An Economic Analysis of 

the Appalachian Coal 

Industry Ecosystem

West Virginia University

and

The University of Tennessee

Human Capital and the CIE 

Prepared for the 

Appalachian Regional Commission 

under contract # PW-18673-16

January 2018
An Economic Analysis of 

the Appalachian Coal 

Industry Ecosystem 

Human Capital and the CIE

Matthew Murray, Professor, Economics; Director, Howard H. Baker Jr. Center 

for Public Policy; and Associate Director, Boyd Center for Business and

Economic Research, University of Tennessee

Péter Schaeffer, Professor, Division of Resource Economics and Management,

and Faculty Research Associate, Regional Research Institute, West Virginia

University

Prepared for the Appalachian Regional Commission, under contract # PW-18673-16

January 2018
2

Table of Contents

Executive Summary ........................................................................................................................... 7

Subtask 1: Existing Human Capital Stock ...................................................................................... 8

1. The Region’s Coal Mining Communities and Labor Force................................................ 10

2. Coal Industry Labor Force and Employment...................................................................... 23

2.1. Coal Mining Employment................................................................................................ 23

2.2. A Profile of the United States Coal Miner................................................................... 30

2.3. Coal Mining Support Employment................................................................................. 36

3. Mobility between Industries and Occupations .................................................................. 37

4. Coal Occupations: Are Other Opportunities Available in Appalachia?.......................... 41

4.1. Matching Coal Worker Occupations to Similar Occupations in Other Industries.. 41

4.2. State by State Occupational Analysis .......................................................................... 42

5. Summary and Recommendations: Subtask 1.......................................................................... 51

Subtask 2: The Education Pipeline ............................................................................................... 52

1. State K-12 Funding Programs ............................................................................................... 54

1.1 Alabama.............................................................................................................................. 55

1.2 Kentucky............................................................................................................................. 55

1.3 Maryland............................................................................................................................. 56

1.4 Mississippi........................................................................................................................... 57

1.5 Ohio..................................................................................................................................... 57

1.6 Pennsylvania ...................................................................................................................... 58

1.7 Tennessee........................................................................................................................... 58

1.8 Virginia................................................................................................................................ 59

1.9 West Virginia...................................................................................................................... 59
3

1.10 Summary........................................................................................................................... 60

2. Local Government Taxes and Burdens................................................................................ 60

3. Elementary and Secondary Education Funding and Spending ........................................ 68

4. Summary and Recommendations: Subtask 2 ..................................................................... 81

References ........................................................................................................................................ 83
4

List of Tables

Table 1: Appalachian Counties with Coal Employment in 2010 ............................................................... 11

Table 2: Appalachian Regional Labor Markets – All Industry and Manufacturing Employment.............. 13

Table 3: Statewide Average Annual Headline (U3) and Alternative Unemployment Rates, 2016........... 15

Table 4: All Industry and Manufacturing Establishments for States and Other Geographies in Appalachia

.................................................................................................................................................................. 16

Table 5: Population Counts and Age Distributions for States and Other Geographies in Appalachia ..... 17

Table 6: Educational Attainment of the Population 25 Years and Older for States and Other Geographies 

in Appalachia............................................................................................................................................. 19

Table 7: State-Level Disease Prevalence (Crude Prevalence, Percent)..................................................... 20

Table 8: 2017 County Health Rankings for Coal-Employment Counties in the Appalachian Region........ 21

Table 9: Per Capita Personal Income (2009 Inflation-Adjusted Dollars) for State and Other Geographies 

in Appalachia............................................................................................................................................. 22

Table 10: Regional Poverty Rates (Percent) for States and Other Geographies in Appalachia................ 23

Table 11: Appalachian States and Regional Coal Employment and Coal Production, 2000 and 2015..... 25

Table 12: State Coal Mining and Related Transportation and Support Employment, 2015 .................... 26

Table 13: Coal Employment and Coal Production by Appalachian County for Counties with Coal 

Employment in 2010................................................................................................................................. 28

Table 13: Coal Employment and Coal Production by Appalachian County for Counties with Coal 

Employment in 2010, (continued) ............................................................................................................ 29

Table 14: Profile of the United States Coal Miner.................................................................................... 32

Table 15: Average Number of Hours Worked by Coal Miners in 2007..................................................... 34

Table 16: United States Coal Mining Occupations by Major SOC Group, 2015........................................ 35

Table 17: National Construction and Extraction Occupations, 2015........................................................ 36

Table 18: Workers Entering, Leaving and Shifting within the Mining, Quarrying, Oil and Gas Extraction 

Industry by Appalachian State .................................................................................................................. 38

Table 19: Coal Mining Employment and the Distribution of Occupations: Alabama ............................... 45

Tale 20: Coal Mining Employment and the Distribution of Occupations: Kentucky ................................ 46

Table 21: Coal Mining Employment and the Distribution of Occupations: Ohio...................................... 46

Table 22: Coal Mining Employment and the Distribution of Occupations: Pennsylvania ........................ 47

Table 23: Coal Mining Employment and the Distribution of Occupations: Virginia................................. 48

Table 24: Coal Mining Employment and the Distribution of Occupations: West Virginia........................ 49

Table 24: Coal Mining Employment and the Distribution of Occupations: West Virginia, (continued)... 50
5

Table 25: Local Government Total Taxes for States and Other Geographies in Appalachia, 2007 and 2012

.................................................................................................................................................................. 61

Table 26: Local Government Major Taxes as a Share of Total Taxes for States and Other Geographies in 

Appalachia, 2012....................................................................................................................................... 65

Table 27: State Severance Taxes, 2016..................................................................................................... 67

Table 28: State-Levied Coal Severance Tax Revenue, State Fiscal Years 2005-2015 ($) .......................... 67

Table 29: Total Elementary-Secondary Revenue, Distribution by Source for States and Other Geographies 

in Appalachia, 2014................................................................................................................................... 70

Table 30: Total Elementary-Secondary State Revenue per Pupil for States and Other Geographies in 

Appalachia, 2000, 2010 and 2014............................................................................................................. 72

Table 31: Total Elementary-Secondary Local Revenue per Pupil for States and Other Geographies in 

Appalachia, 2000, 2010 and 2014............................................................................................................. 74

Table 32: Current Spending per Pupil for States and Other Geographies in Appalachia, 2000, 2010 and 

2014 .......................................................................................................................................................... 77

Table 33: Total Elementary and Secondary School Enrollment for States and Other Geographies in 

Appalachia, 2000, 2010 and 2014............................................................................................................. 80
6

List of Figures

Figure 1: Appalachian Counties with Coal Employment in 2010 .......................................... 12

Figure 2: Coal Employment Trends Since 2000............................................................... 24

Figure 3: Change in Coal Employment in Appalachian Counties, 2010-2015............................ 30

Figure 4: Job-to-Job Flows in West Virginia ................................................................. 39

Figure 5: Local Tax Revenue as a Share of Total Personal Income, Appalachian Counties: 2012... 63

Figure 6: Total Current Spending per Pupil by Geography ................................................. 75

Figure 7: Change in Total Current Spending Per Pupil, 2010 to 2014 .................................... 78

Figure 8: Elementary and Secondary School Enrollment by Geography................................. 79
7

Executive Summary

Task 5 of the comprehensive report has two goals. The first is to examine occupations that might be 

affected by employment losses in the coal industry ecosystem (CIE). The primary focus is on direct

production employment in the coal sector, but some references are also made to managerial support 

workers and indirect workers in the coal industry supply chain. Potentially-impacted occupations are 

identified, as are alternative occupational opportunities in other sectors of the economy where coal 

workers might be absorbed. We also discuss coal worker transition time from unemployment status to 

employment status and identify factors that both encourage and prevent timely transitions. This 

discussion is framed by an overview of broad labor market conditions throughout the Appalachian 

Region. The second goal is to assess the state and local elementary and secondary education funding 

implications of a declining CIE. Considered are state funding sources and mechanisms and local 

funding sources for education that rely on local tax capacity and effort to complement state resources 

in support of elementary and secondary education. Together these various components of the analysis 

enable an evaluation of future employment prospects for the current coal workforce along with the 

funding streams that will affect the quality of the workforce of the future through the support for K12 education.

The analysis of potentially-affected coal miner occupations begins with an overview of labor market 

conditions with a spotlight on mining counties within the Appalachian Region, as defined by those 

counties with coal employment in 2010. These counties are referred to as coal-employment counties

or simply coal counties in what follows. To frame the discussion of coal-employment communities, we 

make comparisons to the Appalachian Region, states that are represented in the Appalachian Region,

and the national economy. The analysis shows that labor markets within coal communities and the 

Appalachian Region itself are generally depressed relative to the states and the United States. The 

characteristics of these labor markets suggests that there will be difficulties creating robust new 

employment opportunities in the Region.

There were 129 counties in the Appalachian Region that had coal employment in 2010. Seventy-eight 

of these counties saw coal employment contract between 2000 and 2015. In 2015, three counties were 

reliant on coal employment for more than 20 percent of their employment base and another 13 

counties were reliant on coal for 10-20 percent of their local employment base. Of these 16 counties, 

only four have experienced employment growth since 2010.

Highly-paid coal miners generally have limited re-employment opportunities within their place of 

residence, especially in terms of similar occupations and pay scales. We evaluate alternative 

employment opportunities for coal workers by isolating their occupational classifications and 

comparing these to equivalent occupational classifications for workers in the manufacturing, 

construction, and transportation sectors. This analysis is undertaken for two regional geographies: (i) 

an aggregation of Appalachian counties within a given state and (ii) entire state economies for 

Appalachian states that have coal communities. These broad regions are chosen since individual 

counties offer insufficient scale and diversity to absorb coal workers. One important implication is 

that coal miners may be required to engage in lengthy commutes or migrate from their current place 

of residence in pursuit of gainful employment opportunities outside of the coal industry. Commuting 

to jobs in another county is already a common occurrence in Appalachia. Outmigration may represent 

a potentially-significant hurdle since the population of the Appalachian Region is characterized by 

relatively low mobility rates relative to the national population. Retraining and other assistance will 

likely be needed for many of those displaced by declining coal production.

The coal sectors in Alabama, Pennsylvania and Ohio have relatively small numbers of occupations that 

are equivalent to occupations in manufacturing, construction and transportation at the state and 

substate regional levels. These small numbers suggest that it will be relatively easy to find 

employment opportunities outside the coal sector. However, digging beneath the surface shows that 

in these same states there are several specific occupational categories in the coal sector that have no

equivalent occupations in other sectors. In other instances, the number of equivalent occupations in 
8

other sectors is limited in supply. As is generally the case, individual counties may be at significant 

risk of hardship through coal industry transition, but this can be masked across multi-county areas.

In contrast, the coal sectors in Kentucky, Virginia and West Virginia each have relatively large 

numbers of occupations without equivalent occupations in the manufacturing, construction and 

transportation sectors. This means that it will be harder to absorb coal workers into other sectors of 

the economy. In Kentucky, six occupations in the coal industry representing 2,901 positions have no 

counterparts outside the coal sector; in Virginia, there are eight occupations with 6,048 positions that 

have no equivalent occupations in manufacturing, construction and transportation; and in West 

Virginia, there are 18 coal occupations with no counterpart occupations elsewhere in the state. For 

West Virginia, these occupations represent 6,580 positions and more than one-third of all occupations

in the state’s coal industry. Six occupations representing 4,722 positions in Kentucky have no 

counterparts in the state.

Funding elementary and secondary education is a core government function that helps promote 

economic development and individual and family wellbeing. Elementary and secondary education is 

funded by revenue from federal, state and local governments. Local revenue is especially important 

since it is so closely tied to the performance of the coal industry. Because incomes are below average 

in the Appalachian Region (i.e. the Region is characterized by low tax capacity), per capita local tax 

burdens are also below the national average. In 2014, nominal per capita local taxes among coalemployment counties totaled $1,298 compared to a national average of $1,875. West Virginia and 

Kentucky have especially low per capita burdens. However, when one accounts for differences in 

income, the evidence indicates that Appalachian counties choose to impose relatively low burdens on 

themselves and are thus characterized by low tax effort. While per capita income in coal communities 

is 94.1 percent of the national average, revenues in coal communities are just 69.2 percent of the 

national average.

All the Appalachian states have state funding programs that contribute significantly to local support 

for K-12 education. In general, these complicated formulas account for low tax capacity jurisdictions 

and seek to both boost funding and narrow funding disparities through foundation aid and/or 

equalization programs targeted to local spending or the local tax base. Nominal per pupil state 

funding for K-12 education was $6,639 in coal-employment Appalachian communities in 2014, which is 

higher than spending levels in other Appalachian counties, states in the Appalachian Region, and the 

United States. Per pupil spending was highest in West Virginia. Total state funding support in recent 

years has grown at rates that compare favorably to other regions. Total local per pupil revenue to 

support elementary and secondary education in coal communities has hovered near the national 

average. Between 2010 and 2014, local per pupil revenue growth was up 14.1 percent in coal 

communities versus 5.6 percent growth for localities across the country. Together these data do not 

reveal declining support for K-12 education in coal-employment communities in Appalachia.

Current education spending per pupil in coal communities was $12,119 in 2014, well ahead of the

$11,307 national average and the $10,798 Appalachian Region average. Coal communities have 

consistently spent more per pupil than the national average since 2000. However, current per pupil 

spending did decline between 2010 and 2014 in Kentucky, Virginia and West Virginia, as well as in a 

number of coal communities in Alabama, Ohio and Tennessee, despite growth in total state and local 

revenue per pupil. In addition, enrollments have declined in all coal-employment states other than 

Alabama, which has seen very small growth. Between 2000 and 2014, coal counties saw enrollment 

counts fall by 158,192. Enrollments fell most sharply in Mississippi (down 24.9 percent) and Maryland 

(down 18.5 percent).

Subtask 1: Existing Human Capital Stock

Our analysis of Subtask 1 begins with a high-level overview of selected characteristics of the 

employment base and labor force of Appalachian coal-producing communities, framed by similar data 
9

for the nation, the Appalachian states, and the Appalachian Region.1 The goal is to place in context 

the labor market conditions in coal communities relative to other relevant geographies to better 

understand their unique circumstances and determine their capacity to absorb workers who might 

choose to leave or be displaced from the coal sector. Labor markets tend to be localized, spanning 

single counties or broader arrays of counties in micropolitan and metropolitan areas. These regions 

represent the primary location for alternative employment opportunities for displaced and 

potentially-displaced coal workers. However, in many instances, these displaced workers may find 

limited job alternatives in their proximate area of residence due to small numbers of employers 

and/or a mismatch between occupational supply and demand. Aggravating the problem are pervasive 

weaknesses in local labor markets that will retard economic development and the creation of 

employment opportunities on the part of newly-locating firms. Thus, larger regional labor markets—

including entire states—may represent prime locations for new employment opportunities for coal 

workers. However, this may require long commutes or outmigration from the current place of 

residence. Whether workers choose to stay in their place of residence or move, retraining may be 

required to align worker skills with the demand side of the labor market.

Following this labor market profile, the discussion turns to a detailed analysis of coal mining 

employment and occupations. Because of data limitations within Appalachian coal-producing regions, 

we rely on a blend of national and regional-specific data to broadly characterize coal industry 

workers. Using a number of data sources, including data from states in the Appalachian Region, we 

identify the occupations associated with coal production activity for the major coal producing areas of

the Appalachian Region. The majority of these occupations reflect production-related work activities 

rather than management-related activities.

Finally, we examine employment dynamics and transitions from unemployment to re-employment.

We are again compelled to rely on a variety of data and other resources to understand these 

dynamics. Using data for industries outside of the coal sector, specifically the manufacturing, 

construction, and transportation sectors, equivalent occupations are identified that might represent 

transition opportunities for coal workers. We present these alternative occupational measures for two 

geographies: individual states that are either partially or wholly located in Appalachia, and then an 

aggregation of Appalachian counties within a given Appalachian state. For each state, there are many 

equivalent occupations in the two geographies of focus that in principle offer alternative employment 

opportunities for management and office-related workers. However, this will not necessarily translate

into rapid transition into new jobs due to competition for available openings. For production workers, 

the problem is more acute, especially in specific communities, specific sectors, and more generally in 

Kentucky, Virginia, and West Virginia. In a significant number of cases, there are simply no equivalent

occupational opportunities in the state outside the coal sector. The problem is aggravated by weak 

 1 For a timely and comprehensive overview of socioeconomic data for the Appalachian Region, see Pollard 

and Jacobsen (2016). Also see An Overview of Coal and the Economy in Appalachia, the first report in this series 

of sponsored research projects.
10

long-term trends in the manufacturing sector which might otherwise offer job opportunities for those 

employed in the coal sector. Growth opportunities in manufacturing are muted, so ongoing worker 

quits and terminations might yield the most significant job openings in the manufacturing sector.

1. The Region’s Coal Mining Communities and Labor 

Force

Appalachia is a large and diverse region, with substantial variation in economic prosperity both 

within and across the states that are represented in the Appalachian Region. To frame economic 

conditions in the Appalachian Region, especially those counties with coal mining employment, we 

begin by presenting selected data for various reference geographies, with an emphasis on the labor 

market. We have broken out the data for counties within the Appalachian Region based on whether or 

not coal employment was present in the county in 2010. Table 1 provides a listing of these 129 coalemployment counties while Figure 1 provides a map of the Region to show where these counties are 

located. We recognize that this county demarcation fails to take into account potentially-important 

linkages to other counties through commuting patterns, the coal supply chain, and the ripple effects 

of the multiplier. At the same time, it helps to highlight those places that may be at the greatest risk 

of direct production and employment losses. Many of the coal-employment communities are located in 

sparsely-to-moderately populated counties and regions. This heightens the impact of coal mining job 

losses for host communities and also constrains alternative job opportunities in the place of current 

employment. However, commuting into and out of coal counties helps spread the negative impacts of 

job losses on households across a larger region.
11

Table 1: Appalachian Counties with Coal Employment in 2010

State County State County State County

Alabama Bibb Ohio Coshocton Pennsylvania Washington 

Alabama Blount Ohio Gallia Pennsylvania Westmoreland 

Alabama Cullman Ohio Guernsey Tennessee Anderson 

Alabama Fayette Ohio Harrison Tennessee Campbell 

Alabama Franklin Ohio Jackson Tennessee Claiborne 

Alabama Jackson Ohio Jefferson Tennessee Cumberland 

Alabama Jefferson Ohio Mahoning Tennessee Fentress 

Alabama Marion Ohio Meigs Tennessee Marion 

Alabama Shelby Ohio Monroe Tennessee Scott 

Alabama Tuscaloosa Ohio Muskingum Virginia Buchanan 

Alabama Walker Ohio Noble Virginia Dickenson 

Alabama Winston Ohio Perry Virginia Lee 

Kentucky Bell Ohio Tuscarawas Virginia Russell 

Kentucky Boyd Ohio Vinton Virginia Tazewell 

Kentucky Breathitt Ohio Washington Virginia Wise + Norton City

Kentucky Clay Pennsylvania Allegheny West Virginia Barbour 

Kentucky Elliott Pennsylvania Armstrong West Virginia Boone 

Kentucky Estill Pennsylvania Beaver West Virginia Clay 

Kentucky Floyd Pennsylvania Bedford West Virginia Fayette 

Kentucky Harlan Pennsylvania Blair West Virginia Grant 

Kentucky Jackson Pennsylvania Butler West Virginia Greenbrier 

Kentucky Johnson Pennsylvania Cambria West Virginia Harrison 

Kentucky Knott Pennsylvania Cameron West Virginia Kanawha 

Kentucky Knox Pennsylvania Carbon West Virginia Lincoln 

Kentucky Laurel Pennsylvania Centre West Virginia Logan 

Kentucky Lawrence Pennsylvania Clarion West Virginia McDowell 

Kentucky Leslie Pennsylvania Clearfield West Virginia Marion 

Kentucky Letcher Pennsylvania Columbia West Virginia Marshall 

Kentucky McCreary Pennsylvania Elk West Virginia Mason 

Kentucky Magoffin Pennsylvania Fayette West Virginia Mercer 

Kentucky Martin Pennsylvania Greene West Virginia Mineral 

Kentucky Owsley Pennsylvania Huntingdon West Virginia Mingo 

Kentucky Perry Pennsylvania Indiana West Virginia Monongalia 

Kentucky Pike Pennsylvania Jefferson West Virginia Nicholas 

Kentucky Pulaski Pennsylvania Lackawanna West Virginia Ohio 

Kentucky Whitley Pennsylvania Luzerne West Virginia Preston 

Maryland Allegany Pennsylvania Lycoming West Virginia Raleigh 

Maryland Garrett Pennsylvania Mercer West Virginia Randolph 

Mississippi Choctaw Pennsylvania Northumberland West Virginia Tucker 

Ohio Athens Pennsylvania Schuylkill West Virginia Upshur 

Ohio Belmont Pennsylvania Somerset West Virginia Wayne 

Ohio Carroll Pennsylvania Tioga West Virginia Webster 

Ohio Columbiana Pennsylvania Venango West Virginia Wyoming 

Source: Mine Safety and Health Administration
12

Figure 1: Appalachian Counties with Coal Employment in 2010

Source: U.S. Mine Safety and Health Administration (MSHA)

The ability of coal workers to be absorbed elsewhere in the economy depends on the vitality 

of job markets outside of the coal sector. Table 2 provides data on manufacturing jobs and jobs in all 

industries for the United States, entire states within the Appalachian Region, the Appalachian Region,

and Appalachian coal communities for 2000, 2010, and 2015. New York, Pennsylvania and Ohio have 

the largest economies as measured by jobs; West Virginia, which lies entirely within the Appalachian 

Region, has the smallest state economy of the 13 states, with just 757,000 jobs in 2015. On average, 

the Appalachian states performed more poorly than the national economy between 2000-2015 as 

measured by job growth. The national economy experienced 7.4 percent job growth compared to 4.9 

percent growth for states that are represented in the Appalachian area. The strongest growth 
13

occurred in Virginia, while Mississippi and Ohio each lost jobs. The Appalachian Region itself had 

employment growth of only 0.9 percent over the period shown. Coal-employment communities 

witnessed a 1.7 percent setback in employment. These broad trends point to the added challenge 

displaced coal workers will confront in identifying alternative job opportunities even within broader

regions outside their place of residence.

Table 2: Appalachian Regional Labor Markets – All Industry and Manufacturing Employment

The Region’s manufacturing sector is especially important since it represents a primary 

employment alternative for many of the occupational categories represented in the coal industry.

Unfortunately, manufacturing jobs are down substantially since 2000 in all of the Appalachian states, 

falling 33.8 percent compared to a 29.0 percent decline for the nation. The best performance was in 

Kentucky, but manufacturing jobs in the state were still down 22.3 percent. Maryland suffered the 

steepest setback with a loss of 39.7 percent of its manufacturing job base. Heavily coal-dependent 

West Virginia lost more than one-third of its manufacturing base between 2000 and 2015.

The manufacturing sector has seen a modest employment rebound since the end of the Great 

Recession in the summer of 2009. Prior to the recession, United States manufacturing jobs had been in 

decline since 1997. But in 2011, the nation’s manufacturing sector experienced 1.7 percent job 

growth, and expansions in employment have taken place every year since then. Appalachian counties 

suffered a fate similar to the United States between 2000 and 2015, with manufacturing jobs shrinking 

33.8 percent while coal-employment counties had 33.2 percent contraction in manufacturing 

employment. Between 2000 and 2015, 106 of the 129 coal employment counties had contractions in 

manufacturing employment. However, between 2010 and 2015, 67 coal communities actually 

experienced employment growth in the manufacturing sector. This recent growth should help temper 

the loss in coal employment. However, at least nationally, the gains in manufacturing are expected to 

2000 2010 2015 2000 2010 2015

Alabama 1,931.2 1,813.2 1,949.1 0.9 7.5 351.4 236.3 257.8 -26.6 9.1

Georgia 3,978.5 3,753.9 4,261.9 7.1 13.5 538.0 343.1 379.1 -29.5 10.5

Kentucky 1,816.6 1,712.2 1,886.1 3.8 10.2 310.4 209.1 241.2 -22.3 15.3

Maryland 2,458.4 2,453.2 2,674.0 8.8 9.0 173.2 114.9 104.5 -39.7 -9.0

Mississippi 1,155.0 1,074.6 1,133.7 -1.8 5.5 222.5 136.0 141.8 -36.3 4.3

New York 8,624.9 8,340.7 9,260.1 7.4 11.0 749.3 455.7 455.0 -39.3 -0.2

North Carolina 3,915.1 3,788.6 4,240.3 8.3 11.9 757.9 431.6 461.5 -39.1 6.9

Ohio 5,624.7 4,908.6 5,423.5 -3.6 10.5 1,021.3 620.3 686.8 -32.8 10.7

Pennsylvania 5,693.3 5,472.2 5,835.6 2.5 6.6 864.0 560.5 567.6 -34.3 1.3

South Carolina 1,854.0 1,758.2 2,006.7 8.2 14.1 336.3 207.8 235.9 -29.9 13.5

Tennessee 2,732.8 2,558.4 2,893.9 5.9 13.1 497.2 298.3 333.0 -33.0 11.6

Virginia 3,519.4 3,536.7 3,859.1 9.7 9.1 363.6 229.9 233.6 -35.8 1.6

West Virginia 735.5 692.4 757.0 2.9 9.3 75.9 49.1 47.7 -37.2 -2.8

United States 132,024.0 127,820.4 141,843.0 7.4 11.0 17,314.4 11,487.5 12,291.7 -29.0 7.0

Appalachian States 44,039.4 41,862.9 46,181.0 4.9 10.3 6,261.0 3,892.5 4,145.5 -33.8 6.5

Appalachian Region 9,412.8 9,079.8 9,501.8 0.9 4.6 1,884.6 1,169.0 1,247.5 -33.8 6.7

Appalachian Coal-Employment Counties 3,802.1 3,679.7 3,736.1 -1.7 1.5 556.1 363.6 371.5 -33.2 2.2

Sources: Bureau of Labor Statistics Quarterly Census of Employment and Wages 

All Industries
 Manufacturing


Employment (thousands) Growth

2000-2015

(%)

Growth

2010-2015

(%)

Employment (thuosands) Growth

2000-2015

(%)

Growth

2010-2015

(%)
14

be modest in the years ahead and employment levels are not projected to return to pre-recession 

levels in the foreseeable future.2

Traditional “headline” (or U3) unemployment rates in the Appalachian states roughly align with 

the national average as shown in the middle column of Table 3.3 However, Appalachian counties and 

Appalachian coal mining communities have elevated unemployment rates. In 2000, coal mining 

counties had an average unemployment rate of 4.9 percent, well ahead of all other geographies shown

in the table. In 2015, unemployment rates in coal mining communities averaged 6.0 percent, again 

higher than all other regions shown. West Virginia had the highest state rate in 2000 and 2015. 

Thirteen coal-producing counties had non-seasonally-adjusted rates equal to or above 10 percent in 

2015; only ten coal-producing counties had lower unemployment rates in 2015 compared to 2000.

(Unfortunately, seasonally-adjusted unemployment rates are not available for individual counties.)

Table 3 provides additional insight into the unemployment situation in the Appalachian states by 

considering alternative unemployment metrics using data for 2016. The U1 unemployment rate shows 

those who are unemployed for 15 weeks or longer as a share of the labor force; the U6 measure 

includes unemployed people as well as underemployed people, such as part-time workers who would 

prefer to be employed full-time. The rates are for the whole state, not just its Appalachian counties, 

since these are the only data available for these measures. Headline unemployment rates actually 

converged to 4.9 percent for the Appalachian states and the United States in 2016. However, the 

Appalachian states have slightly higher unemployment rates for both the U1 and U6 measures. West 

Virginia stands out as having the highest U1 measure among the states (2.7 percent) as well as the 

highest U6 rate (11.0 percent).

 2 IHS Economics, U.S. Economic Outlook, Spring 2017. 3 For background and resources on the measurement of unemployment rates, see 

https://www.bls.gov/cps/cps_htgm.htm
15

Table 3: Statewide Average Annual Headline (U3) and Alternative Unemployment Rates, 2016

Business establishment data for all industries and the manufacturing sector provide a 

complementary employer perspective of regional labor market conditions and are presented in Table 

4 for 2000 and 2014 (the most recent year for which establishment data are available). All-industry

establishments for the United States were up 7.0 percent between 2000 and 2014, versus a 1.3

percent establishment loss for counties in the Appalachian Region. Appalachian coal-employment

communities, on the other hand, had significantly larger establishment losses totaling 5.7 percent.

Manufacturing establishments were down for all geographies shown in Table 4 between 2000 and 

2014. The Appalachian Region performed marginally better than the United States, with 

manufacturing establishments declining 17.3 percent, compared to 17.5 percent in the nation as a 

whole.

