An Economic Analysis of 

the Appalachian Coal 

Industry Ecosystem 

County-level CIE Supply Chain Analysis

Randall Jackson, Director, and

Péter Járosi, Research Assistant Professor

Regional Research Institute, West Virginia University

Prepared for

The Appalachian Regional Commission, under contract # PW-18673-16 

January 2018
1 

Estimating County-level Supply Chain Impacts and Key Suppliers .............................................. 3

Executive Summary .................................................................................................. 3

Introduction........................................................................................................... 5

Overview .............................................................................................................. 5

Analysis ................................................................................................................ 6

CIE Dependence ................................................................................................... 6

CIE Impact......................................................................................................... 15

CIE Risk............................................................................................................. 18

CIE County Typology ............................................................................................. 23

Coal Distressed Counties ........................................................................................... 29

Summary.............................................................................................................. 33

References .............................................................................................................. 34

Appendices.............................................................................................................. 35

Appendix I. CIE Scores, All Industries ........................................................................... 35

Appendix II. All Dependence, Impact, and Risk Scores ....................................................... 49

Appendix III. Dependence, Impact, and Risk Formulae ...................................................... 60

Variable Definitions .............................................................................................. 60

Industry CIE Scores ............................................................................................... 61

Dependency Scores............................................................................................... 62

Impact Scores ..................................................................................................... 64

Risk Scores......................................................................................................... 64

Defining categories by median ................................................................................. 68

Table of Contents
2

List of Figures

Figure 1: Major Coal Industry Supply Chain Link .................................................................. 7

Figure 2: Map of Coal-Dependent Counties, 2005 ................................................................ 10

Figure 3: Map of Coal-Dependent Counties, 2015................................................................ 11

Figure 4: Map of Coal Dependence, 2005 .......................................................................... 12

Figure 5: Map of Coal Dependence, 2015 ......................................................................... 13

Figure 6: Map of CIE Impacted Counties........................................................................... 16

Figure 7: Map of CIE Impact by Quintile........................................................................... 17

Figure 8: Correlation (-0.7786) between Coal Risk Score and Coal Impact Score ........................... 20

Figure 9: Map of 2015 CIE Risk....................................................................................... 21

Figure 10: Map of 2015 CIE Risk Score by Quintile............................................................... 22

Figure 11: CIE County Typology..................................................................................... 24

Figure 12: Maps of CIE Typology, Classes 1 through 4........................................................... 26

Figure 13: Maps of CIE Typology, Classes 5 through 8........................................................... 27

Figure 14: Map of CIE Typology, all Classes....................................................................... 28

Figure 15: CIE Class 1 Counties with One or More Top-20 Rankings .......................................... 30

Figure 16: Top Coal-Distressed Appalachian CIE Counties – All Scores ....................................... 32

List of Tables

Table 1: Top Industry CIE Scores .................................................................................... 9

Table 2: Highest CIE Dependence Counties, 2005 and 2015.................................................... 14

Table 3: Highest CIE Impact Counties ............................................................................. 18

Table 4: Highest CIE Risk Counties and Associated Values .................................................. 23

Table 5: Typology Score Combinations ............................................................................ 24

Table 6: CIE Class 1 Counties with One or More Top-20 Rankings ............................................. 29

Table 7: Top Coal-Distressed Appalachian CIE Counties – All Scores .......................................... 31
3

Estimating County-level Supply Chain Impacts and 

Key Suppliers

Executive Summary

The continuing decline in the U.S. coal industry has implications that differ from industry to industry 

and from region to region. These differences in industry implications arise because of the nature of 

the coal industry ecosystem (CIE), in which each industry occupies its unique position in the coal 

industry supply chain. There are industries that provide goods and services directly to the coal 

industry, and those that supply the coal industry indirectly via provision of goods and services to the 

first-level suppliers and to their suppliers throughout subsequent supply chain levels and linkages. 

Likewise, each region has a unique mix of industries, so as collections of industries, regional economies 

also vary in terms of their position in the CIE, and in terms of the extent to which they are aligned with 

the coal industry. These critical differences, in turn, give rise to impacts of coal decline that can vary 

substantially from region to region, from state to state, and from county to county. 

In this report, we describe an effort to provide for the Appalachian Region a clearer picture of the 

implications of long term declines in the coal industry, and the way in which these implications vary 

geographically. We develop and implement in this report three measures that reveal meaningful 

characteristics of the CIE at the county level, in terms of: industry and place-based CIE dependence, 

changes in CIE-dependent employment, and susceptibility to anticipated continued coal industry 

decline. We then combine these three measures―Dependence, Impact, and Risk―to form a typology 

that we apply to identify and focus on counties in three identifiable categories: Hardship counties, 

Vulnerable counties, and Depressed counties. 

The 123 Hardship counties rank below the median of all counties on the Dependence and Risk 

dimensions, and above the median on the Impact dimension. These counties have experienced high 

levels of negative impacts, but because they have lost most of their CIE-dependent industry jobs, they

are not at risk for further substantial coal decline-driven job loss. The 124 Vulnerable counties rank 

below the median score on the Impact dimension, but above median scores on the Dependence and 

Risk dimensions. These counties did not exhibit negative consequences of CIE decline between 2005 

and 2015, but because they are CIE-dependent and at risk of further coal industry decline, they form a 

group of counties with higher potential for future coal decline-driven job loss. The 83 Depressed

counties score above median on all three dimensions. They suffered CIE-dependent job losses between 

2005 and 2015, they continue to host CIE-dependent industries, and they are at risk of further future 

coal decline job-loss.

Finally, we narrow focus on the Depressed counties that rank highest on all three CIE-dimensions. 

Specifically, there are nine Depressed counties that rank in the top 20 on all three CIE dimensions. 
4

These are Mingo and Boone Counties in West Virginia; Harlan, Leslie, Martin, Pike, and Perry Counties 

in Kentucky; and Buchanan and Dickenson in Virginia. Unemployment rates in these counties range 

from a low of 8.9 percent to a high of 13.2 percent; job losses have been substantial, as high as 34

percent and averaging 21 percent. On average in these counties, roughly one in ten employees works in 

the coal industry itself, and their wages account for almost 23 percent of county totals. In two of these 

counties, coal-industry employment shares exceed 20 percent, and corresponding wage shares of total 

exceed 37 percent. These Depressed counties clearly warrant special attention and concern if current 

coal industry trends continue.
5

Introduction

To depict the production characteristics of the coal industry ecosystem requires an approach that

recognizes the role of production supply chains. Like manufacturing activities, the coal mining industry 

relies on many other industries for the materials and supplies it consumes in the coal mining and 

production process. In turn, these industries also require inputs from other industries to produce the 

supplies used by the coal industry. These second-order suppliers require inputs from third-order 

suppliers, and so on. Together, these direct and indirect industry connections create a web of 

interindustry linkages that make up the coal industry’s supply chain. This report uses industry-specific 

data and formal representations of interindustry linkages to assess Appalachian counties based on three 

primary dimensions of the coal industry ecosystem: Dependence, Impact, and Risk.

Overview

Given the declining trends in U.S. coal industry employment, we need a deeper understanding of the 

ways in which the implications of these declines vary regionally and which regions have been and might 

expect to be most strongly impacted by the downturn. There has been a growing focus on coalimpacted counties by federal agencies, in part due to direct funding and assistance programs for places 

that have been most heavily affected. Although coal-impacted county status generally carries a 

negative connotation, we also note that not all county CIEs have been negatively impacted. This leads 

us to define three important dimensions of CIEs: dependence, impact, and risk. Coal-dependence 

(hereafter simply Dependence) is defined by strong concentrations in industries that are central to the 

coal industry supply chain. Coal-impact (Impact) is defined by observed declines in coal-dependent

industries. Noting the observed relationships between counties that have declined least and their coal 

mine productivity, we define a coal-risk (Risk) index by combining Region-wide and county-based coaldependence and county-level coal mine productivity. Counties with high Dependence scores and lowproductivity mines are at greatest risk of further negative impact and economic distress. 
6

Analysis

To characterize counties relative to the CIE, we develop and implement a set of tools that target key 

supply chain industries and supply chain level impacts at the county level. Our methods use national 

benchmark input-output data from the U.S. Bureau of Economic Analysis, U.S. Department of Labor 

Mine Safety and Health Administration, U.S. Department of Commerce, Census of Population, and U.S. 

Bureau of Labor Statistics (BLS) Census of Employment and Wages (CEW).

1

Each of the next three subsections describes one of the CIE dimensions used to characterize 

Appalachian counties, including conceptual underpinnings and discussions of results presented 

graphically and numerically in tabular format. Mathematical formulations for the three dimensions are 

included as appendices. Next, we present a typology of Appalachian counties derived by combining the 

information generated by the three separate dimensions. The typology’s eight classes provide an 

effective summary of the extent to which Appalachian counties have been affected by coal industry 

declines. 

CIE Dependence

The overall objective in developing a county-based measure of coal dependence is to quantify the 

extent to which a county’s economy is dependent on coal. Counties that have relatively large and 

diverse economies would be expected to be able to adapt to changes in the CIE better than those

whose economic activities are tied strongly, either directly or indirectly, to the coal industry. In terms 

of economic resilience to coal industry downturns, then, Dependence is considered to be a negative. 

CIE Industry Scores

To estimate county dependence on coal requires that we develop a way to measure each industry’s 

direct and indirect dependence on coal. We can then combine this metric with county distributions of 

employment by industry to determine the shares of each industry’s employment that are coal-oriented. 

The ratio of the sum of all industries’ coal-oriented employment to county total employment will then 

provide a direct measure of county coal-dependence.

 

1 The BLS data are enhanced and extended by the Implan Group, a well-established commercial 

provider of such data. Published BLS CEW data omit data values that are subject to disclosure rules. 

Implan provides consistent estimates for missing data at the county level.
7

Figure 1: Major Coal Industry Supply Chain Link

The first step in implementation is to define the CIE to include the coal mining industry and its supply 

chain-linked industries. Coal mining obviously occupies the central CIE position in the supply chain. 

Upstream supplier industries and downstream purchasers can be connected directly by sales to and 

purchases from the coal mining industry, or by supply chain links to suppliers and purchasers to their 

supply chain-linked industries, and so on, as shown in Figure 1. In this report, we focus our analyses on 

coal industry purchases (i.e., upstream, backward linkages) because the industries to which coal is sold 

are more likely to modify their inputs—e.g., substituting natural gas for coal—when coal production 

declines than they are to reduce their activity levels. Indeed, some production declines have resulted 

precisely because the downstream demand for coal production has declined. Therefore, the ties to the 

upstream industries are more easily identified and measured. Upstream industries’ fortunes are tied 

more directly to the coal industry in that they are more likely to see demand for their products decline 

when coal production declines than are downstream industries. 

Direct and indirect upstream purchase requirements all can be identified straightforwardly using 

technical requirements coefficients from benchmark input-output (IO) accounts. The national accounts 

identify the total input requirements, but not their geographical sources. Some supply chain

transactions will be sourced within a county where coal mining occurs, some will be sourced elsewhere 

in Appalachia, and some will be outside of the Appalachian Region. We can estimate the extent to 

which industries in the Region are coal-oriented by comparing their output levels to the levels of supply 
8

needed to satisfy the direct and indirect demand due to coal industry operation in the Appalachian 

Region. For these reasons, we use information from the U.S. Bureau of Economic Analysis national 

input-output accounts to define the technical relationships among industries and, in turn, use this 

technical information in combination with Appalachian coal production statistics to identify the shares 

of output from other industries that would be needed to support the Appalachian Region’s coal 

industry. If an industry in the Appalachian Region produces less output than is needed to support 

Appalachian coal production, then we assume that all its production is entirely coal-dependent. If it 

produces more than enough to satisfy demands directly and indirectly associated with coal, then the 

coal-dependent share is the ratio of the amount needed by the Appalachian coal industry to the 

amount produced. 

