The popularity of public investment in local bio-fuels production as a rural development initiative is growing. An important consideration in determining the level of public support for a plant's development, however, is accurately measuring public externalities resulting from plant activity. The purpose of this research was to first develop a set of community multipliers associated with various bio-fuel plant configurations, and then develop an easy to use tool that allows local communities to measure potential benefits based on varying levels of plant activity.

Deller, Steven

Fortenbery, T. Randall

English

Research Papers in Economics

  University of Wisconsin-Madison 
Department of Agricultural & Applied Economics 
 
 
 
 
 
  Staff Paper No. 505                                           December 2006 
 
 
 
Understanding Community Impacts: A Tool for Evaluating 
Externalities from Local Bio-Fuels Production 
 
By 
 
T. Randall Fortenbery and Steven Deller 
 
 
 
__________________________________ 
    
  AGRICULTURAL  & 
APPLIED ECONOMICS 
____________________________ 
 
STAFF PAPER SERIES 
 
 
 
 
 
 
 
Copyright © 2006 T. Randall Fortenbery & Steven Deller.  All rights reserved.  Readers may 
make verbatim copies of this document for non-commercial purposes by any means, provided 
that this copyright notice appears on all such copies.  
 
 
 
Understanding Community Impacts: A Tool for Evaluating  
 
Externalities from Local Bio-Fuels Production 
 
 
 
 
 
 
 
 
 
 
 
 
 
T. Randall Fortenbery 
Renk Professor of Agribusiness 
Department of Agricultural and Applied Economics 
University of Wisconsin-Madison/Extension 
trforten@wisc.edu
 
Steven Deller 
Professor and Community Development Specialist 
Department of Agricultural and Applied Economics 
University of Wisconsin-Madison/Extension 
scdeller@wisc.edu 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 Understanding Community Impacts: A Tool for Evaluating  
 
Externalities from Local Bio-Fuels Production 
 
Introduction 
The promotion of bio-fuel production has long been a popular strategy to revitalize rural 
communities.  The interest in bio-fuel has been heightened with $3.00 gasoline and the 
fervor to reduce our dependence on oil overall and foreign oil in particular.  Media 
coverage, traditionally limited to corn producing regions, has been pronounced in 
national media outlets including the Chicago Tribune’s (May 7, 2006) coverage of  
professional investors looking to firms specializing in bio-fuels to the Los Angles Times 
(June 29, 2006) coverage of the major US auto manufacturers focusing on building cars 
that are able to run solely on bio-fuels. 
 
At the local level proponents anticipate that the construction of bio-refining plants will 
not only increase local employment, but also enhance farm incomes through purchases of 
local farm production to be used as feed stocks.  Despite optimism regarding the future of 
bio-refining, however, the current market environment is such that potential investors in 
bio-fuels plants often seek financial support from a local community before initiating 
facility construction.  The rush to bio-fuels has almost reached a frenzied state and 
communities are more often than not willing to jump on the bandwagon without 
considering the pros and cons of the proposal.  The challenge to local policy makers is 
determining how extensive the community benefits will be as a result of subsidizing a 
bio-refining plant, and then deciding, based on expected benefits, what an appropriate 
level of public investment might be. 
  2There are several studies in the public and private domains that point to the potential 
benefits of siting a bio-fuels plant (see for example Fortenbery (2005), Nelson et al. 
(2001), and Urbanchuck and Kapell (2002)).  These studies, however, have generated a 
wide range of results, some of which are inconsistent with the impacts generally realized 
by other economic development activities (Swensen (2005)).  In many cases, local 
communities are given the results of analysis conducted by private consultants, but are 
not in a position to evaluate the sensitivity of the results to assumptions made in the 
analysis. 
 
Communities interested in making independent, informed decisions regarding the 
development of a local bio-fuels plant need an objective, independent analysis of the out-
of-plant community impacts associated with bio-fuels production.  Extension educators 
are often requested to provide such an analysis.  One the one hand promoters of 
agricultural interests are champions of bio-fuel plants and expect Extension to support 
such proposals.  Yet, in many instances the case for bio-fuel plants are oversold with 
overly optimistic promises of positive economic impacts.  Extension educators may find 
themselves in the unpleasant situation of removing themselves from an important 
community discussion or alienating a traditional clientele base.  Extension educators are 
in need of an objective analytical tool to help inform local decision makers and concerned 
citizens.    
 