State U11 U32 U63

Alabama 2.0 6.0 9.6

Georgia 2.4 5.4 10.5

Kentucky 2.0 4.9 9.7

Maryland 1.8 4.2 8.1

Mississippi 2.6 5.7 10.9

New York 2.3 4.8 9.4

North Carolina 2.3 5.0 9.4

Ohio 2.0 4.9 9.7

Pennsylvania 2.1 5.6 10.6

South Carolina 2.0 2.8 9.7

Tennessee 1.8 4.7 9.4

Virginia 1.6 4.1 9.1

West Virginia 2.7 6.1 11.0

United States 2.0 4.9 9.6

Appalachian State Average 2.1 4.9 9.8

2

 The "headline" unemployment rate which measures the share of 

the adult population that is in the labor force but unemployed.

1

 Persons unemployed 15 weeks or longer as a percent of the labor 

force.

3

 Accounts for the unemployed plus all marginally attached 

workers and those who are employed part time for economic 

reasons.

Source: Bureau of Labor Statistics
16

Table 4: All Industry and Manufacturing Establishments for States and Other Geographies in

Appalachia

The fall in manufacturing establishments was more acute in Appalachian coal-employment 

counties with a decline of 18.9 percent. Only 17 of the 129 coal-employment counties were able to 

produce growth in manufacturing establishments between 2000 and 2014. For five of these counties, 

there were no more than five manufacturing establishments in 2014. Six coal-employment counties 

had no manufacturing establishments at all in 2000, while five had no establishments in 2014.

Allegheny County, Pennsylvania, with Pittsburgh as county seat, had 1,062 manufacturing 

establishments in 2014, more than any other coal county; there were 1,416 establishments in the 

county in 2000. Twenty-nine counties had more than 100 establishments in 2014, in principle offering 

the potential for job opportunities for coal industry workers seeking alternative employment.

However, these opportunities are likely to arise primarily from quits and terminations rather than 

from firm expansions and new firm locations, given the long-term trend in manufacturing employment 

across the nation and the Region.

Table 5 provides a snapshot of the population and its age distribution for the same geographies as 

presented above for 2000 and 2015. These population measures are especially important since they 

affect the labor force and its age composition. Moreover, net population movements provide a signal 

regarding the health of local economies and labor markets. Of the geographies shown, population 

growth was strongest for the United States between 2000 and 2015 (14.2 percent), followed by the 

Appalachian Region (7.6 percent), and states that are either partially or wholly included in Appalachia

(11.1 percent). Appalachian coal counties saw net population outflows of -0.4 percent, a reflection of 

poor economic prospects for workers.

Appalachian

 Counties Entire
 State

Appalachian

 Counties Entire State

Appalachian

 Counties Entire State

Appalachian

 Counties Entire State

Appalachian

 Counties Entire State

Appalachian

 Counties Entire State

Alabama 63.3 99.8 62.1 97.3 -2.0 -2.4 3.7 5.3 2.8 4.2 -22.8 -20.6

Georgia 52.1 200.4 63.7 220.0 22.2 9.8 3.3 8.7 3.0 7.4 -8.3 -1.2

Kentucky 21.1 89.9 20.1 91.0 -4.8 1.3 0.9 4.2 0.8 3.8 -13.0 -0.8

Maryland 6.1 128.4 5.9 136.1 -2.6 6.0 0.3 3.9 0.2 3.0 -19.9 -1.9

Mississippi 12.7 59.7 12.1 58.3 -4.9 -2.5 1.0 2.8 0.8 2.2 -21.7 -1.9

New York 22.2 492.0 21.7 536.3 -2.0 9.0 1.3 22.1 1.1 16.1 -16.3 -2.3

North Carolina 38.0 203.9 38.1 219.4 0.1 7.6 2.2 11.0 1.7 8.7 -21.7 -1.6

Ohio 42.4 270.5 38.0 249.9 -10.4 -7.6 2.7 17.7 2.3 14.2 -15.6 -1.6

Pennsyvlania 138.8 294.7 134.6 297.7 -3.0 1.0 8.0 16.8 6.6 13.7 -17.0 -1.4

South Carolina 26.3 97.1 26.5 101.9 0.6 4.9 1.6 4.4 1.3 3.8 -17.1 -1.1

Tennessee 56.1 130.8 54.7 131.0 -2.5 0.2 3.4 7.1 2.8 5.6 -19.9 -1.6

Virginia 16.4 175.5 15.0 195.1 -8.6 11.2 0.8 5.8 0.7 5.0 -14.8 -1.1

West Virginia 41.0 41.0 37.1 37.1 -9.5 -9.5 1.5 1.5 1.2 1.2 -17.1 -1.3

United States

Appalachian States 

Appalachian Region

Appalachian Coal-Employment Counties

Source: U.S. Census Bureau County Business Patterns

Establishments (thousands)

All Industries Manufacturing

2000 2014 Growth (%) 2000 2014 Growth (%)

-20.3

7,070 7,563 7.0 354 293 -17.5

2,284 2,371 3.8 111 89

537 530 -1.3 31 25 -17.3

219 207 -5.7 11 9 -18.9
17

Table 5: Population Counts and Age Distributions for States and Other Geographies in Appalachia

The average population size of coal-employment counties was 72,569 in 2015, with 21 of these 

counties having populations larger than 100,000. Seven coal-employment counties had populations less 

than 10,000 people. For these latter communities, alternative job prospects can be expected to be 

especially bleak. Only 50 of the 129 counties had population growth over the 2000 to 2015 window

while 11 counties suffered population losses in excess of 10 percent. These symptoms of weak labor 

markets will in turn further constrain the size and diversity of future labor markets in the Region.

Of particular interest is the 18 to 64 age group since individuals in this cohort tend to have the 

strongest attachment to the labor force. The Appalachian states generally have older populations than 

the nation as a whole, with only Georgia and Mississippi having a lower median age than the nation

overall. The median age in the heavy coal-producing states of Pennsylvania and West Virginia stood at 

40.7 and 42.1 in 2015, compared to 37.8 for the nation. The older median population in the 

Appalachian states generally translates into a smaller share of the adult population in the traditional 

18 to 64 working age group. This limits labor force development by constraining both the number of 

available workers and occupational diversity. Moreover, older workers may find it relatively more 

difficult to find new employment opportunities. Mississippi stands out with the smallest share of the 

population in the 18 to 64 cohort at 61.0 percent in 2015, followed by West Virginia at 61.2 percent.

All states experienced an aging of the population between 2000 and 2015.

The population in the Appalachian Region is less mobile than the national average, which may 

hamper the movement of workers to new employment alternatives outside their existing places of 

residence. Workers with the best options may find opportunities elsewhere while those without 

strong, marketable labor market skills may be left behind in stagnant or contracting regional 

economies. Based on 2010-2014 American Community Survey data, 85.0 percent of the United States

2000 2015 Growth (%) 2000 2015 2000 2015 2000 2015

Alabama 4,447,100 4,858,979 9.3 61.7 61.6 13.0 15.7 35.8 38.7

Georgia 8,186,453 10,214,860 24.8 63.9 62.7 9.6 12.8 33.4 36.3

Kentucky 4,041,769 4,425,092 9.5 62.9 61.9 12.5 15.2 35.9 38.7

Maryland 5,296,486 6,006,401 13.4 63.1 63.4 11.3 14.1 36.0 38.4

Mississippi 2,844,658 2,992,333 5.2 60.7 61.0 12.1 14.7 33.8 36.9

New York 18,976,457 19,795,791 4.3 62.4 63.8 12.9 15.0 35.9 38.3

North Carolina 8,049,313 10,042,802 24.8 63.6 62.1 12.0 15.1 35.3 38.4

Ohio 11,353,140 11,613,423 2.3 61.3 61.5 13.3 15.9 36.2 39.3

Pennsylvania 12,281,054 12,802,503 4.2 60.6 62.0 15.6 17.0 38.0 40.7

South Carolina 4,012,012 4,896,146 22.0 62.7 61.5 12.1 16.2 35.4 39.0

Tennessee 5,689,283 6,600,299 16.0 63.1 61.9 12.4 15.4 35.9 38.6

Virginia 7,078,515 8,382,993 18.4 64.2 63.5 11.2 14.2 35.7 37.8

West Virginia 1,808,344 1,844,128 2.0 62.4 61.2 15.3 18.2 38.9 42.1

United States 281,421,906 321,418,820 14.2 61.9 62.2 12.4 14.9 35.3 37.8

Appalachian States 94,064,584 104,475,750 11.1 62.4 62.5 12.7 15.2 — —

Appalachian Counties 23,638,289 25,417,532 8 61.9 61.9 14.4 16.3 — —

Appalachian Coal-Employment Counties 9,397,124 9,361,350 -0.4 61.2 62.3 16.0 17.2 — —

Source: U.S. Census Bureau Decennial Census and 2015 Population Estimates

Population Shares 18-64 Shares 65 and older Median Age
18

population over the age of one did not move from their place of residence. For the population in the 

Appalachian Region, the comparable figure was 86.8 percent. West Virginia and the Appalachian

portion of Kentucky had rates of 88.3 percent and 86.9 percent, respectively.4

Educational attainment is arguably the most important ingredient to regional development and 

individual prosperity. Unfortunately, educational attainment in the Appalachian Region lags the 

national average, as summarized in Table 6. These differences in attainment will constrain labor 

market and economic development opportunities in the Region and limit the availability and creation 

of high-quality jobs for workers who are displaced from the coal industry ecosystem. Employers who 

require well-educated workers may simply choose to locate production activities in more attractive 

regions. In 2000, just 17.6 percent of adults in Appalachian counties held a bachelors’ degree 

compared to 24.4 percent for the nation; coal-employment communities trailed Appalachian counties 

with a 17.5 percent college degree attainment rate. The Appalachian Region saw marked 

improvement by 2015, with the share of adults with a bachelor’s degree rising to 22.6 percent, a gain 

of 5.0 percentage points. However, the United States showed stronger progress with a 5.4 percentage 

point gain that pushed attainment to 29.8 percent of the adult population. This translates into a 

widening disparity between the Appalachian Region and the United States, from 6.8 percentage points 

in 2000 to 7.2 percentage points in 2012. Coal-employment communities had a slightly better outcome 

than the Appalachian Region in 2015, with 22.7 percent of adults holding a college degree. One 

implication of the time trends shown in Table 6 is that the Appalachian Region has become a relatively 

less attractive place to create jobs based on the educational attainment of the workforce.

 4 Pollard and Jacobsen (2016). 
19

Table 6: Educational Attainment of the Population 25 Years and Older for States and Other 

Geographies in Appalachia

Another important facet of the human capital stock that has implications for economic 

development is the health status of the population. Like education, employers will prefer to locate in 

regions characterized by a healthy population since it is a barometer of workforce quality and 

potentially quality of life. In general, healthier individuals have greater attachment to the labor 

market than individuals in poor health. Moreover, large shares of the adult population with poor 

health status constrain labor availability and diversity. Finally, poor health status creates pressures on 

the health care delivery system which is strained throughout much of rural America and Appalachian 

coal country. Public health expenditures can crowd out other uses of public sector resources that 

might help foster economic development. 

Table 7 presents seven different measures of health status and reveals the relatively poor 

standing of the states that are represented within the Appalachian Region. West Virginia has the 

highest incidence of coronary heart disease, depression, heart attack, kidney disease, skin cancer and 

stroke among the Appalachian states. Kentucky does worse than the nation in all categories except 

depression. 

2000 2015 2000 2015 2000 2015 2000 2015 2000 2015 2000 2015

Alabama 2,887,400 3,239,351 24.7 15.7 30.4 31.0 20.5 22.0 5.4 7.8 19.0 23.5

Georgia 5,185,965 6,500,205 21.4 14.6 28.7 31.0 20.4 21.0 5.2 7.2 24.3 28.8

Kentucky 2,646,397 2,955,216 25.9 15.8 33.6 28.4 18.5 20.8 4.9 7.5 17.1 22.3

Maryland 3,495,595 4,018,459 16.2 10.6 26.7 33.6 20.3 19.5 5.3 6.4 31.4 37.9

Mississippi 1,757,517 1,940,365 27.1 17.7 29.4 25.5 20.9 22.8 5.7 8.6 16.9 20.7

New York 12,542,536 13,435,795 20.9 14.4 27.8 30.3 16.8 16.2 7.2 8.5 27.4 34.2

North Carolina 5,282,994 6,582,301 21.9 14.2 28.4 26.7 20.5 21.8 6.8 9.0 22.5 28.4

Ohio 7,411,740 7,817,508 17.0 10.9 36.1 26.7 19.9 20.7 5.9 8.2 21.1 26.1

Pennsylvania 8,266,284 8,814,112 18.1 10.8 38.1 34.1 15.5 16.3 5.9 7.9 22.4 28.6

South Carolina 2,596,010 3,210,007 23.7 14.4 30.0 36.4 19.3 21.0 6.7 8.9 20.4 25.8

Tennessee 3,744,928 4,380,036 24.1 14.5 31.6 29.8 20.0 21.0 4.7 6.6 19.6 24.9

Virginia 4,666,574 5,566,373 18.5 11.7 26.0 33.0 20.4 19.9 5.6 7.3 29.5 36.3

West Virginia 1,233,581 1,298,118 24.8 15.0 39.4 24.8 16.6 18.5 4.3 6.6 14.8 19.2

United States 182,211,639 211,462,522 19.6 13.3 28.6 40.7 21.0 21.1 6.3 8.1 24.4 29.8

Appalachian States 61,717,521 69,757,846 20.7 13.3 31.1 30.1 18.7 19.4 6.0 7.9 23.5 29.3

Appalachian Region 15,799,129 17,406,203 23.2 14.5 35.5 35.5 17.6 19.3 5.7 8.2 17.6 22.6

Appalachian Coal-Employment Counties 6,373,871 6,533,244 21.6 12.9 38.1 38.3 16.3 17.9 5.6 8.2 17.5 22.8

Source: U.S. Census Bureau Decennial Census and 2015 ACS 5-year Estimates

Population 25 Years and Older

Percent Less than 

High School Diploma 

(or Equivalent)

Percent High School 

Diploma 

(or Equivalent)

Percent Some College 

(No Degree)

Percent Associate's 

Degree

Percent Bachelor's 

Degree or Higher
20

Table 7: State-Level Disease Prevalence (Crude Prevalence, Percent)

Other state-level evidence paints a similar picture. For example, the incidence of disability is 

relatively high in the Region, with 15.6 percent of the Appalachian population being disabled 

compared to 12.1 percent for the United States. For the 18 to 64 age group, the incidence of disability 

in the Appalachian Region was 13.6 percent while the United States’ rate was 10.0 percent. In West 

Virginia, 197,747 individuals in the 18-64 population group were disabled in the 2010-2014 window.

This represented 17.1 percent of all individuals aged 18 to 64.5

Table 8 summarizes six county-level health metrics for coal-employment counties, indicating the 

number and share of the 129 counties, by state, that have an incidence of the specific health disorder 

that exceeds the state average. Coal counties in Alabama and Pennsylvania do not appear to have 

pervasive problems relative to other counties in their states. West Virginia’s coal counties are not 

substantially worse than other counties across the state, though the number of individuals with a body 

mass index (BMI) greater than 30 and adults with no leisure-time physical activity are relatively high.

On the other hand, health status is especially poor for Kentucky, Maryland, Mississippi, Ohio, 

Tennessee, and Virginia. For most of these states and most of the indexes, coal communities perform 

poorly compared to the rest of their respective states and to coal communities across the country.

 5 Data based on the 2010-2014 American Community Survey drawn from Tables 2.1 and 9.1 of Pollard and 

Jacobsen (2016). 

Coronary Heart 

Disease Depression Diabetes

Heart 

Attack

Kidney

 Disease

Skin

 Cancer Stroke

Alabama 5.2 22.1 13.5 5.2 2.8 8.2 4.7

Georgia 4.2 18.3 11.3 4.6 3.0 6.3 3.8

Kentucky 6.0 18.8 13.4 6.7 3.0 7.6 4.3

Maryland 3.8 16.3 10.3 3.7 2.3 5.0 2.8

Mississippi 4.9 18.2 14.7 5.6 2.9 6.1 4.5

New York 4.7 18.8 10.7 4.3 2.8 7.1 3.7

North Carolina 3.8 15.7 9.8 3.9 2.1 4.6 2.4

Ohio 4.2 19.6 11.0 4.9 3.2 6.1 3.5

Pennsylvania 4.7 18.5 10.4 5.0 2.7 5.8 3.6

South Carolina 4.3 19.5 11.8 4.7 2.9 7.0 3.9

Tennessee 4.9 21.2 12.7 6.0 3.5 7.5 4.3

Virginia 3.4 15.7 10.4 3.5 2.3 5.7 3.1

West Virginia 7.4 23.1 14.5 7.0 3.6 7.7 4.8

United States 3.9 19.0 9.9 4.2 2.7 6.1 3.0

Source: U.S. Centers for Disease Control
21

Table 8: 2017 County Health Rankings for Coal-Employment Counties in the Appalachian Region

The discussion above documents the relatively weaker standing of labor markets in the 

Appalachian Region compared to the overall national economy. These patterns translate into poorer 

economic outcomes using other measures of economic wellbeing. Table 9 provides per capita income 

data for 2000 and 2015 in 2009 dollars. Inflation-adjusted per capita income across Appalachian

counties averaged $42,272 in 2015 compared to per capita income of $48,131 for the nation as a 

whole. Coal-employment counties in the Region had an average per capita income of $45,268, 

benefiting from the relatively high-wage jobs tied to the coal industry. Nonetheless, 12 Appalachian

coal counties had inflation-adjusted per capita incomes below $30,000 in 2015, the poorest being 

Elliott County, Kentucky ($23,817). Inflation-adjusted per capita income declined in 12 coal counties 

between 2000 and 2015.

Area

Percentage

of Adults

Reporting

Fair or

Poor

Health

Average

Number of Physically 

Unhealthy

Days Reported in Past 

30 Days

Average

Number of Mentally 

Unhealthy

Days Reported in 

Past 30 Days

Percentage

of Adults

Who Are

Current

Smokers

Percentage

of Adults 

that Report a 

BMI ≥ 30

Percentage of 

Adults

Aged 20 & Over 

Reporting

No Leisure-Time

Physical Activity

Alabama 21.2 4.5 4.4 21.4 34.0 27.7

Number of Counties 3 6 8 0 4 8

Percentage 25.0 50.0 66.7 0.0 33.3 66.7

Kentucky 20.9 4.7 4.4 25.9 32.9 27.8

Number of Counties 23 23 19 13 24 24

Percentage 95.8 95.8 79.2 54.2 100.0 100.0

Maryland 13.3 3.5 3.4 15.1 28.9 21.5

Number of Counties 2 2 2 2 2 2

Percentage 100.0 100.0 100.0 100.0 100.0 100.0

Mississippi 22.2 4.4 4.6 22.5 35.2 31.9

Number of Counties 1 1 0 0 0 1

Percentage 100.0 100.0 0.0 0.0 0.0 100.0

Ohio 15.3 3.7 4.0 21.6 31.4 25.3

Number of Counties 18 17 16 4 15 17

Percentage 94.7 89.5 84.2 21.1 78.9 89.5

Pennsylvania 15.3 3.5 3.9 18.1 29.3 23.1

Number of Counties 3 17 7 10 22 26

Percentage 10.0 56.7 23.3 33.3 73.3 86.7

Tennessee 19.9 4.8 4.4 21.9 31.8 29.8

Number of Counties 5 6 7 5 3 6

Percentage 71.4 85.7 100.0 71.4 42.9 85.7

Virginia 14.6 3.2 3.3 16.5 27.2 21.4

Number of Counties 7 7 7 7 6 7

Percentage 100.0 100.0 100.0 100.0 85.7 100.0

West Virginia 23.7 5.1 4.8 25.7 34.6 29.2

Number of Counties 11 13 16 7 20 19

Percentage 39.3 46.4 57.1 25.0 71.4 67.9

UNITED STATES 17.0 3.9 3.8 17.9 31.0 26.0

Number of Counties 89 90 116 109 104 107

Percentage 68.5 69.2 89.2 83.8 80.0 82.3

Source: Robert Wood Johnson Foundation and the University of Wisconsin Population Health Institute. County Health Rankings & Roadmaps Program, County Health 

Rankings, 2017, <countyhealthrankings.org> 

Notes: Coal counties are those counties with coal mining employment in 2010 as reported in the annual employment and production data file from the U.S. Mine Safety 

and Health Administration (MSHA), <https://arlweb.msha.gov/OpenGovernmentData/DataSets/ MinesProdYearly.zip>.
22

Table 9: Per Capita Personal Income (2009 Inflation-Adjusted Dollars) for State and Other 

Geographies in Appalachia

Poverty rates are also higher in the Appalachian Region, as reported in Table 10. The Appalachian 

Region had a poverty rate of 17.1 percent in 2015 compared to a national figure of 15.5 percent.

Despite relatively strong per capita incomes in mining-employment counties, poverty rates in these 

counties (averaging 17.1 percent) nonetheless exceed the regional average. Thirteen of the counties 

in the Appalachian Region with coal employment had poverty rates equal to or above 30 percent in 

2015. The highest rate was in McCreary County, Kentucky (41.0 percent). Poverty rates increased in 88 

of the 129 counties between 2000 and 2015.

2000 2015

Growth 

Rate 

(%) 2000 2015

Growth 

Rate 

(%)

Alabama $ 20,938 $ 43,066 4.9 20,166 $ $ 41,655 5.0

Georgia 22,442 39,915 3.9 23,892 44,148 4.2

Kentucky 15,530 34,274 5.4 20,632 42,266 4.9

Maryland 19,682 44,559 5.6 29,500 61,307 5.0

Mississippi 16,501 35,182 5.2 17,902 38,085 5.2

New York 20,078 42,192 5.1 29,864 64,262 5.2

North Carolina 21,206 40,238 4.4 22,756 44,645 4.6

Ohio 19,060 40,358 5.1 23,700 47,719 4.8

Pennsylvania 22,356 48,331 5.3 25,256 54,486 5.3

South Carolina 21,629 42,687 4.6 20,717 41,953 4.8

Tennessee 20,265 41,311 4.9 22,574 46,106 4.9

Virginia 17,812 38,071 5.2 23,196 48,169 5.0

West Virginia 18,522 40,262 5.3 18,522 40,262 5.3

United States -- 30,585 48,131 3.1

Appalachian States -- 24,435 50,261 4.9

Appalachian Counties 20,525 42,272 4.9 --

Appalachian Coal-Employment Counties 21,080 45,268 5.2 --

Source: Bureau of Economic Analysis

Appalachian Portions Entire State
23

Table 10: Regional Poverty Rates (Percent) for States and Other Geographies in Appalachia

2. Coal Industry Labor Force and Employment

2.1. Coal Mining Employment

Monthly data maintained by the Federal Reserve Bank of St. Louis show, first, that coal production 

does not follow seasonal cycles and, second, that national coal mining employment has been in longterm decline with only occasional upswings. Employment declined from a monthly average of 173,700

workers in 1985 to 54,700 in 2016. A more recent snapshot of coal employment trends is shown in 

Figure 2 using Mine Safety and Health Administration (MSHA) data. National employment trended 

upward over the period shown, peaking at 91,611 jobs in 2011; by 2015, employment had slipped to 

just 65,971 jobs. Coal employment in the Appalachian Region also peaked in 2011 with a job count of 

60,267. The decline in coal employment has been particularly steep in Appalachia since 2011, with 

employment in 2015 totaling only 38,193, reflecting a loss of 22,074 jobs since the 2011 peak. NonAppalachian coal-producing regions have fared better than the Appalachian Region, with 2015 

employment levels (27,778) exceeding 2000 levels (24,211).

2000 2015

Alabama 16.1 18.8

Georgia 13.0 18.4

Kentucky 15.8 18.9

Maryland 8.5 10.0

Mississippi 19.9 22.5

New York 14.6 15.7

North Carolina 12.3 17.4

Ohio 10.6 15.8

Pennsylvania 11.0 13.5

South Carolina 14.1 17.9

Tennessee 13.5 17.6

Virginia 9.6 11.5

West Virginia 17.9 18.0

United States 12.4 15.5

Appalachian States 12.8 15.9

Appalachian Region 13.6 17.1

Appalachian Coal-Employment Counties 14.6 16.7

Source: U.S. Census Bureau Decennial Census and 2015 ACS 5-Year Estimates
24

Figure 2: Coal Employment Trends Since 2000

Source: Mine Safety and Health Administration and U.S. Energy Information Administration

Table 11 provides detail on coal employment and coal production for the Appalachian states for 

2000 and 2015. Coal production for all the Appalachian states is down 46.9 percent over this period 

compared to just a 16.5 percent contraction for the nation. Appalachian coal production accounted 

for 28.3 percent of all United States coal production in 2000 but fell to 20.1 percent of total 

production in 2015. Coal employment has contracted as well, but the declines have not been as steep 

as the declines in output. The decline for Appalachian states was 19.3 percent, compared to a 7.8 

percent decline for the nation. For the Appalachian Region, this translates into a loss of 9,118 coal 

jobs. This is more than the loss in employment for the national coal industry, indicating employment 

growth in other coal-producing regions outside of the Appalachian Region.

0

10

20

30

40

50

60

70

80

90

100

Thousands

US ARC Non-ARC
25

Table 11: Appalachian States and Regional Coal Employment and Coal Production, 2000 and 2015

Within the Appalachian Region, there is significant variation in the performance of the various 

coal-producing states. Kentucky experienced the largest percentage setback, with coal employment 

falling 51.2 percent. Kentucky also experienced the largest setback in the number of jobs lost (6,214).

West Virginia and Mississippi saw net employment gains between 2000 and 2015. For West Virginia, the 

gain was 7.1 percent. Coal employment in Mississippi jumped 205.6 percent, building from a small 

base of only 108 jobs in 2000. Coal production was down in all Appalachian states other than 

Mississippi between 2000 and 2015. The production setback in Kentucky was the worst in the Region, 

with coal output falling 73.6 percent.

Table 12 provides coal mining employment data, along with data on related support employment, 

provided by the National Mining Association (NMA). A comparison of Tables 11 and 12 shows significant 

discrepancies in the number of coal mining employees reported by MSHA versus the NMA. We place 

greater confidence in the MSHA and Energy Information Agency EIA numbers because the NMA’s 

implied job multipliers are uncommonly large, particularly in the case of states with small coal mining 

employment. A study conducted for the coal industry in southwestern Virginia, encompassing only the 

Appalachian part of the state, estimated that each coal mining job supports 1.27 jobs in other 

2000 2015 Growth (%) 2000 2015 Growth (%)

Alabama 3,365 3,228 -4.1 19.5 13.2 -32.3

Georgia — — — — — —

Kentucky 12,130 5,916 -51.2 105.9 27.9 -73.6

Maryland 470 362 -23 4.5 1.9 -57.9

Mississippi 108 330 205.6 0.9 3.1 248.5

N. Carolina — — — — — —

New York — — — — — —

Ohio 2,681 2,328 -13.2 21.6 17 -21.2

Pennsylvania 7,953 6,477 -18.6 70.5 47.9 -32.1

S. Carolina — — — — — —

Tennessee 439 287 -34.6 2.7 0.9 -66.7

Virginia 5,032 3,065 -39.1 33.1 14.1 -57.3

W. Virginia 15,133 16,200 7.1 164.7 99 -39.9

Appalachian States 47,311 38,193 -19.3 423.4 225 -46.9

United States 71,522 65,971 -7.8 1,073.60 896.9 -16.5

Source: NMA 2016, Map: Economic Impact of Mining (http://nma.org/map/, downloaded March 

14, 2017)

1

 We rounded the numbers to the closest full percentage point

Note: The number in this table are for the states. The MMA does not report them by county and we 

can, therefore, not extract the Appalachian portion of each state.

Employment Production (million tons)
26

industries and each dollar in wage earnings generates $0.64 in additional earnings (Evans, 2013). 

Based on other industry studies, these are more realistic multipliers.

Table 12: State Coal Mining and Related Transportation and Support Employment, 2015

Not all employment associated with mining is located on or near the coal fields. Some engineering 

and many management functions are located at the coal company’s headquarters or back offices, 

which are often in a large city where alternative employment opportunities are more abundant. For 

example, the two largest United States coal companies, Peabody and Arch Coal, which together 

account for one-third of total national coal production, are headquartered in St. Louis. Additionally, 

related activities such as the production of heavy equipment, specialized trucks and vehicles, etc.,

are usually located away from coal field regions, as well. Therefore, the impact of changes in coal 

production and coal industry employment is also felt outside the coal fields. The coal fields 

themselves will see direct production and employment losses and this will give rise to ripples that will 

spread broadly across regions and occupations (for empirical evidence of the ripple effect, see 

Gebremariam, Gebremedhin, and Schaeffer, 2011).

Table 13 shows coal employment and production data for Appalachian coal-employment counties

with active coal employment in 2010 for the years 2000, 2010, and 2015, while Figure 3 shows changes 

in coal employment for counties in the Region that had coal employment in 2010. Within the 

Coal Mining Transportation

Coal Mining 

Support 

Activities

Alabama 4,332 2,197 65 1 11,015

Georgia 76 0 0 0 3,753

Kentucky 14,524 4,075 1,229 7 26,077

Maryland 2,008 126 251 12 8,443

Mississippi 368 307 0 0 3,471

New York 22 0 0 0 9,026

North Carolina 104 31 0 0 8,154

Ohio 4,393 1,421 392 7 17,645

Pennsylvania 11,727 7,127 494 3 40,193

South Carolina 55 0 0 0 4,048

Tennessee 646 69 29 4 3,345

Virginia 5,316 2,543 274 3 16,626

West Virginia 22,750 4,848 908 3 27,667

Total 66,321 22,744 3,642 4 179,463

Source: NMA 2016, Map: Economic Impact of Mining (http://nma.org/map/, downloaded March 14, 2017); State 

level data only

1

 Rounded to the nearest percentage point.