These industry shares, or CIE Scores, for the top industries in 2005 and 2015 are shown along with 

corresponding employment levels in Table 1, and all CIE Industry Scores are listed in Appendix I.

2 The 

value for the coal mining industry has the maximum value of 1.0 in both years indicating that all of its 

employment is coal-dependent, as would be expected. The other industries’ shares lie between zero 

and 1.0, as only portions of their activity levels throughout the Region are dependent on coal. The 

industry-specific scores represent estimates of Dependence that reflect the ability of the entire Region 

to supply its own coal industry requirements. The scores imply that industries throughout the entire 

regional economy supply the entire Appalachian coal industry, irrespective of origin and destination of 

supply and demand, and that output from these industries goes first to the coal supply chain – the CIE –

and then to other industries after all of the CIE demands have been met.

3

 To provide more localized 

detail, parallel computations at the county level contribute to the Risk Score developed below.

4

 

2 A few CIE Scores are quite large primarily because they correspond to industries with very low 

employment values. Consequently, these high scores will have minimal impact on county Dependence 

Scores.

3 The formulation of these scores also implies frictionless transportation costs and no advantage for 

firms located near coal producing regions. 4 Note that the BLS CEW data that we use for our calculations do not include reliable estimates for the 

Rail Transportation industry, so the score for this industry is omitted. No employees were reported in 

this CEW industry in 2005, and only 39 employees were reported for 2015, so, beyond the 

undercounting of Rail Transportation employees, there is no significant impact on any of the 

calculations in the report.
9

Table 1: Top Industry CIE Scores

Industry 2005 CIE 

Score

2005 

Employment

2015 CIE 

Score

2015 

Employment

Coal mining 1 47,140 1 36,535

Mining and oil and gas field machinery 

manufacturing 0.37 4,905 0.29 5,404

Primary smelting and refining of copper 0.04 149 0.16 19

Rubber and plastics hoses and belting 

manufacturing 0.24 2,191 0.13 1,890

Ground or treated mineral and earth 

manufacturing 0.15 483 0.1 595

Stone mining and quarrying 0.08 14,588 0.07 7,972

Commercial and industrial machinery and 

equipment rental and leasing 0.17 4,466 0.06 8,539

Oil and gas extraction 0.16 4,984 0.06 10,692

Water transportation 0.07 1,773 0.06 1,353

Construction machinery manufacturing 0.1 6,384 0.05 7,599

CIE County Dependence Scores

CIE Scores are then applied to county industrial employment levels to derive an estimate of the number 

of coal supply chain-oriented employees in each industry in each county. The sum of these coaldependent county employees over all industries divided by total county employment is the Dependence 

Score for that county. 

For an initial, broad-brush view of the distribution of Dependent Appalachian counties, Figures 2 and 3

present a two-way classification of counties, distinguishing those with greater scores than the median 

Dependence values from those with lower scores than the median. The maximum Dependence Score for 

2005, expressed as a percentage, was 42.2 percent, but only a quarter of the counties had values 

greater than or equal to 1 percent, so the 2005 distribution is heavily skewed. By 2015, the maximum 

value had fallen to 22.4 percent, and less than one-fifth (73 counties, or 17.4 percent) of the counties 

in 2015 had values greater than 1 percent, resulting in a distribution of values that is even more 

strongly skewed. Between the two years, 76 of the 420 counties in the Appalachian Region (18.1

percent) shifted categories from low to high or vice versa, but none of those that switched are heavily 

coal-dependent.5

 

5 Only eight of these counties had Dependence Scores greater than 1 percent in 2015.
10

Figure 2: Map of Coal-Dependent Counties, 2005
11

Figure 3: Map of Coal-Dependent Counties, 2015

A more detailed view of Dependent counties is shown in Figures 4 and 5, which display county 

Dependence by quintile for 2005 and 2015. Bear in mind that there is far less variation in the lower 

four quintile intervals than in the highest quintile interval, and even within the highest quintile 

interval, the distribution remains skewed, where 73 of the 84 score values are less than half of the 22.4

percent maximum value, and ten of these counties have Dependence Scores with values less than 1

percent.
12

Figure 4: Map of Coal Dependence, 2005
13

Figure 5: Map of Coal Dependence, 2015

The complete listing of Dependence Scores by county appears in Appendix II. Table 2 below lists the

counties that had the highest twenty scores in either 2005 or 2015, along with their corresponding 

scores and ranks in each year. The rank ordering of the counties shows some minor instability, but the 

composition of both lists is mostly the same. There are several ways in which Dependence Scores can 

change. Because it is a measure that is based on employed persons, not unemployed persons, county 

Dependence Scores can decline due to reductions in CIE employment or increases in non-CIE 

employment. Conversely, Dependence Scores can increase due to increases in CIE employment (which 
14

is the explanation for the inclusion of the four new counties in the 2015 top 25 ranking) or decreases in 

non-CIE employment. Of course, offsetting changes can leave a county’s Dependence Score 

unchanged.

Table 2: Highest CIE Dependence Counties, 2005 and 2015

County Names 2005 Rank

2005 

Dependence 

Score

2015 Rank

2015 

Dependence 

Score

Boone County, West Virginia 1 42.2 3 21.9

Knott County, Kentucky 2 36.9 21 6.9

Leslie County, Kentucky 3 22.2 14 9.9

Mingo County, West Virginia 4 20.5 2 22.2

Greene County, Pennsylvania 5 19.8 4 18.4

Clay County, West Virginia 6 19.3 39 2.7

Martin County, Kentucky 7 18.3 11 11.9

Buchanan County, Virginia 8 17.1 6 15.3

Letcher County, Kentucky 9 16.4 23 5.6

Dickenson County, Virginia 10 16.3 9 12

Wyoming County, West 

Virginia 11 15.9 1 22.4

McDowell County, West 

Virginia 12 15.8 7 14.8

Pike County, Kentucky 13 15.8 18 8.6

Harlan County, Kentucky 14 14.9 15 9.8

Marshall County, West 

Virginia 15 12.2 5 17.3

Perry County, Kentucky 16 11.8 13 10.3

Logan County, West Virginia 17 11.6 12 11.6

Choctaw County, Mississippi 18 10.5 10 11.9

Webster County, West 

Virginia 19 9.6 8 13.3

Bell County, Kentucky 20 9 24 5.1

Harrison County, Ohio 22 8.9 16 8.9

Marion County, West Virginia 24 6.8 17 8.7

Taylor County, West Virginia 333 0.4 20 7.6

Tucker County, West Virginia 364 0.3 19 7.8
15

CIE Impact

Our county-level CIE Impact Scores are formed by combining the industry-based CIE Scores with 

employment change by industry, expressing the sum of the employment change-weighted CIE Scores as 

a share of total employment. The rationale for this approach is that if observed job loss occurs in coaloriented industries, then this negative economic impact and accompanying economic distress is the 

share of that employment loss that is associated with the coal industry. Employment change is defined 

as 2015 employment less 2005 employment.6 Employment loss yields negative values, so larger 

negative values correspond to greater negative Impact. Perhaps somewhat surprisingly, roughly 40

percent of counties actually gained in CIE related employment, which supports the observation that 

reliance on coal has not been uniformly negative across Appalachia. In 150 Appalachian counties, the 

Impact Score was between 0 percent and 1 percent, indicating relatively insubstantial change in CIE 

employment. Another 15 counties had Impact Scores between 1 percent and 3 percent, and the 

remaining positive Impact Scores fell between 3 percent and 8 percent. Of the counties in the High

Negative Impact and Moderate Negative Impact categories, the largest value is 32.797. All but three of

the 84 counties in the Low Impact category have negative values greater between -0.059 and -0.006, 

and the three positive values are less than 0.002. The Moderate Positive Impact category values range 

from 0.002 to 0.112, and the remainder range upward to 7.733. All Impact Scores are included in 

Appendix I. Figures 6 and 7 show Appalachian county Impact in two-category and quintile 

representation formats, paralleling the Dependence figures above. 

 

6 Of course, employment in CIE industries could be changing for other reasons, but the implied 

assumption of causality is used because of a lack of mechanism by which to identify other causes.
16

Figure 6: Map of CIE Impacted Counties
17

Figure 7: Map of CIE Impact by Quintile

Counties with the highest Impact Scores are shown in Table 3. Thirteen of the 20 most impacted

counties appear in the list of most Dependent counties in Table 2. These thirteen county names 

appear in bold in Table 3.
18

Table 3: Highest CIE Impact Counties

Rank County Names Impact 

Score

1 Knott County, Kentucky -32.8

2 Boone County, West Virginia -27.6

3 Clay County, West Virginia -17.4

4 Leslie County, Kentucky -14.8

5 Letcher County, Kentucky -12.4

6 Martin County, Kentucky -8.6

7 Pike County, Kentucky -8.1

8 Harlan County, Kentucky -7.7

9 Fayette County, Alabama -6.7

10 Mingo County, West Virginia -5.5

11 Wise County, Virginia -5.5

12 Bell County, Kentucky -4.7

13 Grant County, West Virginia -4.4

14 Vinton County, Ohio -4.3

15 Buchanan County, Virginia -3.5

16 Dickenson County, Virginia -2.9

17 Perry County, Kentucky -2.6

18 Clay County, Kentucky -2.4

19 Nicholas County, West Virginia -2.3

20 Elliott County, Kentucky -2.3

Note: Bold counties also appear on list of Dependent counties

CIE Risk

Our objective for this third dimension of CIE counties is to quantify the degree to which Appalachian 

Region counties are at risk of experiencing additional economic hardship should the decline in the coal 

industry continue. We base our conceptual framework for risk on the observation that counties with 

the largest observed CIE declines are generally those with low coal-mine productivity. Consistent with 

established economic principles, the lowest productivity mines will be least profitable and, therefore,

at greatest risk of closure. Highly productive mines will be most profitable and are, thus, at lowest risk 

for closure even in the face of overall industry decline.7 Counties that have no mines but that do have 

employment concentrations in CIE industries are at risk via supply chain linkages. This overall risk is 

directly correlated with the Dependence Scores. Counties that are host to operating mines face direct 

 

7 There are, of course, other reasons why mine can be uncompetitive, such as poor management 

practices, but these factors lie beyond our ability to measure.
19

risks of declining coal industry operation and localized supply-chain linkages that are tied to localized 

coal industry support activity. To capture this additional level of localized risk in coal-producing 

counties, we compute county-specific CIE industry scores from localized rather than Region-wide

production levels, and we then use these localized scores to generate a localized dependence score for 

each county. 

Mine productivity is assigned an index value between 0.0 and 1.0, and the localized dependence score 

values can vary from 0.0 to 1.0. The final Risk Score is the original, Region-wide Dependence Score 

combined with these two new variables. The formula for doing so is CRS = (CDS)(1 + Q)(1 + B), where 

CRS and CDS are CIE Risk and Dependence Scores, Q is the county-specific productivity-based risk

index, and B is the localized, county-specific dependence score. More formal mathematical 

expressions for all measures are included in Appendix III.

