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GUIDE TO PRODUCING A TRADITIONAL

ECONOMIC IMPACT ANALYSIS

FOR A UNIVERSITY

A Report from the Office of the University Economist







May 2009









Timothy D. Hogan, Ph.D.

Professor Emeritus, Department of Economics,

and Research Associate, Center for Competitiveness and Prosperity Research





Center for Competitiveness and Prosperity Research

L. William Seidman Research Institute

W. P. Carey School of Business

Arizona State University

Box 874011

Tempe, Arizona 85287-4011



(480) 965-5362

FAX: (480) 965-5458

EMAIL: Tim.Hogan@asu.edu

www.wpcarey.asu.edu/seid/

GUIDE TO PRODUCING A TRADITIONAL ECONOMIC IMPACT

ANALYSIS FOR A UNIVERSITY

A university affects its regional economy in at least three ways: (1) the institution’s operations

contribute to the region’s economic activity; (2) the university’s educational and training

activities augment the region’s stock of human capital, benefitting both individuals and society;

and (3) the research activities of the institution expand the knowledge base and enhance regional

economic development. This discussion focuses on the first of these contributions — what might

be termed the “traditional” definition of a university economic impact study — the measurement

of the economic impacts resulting from expenditures by the university and its employees,

students, and visitors.



This guide first discusses some points to be considered so that the analysis provides accurate

estimates of the economic impact of the university and conforms to the accepted theory and

practice of regional economics. The second part of this guide addresses the practical issues of the

kinds of data that are needed for the analysis and the steps that are involved in preparing an

economic impact analysis.



METHODOLOGICAL ISSUES



Overall Versus Incremental Economic Activity

The contribution of a university to the regional economy sometimes has been defined broadly in

terms of overall economic activity associated with university operations. This approach is

appropriate for some uses in that it provides an overall measure of the size of the enterprise and

is consistent with analyses that look at the overall economic activity associated with a particular

industry, such as biotech.



However, regional economists conventionally define economic impact in a narrower sense. This

approach defines the economic impact of a university as the incremental economic activity in the

region due to the existence of the institution — versus the level if the university did not exist.

Usually this definition is simplified to include only those activities that are (1) funded by sources

from outside the region, or (2) would occur outside the region if the university did not exist.

Even with this simplified approach, it is difficult to calculate the incremental economic activity

associated with university operations.



Defining the Study Area

Defining the study area is one of the fundamental steps in an economic impact analysis. The

choice is usually governed by both economic and policy factors. From purely an economic point

of view, the study area should be defined as the functional economic area in which the university

is located. Normally this is a recognized economic region, such as a metropolitan area, for which

economic data are reported. In some instances, however, it may be necessary for policy reasons

to define a study area that does not match the university’s functional economic region, which

likely will affect the results of the impact analysis.



For example, if a smaller geographic area, such as a city within a metro area, is chosen, the

measured economic impact will be relatively small since much of the spending and income





1

related to university operations spill outside the study area. Conversely, state-funded institutions

may have good reason to define the study area as the entire state, since the study’s primary

audience may be seen as the state’s legislators and the businesses and residents who pay taxes to

support the institution. Choice of an area larger than the true economic region is likely to have

mixed effects on the impact analysis. Use of a broader region captures more of the university

suppliers and employees, reducing spending and income leakages out of the region and thereby

increasing the size of multiplier effects. On the other hand, a bigger region implies that a smaller

proportion of students, visitors, and other funding sources come to the university from outside

the study area, reducing the measured economic impact.



Direct Versus Total Impacts

In economic impact analysis, there is a fundamental distinction between the direct economic

effects of university operations and the total economic impact of a university on its region. The

direct impacts are the university expenditures for goods and services, the wages and salaries paid

by the university, the jobs it provides to area residents, and taxes and other payments to area

governments. The total economic impact is a measure of the changes in economic activity after

all the secondary and indirect effects caused by the stimulus of the direct impacts have worked

their way through the economy.



