CEMS data; it synthesizes all available CEMS data and transfers it to the local MySQL epa database.
03_cems_query.R	build/03_cems	This program is the third in a series related to EPA CEMS data; it queries CEMS data from the MySQL epa database, builds a GF-EPA crosswalk by boiler id, and returns aggregated CEMS data by hour and year.
00_master.R	build/04_preprocessing	This program provides a preamble and automates the other scripts in the build/04_preprocessing subfolder with the aim of preparing the data for analysis.
01_sulfur.Rmd	build/04_preprocessing	This workbook forms a part of the data cleaning process. It prepares a sulfur instrumental variable (IV) based on plant distance to low sulfur coal. It utilizes cleaned data from EIA-923 as well as its predecessors and network data from the NTAD. It returns <sulfur_iv.csv>.
02_regression_data.do	build/04_preprocessing	This program preprocesses the data in advance of the analysis for the Grandfathering project. It returns …
00_master.R	build/05_analysis	This program provides a preamble and automates the other scripts in the build/05_analysis subfolder with the aim of executing the analysis for the Grandfathering project.
01_plot_survival.R	build/05_analysis	This program is a part of the analysis. It prepares a survival share bar plot returning <fig1.pdf>.
02_tbl_balance.Rmd	build/05_analysis	This workbook is a part of the analysis. It prepares data balance tables using boiler data, EPA-EIA crosswalk, and EPA facility attributes. It returns <tbl5.tex> and <tbl6.tex>. It also returns <fig2.pdf>, which contains a map associating boiler NSR grandfathering share with their plant coordinates.
03_plot_local_reg.R	build/05_analysis	This program is a part of the analysis. It prepares a local regulations plot by state and year. It returns <fig3.pdf>.
04_regs_data.R	build/05_analysis	This program is part of the analysis. It prepares the cleaned boiler data for the regression analysis that follows in <05_regs_main.R>, <06_regs_robust.R>, and <07_regs_netgen.R>.
05_regs_main.R	build/05_analysis	This program is part of the analysis. It performs the main regressions for utilization, survival, and emissions along with their first stages. It returns <tbl1.tex> and <tbl2.tex>, respectively.
06_regs_robust.R	build/05_analysis	This program is part of the analysis. It performs the robustness regressions based on ‘fully vs partially grandfathered’, ‘non-linear age’, ‘spillover’, and ‘anticipation’. It returns <tbl3.tex>, <tbl8.tex>, and <tbl9.tex>.
07_regs_netgen.R	build/05_analysis	This program is a part of the analysis. It calculates the the net-to-gross generation ratio (GR) for as many grandfathered boilers/power plants as possible. It utilizes hourly gross generation data from EPA CEMS and monthly net generation data from EIA-923 and its predecessors. It performs a set of naive regressions and returns <tbl2.tex>.
08_plot_coefyr.R	build/05_analysis	This program is part of the analysis. It prepares a series of plots on the time-dependent effects of grandfathering and returns <fig4a.pdf>, <fig4b.pdf>, and <fig4c.pdf>.
09_plot_coef_cutoff.do	build/05_analysis	This program is part of the analysis. It prepares a coefficient cutoff plot, including utilization, survival, and emissions. It returns <fig5.png>.
10_plot_reg_dist.do	build/05_analysis	This program is part of the analysis. It prepares a distribution of sulfur dioxide regulations plot and returns <fig6.png>.
boilers.R	src	This script provides helper functions related to the boiler dataset prepared in build/02_boilers.
def_paths.R	src	This script provides directory paths within the Grandfathering repository. It is legacy code primarily used in build/01_eia, and otherwise, replaced with the here package.
dir_class.R	src	This script provides helper functions for <def_paths.R>, namely to extract a path’s base folder name and add that name as a class type.
find_newfiles.R	src	This script identifies new online data files for EPA CEMS compared to the local storage of these files. It is called in <02_cems_ingestion.R> only.
networks.R	src	This script provides helper functions related to the sf_networks package and network cleaning. It is called in <01_sulfur.Rmd> only.
plots.R	src	This script provides a set of ggplot2 theme functions.
preamble.R	src	This program provides some of the necessary packages for the Grandfathering repository.
sql_data_transfer.R	src	This script provides the functions necessary to transfer EPA CEMS raw files into the MySQL epa database. It is only used in the build/01_eia subfolder.
sql_db_epa.R	src	This script creates the epa schema within the local MySQL database. The schema is populated with EPA CEMS data. It is only used in the build/01_eia subfolder.
sql_tbl_cems.R	src	This script creates the cems table within the MySQL epa database. This table is populated with EPA CEMS cleaned data. It is only used in the build/01_eia subfolder.
sql_tbl_filelog.R	src	This script creates the filelog table within the MySQL epa database. This table is populated with EPA CEMS) raw data files which have been ingested successfully into the MySQL database. It is only used in the build/01_eia subfolder.
sql_tbl_xwalk.R	src	This script creates the xwalk table within the MySQL epa database. This table is populated with EPA-EIA power plant crosswalk data. It is only used in the build/01_eia subfolder.
stata_regs.R	src	This script provides functions necessary to perform analysis regressions in Stata. It is only used in the build/05_analysis subfolder.
text_colour.R	src	This script provides a text colouring function for workbooks within the Grandfathering project.

Instructions

The previous sections describe the data and software necessary to conduct a replication. This section provides human-readable instruction for performing a replication immediately below, along with a table mapping outputs-to-code.

