This document provides a literature review and methodology for conducting a return on investment analysis of the Speer Boulevard Grade Separation project undertaken by the City and County of Denver in the 1990s. The literature review discusses public transportation investments, return on investment analysis methodology, and taxes related to property that are relevant to the analysis. The methodology section outlines collecting tax revenue data from reports, adjusting values to reflect 2012 dollars using the consumer price index, and using exponential smoothing to forecast future revenues. The analysis will examine costs of the project compared to tax revenues from real estate, business property, occupational privilege, sales, and use taxes to calculate the financial return to the city from the transportation infrastructure investment.

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Return on Investment Analysis Speer Boulevard Grade Separation
Andrew Lindstad
University of Colorado School of Public Affairs
October 3, 2012

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Table of Contents
List of Tables………………………………………………………………. iii
Executive Summary……………………………………………………….. iv
Introduction…………………………………………. ……………………. 1
Purpose…………………………………………………………………….. 5
Literature Review………………………………………………………….. 6
Methodology………………………………………………………………. 17
Findings…………………………………………………………................. 16
Discussion………………………………………………………………….. 20
Recommendations…………………………………………………………. 22
Implications for Future Research…………………………………………... 23
Conclusion…………………………………………………………..............24
References…………………………………………………………………. 26
Appendix A: Course Competencies……………………………...………… 29
Appendix B………………………………………………………………… 31

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List of Tables
1. City and County of Denver: Business Incentive Contracts 2008-2011...............17
2. Total Incentives Awarded and Revenue Collected By Year............................... 18
3. Return on Investment in 2012…………………………........…………………. 18
4. Summary of Survey Results…………………………………………… ……... 19
5. ROI Adjusted for Uncertainty…………………………………………….…… 21

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Executive Summary
Over the past several decades, the local government practice of incentivizing both
business recruitment and business retention has become commonplace. To create jobs and
bolster economic growth, municipalities offer firms cash payments in return for facility
relocation, expansion, and new employment opportunities. Between 2008 and 2011, the City of
Denver’s Office of Economic Development (OED) procured seven business incentive contracts.
In light of these developments, this paper focuses on an analysis of the incentives’ financial
return to the City: an integral component of the program’s overall evaluation. Comparing the
payments expended by the City to the revenue received by the City over time presents a useful
measure of the municipality’s return on investment (ROI). Costs consist of the financial
obligations pledged to these firms by the Office of Economic Development (OED), while
revenue to the City includes the businesses’ sales, OPT, real estate, and business personal
property taxes paid in return. Details on the monetary commitments were extracted from each
incentive’s contract with OED; tax revenue data were gathered from reports accessed through the
City Assessor’s Office. ROI was calculated on the portfolio of incentives as a whole, and reflects
revenues collected through 2012. The analysis also includes input from the Executive Director
of OED; a survey was administered to assist in clarifying the incentive fund’s objectives,
standards, and operations. This study found the ROI to the City to be 292 percent. For every
dollar expended by the City of Denver on recruitment and retention contracts, it received nearly
three dollars in return. In addition, the fund fulfills the OED’s strategic objectives concerning
business retention and business recruitment, and provides new job opportunities for Denver

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citizens. In tandem, these results provide significant justification for the use of business
incentives as an economic development tool.
Investment is an “initial forfeit of something we value in exchange for the anticipated
benefit of getting back more than we put in. The difference between what we put in and what we
got back is the return; we invest in order to yield this return” (Feibel, 2003, p. 1). In this paper, I
explore the Return on Investment (ROI) of a transportation infrastructure project undertaken by
the City and County of Denver in the early 1990’s. Current research suggests public
transportation infrastructure creates an environment for higher property values, which in turn
will result in higher collection of property and use tax for land and businesses in the area
adjacent to the transportation infrastructure investment. But the value of a ROI analysis extends
beyond whether the project “breaks-even” or doesn’t. Public investment decisions must be made
on how to spend limited funding. An ROI analysis is exceptionally helpful in making decisions
about discretionary projects, like the project in this study.
In this paper, I extend the examination of Return on Investment analysis to public
transportation infrastructure investments. The purpose of this study is to develop a methodology
for the prioritization of project decisions made by the City and County of Denver. Specifically, I
will examine the Speer Boulevard Grade Separation project as a window through which to view
the topic. There are many factors I could possibly look at, from building projects to cultural
investment, but transportation improvements are one of the most visible forms of public
investment. I begin by reviewing research on public goods, public transportation infrastructure
investment, and the various types of taxes levied against property and use to provide the
framework to initially guide this study. This approach to analysis will enable me to assess Return