Direct Employment

State

Indirect and 

Induced 

Employment

Coal Mining 

Support Activities 

as Percent of Direct 

Employment1
27

Appalachian Region, 126 of the 129 counties reported coal employment in 2000 and 111 counties 

reported coal employment in 2015, based on data from MSHA. Seventy-eight counties experienced 

coal employment losses between 2000 and 2015, including 19 counties that lost all coal employment.

The largest coal employment base in the Region in 2000 was Pike County, Kentucky with 3,642 jobs; 

by 2015, employment had fallen nearly 57 percent to 1,571 jobs in the county. The highest level of 

reported coal employment in 2015 was in Greene County, Pennsylvania, with 2,476 jobs, an increase 

of 22.8 percent since 2000. In 2015, there were a number of counties with relatively large shares of 

local employment directly tied to coal production. Three counties relied on coal for more than 20 

percent of their employment base: Dickenson County, Virginia (23.4 percent); Boone County, West 

Virginia (28.4 percent); and Wyoming, West Virginia (22.4 percent). Dickenson County is the only one 

of the three to see growth in coal employment between 2010 and 2015. Thirteen additional counties 

had coal employment shares between 10 and 20 percent of the local job base in 2015. Of this set of 

counties, only three experienced employment growth since 2010: Harrison County, Ohio; Greene 

County, Pennsylvania; and Marshall County, West Virginia. The lack of diversification places these

communities at heightened risk since there are so few alternative employment opportunities outside 

the coal sector.

The coal production data tell an equally devastating story. For the Appalachian Region as a whole, 

production was down 46.9 percent between 2000 and 2015, and the Region experienced a 33.8 

percent contraction over the shorter 2010 to 2015 window. Only 21 counties in the Region had coal 

production output growth between 2010 and 2015.
28

Table 13: Coal Employment and Coal Production by Appalachian County for Counties with Coal 

Employment in 2010

State County 2000 2010 2015

Growth

2000-2015

(%)

Growth

2010-2015

(%)

2015 Total 

Covered 

Employment

 % Total 

Covered 

Employment

 2015 2000 2010 2015

Growth

2000-2015

(%)

Growth

2010-2015

(%)

AL Bibb 4 13 6 50.0 -53.8 4,075 0.1 65,510 127,667 62,598 -4.4 -51.0

AL Blount 0 45 0 — -100.0 8,066 0.0 0 148,994 0 — -100.0

AL Cullman 9 17 0 -100.0 -100.0 27,683 0.0 17,006 69,035 0 -100.0 -100.0

AL Fayette 334 372 0 -100.0 -100.0 3,916 0.0 2,603,898 3,037,170 0 -100.0 -100.0

AL Franklin 0 23 28 — 21.7 10,248 0.3 0 109,530 146,955 — 34.2

AL Jackson 6 17 5 -16.7 -70.6 16,286 0.0 4,719 33,623 3,939 -16.5 -88.3

AL Jefferson 1,053 1,403 1,553 47.5 10.7 338,154 0.5 5,235,850 5,834,058 6,570,101 25.5 12.6

AL Marion 16 18 0 -100.0 -100.0 9,606 0.0 80,298 79,174 0 -100.0 -100.0

AL Shelby 20 140 137 585.0 -2.1 83,420 0.2 24,500 323,000 276,798 1,029.8 -14.3

AL Tuscaloosa 945 1,144 668 -29.3 -41.6 91,535 0.7 4,887,332 5,538,415 2,518,567 -48.5 -54.5

AL Walker 954 1,123 764 -19.9 -32.0 18,293 4.2 6,273,641 4,709,373 3,321,332 -47.1 -29.5

AL Winston 24 103 67 179.2 -35.0 7,255 0.9 279,760 685,481 292,252 4.5 -57.4

KY Bell 614 760 371 -39.6 -51.2 8,465 4.4 3,499,158 2,185,176 1,476,947 -57.8 -32.4

KY Boyd 153 71 44 -71.2 -38.0 25,002 0.2 0 0 0 — —

KY Breathitt 108 173 48 -55.6 -72.3 3,149 1.5 1,035,156 953,143 251,064 -75.7 -73.7

KY Clay 19 129 17 -10.5 -86.8 3,981 0.4 9,224 488,874 0 -100.0 -100.0

KY Elliott 0 1 0 — -100.0 906 0.0 0 0 0 — —

KY Estill 32 1 35 9.4 3,400.0 2,341 1.5 42,073 0 0 -100.0 —

KY Floyd 525 303 481 -8.4 58.7 10,977 4.4 2,952,340 1,688,117 2,393,667 -18.9 41.8

KY Harlan 1,426 2,265 860 -39.7 -62.0 6,227 13.8 10,113,302 10,467,335 3,793,465 -62.5 -63.8

KY Jackson 3 5 0 -100.0 -100.0 1,736 0.0 22,355 27,462 0 -100.0 -100.0

KY Johnson 78 63 51 -34.6 -19.0 5,579 0.9 562,368 156,849 122,908 -78.1 -21.6

KY Knott 1,364 1,030 334 -75.5 -67.6 2,432 13.7 13,757,716 5,408,479 2,416,596 -82.4 -55.3

KY Knox 122 138 137 12.3 -0.7 7,637 1.8 389,061 640,539 392,630 0.9 -38.7

KY Laurel 14 3 8 -42.9 166.7 25,648 0.0 29,300 0 6,637 -77.3 —

KY Lawrence 81 38 73 -9.9 92.1 3,205 2.3 576,904 158,632 373,375 -35.3 135.4

KY Leslie 608 748 238 -60.9 -68.2 1,685 14.1 6,719,920 3,667,325 1,361,768 -79.7 -62.9

KY Letcher 1,249 894 182 -85.4 -79.6 4,470 4.1 9,819,215 4,320,891 549,959 -94.4 -87.3

KY McCreary 0 7 4 — -42.9 2,620 0.2 0 0 0 — —

KY Magoffin 0 297 51 — -82.8 1,884 2.7 0 2,726,080 258,011 — -90.5

KY Martin 863 985 325 -62.3 -67.0 2,569 12.7 10,451,298 5,543,738 1,199,069 -88.5 -78.4

KY Owsley 0 5 3 — -40.0 665 0.5 0 4,363 0 — -100.0

KY Perry 1,071 1,887 900 -16.0 -52.3 12,008 7.5 11,096,869 13,105,447 6,291,210 -43.3 -52.0

KY Pike 3,642 3,076 1,571 -56.9 -48.9 21,488 7.3 34,612,427 15,906,793 6,610,826 -80.9 -58.4

KY Pulaski 36 11 0 -100.0 -100.0 25,502 0.0 0 0 0 — —

KY Whitley 114 153 173 51.8 13.1 11,620 1.5 187,628 460,729 394,235 110.1 -14.4

MD Allegany 149 224 179 20.1 -20.1 28,969 0.6 1,261,709 1,702,652 1,128,963 -10.5 -33.7

MD Garrett 321 206 183 -43.0 -11.2 11,789 1.6 3,284,533 812,814 785,728 -76.1 -3.3

MS Choctaw 108 232 218 101.9 -6.0 2,123 10.3 901,951 4,003,505 2,976,276 230.0 -25.7

OH Athens 53 3 0 -100.0 -100.0 20,634 0.0 543,824 26,725 0 -100.0 -100.0

OH Belmont 537 747 676 25.9 -9.5 23,615 2.9 5,517,742 7,559,272 5,401,211 -2.1 -28.5

OH Carroll 11 41 54 390.9 31.7 6,823 0.8 45,051 135,948 185,852 312.5 36.7

OH Columbiana 91 42 0 -100.0 -100.0 30,659 0.0 498,237 91,628 0 -100.0 -100.0

OH Coshocton 45 90 32 -28.9 -64.4 10,998 0.3 57,531 294,832 0 -100.0 -100.0

OH Gallia 22 4 0 -100.0 -100.0 10,904 0.0 202,762 0 0 -100.0 —

OH Guernsey 153 39 11 -92.8 -71.8 15,610 0.1 1,070,817 236,939 17,391 -98.4 -92.7

OH Harrison 311 349 388 24.8 11.2 3,875 10.0 3,014,702 3,915,324 2,738,850 -9.2 -30.0

OH Jackson 153 66 15 -90.2 -77.3 10,323 0.1 1,424,921 370,004 155,115 -89.1 -58.1

OH Jefferson 81 167 94 16.0 -43.7 20,824 0.5 674,171 1,537,382 393,566 -41.6 -74.4

OH Mahoning 4 7 3 -25.0 -57.1 97,706 0.0 7,515 3,252 0 -100.0 -100.0

OH Meigs 761 95 2 -99.7 -97.9 3,557 0.1 4,317,564 735,167 0 -100.0 -100.0

OH Monroe 4 486 481 11,925.0 -1.0 2,886 16.7 0 6,214,246 5,248,702 — -15.5

OH Muskingum 54 20 0 -100.0 -100.0 32,130 0.0 684,698 6,651 0 -100.0 -100.0

OH Noble 39 73 44 12.8 -39.7 3,161 1.4 369,513 774,608 430,225 16.4 -44.5

OH Perry 70 268 329 370.0 22.8 5,548 5.9 971,046 2,774,670 1,355,758 39.6 -51.1

OH Tuscarawas 108 211 153 41.7 -27.5 36,608 0.4 793,044 1,841,499 890,009 12.2 -51.7

OH Vinton 167 115 46 -72.5 -60.0 2,241 2.1 1,198,860 707,864 163,595 -86.4 -76.9

OH Washington 0 5 0 — -100.0 25,154 0.0 0 0 0 — —

PA Allegheny 41 36 14 -65.9 -61.1 685,508 0.0 100 224,542 5,440 5,340.0 -97.6

PA Armstrong 408 381 270 -33.8 -29.1 17,132 1.6 4,286,113 3,400,420 1,275,449 -70.2 -62.5

PA Beaver 65 20 18 -72.3 -10.0 52,103 0.0 591,231 200,135 309,110 -47.7 54.5

PA Bedford 2 6 14 600.0 133.3 15,330 0.1 2,219 37,939 119,238 5,273.5 214.3

PA Blair 3 15 8 166.7 -46.7 58,506 0.0 28,643 718 17,050 -40.5 2,274.7

PA Butler 44 83 57 29.5 -31.3 85,050 0.1 481,630 478,159 448,549 -6.9 -6.2

Coal Employment Coal Production
29

Table 13: Coal Employment and Coal Production by Appalachian County for Counties with Coal 

Employment in 2010, (continued)

State County 2000 2010 2015

Growth

2000-2015

(%)

Growth

2010-2015

(%)

2015 Total 

Covered 

Employment

 % Total 

Covered 

Employment

 2015 2000 2010 2015

Growth

2000-2015

(%)

Growth

2010-2015

(%)

PA Cambria 253 278 198 -21.7 -28.8 53,349 0.4 1,460,543 1,653,646 859,354 -41.2 -48.0

PA Cameron 0 9 0 — -100.0 1,985 0.0 0 39,412 0 — -100.0

PA Carbon 19 19 15 -21.1 -21.1 16,937 0.1 8,084 0 31,170 285.6 —

PA Centre 0 12 0 — -100.0 67,563 0.0 0 98,436 0 — -100.0

PA Clarion 97 76 3 -96.9 -96.1 13,523 0.0 719,522 273,059 10,102 -98.6 -96.3

PA Clearfield 578 666 404 -30.1 -39.3 29,709 1.4 3,271,466 3,449,136 2,066,795 -36.8 -40.1

PA Columbia 35 60 50 42.9 -16.7 24,918 0.2 42,114 179,694 147,724 250.8 -17.8

PA Elk 46 55 9 -80.4 -83.6 14,968 0.1 490,201 353,201 8,721 -98.2 -97.5

PA Fayette 57 52 27 -52.6 -48.1 40,040 0.1 189,534 153,524 23,605 -87.5 -84.6

PA Greene 2,016 2,440 2,476 22.8 1.5 14,440 17.1 28,008,957 22,246,314 25,224,045 -9.9 13.4

PA Huntingdon 0 2 0 — -100.0 12,318 0.0 0 6,390 0 — -100.0

PA Indiana 399 541 412 3.3 -23.8 31,453 1.3 2,298,655 3,227,087 2,771,506 20.6 -14.1

PA Jefferson 174 133 118 -32.2 -11.3 15,637 0.8 955,441 602,554 384,901 -59.7 -36.1

PA Lackawanna 22 13 6 -72.7 -53.8 96,882 0.0 100,489 14,609 0 -100.0 -100.0

PA Luzerne 287 304 339 18.1 11.5 142,346 0.2 1,198,962 211,469 496,389 -58.6 134.7

PA Lycoming 66 35 32 -51.5 -8.6 53,016 0.1 262,743 251,818 119,887 -54.4 -52.4

PA Mercer 5 7 5 0.0 -28.6 47,941 0.0 84,688 89,532 44,584 -47.4 -50.2

PA Northumberland 172 161 178 3.5 10.6 27,487 0.6 932,137 216,017 290,244 -68.9 34.4

PA Schuylkill 800 508 553 -30.9 8.9 49,880 1.1 1,975,200 1,185,477 1,169,584 -40.8 -1.3

PA Somerset 659 1,164 546 -17.1 -53.1 23,991 2.3 5,166,366 5,306,500 2,053,242 -60.3 -61.3

PA Tioga 0 1 0 — -100.0 13,045 0.0 0 0 0 — —

PA Venango 16 9 11 -31.3 22.2 18,921 0.1 0 0 10,985 — —

PA Washington 1,628 775 675 -58.5 -12.9 87,189 0.8 17,696,420 10,633,431 9,789,334 -44.7 -7.9

PA Westmoreland 25 41 39 56.0 -4.9 133,042 0.0 111,920 114,890 204,913 83.1 78.4

TN Anderson 22 96 8 -63.6 -91.7 39,144 0.0 41,378 294,514 0 -100.0 -100.0

TN Campbell 102 296 21 -79.4 -92.9 9,013 0.2 651,004 952,076 68,031 -89.5 -92.9

TN Claiborne 205 135 251 22.4 85.9 8,584 2.9 1,609,175 561,568 821,334 -49.0 46.3

TN Cumberland 49 5 5 -89.8 0.0 17,253 0.0 265,102 0 0 -100.0 —

TN Fentress 3 3 0 -100.0 -100.0 4,668 0.0 11,764 16,789 0 -100.0 -100.0

TN Marion 0 2 2 — 0.0 7,157 0.0 0 0 0 — —

TN Scott 38 21 0 -100.0 -100.0 5,326 0.0 59,491 0 0 -100.0 —

VA Buchanan 1,428 1,707 1,185 -17.0 -30.6 6,872 17.2 11,110,839 8,825,011 7,198,881 -35.2 -18.4

VA Dickenson 667 781 845 26.7 8.2 3,610 23.4 3,537,504 3,347,040 3,585,016 1.3 7.1

VA Lee 279 183 53 -81.0 -71.0 4,467 1.2 941,256 212,213 0 -100.0 -100.0

VA Russell 214 261 46 -78.5 -82.4 7,023 0.7 915,872 726,205 551,660 -39.8 -24.0

VA Tazewell 248 205 178 -28.2 -13.2 15,355 1.2 1,469,825 1,171,314 647,676 -55.9 -44.7

VA Wise + Norton 2,196 1,678 758 -65.5 -54.8 15,960 4.7 15,153,086 7,440,181 2,150,835 -85.8 -71.1

WV Barbour 168 333 277 64.9 -16.8 3,347 8.3 757,994 1,446,928 1,005,556 32.7 -30.5

WV Boone 2,757 4,085 1,687 -38.8 -58.7 5,942 28.4 32,815,535 23,110,119 8,480,679 -74.2 -63.3

WV Clay 362 272 18 -95.0 -93.4 1,386 1.3 5,092,609 2,095,129 0 -100.0 -100.0

WV Fayette 391 983 627 60.4 -36.2 10,886 5.8 3,952,627 6,724,782 2,709,675 -31.4 -59.7

WV Grant 97 28 19 -80.4 -32.1 3,408 0.6 651,898 5,017 51,431 -92.1 925.1

WV Greenbrier 74 450 231 212.2 -48.7 13,226 1.7 563,098 919,184 916,614 62.8 -0.3

WV Harrison 182 104 47 -74.2 -54.8 35,103 0.1 1,292,614 681,038 133,321 -89.7 -80.4

WV Kanawha 1,100 1,468 1,498 36.2 2.0 102,811 1.5 14,253,152 9,648,376 7,657,646 -46.3 -20.6

WV Lincoln 80 237 9 -88.8 -96.2 2,577 0.3 735,563 1,327,389 0 -100.0 -100.0

WV Logan 804 1,909 1,678 108.7 -12.1 10,227 16.4 7,993,970 16,026,303 9,561,932 19.6 -40.3

WV McDowell 787 1,221 867 10.2 -29.0 4,797 18.1 5,246,840 4,988,481 2,681,762 -48.9 -46.2

WV Marion 518 1,172 1,203 132.2 2.6 19,143 6.3 6,021,172 11,387,843 13,756,775 128.5 20.8

WV Marshall 758 1,547 1,595 110.4 3.1 10,601 15.0 10,337,601 13,944,543 16,376,633 58.4 17.4

WV Mason 0 41 0 — -100.0 5,621 0.0 0 157,799 0 — -100.0

WV Mercer 1 14 22 2100.0 57.1 19,793 0.1 0 68,836 149,721 — 117.5

WV Mineral 14 17 2 -85.7 -88.2 7,727 0.0 45,157 74,330 0 -100.0 -100.0

WV Mingo 1,827 1,270 515 -71.8 -59.4 5,563 9.3 22,789,252 8,628,290 3,916,121 -82.8 -54.6

WV Monongalia 1,103 1,341 1,018 -7.7 -24.1 55,109 1.8 11,790,433 10,408,597 6,024,510 -48.9 -42.1

WV Nicholas 339 643 177 -47.8 -72.5 7,785 2.3 4,807,406 3,566,876 655,443 -86.4 -81.6

WV Ohio 0 100 516 — 416.0 29,100 1.8 0 180,308 6,030,582 — 3244.6

WV Preston 251 25 2 -99.2 -92.0 7,294 0.0 1,290,996 88,443 0 -100.0 -100.0

WV Raleigh 790 1,562 1,479 87.2 -5.3 32,291 4.6 9,639,215 7,522,708 5,633,400 -41.6 -25.1

WV Randolph 0 19 20 — 5.3 11,448 0.2 0 0 0 — —

WV Tucker 19 207 220 1057.9 6.3 2,713 8.1 143,798 2,449,174 2,108,354 1366.2 -13.9

WV Upshur 354 251 160 -54.8 -36.3 7,609 2.1 2,932,049 1,059,235 597,769 -79.6 -43.6

WV Wayne 537 798 433 -19.4 -45.7 8,718 5.0 6,011,554 4,745,767 1,031,263 -82.8 -78.3

WV Webster 488 498 337 -30.9 -32.3 1,998 16.9 5,595,049 4,022,561 1,596,491 -71.5 -60.3

WV Wyoming 1,095 1,132 1,059 -3.3 -6.4 4,735 22.4 8,091,589 4,291,637 4,532,920 -44.0 5.6

46,993 55,953 37,587 -20.0 -32.8 1,605,970 2.3 423,445,942 340,115,187 225,045,547 -46.9 -33.8

71,522 86,195 65,971 -7.8 -23.5 139,491,699 0.0 1,073,612,000 1,084,368,148 896,940,563 -16.5 -17.3

Source: Mine Safety and Health Administration and Energy Information Administration

Appalachian CoalEmployment Counties

U.S. Total

Coal Employment Coal Production
30

Figure 3: Gains and Losses for Counties with Coal Employment in 2000

Source: U.S. Mine Safety and Health Administration (MSHA).

2.2. A Profile of the United States Coal Miner

Detailed characteristics of coal miners in the Appalachian Region are generally not available. In 

lieu of such data, Table 14 presents a profile of the United States coal miner assembled from a variety 

of sources. Most of the information is for 2015, with exceptions noted. The table reflects an 

experienced work force with more than three-fourths having earned a high school diploma. However, 

only about 3 percent of coal miners hold a bachelor’s or higher college degree, which is significantly 

lower than both the Appalachian regional average and the national average. While this is expected in 
31

what are, for the most part, blue-collar occupations, we would expect the growing reliance on 

technology in the coal industry (Thibodeau, 2016) to increase educational and training requirements 

from current averages. An important question is whether existing coal workers will pursue educational 

advancement to secure these jobs or, rather, will these emerging jobs go to new individuals.

Other aspects of the qualifications of the coal industry’s work force include job and safety-related 

training. The numbers in Table 14 probably understate such qualifications, as indicated by the large 

number of examinations taken and certificates issued by the West Virginia Office of Miners’ Health, 

Safety and Training. In 2015, this state agency issued 5,785 new certificates, for example, for 

apprentice electrician (172), coal truck driver (130), underground coal miner (459), surface coal miner 

(174), underground mine foreman (191), and qualified diesel instructor (89) (West Virginia Office of 

Miners’ Health, Safety and Training, 2015). The largest number of new certificates (2,152) were for 

safety sensitive personnel. Certificates are awarded after passing an examination. The numbers

reported here do not include duplicates or certificates issued as part of a reciprocity agreement. To 

put the number of new certificates in perspective, in 2015 West Virginia’s coal industry had 16,200 

(MSHA data) or 22,750 (NMA data) employees (see Tables 11 and 12 above). These certifications signal 

the willingness of coal workers to invest in themselves to advance their careers.
32

Table 14: Profile of the United States Coal Miner

Job-related

Safety6

Appalachia

United States

Appalachia

United States

Appalachia

United States

23.63 percent4

24.93 percent4

21.88 percent4

47.3 hours3

Sources:

2.226

1.645

1.636

7.78 percent4

19.10 percent4

30.62 percent4

$836,001

$14,861

$578,202

46 hours1

2.275

$27.80

> 75 percent1

76.7 percent3

3 percent1

2.8 percent3

16 years1

16 years3

7.8 years3

10 – 25 hours1

24 hours1

8 hours1

$32.62

43 years1

44 years1

43.8 percent3

5.2 percent1

3.8 percent3

96.4 percent3

Economic Impact of Coal Mining Jobs Employment Multiplier

Wage Earnings Multiplier

Unionization (in percent) Surface Mines

Underground 

Mines

All Coal 

Mines

Earnings (in $) Average Hourly

Average Weekly

Average Yearly

Average Hours Worked (in hours) Per Week

Work Experience, median, in years

Work Experience in Mining, in years

Demographic Characteristics Median Age, in years

Mean Age, in years

Female, in percent

White, in percent

Qualifications Education (in percent) High School Diploma

Bachelor Degree or Beyond

Experience

Experience in Job Title, in years

Training In annual hours

New Miners, in annual hours

Refresher, in annual hours

6 Thompson et al., 2001; numbers are for all Appalachian coal counties for 1997.

7

 U.S. DHHS reports that in 2007 over 75 percent of all coal mines held safety meetings at least once a week (see McWilliams et al., 

2012b, Table 52, p. 64).

1

 National Mining Association, Profile of the U.S. Coal Miner, 2015, downloaded February 2017.

2

 BLS earnings information for all occupations represented under NAICS code 212100, numbers are for 2015.

3

 McWilliams et al. (2012a), numbers are for 2007.

4

 U.S. Energy Information Administration, 2016, numbers are for 2015.

5

 Evans, 2013; numbers are for 2011 for the coalfields in Appalachian Virginia.
33

The degree of unionization shows interesting differences between coal miners in Appalachia 

versus the national average. In 2015, surface mining in the United States had a degree of unionization 

almost 2.5 times higher than in Appalachia. By contrast, underground mining workers were more 

unionized by almost 30 percent in Appalachia than nationally. Employment in underground coal mines 

is more dominant in Appalachia (27,323 vs. 9,044, or 75.1 percent) than in the United States (39,575 

vs. 24,991, or 61.3 percent), and surface mines are less likely to be unionized than underground mines 

across the United States (U.S. EIA, 2016).

The median age of coal miners in 2016 was 44.7 years, which is above the national average of 

employed persons of 42.2 years (BLS, 2017). Fotta and Bockosh (2000), in a study for the National 

Institute for Occupational Safety and Health, note that workers aged 45 years and older have a higher 

median days of work missed because of injuries. This is an important issue because coal miners, in 

general, are known to be at risk of health disorders due to the nature of the coal workplace. Some 

problems are relatively common for workers engaged in physical production activities, including 

tendonitis and trauma, and exposure to noise and toxins. It is well documented that exposure to dust 

in coal mines leads to coal worker pneumoconiosis (CWP) and chronic obstructive pulmonary disease 

(COPD).6 Crystalline silica dust exposure also contributes to COPD and directly causes silicosis. The 

Department of Health and Human Services (2011) finds that the incidence of CWP is now on the 

upswing after a long period of decline. Concentrations of CWP are present in the Appalachian portions 

of southern West Virginia, eastern Kentucky, and western Virginia. These health conditions can be 

debilitating and lead to premature death. The risk tends to be higher for those working in 

underground mines. The scope of health-related problems for the coal work force is not well 

documented, for individuals or regions.

Table 15 shows typical work assignments (shifts worked and number of hours). The data are for 

2007 and may have changed with the slowdown of coal production, particularly in Appalachia, since 

2011. We have not been able to find region-specific work load and work assignment information. The 

data show that coal workers have relatively long work weeks with hours in excess of 40.

 6 These two health problems are part of a broader class of lung diseases referred to as coal mine dust lung 

disease or CMDLD that are concentrated in the Appalachian Region (Laney and Weissman, 2014). 
34

Table 15: Average Number of Hours Worked by Coal Miners in 2007

The coal mining industry (North American Industry Classification System or NAICS code 21-21000) 

employs workers in a wide range of occupations, including management, sales, computer specialists, 

engineers, truck drivers, and coal production miners narrowly defined. Table 16 presents the list of 

occupations by Standard Occupation Classification (SOC). Coal mining occupations fall into 15 major 

occupation groups,7 which can be further subdivided into 77 individual occupations, as defined by the 

Bureau of Labor Statistics (BLS). Together these occupations employed 69,450 people in 2015 in the 

United States. The three major occupation groups—Construction and Extraction (47 percent), 

Transportation and Material Moving (20 percent), and Installation, Maintenance and Repair (13

percent)— account for more than 80 percent of all employment. (This has important implications for 

our analysis below of alternative employment opportunities in other sectors of the economy since 

most of our data on coal employment is confined to these broad categories.) Mean annual wage 

earnings in these three major occupation groups exceed $50,000. In most Appalachian counties, such 

earnings are well above those of most other occupations, particularly those that do not require a 

college education. The distribution of employees in Table 16 is for the nation and will differ by region, 

as will be clear in the state-by-state analysis below. One reason for deviations from the national 

average is the share of surface mining of all coal mining, which in Appalachia is below the national 

average.

 7 By increasing level of detail, the BLS distinguishes between major group, minor group, broad level, and 

detailed. The definitions of occupations follow the Standard Occupational Classification (SOC). The current version 

has been published in the Federal Register of January 21, 2009 (https://www.bls.gov/soc/soc2010final.pdf, 

downloaded February 22, 2017).

Coal Mines

Underground 43.5 41.9

Most Common 

Number of Shifts 

Worked

2/day (49.8%) 2/day (44.1%)

Surface 49.2 45.9

Most Common 

Number of Shifts 

Worked

2/day (60.5%) 2/day (49.9%) 1/day (51.5%)

Source: Linda Jansen McWilliams, Patricia J. Lenart, Jamie L. Lancaster, and John R. Zeiner, Jr. 

National Survey of the Mining Population, Part II: Mines. U.S. Department of Health and Human 

Services, June 2012 (henceforth, McWilliams et al., 2012b)

Production 

Workers

Production Support 

Workers

Preparation Plant/Mill 

Workers

42.1

1/day (51.4%)

46.4
35

Table 16: United States Coal Mining Occupations by Major SOC Group, 2015

In Table 17 we take a closer look at the largest major occupation group in the coal mining 

industry, Construction and Extraction Occupations. The table reveals the variety of occupations 

included under SOC 47, as well as wide range of salaries. The highest paid occupation is First-line 

Supervisors of Construction Trades and Extraction Workers who, with $78,950 in earnings in 2015,

earned more than twice the annual salary of the lowest paid employees (Construction Laborers), who 

earned $36,340 per annum. All other occupations listed in Table 17 earn more than $40,000, and the 

vast majority earn more than $50,000 annually. 

