Job and Economic 

Development Impact (JEDI) 

Model: A User-Friendly Tool to 

Calculate Economic Impacts 

from Wind Projects

Preprint 

March 2004 • NREL/CP-500-35953 

M. Goldberg 

MRG & Associates 

K. Sinclair and M. Milligan (Consultant) 

National Renewable Energy Laboratory

To be presented at the 2004 Global WINDPOWER 

Conference 

Chicago, Illinois 

March 29-31, 2004 

National Renewable Energy Laboratory 

1617 Cole Boulevard 

Golden, Colorado 80401-3393 

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1

JOB AND ECONOMIC DEVELOPMENT IMPACT (JEDI) MODEL: A USER-FRIENDLY TOOL TO 

CALCULATE ECONOMIC IMPACTS FROM WIND PROJECTS 

Marshall Goldberg 

MRG & Associates 

17798 Starduster Drive 

Nevada City, CA 95959 

USA 

mrgassociates@earthlink.net

Karin C. Sinclair 

National Wind Technology Center 

National Renewable Energy Laboratory 

1617 Cole Blvd. 

Golden, CO 80401 

USA 

Karin_Sinclair@nrel.gov

Michael Milligan 

Consultant 

National Wind Technology Center 

National Renewable Energy Laboratory 

1617 Cole Blvd. 

Golden, CO 80401 

USA 

Michael_Milligan@nrel.gov

Abstract 

The U.S. Department of Energy/National Renewable Energy Laboratory (DOE/NREL) has developed a 

spreadsheet-based wind model (Jobs and Economic Development Impact (JEDI)) that incorporates economic 

multipliers for jobs, income, and output. Originally developed with state-specific parameters, it can also be used 

to conduct county and regional analyses. 

NREL has enlisted the Wind Powering America (WPA) State Wind Working Groups (SWWGs) to conduct 

county-specific economic impact analyses, and has encouraged them to use JEDI if they do not have their own 

economic model. The objective of the analyses is to identify counties within WPA target states, and preferably 

counties with a significant agricultural sector, that could economically benefit from wind development. These 

counties could then explore opportunities to tap into the United States Department of Agriculture (USDA) Farm 

Bill Section 9006 grants and loans to stimulate wind development. 

This paper describes the JEDI model and how it can be used. We will also summarize a series of analyses that 

were completed to fulfill a General Accounting Office (GAO) request to provide estimates of the economic 

development benefits of wind power. 
2

Introduction 

As energy prices rise and the threat of environmental degradation looms on the horizon, our use of fossil fuels 

and nuclear power continues to grow. Yet many policy makers, renewable energy advocates, and citizens across 

the country question our reliance on these conventional energy sources and look toward renewable resources as a 

win-win situation for the environment and local economies. Unfortunately, few have the knowledge or resources 

to quickly and easily analyze the benefits associated with developing renewable power sources such as wind 

turbines. The JEDI model, designed to demonstrate the economic benefits associated with developing wind 

power plants in the United States, now provides a tool to help meet this need.1

The primary goal in developing the initial model was a) to provide a tool for wind developers, renewable energy 

advocates, government officials, decision makers, and other potential users who might not have the resources to 

develop their own economic development model, and b) to easily identify the local economic impacts associated 

with constructing and operating wind power plants. The second goal was to facilitate broad access and usage of 

the model by making it electronically available through NREL. 

To accommodate a potentially broad user base with varying experience with economic development modeling, a 

strong emphasis was placed on designing JEDI in a user-friendly format that could be easily modified 

accommodating varying levels of project-specific information. This insures the greatest flexibility for 

inexperienced spreadsheet users, those unfamiliar with economic impact analysis, and more experienced and 

knowledgeable users who need this type of analysis. 

Methodology 

Basic information about a wind project (at minimum the project’s state, county, or region; the year of 

construction; and the size of the facility), the model calculates the project cost (i.e., specific expenditures) as well 

as the number of jobs, income (i.e., wages and salary), and economic activity that will accrue to the state, county, 

or region being analyzed.2

 To evaluate these impacts, input-output or multiplier analysis is used. 