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on Investment in the City and County of Colorado and consider implications for future research,
policy, practice, and theory.
REVIEW OF LITERATURE
In 1994, the City and County of Denver built a tunnel to carry Speer Blvd. under Sixth
Ave., Broadway and Lincoln St. to alleviate traffic congestion at the busy intersection. The
project estimate was $24 million with a completion date of December 1994. The project resulted
in a three-lane, 49 feet wide, 1,800 feet depressed roadway, split by a 710 feet tunnel. The
construction methods allowed reduced interference with traffic and minimum disturbance to
adjacent structures (Burroughs, Jiang, & Henson, 1994). The project client, the City and County
of Denver Budget and Management Office (BMO), requested a Return on Investment (ROI)
analysis of the Speer Boulevard Grade Separation. The BMO serves as the City’s main resource
for strategic decision making and aims to facilitate fiscally responsible service delivery. The City
of Denver faces fiscal challenges because of both the recession and a structural deficit. The
BMO, consequently, must make choices on how to best allocate scarce city resources. The City
and County may apply this framework in subsequent ROI project analyses.
Capital Funding
Transportation infrastructure is of critical value to the economic, aesthetic, and functional
viability of a city (City and County of Denver, 2011). There are over 1,950 centerline miles of
paved streets, 584 bridges, and over 2,000 miles of storm drainage and sanitary sewer lines in the
City and County of Denver. Each year the City and County adds to these assets, in addition to
maintaining and, in some cases, replacing existing infrastructure (City and County of Denver,
2011).

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These projects are called Capital Improvement Projects (CIP). Capital Improvement
Projects are supported by several different revenue sources. In additional to capital expenditures,
CIP’s are supported by general obligation and revenue bonds, tax increment financing, federal
and state grants, certificates of participation, local improvement districts, metropolitan districts,
and private grants (City and County of Denver, 2011). Capital Improvement Projects are not
supported by operating funds. This is important because, in general, revenue generated and
measured by the Return on Investment will go toward operating funds.
Transportation Investments
In the 1800s, streets were mostly unpaved. In dry weather, dust and dirt tainted homes
and businesses. In wet weather, mud made travel difficult. In most cities, paving streets created
many advantages. In addition to clean air and more accessible properties, paving streets also
helped maintain clean homes and businesses. However, improving streets by paving them was
expensive. Although there were some universal benefits to these improvements, people whose
property fronted a paved street benefited more, making their land more valuable. In the District
of Columbia, Congress required adjacent property owners to contribute 50% of the cost of first-
time paving of streets, curbs, gutters and sidewalks beginning in 1894. However, starting in the
1950’s, federal grants made the practice of property-owner contribution toward transportation
infrastructure finance nearly obsolete (Rybeck, 2004).
Over the past three decades, landowners have found they could rent or sell properties
near transportation infrastructure projects at a premium price. The land values of properties with
convenient locations to transportation infrastructure projects by a greater percentage than did
overall land values for the region because people value access to safe and convenient