Standard

Occupation

Code (SOC) Mean Median

11-0000 Management Occupations 3.52 $62.15 $54.44 $129,270 

13-0000 Business & Financial Operations 2.15 $33.29 $29.68 $69,250 

15-0000 Computer & Mathematical Occupations 0.15 $35.15 $35.78 $73,110 

17-0000 Architecture & Engineering Occupations 3.21 $36.83 $34.62 $76,610 

19-0000 Life, Physical, & Social Science Occupations 0.26 $28.88 $26.63 $60,060 

27-0000 Arts, Design, Entertainment, Sports & Media Not released $21.60 $22.73 $44,920 

29-0000 Healthcare Practitioners & Technical Occupations 0.71 $33.22 $32.05 $69,100 

33-0000 Protective Service Occupations 0.56 $14.63 $13.30 $30,440 

37-0000 Building & Grounds Cleaning & Maintenance 0.25 $15.78 $12.69 $32,820 

41-0000 Sales & Related Occupations 0.11 $50.73 $43.67 $105,530 

43-0000 Office & Administrative Support Occupations 4.28 $19.10 $17.62 $39,720 

47-0000 Construction & Extraction Occupations 47.28 $26.71 $25.55 $55,550 

49-0000 Installation, Maintenance & Repair Occupations 12.68 $27.53 $26.85 $57,270 

51-0000 Production Occupations 4.72 $26.85 $25.87 $55,840 

53-0000 Transp. & Material Moving Occupations 20.03 $24.67 $25.01 $51,320 

Source: BLS 2016a, the numbers are for 2015 for the whole United States, https://www.bls.gov/oes/current/naics4_212100.htm, 

downloaded March 17, 2017 

Occupation Title by Major Occupation Group

Percent of all 

Employees

Hourly Wage Mean 

Annual 

Wage
36

Table 17: National Construction and Extraction Occupations, 2015

2.3. Coal Mining Support Employment

Coal mining support activities are listed under NAICS code 21-3113. Unfortunately, the BLS does 

not make similarly detailed statistics available for these support activities (like office workers) as they 

do for coal mining (Table 16). The major occupation groups for support activities for all mining (NAICS 

code 21-3000) are the same as for coal mining, plus three additional ones: Legal Occupations (SOC 23-

0000), Education, Training and Library Occupations (SOC 25-0000), and Food Preparation and Service

Related Occupations (SOC 35-0000). Because we cannot assume that the relative shares among 

Standard

Occupation

Code (SOC) Mean Median

47-0000 Construction & Extraction Occupations 100.00% $26.71 $25.55 $55,550 

47-1011 First-Line Supervisors of Construction Trades & 

Extraction Workers 12.44% $37.96 $38.79 $78,950 

47-2000 Construction Trades Workers 38.83% $25.44 $25.06 $52,910 

47-2031 Carpenters 0.11% $23.28 $24.69 $48,420 

47-2051 Cement Masons & Concrete Finishers 0.08% $23.60 $26.40 $49,100 

47-2061 Construction Laborers 3.32% $17.47 $15.22 $36,340 

47-2073 Operating Engineers & Other Construction 

Equipment Operators

25.02% $25.70 $24.61 $53,450 

No code1 Construction Equipment Operators other than 

47-20731 0.11%

47-2111 Electricians 10.17% $27.54 $28.05 $57,290 

47-4000 Other Construction & Related Workers 0.27% $27.07 $26.73 $56,310 

47-4061 Rail-Track Laying & Maintenance Equipment 

Operators

0.23% $24.99 $26.16 $51,970 

47-5000 Extraction Workers 48.43% $24.83 $24.59 $51,650 

47-5010 Derrick, Rotary Drill, & Service Unit Operators, 

Oil, Gas, & Mining Not released $19.35 $19.45 $40,240 

47-5013 Service Unit Operators, Oil, Gas, & Mining Not released $19.35 $19.45 $40,240 

47-5021 Earth Drillers, Except Oil & Gas 1.16% $23.38 $22.42 $48,630 

47-5031 Explosives Workers, Ordnance Handling Experts, 

& Blasters 1.10% $29.74 $30.84 $61,860 

47-5040 Mining Machine Operators 20.85% $24.85 $24.32 $51,680 

47-5041 Continuous Mining Machine Operators 12.92% $24.44 $23.52 $50,830 

47-5042 Mine Cutting & Channeling Machine Operators 6.45% $26.00 $26.62 $54,090 

47-5049 Mining Machine Operators, All Other 1.50% $23.36 $23.06 $48,580 

47-5061 Roof Bolters, Mining 14.78% $26.53 $26.41 $55,180 

47-5081 Helpers--Extraction Workers 8.86% $21.16 $21.50 $44,010 

47-5099 Extraction Workers, All Other 1.50% $27.91 $27.25 $58,050 

Source: https://www.bls.gov/oes/current/naics4_212100.htm, downloaded March 17, 2017

1

 This is the difference between SOC code 47-2070 and sub-code 47-2073.

Title of SOC Code 47-0000 Occupations

Percent of 

all 47-0000 

Employees

Hourly Wage

Mean 

Annual 

Wage

Similar to 47-2073
37

occupations are similar for coal mining and non-coal mining support activities, we do not present a 

table similar to Table 17. For all mining activities, including oil and gas extraction, support activities 

employment is about 50 percent of mining employment. The numbers from the NMA in Table 12 show 

much smaller employment in support activities. On the other hand, the indirect and induced 

employment numbers reported by the NMA are implausibly high, as noted above. It seems likely that 

the BLS and the NMA use different definitions to distinguish between coal mining and coal mining 

support occupations.

3. Mobility between Industries and Occupations

Occupational and geographic mobility, alone or in combination, are ways to address job losses 

when a whole industry is in decline. However, geographic mobility that is forced upon individuals and 

households by adverse circumstances rather than choice, often comes with high social costs. 

Therefore, one of the main concerns in dealing with declining employment opportunities in the coal

industry is the ability of laid-off workers and others who are seeking alternative opportunities to find 

jobs in another industry. There are at least three factors to consider. First is the availability of job 

opportunities in other industries, second is the match between the workers’ qualifications and the 

qualification requirements of open jobs, and third is the number of individuals pursuing available jobs. 

The matrix in Figure 4 shows what one would expect: workers are most likely to transition from a job 

in an industry sector to another job in the same industry. Data from the U.S. Census Bureau are 

available only at the state level. Since West Virginia is the only state completely contained within 

Appalachia, and is also the largest coal producer in the Region, we use figures from this state to 

illustrate occupational mobility. Unfortunately, these data are currently publicly available only at a 

high level of industrial aggregation, so that we can only look at flows within, from, and into Mining, 

Quarrying, Oil and Gas Extraction (NAICS code 21). The detailed analysis of West Virginia is 

complemented by aggregate state-level data presented in Table 18.

In West Virginia, in the second quarter of 2005, 827 individuals moved from a job in Mining, 

Quarrying, Oil and Gas Extraction to another job in the same industry, while in the second quarter of 

2015, only 333 workers changed jobs within this industry. The largest number of workers entering this 

industry from another industry in 2005 came from Construction (157 workers), followed by 

Transportation and Warehousing (135 workers). In 2015 these numbers were much lower, with only 68 

workers from Construction and 39 workers from Transportation and Warehousing finding new jobs in 

the Mining, Quarrying, Oil and Gas Extraction industry. The largest source of new workers in 2015 

coming from another industry was Administrative and Support and Waste Management and 

Remediation; 185 new workers came from this industry in 2015 compared to 111 in 2005. This could 

indicate a possible shift in activities within the industry in West Virginia.

The largest outflow of workers in 2005 was to Construction (91 workers), followed by 

Administrative and Support and Waste Management and Remediation (48 workers), and Transportation 
38

and Warehousing (43 workers). As in the case of workers coming from other industries into Mining, 

Quarrying, Oil and Gas Extraction, the number of those leaving the industry also changed significantly 

between 2005 and 2015. In West Virginia in 2015, 161 workers left for Construction, 121 for 

Administrative and Support and Waste Management and Remediation, 91 for Transportation and 

Warehousing, 59 for Retail Trade, and 50 for Manufacturing. 

These transitions highlight the changing job opportunities in Mining, Quarrying, Oil and Gas 

Extraction. While in 2005 the number of workers entering the industry from another industry (864 

workers) was significantly larger than those leaving (349 workers), in 2015 more workers were leaving 

the industry (664 workers) than entering it (480 workers).

Table 18 summarizes these statistics for all states with counties in Appalachia; the data are only 

available at the state level. In the table, “Leaving” includes only workers who go to another industry; 

those who became unemployed or retired are not included. Similarly, “Entering” includes only 

workers who were previously employed in another industry. Mobility between industries is of 

particular interest in a changing economy as it indicates occupational mobility and, therefore, 

worker’s ability to cope with and adjust to changes in job opportunities in different industries.

Table 18: Workers Entering, Leaving and Shifting within the Mining, Quarrying, Oil and Gas Extraction 

Industry by Appalachian State

The matrices in Figure 4 provide a graphical account of flows between industries though the data 

are confined to West Virginia as noted above. They show small flows of workers from Mining, 

Quarrying, Oil and Gas Extraction into other industries, including Utilities, Manufacturing, Wholesale, 

Entering Leaving

Shifting 

within 

Industry Entering Leaving

Shifting 

within 

Industry

Alabama 345 219 87 125 123 37

Georgia 142 104 20 110 90 11

Kentucky 568 205 639 187 397 199

Maryland1 68 38 20 30 40 1

Mississippi 384 259 47 181 302 25

North Carolina 86 63 2 90 24 4

New York 253 120 12 249 116 11

Ohio 287 177 44 367 641 108

Pennsylvania 604 352 193 722 1524 355

South Carolina 56 36 0 43 9 1

Tennessee 111 43 14 82 70 12

Viginia1 275 126 199 149 156 90

West Virginia 864 349 827 480 664 333

1

 Data for Maryland and Virginia for the 2nd quarter of 2005 were not available; data are 

for 2nd quarter of 2006.

State

2005, 2nd Quarter 2015, 2nd Quarter

Source: U.S. Census Bureau, Longitudinal Household-Employer Dynamics. 

https://lehd.ces.census.gov/data/j2j_beta.html 
39

and Transportation, but only small flows into Construction. We would have expected a more balanced 

net flow since there are many employees with construction-related skills and experience. In the 

second quarter of 2015, we see no large flows into the NAICS 21 industry. Kentucky and Pennsylvania 

follow a pattern similar to that of West Virginia. Virginia resembles Kentucky and West Virginia, 

except for relatively large inflows from NAICS sector 55, Management of Companies and Enterprises. 

The other Appalachian states—Alabama, Georgia, Mississippi, New York, North Carolina, Ohio, and 

Tennessee—show relatively large inflows to the NAICS 21 industries, particularly from Construction and 

Manufacturing. South Carolina is similar to Alabama, etc., except that the job movements within 

NAICS 21 are smaller than the inflows from other industries, which makes it unusual. All states have 

relatively small outflows from Mining, Quarrying, Oil and Gas Extraction to other industries.

Figure 4: Job-to-Job Flows in West Virginia

Second Quarter 2015 Second Quarter 2005

Source: U.S. Census Bureau, Longitudinal Employer-Household Dynamics; 

https://lehd.ces.census.gov/data/j2j_beta.html, created using the site’s “Job-to-Job Flows Explorer,” 

downloaded March 23, 2017

Another important consideration in examining job dynamics is the spatial pattern of job openings 

for displaced workers. As demonstrated below, in many small coal-employment communities, there 

are simply few if any other occupational opportunities in other sectors of the regional economy. As a 

result, workers face a number of relatively undesirable options. One is to directly find a job in 

another sector/occupation, which may entail lower compensation. Second, workers could invest in 

education and training and pursue another occupational career, including entrepreneurial activity.

This can be costly in terms of out-of-pocket costs and forgone income. Moreover, there is no 

assurance that a job or viable entrepreneurial opportunity will be forthcoming in a community with a 
40

declining coal employment base. Third, workers could simply withdraw from the labor force. But many 

workers will need to work because of their age and financial commitments. Finally, workers may seek 

job opportunities in other places. While moving is costly and may have consequences for social 

connections and family ties, it may be the only viable option for workers in some communities. In 

general, involuntary occupational changes are associated with lower pay after the change. This is true 

even for workers who have received training to facilitate the transition (Barrett, 2001; Johnson, 

Kawachi and Lewis, 2009).

Fortunately, workers in Appalachia seek and find jobs in geographical areas that extend beyond 

county borders. As such, they may be relatively more inclined to pursue jobs in wide geographic 

areas. Workers in the Appalachian states have commuting times close to the national average of 25.9 

minutes. New Yorkers, with a state average of 32.3 minutes have the longest commute, followed by 

Maryland with 31.2 minutes. Virginia is third with 27.9 minutes and in fourth place is West Virginia 

with 25.6 minutes. In the first three states with their large agglomerations, metropolitan regions may 

have contributed to commuting times above the national average. This is not the case in mostly rural 

West Virginia, however, and indicates that many rural residents already accept a significant commute 

to work. Kentuckians spend the least time commuting—23 minutes. There is no clear pattern 

indicating that urbanized states have significantly longer commuting times. For example, Ohio, with 

multiple metropolitan regions, has an average state-wide commuting time of only 23.2 minutes, the 

second lowest among the Appalachian states. Wool’s observation made 36 years ago still applies: 

“With few exceptions, coal mining is conducted in areas which are beyond normal commuting distance 

from major urban centers. Of the nation's 100 largest standard Metropolitan Statistical Areas, only two

(Pittsburgh and Birmingham) have significant amounts of bituminous coal mining activity. In 1970, 

about one-half of all coal miners resided in rural areas (population under 2,500)" (Wool, 1981: p. 3). 

The geographical concentration of coal mining employment in relatively few rural areas could 

pose a serious policy problem. Fortunately, coal mining workers and support workers are less 

geographically concentrated than their jobs. We illustrate this using Boone County, West Virginia, 

where coal industry employment accounted for 28.4 percent of all employment in 2015. Census data 

on county-to-county commuting of workers, 16 years of age and older, show that 4,653 county 

residents commuted to a job in their home county, while 4,446 workers commuted from elsewhere in 

West Virginia to work in Boone County. An additional 2,956 Boone County residents commuted to work 

in another West Virginia county, the majority of them – 2,142 employees – to neighboring Kanawha

County, the most populous in West Virginia.8 Because Boone County is located in West Virginia’s 

interior, commuting to and from other states was negligible. The commuting data demonstrate that 

commuting regions are significantly larger than counties and, as a result, policies aimed at mitigating 

the impacts of job losses in coal regions should account for commuting patterns.

 8 U.S. Census Bureau 2015. The information on commuting is from the American Community Survey 2009 – 2013.
41

4. Coal Occupations: Are Other Opportunities 

Available in Appalachia?

An important question is the scope of job opportunities for occupational-specific coal workers 

outside the coal sector itself. We have acquired occupational data for coal workers from a number of 

Appalachian states that, to varying degrees of detail, allow for an examination of state-specific 

occupational mixes associated with the state’s coal employment base. For some states like Tennessee

where there is a small number of coal workers, we were simply not able to acquire detailed data from 

the state. For other states—notably Pennsylvania and West Virginia—where the coal industry is more 

prominent, we have considerably more detail on occupational categories and larger numbers of coal 

workers across occupational classifications.

4.1. Matching Coal Worker Occupations to Similar 

Occupations in Other Industries

The best outcome for most displaced or potentially displaced coal workers would be to find good 

paying jobs in the community where they currently reside. In many cases this will simply not be 

possible due to the small size and lack of economic/occupational diversity that characterizes many 

coal-employment counties in Appalachia. For this reason, as well as data limitations for county-level 

economies, we focus on potential employment opportunities in two different sets of regions. The first 

is the set of 129 coal-employment counties in a given Appalachian state. These multicounty regions 

will offer greater employment opportunities than the county of employment while at the same time 

offering reasonably proximate and similar locations to the current place of residence for coal workers.

The second region is the entire state economy that a given coal-employment county is located in. The 

statewide regional economy should, in many instances, be sufficiently large to yield employment 

opportunities for significant numbers of coal workers. However, it may also require outmigration or a 

long commute, as well as retraining.

For each of these broad regions, we use a NAICS-to-SOCS crosswalk applied to the manufacturing, 

transportation, and construction industries to determine existing levels and the mix of occupations.

These three industries were chosen since they will offer occupational opportunities that are similar if 

not exactly equivalent to those for coal production workers. We have acquired occupational data for 

coal workers from the individual states that include some detail on both production and nonproduction occupations; there is some inconsistency in the occupational groups provided by the 

respective states, as well as differences in the years for which the data apply. Importantly, the 

number of occupational positions in the state-specific data generally do not match job counts from 

other sources; this problem clearly surfaced above in the context of other data on the coal industry.

Given the nature of the data, we caution the reader to place emphasis on orders of magnitude rather 
42

than specific data points. Despite the differences in the data and this cautionary note, these figures 

will still allow a comparison of occupational patterns in the coal industry to the same occupational 

patterns in other sectors of the economy. This will shed considerable light on the capacity of other 

sectors to absorb displaced coal workers as well as coal workers who simply seek employment 

opportunities outside the coal industry.

4.2. State by State Occupational Analysis

Tables 19-24 provide the occupational data for the Appalachian states that have coal 

employment, other than Tennessee. The first column of numerical data (State Total) shows the 

number of coal workers by occupation. The next two columns of data report coal mining occupations 

as a share of (i) occupations in the statewide manufacturing, transportation and construction sectors 

and (ii) occupations in the state’s Appalachian portions in the manufacturing, transportation and 

construction sectors. For example, in Table 19, Alabama reports 2,150 occupations in the coal 

industry. This represents 0.5 percent of statewide positions in manufacturing, transportation and 

construction and 0.8 percent of positions in the Appalachian portions of the state for the same 

sectors. The final two columns of data show the number of occupations in manufacturing, 

transportation and construction for the state and the Appalachian portions of the state. For example,

for Alabama there are 7,820 Electricians outside the coal industry in the statewide manufacturing, 

transportation and construction sectors; there are no Continuous Mine Machine Operators, Mining 

Machine Operators, Roof Bolters or Mine Shuttle Car Operators in the manufacturing, transportation 

and construction sectors either within the Appalachian Region of the state or across the state.

A review of the tables shows that the overall number of occupational positions engaged in coal 

production is generally modest compared to all occupational positions in the state in the 

manufacturing, construction and transportation sectors, though there are exceptions. Kentucky and 

West Virginia, for example, have relatively large numbers of coal-related occupations, representing 

3.8 percent and 17.4 percent of the same statewide occupations in manufacturing, construction and 

transportation. As would be expected, the relative importance of coal occupations rises as the region 

of focus is narrowed to Appalachian portions of a state. For example, in Kentucky, coal-related 

occupations represent 25.0 percent of the number of occupations in the manufacturing, construction 

and transportation sectors across the Appalachian portions of the state.

Non-production coal occupations tend to be small shares of equivalent occupations in 

manufacturing, construction and transportation, though again there are numerous exceptions. This 

suggests that workers in these occupations should face reasonably bright employment prospects

outside the coal industry. These alternatives are brighter still when it is recognized that there is a 

wide range of other sectors of the economy that will employ individuals in the same occupations.

The situation for production workers varies by state and by occupation. To draw out some of the 

more salient issues, we provide the following state-by-state summary assessment.
43

• Alabama. Table 19 shows the state’s coal mining employment by occupation, with a total 

of 2,150 jobs across production and non-production classifications, representing 0.5 

percent and 0.8 percent of occupations in the manufacturing, construction and 

transportation sectors across the state and across Appalachian portion of the state, 

respectively. In relative terms, the management and office-related occupations in coal 

counties are small shares of regional and statewide occupations in the three highlighted 

sectors. However, this is not the case for all occupations. Outside the coal sector, there 

are no Continuous Mining Machine Operator, Mining Machine Operator or Roof Bolt 

occupations in other sectors in either the Appalachian portion of the state or the state 

itself. There are 210 Excavating and Loading Machine occupations in the coal industry 

compared to 320 similar occupations across the state and just 203 equivalent occupations 

in the Appalachian portion of the state. These coal industry occupations are 65.6 percent 

of equivalent statewide occupations and 103.4 percent of occupations in the Appalachian 

portion of the state. These high figures suggest that coal workers in these occupations will

face stiff competition in the pursuit of alternative jobs in other sectors of the state and 

regional economies.

• Kentucky. As shown in Table 20, a total of 6,100 occupations in Kentucky are tied to coal 

activity, representing 1.4 percent of state occupations in the three highlighted sectors and 

9.3 percent of the same occupations in these industries in the Appalachian portion of the 

state. The data show no Management or office-related occupations tied to coal, but there 

are 170 Engineering occupations that account for 11.0 percent of the Appalachian portion

and just 1.7 percent of statewide occupations in manufacturing, construction and 

transportation. For several occupations, including Mining and Geological Engineers, 

Continuous Mining Machine Operators, Mine Cutting Machine Operators, Mining Machine 

Operators, Roof Bolters, Extraction Workers and Loading Machine Operators, there are no 

equivalent positions outside the coal sector in the state. For those occupations among this 

group with no disclosure issues, this represents 1,320 positions. For Helpers, there are 

more than three times as many occupations in the coal industry than in other sectors 

across the state; there are only 15 equivalent occupations in the Appalachian portion of 

the state outside of the coal sector.

• Ohio. As shown in Table 21, the state reports 2,332 occupational positions in the coal 

industry, representing 0.2 percent of occupational positions in manufacturing, 

construction and transportation in the state and 1.7 percent of occupations in the same 

industries for the Appalachian portion of the state. Four occupations together account for 

628 positions that have no equivalent occupations elsewhere in the state or regional 

economies. Operating Engineers and Mobile Heavy Equipment Mechanics in the coal sector 

are a relatively large share of the total number of equivalent occupations within the 

Appalachian portion of the state.

• Pennsylvania. The state provided a high level of detail for its 4,700 coal-related 

occupations, as shown in Table 22. Despite the relatively large number of jobs, coalrelated occupations account for small shares of statewide (0.4 percent) and regional (1.0

percent) occupations in the three highlighted sectors. Eighteen occupations in the coal 

sector have no counterpart occupations in the Appalachian portion of the state or the 

state as a whole. These occupations represent a total of 7,652 positions. Helpers, 

Excavating and Loading Machine Operators, Pump Operators, Operating Engineers and 

Mobile Heavy Equipment Mechanics account for large shares of equivalent statewide and 

regional occupations in manufacturing, construction and transportation. For Helpers, the 

number of positions in the coal sector is 533.0 percent of the positions outside the coal 

sector within the Appalachian portion of the state and 238.0 percent of statewide 

occupations, illustrating the dominance of the coal industry and highlighting the relatively 

limited employment opportunities outside the coal sector.

• Virginia. Table 23 reveals that coal-related occupations in Virginia total 6,051, 

representing 1.1 percent of counterpart statewide occupations and 10.3 percent of the 
44

Appalachian portion’s occupations in manufacturing, construction and transportation.

Eight occupations accounting for 6,048 positions have no counterparts at the state or 

regional levels. The number of Operating Engineers and Mobile Heavy Equipment 

Mechanics in the coal sector exceeds the number of equivalent occupations in other 

sectors within the Appalachian portion of the state.

• West Virginia. The state’s large coal sector has 12,780 positions that represent 12.3

percent of all positions across the state in the manufacturing, construction and 

transportation sectors, as shown in Table 24. Nineteen occupations have no counterparts 

within the state, together representing 4,510 positions. These 19 occupations alone 

account for 35.3 percent of all coal jobs in West Virginia. Three occupations are equally or 

more heavily represented in the coal industry than in the three highlighted sectors, while 

another four occupations have position counts that are at least 50 percent larger than the 

count of occupations in the other sectors. Finally, note that there are seven occupations 

for which data are suppressed due to concerns over disclosure (D). This generally implies 

small numbers of employers which in turn suggests constrained alternative employment 

opportunities for workers in these occupations.

The discussion above focused on direct occupation-to-occupation matching between the coal 

sector and the manufacturing, construction and transportation sectors at the Detailed Occupation (six 

digit) level. The job outlook is not nearly as dire if one rolls these occupations up to the two-digit 

Major Group levels for Construction and Extraction Occupations (47), Installation, Maintenance and 

Repair Occupations (49), Production Occupations (51) and Transportation and Material Moving 

Occupations (53). This is an important consideration since some of these occupations will depend on 

similar skills, formal training, and on-the-job training. For example, consider SOC 47 for Kentucky (see 

Table 20 above). There are 52,680 occupational positions at the state level and 8,007 occupational 

positions in the Appalachian portion of the state for these Major Groups. If we sum the disclosed data 

fields for Detailed Occupations within Major Group 47, there are 6,660 occupational positions. This 

represents 12.6 percent of statewide occupations and 83.2 percent of occupations within the 

Appalachian portion of the state. Similarly, consider Major Group 51 for West Virginia. Table 24 shows

that there are 27,050 occupational positions in this group. West Virginia reports 560 occupational 

positions in this same group for the coal industry, representing just 2.1 percent of statewide 

occupations.

These figures indicate broader occupational opportunities for coal workers, though in specific 

instances the number of alternative positions even at the major SOC group level may be problematic.