Estimates of the direct effects and the total impact are produced by very different methods. The

information used to calculate the direct impacts is normally collected from a combination of

university records and surveys of various groups within the university community. Researchers,

however, often have to fill in gaps in the data from secondary sources. Although other methods

have been used in the past, the prevailing current practice is to use a regional economic impact

model to obtain estimates of the total economic impact.



If some type of computer model of regional economic impact is not already available to the

researcher, one of the three most commonly used regional models — IMPLAN, REMI, and

RIMS II — can be purchased. A ready-to-run version of these models specifically developed for

the study area can be obtained from the following suppliers:

 IMPLAN from the Minnesota IMPLAN Group Inc. (implan.com)

 REMI from Regional Economic Models Inc. (www.remi.com)

 RIMS II from the U. S. Bureau of Economic Analysis (www.bea.gov)



In these regional economic impact models, the estimates of the direct university impacts are used

as the inputs to the estimation process, and the computer model generates detailed estimates of

the total economic impact of the university. (RIMS II is actually a detailed set of multipliers

rather than a complete model, so some additional steps are necessary compared to the other two

models.)



CALCULATING THE DIRECT ECONOMIC IMPACTS

The following subsections discuss the practical issues of the kinds of data that are needed and the

steps involved in calculating each of the components of the direct impacts. First, however, a few

general comments apply throughout the process:









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1. Obtaining all of the data in the form necessary to accurately calculate the incremental

economic impact of a university would be an extremely arduous, if not impossible, task.

In practice, many simplifying assumptions and estimation procedures will likely be

necessary. The typical approach includes only those activities that are (a) funded by

sources from outside the region, or (b) would occur outside the region if the university

did not exist. Activities falling under (a) can generally be quantified; those in group (b)

are much more difficult to deal with. In many cases, they are either ignored or estimated

on an ad hoc basis.

2. To facilitate the process of estimating the incremental impacts, data should be segregated

by funding source to the extent possible, for example, state government appropriations,

federal research funds, and private grants. Where the explicit funding source is

ambiguous, it is desirable to categorize the funding as coming from a local source or from

outside the region.

3. To the extent possible, the data should be disaggregated by types of goods and services

that match the spending categories/industry sectors used by the particular regional

economic impact model that will be used for the analysis.

4. Ideally, the data should relate only to goods and services purchased from suppliers within

the study area. This requirement obviously makes the data collection process much more

complicated. Modern regional economic impact models, such as IMPLAN and REMI,

include procedures to produce estimates of within-region expenditures, but the figures

derived from actual university purchasing records would of course produce a more

accurate measure than the estimated values produced by the computer model.

5. Usually, there are multiple ways that direct impacts of the university can be specified as

inputs in the regional economic impact models, such as expenditures, employment, or

income payments. Care must be taken not to specify two variables that are actually

measuring the same direct impact, for example, the number of employees and the

compensation paid to those employees. For the discussion that follows, the approach is to

specify the direct impacts in terms of expenditures.



Institutional Expenditures

Direct purchases of goods and services by the university from vendors in the region are one of

the major components of the direct impacts. Publicly available data sources, such as annual

reports or websites, cannot be counted on to provide the detailed data needed for the analysis. In

most cases, data collection efforts will involve special data requests to the appropriate university

offices, and often surveys of individual units within the university.



Data relating to all university-related expenditures should be included, not just those associated

with the main university budget. This may encompass a wide variety of university-related

activities, including summer school and training programs, conferences and entertainment

events, athletic departments, research and grants, university foundations, and auxiliary

enterprises, such as student living and dining facilities. A complete accounting of the annual

economic impact of a university should also include construction expenditures.



As suggested above, to the extent possible, the data should be collected in a way that provides

figures for detailed expenditure categories for each funding source. Having the data organized in

this manner will make it easier to calculate the incremental impact.







3

Once all of the expenditure data have been collected, a set of figures representing total university

spending for each type of good/service from each funding category should be prepared. If an

estimate of the overall economic impact of university operations is desired, this set of spending

figures can be aggregated to produce figures on the total direct university expenditures to be

reported as such and to be used as inputs to the regional economic impact model.