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transportation systems and because the proximity to convenient transportation infrastructure
creates greater visibility and accessibility to clients, employees, and customers (Rybeck, 2004).
Return on Investment
The empirical evaluation of the effects of public capital on output was brought to the
limelight by the work of Aschauer (1989a, 1989b). Using a production function approach,
Aschauer produced results that identified public capital as a very powerful engine for growth in
the US. Subsequent work applying the same methodology to regional and sector-specific data,
however, failed to replicate such large effects. Indeed, it often failed to find meaningful positive
effects. Gramlich (1994) and Munnell (1992) present detailed surveys of the literature, and
Hulten and Schwab (1993) offers a detailed presentation on the infrastructure debate.
The work of Aschauer also inspired an important body of literature on the impact of
infrastructure development for other countries. This literature includes country specific
contributions, such as Otto and Voss (1996) for Australia, Seitz (1994) for Germany, Sturm and
de Haan (1995) for Holland, Merriman (1990) for Japan, Shah (1992) for Mexico, Pereira and
Roca (1999) for Spain, Berndt and Hansson (1992) for Sweden, and Lynde and Richmond
(1993) for the UK. It also includes papers with a multi-country focus such as Aschauer (1989c),
Evans and Karras (1993), Ford and Poret (1991), and Mittnik and Newman (1998), all focusing
on developed OECD countries.
The magnitude and significance of the empirical results vary greatly. Most of this
literature focuses on measuring the effects of public capital formation on private output using a
single-equation, static production function approach. In this approach, private output is regressed
on public capital in addition to private employment and capital. This approach has been

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criticized on econometric grounds, because such estimates in levels are based on non-stationary
variables and, therefore, OLS estimates are spurious in the absence of cointegration. Moreover,
OLS estimates suffer from simultaneity bias and even if this bias is corrected, they still do not
lend themselves to conclusions about causality. A comprehensive discussion of these
econometric problems is presented by Munnell (1992).
The focus on public investment in transportation infrastructures, and not on a more
comprehensive measure of public investment, is dictated by data availability. In fact, even this
data was only recently made available, and was itself the result of a long and meticulous effort
by the authors and sponsored by the Portuguese Ministry of Planning. It should be pointed out,
however, that focusing on transportation infrastructure does not detract from the relevance of the
analysis. This is because as argued before, the development strategy in Portugal, as well as in
others less developed EU countries, has been based primarily on public investment in
transportation infrastructures. Furthermore, it does not detract from the comparability of our
results. Indeed, we do compare our results with results in other studies using similar data
Measuring Return on Investment
Measuring and monitoring the outcomes for capital improvement projects over time is a
necessary step in performance and quality control (Felsenstein et al., 1995). First, it is important
to identify all revenue streams. It is also important to verify assumptions, account for
displacement effects, and consider opportunity costs. It is also important to use a present value
analysis. Each revenue and cost should be projected over time before compared in today’s
dollars (Berkebile & Harris, 2008). The exact method of measuring economic impact will be
discussed in the methodology section below.
Taxes on Land and Buildings

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Property tax is the largest single source of local revenue. Property taxes raised $253
billion in revenue for the City and County of Denver in 2001 and accounted for almost half of
the revenues of local governments (Gruber, 2005). Because buildings must be produced and
maintained in order to have value, a tax on building values is a cost of production on the owners’
efforts to create and maintain value in their buildings. Using a net present value calculation, a 1%
or 2% property tax is equivalent to a one-time sales tax on building labor and materials of
between 9% and 17% (Rybeck, 2004).
The other part of the property tax is a tax on the value of land. Land value is determined
by the value of public goods and services. Thus, the value of land reflects the value of public
infrastructure investments that benefit particular locations. As a result, taxes on land values are
often referred to as value-capture taxes, because they return to the public treasury wealth that is
created by public expenditures (Rybeck, 2004).
Transportation investments often affect nearby land values. This investment can choke
off development, pushing new growth to cheaper sites remote from these investments. This
“leapfrog” development creates a demand for infrastructure extension that starts the process over
again. Transportation infrastructure, intended to facilitate development, thus chases it away.
Resulting sprawl strains the transportation, fiscal, and environmental systems upon which
communities rely (Rybeck, 2004).
In addition to taxes on buildings and land, there are additional taxes that figure into the
Return on Investment analysis. The County Treasurer collects real estate tax. This tax is assessed
at 29 percent of the actual value of commercial property. Business owners pay this tax only if
they own the property they operate. Business personal property (BPP) tax is assessed on all
income producing property, including machinery, equipment, furniture, trade fixtures, and signs.

