Appendix O

Economic Impact Analysis Methodology

October 2013 Nevada and Northeastern California Greater Sage-Grouse Draft LUPA/EIS O-1

APPENDIX O

ECONOMIC IMPACT ANALYSIS METHODOLOGY

INTRODUCTION

This appendix describes the methods and data that underlie the economic 

impact modeling analysis. Input-output models such as the Impact Analysis for 

Planning (IMPLAN) model, an economic impact analysis model, provide a 

quantitative representation of the production relationships between individual 

economic sectors. Thus, the economic modeling analysis uses information about 

physical production quantities and the prices and costs for goods and services.

The inputs required to run the IMPLAN model are described in the following 

narrative and tables. The resulting estimates from the IMPLAN model, by 

alternative, are in Chapter 4, Environmental Consequences, Section 4.20, 

Social and Economic Impacts (Including Environmental Justice). The first portion

of the following information describes general aspects of the IMPLAN model 

and how it was used to estimate economic impacts. The remaining sections 

provide additional detailed data used in the analysis for livestock grazing, 

recreation, and oil and gas.

THE IMPLAN MODEL

IMPLAN is a regional economic model that provides a mathematical accounting 

of the flow of money, goods, and services through a region’s economy. The 

model provides estimates of how a specific economic activity translates into 

jobs and income for the region. It includes the ripple effect (also called the 

multiplier effect) of changes in economic sectors that may not be directly 

impacted by management actions, but are linked to industries that are directly 

impacted. In IMPLAN, these ripple effects are termed indirect impacts (for 

changes in industries that sell inputs to the industries that are directly impacted) 

and induced impacts (for changes in household spending as household income 

increases or decreases due to the changes in production).

This analysis used IMPLAN 2011; prior to running the model, cost and price 

data were converted to a consistent dollar year (2011) using sector-specific 
Appendix O. Economic Impact Analysis Methodology

O-2 Nevada and Northeastern California Greater Sage-Grouse Draft LUPA/EIS October 2013

adjustment factors from the IMPLAN model. The values in this appendix are 

expressed in year 2011 dollars.

The current IMPLAN model has 440 economic sectors, of which 309 are 

represented in the Socioeconomic Study Area counties. This analysis involved 

direct changes in economic activity for 27 IMPLAN economic sectors, as well as 

changes in all other related sectors due to the ripple effect. The IMPLAN

production coefficients were modified to reflect the interaction of producing 

sectors in the Socioeconomic Study Areas. As a result, the calibrated model 

does a better job of generating multipliers and the subsequent impacts that 

reflect the interaction between and among the sectors in the Socioeconomic 

Study Area compared to a model using unadjusted national coefficients. Key 

variables used in the IMPLAN model were filled in using data specific to the 

Socioeconomic Study Area, including employment estimates, labor earnings, and 

total industry output.

The trade data available in the current version of IMPLAN (Version 3.0) make it 

possible to do multi-region analysis to track how an impact on any of the 

IMPLAN sectors in the study area affects production in any of the sectors in any 

other region of the US. For this analysis, this feature allowed the estimation of 

how an impact in the primary study area disperses into the secondary study 

area, and how these effects in the secondary study area create additional local 

effects in the primary study area. As a result, it was possible to estimate not 

only the jobs and income generation in the primary study area, but to also 

estimate how the economic activity in the primary study area affected jobs and 

income generation in the secondary study area.

LIVESTOCK GRAZING

Economic impacts from changes to livestock grazing are a function of the 

amount of forage available and the economic value of forage.

Forage availability was measured in Animal Unit Months (AUMs), with one AUM 

defined as the amount of forage needed to feed one cow, one horse, or five 

sheep for one month. Data on forage availability were obtained from BLM's 

Rangeland Administration System (BLM 2012) and from the Forest Service’s

INFRA range module (Forest Service 2013). Two types of AUM measures were 

used: Active AUMs and Billed AUMs. Active AUMs measure the amount of 

forage from land available for grazing. The Forest Service designates this 

measure “permitted” AUMs. Billed AUMs measure the amount of forage for 

which the BLM and Forest Service bill annually (i.e., the amount of forage that 

ranchers actually use, which is typically less than the amount of forage available). 