Input-output models were originally developed to trace supply linkages in the economy. For example, they show 

how purchases of wind turbines not only benefit turbine manufacturers, but also the fabricated metal industries 

and others businesses supplying inputs to those manufacturers. The benefits that are ultimately generated by 

expenditures for wind plants depend on the extent to which those expenditures are spent locally and the structure 

of the local economy. Consistent with the spending pattern and location-specific economic structure (state, 

county, or region), different expenditures support a different level of employment, income, and output. 

Input-output analysis is a method of evaluating and summing the impacts of a series of effects generated by an 

expenditure (i.e., input). To determine the total effect of developing a wind power plant, three impacts are 

examined for each expenditure. These include direct effect, indirect effect, and induced effect. 

 

1 Marshall Goldberg, of MRG & ASSOCIATES, designed the model under contract to the National Renewable Energy Laboratory 

(NREL). 

2 Although JEDI was originally designed to provide state level analysis, the model also includes a “User Add-in Location” feature. This 

feature allows users to import specific county or region level multipliers and personal expenditure patterns to localize the analysis to a 

location other than the state level. 
3

Direct effect: Direct effects are the on-site or immediate effects created by an expenditure. In 

constructing a wind plant, it refers to the on-site jobs of the contractors and crews hired to 

construct the plant. It also includes the jobs at the turbine manufacturing plants and the jobs at the 

tower and blade factories. 

Indirect effect: Indirect effects refer to the increase in economic activity that occurs when a 

contractor, vendor or manufacturer receives payment for goods or services and in turn is able to 

pay others who support their business. For instance, this impact includes the banker who finances 

the contractor; the accountant who keeps the contractor’s books; and the steel mills and electrical 

manufacturers and other suppliers that provide the necessary materials. 

Induced effect: Induced effects refer to the change in wealth and income that is induced by the 

spending of those persons directly and indirectly employed by the project. This would include 

spending on food, clothing, or day care by those directly or indirectly employed by the project, 

retail services, public transit, utilities, cars, oil, property & income taxes, medical services, and 

insurance, for example. 

The sum of these three effects yields a total effect that results from a single expenditure. To accomplish this 

analysis at the state level, state-specific multipliers and personal expenditure patterns are used to derive the 

results. These state-by-state multipliers for employment, wage and salary income and output (economic activity), 

and personal expenditure patterns were adapted from the IMPLAN Professional model using year 2000 data, the 

most current data available last year.3 The changes in expenditures from investments in developing wind power 

plants are matched with their appropriate multipliers for each sector affected by the change in expenditure. 

Consistent with an analysis of this type and scope, the assumptions play an important role in influencing the 

results. Thus, to accommodate the greatest level of flexibility in user skill level and availability of specific 

detailed project information, the model is designed to incorporate model default values or new values entered by 

the user. The default values represent a reasonable expenditure pattern for constructing and operating a wind 

power plant in the United States and the share of expenditures spent locally. The default expenditure pattern is 

based on a review of numerous wind resource studies. 

Currently, not every project will follow this exact “default” pattern for expenditures. Project size, location, 

financing arrangements, and numerous site-specific factors influence the construction and operating costs. 

Similarly, the availability of local resources (including skilled labor and materials) and the availability of locally 

manufactured power plant components will have a significant effect on the costs and the economic benefits that 

accrue to the state or local region. To the extent the user has and can incorporate project-specific data and the 

share of spending that is expected to occur locally, the more localized the impact analysis will be. 

Analyses 

An early version of JEDI was used by the Union of Concerned Scientists to conduct economic impact analyses in 

Arizona, Idaho, and Washington. A presentation of these analyses is available at NREL’s Wind Powering 

American web page.4

 

 

3 See Minnesota IMPLAN Group (MIG, Inc), Stillwater, Minnesota, 651/439-4421, www.IMPLAN.com. IMPLAN (Impact Analysis 

for PLANning) Professional is a social accounting and impact analysis tool. 

4 Go to http://www.eere.energy.gov/windpoweringamerica/pdfs/econ_clemmer.pdf for February 2003 presentation by Steve Clemmer, 
4

In 2003, the GAO requested that NREL conduct economic impact analyses of projects in 11 counties from a total 

of 5 different states. These include: Alameda and Solano in California; Weld in Colorado; Buena Vista, 

Cherokee, and Dickinson in Iowa; Pipestone and Rock in Minnesota; and Crockett, Pecos, and Upton in Texas. 