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The City and County of Denver collects the occupational privilege tax (OPT) monthly. It is
levied per employee. Sales tax is imposed on the purchase price paid or charged on retail sales,
leases, or rentals of tangible personal property, and on certain services. Consumer Use Tax is
used to supplement sales tax, and is imposed on tangible personal property that it used, stored, or
consumed within the City and County of Denver. Generally, use tax is used as a complement to
sales tax that is due when Denver sales tax was not collected on retail purchase of taxable
property (City and County of Denver, 2011).
Practical Use of ROI: Budget Prioritizing
In the City and County of Denver, discretionary project needs account for an estimated
15% of capital budget expenditures (approximately $10 million) each year. As a result, many
discretionary capital projects are unfunded because of the lack of capital revenue available. The
City and County must prioritize annual capital funding allocations of existing infrastructure
above new, discretionary projects. Budget and Management, the Mayor’s Office, and City
Council are responsible for identifying funding and selecting projects undertaken within the
funds available. They also identify and develop plans to address critical needs that are not
currently funded. An entity called the Investment Committee recommends which capital
discretionary projects to fund. The Investment Committee takes a broader view of capital
budgeting and attempts to align capital projects with other important City and County initiatives
(City and County of Denver, 2011).
METHODOLOGY
In this section, I will describe the analytic strategy of this study. Following that there is a
description of the data collection and measurement process and a description the analytical

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methods used to examine the data. I will conclude with an examination of ethical implications
and mitigation techniques.
Analytic Strategy
I will conduct this analysis using quantitative measures. The process will involve
extricating data from existing agency records, a process defined as secondary analysis (Maxfield
& Babbie, 2011). Although secondary data eliminate the costs associated with conducting
original research, it requires the cooperation of organizations and staff and leaves researchers
with less control over the data collection process (Maxfield & Babbie, 2011).
I will access reports of tax revenues in the area impacted by the Speer Boulevard Grade
Separation through the City and County of Denver’s Assessor’s Office. I will examine tax
revenue streams of real estate, business personal property, occupational privilege tax (OPT),
sales, and consumer use tax. I will use two steps to modify nominal data to reflect 2012 values. I
will use the 2012 Consumer Price Index estimate from the Colorado Office of State Planning and
Budgeting. I will forecast business, personal property, and real estate taxes using forecasting
methods. The most appropriate approach is exponential smoothing because it will allow me to
assign larger weights to the most recent data. To reflect this trend in the data, I will use a α
(smoothing constant) value of .9, weigh 2011 data at 90 percent, and the average 2008-2010
data, weighted at 10 percent.
Ethics
During this process I will assess potential risk to participants of the study. At this time, I
do not anticipate any physical, psychological, social, economic, or legal harm as a result of
participating in this study. I will not suppress, falsify, or invent findings to meet the researcher’s

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or an audience’s needs. In the process of writing and disseminating research findings, I will not
use language or words that are biased against persons based on gender, sexual orientation, racial
or ethnic groups, disability, or age.
Findings
Table 1 summarizes the incentives offered by the OED between 2008 and 2011.
Taxpayer names were left off at the request of the Assessor’s Office.
TABLE 1: City and County of Denver: Business Incentive Contracts 2008-2011
Year Firm Retention/
Recruitment
Total
Incentive
Awarded ($)
Relocation
Incentive ($)
Job Creation
Incentive ($)
Job
Retention
Incentive
($)
Expansion
Incentive($)
2008 1 Retention 963,000 600,000 363,000
2010 2 Retention 330,000 180,000 150,000
2010 3 Recruitment 100,000 50,000 50,000
2010 4 Recruitment 455,000 50,000 405,000
2011 5 Recruitment 850,000 250,000 600,000
2011 6 Recruitment 155,000 40,000 115,000
2011 7 Recruitment 30,000 30,000
OED contracts are written with one of two intentions: retention or recruitment. Retention
contracts incentivize a current Denver business to stay in the City and to grow and expand.
Incentives are awarded for job creation, job retention, and/or facility expansion. Recruitment
contracts are offered to bring new businesses into the City; both relocation and job creation
incentives are put forward. Job creation and job retention incentives are awarded on a per
employee basis. Both the incentive amount per employee and the maximum level awarded vary
by contract. The OED and the Assessor’s Office use OPT records to track and validate the firms’
employment levels.
Return on Investment