1. Run all Rmd files in build/01_eia in any order. Use of the automation script bulid/01_eia/00_master.R is optional. Produced files include:
   • eia_capacity.csv
   • eia_fuel.xlsx
   • eia_netgen_unit.csv
   • eia_netgen.csv
   • eia_sales.csv
   • eia_sulfur.csv
2. Run all R files in build/02_boilers in the order provided. Use of the automation script bulid/02_boilers/00_master.R is required. Note that build/02_boilers/07_merge_boilers_to_regulations.R requires manual intervention to prepare handmatched_pa_maine_nm_mass.csv. Our copy of that file is included in the data repository. Produced files include:
   • regression_vars.csv
   • coal_char_data_by_plant_year.csv
3. Run all R files in build/03_cems in the order provided. Note that build/03_cems/03_cems_query.R requires manual intervention to prepare data/xwalk/gf_cems_xwalk.dta. Produced files include:
   • cems_yr.dta
4. Run all R and do files in build/04_preprocessing in any order. Use of the automation script bulid/04_preprocessing/00_master.R is optional. Produced files include:
   • sulfur_iv.csv
   • regressions_ready_data.dta
5. Run all R, Rmd, and do files in build/05_analysis in the order provided. Use of the automation script bulid/05_analysis/00_master.R is required. Produced files are summarized in the output-code table below.

Reference	File	Code	Title
Figure 1	fig1.pdf	build/05_analysis/01_plot_survival.R	Propensity to survive until 2014 for boilers from different vintages
Figure 2	fig2.pdf	build/05_analysis/02_tbl_balance.Rmd	Coal-fired boilers by initial NSR grandfathering status
Figure 3	fig3.pdf	build/05_analysis/03_plot_local_reg.R	Mean inverse local regulations by state and year
Figure 4	fig4a.pdf	build/05_analysis/08_plot_coefyr.R	Time-dependent effects of NSR grandfathering: Hourly utilization
Figure 4	fig4b.pdf	build/05_analysis/08_plot_coefyr.R	Time-dependent effects of NSR grandfathering: Survival
Figure 4	fig4c.pdf	build/05_analysis/08_plot_coefyr.R	Time-dependent effects of NSR grandfathering: Sulfur emissions rate
Figure 5	fig5.png	build/05_analysis/09_plot_coef_cutoff.do	Grandfathering coefficient estimates depending on the set of considered boilers
Figure 6	fig6.png	build/05_analysis/10_plot_reg_dist.do	Distribution of sulfur dioxide regulations in the data
Table 1	tbl1.tex	build/05_analysis/05_regs_main.R	Main regression results
Table 2	tbl2.tex	build/05_analysis/07_regs_netgen.R	Net-to-gross generation ratio regressions
Table 3	tbl3.tex	build/05_analysis/06_regs_robust.R	Fully versus partially grandfathered regression results
Table 4	N/A	N/A	Variables summary
Table 5	tbl5.tex	build/05_analysis/02_tbl_balance.Rmd	Average characteristics of boilers by NSR grandfathering status
Table 6	tbl6.tex	build/05_analysis/02_tbl_balance.Rmd	Average characteristics of boilers by local regulation
Table 7	tbl7.tex	build/05_analysis/05_regs_main.R	Main regression first-stage results
Table 8	tbl8.tex	build/05_analysis/06_regs_robust.R	Robustness regression results
Table 9	tbl9.tex	build/05_analysis/06_regs_robust.R	Anticipation regression results

Citation

Please cite the paper as:

Bialek-Gregory, Sylwia, Jack Gregory, Bridget Pals, and Richard Revesz. Forthcoming.
“Still your grandfather’s boiler: Estimating the effects of the Clean Air Act’s grandfathering provisions.”
Journal of the Association of Environmental and Resource Economists.

Please cite the repository as:

Bialek-Gregory, Sylwia, Jack Gregory, Bridget Pals, and Richard Revesz. Forthcoming.
Grandfathering. Version 4.0. GitHub repository. Available at https://github.com/jack-gregory/Grandfathering.

References

Huetteman, J, J Tafoya, T Johnson, and J Schreifels. 2021. “EPA-EIA Power Sector Data Crosswalk.” United States Environmental Protection Agency (EPA). https://www.epa.gov/airmarkets/power-sector-data-crosswalk.

US DOT. 2022. “National Transportation Atlas Database.” Bureau of Transportation Statistics. https://www.bts.gov/ntad.

US EIA. 2005. “Form EIA-767: Steam-Electric Plant Operation and Design Report.” U.S. Department of Energy. https://www.eia.gov/electricity/data/eia767/.

———. 2019a. “Form EIA-860: Annual Electric Generator Report.” U.S. Department of Energy. https://www.eia.gov/electricity/data/eia860/.

———. 2019b. “Form EIA-923: Power Plant Operations Report.” https://www.eia.gov/electricity/data/eia923/.

———. 2019c. “State Electricity Data.” U.S. Department of Energy. https://www.eia.gov/electricity/data/state/.

———. 2021a. “Form EIA-861: Annual Electric Power Industry Report.” U.S. Department of Energy. https://www.eia.gov/electricity/data/eia861/.

———. 2021b. “US Energy Atlas.” https://atlas.eia.gov/.

———. 2023. “Form EIA-423: Monthly Cost and Quality of Fuels for Electric Plants Report.” U.S. Department of Energy. https://www.eia.gov/electricity/data/eia423/.

US EPA. 2021a. “County Nonattainment Data.” https://www3.epa.gov/airquality/greenbook/downld/phistory.xls.

———. 2021b. “Power Sector Data.” Office of Atmospheric Protection, Clean Air; Power Division. https://campd.epa.gov.

Footnotes

1. Continuous emission monitoring system (CEMS) data published by the US Environmental Protection Agency (EPA). ↩