To develop estimates of the university’s direct impacts based on the incremental definition of its

economic impact requires more work. To the extent that the data allow, expenditures funded by

identifiable “outside” sources can be tabulated directly. In the other instances, however, it may

be impossible to identify whether expenditures were funded by nonlocal sources. In these cases,

estimation procedures will have to be developed based upon the available information. For

example, the share of funding for instructional programs that comes from tuition payments from

out-of-region students plus other nonlocal sources could be used to estimate the proportion of

instructional-related expenditures that should be designated as part of the incremental impacts.



Other Institutional Data

In addition to the expenditure data, certain other information relating to university operations are

also necessary inputs to an economic impact analysis.



Employment

Providing jobs to area residents is one of the direct economic contributions of the university to

the region, but based on the expenditure-based methodology described in this paper, employment

numbers do not serve as a measure of direct impacts for the estimation process. However,

information relating to university employment is needed to develop estimates of another major

component of university-related expenditures: spending by faculty and staff. Job numbers by

type of employee — faculty, staff, graduate assistants, student workers, etc. — are usually

readily available from university sources. In addition, the number of jobs created and supported

in the regional economy is of interest to the audience of an economic impact analysis and is

usually reported as one aspect of the economic impact of a university. The popular regional

economic impact models produce detailed estimates of the total number of jobs created and

supported in the region as one of the outputs of the exercise.



Again, there are two important caveats relating to this information. First, job figures should be

collected for those employed on all university-related activities, including auxiliary enterprises,

the athletic department, etc. Second, if possible, it is desirable to collect the employment data

separately by type of employee and by funding source to facilitate estimation of incremental

impact measures.



Wages and Salaries

While income payments to area residents are certainly a positive contribution to the regional

economy, the wages and salaries paid to university employees do not constitute a direct

economic impact in the expenditure-based methodology presented here. The direct impact comes

when university employees spend this income. However, the wage and salary figures are an

important input for estimating employee expenditures (this process will be discussed in the next

subsection). Data on wage and salary payments by type of employee should be available from

university records.







4

The information should be collected for those employed on all university-related activities, and,

if possible, it is desirable to collect the data separately by funding source to facilitate estimation

of incremental impact measures.



Enrollment

Information on the number of students attending the university is a key ingredient for preparing

estimates of student spending. Separate enrollment figures are usually available for the separate

school terms: semesters or quarters, summer school sessions, etc. It is desirable to collect

separate information for each term as enrollment figures can vary widely. The data should also

be collected on a head-count basis not in terms of FTE. If the university has multiple campuses,

care should be taken to avoid double-counting.



To the extent possible, the enrollment figures should be split into “within region” and “out-of-

region” groups. It is desirable to collect separate counts for undergraduate versus graduate status,

since spending levels and patterns are likely to differ.



Faculty and Staff Expenditures

Spending by its employees for goods and services supplied by vendors in the region make up

another component of the direct economic impacts of a university.



If resources permit, the preferred approach to obtain information on employee spending is

through an employee survey. This data collection effort could be part of a broader survey

program, but for the economic impact study, the primary purpose of the survey is to provide

statistically valid estimates of household income and spending of employee households by type

of product and service. Given probable different spending patterns between faculty, staff, and

student employees, the survey should be constructed to provide separate spending data for each

group.



If it is not possible to obtain survey information, an alternative approach is to prepare the

expenditure estimates based on household spending information from the Consumer Expenditure

Survey, produced by the U.S. Bureau of Labor Statistics. Detailed information on spending

patterns of U. S. households categorized by income, age, region of residence, and other

characteristics are available from the BLS website (www.bls.gov/cex/).



Only spending funded by university-related income should be included. An efficient way to do

this is to convert the employee spending information into measures of spending per dollar of

income and then multiply these spending factors by the aggregate wage and salary figures from

university records.