For each of these counties, three wind project scenarios were analyzed. The scenarios included analysis of a 150 

MW plant, a 40 MW plant, and twenty 2 MW plants. Table 1 summarizes the scenario results. 

Although each of the plants has a similar expenditure pattern (construction and annual O&M costs), the share of 

local spending varies depending upon the project location and availability of skilled labor and local businesses to 

meet project needs. In addition to these parameters, the analysis assumes the 150 MW and 40 MW plants are 

developed (owned) by non-local investors, are financed by non-local lenders and include land lease payments to 

local landowners (estimated at $4,000 per 1.5 MW turbine). The twenty 2 MW plants are assumed to be 

developed by local residents (landowners), equity payments are made to local residents, all financing is by local 

lending institutions and no land lease payments are made. The local ownership and local financing result in more 

dollars remaining in the local economy (i.e., more local spending and fewer monetary leakages) when compared 

with a project of similar size not locally owned or financed. 

In addition to the GAO scenarios, economic impact analyses are being conducted in conjunction with NREL in 

Colorado, Montana, Oregon, and Virginia. Other states, including Arizona, Idaho, Michigan, and Nevada, are in 

various stages of conducting these analyses. 

Important Considerations 

Three important points should be considered when using JEDI. First, JEDI is intended to construct a reasonable 

profile of investments (i.e., wind power plant construction and operating costs) and demonstrate the economic 

impacts that will likely result, assuming a project occurs during the stated period of analysis. Given future 

changes in wind power plant costs and potential changes in industry and personal consumption patterns in the 

economy, the analysis is not intended to provide a precise forecast, but rather an approximate estimate of overall 

impacts. 

Second, the analysis is specific to developing a wind power plant and thus is considered a gross analysis. That is, 

it doesn’t reflect net impacts associated with alternate spending of the money (such as constructing and operating 

other types of electricity-generating power plants) or replacement of existing power generation resources. 

Third, the analysis does not account for changes in electricity prices or end-user electricity bills that could result 

from developing wind power plants versus other types of power plants. 

Fourth, the analysis assumes the output from the power plant and the specific terms of the power purchase 

agreement generate sufficient revenues to accommodate the equity and debt repayment and annual operating 

expenditures. To the extent additional revenues (i.e., profits and/or tax advantages above actual costs) accrue to 

the project owner, there will be additional benefits. If the project owner is local, these additional benefits will 

contribute to the local share, however these benefits are not included in the analysis. 

 

Union of Concerned Scientists. 
5

TABLE 1. GAO WIND PROJECT SCENARIOS – JEDI ANALYSES

Site Location 

(county) Project Size 

Number of 

Turbines 

Local 

Construction 

Cost Spending 

(millions) 

Local Annual 

O&M 

Spending 

(millions) 

Total Jobs (Direct, 

Indirect, Induced) 

Impacts (During 

Construction) 

Total Jobs (Direct, 

Indirect, Induced) 

Impacts (During 

Operating Years) 