Correlation between Risk Score and Coal Impact

To confirm the validity of the Risk Score formulation and its interpretation, we calculated the 2005 CIE 

Risk Scores and compared them to the CIE Impact Scores. If our representation of Risk is well 

formulated, we should expect high-risk counties in 2005 to experience high negative impacts over the 

2005-2015 period, hence a negative correlation between the two variables across counties. Our 

expectations were confirmed by a correlation coefficient of -0.78. This suggests that most, but not all, 

high-risk counties indeed experienced negative impacts. There are some exceptions, of course, but an 

examination of the plot of this relationship in Figure 8 reveals that even in the absence of the extreme 

values on both scales, the generally negative relationship is readily apparent. This result confirms that 

counties with high 2015 CIE Risk warrant special attention and concern should the declining coal 

industry trends continue.
20

Figure 8: Correlation (-0.779) between Coal Risk Score and Coal Impact Score

Consistent with Dependence and Impact presentations above, Figure 9 displays the broad-brush view of 

Risk by county, and Figure 10 displays Risk Scores by quintile. Since the objective is to identify counties 

still at risk of economic hardship from future coal decline, the only the Risk measure based on 2015 

data is used for the CIE analysis.

-35%

-30%

-25%

-20%

-15%

-10%

-5%

0%

5%

10%

0% 10% 20% 30% 40% 50% 60% 70%

Coal Impact Score between 2005 - 2015

Coal Risk Score in 2005
21

Figure 9: Map of 2015 CIE Risk
22

Figure 10: Map of 2015 CIE Risk Score by Quintile

Ten of the 20 most impacted counties appear in the lists in Tables 2 and 3. These ten county names 

appear in bold in Table 4. Because Dependence is a component of Risk, these two measures are more 

strongly correlated than other CIE-dimension pairs.
23

Table 4: Highest CIE Risk Counties and Associated Values

Rank County Names Region-wide 

Dependence

Localized 

Dependence

MineProductivity 

Risk

Risk 

Score

1 Wyoming County, West Virginia 22.4 7.1 77.4 42.5

2 Boone County, West Virginia 21.9 6.5 64.6 38.4

3 Mingo County, West Virginia 22.2 5.8 50.3 35.3

4 McDowell County, West 

Virginia 14.8 3.2 97.6 30.2

5 Buchanan County, Virginia 15.3 4.5 46.3 23.4

6 Webster County, West Virginia 13.3 2.9 69.7 23.2

7 Martin County, Kentucky 11.9 3 87.5 22.9

8 Dickenson County, Virginia 12 3.3 78.2 22.1

9 Greene County, Pennsylvania 18.4 0 0 18.4

10 Logan County, West Virginia 11.6 3.5 53 18.3

11 Harlan County, Kentucky 9.8 2.6 75.2 17.7

12 Marshall County, West Virginia 17.3 0 0 17.3

13 Pike County, Kentucky 8.6 2.9 77.2 15.7

14 Leslie County, Kentucky 9.9 2 52.9 15.5

15 Perry County, Kentucky 10.3 2.6 40 14.8

16 Choctaw County, Mississippi 11.9 0.4 5.6 12.6

17 Harrison County, Ohio 8.9 1.7 30.2 11.7

18 Letcher County, Kentucky 5.6 1.5 91.6 10.9

19 Raleigh County, West Virginia 5.8 2.1 82.4 10.9

20 Taylor County, West Virginia 7.6 1.1 31.3 10.1

Note: Bold counties also appear in the list of most Dependent and Impacted counties.

CIE County Typology

To combine the information from the three dimensions and create a more comprehensive perspective 

on the Appalachian Region CIE, we developed a typology using an eight-way classification scheme. We 

assign counties to classes using combinations of the three High–Low groups on each dimension. 

Counties in Class 1 have High scores on all dimensions, counties in Class 8 have Low scores on all 

dimensions, and those in Classes 2–7 have varying combinations of High and Low category scores on the 
24

three dimensions. The resulting typology is depicted graphically in figure 11 and in tabular form in 

Table 5, along with the number of counties in each Class.

Figure 11: CIE County Typology

Table 5: Typology Score Combinations

Class Dependence Impact Risk Counties 

in Class

1 High High High 83

2 High High Low 2

3 High Low High 124

4 Low High High 2

5 High Low Low 1

6 Low High Low 123

7 Low Low High 1

8 Low Low Low 84
25

Counties in Classes 1 through 8 can be seen in the panels of Maps 9 and 10, and the overall distribution 

of counties by Class is shown in Map 11. Classes 1, 3, 6, and 8 are the most heavily populated, as would 

be expected given the correlation between Dependence and Risk. Counties in Class 1 are clearly the 

most distressed, and comprise the Depressed category. Counties in Class 3, the Vulnerable counties,

have not yet faced the levels of economic hardship of other CIE-dependent counties but are vulnerable 

to continued coal-industry decline. The Class 6 Hardship counties have experienced CIE-based 

declines, but because they have lost the majority of their CIE, their economies are no longer CIEdependent, so are not expected to incur further substantial CIE-based job loss. Counties in Class 8 are 

the least affected by the coal industry. 
26

Figure 12: Maps of CIE Typology, Classes 1 through 4
27

Figure 13: Maps of CIE Typology, Classes 5 through 8
28

Figure 14: Map of CIE Typology, all Classes

Three spatial patterns are most evident from these maps. First, the Class 1 Depressed counties are 

most heavily clustered near the West Virginia, Kentucky, and Virginia border intersections. Second, 

the Class 6 Hardship counties tend to be located near the periphery of the Region. Third, while the 

Class 3 Vulnerable counties are relatively widely dispersed in the Region’s southern states, they 

dominate West Virginia and Pennsylvania counties in the Region. There is also a cluster of nine 

contiguous Class 3 counties in eastern Ohio.
29

Coal-Distressed Counties

This section focuses on counties in Class 1 whose scores on all dimensions distinguish them from the

others. We identify two sets of such counties. The first set is composed of those counties within Class 

1 that also hold a top-20 ranking in at least one of the three CIE dimensions. This first set is shown in 

Table 6, along with their dimension-rankings and key socioeconomic variables. The group of counties 

shaded dark blue have no ranking lower than 20 on any of the CIE dimensions. The group in light blue 

has only one ranking lower than the top-20 ranking, and the third group has only one top-20 ranking. 

As can be seen in Figure 15, these counties are clustered in the heart of the Appalachian Region, with 

Vinton County, Ohio, as the only county located outside of West Virginia, Virginia, and Kentucky.

Table 6: CIE Class 1 Counties with One or More Top-20 Rankings

County

2015 

Dependence 

Rank

Impact 

Rank

2015 

Risk 

Rank

Unemployment Rate 

%

Population

Per 

capita 

personal 

income 

$

Mingo County, West 

Virginia 2 10 3 13.2 25,292 29,416

Harlan County, Kentucky 15 8 11 11.9 27,703 27,920

Leslie County, Kentucky 14 4 14 10.9 10,711 30,047

Buchanan County, Virginia 6 15 5 10.9 22,776 32,032

Dickenson County, Virginia 9 16 8 10.1 15,115 28,443

Boone County, West 

Virginia 3 2 2 9.7 23,372 31,352

Martin County, Kentucky 11 6 7 9.6 12,307 27,056

Pike County, Kentucky 18 7 13 9.3 61,792 33,354

Perry County, Kentucky 13 17 15 8.9 27,565 35,148

McDowell County, West 

Virginia 7 25 4 12.8 19,835 27,107

Letcher County, Kentucky 23 5 18 11.2 23,123 30,562

Logan County, West Virginia 12 22 10 11.2 34,707 33,546

Wise County, Virginia 31 11 27 12.6 43,657 29,829

Clay County, West Virginia 39 3 42 11.2 8,910 29,045

Knott County, Kentucky 21 1 24 10 15,693 28,652

Clay County, Kentucky 108 18 94 9.5 21,013 26,608

Nicholas County, West 

Virginia 34 19 31 9.1 25,594 32,184

Bell County, Kentucky 24 12 22 8.5 27,337 29,042

Vinton County, Ohio 66 14 60 6.5 13,048 30,478

Note: Bold counties are “Distressed” and those in italics are “At-Risk” counties in the 2017 

Appalachian Regional Commission classifications. The appearance of Vinton County, Ohio in this table is 

largely due to the presence of a single large employer that provides services to the mining industry.
30

Figure 15: CIE Class 1 Counties with One or More Top-20 Rankings
31

The second set of counties includes those that ranked in the top 20 in Risk, Impact, and Dependence in 

either 2005 or 2015. These are the counties that appear in bold in table 4, and all are present in Table 

6 above. The 2005 and 2015 employment and wages data for these counties, along with 2015 coal 

industry data, are shown in Table 7 below. These counties are also shown in Figure 16.

Table 7: Top Coal-Distressed Appalachian CIE Counties – All Scores

2005 2015 2015 Coal 

Industry

Name Total

Employment

Wages 

($M)

Total 

Employment

Wages 

($M) Employment Wages ($M)

Boone County, West 

Virginia 8,977 369.7 5,925 272.1 1,278 101.3

Buchanan County, Virginia 7,926 268.8 6,856 307.2 1,012 95.5

Dickenson County, 

Virginia 3,368 98 3,606 140.2 405 31.8

Harlan County, Kentucky 8,625 264.3 6,227 217.9 605 41.3

Leslie County, Kentucky 2,270 77.5 1,683 59.7 164 11.4

Letcher County, 

Kentucky 6,769 202 4,471 156 239 12.9

Martin County, Kentucky 3,222 110.5 2,584 106.9 300 19.7

Mingo County, West 

Virginia 8,291 294.2 5,553 244.9 1,216 98.9

Perry County, Kentucky 13,680 432.4 12,000 450.5 1,205 78.7

Pike County, Kentucky 24,579 799.2 21,500 879.1 1,779 112.8

Note: Bold counties are “Distressed” and those in italics are “At-Risk” counties in the 2017 

Appalachian Regional Commission classifications. 
32

Figure 16: Top Coal-Distressed Appalachian CIE Counties – All Scores
33

Summary

Through a comprehensive, quantitative, supply chain-based assessment of Appalachian Region 

counties, we identified industry and county characteristics related to the Coal Industry Ecosystem 

(CIE). Industry measures were developed to identify their relative positions in the coal industry supply 

chain, and these measures were weighted by employment and by employment change to construct 

county-based measures of CIE Dependence and CIE Impacts. We also developed a measure of risk that 

indicates each county’s susceptibility to continued coal industry decline. This risk measure is built 

upon the Region-wide CIE industry self-sufficiency Dependence Score, and adds a locally-based CIE 

industry self-sufficiency measure and an independent dimension that varies with the inverse of coal 

mine productivity. The 2005 Risk Score was shown to have a strong negative correlation with the 

Impact Score, validating its use as an indicator of susceptibility to negative impacts of continuing coal 

industry decline.