To accommodate this need, we have developed a simple, menu driven computer program 
for use by Extension educators and local decision makers.  The program is based on 
  3empirical input/output analysis developed using IMPLAN.  It incorporates the economic 
multipliers identified with IMPLAN, and allows users to evaluate expected community 
impacts based on three different activities: 1) total plant employment, 2) total plant sales, 
and 3) total income earned by plant employees. 
 
Input/Output Analysis and Data Development 
 
Input/output analysis is a modeling technique that measures the interaction between 
different sectors of an economy, and identifies multipliers that reflect total economic 
activity generated as a result of a specific activity in a particular sector.  One can think of 
an input/output model of the local economy as a spreadsheet capturing the flow of dollars 
within the economy.  The columns of the spreadsheet represent buyers (demand) and 
rows represent sellers (supply), with the individual cells of the spreadsheet capturing the 
flow of dollars between buyers and sellers.   
 
When a new business is located in a community, the total economic activity that occurs is 
not only that directly associated with the new business (such as sales to customers), but 
also activity that results from the new business buying services from other businesses, 
and the activity that results from their employees spending at least some part of their 
income locally (for example, the local grocery store, the movie theatre, the local gas 
station).  By changing elements in the spreadsheet (the input/output model) we can trace 
how that change ripples throughout the whole of the economy.  Input/output analysis 
  4identifies a matrix of multipliers that measures both the direct and ancillary impacts 
associated with the new business.   
 
Using IMPLAN, multipliers can be estimated that are both geographically and industry 
specific for those industry sectors recognized by IMPLAN.  Unfortunately, bio-fuels is 
not a specific industry choice in IMPLAN.  To develop our decision tool multipliers for 
the State of Wisconsin were estimated by evaluating a bio-fuels plant’s impact on the 
business sectors it would interact with; in other words, rather than “shocking” the local 
economy by inserting a bio-fuels plant, the local economy was “shocked” by growth in 
every other business sector the plant would be expected to interact with.  The multipliers 
identified were than imbedded in the software decision tool.  The tool provides the 
flexibility of evaluating community impacts based on different levels of plant activity, 
with specific multipliers based on a given production technology for each plant 
considered. 
 
Decision Software – Community Impacts of Bio-Diesel and Bio-Ethanol Plants 
 
The community decision software, titled Community Impacts of Bio-Diesel and Bio-
Ethanol Plants (BDBE for short) (Fortenbery et al. (2005)) considers two different bio-
fuel products, and three different plant configurations.    The bio-fuel products considered 
are vegetable oil and recycled grease based bio-diesel and corn based ethanol.  Two 
different size bio-diesel plants are considered and one ethanol plant.  The bio-diesel 
plants include a 4 million gallon per year production plant and a 10 million gallon per 
  5year plant.  The ethanol plant considered is a 40 million gallon per year plant.  The 
technology for the bio-diesel plant is taken from Fortenbery (2005).  This represents the 
current scale of plants under consideration in several Upper Midwest locations.  The 
ethanol plant technology is based on Fortenbery and Deller (2006), and is consistent with 
the average size plant from McNew and Griffith (2005). 
 
BDBE allows community impacts to be estimated based on a matrix of multipliers 
associated with plant employment, total plant sales, and total plant employee income.  
The software allows community policy makers to evaluate long-run impacts from the 
development of a new plant, and also the marginal increase in community benefits 
associated with public investments in plant expansion and/or investments in technologies 
that improve the efficiency of an existing plant.   The software does not account for short 
run activity resulting from initial plant construction, including jobs associated with 
construction. 
 
Generally, the community impact results estimated with BDBE should be viewed as 
lower bound estimates of actual impacts.   Economic impacts associated with price 
increases in inputs purchased (including primary feed-stocks) are not considered.  This 
allows community leaders to make conservative estimates relative to the benefit/cost ratio 
associated with plant development, and increases the likelihood that the anticipated pay-
back from any public investment will actually be realized. 
 