The Forest Service uses the designation “authorized” AUMs. Data for 2011 

were used for active AUMs, except for active AUMs on the Humboldt-Toiyabe

National Forest, for which 2012 data were used. Data for 2000 to 2011 were 

used to develop a 12-year average for billed AUMs.
Appendix O. Economic Impact Analysis Methodology

October 2013 Nevada and Northeastern California Greater Sage-Grouse Draft LUPA/EIS O-3 

Forage availability was estimated for all alternatives. Alternatives A, B, D, and E 

used the current data for active AUMs (obtained as explained above). 

Alternative C discounted the current data to remove 100 percent of active 

AUMs in GRSG habitat (all designated habitat [ADH]). Alternative F discounted 

the current data to remove 62.5 percent of active AUMs in ADH.1 The analysis 

estimated 2,556,646 total active AUMs in the Socioeconomic Study Area, 

including 276,191 in the Humboldt-Toiyabe National Forest, 191,733 in the 

California BLM planning area, and 2,088,722 in the Nevada BLM planning area.2

The analysis also estimated 2,223,515 active AUMs in ADH in the 

Socioeconomic Study Area (BLM 2013a), including 272,594 in the HumboldtToiyabe National Forest, 172,231 in the California BLM planning area, and 

1,778,690 in the Nevada BLM planning area.3 This information was used to 

calculate the total active AUMs that would be available for grazing under each 

alternative, including those in and not in ADH. The results of these calculations 

are presented in Table O-1, Estimated Active Annual Animal Unit Months by 

Alternative, below. 

Table O-1

Estimated Active Annual Animal Unit Months by Alternative

Agency Initial Alternatives A, 

B, D, and E Alternative C Alternative F

Active

Forest Service 276,191 276,191 3,597 105,820

California BLM 191,733 191,733 19,502 84,089

Nevada BLM 2,088,722 2,088,722 310,032 977,041

Socioeconomic Study Area 2,556,646 2,556,646 333,131 1,166,949

Sources: Calculated based on data from BLM 2012, BLM 2013a, Forest Service 2013, and share of AUMs in ADH

from Chapter 4, Environmental Consequences, Section 4.9, Livestock Grazing.

Table O-2, Estimated Billed Annual Animal Unit Months by Alternative, shows 

two scenarios for the number of billed AUMS under each alternative. For the 

high impact scenario, the analysis assumed that ranchers would choose to 

maintain a constant ratio of active to billed AUMs so any reduction to active 

AUMs would result in a proportional reduction to billed AUMs. Thus, the 

analysis applied the current ratio of active to billed AUMs to the calculated 

number of reduce active AUMS under each alternative to calculate the 

corresponding number of reduced billed AUMs under each alternative. For the 

 

1 Under Alternative F, 25 percent of the area in ADH must be rested each year. Of the remaining 75 percent, 50 

percent must be set aside. Thus, the total area available for forage in ADH is reduced by 62.5 percent. 2 The number of active AUMs listed for the Humboldt-Toiyabe National Forest represents the number of active 

AUMs within the National Forest and within the Socioeconomic Study Area, not all active AUMS in the National 

Forest.

3

 Because permitted AUMs include active and suspended AUMs (in BLM terminology), this comparison of total 

active AUMs with ADH permitted AUMs may overestimate the loss of AUMs under Alternative C.
Appendix O. Economic Impact Analysis Methodology

O-4 Nevada and Northeastern California Greater Sage-Grouse Draft LUPA/EIS October 2013 

low impact scenario, the analysis assumed that ranchers would continue to use 

as many of the initial billed AUMs as possible. If active AUMs were not reduced 

beyond the initial amount of billed AUMs, ranchers would continue to use the 

initial billed AUMs, resulting in no impact. If active AUMs were reduced beyond 

the initial amount of billed AUMs, ranchers would use all of the reduced active 

AUMs. Thus, when the number of reduced active AUMs was less than number 

of the initial billed AUMs, the analysis used the number of reduced active AUMs 

as the number of reduced billed AUMs under each alternative. Otherwise, the 

analysis assumed no change in the number of billed AUMs. 