In general, workers would require transitional education and training, and they may need to relocate 

to find gainful employment. These opportunities are broader still for workers who are willing to cross 

major occupational group lines for alternative employment opportunities. There would certainly be 

impediments to occupational mobility given the uniqueness of employment and the environment in 

the coal industry.
45

Table 19: Coal Mining Employment and the Distribution of Occupations: Alabama

Occupation 

Code Name Entire State

As percent of 

State 

Manufacturing, 

Construction & 

Transportation 

Employment

As percent of State's 

ARC Counties' 

Manufacturing, 

Construction & 

Transportation 

Employment Entire State

Appalachian 

Portion

00-0000 Total, All Occupations 2,150 0.5 0.8 413,100 262,533

11-0000 Management Occupations 80 0.5 0.8 16,500 10,486

43-0000** Office and Administrative Support Occupations 30 0.1 0.1 42,640 27,099

43-3031 Bookkeeping, Accounting, and Auditing Clerks 30 0.8 1.3 3,530 2,243

47-0000** Construction and Extraction Occupations 680 1.3 2.0 53,870 34,235

47-2073 Operating Engineers and Other Construction Equipment Operators 100 3.5 5.5 2,870 1,824

47-2111 Electricians 180 2.3 3.6 7,820 4,970

47-5041 Continuous Mining Machine Operators 90 — — — —

47-5049 Mining Machine Operators, All Other 60 — — — —

47-5061 Roof Bolters, Mining 250 — — — —

49-0000 Installation, Maintenance and Repair Occupations D D D 33,010 20,979

49-1011 First-Line Supervisors of Mechanics, Installers, and Repairers D D D 2,760 1,754

49-3042 Mobile Heavy Equipment Mechanics, Except Engines 50 10.0 15.7 500 318

53-0000 Transportation and Material Moving Occupations 540 0.8 1.3 67,520 42,910

53-3032 Heavy and Tractor-Trailer Truck Drivers 80 0.3 0.5 23,650 15,030

53-7032 Excavating and Loading Machine and Dragline Operators 210 65.6 103.3 320 203

53-7111 Mine Shuttle Car Operators 50 — — — —

— indicates absence of occupation in any industry

**Indicates calculated major group; data absent from state sources

Source: Alabama Department of Labor 2016 Estimates/Bureau of Labor Statistics 2016 Occupational Employment Statistics; state total and ARC shares of employment calculated using 2015 

QCEW data provided by IMPLAN

Coal Mining Occupations

Coal Mining Employment

Manufacturing, Construction 

and Transportation 

Employment
46

Table 20: Coal Mining Employment and the Distribution of Occupations: Kentucky

Table 21: Coal Mining Employment and the Distribution of Occupations: Ohio

Occupation 

Code Name Entire State

As percent of 

State 

Manufacturing, 

Construction & 

Transportation 

Employment

As percent of 

State's ARC 

Counties' 

Manufacturing, 

Construction & 

Transportation 

Employment

Entire 

State

Appalachian 

Portion

00-0000 Total, All Occupations 6,100* 1.4 9.3 431,910 65,644

17-0000** Architecture and Engineering Occupations 170 1.7 11.0 10,160 1,544

17-2151 Mining and Geological Engineers, Including Mining Safety Engineers 170 — — — —

47-0000** Construction and Extraction Occupations D D D 52,680 8,007

47-1011 First-Line Supervisors of Construction Trades and Extraction Work 830 16.6 109.4 4,990 758

47-2073 Operating Engineers and Other Construction Equipment Operators 1,090 28.5 187.7 3,820 581

47-2111 Electricians 680 9.9 65.2 6,860 1,043

47-5021 Earth Drillers, Except Oil and Gas D D D 150 23

47-5041 Continuous Mining Machine Operators 740 — — — —

47-5042 Mine Cutting and Channeling Machine Operators D D D — —

47-5049 Mining Machine Operators, All Other 40 — — — —

47-5061 Roof Bolters, Mining 370 — — — —

47-5081 Helpers--Extraction Workers 310 310.0 2039.7 100 15

47-5099 Extraction Workers, All Other D D D — —

49-0000** Installation, Maintenance, and Repair Occupations 400 1.3 29,770 4,525

49-3042 Mobile Heavy Equipment Mechanics, Except Engines 400 71.4 470.0 560 85

53-0000** Transportation and Material Moving Occupations D D D 97,630 14,838

53-3032 Heavy and Tractor-Trailer Truck Drivers 2,300 11.3 74.5 20,310 3,087

53-7032 Excavating and Loading Machine and Dragline Operators D D D 300 46

53-7033 Loading Machine Operators, Underground Mining D D D — —

D indicates coal industry occupation data not disclosed by state agencies 

— indicates absence of occupation in any industry

*Occupation distribution provided for eastern region of the state while industry total is for whole state

**Indicates calculated major group; data absent from state sources

Coal Mining

 Employment

Manufacturing, 

Construction and 

Transportation 

Coal Mining Occupations Employment

Source: Kentucky Office of Employment & Training, Workforce Intelligence Branch, Occupational Employment Projections Program, 2016 data; state total and ARC shares of 

employment calculated using 2015 QCEW data provided by IMPLAN 

Occupation 

Code Name Entire State

As percent of State 

Manufacturing, 

Construction & 

Transportation 

Employment

As percent of 

State's ARC 

Counties' 

Manufacturing, 

Construction & 

Transportation 

Employment Entire State

Appalachian 

Portion

00-0000 Total, All Occupations 2,332 0.2 1.7 1,072,990 140,164

11-0000 Management Occupations 36 0.1 0.5 52,450 6,851

47-0000 Construction and Extraction Occupations 1,225 0.9 7.0 133,390 17,425

47-1011 First-Line Supervisors of Construction Trades and Extraction 75 0.7 5.4 10,730 1,402

47-2073 Operating Engineers and Other Construction Equipment Operators 442 4.6 35.0 9,660 1,262

47-5041 Continuous Mining Machine Operators 106 — — — —

47-5042 Mine Cutting and Channeling Machine Operators 275 — — — —

47-5081 Helpers--Extraction Workers 139 — — — —

49-0000 Installation Maintenance and Repair Occupations 276 0.4 3.1 69,190 9,038

49-3042 Mobile Heavy Equipment Mechanics Except Engines 108 8.4 64.6 1,280 167

51-0000 Production Occupations 90 0.0 0.2 388,280 50,721

53-0000 Transportation and Material Moving Occupations 601 0.3 2.6 173,660 22,685

53-7033 Loading Machine Operators Underground Mining 108 — — — —

D indicates coal industry occupation data not disclosed by state agencies 

— indicates absence of occupation in any industry

Manufacturing, Construction 

and Transportation 

Coal Mining Occupations Employment

Coal Mining

 Employment

Source: Ohio Dept of Jobs and Family Services 2014 Estimates/Bureau of Labor Statistics 2014 Occupational Employment Statistics; state total and ARC shares of employment calculated 

using 2015 QCEW data provided by IMPLAN
47

Table 22: Coal Mining Employment and the Distribution of Occupations: Pennsylvania

Occupation 

Code Name Entire State

As percent of State 

Manufacturing, 

Construction & 

Transportation 

Employment

As percent of 

State's ARC 

Counties' 

Manufacturing, 

Construction & 

Transportation 

Employment Entire State

Appalachian 

Portion

00-0000 Total, All Occupations 4,700 0.4 1.0 1,085,980 484,982

11-0000** Management Occupations 79 0.2 0.4 42,850 19,136

11-1021 General & Operations Managers 62 0.4 0.9 15,930 7,114

11-3051 Industrial Production Managers 17 0.4 0.8 4,900 2,188

13-0000** Business and Financial Operations Occupations 39 0.1 0.3 31,480 14,058

13-1023 Purchasing Agents 27 0.5 1.2 5,170 2,309

13-2011 Accountants & Auditors 12 0.2 0.4 7,620 3,403

17-0000** Architecture and Engineering Occupations 38 0.1 0.2 36,600 16,345

17-2151 Mining & Geological Engineers 38 — — — —

29-0000** Healthcare Practitioners and Technical Occupations 14 0.9 2.1 1,530 683

29-9011 Occupational Health & Safety Specialists 14 1.6 3.5 890 397

43-0000** Office and Administrative Support Occupations 228 0.2 0.4 135,280 60,414

43-3031 Bookkeeping, Accounting & Auditing Clerks 15 0.1 0.3 9,730 4,345

43-5032 Dispatchers 14 0.3 0.8 4,170 1,862

43-5081 Stock Clerks & Order Fillers 15 0.2 0.4 9,310 4,158

43-9061 Office Clerks, General 185 0.9 2.1 19,890 8,883

47-0000** Construction and Extraction Occupations 2,149 1.3 3.0 161,530 72,137

47-1011 Supervisors - Construction Trades & Extraction Workers 281 1.9 — 14,560 —

47-2061 Construction Laborers 58 0.2 0.4 33,270 14,858

47-2073

Operating Engineers & Other Construction Equipment 

Operators 291 2.5 5.6 11,600 5,180

47-2111 Electricians 131 0.7 1.5 19,580 8,744

47-4061 Rail-Track Laying & Maintenance Equipment Operators 30 6.6 14.7 450 201

47-5013 Service Unit Operators, Oil, Gas & Mining 31 — — — —

47-5041 Continuous Mining Machine Operators 325 — — — —

47-5042 Mine Cutting & Channeling Machine Operators 204 — — — —

47-5049 Mining Machine Operators, All Other 40 — — — —

47-5061 Roof Bolters, Mining 383 — — — —

47-5081 Helpers - Extraction Workers 333 238.0 533.0 140 63

47-5099 Extraction Workers, All Other 42 — — — —

49-0000** Installation, Maintenance, and Repair Occupations 522 0.8 1.7 66,780 29,823

49-1011 Supervisors - Mechanics, Installers & Repairers 62 1.3 2.8 4,840 2,161

49-3042 Mobile Heavy Equipment Mechanics 204 12.2 27.4 1,670 746

49-9041 Industrial Machinery Mechanics 84 1.1 2.4 7,810 3,488

49-9043 Maintenance Workers, Machinery 43 1.3 2.9 7,390 1,487

49-9071 Maintenance & Repair Workers, General 129 1.0 2.3 12,420 5,547

51-0000** Production Occupations 252 0.1 0.2 304,410 135,945

51-1011 Supervisors - Production & Operating Workers 66 0.3 0.7 21,800 9,736

51-4121 Welders, Cutters, Solderers & Brazers 84 0.7 1.5 12,390 5,533

51-9021 Crushing, Grinding & Polishing Machine Setters/Oprs/Tndrs 44 5.0 11.1 890 397

51-9061 Inspectors, Testers, Sorters, Samplers & Weighers 58 0.0 0.9 14150† 6,319

53-0000** Transportation and Material Moving Occupations 1,128 0.5 1.0 243,820 108,886

53-1021 Supervisors - Helpers, Laborers & Material Movers 16 0.3 0.7 5,440 2,429

53-1031 Supervisors - Transportation & Vehicle Operators 23 0.4 0.9 5,810 2,595

53-3032 Heavy & Tractor-Trailer Truck Drivers 101 0.2 0.4 59,730 26,674

53-4013 Rail Yard Engineers, Dinkey Operators & Hostlers 24 10.6 23.8 230 103

53-7011 Conveyor Operators & Tenders 120 9.7 21.6 1240† 554

53-7032 Excavating & Loading Machine & Dragline Operators 406 169.2 379.5 510 107

53-7033 Loading Machine Operators, Underground Mining 106 — — — —

53-7051 Industrial Truck & Tractor Operators 22 0.1 0.2 23,680 10,575

53-7061 Cleaners of Vehicles & Equipment 19 1.6 3.5 1,190 531

53-7062 Laborers & Freight, Stock & Material Movers 51 0.1 0.2 66,960 29,903

53-7063 Machine Feeders & Offbearers 24 0.7 1.6 3,320† 1,483

53-7072 Pump Operators 30 74.0 165.8 40 18

53-7111 Mine Shuttle Car Operators 186 — — — —

99-9999 Other Misc. Occupations 249 — — — —

D indicates coal industry occupation data not disclosed by state agencies 

— indicates absence of occupation in any industry

**Indicates calculated major group; data absent from state sources

†Indicates employment undisclosed for at least one of three industries; partial sum

Coal Mining Occupations

Manufacturing, Construction 

and Transportation 

Coal Employment Employment

Source: Pennsylvania Dept of Labor and Industry 2016 Estimates/Bureau of Labor Statistics 2016 Occupational Employment Statistics; state total and ARC shares of 

employment calculated using 2015 QCEW data provided by IMPLAN
48

Table 23: Coal Mining Employment and the Distribution of Occupations: Virginia

Occupation 

Code Name Entire State

As percent of 

State 

Manufacturing, 

Construction & 

Transportation 

Employment

As percent of 

State's ARC 

Counties' 

Manufacturing, 

Construction & 

Transportation 

Employment Entire State

Appalachian 

Portion

00-0000 Total, All Occupations 6,051 1.1 10.3 538,020 58,589

11-0000 Management Occupations 235 1.1 10.3 20,940 2,280

43-0000 Office and Administrative Support Occupations 311 0.4 4.0 71,820 7,821

47-0000 Construction and Extraction Occupations 3,752 3.1 28.7 119,860 13,053

47-2000 Construction Trades Workers 1,321 — — — —

47-2073

Operating Engineers and Other Construction Equipment 

Operators 873 13.5 123.7 6,480 706

47-5000 Extraction Workers 2,055 — — — —

47-5041 Continuous Mining Machine Operators 1,203 — — — —

47-5042 Mine Cutting and Channeling Machine Operators 323 — — — —

47-5051 Rock Splitters, Quarry 233 — — — —

49-0000 Installation, Maintenance, and Repair Occupations 529 1.4 12.5 38,980 4,245

49-3042 Mobile Heavy Equipment Mechanics, Except Engines 214 17.8 163.8 1,200 131

49-9000 Other Installation, Maintenance, and Repair Occupations 253 — — — —

49-9041 Industrial Machinery Mechanics 142 2.9 26.7 4,890 533

51-0000 Production Occupations 374 0.3 2.9 119,260 12,987

51-9000 Other Production Occupations 232 — — — —

53-0000 Transportation and Material Moving Occupations 615 0.6 5.7 99,920 10,881

53-7000 Material Moving Workers 428 — — — —

D indicates coal industry occupation data not disclosed by state agencies 

— indicates absence of occupation in any industry

Source: Virginia Employment Commission 2014 Estimates/Bureau of Labor Statistics 2014 Occupational Employment Statistics; state total and ARC shares of employment 

calculated using 2015 QCEW data provided by IMPLAN

Coal Mining Occupations

Manufacturing, Construction 

and Transportation 

Employment
49

Table 24: Coal Mining Employment and the Distribution of Occupations: West Virginia

Occupation 

Code Name Entire State

As percent of 

State 

Manufacturing, 

Construction & 

Transportation 

Employment

As percent of 

State's ARC 

Counties' 

Manufacturing, 

Construction & 

Transportation 

Employment Entire State

Appalachian 

Portion

00-0000 Total all occupations 12,780 12.3 12.3 104,210 104,210

11-0000 Management Occupations 340 9.2 9.2 3,690 3,690

11-1021 General and Operations Managers 140 9.7 9.7 1,450 1,450

11-3011 Administrative Services Managers 70 87.5 87.5 80 80

11-3051 Industrial Production Managers D D D 590 590

11-9021 Construction Managers D D D 360 360

11-9199 Managers, All Other 30 27.3 27.3 110 110

13-0000 Business and Financial Operations Occupations 110 6.0 6.0 1,840 1,840

13-1023

Purchasing Agents, Except Wholesale, Retail, and Farm 

Products 30 13.0 13.0 230 230

13-1041

Compliance Officers, Except Agriculture, Construction, 

Health and Safety, and Transportation 10 — — — —

13-1071 Human Resources Specialists 20 13.3 13.3 150 150

13-2011 Accountants and Auditors 10 3.1 3.1 320 320

17-0000 Architecture and Engineering Occupations 250 12.3 12.3 2,040 2,040

17-1022 Surveyors 30 — — — —

17-2081 Environmental Engineers 10 — — — —

17-2151

Mining and Geological Engineers, Including Mining 

Safety Engineers 140 — — — —

19-0000 Life, Physical, and Social Science Occupations D D D 660 660

29-0000 Healthcare Practitioners and Technical Occupations 80 44.4 44.4 180 180

29-9011 Occupational Health and Safety Specialists 50 50.0 50.0 100 100

29-9012 Occupational Health and Safety Technicians 30 — — — —

33-0000 Protective Service Occupations 100 100.0 100.0 100† 100

33-9032 Security Guards 90 90.0 90.0 100 100

37-0000

Building and Grounds Cleaning and Maintenance 

Occupations 60 13.3 13.3 450 450

37-2011

Janitors and Cleaners, Except Maids and Housekeeping 

Cleaners 50 12.8 12.8 390 390

43-0000 Office and Administrative Support Occupations 480 4.2 4.2 11,490 11,490

43-1011

First-Line Supervisors of Office and Administrative 

Support Workers 20 3.1 3.1 640 640

43-3031 Bookkeeping, Accounting, and Auditing Clerks 40 5.5 5.5 730 730

43-3051 Payroll and Timekeeping Clerks 20 16.7 16.7 120 120

43-5032 Dispatchers, Except Police, Fire, and Ambulance 90 32.1 32.1 280 280

43-5081 Stock Clerks and Order Fillers 110 13.3 13.3 830 830

43-6014

Secretaries and Administrative Assistants, Except Legal, 

Medical, D D D 1,110 1,110

43-9061 Office Clerks, General 110 5.3 5.3 2,080 2,080

Coal Mining Occupations Coal Mining Employment

Manufacturing, 

Construction and 

Transportation 

Employment
50

Table 24: Coal Mining Employment and the Distribution of Occupations: West Virginia, (continued)

Occupation Code Name Entire State

As percent of State 

Manufacturing, 

Construction & 

Transportation 

Employment

As percent of State's 

ARC Counties' 

Manufacturing, 

Construction & 

Transportation 

Employment Entire State

Appalachian 

Portion

00-0000 Total all occupations 12,780 12.3 12.3 104,210 104,210

47-0000 Construction and Extraction Occupations 6,440 28.8 28.8 22,350 22,350

47-1011

First-Line Supervisors of Construction Trades and 

Extraction Work 890 36.9 36.9 2,410 2,410

47-2061 Construction Laborers 180 2.9 2.9 6180† 6,180

47-2073

Operating Engineers and Other Construction 

Equipment Operators 1,210 48.2 48.2 2,510 2,510

47-2111 Electricians 860 41.5 41.5 2,070 2,070

47-5041 Continuous Mining Machine Operators 570 — — — —

47-5042 Mine Cutting and Channeling Machine Operators 280 — — — —

47-5049 Mining Machine Operators, All Other 40 — — — —

47-5061 Roof Bolters, Mining 1,610 — — — —

47-5081 Helpers--Extraction Workers 460 — — — —

47-5099 Extraction Workers, All Other D D D — —

49-0000 Installation, Maintenance, and Repair Occupations 1,520 16.6 16.6 9,180 9,180

49-1011

First-Line Supervisors of Mechanics, Installers, and 

Repairers 240 35.3 35.3 680 680

49-2092 Electric Motor, Power Tool, and Related Repairers 60 — — — —

49-3031 Bus and Truck Mechanics and Diesel Engine Specialists 60 6.1 6.1 980 980

49-3042 Mobile Heavy Equipment Mechanics, Except Engines 480 137.1 137.1 350† 350

49-9041 Industrial Machinery Mechanics 80 7.1 7.1 1130† 1,130

49-9043 Maintenance Workers, Machinery 80 53.3 53.3 150 150

49-9071 Maintenance and Repair Workers, General 470 29.9 29.9 1,570 1,570

49-9098

Helpers--Installation, Maintenance, and Repair 

Workers 30 6.1 6.1 490 490

51-0000 Production Occupations 560 2.1 2.1 27,050 27,050

51-1011

First-Line Supervisors of Production and Operating 

Workers 60 2.4 2.4 2,460 2,460

51-4121 Welders, Cutters, Solderers, and Brazers 110 6.6 6.6 1,670 1,670

51-8099 Plant and System Operators, All Other D D D — —

51-9021

Crushing, Grinding, and Polishing Machine Setters, 

Operators, and Tenders 50 — — — —

51-9061 Inspectors, Testers, Sorters, Samplers, and Weighers 240 15.9 15.9 1,510 1,510

53-0000 Transportation and Material Moving Occupations 2,790 12.4 12.4 22,480 22,480

53-1031

First-Line Supervisors of Transportation and MaterialMoving Mach 190 43.2 43.2 440 440

53-3032 Heavy and Tractor-Trailer Truck Drivers 310 4.2 4.2 7,410 7,410

53-7011 Conveyor Operators and Tenders 350 — — — —

53-7021 Crane and Tower Operators 30 30.0 30.0 100† 100

53-7032

Excavating and Loading Machine and Dragline 

Operators 700 411.8 411.8 170 170

53-7033 Loading Machine Operators, Underground Mining 330 — — — —

53-7041 Hoist and Winch Operators 30 — — — —

53-7062

Laborers and Freight, Stock, and Material Movers, 

Hand 250 4.6 4.6 5,490 5,490

53-7072 Pump Operators, Except Wellhead Pumpers D D D — —

53-7111 Mine Shuttle Car Operators 510 — — — —

Source: West Virginia Dept of Commerce 2016 Estimates/Bureau of Labor Statistics 2016 Occupational Employment Statistics 

D indicates coal industry occupation data not disclosed by state agencies 

— indicates absence of occupation in any industry

†Indicates employment undisclosed for at least one of three industries; partial sum

Coal Mining Occupations Coal Mining Employment

Manufacturing, 

Construction and 

Transportation 

Employment
51

5. Summary and Recommendations: Subtask 1

The problems confronting coal regions in Appalachia and across the country are daunting. Morris 

(2016) notes that for the nation as a whole, as much as $2.3 billion will be needed for pension 

assurance, $3 billion for mine reclamation, plus spending on training and infrastructure. She puts the 

price tag “...easily in the tens of billions of dollars over a decade.” There is certainly disappointment 

in coal country at what has not been done; there will also likely be disappointment in ten years at 

what was not done. 

One feature of the decline of coal employment is that the number of jobs lost is small relative to 

total employment. This means that the nation and even most individual states should be able to 

absorb the losses relatively quickly. However, though the share of jobs lost is not overwhelming at an 

aggregate level, because it is geographically concentrated, for the coal-employment regions the losses 

are devastating. Without assistance, the losses will result in a sustained economic crisis. The rural and 

often relatively remote locations of many coal mining jobs compound the problems faced by coal 

counties.

As documented above, many coal regions in the Appalachian Region have been devastated by 

long-term and near-term declines in the fortunes of the coal industry. Much of this is due to 

technological innovations, but public policy has played a role as well. These problems are ongoing and 

workers in many counties of Appalachia are struggling to find alternative employment opportunities.

The needs are compelling and immediate and similar to the problems encountered in the context of 

other structural processes of labor market adjustment.9 We provide the following recommendations 

for consideration.

• Economic base studies are needed that document the strengths and weaknesses of 

regional economies centered around coal-employment and coal-production communities.

Complementary analyses are required of local labor markets to help enable the matching 

of worker skills and needs with those of employers and potential employers. These studies 

should seek to identify viable employment alternatives to employment in the coal sector.

If it is not practical or cost-effective to promote alternative engines of economic 

development, then assistance should be provided to encourage workers to pursue 

employment opportunities outside their current place of residence. Policy should not be 

used to encourage people to remain in regions that will remain depressed.

• Transitional assistance to workers and families should be evaluated as a possible policy 

tool. One facet would focus on transitioning workers to alternative places of employment, 

both within workers’ commuting ranges and beyond. Providing homeowners with financial 

assistance may increase their ability to move from origin regions with a severely 

depressed real estate market. The inability to sell a home for lack of buyers could prevent 

 9 For example, see Autor et al. (2013) who explore the local consequences of adjustment in the face of rising 

imports from China. 
52

mobility while leaving, and letting the mortgage and/or property taxes go into default

would add further hardship to local governments and regional economies. For older 

workers, assistance for transitioning from work to retirement should also be considered.

• Little is known about the detailed characteristics of coal workers in Appalachia. There are 

spotty data from the Region as well as more detailed national data, but together this 

information paints an inadequate picture of coal workers and their many characteristics in 

the Appalachian Region. This information is essential to the design and implementation of 

people-based policies of economic development, and in particular with education and 

training programs. Worker and establishment surveys could provide rich data to inform the 

policymaking process.

• A re-development fund could be capitalized using coal severance tax revenue, general tax 

revenue, and potentially federal funds with the intent of providing assistance to workers 

and communities. These funds could be used to help support the recommendations made 

above through various forms of expenditures. Funds might also be used to provide 

financial support to entrepreneurs through a revolving loan fund, loan subsidies, or loan 

guarantees.

Subtask 2: The Education Pipeline

The discussion in Subtask 1 above focused primarily on current labor market conditions and 

occupational patterns in the coal industry compared to other sectors of the Appalachian Region.

Attention in Subtask 2 turns to public funding and expenditure patterns that will affect the future 

labor force through the support of elementary and secondary education.

Local tax revenues are an important source of funding for K-12 education, complementing receipts 

from the federal government and state governments. Declines in the economic base arising from 

contractions in coal employment and coal production can affect virtually all state and local revenue 

sources either directly or indirectly through ripple effects that spill across economic sectors and 

communities. Sales and gross receipts taxes may fall from reduced consumer spending; the same 

revenue sources can be adversely affected by reduced business-to-business transactions, many of 

which are subject to taxation. Personal income taxes may suffer through reductions in wage and 

salary income as well as other forms of income like rental and pass-through income from limited 

liability business entities. Corporate income taxes may suffer directly and indirectly through reduced 

firm profitability. The property tax will face downward pressure from any reductions in business 

activity and residential housing activity. Because of the way in which the property tax base is 

determined for tax purposes through re-assessments, negative effects on the property tax may lag 

behind declines in coal-related activity. In general, taxes are tied to economic activity, and when this 

activity is reduced, so too are tax revenues.
53

To provide a sense of how important coal employment is to state and local revenue generation, 

consider the results of an economic impact assessment of West Virginia’s coal industry that was 

conducted for this report.10 The impact estimates were arrived at using the well-established IMPLAN 

modeling framework that estimates indirect and induced economic effects that arise from direct 

activity in the coal industry. Based on direct employment of 14,577 coal workers in West Virginia, 

total state and local taxes are estimated to be $335.6 million, or $23,023 per direct job. Of this total, 

$161.5 million in revenue accrues to the state and local property tax alone, translating to $11,082 per 

direct job in the coal sector. These figures highlight the potential revenue risk associated with 

reductions in coal industry employment.

In practice, the extent and impact of these negative revenue consequences will depend on the 

magnitude of coal-related contractions in the economic base, the nature of state aid programs for 

education, the structure of local revenue sources, and the behavioral response of the statewide and 

local electorate in affected communities. For some communities, changes in coal activity are modest, 

which means revenue consequences for public schools and other public services will also be modest.

Other counties have seen significant changes, and more significant changes may be on the horizon.

These communities will struggle to meet public service delivery needs. Weakened revenue raising 

ability at the local level may translate into higher state education aid through funding equalization 

programs. In places where there is local control over tax rates, it may be possible to mitigate the 

consequences of declining tax bases with rate increases. But raising rates in the face of declining tax 

bases can be politically daunting, to say the least. Some of the pressure on school finances might be 

reduced through the outmigration of families with children of school age. In fact, as discussed more 

fully below, there has been a widespread reduction in school-age enrollments in most broad coalemployment regions of Appalachia. This translates into reduced state and federal aid that is tied to 

student enrollment counts. In addition, school systems may find that they have excess capacity in 

terms of instructional staff (including shrinking class sizes) and the schooling capital stock. Winding 

these resources down to match declining enrollment counts will create further disruptions in the 

community and local government budgets. In the near term, these excess capacity costs will be an 

additional burden to serve delivery responsibilities. Policy options include school closings and 

system/function consolidations.

The analysis that follows digs deeper into elementary and secondary education finance and 

spending patterns for 129 coal-employment counties across Appalachia. The discussion begins with an 

overview of state funding programs that transfer resources to local school districts to support 

elementary and secondary education. The focus then turns to the performance of local government 

revenue collections. Local revenue performance is important since it is the locally-determined

foundation for funding public schools—healthy overall revenue streams will help support fiscal health 

for public schools. A key finding is relatively low tax collections and low tax effort on the part of many 

 10The authors would like to thank Eric Bowen, Christiadi and John Deskins, who are affiliated with the Bureau 

of Business and Economic Research at West Virginia University, for providing these estimates. 
54

coal communities that could hamper school funding and the ability to support the delivery of other 

locally-provided public services. We then consider education funding sourced by federal, state, and 

local governments. Most of the evidence on taxes and school spending that is presented in the analysis 

below yields few symptoms of broad-based weakening of overall fiscal health, or more specifically,

support for K-12 education in coal communities in the Appalachian Region. Importantly, current 

spending per pupil, at least on average, is relatively high in coal communities and this spending has 

improved relative to the national average since 2010. However, nominal current spending per pupil 

fell in Kentucky, Virginia, and West Virginia between 2010 and 2014, as well as in a number of 

counties in Alabama, Ohio and Tennessee.

1. State K-12 Funding Programs

State funding formulas for elementary and secondary education determine the amount of state 

revenues that flow to local schools. These formulas typically affect the level of locally-provided

funding support as well, through matching and/or local funding requirements. Of particular interest is 

the way that these formulas respond to changes in local tax capacity, or changes in the ability to 

generate revenue from own-source local tax bases. Declines in the CIE can be expected to put 

downward pressure on all local revenue sources, from traditional tax bases to fees and charges, as 

discussed above. Most funding formulas directly account for local tax capacity and steer more revenue 

toward lower-capacity school districts. Thus as the coal industry wanes and tax bases suffer, more 

revenue should flow to affected systems. In various ways, the formulas try to provide some degree of 

equalization that narrows spending differentials across high and low tax capacity districts. Tax effort, 

or the extent to which local tax bases are actually used to support revenue generation, is also an 

important element of many funding formulas. Absent effort requirements, some local communities 

may simply choose to provide less local funding support when state aid is forthcoming. Tax effort 

requirements are intended to raise overall spending above levels that would otherwise take place at 

the local level.

In practice, the way in which state aid formulas respond to changes in local capacity is very 

complicated. In the simplest case, a school district’s capacity changes and the formula determines the 

consequences for state aid and potentially locally-required funding support. But in other contexts, 

there are many moving parts that need to be accounted for. For example, formulas are typically tied 

to some measure of enrollments. When economic conditions deteriorate, people may leave the 

community, meaning lower enrollments. Declining economic conditions may also lead to policy 

changes that raise or lower local tax effort. States may also choose to change the nature of the 

funding formula for any of a number of reasons and this will ripple across school systems.

A concise state-by-state synopsis of funding formulas follows:
55

1.1 Alabama

Alabama’s foundation funding formula is unit-based. The “foundation” is intended to provide a 

basic level of state-supported education funding that can then be topped off by local support. The 

state determines each district’s number of instructional units based on the prior year’s average daily 

membership (ADM). Total revenue needed for instructional costs like salaries and benefits (based on 

prescribed student-teacher ratios), and ADM-dependent expenses like textbooks and materials are 

based on the number of grade-level weighted instructional units the district is assigned. State 

instructional funding responsibility to the district is then determined by reducing unit-based 

instructional costs by 10 mills of expected local property. Reduced tax capacity from declining coal 

activity would translate into higher state funding. In the event of unexpected enrollment growth, 

districts are allocated additional instructional units.

Block grants are provided by the state for transportation, school nurses, and other noninstructional costs, and are not weighted based on grade level. Capital costs are power-equalized by 

the state; the state matches locally-raised funds for capital improvements such that each mill of local 

effort provides the same amount of revenue. As with operating costs, this funding system would 

provide more support to local systems should tax capacity decline.

Alabama school districts do not levy taxes; counties and cities levy property and sales taxes which 

fund local participation in the foundation program (Verstegen 2015, 1-4). In the event of shortfalls to 

state revenue, proration may occur. The state has set up a proration trust fund to prevent funding 

gaps (AL Const. amend. 856).

1.2 Kentucky

Kentucky’s formula for funding K-12 education—called the Support Education Excellence 

in Kentucky program, or SEEK—utilizes both foundation and equalization programs.11 A per-pupil base 

is legislated in the state’s biennial budget. The state calculates adjusted average daily attendance 

(AADA) each year, with weights for exceptional students and predicted enrollment growth built in. 

Districts receive SEEK funding based on AADA. A minimum local effort of 3 mills of tax on property and 

motor vehicle assessments is required by each district as well as a half mill of effort earmarked for 

capital costs (Verstegen 2015, 87-89). The state’s two-tiered approach allows districts to raise 

 11 Foundation aid represents a minimum grant provided by the state, typically on a per pupil or weighted per 

pupil basis. Equalization aid accounts for differential tax capacity across school districts and can be implemented 

in a number of different ways. For example, a guaranteed tax base (GTB) is a matching grant that ensures an equal 

per pupil tax base across school districts.
56

additional revenue. Reductions in tax capacity would diminish the amount of revenue generated from 

these minimum effort requirements; rates could be increased to sustain revenues.