To obtain an estimate of amount of employee expenditures that should be included in the

economic impact analysis based on the incremental approach, an estimate of the proportion of

total employee wages and salaries that were funded from sources consistent with that definition

would be needed.









5

Student Expenditures

Student expenditures are another important component of the direct impact of university

operations. Again, the preferred method to obtain spending information is through a survey of

students at the university. To provide information based on the incremental impact approach, the

survey should divide students into three groups: students from outside the region, students from

inside the region who would have gone elsewhere to school if the university did not exist, and

students who would have stayed in the region if the university did not exist. For estimates based

on the incremental approach, only spending information from the first two groups should be

included, and the proportion of the number of students in the first two groups to the total number

of students surveyed should be recorded. If the overall economic impact of university operations

is desired, then spending information should be collected that is representative of the entire

student population.



Detailed issues relating to the proper design of the questionnaire are outside the scope of this

discussion, but certain issues must be addressed:

 Payments for products and services provided by the university, such as tuition and dorm

fees, should not be included to avoid double-counting.

 Only purchases of goods and services from local suppliers should be included.

 Information on university employment status should be obtained to avoid double-

counting in the student and employee spending categories.



If it is not possible to conduct a student survey, alternative sources of valid data on student

spending are limited. The household spending information from the U. S. Consumer Expenditure

Survey does not provide a reasonable substitute as it did for employee expenditures since student

spending patterns are much different than those of typical households. Probably the best

approach is to use information on student spending from another university economic impact

study, with appropriate adjustments to make the information fit the situation as nearly as

possible, for example applying inflation rates to account for differences in timing.



Once measures of per student expenditures have been developed, estimates of total student

expenditures can be prepared using university headcount enrollment figures. Estimates of the

direct impact of student expenditures based on the incremental definition of economic impact

also require an estimate of the total number of students in the region because of the existence of

the university. A student survey would provide information to produce this estimate. Without

survey information, information relating to the proportion of the student body from the local area

may be available from university sources. If not, an estimate could be developed from

information on students’ permanent addresses from university records or possibly other ad hoc

sources.



Visitor Expenditures

Spending by university-related visitors is another major component of the direct impacts of a

university on the regional economy. Collecting information relating to expenditures by

university-related visitors can be very time consuming. A list of the different types of university-

related visits include, for example, friends and family, attendees of athletic and other university-

related events, attendees at university-related conferences, and other visitors coming for a wide









6

variety of purposes, including faculty recruitment, visiting scholars, prospective students, and

family members on campus visits.



The process of data collection usually involves contacting a variety of university offices for

information relating to each type of visitor. For some types of visits, this may require either a

formal or informal survey of each college and/or individual university unit.



Obtaining actual data relating to the types and amounts of spending by visitors is problematic. It

is generally not within the scope of a university economic impact study to conduct a visitor

survey. In some cases, units whose activities generate large numbers of visitors, such as the

athletic department or the university conference center, may conduct attendee surveys that can

provide the information. Lacking that sort of information, it is often possible to obtain

information on spending by business travelers and/or tourists to the region from local visitor and

convention bureaus that can be employed to develop reasonable estimates of university visitor

spending.



For an estimate of visitor expenditures based on the incremental approach, information on the

proportion of visitors from outside the region is also needed. Since this proportion could be

expected to vary widely among different types of visitors, obtaining this proportion for each

visitor group included in the calculations is desirable. The usual source for this information is the

specific university units involved.



Payments to Regional Governments

The final component of the direct impacts of university operations is taxes and other payments to

governmental units in the region.



Assuming the university itself is a non-profit institution, taxes paid may be limited, but the

university likely pays some amount of sales taxes, fees, and perhaps in-lieu payments to local

governments. These payments should be captured by the university’s accounting system and

retrievable during the process of collecting university expenditure data.



Some data on local taxes paid by the university and its employees could be obtained as a

component of the information collected from surveys. For the most part, however, estimates of

local taxes paid have to developed by the researchers. For example, estimates of sales taxes

could be derived from the available expenditure data.









7



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