Table O-2 

Estimated Billed Annual Animal Unit Months by Alternative

Agency Initial Alternatives A, 

B, D, and E Alternative C Alternative F

High Impact Scenario

Forest Service 234,662 234,662 3,056 89,908

California BLM 119,729 119,729 12,178 52,510

Nevada BLM 1,228,727 1,228,727 182,382 574,761

Socioeconomic Study Area 1,583,118 1,583,118 197,616 717,179

Low Impact Scenario

Forest Service 234,662 234,662 3,597 105,820

California BLM 119,729 119,729 19,502 84,089

Nevada BLM 1,228,727 1,228,727 310,032 977,041

Socioeconomic Study Area 1,583,118 1,583,118 333,131 1,166,949

Sources: Calculated based on data from BLM 2012, BLM 2013a, Forest Service 2013, and Chapter 4, 

Environmental Consequences, Section 4.9, Livestock Grazing. 

Table O-3, Estimated Reduction in Annual Animal Unit Months by Alternative 

and Livestock Type, shows the two scenarios for resulting AUM reductions, 

calculated as the difference between the initial billed AUMs and the reduced 

billed AUMs under each alternative. AUMs are distinguished between those 

allocated to sheep, and those allocated to cattle and other animals, to allow 

different valuation of forage, as explained further below. 

The economic value of forage is estimated based on the value of production 

associated with the forage. Values for cattle and sheep are estimated separately, 

with the value of forage for other animals considered equivalent to the value for 

cattle. Due to price fluctuations, average per-AUM values for cattle and sheep 

are based on the 2002 to 2011 average value of production estimates from the 

(US Department of Agriculture, Economic Research Service 2012). The value 

for cattle is $50.37 per AUM, and the value for sheep is $57.20 per AUM in the 

Socioeconomic Study Area (in 2010 dollars). Including indirect and induced 

impacts, the value of one AUM in the Socioeconomic Study Area for cattle is
Appendix O. Economic Impact Analysis Methodology

October 2013 Nevada and Northeastern California Greater Sage-Grouse Draft LUPA/EIS O-5 

Table O-3

Estimated Reduction in Annual Animal Unit Months by Alternative and Livestock Type

High Impact Scenario Low Impact Scenario

Agency

Alternatives

A, B, D, E

Alternative 

C

Alternative 

F

Alternatives

A, B, D, E

Alternative 

C

Alternative 

F

Total

Forest Service 0 -231,606 -144,754 0 -231,065 -128,842

California BLM 0 -107,551 -67,219 0 -100,227 -35,640

Nevada BLM 0 -1,046,345 -653,966 0 -918,695 -251,686

Socioeconomic 

Study Area

0 -1,385,502 -865,939 0 -1,249,987 -416,169

Cattle and Other

Forest Service 0 -192,156 -120,098 0 -191,708 -106,897

California BLM 0 -103,300 -64,563 0 -96,266 -34,232

Nevada BLM 0 -965,969 -603,731 0 -848,124 -232,353

Socioeconomic 

Study Area

0 -1,261,426 -788,391 0 -1,136,098 -373,481

Sheep

Forest Service 0 -39,450 -24,656 0 -39,357 -21,946

California BLM 0 -4,251 -2,657 0 -3,961 -1,409

Nevada BLM 0 -80,376 -50,235 0 -70,571 -19,334

Socioeconomic 

Study Area

0 -124,076 -77,548 0 -113,889 -42,688

Sources: Calculated based on data from BLM 2012, BLM 2013a, and Forest Service 2013.