Each of these dimensions, as measured by Dependence, Impact, and Risk Scores, was assessed 

independently, and used subsequently in the construction of an eight-class county typology. The 

typology was used to identify four dominant county classes. Class 1 Depressed counties are the most 

highly distressed, with High Dependence, High Negative Impact, and High Risk Scores. They have 

already suffered negative CIE-related economic impacts, and are susceptible to future coal-industry 

declines. Class 3 Vulnerable counties have not yet faced levels of economic hardship comparable to 

those in Class 1, but they remain vulnerable to continued coal-industry decline. Class 6 Hardship 

counties have experienced CIE-based decline, but their economies are no longer CIE-dependent, so 

they are not subject to increased CIE-driven hardship in future, though many continue to suffer the 

consequences of recent coal-industry decline. Counties in Class 8 are not strongly tied to the CIE ― and 

have been and are expected to continue to be ― the least affected by the coal industry fortunes. 

The typology and the three county-level CIE Scores were used as a lens through which to identify the 

most distressed Appalachian counties whose condition can be most directly attributed to the CIE. 

These counties would be distressed by any number of measures, but given their strong ties to the CIE 

and vulnerability to continued coal-industry decline, they are particularly strong candidates for more 

in-depth analysis to identify policies and programs that might be implemented to dampen the negative 

impacts and alleviate some of the economic distress that can and will continue to be attributable to 

coal industry decline. 
34

References

U.S. Department of Commerce, Bureau of Economic Analysis. Benchmark Input-Output Data. 

https://www.bea.gov/industry/io_benchmark.htm

U.S. Department of Commerce, Census of Population. https://www.census.gov/topics/population.html

U.S. Department of Labor, Bureau of Labor Statistics. Census of Employment and Wages. 

http://www.bls.gov/home.htm

U.S. Department of Labor, Mine Safety and Health Administration. https://www.msha.gov/datareports/data-sources-calculators
35

Appendices

Appendix I. CIE Scores, All Industries

BEA Codes Name 2005 CIE 

Score

2005 

Employment

2015 CIE 

Score

2015 

Employment

1111A0 Oilseed farming 0.01 70 0 276

1111B0 Grain farming 0.01 304 0 760

111200 Vegetable and melon farming 0 1,963 0 2,525

111300 Fruit and tree nut farming 0 1,604 0 1,768

111400 Greenhouse, nursery, and 

floriculture production 0 9,019 0 6,859

111900 Other crop farming 0.05 817 0.02 973

1121A0

Beef cattle ranching and farming, 

including feedlots and dualpurpose ranching and farming0 963 0 1,175

112120 Dairy cattle and milk production 0 3,102 0 4,336

112A00 Animal production, except cattle 

and poultry and eggs 0 1,363 0 1,855

112300 Poultry and egg production 0 3,418 0 3,647

113000 Forestry and logging 0.04 7,850 0.02 6,169

114000 Fishing, hunting and trapping 0.01 138 0 171

115000 Support activities for agriculture 

and forestry 0.05 4,903 0.03 4,903

211000 Oil and gas extraction 0.16 4,984 0.06 10,692

212100 Coal mining 1 47,140 1 36,535

2122A0 Iron, gold, silver, and other metal 

ore mining 0.08 456 0.04 651

212230 Copper, nickel, lead, and zinc 

mining 0.69 19 0.02 717

212310 Stone mining and quarrying 0.08 14,588 0.07 7,972

2123A0 Other nonmetallic mineral mining 

and quarrying 0.03 3,697 0.02 2,478

213111 Drilling oil and gas wells 0 2,650 0 3,697

21311A Other support activities for mining 0.08 11,628 0.04 21,421

221100 Electric power generation, 

transmission, and distribution 0.01 53,077 0 49,397

221200 Natural gas distribution 0.01 7,914 0.01 8,224

221300 Water, sewage and other systems 0 21,846 0 23,376

23 Construction 0 474,924 0 403,310

321100 Sawmills and wood preservation 0.01 21,687 0.01 17,295

321200 Veneer, plywood, and engineered 

wood product manufacturing 0 13,722 0 7,082

321910 Millwork 0 24,409 0 15,672

3219A0 All other wood product 

manufacturing 0 32,982 0 21,057
36

327100 Clay product and refractory 

manufacturing

0 15,0120 8,652

327200 Glass and glass product 

manufacturing

0 16,6580 13,522

327310 Cement manufacturing 0.01 1,9600 2,111

327320 Ready

-mix concrete 

manufacturing 0.01 9,563

0 7,223

327330 Concrete pipe, brick, and block 

manufacturing 0.01 2,937 0.01 2,277

327390 Other concrete product 

manufacturing

0 6,0510 4,752

327400 Lime and gypsum product 

manufacturing 0.01 1,302

0 1,381

327910 Abrasive product manufacturing 0.03 727 0.02 532

327991 Cut stone and stone product 

manufacturing 0.01 3,459

0 3,844

327992 Ground or treated mineral and 

earth manufacturing 0.15 483 0.1 595

327993 Mineral wool manufacturing0 2,4200 1,163

327999 Miscellaneous nonmetallic mineral 

products 0.03 1,098 0.03 733

331110 Iron and steel mills and ferroalloy 

manufacturing 0.01 21,746 0.01 19,071

331200 Steel product manufacturing from 

purchased steel 0.02 11,776 0.01 8,922

33131A Alumina refining and primary 

aluminum production 0.01 2,350 0.02 466

331314 Secondary smelting and alloying of 

aluminum 0.01 1,362

0 954

33131B Aluminum product manufacturing 

from purchased aluminum

0 9,6980 9,020

331411 Primary smelting and refining of 

copper

0.04 149 0.16 19

331419

Primary smelting and refining of 

nonferrous metal (except copper 

and aluminum)

0.01 1,787 0.05 285

331420 Copper rolling, drawing, extruding 

and alloying 0.01 8,205 0.01 3,262

331490

Nonferrous metal (except copper 

and aluminum) rolling, drawing, 

extruding and alloying

0.01 6,151 0.01 7,400

331510 Ferrous metal foundries 0.03 13,030 0.01 10,472

331520 Nonferrous metal foundries 0.01 6,430 0.01 4,838

33211A All other forging, stamping, and 

sintering 0.01 9,383 0.01 9,807

332114 Custom roll forming 0.02 603 0.01 601

33211B Crown and closure manufacturing 

and metal stamping 0.01 5,634 0.01 4,969
37

332200 Cutlery and handtool 

manufacturing 0.02 6,038 0.01 4,088

332310 Plate work and fabricated 

structural product manufacturing 0.01 21,666

0 20,661

332320 Ornamental and architectural 

metal products manufacturing 0.01 21,070

0 18,463

332410 Power boiler and heat exchanger 

manufacturing

0 3,1250 2,578

332420 Metal tank (heavy gauge) 

manufacturing

0 2,7050 3,481

332430

Metal can, box, and other metal 

container (light gauge) 

manufacturing

0.01 5,7120 4,514

332500 Hardware manufacturing 0.02 3,683 0.01 1,908

332600 Spring and wire product 

manufacturing 0.01 6,621 0.01 4,380

332710 Machine shops 0.02 26,196 0.01 27,290

332720 Turned product and screw, nut, 

and bolt manufacturing 0.08 5,928 0.04 6,530

332800 Coating, engraving, heat treating 

and allied activities 0.02 11,205 0.01 9,999

33291A Valve and fittings other than 

plumbing 0.02 6,671 0.01 5,861

332913 Plumbing fixture fitting and trim 

manufacturing 0.01 850

0 999

332991 Ball and roller bearing 

manufacturing 0.01 5,944 0.01 4,416

33299A Ammunition, arms, ordnance, and 

accessories manufacturing

0 5,1920 5,955

332996 Fabricated pipe and pipe fitting 

manufacturing 0.01 2,002

0 2,497

33299B Other fabricated metal 

manufacturing 0.02 6,987 0.01 5,408

333111 Farm machinery and equipment 

manufacturing 0.01 2,647

0 3,409

333112 Lawn and garden equipment 

manufacturing

0 2,6920 1,800

333120 Construction machinery 

manufacturing 0.1 6,384 0.05 7,599

333130 Mining and oil and gas field 

machinery manufacturing 0.37 4,905 0.29 5,405

33329A Other industrial machinery 

manufacturing

0 9,2070 6,852

333220 Plastics and rubber industry 

machinery manufacturing

0 2,1220 1,568

333295 Semiconductor machinery 

manufacturing

0 243 0.01 104
38

33331A

Vending, commercial laundry, and 

other commercial and service 

industry machinery manufacturing

0 4,5040 3,106

333313 Office machinery manufacturing 0.04 230 0.02 154

333314 Optical instrument and lens 

manufacturing

0 9860 549

333315 Photographic and photocopying 

equipment manufacturing 0.01 308

0 47

33341A Air purification and ventilation 

equipment manufacturing

0 2,4920 1,759

333414 Heating equipment (except warm 

air furnaces) manufacturing

0 3,5090 1,934

333415

Air conditioning, refrigeration, 

and warm air heating equipment 

manufacturing

0 8,3830 5,945

333511 Industrial mold manufacturing0 4,7500 3,268

33351A Metal cutting and forming 

machine tool manufacturing 0.01 3,058

0 3,553

333514 Special tool, die, jig, and fixture 

manufacturing

0 8,7850 6,668

33351B

Cutting and machine tool 

accessory, rolling mill, and other 

metalworking machinery 

manufacturing

0.03 6,286 0.02 5,229

333611 Turbine and turbine generator set 

units manufacturing

0 3,5580 4,866

333612

Speed changer, industrial high-

speed drive, and gear 

manufacturing

0.09 740 0.02 1,436

333613 Mechanical power transmission 

equipment manufacturing 0.02 1,742 0.02 954

333618 Other engine equipment 

manufacturing 0.02 6,383 0.01 6,112

33391A Pump and pumping equipment 

manufacturing 0.01 1,931

0 2,084

333912 Air and gas compressor 

manufacturing

0 3,8890 3,739

333920 Material handling equipment 

manufacturing 0.06 9,012 0.03 9,722

333991 Power

-driven handtool 

manufacturing

0 1,9340 616

33399A Other general purpose machinery 

manufacturing 0.0

1 4,6120 5,276

333993 Packaging machinery 

manufacturing

0 1,3810 1,294

333994 Industrial process furnace and 

oven manufacturing

0 1,8480 1,593

33399B Fluid power process machinery 0.03 3,296 0.02 3,014

334111 Electronic computer 

manufacturing

0 5,7870 2,161
39

334112 Computer storage device 

manufacturing 0.01 547

0 733

33411A

Computer terminals and other 

computer peripheral equipment 

manufacturing

0.04 1,754 0.01 3,157

334210 Telephone apparatus 

manufacturing 0.01 3,097

0 3,012

334220 Broadcast and wireless 

communications equipment

0 3,8280 2,954

334290 Other communications equipment 

manufacturing 0.01 1,208 0.01 836

334300 Audio and video equipment 

manufacturing

0 3,2180 669

33441A Other electronic component 

manufacturing 0.01 15,136 0.01 8,61

3

334413 Semiconductor and related device 

manufacturing 0.08 1,303 0.03 1,573

334418

Printed circuit assembly 

(electronic assembly) 