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Table 2 summarizes the aggregate revenue collected and incentives awarded per year
after adjustments for inflation. All numbers reflect 2012 prices. Inflation adjustments were made
based on Denver-Greeley-Boulder CPI values. The incentive value in 2008 reflects one retention
contract, the amount in 2010 is the sum of two recruitment incentives and one retention
transaction, and the 2011 incentive value is comprised of three recruitment contracts. 2012 tax
information was forecasted: OPT and Sales/Use values were extrapolated from data collected
through April; business personal property and real estate were forecasted utilizing previous
years’ data.
TABLE 2: Total Incentives Awarded and Revenue Collected By Year
Year Incentives
Awarded ($)
Tax Revenue ($) TOTAL Tax
Revenue ($)
OPT Sales/Use BPP RE
2008 1,039,953 31,483 225,554 769,281 205 1,026,524
2009 32,916 119,038 879,541 212 1,031,707
2010 944,276 71,047 429,927 1,265,488 212 2,071,198
2011 1,065,015 80,104 319,822 2,117,641 156 2,517,723
2012* 104,784 325,314 2,005,863 160 2,486,121
TOTAL
S
3,094,244 320,334 1,419,656 7,392,338 945 9,133,272
*2012 values are forecasted
Between 2008 and 2011, seven incentive contracts were awarded totaling close to $3.1
million. Revenues collected by the City of Denver from the firms to which these incentives were
tendered have exceeded $9.1 million. The largest portion (81 percent) of revenue is derived from
the business personal property tax, with sales and use comprising 16 percent of the revenues, and
OPT and real estate combining for the remaining 3 percent.
Table 3 illustrates the ROI on these incentives at discount rates of 2, 3, and 4 percent.
TABLE 3: Return on Investment in 2012
Discount Rate Total Incentive Value ($) Total Tax Revenue ($) ROI (Revenue/Cost)
2 3,194,419 9,415,070 295%

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3 3,269,224 9,559,445 292%
4 3,345,543 9,706,178 290%
ROI was calculated by dividing the discounted total returns (the tax revenues) by the
discounted total costs (incentive amounts). At a two percent discount rate, the ROI is equal to
295 percent; at a three percent discount rate, ROI is at 292 percent; and at a four percent discount
rate, ROI is equal to 290 percent. These findings indicate that for every one dollar invested in
business incentives over the 2008 to 2011 time period, by 2012, the City has received close to
three dollars in return.
Discussion
The findings of this report indicate that the City and County of Denver has received a
substantial positive return on investment for its business incentives awarded. The average ROI at
discount rates of 2, 3, and 4 percent is 292 percent. For every dollar expended through the City’s
general fund by OED on incentivizing private businesses, the municipality has received close to
three dollars in tax revenue in return. Of note, 81 percent of the portfolio’s tax revenue comes
from business personal property taxes collected from these firms.
The business incentive fund (BIF) also fulfills the OED’s JumpStart 2012 policy
objectives of business recruitment and business retention, and the fund aligns with the Mayor’s
priority of job creation. Current OED BIF evaluation focuses primarily on job creation, but also
addresses subsequent private capital investment and a general increase in the City’s tax base. To
ensure that businesses realize their pledged obligations, the OED includes clawback measures,
using OPT filings to validate the number of new jobs reported by incentivized firms. The
contracts also designate a minimum lease agreement, and outline limits for the number of
employees incentivized and the length of the firm’s period of eligibility to collect incentives.