California 

 Alameda 40 MW 54 – 750kW $ 5.1 $ 0.8 84 17 

 Alameda 20 – 2MW* $ 5.1 $ 6.7 84 38 

 Alameda 150 MW 100 – 1500kW $ 19.1 $ 3.1 314 65 

 Solano 40 MW 27 – 1500kW $ 5.1 $ 0.8 86 17 

 Solano 20 – 2MW* $ 5.1 $ 6.7 86 34 

 Solano 150 MW 100 – 1500kW $ 19.1 $ 3.1 321 64 

Colorado 

 Weld 40 MW 27 – 1500kW $ 5.1 $ 0.8 103 20 

 Weld 20 – 2MW* $ 5.1 $ 6.7 103 46 

 Weld 150 MW 100 – 1500kW $ 17.5 $ 3.1 349 76 

Iowa 

 Buena Vista 40 MW 54 – 750kW $ 0.5 $ 1.3 13 23 

 Buena Vista 20 – 2MW* $ 0.5 $ 7.2 13 48 

 Buena Vista 150 MW 200 – 750kW $ 1.9 $ 4.9 47 86 

 Cherokee 40 MW 27 – 1500kW $ 0.3 $ 1.3 9 25 

 Cherokee 20 – 2MW* $ 0.3 $ 7.2 9 52 

 Cherokee 150 MW 100 – 1500kW $ 1.3 $ 4.9 33 93 

 Dickinson 40 MW 54 – 750kW $ 0.5 $ 1.3 11 22 

 Dickinson 20 – 2MW* $ 0.5 $ 7.2 11 48 

 Dickinson 150 MW 200 – 750kW $ 1.9 $ 4.9 40 81 

Minnesota 

 Pipestone 40 MW 27 – 1500kW $ 0.3 $ 0.3 7 12 

 Pipestone 20 – 2MW* $ 0.3 $ 6.2 7 36 

 Pipestone 150 MW 100 – 1500kW $ 1.3 $ 1.3 28 45 

 Rock 40 MW 27 – 1500kW $ 0.3 $ 0.3 7 12 

 Rock 20 – 2MW* $ 0.3 $ 6.2 7 38 

 Rock 150 MW 100 – 1500kW $ 1.3 $ 1.3 27 45 

Texas 

 Crockett 40 MW 27 – 1500kW $ 0.3 $ 1.2 6 16 

 Crockett 20 – 2MW* $ 0.3 $ 7.1 6 37 

 Crockett 150 MW 100 – 1500kW $ 1.3 $ 4.6 21 60 

 Pecos 40 MW 54 – 750kW $ 0.5 $ 1.2 10 18 

 Pecos 20 – 2MW* $ 0.5 $ 7.1 10 39 

 Pecos 150 MW 200 – 750kW $ 1.9 $ 4.7 36 67 

 Upton 40 MW 27 – 1500kW $ 0.3 $ 1.2 6 13 

 Upton 20 – 2MW* $ 0.3 $ 7.1 6 32 

 Upton 150 MW 100 – 1500kW $ 1.3 $ 4.6 22 47 

 * Scenario includes no land lease payments due to landowner development. 
6

Entering Data and Running the Model 

The JEDI model is designed for all levels of users, requiring no experience with spreadsheets or background in 

economic modeling. The model includes on-line instructions on how to proceed with entering data for analysis, 

as well as detailed information (comments) to assist users in understanding the type of data required in specific 

cells. A documentation file is also included with the model. 

For those users with little or no experience with wind power plants or economic impact analysis, minimal inputs 

are required, such as the state in which the wind plant will be built, the year the plant will be built, and the size of 

the plant. The user can then choose to accept all project defaults (or review and edit the defaults) and go directly 

to Summary Impacts to view the results of the analysis. 

For those users with more experience with wind power plants and/or economic impact analysis (i.e., those with 

more project-specific information on costs and expenditures, financing, taxes, and local share of spending, among 

others), project-specific values can be entered to override the default values. 

Once the analysis is complete, the user has several options for saving the data and results including printing the 

results, saving the model (using a different name), or copying the results into a spreadsheet format. 

Interpreting the Results 

Regardless of the amount of project-specific data entered by the user, JEDI provides sufficient information to 

help users better understand the economic impacts associated with the project being analyzed. The model 

provides basic project information to identify the magnitude of the construction-related spending and ongoing 

operating and maintenance (O&M) expenditures, as well as the portion of local spending. As noted earlier, these 

outputs should not be interpreted as precise values. Instead, they should be used as an indication of the magnitude 

of the potential economic development impacts. The “local share” values  default or user modified  are 

determined in the model for each of the expenditures. Similarly, the model identifies local spending on debt and 

equity payments, property taxes and land lease payments. 

In addition to the basic project information, the model provides analysis (divided into direct, indirect and induced 

impacts) of the local jobs, earnings, and output (economic activity) generated as a result of the project. This 

includes the one-time impacts from the construction phase, as well as the annual or ongoing impacts from the 

annual operations. 

For example, JEDI can be used to quickly and easily find the economic impacts from a 100-megawatt (MW) wind 

power plant in Colorado to be built in the year 2004 using 1.5-MW turbines at a cost of $1000 per kW. Figure 1 

shows the results of such an analysis. By entering this information into the model and accepting the model 

defaults, we find that the construction of the plant will support just over 220 local jobs (full-time equivalent for a 

year) and generate almost $12 million in local economic activity during the construction period. Of the total jobs, 

85 are directly attributable to the construction sector. 