manufacturing

0.01 4,5940 5,162

334510

Electromedical and 

electrotherapeutic apparatus 

manufacturing

0 2,2940 4,410

334511 Search, detection, and navigation 

instruments manufacturing

0 4,9650 3,104

334512 Automatic environmental control 

manufacturing 0.01 1,292 0.01 423

334513 Industrial process variable 

instruments manufacturing

0 5,0350 5,175

334514 Totalizing fluid meter and 

counting device manufacturing 0.01 2,824

0 2,378

334515 Electricity and signal testing 

instruments manufacturing

0 2,0790 684

334516 Analytical laboratory instrument 

manufacturing

0 1,3910 1,213

334517 Irradiation apparatus 

manufacturing

0.01 152 0.01 124

33451A

Watch, clock, and other 

measuring and controlling device 

manufacturing

0 2,6210 1,931

334610 Manufacturing and reproducing 

magnetic and optical media

0 6,0350 1,952

335110 Electric lamp bulb and part 

manufacturing

0 2,3840 1,042

335120 Lighting fixture manufacturing 0.01 3,3070 4,453

335210 Small electrical appliance 

manufacturing

0 1,8230 2,523

335221 Household cooking appliance 

manufacturing

0 4,4560 3,794
40

335222 Household refrigerator and home 

freezer manufacturing

0 2,6110 2,099

335224 Household laundry equipment 

manufacturing

0 8310

335228 Other major household appliance 

manufacturing

0 1,3510 1,102

335311 Power, distribution, and specialty 

transformer manufacturing

0 2,0960 2,142

335312 Motor and generator 

manufacturing 0.01 6,813

0 5,373

335313 Switchgear and switchboard 

apparatus manufacturing 0.01 3,233

0 5,012

335314 Relay and industrial control 

manufacturing 0.01 4,685 0.01 6,433

335911 Storage battery manufacturing 0.01 2,5370 1,935

335912 Primary battery manufacturing0 1,8040 1,064

335920 Communication and energy wire 

and cable manufacturing

0 4,1380 3,100

335930 Wiring device manufacturing0 5,5210 4,994

335991 Carbon and graphite product 

manufacturing

0 2,7080 2,133

335999

All other miscellaneous electrical 

equipment and component 

manufacturing

0.01 1,632 0.01 1,470

336111 Automobile manufacturing0 15,4770 20,404

336112 Light truck and utility vehicle 

manufacturing

0 3,4570 3,446

336120 Heavy duty truck manufacturing0 7,7570 6,712

336211 Motor vehicle body manufacturing0 4,9280 6,425

336212 Truck trailer manufacturing0 4,0800 4,459

336213 Motor home manufacturing0 2,2100 1,815

336214 Travel trailer and camper 

manufacturing

0 3,6490 2,807

336310 Motor vehicle gasoline engine and 

engine parts manufacturing 0.01 10,772

0 11,429

336320

Motor vehicle electrical and 

electronic equipment 

manufacturing

0.01 14,6930 12,831

3363A0

Motor vehicle steering, suspension 

component (except spring), and 

brake systems manufacturing

0.01 12,6210 11,778

336350 Motor vehicle transmission and 

power train parts manufacturing 0.01 8,764

0 10,050

336360 Motor vehicle seating and interior 

trim manufacturing

0 8,6140 12,429

336370 Motor vehicle metal stamping0 8,5360 11,255

336390 Other motor vehicle parts 

manufacturing 0.01 18,024 0.01 16,873
41

336411 Aircraft manufacturing0 3,9220 4,104

336412 Aircraft engine and engine parts 

manufacturing

0 3,6100 4,634

336413 Other aircraft parts and auxiliary 

equipment manufacturing

0 4,5100 4,630

336414 Guided missile and space vehicle 

manufacturing

0 2,2910 2,171

33641A Propulsion units and parts for 

space vehicles and guided missiles

0 1,9020 2,654

336500 Railroad rolling stock 

manufacturing 0.01 10,801 0.01 10,269

336611 Ship building and repairing 0.03 533 0.01 988

336612 Boat building0 8,6650 3,037

336991 Motorcycle, bicycle, and parts 

manufacturing

0 6470 744

336992

Military armored vehicle, tank, 

and tank component 

manufacturing

0 2010 815

336999 All other transportation 

equipment manufacturing

0 5560 524

337110 Wood kitchen cabinet and 

countertop manufacturing

0 17,1030 11,161

337121 Upholstered household furniture 

manufacturing

0 36,8240 25,162

337122 Nonupholstered wood household 

furniture manufacturing

0 21,6570 5,442

33712A Other household nonupholstered 

furniture

0 2,9170 1,134

337127 Institutional furniture 

manufacturing

0 4,8120 1,694

33721A

Office furniture and custom 

architectural woodwork and 

millwork manufacturing

0 4,9200 5,331

337215 Showcase, partition, shelving, and 

locker manufacturing

0 8,2940 5,972

337900 Other furniture related product 

manufacturing

0 5,0210 3,908

339112 Surgical and medical instrument 

manufacturing

0 2,8260 3,065

339113 Surgical appliance and supplies 

manufacturing

0 10,8200 8,057

339114 Dental equipment and supplies 

manufacturing

0 4590 330

339115 Ophthalmic goods manufacturing0 3,6870 2,375

339116 Dental laboratories0 3,3700 2,997

339910 Jewelry and silverware 

manufacturing

0 4800 308

339920 Sporting and athletic goods 

manufacturing

0 3,5020 2,379
42

339930 Doll, toy, and game 

manufacturing

0 1,2260 463

339940 Office supplies (except paper) 

manufacturing

0 1,1220 1,240

339950 Sign manufacturing0 5,8770 5,702

339990 All other miscellaneous 

manufacturing

0.01 12,453 0.01 8,707

311111 Dog and cat food manufacturing0 2,1080 2,761

311119 Other animal food manufacturing0 2,7980 2,502

311210 Flour milling and malt 

manufacturing

0 8220 633

311221 Wet corn milling 0.02 171 0.01 284

31122A Soybean and other oilseed 

processing 0.01 343

0 469

311225 Fats and oils refining and blending0 4150 513

311230 Breakfast cereal manufacturing0 20104

311300 Sugar and confectionery product 

manufacturing

0 6,2490 5,771

311410 Frozen food manufacturing0 7,1190 6,807

311420 Fruit and vegetable canning, 

pickling, and drying

0 5,3820 3,886

31151A Fluid milk and butter 

manufacturing

0 5,4850 5,809

311513 Cheese manufacturing0 1,4280 1,629

311514 Dry, condensed, and evaporated 

dairy product manufacturing

0 4100 344

311520 Ice cream and frozen dessert 

manufacturing

0 2,0440 1,658

31161A

Animal (except poultry) 

slaughtering, rendering, and 

processing

0 17,0680 12,410

311615 Poultry processing0 46,7400 43,820

311700 Seafood product preparation and 

packaging

0 1,2170 318

311810 Bread and bakery product 

manufacturing

0 20,7680 17,311

3118A0 Cookie, cracker, pasta, and 

tortilla manufacturing

0 4,7150 6,180

311910 Snack food manufacturing0 3,5870 3,452

311920 Coffee and tea manufacturing0 9710 1,776

311930 Flavoring syrup and concentrate 

manufacturing 0.01 60

0 63

311940 Seasoning and dressing 

manufacturing

0 1,2460 2,142

311990 All other food manufacturing0 2,2550 2,750

312110 Soft drink and ice manufacturing0 11,6660 8,295

312120 Breweries0 1,3280 2,702

312130 Wineries0 1,5710 2,538
43

312140 Distilleries100 468

312200 Tobacco product manufacturing0 7,6280 2,315

313100 Fiber, yarn, and thread mills0 20,5620 11,055

313200 Fabric mills0 35,7510 19,074

313300 Textile and fabric finishing and 

fabric coating mills

0 15,3240 8,057

314110 Carpet and rug mills0 36,4630 24,485

314120 Curtain and linen mills0 8,9130 2,821

314900 Other textile product mills 0.01 12,591 0.01 8,856

315000 Apparel manufacturing0 31,8240 10,138

316000 Leather and allied product 

manufacturing

0 3,3360 1,899

322110 Pulp mills 0.01 5190 744

322120 Paper mills 0.01 9,9240 6,173

322130 Paperboard mills 0.01 3,586 0.01 2,938

322210 Paperboard container 

manufacturing 0.01 16,271

0 13,889

322220 Paper bag and coated and treated 

paper manufacturing 0.01 6,628 0.01 5,578

322230 Stationery product manufacturing0 4,8310 3,158

322291 Sanitary paper product 

manufacturing

0 3,4120 4,473

322299 All other converted paper product 

manufacturing

0 2,2810 2,102

323110 Printing 0.01 40,7140 28,043

323120 Support activities for printing 0.01 2,8360 1,901

324110 Petroleum refineries 0.09 2,587 0.05 2,561

324121 Asphalt paving mixture and block 

manufacturing

0 1,7530 1,701

324122 Asphalt shingle and coating 

materials manufacturing

0 1,2850 815

324190 Other petroleum and coal 

products manufacturing 0.03 3,739 0.02 3,940

325110 Petrochemical manufacturing 0.06 902 0.03 902

325120 Industrial gas manufacturing 0.02 2,827 0.02 1,400

325130 Synthetic dye and pigment 

manufacturing 0.01 3,434

0 2,735

325180 Other basic inorganic chemical 

manufacturing

0 14,013 0.01 4,511

325190 Other basic organic chemical 

manufacturing 0.01 4,032

0 10,626

325211 Plastics material and resin 

manufacturing 0.01 9,692

0 9,172

3252A0

Synthetic rubber and artificial and 

synthetic fibers and filaments 

manufacturing

0.01 9,0900 8,120

325310 Fertilizer manufacturing 0.01 1,578 0.01 723
44

325320 Pesticide and other agricultural 

chemical manufacturing

0 4920 482

325411 Medicinal and botanical 

manufacturing

0 5420 684

325412 Pharmaceutical preparation 

manufacturing

0 10,3870 12,033

325413 In

-vitro diagnostic substance 

manufacturing

0 5540 861

325414 Biological product (except 

diagnostic) manufacturing

0 2,3590 2,797

325510 Paint and coating manufacturing 0.01 3,688 0.01 2,353

325520 Adhesive manufacturing 0.01 2,1800 1,793

325610 Soap and cleaning compound 

manufacturing

0 4,8840 4,851

325620 Toilet preparation manufacturing0 1,5230 1,220

325910 Printing ink manufacturing 0.01 566 0.01 458

3259A0 All other chemical product and 

preparation manufacturing 0.07 7,567 0.03 8,035

326110

Plastics packaging materials and 

unlaminated film and sheet 

manufacturing

0.01 12,9710 12,541

326120

Plastics pipe, pipe fitting, and 

unlaminated profile shape 

manufacturing

0.01 6,1100 5,525

326130

Laminated plastics plate, sheet 

(except packaging), and shape 

manufacturing

0 3,9020 2,408

326140 Polystyrene foam product 

manufacturing

0 3,0300 3,704

326150

Urethane and other foam product 

(except polystyrene) 

manufacturing

0 5,3810 5,159

326160 Plastics bottle manufacturing0 2,1270 2,485

326190 Other plastics product 

manufacturing 0.01 43,730

0 39,822

326210 Tire manufacturing 0.04 13,308 0.02 12,747

326220 Rubber and plastics hoses and 

belting manufacturing 0.24 2,191 0.13 1,890

326290 Other rubber product 

manufacturing 0.01 11,474 0.01 12,104

420000 Wholesale trade 0.02 349,063 0.01 332,949

441000 Motor vehicle and parts dealers0 160,2350 158,078

445000 Food and beverage stores0 226,9160 222,990

452000 General merchandise stores0 273,2680 273,303

4A0000 Other retail0 624,5760 553,898

481000 Air transportation 0.01 16,055 0.01 8,361

482000 Rail transportation10 0.33 39

483000 Water transportation 0.07 1,773 0.06 1,353
45

484000 Truck transportation 0.01 143,624 0.01 131,836

485000 Transit and ground passenger 

transportation

0 55,8170 44,943

486000 Pipeline transportation0 28,137 0.02 4,193

48A000

Scenic and sightseeing 

transportation and support 

activities for transportation

0.01 63,855 0.01 32,906

492000 Couriers and messengers 0.01 59,936 0.01 32,364

493000 Warehousing and storage0 84,7210 70,431

511110 Newspaper publishers 0.01 28,1800 17,466

511120 Periodical Publishers 0.01 5,355 0.01 3,759 511130 Book publishers 0 1,506 0 1,527

5111A0 Directory, mailing list, and other 

publishers 0.01 3,648 0.01 1,431

511200 Software publishers0 6,7720 8,791

512100 Motion picture and video 

industries

0 10,2960 9,183

512200 Sound recording industries0 4220 404

515100 Radio and television broadcasting 0.01 16,7220 13,639

515200 Cable and other subscription 

programming 0.01 3,823 0.01 1,917

517110 Wired telecommunications 

carriers

0 47,0710 34,902

517210 Wireless telecommunications 

carriers (except satellite)