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Limitations of Research
This method of measuring ROI makes the assumption that in the absence of these
incentives, firms would have either left Denver (retention contracts) or relocated elsewhere
(relocation contracts), and therefore presents the best case scenario ROI. In the absence of these
incentives, this analysis assumes that no comparable businesses would take their place without
similar government intervention; in other words, this model presents findings that assume that
the businesses incentivized fill a niche that market forces would not and could not have
otherwise provided in the given time period.
Although it is impossible to determine the likelihood that firms would have left or
relocated elsewhere, it is important to address this uncertainty and to provide an ROI that takes
this asymmetry of information into account. Table 5 illustrates how the probability of firms
relocating or staying absent the incentives affects the City’s ROI.
TABLE 5: ROI Adjusted for Uncertainty 3% DiscountRate
Likelihood of Relocation/Retention
Absent the Incentive
Revenue Attributable to
INCENTIVES ($)
Cost = Incentive
Awarded ($)
ROI
100% 0 3,269,224 0%
90% 955,945 3,269,224 29%
80% 1,911,889 3,269,224 58%
70% 2,867,834 3,269,224 88%
60% 3,823,778 3,269,224 117%
50% 4,779,723 3,269,224 146%
40% 5,735,667 3,269,224 175%
30% 6,691,612 3,269,224 205%
20% 7,647,556 3,269,224 234%
10% 8,603,501 3,269,224 263%
0% 9,559,445 3,269,224 292%
Return on investment increases as firms’ location choices become more contingent upon
the incentives awarded. As the probability increases that firms would have located in Denver
regardless of the incentive awarded, the return to the city attributable to the incentives declines.

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This finding implies that the City achieves a greater return on investment when it incentivizes
firms least likely to choose Denver absent any subsidies offered. However, it is important to keep
in mind that the companies that require the most persuasion and financing to relocate are often
also the first companies to leave (Branham, 2011). If a firm’s decision is entirely contingent on
the financing awarded, then that firm is likely more apt to move again when presented with
another competitive offer. When making these investments, therefore, municipalities must find a
balance; they will see greater returns from firms that heavily weigh incentives in their decision
making, but should not incent businesses that decide solely on the size of the subsidy offered.
Overall, analysis was restricted because of the privacy limitations that prevented the
researcher from accessing sales and use tax information on an individual firm basis. Without the
ability to distinguish each firm’s contribution to the sales and use tax stream from the aggregate
sum, overall ROI could be determined only on the portfolio of firms as a whole. This limitation
is noteworthy because the incentives themselves vary significantly in their size, objectives,
obligations, and industries. It would have been beneficial to distinguish and compare ROIs
between types of firms, neighborhoods, recruitment versus retention, and other defining
characteristics.
Assumptions also limited the analysis. First, the research assumed that all incentives were
paid in full and in the year that they were offered. Working and collaborating with OED’s
accounting department to track and record the exact payment amounts and timing would result in
a more exact ROI analysis. Most importantly, the analysis assumed that the firms incentivized
would have chosen to leave Denver or relocate elsewhere in the absence of the awarded
subsidies. This assumption does not take into account the likelihood that firms would have
stayed or moved here absent the payments awarded. The research also fails to account for the

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possibility that a new firm would have naturally taken the place of these incentivized firms in
their absence. It is possible that the revenue streams would have been replaced by alternate firms
without government intervention.
Recommendations
The first recommendation is to give OED access to pertinent tax information. This would
allow the agency to more accurately measure the City’s ROI from incentives offered. One
possibility for working around the privacy restrictions would be for the business to grant access
to tax information for the OED in the incentive contract itself. By accepting the terms of the
contract, therefore, the business would allow the OED to access its relevant tax payment records.
This would allow for a more thorough analysis by OED, and would also serve to increase
transparency in the transaction. Another option would be to increase collaboration and
communication with the Department of Finance in accessing and tracking this information.
A second recommendation is to incorporate ROI into a larger economic impact report.
Because the BIF fulfills other important policy objectives, it is imperative to combine these
analyses into a comprehensive and regular evaluation. The BIF should not be judged solely on its
return to the City, but the ROI is an important and substantial piece of the overall justification,
and should be reviewed annually. Contracts should be analyzed and evaluated both individually
and collectively as a portfolio. A complete analysis will also include data on job creation, job
quality, private capital invested, and an analysis of the current business environment.
A third recommendation is to analyze and look at recruitment and retention incentives as
two distinct programs. Business recruitment and retention are two separate pillars of OED’s
JumpStart2012 and ultimately serve different policy objectives. Additionally, the probability that