$101.14 and for sheep is $124.91 (in 2010 dollars). Table O-4, Assumptions 

for Analysis of Impacts on Output for Livestock Grazing, shows the economic 

impact assumptions for cattle and sheep. The direct economic impact is the 

estimated change in livestock output per AUM; IMPLAN generates the indirect 

and induced impacts.

Table O-4

Assumptions for Analysis of Impacts on Output for Livestock Grazing

Economic Impact Cattle Sheep

Direct Economic Impact ($/AUM) $50.37 $57.20

Indirect Economic Impact ($/AUM)1 $42.50 $56.27

Induced Economic Impact ($/AUM)2 $8.26 $11.45

Total Economic Impact ($/AUM) $101.14 $124.91

Multiplier (Total Impact/Direct Impact) 2.01 2.18

Note: All dollar values are in 2010 dollars. 1

Indirect impacts reflect increased demand in sectors that directly or indirectly provide supplies to the livestock

industry. 2

Induced impacts reflect increased demand in the consumer and government sectors.
Appendix O. Economic Impact Analysis Methodology

O-6 Nevada and Northeastern California Greater Sage-Grouse Draft LUPA/EIS October 2013 

Table O-5, Assumptions for Analysis of Employment Impacts for Livestock 

Grazing, provides a summary of the employment impacts that would result, 

according to IMPLAN, based on unit changes in livestock AUMs.

Table O-5

Assumptions for Analysis of Employment Impacts for Livestock Grazing

Employment Impact Cattle Sheep

Direct Employment (Jobs/1,000 AUMs) 0.000559 0.000980

Indirect Employment (Jobs/1,000 AUMs) 0.000435 0.000708

Induced Employment (Jobs/1,000 AUMs) 0.000072 0.000099

Total Employment (Jobs/1,000 AUMs) 0.001065 0.001787

Multiplier (Total Impact/Direct Impact) 1.91 1.82

Average Earnings per Job (2010 dollars) $35,239 $21,672

Note: Direct, indirect, and induced employment impacts and average earnings per job are calculated using

IMPLAN.

GEOTHERMAL EXPLORATION AND DEVELOPMENT

Economic impacts from geothermal exploration and development are a function 

of construction and operation expenditures for geothermal electricity 

development, including drilling wells (exploratory, production and injection), 

constructing power plants, and operating facilities. In the Reasonably 

Foreseeable Development scenario for geothermal development, BLM 

developed a scenario to serve as a basis for analyzing impacts resulting from 

future leasing and development of federal geothermal resources within the 

decision area over the next 20 years. 

To estimate economic activity associated with geothermal development, BLM 

first used the National Renewable Energy Laboratory’s Jobs and Economic 

Development Impact (JEDI) model (NREL, 2012) to determine approximate 

capital and operating costs associated with a representative power plant. The 

assumptions used a 15 MW nameplate capacity and typical conditions for the 

planning area: a resource at about 310 degrees Fahrenheit at a depth of 5,500 

feet; binary cycle; and two production wells per injection well (BLM 2013c). 

BLM used standard assumptions from the National Renewable Energy 

Laboratory for the local share of construction and operating expenses that 

would be spent within the state of Nevada, as an approximation for the study 

area (local spending assumptions were available at the state level but not the 

county level). BLM then used IMPLAN, calibrated to the specific region of the 

socioeconomic study area, to calculate indirect and induced impacts associated 

with a given direct expenditure. Table O-6, Assumptions for Analysis of 

Impacts on Output for Geothermal Exploration and Development, shows the 

resulting assumptions for construction and operation of an individual power 

plant. 
Appendix O. Economic Impact Analysis Methodology

October 2013 Nevada and Northeastern California Greater Sage-Grouse Draft LUPA/EIS O-7 

Table O-6

Assumptions for Analysis of Impacts on Output for Geothermal Exploration and 

Development

Economic Impact

(millions of 2010 dollars)