0 12,2610 9,669

517A00

Satellite, telecommunications 

resellers, and all other 

telecommunications

0.01 5,9010 3,041

518200 Data processing, hosting, and 

related services 0.01 13,105 0.01 11,706

5191A0

News syndicates, libraries, 

archives and all other information 

services

0 11,6470 10,319

519130

Internet publishing and 

broadcasting and Web search 

portals

0.04 589 0.03 1,876

52A000 Monetary authorities and 

depository credit intermediation 0.01 146,920

0 137,403

522A00

Nondepository credit

intermediation and related 

activities

0.02 44,736 0.01 41,163

523A00

Securities and commodity 

contracts intermediation and 

brokerage

0.03 11,265 0.02 8,910

523900 Other financial investment 

activities 0.04 6,361 0.02 11,941

524100 Insurance carriers0 66,3510 56,224

524200 Insurance agencies, brokerages, 

and related activities 0.01 52,007

0 57,064
46

525000 Funds, trusts, and other financial 

vehicles

0 1,8650 146

531 Housing and other real estate0 68,3450 67,767

532100 Automotive equipment rental and 

leasing 0.01 9,049 0.01 10,728

532A00 Consumer goods and general 

rental centers 0.01 25,237

0 15,614

532400

Commercial and industrial 

machinery and equipment rental 

and leasing

0.17 4,466 0.06 8,539

533000 Lessors of nonfinancial intangible 

assets 0.04 951 0.03 823

541100 Legal services 0.01 61,252 0.01 55,498

541511 Custom computer programming 

services

0 19,5400 25,305

541512 Computer systems design services 0.01 19,138 0.01 36,014

54151A Other computer related services, 

including facilities management 0.01 7,536 0.01 6,590

541200 Accounting, tax preparation, 

bookkeeping, and payroll services 0.02 44,687 0.01 46,303

541300 Architectural, engineering, and 

related services 0.02 86,817 0.01 91,468

541400 Specialized design services 0.01 6,710 0.01 4,753

541610 Management consulting services 0.01 31,809 0.01 34,582

5416A0 Environmental and other technical 

consulting services 0.02 5,752 0.01 8,797

541700 Scientific research and 

development services

0 23,2690 27,961

541800 Advertising, public relations, and 

related services 0.02 16,106 0.01 14,353

5419A0

Marketing research and all other 

miscellaneous professional, 

scientific, and technical services

0.02 6,719 0.01 7,948

541920 Photographic services0 6,1970 3,130

541940 Veterinary services0 19,8910 25,826

550000 Management of companies and 

enterprises 0.04 87,229 0.02 128,312

561100 Office administrative services 0.01 18,614 0.01 17,390

561200 Facilities support services 0.01 5,1290 9,969

561300 Employment services 0.01 190,4560 218,494

561400 Business support services 0.01 59,139 0.01 66,562

561500 Travel arrangement and 

reservation services 0.01 9,463 0.01 7,336

561600 Investigation and security services 0.01 37,926 0.01 44,104

561700 Services to buildings and dwellings 0.01 101,402 0.01 117,449

561900 Other support services 0.01 16,083 0.01 16,230

562000 Waste management and 

remediation services 0.01 25,754 0.01 31,623
47

611100 Elementary and secondary schools0 615,3040 583,384

611A00

Junior colleges, colleges, 

universities, and professional 

schools

0 207,6380 246,271

611B00 Other educational services0 33,5160 35,063

621100 Offices of physicians0 163,9520 192,373

621200 Offices of dentists0 51,7200 57,648

621300 Offices of other health 

practitioners

0 45,5840 63,090

621400 Outpatient care centers0 47,1890 65,331

621500 Medical and diagnostic 

laboratories

0 10,2970 14,457

621600 Home health care services0 53,2120 74,457

621900 Other ambulatory health care 

services

0 26,5470 31,922

622000 Hospitals0 441,8320 457,206

623A00 Nursing and community care 

facilities

0 207,7350 223,211

623B00

Residential mental retardation, 

mental health, substance abuse 

and other facilities

0 73,6670 80,872

624100 Individual and family services0 93,2800 138,691

624A00

Community food, housing, and 

other relief services, including 

rehabilitation services

0 42,6840 39,971

624400 Child day care services0 56,2680 58,492

711100 Performing arts companies 0.01 4,7690 5,031

711200 Spectator sports0 6,2870 5,497

711A00

Promoters of performing arts and 

sports and agents for public 

figures

0 4,3670 7,695

711500 Independent artists, writers, and 

performers 0.01 1,299 0.01 1,195

712000 Museums, historical sites, zoos, 

and parks

0 12,1660 13,610

713100 Amusement parks and arcades0 6,0950 7,069

713200 Gambling industries (except 

casino hotels)