Tier I equalization lets districts raise funding beyond SEEK levels and also receive additional state 

support. Districts may levy an equivalent tax rate (ETR) that generates up to 15 percent of total 

calculated SEEK funding. If the currently levied rate exceeds this ETR, the maximum additional 

revenue the district can be expected to generate is capped according to its relative property tax 

wealth. For example, the state provides 60 percent of maximum Tier I funding for a district with 40 

percent of the state average property tax wealth. Tier II funding allows districts to levy a 

supplementary tax to raise up to 30 percent of the total of SEEK and Tier I funding; the state does not 

supplement this (Kentucky Department of Education 2015, 5-7).

Capital costs are funded by an additional earmarked half-mill of local effort and are subject to 

the same equalization arrangement as Tier I funding when used for debt; Kentucky provides $100 per 

AADA (Verstegen 2015, 89). The state maintains the right to adjust SEEK funding according to 

availability of funds (Kentucky Department of Education 2015, 9).

1.3 Maryland

Maryland elementary and secondary education funding consists of three categories: general aid, 

targeted aid, and other funds (e.g., for transportation and capital outlays). General aid includes: 

foundation funding, the guaranteed tax base (or GTB), and funding for Geographic Cost of Education 

Indexing (GCEI). Targeted aid for special education students is allocated based on weighted full time 

equivalent students (FTE) (Verstegen 2015, 104).

Maryland’s foundation per-pupil base is the 2008 level adjusted yearly for inflation (Maryland 

Department of Legislative Services 2014, 70-72). The county share of the program is based on taxable 

property and net taxable income. The GTB program further equalizes costs for counties with wealth 

less than 80 percent of the statewide average (the guaranteed base), so long as the county’s 

appropriations already surpass the required foundation county share—i.e., local tax effort is relatively 

high. The county’s existing tax rate is applied to the difference between the guaranteed base and 

their own, incentivizing funding beyond local share. Per-pupil allocations under the GTB are capped at 

20 percent of the foundation per pupil amount (Maryland Department of Legislative Services 2014, 

85). Maryland also provides additional money to counties with above average education costs through 

its GCEI. The GCEI accounts for higher energy costs, cost of living (based on home prices), as well as 

wages needed to draw personnel to less attractive schools (Imazeki 2015, 13).
57

Counties distribute property and income tax revenue to fiscally-dependent districts. No minimum 

tax effort is required by Maryland, but counties may not decrease per-pupil funding. However, the 

state may require additional effort from counties with below state average education effort (local 

education funding relative to local wealth) (Verstegen 2015, 107). Counties may apply for waivers if 

unable to meet these requirements and may receive additional state funding to make up for lacking 

local funds (Chechovich 2016, 10).

1.4 Mississippi

Mississippi’s Adequate Education Program (MAEP) per-student base cost is calculated every four 

years based on the average cost to educate students at schools the state deems “successful and 

efficient” (Verstegen 2015, 121). In intermediate years, 40 percent of the base cost is adjusted for 

inflation. Special categories of students are funded separately. Total district funding under MAEP is 

the sum of ADM-based allocations and categorical funding for special types of students. 

Minimum required district effort is the equivalent of 28 mills of property tax (not to exceed 55 

mills except by referendum). Reductions in tax capacity would reduce the amount of revenue 

generated from the minimum effort requirement because tax bases have shrunk. Local funding sources 

include property tax and tuition revenues (Verstegen 2015, 123). However, district share is capped at 

27 percent of MAEP program costs. Wealthier districts do not receive more state funds as they spend 

more from local sources. (EdBuild 2017, 5).

1.5 Ohio

The Ohio General Assembly legislates the minimum per-pupil spending level biennially. A State 

Share Index (SSI) based on property tax capacity and relative district median income is applied to the 

bulk of state-calculated funding totals. Districts are responsible for the difference between calculated 

funding and the state’s share. Districts may levy income taxes on residents in addition to traditional 

school property taxes. The state guarantees a total level of funding not less than the foundation total 

in the previous biennium but caps growth at 7.5 percent (Ohio Department of Education 2016, 17).

Targeted Assistance and Capacity Aid are equalization programs that may offset a portion of 

district share for places with low capacity. Under Targeted Assistance, Ohio ranks district per-pupil 

wealth (based on property value and income) and provides 6 mills on the difference between district 

and threshold wealth (i.e. the district ranked 490th out of all districts); districts are also eligible if 

agricultural real property makes up 10 percent of total real property values (Ohio Department of 

Education 2016, 7-9). Capacity Aid, a second offset, was introduced in the previous biennium and is 
58

based solely on district relative property tax capacity (Ohio Department of Education 2016, 16). 

Responsibility for capital costs is apportioned based on property wealth per student (Verstegen 2015, 

170).

1.6 Pennsylvania

Prior to the 2015 fiscal year, Pennsylvania was one of three states without a set education funding 

formula. Instead, the state guaranteed districts a 2 percent bump in funding each year regardless of 

enrollment shifts. Now, the Pennsylvania Senate Basic Education Funding (BEF) Commission 

recommends appropriations for K-12 basic aid in each fiscal year’s budget; provisions for 

transportation, capital outlays, and special and technical education, among others, are made 

separately.

BEF appropriations are apportioned based on districts’ adjusted, weighted ADM. District ADMs are 

weighted for enrollments in the following categories: poverty, acute poverty, concentrated poverty, 

limited English language abilities, and charter school membership; ADM is also adjusted for population 

density. Local effort, capacity, and median household income indices are applied to the new ADM. 

Districts receive state funding based on their share of the state’s total adjusted weighted ADM. While 

no per-pupil base exists in the new funding formula, districts are guaranteed to receive a minimum of 

FY 2014 funding levels. School districts levy their own income and property taxes to fund costs not 

covered by state-distributed funds (Basic Education Commission 2015).

1.7 Tennessee

Tennessee’s Basic Education Program (BEP) funding formula is ADM-based and tied to various 

expenditure categories. On average, the BEP pays for 75 percent of instructional costs (including 

benefits), 75 percent of classroom support (materials, technology, etc.), and 50 percent of nonclassroom administrative and maintenance costs (including capital outlays). The formula accounts for 

school system ability to pay through a county Fiscal Capacity Index (FCI). School districts in counties 

with greater fiscal capacity shoulder a larger share of their BEP total costs. Districts receive at 

minimum the prior year’s funding, adjusted for enrollment and salary changes. The last component of 

funding is the Cost Differential Factor, which provides additional funds for places with high 

community-wide salaries which are believed to raise schooling costs (Tennessee Department of 

Education 2016).
59

Local funding comes mainly from property and sales taxes, with no required minimum tax effort. 

City school districts may receive additional appropriations from city government, and special school 

districts may levy their own property tax with permission from the legislature (Verstegen 2015, 201).

1.8 Virginia

Virginia K-12 funding includes five categories: Standards of Quality (SOQ), categorical, 

supplemental, incentive, and lottery aid. For FY 2015, SOQ funding represented 91 percent of total 

state aid. The state’s Joint Legislative Audit Review Committee (JLARC) calculates the minimum 

funding per pupil by county necessary to meet the state’s SOQ. The state reduces total county funding 

for basic aid (the majority of SOQ funding) by the county’s share of a .0125 percent sales tax. 

Apportionment is based on the county’s share of state school-aged population. The remainder is split 

between the state and county based on the Local Composite Index (LCI), which approximates the 

county’s ability to pay (i.e., tax capacity) (Verstegen 2015, 222-223).

The LCI measures a county’s retail sales and adjusted gross income tax wealth relative to the 

state’s. The state calculates the LCI so that i) the state pays 55 percent of LCI-adjusted funding and 

ii) no county receives less than 20 percent or more than 80 percent of total aid from the state

(Dickey, 2009). The General Assembly has revised the SOQ to shift financial burdens away from the 

state, most notably during the Great Recession (Duncombe and Cassidy 2016, 1-3).

School districts are fiscally dependent; local shares of funding come from county property, sales,

and special tax revenues (Verstegen 2015, 230).

1.9 West Virginia

West Virginia’s Public School Support Program (PSSP) is a foundation formula based on net 

enrollment and school-age population density. If county net enrollment does not meet a threshold of 

1,400, the state adjusts the number upward (West Virginia Department of Education 2015, 8). This, in 

combination with preferential funding ratios for teachers, personnel, and transportation based on 

student density, ensures that sparsely-populated counties receive more funding per pupil for 

educators and staff members, whose minimum salaries are set by the state (West Virginia Department 

of Education 2015, 2). This provision in principle provides some protection to rural communities that 

are dependent on coal production and employment. While counties may supplement salaries using 

local funds, salary equity law caps supplementation to ten percent of the lowest-paid employee of 

similar education and experience. Foundation allowances for instructional improvement, technology, 
60

and other programs are based solely on adjusted net enrollment and are unaffected by local capacity 

or effort (West Virginia Department of Education 2015, 8).

West Virginia requires the same amount of tax effort from each county, levied on four classes of 

property (1.94 mills on Class I Property, 3.88 mills on Class II, and 7.76 mills on Classes III and IV); 

beyond required effort, counties may levy additional taxes on the same four classes of property 

capped at the state rates (West Virginia Department of Education 2015, 5).

1.10 Summary

Perhaps the most important takeaway from this discussion is the complexity of the various funding 

schemes across the states. At the same time, it is rather clear that the state funding formulas 

generally account in some way for local tax capacity and/or tax effort. This should offer some 

protection to local school systems that witness deterioration in local fiscal conditions. However, 

funding formulas typically do not hold local school districts completely harmless for losses in local tax 

capacity; i.e., own source revenue losses are never fully replaced by state aid. Another important 

point is that both the state and their constituent local governments hold fate in their own hands when 

it comes to funding elementary and secondary education. As discussed below, the Appalachian states 

and many coal-employment communities have untapped tax capacity that can be used to fund public 

education.

2. Local Government Taxes and Burdens

Local government revenue performance will directly affect the ability to provide public education 

and other locally-provided services. Total local government tax revenue, population and local tax 

burden data are provided in Table 25 for the 2007 and 2012 Census of Government years to frame the 

revenue performance and fiscal health of coal-employment communities. As with the analysis in 

Subtask 1 presented above, we focus on a number of key geographies, including states that are either 

partially or wholly in Appalachia, coal-employment communities in the Appalachian Region, the entire 

Appalachian Region, and the United States as a whole. For all local governments across the country, 

taxes per capita stood at $1,875 in 2012, compared to $1,224 for counties in the Appalachian Region

and $1,297 for coal communities within Appalachia. The relative per capita burden in coal 

communities was just 69.2 percent (i.e. $1,298/$1,875) of the national average and 63.9 percent (i.e. 

$1,298/$2,032) of the average of states that are either partially or wholly in Appalachia in 2012.

Relative per capita burdens were only 48.7 percent of the Appalachian statewide average in West 

Virginia and 32.6 percent of the average in Kentucky.
61

Table 25: Local Government Total Taxes for States and Other Geographies in Appalachia, 2007 and 

2012

Local Total Local Total

Government Personal Government Personal

Total Taxes Income Total Total Taxes Income Total

Area (thous $) (thous $) Population (thous $) (thous $) Population 2007 2012 2007 2012

Alabama 4,642,148 152,246,048 4,672,840 5,165,992 170,881,367 4,815,960 $ 993 $1,073 3.05% 3.02%

Appalachian Alabama 3,034,183 100,709,839 2,993,512 3,337,291 113,244,852 3,082,381 $1,014 $1,083 3.01% 2.95%

Coal Counties, Alabama 1,859,184 51,931,538 1,406,520 1,979,118 57,286,886 1,440,384 $1,322 $1,374 3.58% 3.45%

Non-Appalachian Alabama 1,607,965 51,536,209 1,679,328 1,828,701 57,636,515 1,733,579 $ 958 $1,055 3.12% 3.17%

Georgia 14,836,604 332,074,930 9,349,988 15,592,462 365,480,928 9,914,668 $1,587 $1,573 4.47% 4.27%

Appalachian Georgia 4,069,260 89,150,001 2,805,474 4,243,798 99,185,573 2,997,461 $1,450 $1,416 4.56% 4.28%

Coal Counties, Georgia – – – – – – – – – – 

Non-Appalachian Georgia 10,767,344 242,924,929 6,544,514 11,348,664 266,295,355 6,917,207 $1,645 $1,641 4.43% 4.26%

Kentucky 3,796,832 134,438,098 4,256,672 4,524,196 155,996,922 4,384,799 $ 892 $1,032 2.82% 2.90%

Appalachian Kentucky 621,095 28,960,405 1,181,504 781,826 34,029,685 1,183,185 $ 526 $ 661 2.14% 2.30%

Coal Counties, Kentucky 341,959 15,887,984 642,927 423,823 18,552,802 638,937 $ 532 $ 663 2.15% 2.28%

Non-Appalachian Kentucky 3,175,737 105,477,693 3,075,168 3,742,370 121,967,237 3,201,614 $1,033 $1,169 3.01% 3.07%

Maryland 10,925,407 267,773,656 5,653,408 13,112,085 314,159,795 5,889,651 $1,933 $2,226 4.08% 4.17%

Appalachian Maryland 332,046 8,021,213 250,770 426,256 9,516,942 253,094 $1,324 $1,684 4.14% 4.48%

Coal Counties, Maryland 125,055 3,026,635 104,597 197,827 3,638,432 103,879 $1,196 $1,904 4.13% 5.44%

Non-Appalachian Maryland 10,593,361 259,752,443 5,402,638 12,685,829 304,642,853 5,636,557 $1,961 $2,251 4.08% 4.16%

Mississippi 2,329,317 85,615,593 2,928,350 2,759,363 98,264,480 2,984,945 $ 795 $ 924 2.72% 2.81%

Appalachian Mississippi 388,811 16,119,633 625,219 455,741 19,011,389 629,569 $ 622 $ 724 2.41% 2.40%

Coal Counties, Mississippi 4,391 188,838 8,680 4,478 216,137 8,357 $ 506 $ 536 2.33% 2.07%

Non-Appalachian Mississippi 1,940,506 69,495,960 2,303,131 2,303,622 79,253,091 2,355,376 $ 843 $ 978 2.79% 2.91%

New York 70,862,196 908,162,948 19,132,335 80,187,183 1,053,660,783 19,602,769 $3,704 $4,091 7.80% 7.61%

Appalachian New York 2,079,639 32,037,730 1,069,195 2,448,303 37,844,236 1,060,605 $1,945 $2,308 6.49% 6.47%

Coal Counties, New York – – – – – – – – – – 

Non-Appalachian New York 68,782,557 876,125,218 18,063,140 77,738,880 1,015,816,547 18,542,164 $3,808 $4,193 7.85% 7.65%

North Carolina 10,647,270 328,369,034 9,118,037 11,738,089 376,200,549 9,746,175 $1,168 $1,204 3.24% 3.12%

Appalachian North Carolina 1,698,749 52,876,034 1,658,679 1,775,727 57,714,030 1,708,358 $1,024 $1,039 3.21% 3.08%

Coal Counties, North Carolina – – – – – – – – – – 

Non-Appalachian North Carolina 8,948,521 275,493,000 7,459,358 9,962,362 318,486,519 8,037,817 $1,200 $1,239 3.25% 3.13%

Ohio 19,937,435 408,126,658 11,500,468 20,899,220 465,139,834 11,550,839 $1,734 $1,809 4.89% 4.49%

Appalachian Ohio 2,089,193 59,728,696 2,048,579 2,168,704 68,113,122 2,027,860 $1,020 $1,069 3.50% 3.18%

Coal Counties, Ohio 1,093,677 31,468,053 1,086,902 1,171,355 36,007,028 1,071,247 $1,006 $1,093 3.48% 3.25%

Non-Appalachian Ohio 17,848,242 348,397,962 9,451,889 18,730,516 397,026,712 9,522,979 $1,888 $1,967 5.12% 4.72%

Pennsylvania 21,254,896 506,357,616 12,563,937 24,084,475 585,851,545 12,771,854 $1,692 $1,886 4.20% 4.11%

Appalachian Pennsylvania 7,792,333 203,207,105 5,784,871 8,659,225 234,977,960 5,788,440 $1,347 $1,496 3.83% 3.69%

Coal Counties, Pennsylvania 6,217,814 164,158,187 4,524,533 6,840,508 189,808,518 4,527,016 $1,374 $1,511 3.79% 3.60%

Non-Appalachian Pennsylvania 13,462,563 303,150,511 6,779,066 15,425,250 350,873,585 6,983,414 $1,986 $2,209 4.44% 4.40%

South Carolina 5,198,617 142,015,184 4,444,110 6,228,651 166,397,814 4,720,760 $1,170 $1,319 3.66% 3.74%

Appalachian South Carolina 1,128,453 36,321,644 1,127,417 1,253,478 42,576,188 1,194,278 $1,001 $1,050 3.11% 2.94%

Coal Counties, South Carolina – – – – – – – – – – 

Non-Appalachian South Carolina 4,070,164 105,693,540 3,316,693 4,975,173 123,821,626 3,526,482 $1,227 $1,411 3.85% 4.02%

Tennessee 7,277,126 210,695,574 6,175,727 7,995,185 250,285,838 6,454,306 $1,178 $1,239 3.45% 3.19%

Appalachian Tennessee 2,597,164 83,521,149 2,722,902 2,929,903 99,296,835 2,814,573 $ 954 $1,041 3.11% 2.95%

Coal Counties, Tennessee 202,575 7,468,188 268,175 232,833 8,615,015 272,946 $ 755 $ 853 2.71% 2.70%

Non-Appalachian Tennessee 4,679,962 127,174,425 3,452,825 5,065,282 150,989,003 3,639,733 $1,355 $1,392 3.68% 3.35%

Virginia 13,704,928 345,335,541 7,751,000 15,031,885 403,880,401 8,192,048 $1,768 $1,835 3.97% 3.72%

Appalachian Virginia 679,862 21,988,858 767,099 783,639 25,087,703 766,246 $ 886 $1,023 3.09% 3.12%

Coal Counties, Virginia 158,231 4,898,376 184,433 203,500 5,623,561 182,751 $ 858 $1,114 3.23% 3.62%

Non-Appalachian Virginia 13,025,066 323,346,683 6,983,901 14,248,246 378,792,698 7,425,802 $1,865 $1,919 4.03% 3.76%

West Virginia 1,436,514 53,779,085 1,834,052 1,775,955 64,623,761 1,856,560 $ 783 $ 957 2.67% 2.75%

Appalachian West Virginia 1,436,514 53,779,085 1,834,052 1,775,955 64,623,761 1,856,560 $ 783 $ 957 2.67% 2.75%

Coal Counties, West Virginia 885,074 33,377,607 1,127,727 1,125,291 39,934,019 1,136,657 $ 785 $ 990 2.65% 2.82%

Non-Appalachian West Virginia – – – – – – – – – – 

Appalachian States 186,849,290 3,874,989,965 99,380,924 209,094,741 4,470,824,017 102,885,334 $1,880 $2,032 4.82% 4.68%

Appalachian Counties, Total 27,947,302 786,421,392 24,869,273 31,039,846 905,222,276 25,362,610 $1,124 $1,224 3.55% 3.43%

Coal Counties, Total 10,887,960 312,405,406 9,354,494 12,178,733 359,682,398 9,382,174 $1,164 $1,298 3.49% 3.39%

Non-Appalachian Counties, Total 158,901,988 3,088,568,573 74,511,651 178,054,895 3,565,601,741 77,522,724 $2,133 $2,297 5.14% 4.99%

UNITED STATES 526,028,677 11,995,419,000 301,231,207 588,804,387 13,904,485,000 313,998,379 $1,746 $1,875 4.39% 4.23%

Source: U.S. Census Bureau, Census of Governments 2007 and 2012; Bureau of Economic Analysis; and U.S. Census Bureau, Population Division

Notes: Coal counties are those counties with coal mining employment in 2010 as reported in the annual employment and production data file from the U.S. Mine Safety and 

Health Administration (MSHA) <https://arlweb.msha.gov/OpenGovernmentData/DataSets/MinesProdYearly.zip>.

Appalachian States is the sum of all states in the Appalachian region.

2007 2012 Local Government Total Taxes: 

Personal 

Per Capita Income
62

One explanation for these relatively low tax burdens in coal-employment communities and the 

Region as a whole is low tax capacity. In general, poorer communities will have lower tax capacity 

than higher-income places. A good measure of capacity or ability to pay is county personal income, 

which is a resident-based measure of income that accrues from all sources, from wages and salaries to 

transfer income.12 For individuals and households, local sales and property taxes, along with other 

taxes and fees, are paid from personal income. Data from Table 9 (above) indicate that per capita 

income in coal-employment counties ($45,268) is 94.1 percent of the national average ($48,131). This 

is indicative of low tax capacity. However, the data in Table 25 show that revenues in coal 

communities are just 69.2 percent of the national average as noted above. Thus, relatively low 

incomes do not fully explain low revenue collections.

As noted above, tax effort is the extent to which own-source tax bases are utilized relative to 

revenue-generating capacity. In practice, tax effort may be defined as the ratio of taxes to personal 

income, with personal income serving as the measure of capacity. Tax effort might be viewed as a 

combination of fate and choice, especially in the short run. On one hand, capacity is fixed and 

constrained, and largely beyond the influence of policymakers, in the short run; employment levels 

are determined, compensation levels are set and so on. However, voters and elected officials can 

often affect tax effort through the choice of tax rates and/or bases. In practice, these choices may be 

constrained by state constitutions and legislative action. For example, states commonly require 

uniform and fairly assessed property tax bases. Property tax rates may be chosen by local 

communities, though they may also be constrained by state statute. In Alabama, local governments 

have considerable discretion over sales tax rates and bases. Local policy flexibility and practice varies 

across the states in Appalachia.

The data in the final two columns of Table 25 present tax effort figures, as measured by the ratio 

of taxes collected to personal income, while Figure 5 provides a snapshot of burdens for 2012 across 

the Appalachian Region. The data reveal the low tax effort of coal-employment counties (as well as 

many other counties) in Appalachia. In both 2007 and 2012, coal-employment communities had 

smaller tax burdens as a share of local personal income than all other broad geographies shown in 

Table 25, averaging 3.49 percent and 3.39 percent in each of the two years. For 2012, this is 80.1 

percent of the United States average. Coal communities in Mississippi and Kentucky had the smallest 

tax burdens as a share of personal income of any of the geographies shown in the table. For these two 

states, burdens in 2012 were only 44.2 percent and 48.7 percent of the Appalachian statewide 

average, respectively, and 48.9 and 53.9 percent of the national average. A number of coalemployment counties have exceptionally low tax burdens that are less than 2.0 percent of personal 

income, including ten in Kentucky, three in Alabama, one in Virginia, and six in West Virginia. The 

 12 Personal income includes wages and salaries, farm and nonfarm proprietors’ income, rent, interest, dividends 

and transfer payments. Income is assigned to where people live. For example, if an individual resides in one county 

but earns wage income in an adjacent county or another state, that income is assigned based on where the worker 

lives, not where individual works.
63

combination of low capacity and low effort may compromise the ability to fund local schools and 

other public services.

Figure 5: Local Tax Revenue as a Share of Total Personal Income, Appalachian Counties, 2012

Source: U.S. Census Bureau, Census of Governments 2012 and Bureau of Economic Analysis.

Nominal local government tax collections per capita were up modestly between 2007 and 2012, 

with growth dampened by the impacts of the Great Recession. This was a period of relative stability 

for coal employment in the Region, preceding the sharp reductions in employment that transpired in 

Appalachia in subsequent years. Nominal taxes per capita were up 11.4 percent in coal-employment 

communities versus 8.9 percent revenue growth for all Appalachian counties and 8.1 percent revenue 

growth for states that are either partially or wholly in Appalachia. Surprisingly, several coalOHIO

KENTUCKY

TENNESSEE

MISSISSIPPI

ALABAMA

GEORGIA

SOUTH

CAROLINA

NORTH CAROLINA

VIRGINIA

MARYLAND

PENNSYLVANIA

NEW YORK

WEST

VIRGINIA

Less than 2.00%

2.00% to 2.99%

0 50 100

Miles

4.00% and higher

3.00% to 3.99%
64

employment regions have seen much stronger growth in per capita local tax collections. For example, 

coal counties in West Virginia, Kentucky and Pennsylvania had growth of 26.1 percent, 24.6 percent 

and 10.0 percent. Taxes as a share of personal income were up in coal-employment communities in 

Kentucky, Maryland, Virginia and West Virginia, and down in Alabama, Mississippi, Ohio, Pennsylvania 

and Tennessee. Note that 2012 burdens as a share of personal income were down for all five broad 

regions summarized at the bottom of Table 25 compared to 2007, a likely legacy of the Great 

Recession.

Tax portfolios vary across states based on a number of factors, including constitutions and 

statutes, public policy choices, and historical inertia. As shown in Table 26, Appalachian counties and

non-Appalachian counties rely on the property tax for about two-thirds of all local own-source tax 

collections. While this may seem high, it is actually below the national average of 73.5 percent. The 

property tax is an especially important revenue source for K-12 education not just because of its size, 

but also because local control can be exercised to affect collections through rate adjustments. On 

average, coal communities place roughly similar reliance on the property tax as other local 

governments. However, as one would expect, there is considerable variation around this average. For 

example, Alabama is least reliant on the property tax with only 43.5 percent of revenues coming from 

the tax in coal-employment communities; Mississippi is most reliant, with well over 90 percent of all 

collections coming from the property tax for all geographies considered. Local communities in West 

Virginia are highly reliant on the property tax, as it represents 77.4 percent of local tax collections.
65

Table 26: Local Government Major Taxes as a Share of Total Taxes for States and Other Geographies 

in Appalachia, 2012

Area

Property

Tax

Total Sales & Gross Receipts

Tax

Total

Income

Taxes

Severance

Tax

Other 

Taxes

Alabama 43.2% 42.1% 2.0% 0.1% 12.7%

Appalachian Alabama 45.1% 39.7% 2.8% 0.1% 12.4%

Coal Counties, Alabama 43.5% 37.9% 3.9% 0.1% 14.6%

Non-Appalachian Alabama 39.8% 46.4% 0.4% 0.0% 13.3%

Georgia 66.0% 31.6% 0.0% 0.0% 2.4%

Appalachian Georgia 65.6% 32.6% 0.0% 0.0% 1.7%

Coal Counties, Georgia – – – – – 

Non-Appalachian Georgia 66.1% 31.2% 0.0% 0.0% 2.7%

Kentucky 57.5% 12.7% 27.4% 0.0% 2.4%

Appalachian Kentucky 59.8% 17.7% 18.4% 0.0% 4.1%

Coal Counties, Kentucky 61.2% 17.2% 17.7% 0.0% 3.9%

Non-Appalachian Kentucky 57.0% 11.7% 29.3% 0.0% 2.0%

Maryland 55.7% 5.8% 33.3% 0.0% 5.3%

Appalachian Maryland 69.0% 2.6% 23.5% 0.0% 4.9%

Coal Counties, Maryland 74.2% 3.9% 18.0% 0.0% 3.9%

Non-Appalachian Maryland 55.2% 5.9% 33.6% 0.0% 5.3%

Mississippi 93.1% 3.8% 0.0% 0.0% 3.1%

Appalachian Mississippi 95.4% 1.7% 0.0% 0.0% 2.9%

Coal Counties, Mississippi 97.1% 1.5% 0.0% 0.0% 1.5%

Non-Appalachian Mississippi 92.7% 4.2% 0.0% 0.0% 3.1%

New York 59.3% 19.0% 18.3% 0.0% 3.4%

Appalachian New York 73.0% 25.1% 0.0% 0.0% 1.9%

Coal Counties, New York – – – – – 

Non-Appalachian New York 58.9% 18.8% 18.9% 0.0% 3.4%

North Carolina 75.8% 21.5% 0.0% 0.0% 2.7%

Appalachian North Carolina 76.1% 21.4% 0.0% 0.0% 2.5%

Coal Counties, North Carolina – – – – – 

Non-Appalachian North Carolina 75.7% 21.5% 0.0% 0.0% 2.8%

Ohio 64.9% 9.7% 22.2% 0.0% 3.2%

Appalachian Ohio 72.1% 12.1% 11.7% 0.0% 4.1%

Coal Counties, Ohio 69.4% 12.8% 13.6% 0.0% 4.2%

Non-Appalachian Ohio 64.0% 9.5% 23.4% 0.0% 3.1%

Pennsylvania 70.7% 5.1% 18.8% 0.0% 5.4%

Appalachian Pennsylvania 75.4% 3.9% 15.4% 0.0% 5.2%

Coal Counties, Pennsylvania 73.3% 4.9% 16.2% 0.0% 5.6%

Non-Appalachian Pennsylvania 68.1% 5.7% 20.7% 0.0% 5.6%

South Carolina 78.2% 10.5% 0.0% 0.0% 11.3%

Appalachian South Carolina 85.7% 4.3% 0.0% 0.0% 10.0%

Coal Counties, South Carolina – – – – – 

Non-Appalachian South Carolina 76.4% 12.0% 0.0% 0.0% 11.6%

Tennessee 64.2% 30.7% 0.0% 0.1% 5.0%

Appalachian Tennessee 63.0% 33.1% 0.0% 0.1% 3.8%

Coal Counties, Tennessee 58.6% 36.8% 0.0% 0.9% 3.8%

Non-Appalachian Tennessee 64.9% 29.3% 0.0% 0.1% 5.7%

Virginia 75.2% 16.3% 0.0% 0.3% 8.1%

Appalachian Virginia 66.6% 21.2% 0.0% 6.5% 5.7%

Coal Counties, Virginia 54.9% 15.9% 0.0% 25.1% 4.1%

Non-Appalachian Virginia 75.7% 16.1% 0.0% 0.0% 8.3%

West Virginia 80.5% 7.0% 0.0% 0.0% 12.5%

Appalachian West Virginia 80.5% 7.0% 0.0% 0.0% 12.5%

Coal Counties, West Virginia 77.4% 9.0% 0.0% 0.0% 13.6%

Non-Appalachian West Virginia – – – – – 

Appalachian States 64.5% 16.9% 14.1% 0.0% 4.5%

Appalachian Counties, Total 69.6% 18.6% 6.2% 0.2% 5.4%

Coal Counties, Total 67.5% 12.6% 12.0% 0.5% 7.5%

Non-Appalachian Counties, Total 63.6% 16.6% 15.5% 0.0% 4.4%

UNITED STATES 73.5% 16.6% 5.7% 0.0% 4.1%

Source: U.S. Census Bureau, Census of Governments 2012

Notes: Coal counties are those counties with coal mining employment in 2010 as reported in the annual employment and 

production data file from the U.S. Mine Safety and Health Administration (MSHA), 

<https://arlweb.msha.gov/OpenGovernmentData/DataSets/ MinesProdYearly.zip>.