Traditional 

Hydrothermal

Plant

Enhanced Geothermal 

Systems Plant

Construction

Direct Economic Impact1 $42.4 $42.7

Indirect Economic Impact2 $3.7 $4.0

Induced Economic Impact3 $9.3 $9.9

Total Economic Impact $55.4 $56.6

Multiplier (total impact/direct impact) 1.31 1.33

Operation

Direct Economic Impact1 $1.3 $1.2

Indirect Economic Impact2 $0.0 $0.0

Induced Economic Impact3 $0.7 $0.6

Total Economic Impact $2.0 $1.8

Multiplier (total impact/direct impact) 1.56 1.56

Notes: Details may not add to total due to rounding. 1

Direct economic impact is the average expenditure per plant, assuming an average nameplate capacity of 15 

MW. 2

Indirect impacts from IMPLAN reflect increased demand in sectors that directly or indirectly provide support

for the geothermal exploration and development industry. 3

Induced impacts from IMPLAN reflect increased demand in the consumer and government sectors (e.g.,

employee wages).

Table O-7, Assumptions for Employment Impact Analysis for Geothermal 

Exploration and Development Activities, provides a summary of employment 

impacts according to IMPLAN results, based on construction and operation of 

each type of power plant.

OIL AND GAS

The economic impact of oil and gas reflects drilling, completion, and production 

activities. The number of wells expected to be developed, and how BLM 

developed its assumptions, is discussed in Chapter 4, Environmental 

Consequences, Section 4.12, Minerals – Fluid. BLM assumed a completion rate 

ranging from 10 percent to 75 percent, as well as production per well 

completed, using assumptions appropriate to the area. Table O-8, Oil and Gas 

Wells and Production, provides the resulting estimated numbers of wells and 

production that were used for the economic analysis.

The costs of drilling and completing wells and producing oil and gas also are 

relevant for the economic impact analysis. Starting with the estimate of $3.25 

million for drilling and completion of one well (BLM 2013b), the estimate was 

adjusted from 2012 to 2010 dollars using price indices from IMPLAN, then the 

percentage of local spending and breakouts into drilling and completion costs
Appendix O. Economic Impact Analysis Methodology

O-8 Nevada and Northeastern California Greater Sage-Grouse Draft LUPA/EIS October 2013 

Table O-7

Assumptions for Employment Impact Analysis for Geothermal Exploration and 

Development Activities

Employment Impact

(number of jobs per plant)

Traditional 

Hydrothermal Plant

Enhanced Geothermal 

Systems Plant

Construction

Direct Employment

Indirect Employment

Induced Employment

Total Employment

Multiplier (Total Impact/Direct Impact)

Average Earnings per Job (2010 dollars)

246.1

31.7

77.6

355.4

1.44

$57,107

272.5

33.3

82.8

388.6

1.43

$62,996

Operation

Direct Employment

Indirect Employment

Induced Employment

Total Employment

Multiplier (Total Impact/Direct Impact)

Average Earnings per Job (2011 dollars)

10.0

0.0

5.9

15.9

1.59

$94,220

9.0

0.0

5.4

14.4

1.60

$95,237

Note: Direct, indirect, and induced employment 

as described in the text. 

impact and average earnings per job are calculated using IMPLAN, 

Table O-8 

Oil and Gas Wells and Production

Area 

Wells 

drilled on 

new leases

Wells 

completed on 

new leases

Wells 

drilled on 

existing 

leases

Wells 

completed on 

existing leases

Production 

(barrels of oil

per completed 

well)

Great Basin Core 10 7.5 50 37.5 1,000,000

NW-Interior NV 0 0 1 0.1 200,000

Warm Springs 1 0.6 3 1.8 200,000

Quinn Range NV 20 10 20 10 1,000,000

Source: BLM (2013b). The BLM’s analysis also indicates that there would be some gas production, which would be 

used on location or vented to the atmosphere (BLM 2013b). Because the gas may simply be vented without being 

used productively, the economic analysis does not factor in the potential to sell it.

were estimated based on IMPLAN factors and costs for wells in other parts of 

the Great Basin. The price for oil from Utah was used since the Energy 

Information Administration does not provide a price for Nevada; the price and 

cost per barrel of oil were based on EIA (2010) and EIA (2013). IMPLAN was 

then used to generate output, employment, and earnings multipliers per unit. 