0 6,9740 11,595

713900 Other amusement and recreation 

industries

0 75,6400 74,715

721000 Accommodation0 91,6200 105,133

722110 Full-service restaurants0 313,9490 351,225

722211 Limited-service restaurants0 328,3590 382,610

722A00 All other food and drinking places0 49,5020 56,232

811100 Automotive repair and 

maintenance

0 59,8790 57,928
48

811200

Electronic and precision 

equipment repair and 

maintenance

0.01 6,438 0 6,769

811300

Commercial and industrial 

machinery and equipment repair 

and maintenance

0.01 17,026 0 18,186

811400 Personal and household goods 

repair and maintenance 0.01 4,703 0.01 3,488

812100 Personal care services 0 36,110 0 37,560

812200 Death care services 0 16,392 0 16,337

812300 Dry-cleaning and laundry services 0 22,385 0 17,940

812900 Other personal services 0 9,854 0 10,491

813100 Religious organizations 0 10,455 0 12,434

813A00 Grantmaking, giving, and social 

advocacy organizations 0 21,479 0 19,829

813B00 Civic, social, professional, and 

similar organizations 0 56,412 0 51,686

814000 Private households 0 14,086 0 14,060

491000 Postal Service 0.01 59,304 0 45,610

92 Government 0 465,186 0 473,556

Data	Sources:	Bureau	of	Labor	Statistics and	Bureau	of	Economic	Analysis
49

Appendix II. All Dependence, Impact, and Risk Scores

FIPS County Names 2015 Global 

Dependence

2015 Local 

Dependence

Impact 

Score

2015 MineProductivity 

Risk

2015 

Total 

Risk

1007 Bibb, AL 0.25 0 -0.18 0 0.25

1009 Blount, AL 0.92 0.21 0.61 77.62 1.65

1015 Calhoun, AL 0.25 0 -0.08 0 0.25

1017 Chambers, AL 0.29 0 -0.04 0 0.29

1019 Cherokee, AL 0.19 0 -0.07 0 0.19

1021 Chilton, AL 0.25 0 0.1 0 0.25

1027 Clay, AL 0.24 0 -0.1 0 0.24

1029 Cleburne, AL 0.16 0 -0.12 0 0.16

1033 Colbert, AL 0.33 0 0.06 0 0.33

1037 Coosa, AL 0.19 0 0 0 0.19

1043 Cullman, AL 0.26 0 -0.12 0 0.26

1049 DeKalb, AL 0.26 0 0.02 0 0.26

1051 Elmore, AL 0.18 0 0.03 0 0.18

1055 Etowah, AL 0.31 0 0.03 0 0.31

1057 Fayette, AL 0.25 0 -6.69 0 0.25

1059 Franklin, AL 0.35 0 0.05 40.61 0.49

1065 Hale, AL 0.35 0 0 0 0.35

1071 Jackson, AL 0.24 0 -0.14 7.62 0.26

1073 Jefferson, AL 0.7 0.16 -0.14 78.27 1.26

1075 Lamar, AL 0.69 0 0.02 0 0.69

1077 Lauderdale, AL 0.23 0 -0.03 0 0.23

1079 Lawrence, AL 0.22 0 -0.18 0 0.22

1083 Limestone, AL 0.24 0 -0.11 0 0.24

1087 Macon, AL 0.09 0 -0.08 0 0.09

1089 Madison, AL 0.3 0 0.03 0 0.3

1093 Marion, AL 0.34 0 -0.38 0 0.34

1095 Marshall, AL 0.24 0 -0.03 0 0.24

1103 Morgan, AL 0.33 0 -0.02 0 0.33

1107 Pickens, AL 0.28 0 -0.13 0 0.28

1111 Randolph, AL 0.24 0 0 0 0.24

1115 St. Clair, AL 0.29 0 0.09 0 0.29

1117 Shelby, AL 0.59 0.05 0.31 47.52 0.87

1121 Talladega, AL 0.3 0 -0.03 0 0.3

1123 Tallapoosa, AL 0.26 0 0 0 0.26
50

1125 Tuscaloosa, AL 1.92 0.62 0.39 81.27 3.5

1127 Walker, AL 2.06 0.62-0.33 76.29 3.65

1133 Winston, AL 0.77 0.16 0.34 76.04 1.35

13011 Banks, GA 0.190-0.010 0.19

13013 Barrow, GA 0.30 0.140 0.3

13015 Bartow, GA 0.410 0.140 0.41

13045 Carroll, GA 0.250 0.080 0.25

13047 Catoosa, GA 0.20-0.020 0.2

13055 Chattooga, GA 0.180-0.040 0.18

13057 Cherokee, GA 0.250 0.120 0.25

13083 Dade, GA 0.210-0.050 0.21

13085 Dawson, GA 0.190 0.050 0.19

13097 Douglas, GA 0.270 0.040 0.27

13105 Elbert, GA 0.570-0.050 0.57

13111 Fannin, GA 0.20 0.030 0.2

13115 Floyd, GA 0.230-0.020 0.23

13117 Forsyth, GA 0.350 0.310 0.35

13119 Franklin, GA 0.310-0.050 0.31

13123 Gilmer, GA 0.210-0.080 0.21

13129 Gordon, GA 0.250-0.040 0.25

13135 Gwinnett, GA 0.390 0.050 0.39

13137 Habersham, GA 0.180-0.080 0.18

13139 Hall, GA 0.250-0.040 0.25

13143 Haralson, GA 0.30 0.020 0.3

13147 Hart, GA 0.260-0.080 0.26

13149 Heard, GA 0.40-0.250 0.4

13157 Jackson, GA 0.470 0.540 0.47

13187 Lumpkin, GA 0.170-0.110 0.17

13195 Madison, GA 0.240-0.160 0.24

13213 Murray, GA 0.50 0.180 0.5

13223 Paulding, GA 0.20 0.10 0.2

13227 Pickens, GA 0.320-0.10 0.32

13233 Polk, GA 0.240-0.040 0.24

13241 Rabun, GA 0.160-0.10 0.16

13257 Stephens, GA 0.290-0.10 0.29

13281 Towns, GA 0.160-0.090 0.16

13291 Union, GA 0.19000 0.19

13295 Walker, GA 0.190-0.020 0.19

13311 White, GA 0.30 0.210 0.3

13313 Whitfield, GA 0.280-0.030 0.28

21001 Adair, KY 0.180-0.080 0.18
51

21011 Bath, KY 0.140-0.010 0.14

21013 Bell, KY 5.12 1.54-4.66 82.7 9.5

21019 Boyd, KY 0.620-0.11 22.65 0.76

21025 Breathitt, KY 1.51 0.32 0.71 61.27 2.44

21043 Carter, KY 0.56 0.1 0.1 87.09 1.05

21045 Casey, KY 0.310-0.030 0.31

21049 Clark, KY 0.370 0.020 0.37

21051 Clay, KY 0.540-2.44 50.1 0.82

21053 Clinton, KY 0.160 0.070 0.16

21057 Cumberland, KY 0.170 0.040 0.17

21061 Edmonson, KY 0.150 0.050 0.15

21063 Elliott, KY 0.070-2.290 0.07

21065 Estill, KY 0.180-0.05 50 0.26

21069 Fleming, KY 0.230-0.130 0.23

21071 Floyd, KY 4.02 1.23-1.8 65.64 6.74

21079 Garrard, KY 0.280 0.050 0.28

21087 Green, KY 0.130-0.030 0.13

21089 Greenup, KY 0.290-0.110 0.29

21095 Harlan, KY 9.84 2.61-7.73 75.2 17.68

21099 Hart, KY 0.190-0.020 0.19

21109 Jackson, KY 0.20-0.330 0.2

21115 Johnson, KY 2.03 0.41-0.63 86.37 3.79

21119 Knott, KY 6.92 0.83-32.8 27.17 8.88

21121 Knox, KY 0.68 0.1-0.72 100 1.36

21125 Laurel, KY 1.1 0.16 0.08 100 2.21

21127 Lawrence, KY 0.49 0.06-0.72 63.24 0.8

21129 Lee, KY 0.49 0.02-0.95 19.59 0.59

21131 Leslie, KY 9.95 2.01-14.76 52.91 15.51

21133 Letcher, KY 5.62 1.49-12.36 91.6 10.93

21135 Lewis, KY 0.250 0.040 0.25

21137 Lincoln, KY 0.320 0.180 0.32

21147 McCreary, KY 1.18 0.15 0.49 100 2.36

21151 Madison, KY 0.37 0.02 0.11 7.42 0.4

21153 Magoffin, KY 1.75 0.34-0.28 64.18 2.89

21159 Martin, KY 11.863-8.57 87.48 22.9

21165 Menifee, KY 0.380 0.030 0.38

21169 Metcalfe, KY 0.260-0.090 0.26

21171 Monroe, KY 0.320-0.230 0.32

21173 Montgomery, KY 0.720 0.110 0.72

21175 Morgan, KY 2.71 0.56 2.32 78.71 4.87

21181 Nicholas, KY 0.150-0.030 0.15
52

21189 Owsley, KY 4.39 0.244 36.5 6.01

21193 Perry, KY 10.3 2.57-2.57 40 14.79

21195 Pike, KY 8.59 2.87-8.07 77.21 15.66

21197 Powell, KY 0.360 0.140 0.36

21199 Pulaski, KY 0.230-0.060 0.23

21201 Robertson, KY 0.110 0.030 0.11

21203 Rockcastle, KY 0.220 0.020 0.22

21205 Rowan, KY 0.230-0.010 0.23

21207 Russell, KY 0.230-0.080 0.23

21231 Wayne, KY 0.250-0.080 0.25

21235 Whitley, KY 1.59 0.32 1.19 100 3.2

21237 Wolfe, KY 2.59 0.38 2.3 75.55 4.56

24001 Allegany, MD 0.23 0.01-0.12 42.96 0.32

24023 Garrett, MD 1.14 0.26-1.59 77.2 2.03

24043 Washington, MD 0.310-0.010 0.31

28003 Alcorn, MS 0.270 0.010 0.27

28009 Benton, MS 0.220-0.220 0.22

28013 Calhoun, MS 0.290-0.10 0.29

28017 Chickasaw, MS 0.160-0.010 0.16

28019 Choctaw, MS 11.9 0.38 1.78 5.57 12.61

28025 Clay, MS 0.250-0.10 0.25

28057 Itawamba, MS 0.230-0.150 0.23

28069 Kemper, MS 2.590.21 3.51 100 5.2

28081 Lee, MS 0.320 0.020 0.32

28087 Lowndes, MS 0.280 0.070 0.28

28093 Marshall, MS 0.230 0.020 0.23

28095 Monroe, MS 0.250-0.170 0.25

28097 Montgomery, MS 0.250-0.110 0.25

28103 Noxubee, MS 0.230-0.180 0.23

28105 Oktibbeha, MS 0.230 0.050 0.23

28107 Panola, MS 0.290-0.150 0.29

28115 Pontotoc, MS 0.130-0.020 0.13

28117 Prentiss, MS 0.220-0.020 0.22

28139 Tippah, MS 0.280-0.010 0.28

28141 Tishomingo, MS 0.240 0.020 0.24

28145 Union, MS 0.270 0.130 0.27

28155 Webster, MS 0.310-0.040 0.31

28159 Winston, MS 0.60-0.120 0.6
53

28161 Yalobusha, MS 0.22000 0.22

36003 Allegany, NY 0.150-0.120 0.15

36007 Broome, NY 0.230-0.080 0.23

36009 Cattaraugus, NY 0.20-0.090 0.2

36013 Chautauqua, NY 0.260-0.030 0.26

36015 Chemung, NY 0.390 0.230 0.39

36017 Chenango, NY 0.470 0.340 0.47

36023 Cortland, NY 0.220-0.030 0.22

36025 Delaware, NY 0.230-0.070 0.23

36077 Otsego, NY 0.130-0.050 0.13

36095 Schoharie, NY 0.160-0.060 0.16

36097 Schuyler, NY 0.140-0.050 0.14

36101 Steuben, NY 0.250 0.030 0.25

36107 Tioga, NY 0.350 0.180 0.35

36109 Tompkins, NY 0.170-0.010 0.17

37003 Alexander, NC 0.150 0.010 0.15

37005 Alleghany, NC 0.150-0.050 0.15

37009 Ashe, NC 0.360-0.060 0.36

37011 Avery, NC 0.190-0.050 0.19

37021 Buncombe, NC 0.260 0.080 0.26

37023 Burke, NC 0.160-0.110 0.16

37027 Caldwell, NC 0.240-0.10 0.24

37039 Cherokee, NC 0.230-0.110 0.23

37043 Clay, NC 0.160-0.030 0.16

37059 Davie, NC 0.250-0.020 0.25

37067 Forsyth, NC 0.320 0.050 0.32

37075 Graham, NC 0.20-0.140 0.2

37087 Haywood, NC 0.170-0.050 0.17

37089 Henderson, NC 0.290-0.060 0.29

37099 Jackson, NC 0.160-0.10 0.16

37111 McDowell, NC 0.220 0.010 0.22

37113 Macon, NC 0.170-0.150 0.17

37115 Madison, NC 0.160-0.230 0.16

37121 Mitchell, NC 0.440-0.030 0.44

37149 Polk, NC 0.190-0.010 0.19

37161 Rutherford, NC 0.310-0.150 0.31

37169 Stokes, NC 0.240 0.060 0.24

37171 Surry, NC 0.39 0.02 0.06 8.17 0.42
54

37173 Swain, NC 0.10 0.040 0.1

37175 Transylvania, NC 0.190-0.060 0.19

37189 Watauga, NC 0.190-0.030 0.19

37193 Wilkes, NC 0.330-0.30 0.33