Once this project is operational, it continues to benefit the state by providing 40 full-time equivalent jobs each 

year of operation (20 directly employed by the wind plant). Total annual local spending from the ongoing 

operations is approximately $1.3 million. 
7

Wind Plant - Project Data Summary 

Year of Construction 2004 

Project Location COLORADO 

Project Size - Nameplate Capacity (MW) 100.0 

Turbine Size (KW) 1500 

Number of Turbines 67 

Construction Cost ($/KW) $1,000 

Annual Direct O&M Cost ($/KW) $12.50 

Money Value (Dollar Year) 2004 

Project Construction Cost $100,000,000 

 Local Spending $11,692,658 

Total Annual Operational Expenses $16,841,333 

 Direct Operating and Maintenance Costs $1,250,000 

 Local Spending $781,623 

 Other Annual Costs $15,591,333 

 Local Spending $551,333 

 Debt and Equity Payments $0 

 Property Taxes $283,333 

 Land Lease $268,000 

 

Local Economic Impacts - Summary Results 

 Jobs Earnings Output 

 During construction period 

 Direct Impacts 92 $3.02 $11.43 

 Construction Sector Only 85 $2.79 $10.71 

 Indirect Impacts 58 $2.14 $6.87 

 Induced Impacts 71 $2.19 $6.60 

 

 Total Impacts (Direct, Indirect, Induced) 222 $7.36 $24.90 

 

 During operating years (annual) 

 Direct Impacts 26 $0.80 $1.33 

 Plant Workers Only 20 $0.62 $0.62 

 Indirect Impacts 4 $0.14 $0.50 

 Induced Impacts 10 $0.31 $0.94 

 

 Total Impacts (Direct, Indirect, Induced) 40 $1.26 $2.77 

Totals may not add up due to independent rounding. 

FIGURE 1. LOCAL ECONOMIC IMPACTS FROM 100-MW 

COLORADO WIND FARM EXAMPLE USING JEDI 
8

User Add-In Location Feature

The initial JEDI model design provided for state-level impact analysis. After its introduction, it was apparent 

many potential users might also wish to perform a similar level of analysis for a smaller or more localized region 

(such as an individual county or group of counties) or for a larger region (such as a group of neighboring states) 

to better capture the regional benefits. The high cost of including multiplier and expenditure data in the model for 

every county in the United States and the complexities associated with designing the model to analyze the endless 

number of possibilities for combining counties and states made this impractical. 

To accommodate those users who desire this level of analysis, a User Add-In Location feature is provided. This 

feature allows users with the capability to derive or obtain the necessary data inputs to complete analysis for a 

specific region of interest other than the state level included with the base model. The necessary inputs include 

direct, indirect, and induced multipliers for employment, earnings and output (per million dollars change in final 

demand) and personal consumption expenditures (i.e., average consumer expenditures on goods and services 

calculated as a percentage for each industry  totaling 100 percent combined), for the 14 aggregated industries 

analyzed in the model. More detail on the sectors contained in each industry can be found as an appendix to the 

model, which is made available to all JEDI users. 

The aggregated industries include: 

1. Agriculture 

2. Construction 

3. Electrical Equipment 

4. Fabricated Metals 

5. Finance, Insurance, and Real Estate 

6. Government 

7. Machinery 

8. Mining 

9. Other Manufacturing 

10. Other Services 

11. Professional Services 

12. Retail Trade 

13. Transportation, Communication and Public Utilities 

14. Wholesale Trade 

Once the user’s new location data are entered into JEDI, the user need only identify the location of the wind plant 

(in the project description section of the ProjectData worksheet) as MyCounty or MyRegion (depending on where 

the data are entered in the User Add-In Location worksheet) and proceed with the analysis. 

Data Sources 

Analyzing the economic impacts of constructing and operating wind power plants requires a large amount of 

project-specific data, state-specific input-output multipliers and personal expenditure patterns, and price deflators. 