Appalachian States is the sum of all states in the Appalachian region.
66

Sales and gross receipts taxes accounted for just 12.6 percent of local revenue in coalemployment counties compared to 18.6 percent for all Appalachian counties and 16.6 percent for all 

local governments across the country. Local governments in Alabama, Georgia, and Tennessee place 

heavy reliance on the local sales tax, where it represents about one-third of local collections. Sales 

and gross receipts taxes are a small share of the local revenue portfolio in Maryland, Mississippi, 

Pennsylvania and West Virginia.

Local personal income tax revenue accrues to coal counties in Alabama, Kentucky, Maryland, Ohio 

and Pennsylvania. Local corporation income tax revenues accrue to coal counties in Kentucky and Ohio 

as well as a small number of non-coal counties in New York and Pennsylvania. In Kentucky, local 

governments cannot tax income, but can adopt occupational license taxes that are defined as 

corporation income taxes for reporting purposes to the U.S. Census Bureau. Ohio replaced its 

corporation income tax with a gross receipts tax in 2005, but local communities can impose a 

municipal corporation income tax as well as choose the rate; more than 600 municipalities across the 

state have adopted this tax instrument. Together, personal and corporation income taxes were 12.0 

percent of local revenue in coal-employment counties in 2012, almost twice the share for all 

Appalachian counties.

The other tax category accounts for license taxes, death and gift taxes, documentary and stock 

transfer taxes, and other small revenue sources. These small pieces add up to represent a significant 

7.5 percent share of tax collections for coal counties, which is higher than all of the other broad 

geographies shown in the table. Coal counties in Alabama and West Virginia generate 14.6 percent and 

13.6 percent of their revenue from these smaller tax instruments. While the individual contribution of 

each tax is small, together the revenues can be substantial. Moreover, states generally enable local 

discretion in setting the rates of some of these tax instruments, which gives local governments 

additional revenue autonomy to help fund government services.

Local severance tax revenue was just 0.5 percent of local own-source taxes for coal communities 

in 2012, with most communities showing little to no severance tax revenue. Census data in Table 26 

reflects revenues administered at the county level; Alabama, Kentucky, Tennessee, and West Virginia 

collect and distribute severance revenue to counties, while Virginia and Maryland give counties the 

authority to collect tax.13 Ohio’s coal severance revenue is distributed to reclamation and geological 

mapping funds, but is not remitted to counties of severance directly (Ohio Department of Taxation).

State coal severance tax rates are presented in Table 27 while state severance tax collections for 2005

to 2015 are shown in Table 28.

 13 The following excludes revenue from mining permit fees, per acre permit fees, and reclamation fees.
67

Table 27: State Severance Taxes, 2016

Table 28: State-Levied Coal Severance Tax Revenue, State Fiscal Years 2005-2015 ($)

For coal counties in Virginia, severance taxes account for 25.1 percent of local tax collections. 

The state itself levies only a small Coal Surface Mining Reclamation Tax; it instead authorizes counties 

of severance to levy two separate gross receipts taxes. The severance license and coal road 

improvement taxes are between 0.75 and 1.0 percent of gross receipts depending on mine size. 

Severance license revenue remains with the county of severance, while 20 percent of all coal road 

improvement tax revenues are distributed to Wise County (VA Code 58.1-3742-3743). Local severance 

revenue for Maryland coal counties comes from a 30 cent per ton tax on coal levied by Garrett and 

other Maryland coal counties14 (MD Local Government Code 20-301-306). Additionally, 6 cents of the 

state’s 15 cent Mine Reclamation Surcharge Tax are also distributed back to counties of severance. 

 14 Revenues are small enough to be negligible in Table 27.

State Title and application of tax Rate

Alabama Coal Severance Tax $.135/ton

Coal and Lignite Severance Tax $.20/ton in select counties

Kentucky Coal Severance Tax 4.5% of gross value, less transportation expenses; $0.50/ton minimum for extraction and processing

Marylanda Mine Reclamation Surcharge $.15/ton of coal removed by open-pit, strip or deep mine methods

Bond Supplement Reserve Surcharge $.02/ton of coal removed by open pit or strip methods

Ohio Resource Severance Tax $.10/ton

Surface Mining Tax an additional 1.2 cents per ton on surface mining operations

Reclamation Tax an additional 12, 14, or 16 cents per ton on operations without a full cost bond, depending of 

Reclamation Forfeiture Fund Balance

Tennessee Coal Severance Tax b $1.00/ton (effective 7/17/13)

Virginiac Coal Surface Mining Reclamation Tax

$.04/ton surface-mined clean coal; $.03/ton deep-mined clean coal; $.015/ton on prepared coal if 

Surface Mining Reclamation Fund balance less than $20 mil (beginning in FY 2018, if balance is less 

than $1.75 mil)

West Virginia Natural Resource Severance Taxes

Greater of 5% or $.75/ton for seams >45"

(4.65% for state purposes, .35% distributed to local governments)

Seams between 37" and 45": greater of 2% or $.75/ton

(1.65% for state purposes, .35% distributed to local governments)

Seams less than 37": greater of 1% or $.75/ton

(0.65% for state purposes, .35% distributed to local governments)

Coal from gob, refuse piles, or other sources of waste coal: 2.5% 

Workers' compensation debt reduction fund tax: $.56/ton

Sources: The Council of State Governments, 2016, state codes

a

Maryland authorizes collection of $.30/ton by county of severance.

b

Except any mineral fuel used in the production of energy, including coal and lignite.

c

Virginia authorizes License and Road Improvement Gross Receipts tax collection by counties of severance.

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Alabama $6,463,266 $6,217,984 $6,620,139 $6,200,358 $6,444,763 $6,415,677 $3,452,559 $9,141,626 $5,582,315 $4,981,975 $3,123,841

Kentucky 224,490,111 221,952,516 232,977,827 292,591,094 271,943,100 295,836,611 298,263,637 230,540,150 197,525,899 180,283,352 120,607,931

Marylanda 28,310 729,183 311,171 1,055,460 468,107 1,055,460 453,290 524,342 362,765 406,757 7,105

Mississippi — — — — — — — — — — —

Ohio 2,052,560 2,216,710 2,016,846 4,463852c 6,272,478 6,269,174 6,792,419 5,626,852 7,427,496 4,461,153 4,910,033

Pennsylvania — — — — — — — — — — —

Tennessee 60,139 47,394 37,705 42,905 42,539 117,509 52,918 65,120 117,132 46,241 60,517

Virginiaab 327,047 318,880 323,689 326,890 373,190 292,086 518,652 283,251 209,332 119,138 116,332

West Virginia 242,684,024 319,530,614 384,275,642 419,380,680 456,272,342 480,814,413 526,817,310 531,108,015 451,646,047 407,147,587 375,588,311

Sources: State revenue and operating budget reports

a

 The bulk of severance taxes in Virginia and Maryland are collected at the local level.

b

 Revenues include permit fees in addition to per ton tax.

c Ohio began levying Reclamation Fund Tax.
68

State revenues from the Mine Reclamation Surcharge Tax are listed in Table 28 (MD Environment Code 

§ 15-509).

Alabama levies two separate severance taxes on coal. All of a 20 cent per ton tax is distributed 

back to the counties of severance. Sixty percent of the revenue from an additional 13.5 cent per ton 

tax is returned to counties of severance; the remainder is earmarked for various economic 

development funds with leftover proceeds funneled to the state’s general fund (Alabama Department 

of Revenue). 

Kentucky distributes one half of state-collected severance revenue into two separate funds: the 

Local Government Economic Assistance Fund (LGEAF) and the Local Government Economic 

Development Fund (LGEAD). The LGEAF primarily funds public works projects and the coal haul road 

system (KRS 42.450), while the LGEAD was created to distribute severance revenues back to county 

general funds based on share of coal production, employment, and potential to benefit from industrial 

development projects (KRS 42.4585, 42.4592, 42.470). 

For the small number of coal counties in Tennessee, severance taxes are just 0.9 percent of 

collections, likely from county-set non-coal mineral taxes (§ 67-7-110), the proceeds of which may go

to county general funds. Tennessee collects then remits all state coal severance revenue (except a 

small portion for administration) to the counties of severance, but mandates that half goes to county 

education and the other half to road and stream maintenance (§ TN Code 67-7-201).

West Virginia shows no locally-levied severance tax collections in 2012. However, severance 

revenues are distributed to all counties in West Virginia, including counties without severance 

activity. For example, of the regular 5 percent rate, one-quarter of the proceeds from 0.35 percent of 

the tax rate is distributed to all counties based on population share. The other three-quarters goes to 

counties of severance, as does the rest of the 5 percent rate proceeds. Severance revenue to counties 

must be used for economic development or infrastructure projects (WVC §11-13A-6 &6-A).

3. Elementary and Secondary Education Funding 

and Spending

Federal, state and local governments all contribute to funding elementary and secondary 

education. The federal government provides modest financing, representing 8.4 percent of schooling 

revenues across all states in 2014, as reported in Table 29. Appalachian counties had 9.0 percent of 

revenue sourced by the federal government compared to 8.8 percent for coal-employment counties 

within the Region. Coal counties in all states other than Pennsylvania have higher-than-average shares 

of revenue from the federal government.15 The relative role of the states has grown over time in order 

 15 Coal-employment counties in Pennsylvania accounted for 62.8 percent of all federal revenue going to public 

schools in coal communities across the Appalachian Region in 2014.
69

to address local disparities in tax capacity that contribute to wide disparities in per pupil spending. In 

2014, for the nation as a whole, 45.9 percent of elementary and secondary revenue came from state 

government coffers. For the Appalachian Region the comparable figure is 50.5 percent and for coal 

communities the figure is 47.6 percent. Coal communities in Kentucky are most reliant on state 

revenues (64.4 percent of revenues), followed by Virginia, Maryland, and West Virginia; Mississippi and 

Pennsylvania have the smallest shares of state revenue supporting K-12 education.

For all states, local government revenues account for 45.6 percent of K-12 revenue resources. For 

the Appalachian Region, the average is 40.5 percent, and for Appalachian coal communities the 

average is 43.6 percent. Below the coal community average, which is heavily affected by 

Pennsylvania, are Alabama (39.3 percent), Kentucky (19.8 percent), Maryland (31.7 percent), Ohio 

(40.4 percent), Tennessee (35.2 percent), Virginia (29.6 percent) and West Virginia (32.4 percent).

State funding support for K-12 education is substantial across all states in the Appalachian Region

as shown in Table 30. In 2014, total state funding per pupil was $6,639 in coal-employment 

communities, higher than spending in other Appalachian counties, states in the Appalachian Region,

and the United States. The highest level of state support is in West Virginia; the lowest levels are in 

Tennessee and Mississippi.
70

Table 29: Total Elementary-Secondary Revenue, Distribution by Source for States and Other 

Geographies in Appalachia, 2014

Area Federal State Local Federal State Local

Alabama 794,090 4,031,547 2,531,630 10.8 54.8 34.4

Appalachian Alabama 465,933 2,602,023 1,726,741 9.7 54.3 36.0

Coal Counties, Alabama 216,130 1,180,593 904,807 9.4 51.3 39.3

Non-Appalachian Alabama 328,157 1,429,524 804,889 12.8 55.8 31.4

Georgia 1,804,212 7,837,335 8,180,073 10.1 44.0 45.9

Appalachian Georgia 470,699 2,672,951 2,434,120 8.4 47.9 43.6

Coal Counties, Georgia – – – – – –

Non-Appalachian Georgia 1,333,513 5,164,384 5,745,953 10.9 42.2 46.9

Kentucky 825,742 3,966,872 2,437,243 11.4 54.9 33.7

Appalachian Kentucky 300,493 1,317,503 418,094 14.8 64.7 20.5

Coal Counties, Kentucky 181,281 740,091 227,147 15.8 64.4 19.8

Non-Appalachian Kentucky 525,249 2,649,369 2,019,149 10.1 51.0 38.9

Maryland 816,033 6,186,736 6,979,775 5.8 44.2 49.9

Appalachian Maryland 39,400 294,846 173,677 7.8 58.0 34.2

Coal Counties, Maryland 18,398 109,846 59,451 9.8 58.5 31.7

Non-Appalachian Maryland 776,633 5,891,890 6,806,098 5.8 43.7 50.5

Mississippi 664,697 2,243,098 1,572,310 14.8 50.1 35.1

Appalachian Mississippi 139,998 495,480 283,379 15.2 53.9 30.8

Coal Counties, Mississippi 2,013 7,114 7,601 12.0 42.5 45.4

Non-Appalachian Mississippi 524,699 1,747,618 1,288,931 14.7 49.1 36.2

New York 3,346,420 24,816,869 33,154,746 5.5 40.5 54.1

Appalachian New York 167,340 1,872,458 1,081,495 5.4 60.0 34.6

Coal Counties, New York – – – – – –

Non-Appalachian New York 3,179,080 22,944,411 32,073,251 5.5 39.4 55.1

North Carolina 1,529,624 7,849,343 4,083,787 11.4 58.3 30.3

Appalachian North Carolina 257,844 1,314,015 606,423 11.8 60.3 27.8

Coal Counties, North Carolina – – – – – –

Non-Appalachian North Carolina 1,271,780 6,535,328 3,477,364 11.3 57.9 30.8

Ohio 1,692,769 9,492,461 12,176,077 7.2 40.6 52.1

Appalachian Ohio 350,924 1,936,848 1,532,743 9.2 50.7 40.1

Coal Counties, Ohio 195,983 1,011,030 817,917 9.7 49.9 40.4

Non-Appalachian Ohio 1,341,845 7,555,613 10,643,334 6.9 38.7 54.5

Pennsylvania 1,812,609 10,272,392 16,983,068 6.2 35.3 58.4

Appalachian Pennsylvania 830,796 5,170,971 6,370,766 6.7 41.8 51.5

Coal Counties, Pennsylvania 659,516 3,944,262 4,935,898 6.9 41.3 51.7

Non-Appalachian Pennsylvania 981,813 5,101,421 10,612,302 5.9 30.6 63.6

South Carolina 812,536 3,902,923 3,702,239 9.7 46.4 44.0

Appalachian South Carolina 175,049 1,009,930 838,756 8.6 49.9 41.4

Coal Counties, South Carolina – – – – – –

Non-Appalachian South Carolina 637,487 2,892,993 2,863,483 10.0 45.2 44.8

Tennessee 1,095,377 4,315,952 3,826,453 11.9 46.7 41.4

Appalachian Tennessee 447,806 1,758,616 1,524,796 12.0 47.1 40.9

Coal Counties, Tennessee 50,744 202,717 137,763 13.0 51.8 35.2

Non-Appalachian Tennessee 647,571 2,557,336 2,301,657 11.8 46.4 41.8

Virginia 1,009,659 5,994,897 8,343,306 6.6 39.1 54.4

Appalachian Virginia 101,869 604,780 413,608 9.1 54.0 36.9

Coal Counties, Virginia 29,945 161,750 80,667 11.0 59.4 29.6

Non-Appalachian Virginia 907,790 5,390,117 7,929,698 6.4 37.9 55.7

West Virginia 351,957 2,033,948 1,128,984 10.0 57.9 32.1

Appalachian West Virginia 351,957 2,033,948 1,128,984 10.0 57.9 32.1

Coal Counties, West Virginia 228,607 1,215,286 692,206 10.7 56.9 32.4

Non-Appalachian West Virginia – – – – – –

Appalachian States 16,555,725 92,944,373 105,099,691 7.7 43.3 49.0

Appalachian Counties, Total 4,100,108 23,084,369 18,533,582 9.0 50.5 40.5

Coal Counties, Total 1,582,617 8,572,689 7,863,457 8.8 47.6 43.6

Non-Appalachian Counties, Total 12,455,617 69,860,004 86,566,109 7.4 41.4 51.3

UNITED STATES 52,882,083 288,584,445 286,750,061 8.4 45.9 45.6

Source: U.S. Census Bureau, Annual Survey of School System Finances

Total Revenue (thous $) Distribution (%)

Notes: Coal counties are those counties with coal mining employment in 2010 as reported in the annual 

employment and production data file from the U.S. Mine Safety and Health Administration (MSHA), 

<https://arlweb.msha.gov/ OpenGovernmentData/DataSets/MinesProdYearly.zip>.

Appalachian states is the sum of all states in the Appalachian region.
71

Total per pupil state K-12 funding in coal communities was up 43.9 percent between 2000 and 

2010 and 11.2 percent in the more recent 2010-2014 window. These growth rates compare favorably 

to the rates for most other geographies shown in the bottom panel of Table 30. Coal communities in 

Alabama, Mississippi, and Ohio experienced more rapid growth in per pupil state funding than these 

entire states between 2010 and 2014. Maryland coal communities were the only places to see 

reductions in total per pupil state funding during the same time period. These state funding data do 

not show any broad-based signs of weakening support for K-12 education in coal-employment counties 

of Appalachia.
72

Table 30: Total Elementary-Secondary State Revenue per Pupil for States and Other Geographies in

Appalachia, 2000, 2010 and 2014

Area 2000 2010 2014 2000 to 2010 2010 to 2014

Alabama 4,114 5,074 5,447 23.4 7.4

Appalachian Alabama 4,104 5,111 5,505 24.5 7.7

Coal Counties, Alabama 4,085 4,925 5,425 20.6 10.1

Non-Appalachian Alabama 4,131 5,009 5,345 21.3 6.7

Georgia 3,800 4,058 4,612 6.8 13.7

Appalachian Georgia 3,805 4,104 4,759 7.9 16.0

Coal Counties, Georgia – – – – –

Non-Appalachian Georgia 3,798 4,036 4,540 6.3 12.5

Kentucky 4,042 5,386 5,775 33.3 7.2

Appalachian Kentucky 4,617 6,221 6,656 34.8 7.0

Coal Counties, Kentucky 4,715 6,302 6,708 33.7 6.4

Non-Appalachian Kentucky 3,780 5,037 5,418 33.2 7.6

Maryland 3,312 6,537 7,146 97.3 9.3

Appalachian Maryland 3,757 8,083 8,364 115.2 3.5

Coal Counties, Maryland 4,132 8,999 8,610 117.8 -4.3

Non-Appalachian Maryland 3,293 6,469 7,094 96.5 9.7

Mississippi 3,012 4,290 4,555 42.4 6.2

Appalachian Mississippi 3,190 4,559 4,853 42.9 6.5

Coal Counties, Mississippi 3,482 4,268 4,992 22.6 17.0

Non-Appalachian Mississippi 2,963 4,219 4,477 42.4 6.1

New York 4,811 8,568 9,477 78.1 10.6

Appalachian New York 6,478 11,417 12,711 76.2 11.3

Coal Counties, New York – – – – –

Non-Appalachian New York 4,697 8,391 9,285 78.7 10.6

North Carolina 4,675 5,159 5,446 10.3 5.6

Appalachian North Carolina 4,841 5,440 5,764 12.4 6.0

Coal Counties, North Carolina – – – – –

Non-Appalachian North Carolina 4,640 5,104 5,386 10.0 5.5

Ohio 3,526 5,982 5,927 69.7 -0.9

Appalachian Ohio 4,470 6,703 6,867 50.0 2.4

Coal Counties, Ohio 4,305 6,634 6,917 54.1 4.3

Non-Appalachian Ohio 3,311 5,825 5,726 76.0 -1.7

Pennsylvania 3,458 5,604 6,399 62.1 14.2

Appalachian Pennsylvania 3,904 6,156 7,064 57.7 14.8

Coal Counties, Pennsylvania 3,901 6,123 6,992 57.0 14.2

Non-Appalachian Pennsylvania 3,046 5,138 5,842 68.7 13.7

South Carolina 3,630 4,720 5,351 30.0 13.4

Appalachian South Carolina 3,491 4,636 5,329 32.8 15.0

Coal Counties, South Carolina – – – – –

Non-Appalachian South Carolina 3,675 4,749 5,359 29.2 12.8

Tennessee 2,678 3,947 4,348 47.4 10.2

Appalachian Tennessee 2,710 3,946 4,275 45.6 8.3

Coal Counties, Tennessee 3,126 4,616 4,874 47.6 5.6

Non-Appalachian Tennessee 2,655 3,948 4,400 48.7 11.4

Virginia 3,321 4,411 4,708 32.8 6.8

Appalachian Virginia 4,303 5,642 5,801 31.1 2.8

Coal Counties, Virginia 4,872 6,082 6,102 24.8 0.3

Non-Appalachian Virginia 3,214 4,293 4,611 33.6 7.4

West Virginia 4,692 5,953 7,257 26.9 21.9

Appalachian West Virginia 4,692 5,953 7,257 26.9 21.9

Coal Counties, West Virginia 4,732 6,094 7,121 28.8 16.9

Non-Appalachian West Virginia – – – – –

Appalachian States 3,871 5,696 6,185 47.1 8.6

Appalachian Counties, Total 4,099 5,588 6,165 36.3 10.3

Coal Counties, Total 4,149 5,971 6,639 43.9 11.2

Non-Appalachian Counties, Total 3,794 5,732 6,192 51.1 8.0

UNITED STATES 4,010 5,340 5,969 33.2 11.8

Source: U.S. Census Bureau, Annual Survey of School System Finances

Total State Revenue Per Pupil ($) Growth (%)

Notes: Coal counties are those counties with coal mining employment in 2010 as reported in the annual 

employment and production data file from the U.S. Mine Safety and Health Administration (MSHA), 

<https://arlweb.msha.gov/ OpenGovernmentData/ DataSets/MinesProdYearly.zip>.

Appalachian States is the sum of all states in the Appalachian region.
73

Locally-generated per pupil revenue data for elementary and secondary education are presented 

in Table 31. (These are aggregate data for all local public school systems in a county.) Total local 

revenues in coal-employment communities were slightly higher than the national average in 2000, 

below the national average in 2010, and then slightly above the national average again in 2014. Local 

per pupil revenue growth in coal communities was below the national average for 2000-2010, but was 

up by 14.1 percent compared to 5.6 percent for the nation between 2010 and 2014. These same 

communities experienced stronger revenue growth in Alabama, Mississippi, Ohio, Tennessee and 

Virginia than each state as a whole. As with the state funding data presented above, these local 

revenue patterns do not indicate declining support for K-12 education in coal communities in 

Appalachia. At the same time, local contributions to school spending are very low in some 

communities. For example, one Alabama county, 14 counties in Kentucky, three counties in 

Tennessee, and three counties in West Virginia commit less than $2,000 per pupil in support of 

elementary and secondary education.
74

Table 31: Total Elementary-Secondary Local Revenue per Pupil for States and Other Geographies in 

Appalachia, 2000, 2010 and 2014

Area 2000 2010 2014 2000 to 2010 2010 to 2014

Alabama 1,994 3,134 3,421 57.1 9.2

Appalachian Alabama 2,274 3,320 3,653 46.0 10.1

Coal Counties, Alabama 2,675 3,778 4,157 41.2 10.0

Non-Appalachian Alabama 1,511 2,801 3,010 85.4 7.4

Georgia 3,570 5,120 4,814 43.4 -6.0

Appalachian Georgia 3,461 4,780 4,333 38.1 -9.3

Coal Counties, Georgia – – – – –

Non-Appalachian Georgia 3,612 5,283 5,052 46.3 -4.4

Kentucky 1,996 3,177 3,548 59.1 11.7

Appalachian Kentucky 1,216 1,871 2,112 53.9 12.9

Coal Counties, Kentucky 1,195 1,860 2,059 55.6 10.7

Non-Appalachian Kentucky 2,351 3,724 4,129 58.4 10.9

Maryland 4,968 7,991 8,062 60.9 0.9

Appalachian Maryland 3,292 4,801 4,927 45.8 2.6

Coal Counties, Maryland 3,157 4,716 4,660 49.4 -1.2

Non-Appalachian Maryland 5,042 8,130 8,195 61.3 0.8

Mississippi 1,743 2,871 3,193 64.7 11.2

Appalachian Mississippi 1,586 2,493 2,776 57.2 11.3

Coal Counties, Mississippi 1,452 3,664 5,334 152.4 45.6

Non-Appalachian Mississippi 1,786 2,970 3,302 66.3 11.2

New York 5,662 10,621 12,662 87.6 19.2

Appalachian New York 3,573 6,009 7,342 68.2 22.2

Coal Counties, New York – – – – –

Non-Appalachian New York 5,805 10,907 12,979 87.9 19.0

North Carolina 2,017 5,014 2,833 148.6 -43.5

Appalachian North Carolina 2,051 3,556 2,660 73.4 -25.2

Coal Counties, North Carolina – – – – –

Non-Appalachian North Carolina 2,010 5,298 2,866 163.6 -45.9

Ohio 4,422 6,558 7,603 48.3 15.9

Appalachian Ohio 3,105 4,612 5,435 48.5 17.8

Coal Counties, Ohio 3,109 4,583 5,595 47.4 22.1

Non-Appalachian Ohio 4,721 6,979 8,066 47.8 15.6

Pennsylvania 5,557 9,196 10,579 65.5 15.0

Appalachian Pennsylvania 4,874 7,584 8,703 55.6 14.8

Coal Counties, Pennsylvania 5,019 7,689 8,750 53.2 13.8

Non-Appalachian Pennsylvania 6,187 10,557 12,152 70.6 15.1

South Carolina 2,855 4,639 5,076 62.5 9.4

Appalachian South Carolina 3,083 4,133 4,426 34.1 7.1

Coal Counties, South Carolina – – – – –

Non-Appalachian South Carolina 2,781 4,815 5,304 73.2 10.1

Tennessee 2,697 3,579 3,855 32.7 7.7

Appalachian Tennessee 2,630 3,452 3,707 31.3 7.4

Coal Counties, Tennessee 2,096 2,865 3,312 36.7 15.6

Non-Appalachian Tennessee 2,747 3,670 3,960 33.6 7.9

Virginia 4,112 6,359 6,553 54.7 3.0

Appalachian Virginia 2,384 3,590 3,967 50.6 10.5

Coal Counties, Virginia 1,746 2,530 3,043 44.9 20.3

Non-Appalachian Virginia 4,301 6,623 6,784 54.0 2.4

West Virginia 2,295 3,496 4,028 52.4 15.2

Appalachian West Virginia 2,295 3,496 4,028 52.4 15.2

Coal Counties, West Virginia 2,279 3,390 4,056 48.7 19.7

Non-Appalachian West Virginia – – – – –

Appalachian States 3,987 6,554 6,994 64.4 6.7

Appalachian Counties, Total 3,126 4,608 4,950 47.4 7.4

Coal Counties, Total 3,598 5,339 6,090 48.4 14.1

Non-Appalachian Counties, Total 4,277 7,206 7,673 68.5 6.5

UNITED STATES 3,591 5,618 5,931 56.5 5.6

Source: U.S. Census Bureau, Annual Survey of School System Finances

Total Local Revenue Per Pupil ($) Growth (%)

Notes: Coal counties are those counties with coal mining employment in 2010 as reported in the annual 

employment and production data file from the U.S. Mine Safety and Health Administration (MSHA), 

<https://arlweb.msha.gov/ OpenGovernmentData/ DataSets/MinesProdYearly.zip>.