37197 Yadkin, NC 0.210 0.010 0.21

37199 Yancey, NC 0.190-0.150 0.19

39001 Adams, OH 0.220-0.080 0.22

39007 Ashtabula, OH 0.280-0.040 0.28

39009 Athens, OH 0.33 0.05-0.07 30.88 0.43

39013 Belmont, OH 3.38 0.35 0.14 13.78 3.86

39015 Brown, OH 0.59 0.1 0.37 50 0.89

39019 Carroll, OH 1.9 0.47 1.83 68.88 3.23

39025 Clermont, OH 0.30 0.050 0.3

39029 Columbiana, OH 0.36 0.02-0.21 6.51 0.39

39031 Coshocton, OH 0.570-0.88 36.15 0.77

39053 Gallia, OH 0.170-0.280 0.17

39059 Guernsey, OH 0.68 0.07 0.37 29.18 0.88

39067 Harrison, OH 8.86 1.71 0.03 30.17 11.73

39071 Highland, OH 0.240-0.120 0.24

39073 Hocking, OH 0.280 0.060 0.28

39075 Holmes, OH 0.360 0.02 1.69 0.36

39079 Jackson, OH 0.6 0.13-1.09 55.81 0.94

39081 Jefferson, OH 0.48 0.08-0.34 79.02 0.86

39087 Lawrence, OH 0.320 0.110 0.32

39099 Mahoning, OH 0.350-0.02 0.38 0.35

39105 Meigs, OH 0.240-0.5 6.98 0.25

39111 Monroe, OH 0.550 0.050 0.55

39115 Morgan, OH 0.30 0.040 0.3

39119 Muskingum, OH 0.290-0.060 0.29

39121 Noble, OH 1.870 0.10 1.87

39127 Perry, OH 1.42 0.34-0.04 80.14 2.56

39131 Pike, OH 0.30 0.080 0.3

39141 Ross, OH 0.170-0.020 0.17

39145 Scioto, OH 0.170-0.060 0.17

39155 Trumbull, OH 0.290-0.120 0.29

39157 Tuscarawas, OH 0.94 0.16 0.27 51.28 1.43

39163 Vinton, OH 1.14 0.13-4.27 89.74 2.17

39167 Washington, OH 0.410-0.110 0.41
55

42003 Allegheny, PA 0.370 0.07 0.51 0.37

42005 Armstrong, PA 3.3 1.04-0.35 60.29 5.35

42007 Beaver, PA 0.330 0.010 0.33

42009 Bedford, PA 0.580 0.17 3.65 0.6

42013 Blair, PA 0.390-0.01 3.4 0.4

42015 Bradford, PA 0.520 0.440 0.52

42019 Butler, PA 0.52 0.03 0.17 10.03 0.57

42021 Cambria, PA 0.55 0.11 0.07 70.48 0.94

42023 Cameron, PA 0.410-0.250 0.41

42025 Carbon, PA 0.25 0.01 0.07 22 0.31

42027 Centre, PA 0.250 0.11 1.41 0.25

42031 Clarion, PA 1.02 0.24-0.03 71.79 1.76

42033 Clearfield, PA 1.18 0.33-0.6 62.87 1.93

42035 Clinton, PA 0.330 0.190 0.33

42037 Columbia, PA 0.39 0.03 0.24 49.83 0.58

42039 Crawford, PA 0.390 0.130 0.39

42047 Elk, PA 0.440-0.05 14.94 0.51

42049 Erie, PA 0.290-0.060 0.29

42051 Fayette, PA 0.52 0.02 0.24 16.75 0.6

42053 Forest, PA 0.380 0.60 0.38

42057 Fulton, PA 1.510-0.350 1.51

42059 Greene, PA 18.40 2.50 18.4

42061 Huntingdon, PA 0.230-0.230 0.23

42063 Indiana, PA 1.87 0.34 0.03 35.54 2.54

42065 Jefferson, PA 1.96 0.24 0.37 94.75 3.83

42067 Juniata, PA 0.210-0.020 0.21

42069 Lackawanna, PA 0.2700 0.77 0.27

42073 Lawrence, PA 0.30-0.110 0.3

42079 Luzerne, PA 0.48 0.03 0.03 59.15 0.76

42081 Lycoming, PA 0.49 0.02 0.36 13.87 0.56

42083 McKean, PA 0.670 0.290 0.67

42085 Mercer, PA 0.330 0.010 0.33

42087 Mifflin, PA 0.20-0.120 0.2

42089 Monroe, PA 0.180-0.060 0.18

42093 Montour, PA 0.250-0.10 0.25

42097 Northumberland, 

PA 0.49 0.04

-0.18 100 0.97

42099 Perry, PA 0.180-0.050 0.18

42103 Pike, PA 0.180-0.030 0.18

42105 Potter, PA 0.370-0.070 0.37

42107 Schuylkill, PA 1.12 0.2 0.46 100 2.24
56

42109 Snyder, PA 0.190-0.070 0.19

42111 Somerset, PA 2.63 0.86-0.39 86.22 4.93

42113 Sullivan, PA 0.330 0.20 0.33

42115 Susquehanna, PA 0.690 0.570 0.69

42117 Tioga, PA 0.410 0.310 0.41

42119 Union, PA 0.180-0.020 0.18

42121 Venango, PA 1.59 0.02-0.08 15.79 1.85

42123 Warren, PA 0.550 0.250 0.55

42125 Washington, PA 1.880 0.530 1.88

42127 Wayne, PA 0.310 0.10 0.31

42129 Westmoreland, 

PA 0.41 0.02

-0.02 5.51 0.43

42131 Wyoming, PA 0.50 0.610 0.5

45007 Anderson, SC 0.270 0.070 0.27

45021 Cherokee, SC 0.220-0.060 0.22

45045 Greenville, SC 0.360 0.040 0.36

45073 Oconee, SC 0.330-0.030 0.33

45077 Pickens, SC 0.20-0.070 0.2

45083 Spartanburg, SC 0.330 0.060 0.33

47001 Anderson, TN 0.350-0.09 2.54 0.36

47007 Bledsoe, TN 0.120-0.060 0.12

47009 Blount, TN 0.290 0.060 0.29

47011 Bradley, TN 0.23000 0.23

47013 Campbell, TN 0.41 0.06-0.1 55.01 0.64

47015 Cannon, TN 0.390 0.910 0.39

47019 Carter, TN 0.240-0.150 0.24

47025 Claiborne, TN 2.24 0.6-0.76 94.57 4.38

47027 Clay, TN 0.230 0.010 0.23

47029 Cocke, TN 0.220-0.10 0.22

47031 Coffee, TN 0.30-0.030 0.3

47035 Cumberland, TN 0.270-0.02 3.6 0.28

47041 DeKalb, TN 0.30-0.110 0.3

47049 Fentress, TN 0.20-0.030 0.2

47051 Franklin, TN 0.230 0.040 0.23

47057 Grainger, TN 0.230-0.060 0.23

47059 Greene, TN 0.40 0.10 0.4

47061 Grundy, TN 0.180-0.670 0.18

47063 Hamblen, TN 0.250-0.130 0.25

47065 Hamilton, TN 0.340-0.040 0.34
57

47067 Hancock, TN 0.070-0.040 0.07

47073 Hawkins, TN 0.260-0.330 0.26

47087 Jackson, TN 0.270-0.140 0.27

47089 Jefferson, TN 0.240 2.130 0.24

47091 Johnson, TN 0.270-0.150 0.27

47093 Knox, TN 0.33 0.01 0.06 1.84 0.33

47099 Lawrence, TN 0.270-0.080 0.27

47101 Lewis, TN 0.260-0.370 0.26

47105 Loudon, TN 0.30-0.220 0.3

47107 McMinn, TN 0.33000 0.33

47111 Macon, TN 0.190-0.140 0.19

47115 Marion, TN 0.530 0.240 0.53

47121 Meigs, TN 0.280-0.020 0.28

47123 Monroe, TN 0.310 0.150 0.31

47129 Morgan, TN 0.20 0.020 0.2

47133 Overton, TN 0.890 1.010 0.89

47137 Pickett, TN 0.330 0.150 0.33

47139 Polk, TN 0.160 0.0600.16

47141 Putnam, TN 0.250 0.010 0.25

47143 Rhea, TN 0.190-0.160 0.19

47145 Roane, TN 0.20-0.080 0.2

47151 Scott, TN 0.350-0.520 0.35

47153 Sequatchie, TN 0.370-0.460 0.37

47155 Sevier, TN 0.190 0.760 0.19

47159 Smith, TN 0.440 4.650 0.44

47163 Sullivan, TN 0.270 0.060 0.27

47171 Unicoi, TN 0.390-0.020 0.39

47173 Union, TN 0.210-0.10 0.21

47175 Van Buren, TN 0.940-0.530 0.94

47177 Warren, TN 0.380-0.030 0.38

47179 Washington, TN 0.250 0.020 0.25

47185 White, TN 0.280-0.120 0.28

51005 Alleghany, VA 0.250-0.090 0.25

51017 Bath, VA 0.25000 0.25

51021 Bland, VA 0.510 0.260 0.51

51023 Botetourt, VA 0.40-0.190 0.4

51027 Buchanan, VA 15.32 4.51-3.52 46.25 23.41

51035 Carroll, VA 0.23000 0.23

51045 Craig, VA 0.160-0.030 0.16

51051 Dickenson, VA 12.01 3.3-2.86 78.21 22.1
58

51063 Floyd, VA 0.160-0.050 0.16

51071 Giles, VA 0.650-0.270 0.65

51077 Grayson, VA 0.130-0.250 0.13

51089 Henry, VA 0.240-0.040 0.24

51091 Highland, VA 0.350-0.160 0.35

51105 Lee, VA 3.27 0.44-1.05 72.7 5.68

51121 Montgomery, VA 0.320 0.030 0.32

51141 Patrick, VA 0.20-0.10 0.2

51155 Pulaski, VA 0.250-0.150 0.25

51163 Rockbridge, VA 0.140-0.070 0.14

51167 Russell, VA 3.1 0.99-1.09 54.41 4.84

51169 Scott, VA 1.380 0.220 1.38

51173 Smyth, VA 0.670 0.050 0.67

51185 Tazewell, VA 3.4 1.05 0.72 75.31 6.03

51191 Washington, VA 0.650-0.80 0.65

51195 Wise, VA 3.89 1.1-5.48 100 7.86

51197 Wythe, VA 0.270-0.30 0.27

54001 Barbour, WV 4.2 1.04 2.34 88.48 7.99

54003 Berkeley, WV 0.230 0.020 0.23

54005 Boone, WV 21.87 6.54-27.62 64.64 38.36

54007 Braxton, WV 4.24 1.18 1.37 78.23 7.64

54009 Brooke, WV 0.270-0.730 0.27

54011 Cabell, WV 0.330-0.150 0.33

54013 Calhoun, WV 0.60-0.740 0.6

54015 Clay, WV 2.66 0.17-17.44 56.24 4.16

54017 Doddridge, WV 0.880 1.820 0.88

54019 Fayette, WV 4.52 1.5 0.68 76.72 8.1

54021 Gilmer, WV 0.870 0.740 0.87

54023 Grant, WV 0.24 0.01-4.4 100 0.48

54025 Greenbrier, WV 2.11 0.63 1.59 82.19 3.87

54027 Hampshire, WV 0.21000 0.21

54029 Hancock, WV 0.460-0.050 0.46

54031 Hardy, WV 0.260-0.090 0.26

54033 Harrison, WV 0.66 0.08-0.02 33.34 0.88

54035 Jackson, WV 0.350-0.340 0.35

54037 Jefferson, WV 0.180-0.10 0.18

54039 Kanawha, WV 1.52 0.44 0.02 63.28 2.49

54041 Lewis, WV 0.980 0.990 0.98
59

54043 Lincoln, WV 0.43 0 -1.28 43.33 0.61

54045 Logan, WV 11.57 3.51 -1.8 53 18.32

54047 McDowell, WV 14.82 3.19 -1.29 97.62 30.22

54049 Marion, WV 8.71 0.91 1.4 11.65 9.82

54051 Marshall, WV 17.31 0 4.27 0 17.31

54053 Mason, WV 0.26 0 -0.22 0 0.26

54055 Mercer, WV 1.07 0.14 0.53 69.05 1.81

54057 Mineral, WV 0.4 0.04 -0.03 28.18 0.51

54059 Mingo, WV 22.22 5.82 -5.54 50.26 35.33

54061 Monongalia, WV 0.73 0.15 0.1 49.58 1.09

54063 Monroe, WV 0.21 0 0.05 0 0.21

54065 Morgan, WV 0.17 0 -0.08 0 0.17

54067 Nicholas, WV 3.33 0.9 -2.32 84.3 6.2

54069 Ohio, WV 1.89 0 1.68 0 1.89

54071 Pendleton, WV 0.35 0 -0.05 0 0.35

54073 Pleasants, WV 0.42 0 0.11 0 0.42

54075 Pocahontas, WV 0.21 0 -0.18 0 0.21

54077 Preston, WV 0.58 0.07 -0.41 34.71 0.78

54079 Putnam, WV 0.47 0.02 0.28 8.88 0.51

54081 Raleigh, WV 5.83 2.07 0.92 82.44 10.85

54083 Randolph, WV 2.32 0.55 0.81 59.4 3.72

54085 Ritchie, WV 1.26 0 0.86 0 1.26

54087 Roane, WV 1.04 0 0.13 0 1.04

54089 Summers, WV 0.24 0 0.06 0 0.24

54091 Taylor, WV 7.63 1.1 7.73 31.32 10.13

54093 Tucker, WV 7.78 0 7.22 0 7.78

54095 Tyler, WV 0.28 0 0.23 0 0.28

54097 Upshur, WV 1.1 0.22 -0.98 86.68 2.05

54099 Wayne, WV 4.41 0.94 -1.31 100 8.91

54101 Webster, WV 13.3 2.88 0.63 69.65 23.22

54103 Wetzel, WV 0.39 0 0.39 0 0.39

54105 Wirt, WV 0.3 0 -0.25 0 0.3

54107 Wood, WV 0.22 0 -0.05 0 0.22

54109 Wyoming, WV 22.36 7.05 2.57 77.43 42.47

Data Sources: Bureau of Labor Statistics, Bureau of Economic Analysis and Mine Safety and Health 

Administration