The project-specific data include a bill of goods (costs associated with actual construction of the facility, roads, 

etc., as well as costs for equipment and other services and fees), annual operating and maintenance costs and data 

on the portion of expenditures spent locally, financing terms, and tax rates. More specifically, the model requires 

the following project inputs: 
9

• Construction Costs (materials and labor) 

• Equipment Costs (turbines, rotors, towers, etc.) 

• Other Costs (utility interconnection, engineering, land easements, permitting, etc.) 

• Annual Operating and Maintenance Costs (personnel, materials and services) 

• Other Parameters (financial: debt and equity, taxes, and land lease) 

Unfortunately, many developers consider this type of information proprietary due to competitive forces in the 

marketplace. Similarly, project-specific differences can and do significantly impact costs. As a result, it is nearly 

impossible to identify a one-price-fits-all situation. Nevertheless, the model provides reasonable default values 

for each of the inputs noted above and all of those necessary for the analysis. These values represent average 

costs and spending patterns derived from a number of sources (project specific data contained in reports and 

studies) and research and analysis of renewable resources undertaken by the model developer during the past 10 

years. Among other sources (including personal communications and anecdotal evidence gathered to complete 

previous renewable studies), the model incorporates specific project-related data derived from the following 

sources: 

BBC Research and Consulting. Potential Economic Benefits from Commercial Wind Power Facilities in Quay 

County. New Mexico Energy, Minerals and Natural Resources Department, Santa Fe, New Mexico. July 15, 

2000. 

DanMar and Associates. Economic Impact Analysis of WINDPOWER DEVELOPMENT in Southwest Minnesota. 

Southwest Regional Development Commission, Slayton, Minnesota. September 1996. 

Office of Utility Technologies, Energy Efficiency and Renewable Energy. Renewable Energy Technology 

Characterizations. Electric Power Research Institute and U.S. Department of Energy. December 1997. TR109496. 

Wind, Thomas A. Wind Farm Feasibility Study. Iowa Association of Municipal Utilities, Ankeny, Iowa. April 

1996. 

Personal communications with Dan Juhl, a wind project developer in Minnesota, 2003. 

Personal communications with Steve Clemmer, Research Director, Clean Energy Program, Union of Concerned 

Scientists, Cambridge, Massachusetts, 2003. 

The state-by-state input-output multipliers and household commodity demand/personal consumption expenditure 

patterns were derived from IMPLAN ProfessionalTM Version 2.0, using 2000 state data files for the respective 

states. Minnesota IMPLAN Group, Inc., Stillwater, Minnesota. 

The U.S. price deflators were derived from Current Dollar and “Real” Gross Domestic Product data downloaded 

from the Bureau of Economic Analysis Web site, http://www.bea.doc.gov, December 2002. 
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Job and Economic Development Impact (JEDI) Model: A User-Friendly Tool to Calculate 

Economic Impacts from Wind Projects 

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M. Goldberg*, K. Sinclair, and M. Milligan 

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WER4 6003 

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*MRG & Associates National Renewable Energy Laboratory 

 17798 Starduster Drive 1617 Cole Blvd. 

 Nevada City, CA 95959 Golden, CO 80401-3393 

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13. ABSTRACT (Maximum 200 words)

The U.S. Department of Energy/National Renewable Energy Laboratory (DOE/NREL) has developed a spreadsheet-based wind 

model (Jobs and Economic Development Impact (JEDI)) that incorporates economic multipliers for jobs, income, and output. 

Originally developed with state-specific parameters, it can also be used to conduct county and regional analyses. 

NREL has enlisted the Wind Powering America (WPA) State Wind Working Groups (SWWGs) to conduct county-specific economic 

impact analyses and has encouraged them to use JEDI if they do not have their own economic model. The objective of the 

analyses is to identify counties within WPA target states, and preferably counties with a significant agricultural sector, that could 

economically benefit from wind development. These counties could then explore opportunities to tap into the United States 

Department of Agriculture (USDA) Farm Bill Section 9006 grants and loans to stimulate wind development. 

This paper describes the JEDI model and how it can be used. We will also summarize a series of analyses that were completed to

fulfill a General Accounting Office (GAO) request to provide estimates of the economic development benefits of wind power. 

14. SUBJECT TERMS 15. NUMBER OF PAGES

wind energy; wind turbine; wind energy; wind energy model; JEDI; Job and Economic 

Development Impact model 16. PRICE CODE

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