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existing firms leave the City is likely significantly different than the likelihood that firms looking
to relocate go elsewhere, and this disparity has a significant impact on the City’s realized ROI.
Implications for Future Research
The significant positive return illustrated by this analysis provides considerable
justification for the City’s expenditure on business incentives. This justification, however, would
be strengthened if it compared positively to the ROI of other economic development activities. In
the future, therefore, similar studies should be conducted on other economic development
projects operated by OED and other pertinent city agencies. A comparison and analysis of the
returns generated by these activities would be beneficial in directing future policy decisions.
In addition, the Mayor has proposed a measure for the November 2012 ballot that would
both eliminate TABOR restrictions and exempt new equipment purchases from the business
personal property tax. Both of these items will have a significant impact on the BIF’s ROI.
Lifting TABOR constraints will provide the City with a substantial increase in revenue, but it
will also add significant costs to businesses and make Denver a relatively less attractive locale to
in which to operate. Exempting new equipment from the business personal property tax will also
gauge the fund’s most significant (82 percent) revenue stream. If the measure passes, the City
will need to carefully consider and analyze its implications when making future BIF decisions.
Denver should also continue to assess and market its competitive advantages as a City. It
is imperative for the municipality to understand both its strengths and weaknesses as an
environment to do business, and to identify and pursue opportunities that coincide with the assets
that if offers: a highly educated workforce, proximity to an international airport, a central
national location, substantial transportation infrastructure, and a high quality of life.
Conclusion

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Although literature on business incentives questions the nationwide impact of these
subsidies, this analysis has supported the effectiveness of business incentives as a tool to
generate revenue and create employment opportunities for the City of Denver and its citizens.
For every dollar offered by the City as an incentive for a firm to either stay in or move to Denver
between 2008 and 2011, the City received close to three dollars in revenue in return in 2012. The
BIF also satisfies OED strategic and policy goals of business retention and recruitment, as well
as the Mayor’s job creation priority. Overall, the BIF can be justified on both economic and
political levels.
To more effectively and efficiently administer the program, it is recommended that the
OED gain access to all relevant tax information pertinent to incentivized firms, through either
contract stipulations or collaboration with the Department of Finance. It is also suggested that the
ROI be incorporated into existing OED BIF analyses and that evaluations be conducted annually
on both the individual incentives and the portfolio as a whole. Lastly, it is recommended that
retention and relocation efforts are evaluated and assessed separately; because business retention
and business recruitment are two distinct strategic objectives, the returns on and products of
these activities should be looked at discretely.
Overall, the City of Denver should carefully monitor and assess its use of business
incentives, and take care to align the program with OED and City objectives. Return on
investment is an essential component of the program’s evaluation, but should be judged in
relation to other economic development alternatives, and must be evaluated in light of the City’s
larger business and political contexts. Denver’s business climate, tax structure, and competitor’s
offerings are continually changing and evolving; BIF strategy must constantly adapt to these
changing circumstances. Nonetheless, this study on the return the of investment of business

21. 21
incentive contracts conferred between 2008 and 2011 indicates a 292 percent return on
investment in 2012; a sizable yield that supports continued use of this economic development
activity in the future.
Works Cited
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impacts of economic development projects. Government Finance Review, 24(3), 18.
Burroughs, D., Jiang, S.-S., & Henson, H. (1994). Depressing Traffic Top-Down. Civil
Engineering, 62-64.
City and County of Denver. (2011). Capital Improvement Program Six-Year Capital
Improvement Plan. Denver, CO: City and County of Denver.
Feibel, B. J. (2003). Investment Performance Measurement. Hoboken, New Jersey: John Wiley
& Sons, Inc.
Felsenstein, D., Persky, J., & Wiewel, W. (1995). Are subsidies worth it?: How to calculate
costs and benefits of business incentives. Government Finance Review, 11(5), 23.
Gruber, J. (2005). Public Finance and Public Policy. New York: Worth Publishers.
Maxfield, M. G., & Babbie, E. R. (2011). Research methods for criminal justice and criminology
(6th ed.). Belmont, CA: Wadsworth.
Rybeck, R. (2004). Using Value Capture to Finance Infrastructure and Encourage Compact
Development. Public Works Management & Policy, 249-60.