  6Figures 1 through 3 are illustrations of the BDBE program screens.  The top panel in 
Figure 3 is a picture of the BDBE input screen.  The user selects both the Type of 
Analysis and the Type of Industry from drop down menus.  The user then enters an event 
level associated with those choices.  The second panel shows the results from selecting 
employment analysis of a bio-ethanol plant for evaluation.  In the example illustrated 
here the user has indicated the plant will employ 32 people (the event level).  The first 
rows below the input section identify the multipliers associated with bio-ethanol plant 
employment, and the second row presents estimated employment levels based on the 
multipliers.  The cell labeled Initial identifies direct employment at the plant, and the 
Indirect cell refers to jobs created as a result of business to business transactions between 
the ethanol plant and other businesses (e.g., utilities, transport firms, office supply 
companies, etc.).  The Induced category represents additional jobs created from activity 
associated with labor spending wages in the local economy (e.g., spending income in 
grocery stores, movie theaters and barber shops).  The total is the sum of all jobs created.   
 
Software Applications 
 
An important application of BDBE is conducting sensitivity analysis on potential changes 
in plant configurations.  For example, total plant sales can be altered in the event level 
window to facilitate different assumptions relative to either prices received by the plant 
or assumptions concerning standard operation as a percent of full capacity.  Plants 
expected to operate at 80 percent capacity would have less total sales than those operating 
at full capacity, and the resulting economic impacts would be less.  Since the assumptions 
  7used to estimate the initial multipliers are less generous than most previous studies 
relative to overall plant impacts, the results from BDBE can be combined with other 
studies to identify a range of potential benefits. 
 
The multipliers estimated thorough IMPLAN and used to develop BDBE are provided in 
Table 1.  Note that the multipliers vary considerably across plant configurations.  This in 
and of itself is an important element of Extension educational programs; each proposed 
plant configuration results in a unique community impact, and the estimated impacts 
from one configuration are not directly transferable to another configuration. 
Communities considering public investment in bio-fuels plants can compare expected 
returns across plant types.   
 
BDBE can be used to estimate the impacts from the development of a single plant, or the 
aggregate state wide impacts from the development of, say, 10 separate bio- plants (their 
total activity levels would be summed and entered in the event window).  In addition, 
BDBE can be used by Extension educators to help community leaders understand the 
marginal impacts expected from a change in plant size or efficiency.  In many 
communities that have an existing bio-fuels plant (in most cases ethanol), serious 
discussion has centered on both plant expansion and the adoption of new technologies 
that improve existing plant productivity.  As an example, the impacts associated with 
adopting an enzyme technology developed by Lucigen, a relatively new enzyme 
company that has focused a part of its enzyme innovations on increasing the yield from 
corn based ethanol production, are provided in Figure 4.  The increased output is based 
  8on Lucigen’s estimates (Biondi).  By inputting the marginal increase in plant sales 
anticipated by adopting Lucigen technology, the impacts associated increased plant 
efficiency can be calculated.  Again, this allows local policy makers to evaluate the 
expected return to the community associated with public investment in plant expansion or 
the adoption of new technology. 
 
An important provision in facilitating community use of BDBE is insuring accessibility.  
The program was developed in Virtual Basic, and compiled to be a stand alone program.  
All components were then place in a zip file.  The zip file can be downloaded from a 
public website (www.aae.wisc.edu/renk) and unzipped.  The program includes an 
introduction to the basic concepts of input/output analysis, a glossary of terms to facilitate 
the understanding of various effects (for example the differences between indirect and 
induced effects), and the input section itself.  The input section is quite simple to use and 
the results are presented directly on the input screen. 
 
Conclusions 
 
An important component in community evaluation of returns to public investments in 
bio-fuels plants has been missing.  To date there has been no independent means for 
communities to easily evaluate benefits to either new plant development or investments 
in plant expansion or technological improvements.  The computer program presented 
here fills that need and provides Extension educators with an objective economic impact 
tool.   The plant models used to construct the matrix of multipliers are representative of 
  9plants currently in operation or under consideration, and most technological innovations 
in development do not appear to alter the production function significantly.   
 
This program can also serve as a framework for other stand along economic impact 
programs designed for specific industries.  Many times access to complex impact 
modeling software such as IMPLAN is limited or is beyond the scope of the Extension 
educational program.   Programs such as BDBE can be readily constructed for a range of 
specific industries and are readily accessible to all Extension educators. 
  10Table 1.  Estimated Multipliers by Plant.   
 