Appalachian States is the sum of all states in the Appalachian region.
75

The federal, state and local revenue data discussed above include revenue that is used for all 

schooling functions. Current spending per pupil reveals how much of this revenue is actually being 

used for instructional purposes. As illustrated in Figure 6, current spending per pupil has generally 

been trending upward over time, with a sluggish pattern emerging in the years following the Great 

Recession. Coal-employment communities have consistently spent more per pupil than the other 

geographies displayed in the figure. Moreover, these same places have seen more rapid recent growth 

than their non-coal counterparts in recent years.

Figure 6: Total Current Spending per Pupil by Geography

6,000

7,000

8,000

9,000

10,000

11,000

12,000

13,000

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Spending per Pupil (dollars)

Appalachian States Coal Counties Non-Coal Counties U.S.

Source: U.S. Census Bureau, Annual Survey of School System Finances

Notes: Coal counties are those counties with coal mining employment in 2010 as reported in the annual 

employment and production data file from the U.S. Mine Safety and Health Administration (MSHA), 

<https://arlweb.msha.gov/ OpenGovernmentData/ DataSets/MinesProdYearly.zip>.

Non-Coal Counties are those ARC counties without coal mining employment in 2010.

Appalachian States is the sum of all states in the Appalachian region.
76

Table 32 provides summary data on nominal current spending per pupil for the Appalachian states 

and related geographies for 2000, 2010, and 2014. With just two exceptions, all counties in West 

Virginia spend more than $10,000 per pupil in instructional expenditures. Spending per pupil is less 

than $9,000 in four counties in Alabama, three counties in Kentucky, all six coal-employment counties 

in Tennessee, and one county in Virginia. Current spending per pupil in elementary and secondary 

education averaged $11,307 across all states in 2014. In comparison, spending in Appalachian counties 

averaged $10,798, or 95.5 percent of the national average. Coal-employment counties, on the other 

hand, spent $12,119 per pupil in 2014, well above the national average. Patterns for coal communities 

are largely the same as the schooling revenue patterns discussed above. Coal communities have seen 

per pupil spending growth that exceeded the nation in the 2000 to 2010 and 2010 to 2014 windows. In 

the more recent 2010 to 2014-time period, per pupil spending in coal communities was up 7.2 

percent, significantly above the national average of 4.3 percent.

As is often the case, averages can mask significant differences that lay beneath the surface of the 

data. While coal communities did well on average between 2010 and 2014 (in large part because of 

exceptional growth in spending in Pennsylvania), current per pupil spending declined in Kentucky, 

Virginia and West Virginia. (See figure 7 for coal communities that experienced increases and 

decreases in per pupil funding between 2010 and 2014.) In Kentucky, spending per pupil was up 

statewide at a 4.0 percent rate, but spending in coal communities was down 0.9 percent. In Virginia, 

statewide spending grew 3.5 percent, but per pupil spending fell 2.6 percent in coal-employment 

counties of the state. Coal communities in West Virginia saw spending contract 2.2 percent versus a 

statewide 2.0 percent setback. A number of coal communities in Alabama, Ohio, and Tennessee also 

saw reductions in current per pupil spending. These reductions in current per pupil spending are 

inconsistent with the growth in total state and local revenue per pupil revenue data presented in 

Tables 30 and 31. 
77

Table 32: Current Spending per Pupil for States and Other Geographies in Appalachia, 2000, 2010 and 

2014

Area 2000 2010 2014 2000 to 2010 2010 to 2014

Alabama 5,843 9,033 9,192 54.6 1.8

Appalachian Alabama 5,942 9,133 9,316 53.7 2.0

Coal Counties, Alabama 6,086 9,391 9,586 54.3 2.1

Non-Appalachian Alabama 5,674 8,853 8,972 56.0 1.3

Georgia 6,451 9,469 9,299 46.8 -1.8

Appalachian Georgia 6,290 9,091 9,011 44.5 -0.9

Coal Counties, Georgia – – – – –

Non-Appalachian Georgia 6,512 9,650 9,441 48.2 -2.2

Kentucky 6,017 9,045 9,403 50.3 4.0

Appalachian Kentucky 6,027 9,122 9,076 51.4 -0.5

Coal Counties, Kentucky 6,122 9,307 9,227 52.0 -0.9

Non-Appalachian Kentucky 6,013 9,013 9,536 49.9 5.8

Maryland 7,517 13,765 14,030 83.1 1.9

Appalachian Maryland 7,145 13,018 13,350 82.2 2.6

Coal Counties, Maryland 7,641 14,141 14,368 85.1 1.6

Non-Appalachian Maryland 7,534 13,798 14,059 83.1 1.9

Mississippi 5,043 8,156 8,301 61.7 1.8

Appalachian Mississippi 5,012 8,229 8,331 64.2 1.2

Coal Counties, Mississippi 4,967 9,595 10,005 93.2 4.3

Non-Appalachian Mississippi 5,051 8,137 8,293 61.1 1.9

New York 10,237 19,357 21,789 89.1 12.6

Appalachian New York 9,353 16,479 18,314 76.2 11.1

Coal Counties, New York – – – – –

Non-Appalachian New York 10,297 19,536 21,997 89.7 12.6

North Carolina 6,096 8,458 8,558 38.8 1.2

Appalachian North Carolina 6,248 8,733 8,863 39.8 1.5

Coal Counties, North Carolina – – – – –

Non-Appalachian North Carolina 6,063 8,404 8,501 38.6 1.2

Ohio 7,194 11,600 12,094 61.2 4.3

Appalachian Ohio 6,537 10,690 11,253 63.5 5.3

Coal Counties, Ohio 6,575 10,636 11,534 61.8 8.4

Non-Appalachian Ohio 7,344 11,797 12,274 60.6 4.0

Pennsylvania 8,071 13,311 15,203 64.9 14.2

Appalachian Pennsylvania 7,891 12,665 14,341 60.5 13.2

Coal Counties, Pennsylvania 8,007 12,690 14,347 58.5 13.1

Non-Appalachian Pennsylvania 8,238 13,857 15,926 68.2 14.9

South Carolina 6,185 9,269 9,890 49.9 6.7

Appalachian South Carolina 5,985 8,460 9,116 41.4 7.8

Coal Counties, South Carolina – – – – –

Non-Appalachian South Carolina 6,249 9,552 10,162 52.9 6.4

Tennessee 5,450 8,151 8,703 49.6 6.8

Appalachian Tennessee 5,411 7,912 8,544 46.2 8.0

Coal Counties, Tennessee 5,356 8,196 8,634 53.0 5.3

Non-Appalachian Tennessee 5,479 8,322 8,815 51.9 5.9

Virginia 6,896 10,661 11,034 54.6 3.5

Appalachian Virginia 6,471 9,618 9,801 48.6 1.9

Coal Counties, Virginia 6,496 9,761 9,506 50.3 -2.6

Non-Appalachian Virginia 6,942 10,760 11,144 55.0 3.6

West Virginia 7,220 11,630 11,397 61.1 -2.0

Appalachian West Virginia 7,220 11,630 11,397 61.1 -2.0

Coal Counties, West Virginia 7,314 11,718 11,458 60.2 -2.2

Non-Appalachian West Virginia – – – – –

Appalachian States 7,375 11,998 12,748 62.7 6.2

Appalachian Counties, Total 6,713 10,292 10,798 53.3 4.9

Coal Counties, Total 7,185 11,300 12,119 57.3 7.2

Non-Appalachian Counties, Total 7,598 12,570 13,395 65.4 6.6

UNITED STATES 6,998 10,842 11,307 54.9 4.3

Source: U.S. Census Bureau, Annual Survey of School System Finances

Current Spending Per Pupil ($) Growth (%)

Notes: Coal counties are those counties with coal mining employment in 2010 as reported in the annual 

employment and production data file from the U.S. Mine Safety and Health Administration (MSHA), 

<https://arlweb.msha.gov/ OpenGovernmentData/DataSets/MinesProdYearly.zip>.

Appalachian States is the sum of all states in the Appalachian region.
78

Figure 7: Change in Total Current Spending Per Pupil, 2010 to 2014

Source: U.S. Census Bureau, Annual Survey of School System Finances

The population data that were presented above in Table 5 showed the United States population 

growing 14.2 percent between 2000 and 2014 compared to a 0.4 percent loss for coal communities 

within Appalachia. The K-12 enrollment data in Figure 8 illustrates the consequences of this 

outmigration for the school-aged population in the Region. Schools in coal-employment counties saw 

enrollment counts fall by 158,192 between 2000 and 2014, representing a decline of 10.9 percent.

Non-coal communities in the Appalachian Region, on the other hand, had enrollment growth of 2.3 

percent over the same time period.
79

Figure 8: Elementary and Secondary School Enrollment by Geography

It is remarkable that enrollments have declined between 2000 and 2014 for the aggregate of coalemployment communities in all states other than Alabama, where enrollments were up only 0.2 

percent, or just 471 children. (See Table 33.) The largest declines were in Mississippi (-24.9 percent), 

Maryland (-18.5 percent), Ohio (-17.9 percent), Pennsylvania (-14.9 percent) and Virginia (-13.7 

percent). West Virginia’s K-12 enrollments fell 6.7 percent, while Kentucky’s were down 6.2 percent,

and Tennessee had the smallest contraction of 1.8 percent. These enrollment reductions help ease 

operational funding pressures associated with declining economic fortunes. At the same time, it may 

leave excess capacity in instructional capacity, as well as excess capacity in school administration and 

the physical capital stock of school buildings and support structures.

11.0

11.1

11.2

11.3

11.4

11.5

11.6

11.7

11.8

11.9

12.0

1.0

1.2

1.4

1.6

1.8

2.0

2.2

2.4

2.6

2.8

3.0

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Non-Appalachian County Enrollment (millions)

Coal & Non-Coal County Enrollment (millions)

Coal Counties Non-Coal Counties Non-Appalachian Counties

Source: U.S. Census Bureau, Annual Survey of School System Finances

Notes: Coal counties are those counties with coal mining employment in 2010 as reported in the annual 

employment and production data file from the U.S. Mine Safety and Health Administration (MSHA), 

<https://arlweb.msha.gov/ OpenGovernmentData/ DataSets/MinesProdYearly.zip>.

Non-Coal Counties are those ARC counties without coal mining employment in 2010.

REGION is the sum of all states in the Appalachian region.
80

Table 33: Total Elementary and Secondary School Enrollment for States and Other Geographies in

Appalachia, 2000, 2010 and 2014

Area 2000 2010 2014 2000 to 2010 2010 to 2014

Alabama 730,184 748,889 740,081 2.56 -1.18

Appalachian Alabama 462,286 480,373 472,633 3.91 -1.61

Coal Counties, Alabama 217,167 224,191 217,638 3.23 -2.92

Non-Appalachian Alabama 267,898 268,516 267,448 0.23 -0.40

Georgia 1,422,941 1,660,643 1,699,185 16.70 2.32

Appalachian Georgia 389,666 539,058 561,720 38.34 4.20

Coal Counties, Georgia – – – – –

Non-Appalachian Georgia 1,033,275 1,121,585 1,137,465 8.55 1.42

Kentucky 646,467 679,901 686,938 5.17 1.04

Appalachian Kentucky 202,141 200,790 197,945 -0.67 -1.42

Coal Counties, Kentucky 117,582 112,057 110,332 -4.70 -1.54

Non-Appalachian Kentucky 444,326 479,111 488,993 7.83 2.06

Maryland 846,582 848,252 865,768 0.20 2.06

Appalachian Maryland 35,604 35,365 35,253 -0.67 -0.32

Coal Counties, Maryland 15,651 13,463 12,758 -13.98 -5.24

Non-Appalachian Maryland 810,978 812,887 830,515 0.24 2.17

Mississippi 499,362 491,651 492,421 -1.54 0.16

Appalachian Mississippi 107,634 102,205 102,089 -5.04 -0.11

Coal Counties, Mississippi 1,897 1,602 1,425 -15.55 -11.05

Non-Appalachian Mississippi 391,728 389,446 390,332 -0.58 0.23

New York 2,861,478 2,697,357 2,618,542 -5.74 -2.92

Appalachian New York 183,285 157,687 147,306 -13.97 -6.58

Coal Counties, New York – – – – –

Non-Appalachian New York 2,678,193 2,539,670 2,471,236 -5.17 -2.69

North Carolina 1,261,586 1,444,409 1,441,391 14.49 -0.21

Appalachian North Carolina 222,341 235,814 227,952 6.06 -3.33

Coal Counties, North Carolina – – – – –

Non-Appalachian North Carolina 1,039,245 1,208,595 1,213,439 16.30 0.40

Ohio 1,822,566 1,669,748 1,601,566 -8.38 -4.08

Appalachian Ohio 338,080 297,133 282,036 -12.11 -5.08

Coal Counties, Ohio 178,111 154,419 146,176 -13.30 -5.34

Non-Appalachian Ohio 1,484,486 1,372,615 1,319,530 -7.54 -3.87

Pennsylvania 1,782,444 1,682,887 1,605,292 -5.59 -4.61

Appalachian Pennsylvania 856,361 770,436 731,987 -10.03 -4.99

Coal Counties, Pennsylvania 662,977 589,466 564,114 -11.09 -4.30

Non-Appalachian Pennsylvania 926,083 912,451 873,305 -1.47 -4.29

South Carolina 666,780 715,590 729,386 7.32 1.93

Appalachian South Carolina 162,636 185,231 189,514 13.89 2.31

Coal Counties, South Carolina – – – – –

Non-Appalachian South Carolina 504,144 530,359 539,872 5.20 1.79

Tennessee 907,222 971,414 992,583 7.08 2.18

Appalachian Tennessee 386,630 405,481 411,329 4.88 1.44

Coal Counties, Tennessee 42,351 41,725 41,593 -1.48 -0.32

Non-Appalachian Tennessee 520,592 565,933 581,254 8.71 2.71

Virginia 1,132,673 1,244,673 1,273,211 9.89 2.29

Appalachian Virginia 111,858 108,123 104,258 -3.34 -3.57

Coal Counties, Virginia 30,726 28,351 26,507 -7.73 -6.50

Non-Appalachian Virginia 1,020,815 1,136,550 1,168,953 11.34 2.85

West Virginia 290,982 281,828 280,265 -3.15 -0.55

Appalachian West Virginia 290,982 281,828 280,265 -3.15 -0.55

Coal Counties, West Virginia 182,937 171,748 170,664 -6.12 -0.63

Non-Appalachian West Virginia – – – – –

Appalachian States 14,871,267 15,137,242 15,026,629 1.79 -0.73

Appalachian Counties, Total 3,749,504 3,799,524 3,744,287 1.33 -1.45

Coal Counties, Total 1,449,399 1,337,022 1,291,207 -7.75 -3.43

Non-Appalachian Counties, Total 11,121,763 11,337,718 11,282,342 1.94 -0.49

UNITED STATES 46,432,782 48,266,209 48,349,251 3.95 0.17

Source: U.S. Census Bureau, Annual Survey of School System Finances.

Enrollment Growth (%)

Notes: Coal counties are those counties with coal mining employment in 2010 as reported in the annual 

employment and production data file from the U.S. Mine Safety and Health Administration (MSHA), 

<https://arlweb.msha.gov/ OpenGovernmentData/DataSets/MinesProdYearly.zip>.

Enrollments represent fall memberships collected by the National Center for Education Statistics on the Common 

Core of Data agency universe file—“Local Education Agency (School District) Universe Survey, Provisional Version 

1a.” Enrollments for state educational facilities, federal school systems, and charter schools whose charters are 

held by a nongovernmental entity have been excluded. Enrollments were subject to adjustment if they were 

inconsistent with the finances reported.

Appalachian States is the sum of all states in the Appalachian region.
81

4. Summary and Recommendations: Subtask 2

Declining coal-related economic activity gives rise to the threat of significant reductions in public 

funding for elementary and secondary education, especially where there are concentrations of coal 

employment and school-age children. An economic impact study for West Virginia noted above 

highlights the risk, showing that each job directly tied to the coal industry is associated with $23,023 

in state and local taxes. However, the analysis presented here does not find broad-based weakening of

overall fiscal health or total state and local funding support for K-12 education in coal-employment 

communities of Appalachia since 2000. State and local finances have remained relatively healthy and 

total revenues to support schooling have shown decent growth. One important indicator, current per 

pupil spending, has been consistently higher in coal-employment communities, with spending 

disparities actually rising relative to other key geographies since 2009.

Despite these broad findings, there are pockets of coal-employment regions of Appalachia that 

remain at risk. First, current per pupil spending in Kentucky, Virginia, and West Virginia and several 

coal-employment communities in Alabama, Ohio, and Tennessee has declined in nominal terms since 

2010. While total state and local revenues have seen healthy growth in these same places, the funding 

has not made it to the classroom. Second, many local communities, especially in Kentucky, 

Mississippi, West Virginia, and Virginia, exhibit low tax effort. While some of this low effort may 

reflect state-level constraints on the local ability to generate revenue, it largely reflects the 

community’s choice to tax itself relatively lightly. This limits the ability to fund schools as well as 

other locally-provided public services.

• Declining school enrollments have been pronounced in some coal-employment regions. In 

Ohio, for example, enrollments fell by 31,935 between 2000 and 2014 in counties where coal 

employment was present in 2010. Because of the small size of many coal regions of 

Appalachia, even modest enrollment reductions may give rise to excess capacity in school 

administration and instructional capacity (including the building capital stock). Opportunities 

for consolidation and cost savings may exist in some communities. Further analysis would be 

required to identify candidate school systems and specific functions that might be 

consolidated.

• Many coal-employment regions of Appalachia are characterized by low tax effort. That is, 

given their capacity to generate revenues from own-source tax bases, they have taxed

themselves relatively lightly. While this has the desirable effect of limiting government’s role 

in the economy, it also constrains the ability to fund elementary and secondary education 

which is critical to economic development and individual wellbeing. Low tax effort is 

especially pronounced in local coal-employment communities in Kentucky, Mississippi, 

Tennessee, and West Virginia. A large part of this reflects the choice of community residents.

In Tennessee, for example, local governments have considerable revenue-raising potential 

through the local option sales tax, the local property tax, and other taxes and fees. More 

generally, virtually all local governments have the capacity to raise revenues from instruments 

like the property tax, as well as smaller fees and charges that can collectively be significant. 

On the other hand, what appears to be low effort may in some instances be partially 

attributable to limited revenue-raising autonomy granted by the state—in other words, stateconstrained local capacity. Additional inquiry into local government revenue-raising capacity 

and effort is warranted to determine potential options for expanded local choice over tax 

rates to better enable the funding of local public schooling.
82

• The importance of education as a foundation for economic development cannot be overstated.

Educational attainment in coal-employment regions of Appalachia, as well as Appalachia more 

generally, lags the nation. While progress has been made in improving attainment rates, the 

gap between the Appalachian Region and the nation has widened rather than narrowed over 

time, as discussed above. Consideration should be given to capitalization of a legacy 

investment fund or creation of new dedicated funding streams that can be used to enhance 

investments in elementary and secondary education in coal-employment communities of the 

Appalachian Region. Proceeds would supplement rather than supplant traditional funding 

sources. Funding sources could include coal severance tax revenues, general revenues from 

states and local communities, federal revenues and funds from the private sector. Fund 

utilization could be managed by a board representing the general public, the private sector 

and school officials. Resources would be used to develop and deliver unique instructional and 

related programs that complement traditional schooling services. This might include STEM 

classes, school-to-work internships, and advanced placement coursework to better prepares 

students for college. Pooling of resources across school districts may lead to efficiencies and 

exploit economies of scale in program delivery. Such partnerships should be strongly 

encouraged.

• The failure to invest state and local dollars in traditional K-12 education may have dire 

consequences for students and communities. The Appalachian Region has long struggled to 

promote school achievement and educational attainment and this has certainly affected the 

Region’s path of economic development. As discussed above, nominal current spending per 

pupil has fallen in Kentucky, Virginia, and West Virginia, as well as in a number of counties in 

Alabama, Ohio, and Tennessee, since 2010. This sends a signal that schooling is not valued, a 

signal that can hamper efforts to recruit new businesses and promote economic development.

Lower spending can also lead to substantive effects on student outcomes that may affect their 

life experience and performance in the labor market. States and localities must set their own 

budget priorities. But it is hard to argue that elementary and secondary education should not 

be a top funding priority given its well-documented impact on people and places. States in the 

Appalachian Region should consider additional state-level funding support and/or require 

greater local funding (effort) for K-12 education as part of their state aid programs.
83

References

Alabama Constitution. Amend 856

Alabama Department of Revenue. General Summary of State Taxes 2016. Montgomery, AL.

http://revenue.alabama.gov/publications/tax-policy/general_summary_of_state_taxes.pdf

Augenblick, Palaich and Associates. Equity and Adequacy in Alabama Schools and Districts. March 

2015. 

https://www.alsde.edu/sec/comm/Related%Documents/Alabama%Final%Report%209.8.15.pdf

Autor, David H., David Dorn and Gordon H. Hansen, 2013. “The China Syndrome: Local Labor Market 

Effects of Import Competition in the United States.” American Economic Review 103: 2121-2168.

Barrett, Jim, 2001. “Worker Transition and Global Climate Change.” Prepared for the Pew Center on 

Global Change. https://www.c2es.org/publications/worker-transition-global-climate-change, 

downloaded May 2, 2017

BLS, 2017. Labor Force Statistics from the Current Population Survey. Table 18B: Employed Persons 

by Detailed Industry and Age (Annual Averages). Bureau of Labor Statistics. 

https://www.bls.gov/cps/cpsaat18b.htm, downloaded April 27, 2017

Cassidy, Michael and Duncombe, Chris. Virginia’s Eroding Standards of Quality. The Commonwealth 

Institute. January 6, 2016. http://www.thecommonwealthinstitute.org/wpcontent/uploads/2016/01/eroding_standards_report_v5.pdf

Chechovich, Laura. Funding Formulas and Revenue Streams: A Primer on Public School Finance in 

Maryland. Report. College of Education, University of Maryland. September 2016. 

http://www.education.umd.edu/TLPL/centers/MEP/Research/k12Education/Checovich_Primer_Fi

nance_Maryland_9.15.16.pdf

Congressional Budget Office, 2014. The Slow Recovery of the Labor Market. Publication Number 4837.

https://www.cbo.gov/sites/default/files/113th-congress-2013-2014/reports/45011-

LaborMarketReview.pdf, downloaded March 27, 2017

Dickey, Kent C. Overview of the Standards of Quality Funding Process. (presentation, Standing 

Committee of the Standards of Quality, April 29, 2009)

Evans, Sam, 2013. Economic Impacts of Job Losses in the Coal Mining Industry. KIRES Paper No.7, King

University School of Business, King Institute for Regional Economic Studies.

http://www.king.edu/_resources/pdfs/business/KIRES_7_Ecomonic_Impacts_of_Job_Losses_in_th

e_Coal_Mining_Industry_v2.pdf, downloaded March 16, 2017Fotta, Barbara and George Bockosh, 

2000. “The Aging Workforce: An Emerging Issue in the Mining Industry.” Proceedings of the 31st 

Annual Institute on Mining Health, Safety and Research, Roanoke, Virginia, August 27-30, 2000. 

Bockosh GR, Karmis M, Langton J, McCarter MK, Rowe B, eds., Blacksburg, VA: Virginia Polytechnic 

Institute and State University: 33-45. Also available at 

https://www.cdc.gov/niosh/mining/works/coversheet1199.html, downloaded April 27, 2017

Gebremariam, G.H., T.G. Gebremedhin and P.V. Schaeffer, 2011. “Employment, Income, and 

Migration in Appalachia: A Spatial Simultaneous Equations Approach.” Journal of Regional Science, 

51(1): 102-120

Green, Adrienne, 2016. “What the Backlash Against Coal Feels Like to a West Virginian Miner: Gary 

Campbell Reflects on the Pride America Once Reserved for those who Helped Fuel its Growth.” 

The Atlantic, August 17. https://www.theatlantic.com/business/archive/2016/08/coalmining/496277/, downloaded April 26, 2017

Imazeki, Jennifer and APA Consulting. Geographic Cost of Education Adjustment for Maryland. 

Report. November 23, 2015. http://marylandpublicschools.org/Documents/adequacystudy/APAPOA-GCEI-Report-Rev-11232015.pdf

Johnson, Richard W., Janette Kawachi, and Eric K. Lewis, 2009. Older Workers on the Move: 

Recareering in Later Life. Washington, DC: AARP Public Policy Institute

Kentucky Department of Education. Support Education Excellence in Kentucky Executive Summary for 

the 2014-2015 Year. Division of District Support. Lexington, KY. July 23, 2015. 

http://education.ky.gov/districts/SEEK/Documents/SEEK%20Executive%20Summary%202014-

15.doc

Kentucky Rev Stat 42.450, 42.4585, 42.4592, 42.470

Laney, A. Scott and David N. Weissman, 2014. “Respiratory Diseases Caused by Coal Mine Dust.”

Journal of Occupational Environmental Medicine 56: S18-S22
84

Maryland Department of Legislative Services. Legislative Handbook Series Volume IX Education in 

Maryland. Annapolis, MD. 2014. http:// mgaleg.maryland.gov/Pubs/LegisLegal/2014-

legislativehandbookseries-vol-9.pdf

Maryland Environment Code § 15-509 (2016)

Maryland Local Government Code 20-301-306 (2016)

Ohio Department of Education. FY 16 School Finance Payment Report: Line by Line Explanation.

Office of Budget and School Funding. Columbus, OH. 2016. 

http://education.ohio.gov/getattachment/Topics/Finance-and-Funding/State-Funding-ForSchools/Traditional-Public-School-Funding/SFPR-Funding-Form-Line-by-Line-Explanation-FY2016-

1.pdf.aspx

Ohio Department of Taxation. Severance Tax. Columbus, OH. 

http://www.tax.ohio.gov/Portals/0/communications/publications/severance_tax.pdf

Pennsylvania Department of Education. Basic Education Funding Report. Basic Education Funding 

Commission. Harrisburg, PA. June, 18 2015. 

http://www.education.pa.gov/Documents/About%20PDE/Press/BASIC%20EDUCATION%20FUNDING

%20COMMISSION%20FINAL%20REPORT.pdf

Pollard, Kelvin and Linda A. Jacobsen, 2016. The Appalachian Region: A Data Overview from the 2010-

2014 American Community Survey Chartbook. Prepared by the Population Reference Bureau for 

the Appalachian Regional Commission.

https://www.arc.gov/assets/research_reports/DataOverviewfrom2010to2014ACS.pdf, downloaded 

April 4, 2017. 

Thibodeau. Patrick, 2016. “Robotics, Driverless Tech Are Taking Over Mining Jobs.” Computerworld, 

October 28. http://www.computerworld.com/article/3136675/it-careers/robotics-driverlesstech-are-taking-over-mining-jobs.html. Downloaded April 25, 2017

Thompson, Eric C., Mark C. Berger, Steven N. Allen, and Jonathan M. Roenker, 2001. A Study on the

Current Economic Impacts of the Appalachian Coal Industry and its Future in the Region. Center

for Business and Economic Research, Gatton College of Business and Economics, University of

Kentucky, Lexington, KY.

file:///C:/Users/pschaef/Dropbox/RESEARCH/PAPERS%20&%20PROJECTS/ARC%20Coal%20Eco%20St

ystem/References/CurrentEconomicImpactsofAppalachianCoalIndustry.pdf, downloaded March 16,

2017

Tennessee Code §67-7-110 (2016)

Tennessee Code§ 67-7-201 (2016)

Tennessee Department of Education. BEP Handbook. Tennessee State Board of Education. Nashville, 

TN. July 2016. 

https://www.tn.gov/assets/entities/sbe/attachments/BEPHandbook_revised_July_2016.pdf

U.S. Census Bureau, 2015. Commuting (Journey to Work), Table 1 

https://www.census.gov/hhes/commuting/, downloaded May 30, 2017

U.S. Department of Health and Human Services, 2011. Coal Mine Dust Exposures and Associated 

Health Outcomes: A Review of Information Published Since 1995. Current Intelligence Bulletin 64. 

https://www.cdc.gov/niosh/docs/2011-172/pdfs/2011-172.pdf, downloaded February 16, 2017

Verstegen, Deborah A. A Quick Glance at School Finance: A 50 State Survey of School Finance 

Policies. Wordpress. 2015. https://schoolfinancesdav.wordpress.com/

Virginia Code § 58.1-3741-3743 (2016)

West Virginia Code §11-13A-6 &6-A

West Virginia Department of Education. Executive Summary of the Public School Support Program 

Based on the Final Computations for the 2015-2016 Year. Office of School Finance. Charleston, 

WV. April 2, 2015. https://wvde.state.wv.us/finance/pssp/2015-2016/ 

PSSP%2016%20Executive%20Summary%20-%20Final%20Comps.pdf

West Virginia Office of Miners’ Health, Safety and Training, 2015. 2015 Statistical Report and Director 

of Mines. Charleston, WV. http://www.wvminesafety.org/PDFs/2015%20Annual%20Report%20-

%20CY.pdf, downloaded March 16, 2017

Wool, Harold, 1981. “Coal Industry Resurgence Attracts Variety of New Workers.” Monthly Labor 

Review, January: 3-8