Impacts were estimated by multiplying per-unit impact estimates by the number 
Appendix O. Economic Impact Analysis Methodology

October 2013 Nevada and Northeastern California Greater Sage-Grouse Draft LUPA/EIS O-9 

of wells drilled and completed, and number of barrels of oil produced. Table 

O-9, Assumptions for Analysis of Output, Earnings, and Employment for Oil and 

Gas, provides a summary of the per-unit values used for output, employment, 

and earnings. 

Table O-9

Assumptions for Analysis of Output, Earnings, and Employment for Oil and Gas

Economic Impact1 Drilling

(per well)

Completion

(per well)

Production

(per MBO)

Direct output $1,357,100 $994,335 $79,724

Indirect output $257,013 $180,167 $10,937

Induced output $478,418 $381,268 $5,373

Total output $2,092,531 $1,555,770 $96,034

Multiplier2 1.54 1.56 1.20

Direct earnings $717,311 $580,892 $4,405

Indirect earnings $102,923 $73,455 $4,761

Induced earnings $161,781 $128,959 $1,818

Total earnings $982,015 $783,306 $10,984

Multiplier 1.37 1.35 2.49

Direct employment 8.1 6.7 0.060660

Indirect employment 2.0 1.5 0.074855

Induced employment 4.0 3.2 0.045061

Total employment 14.1 11.4 0.180576

Multiplier 1.74 1.70 2.98

Average earnings per job $69,646 $68,711 $60,825

Sources: BLM 2013b, EIA 2010, EIA 2013, and the IMPLAN model, as described in the text.

MBO = thousands of barrels of oil

1. All dollar figures are in 2010 dollars.

2. Multiplier is calculated as total impact divided by direct impact.
Appendix O. Economic Impact Analysis Methodology

O-10 Nevada and Northeastern California Greater Sage-Grouse Draft LUPA/EIS October 2013

REFERENCES

BLM (United States Department of the Interior, Bureau of Land Management). 2012. Data from BLM 

Rangeland Administration System. 

_____. 2013a. Grazing Impacts. Data provided in personal communication from Mike Tietmeyer, BLM, 

Nevada State Office. May and June 2013.

_____. 2013b. Oil and Gas Data. Data provided in personal communication from John Menghini, 

Petroleum Engineer, BLM, May and June 2013.

_____. 2013c. Geothermal RFD. Personal communication via Sheila Mallory, BLM, Nevada State Office. 

June 2013.

NREL (National Renewable Energy Laboratory). 2012. Jobs and Economic Development Impact 

Geothermal Model, Release GT08.02.12. Internet Web site: 

http://www.nrel.gov/analysis/jedi/download.html. Accessed in May 2013.

US Department of Agriculture, Economic Research Service. 2012. Commodity Costs and Returns. 

Internet Web site: http://www.ers.usda.gov/data-products/commodity-costs-and-returns.aspx.

Accessed in August 2012.

EIA (Energy Information Administration). 2010. 2009 Oil & Gas Lease Equipment & Operating Costs, Oil 

Production for the Rocky Mountain Region. Internet Web site: 

http://www.eia.gov/pub/oil_gas/natural_gas/data_publications/cost_indices_equipment_producti

on/current/coststudy.html. Accessed in June 2013.

_____. 2013. Utah Crude Oil First Purchase Price (Dollars per Barrel), converted to 2010 dollars. 

Internet Web site: http://www.eia.gov/dnav/pet/hist/LeafHandler.ashx?n=pet&s=f004049__

3&f=m. Accessed in June 2013.

US Forest Service (United States Department of Agriculture, Forest Service). 2013. Humboldt-Toiyabe 

National Forest Permitted and Authorized AUMs. Data provided in personal communication 

from Chris Miller, US Forest Service, May and June 2013.