Jobs Direct Indirect Induced Total
Four Million Gallon per Year - Bio-diesel  1.00 0.25 0.45 1.70
Ten Million Gallon per Year - Bio-diesel  1.00 0.55 1.00 2.55
Forty Million Gallon per Year - Ethanol 1.00 1.43 1.98 4.40
Industry Output
Four Million Gallon per Year - Bio-diesel  1.00 0.05 0.06 1.11
Ten Million Gallon per Year - Bio-diesel  1.00 0.04 0.05 1.09
Forty Million Gallon per Year - Ethanol 1.08 0.08 0.51 1.68
Total Income
Four Million Gallon per Year - Bio-diesel  1.00 0.46 0.62 2.08
Ten Million Gallon per Year - Bio-diesel  1.00 1.03 1.38 3.41
Forty Million Gallon per Year - Ethanol 1.00 0.36 0.39 1.75
  11Figure 1.  Front page 
 
 
Figure 2.  Menu selection – second page   
 
 
  12Figure 3.  Economic impact assessment page 
 
 
 
 
  13Figure 4.  Measuring marginal impacts from increased productivity, thus increased sales 
 
 
 
  14References 
 
Badger State Ethanol.  http://www.badgerstateethanol.com/company_history.htm. 
 
Biondi, J.  Chief Operating officer, Lucigen.  Personal communication. 
 
Chicago Tribune.  May 7, 2006 
 
Energy Information Administration.  Petroleum Marketing Monthly, various issues. 
 
Fortenbery, T.R. (2005).  “Biodiesel Feasibility Study:  An Evaluation of Biodiesel 
Feasibility in Wisconsin,” Department of Agricultural and Applied Economics, 
UW-Madison, Staff Paper No. 481.  
 
Fortenbery, T. R. and S. Deller (2006).  “Perfectly Elastic Supply Curve?  Accurate 
Measures of Community Impacts from Ethanol Production,”  unpublished 
working paper, Department of Agricultural and Applied Economics, UW-
Madison. 
 
Fortenbery, T.R., S. Deller, H. Park, and B. Thomas (2005).  Community Impact of Bio-
diesel and Bio-ethanol Plants.  Software developed by the Renk Agribusiness 
Institute, University of Wisconsin – Madison. 
 
Los Angeles Times.  June 29, 2006.  
 
McNew, K. and D. Griffith (2005).  “Measuring the Impact of Ethanol Plants on Local 
Grain Prices,”  Review of Agricultural Economics, 27(2):164-180.    
 
Nelson, R., MARC-IV Consulting, and J. Leatherman (2001).  “Kansas Soybean Based 
Biodiesel IMPLAN Analysis: Estimating the Impact of a Soybean Processing and 
Biodiesel Production Plant in the Crawford and Ford Counties and the State of 
Kansas,” Kansas Soybean Commission and Energy Programs Division – Kansas 
Corporation Commission. 
 
Swensen, D. (2005).  “Model Economic Analyses:  An Economic Impact Assessment of 
an Ethanol Production Facility in Iowa”, Department of Economics, Iowa State 
University, http://www.econ.iastate.edu/research/webpapers/paper_12226.pdf. 
 
Urbanchuck, J. and J. Kapell (2002)..  “Ethanol and the Local Community”, AUS 
Consultants and SJH and Company,  
http://www.ethanolrfa.org/Ethanol_Local_Community.PDF. 
 
Vermeer, M.  Todd and Sargent.  Iowa.  Personal communication.  
  15Abstract 
The popularity of public investment in local bio-fuels production as a rural development 
initiative is growing.  An important consideration in determining the level of public 
support for a plant’s development, however, is accurately measuring public externalities 
resulting from plant activity.  The purpose of this research was to first develop a set of 
community multipliers associated with various bio-fuel plant configurations, and then 
develop an easy to use tool that allows local communities to measure potential benefits 
based on varying levels of plant activity.   
  16

Understanding Community Impacts: A Tool for Evaluating Externalities from Local Bio-Fuels Production

http://www.aae.wisc.edu/pubs/sps/pdf/stpap505.pdf

Understanding Community Impacts: A Tool for Evaluating Externalities from Local Bio-Fuels Production

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