How do you disrupt the power structure inherent in CBA negotiations?

My latest research just published online at the Journal of Urban Affairs

ABSTRACT: Community empowerment movements challenge local government administrators and planners to emphasize people instead of development profits in the planning process. Community Benefits Agreements (CBAs) are popular tools to advance this objective. Executed by and between local governments, communities, and project developers, CBAs detail how economic benefits from new development are shared with residents. One question understudied in the literature is how does a community know if it received an equitable distribution in a CBA? In this case study of a new $1.6 billion satellite campus for the University of California, documents in and out of the public domain are analyzed to determine what economic benefits could be shared with the community, what portion was disclosed to the community, and what portion of the benefits were included in the CBA. A key recommendation from the findings is to build a CBA metric that local governments and communities can use to establish an early target value for benefits before negotiations with project proponents.

Bill Farley (2023) Disrupting the knowledge and power imbalance in Community Benefits Agreement negotiations: Lessons from the Aggie Square development in Sacramento, California, Journal of Urban Affairs, DOI: 10.1080/07352166.2022.2155527

Link to the JUA article.

The accepted manuscript is available here.

If you don’t have access to JUA and need a copy of the published article send me an email.

Placing economic impact claims in context

Large and small private investors seeking public subsidies routinely turn to “Economic Impact” reports to make their case. The missing piece in virtually all of these reports is the size of the local economy where the project is situated. This is purposeful to encourage active imaginations to place a high priority on the proponents project.

To mitigate the irrational exuberance which can be whipped up with these reports, the size of the local economy (and recent organic growth) must be placed next to the proponents claims. This important contextual information can be derived from readily available data on aggregate income published online by the US Census Bureau. Here are the 7 steps to find the size of your local economy for a given year (we are in search of table B19025.

  1. Go to the advanced search function at
  2. On the menu on the left hand side of the screen select Topics>
  3. Select Income and Poverty
  4. Then select “Income and Earnings” (at the top of the list)
  5. Check the box for “Income (Households, Families, Individuals)
  6. On the menu on the left side of the screen select Geographies>
  7. There will be nine boxes with each representing a different type of geography. Select the “Metropolitan Statistical Area” option. It will take some time to load. Scroll down and “check” the box next to your area. Note: I recommend MSAs because most economic reports address regional economies which span multiple jurisdictions.
  8. Finally, select the year.

On the right hand side of your screen there will be a list of tables which provide data that meet the filters you selected. If you select the “x” to close out your “Select Years” filter the list will fill the center of your screen. Scroll down to find table B19025: AGGREGATE HOUSEHOLD INCOME IN THE PAST 12 MONTHS. On the example below it was about 35 tables down the list.

You can change the years to see the annual growth of the economy.

Example #1: City of Detroit lands the NFL Draft after five years of trying

The claim is made that the event has brought $100 million in economic activity to other cities. No mention is made of the numerator – the size of the Detroit economy.

The aggregate income for the Detroit-Warren-Dearborn MSA in 2020 was $150 billion. This is up from $125 billion in 2015. So, to place the $100 million impact of the NFL Draft in context, it represents up to 0.67% in activity, while organic growth in the economy averaged four percent (4.0%) over a five year period.

Example #2: Richmond garners $161 million from UCI Cycling Race

Chmura is a well-connected economic consulting group that prepares reports on the economic impacts of public and private activities. They prepared economic impact reports on VCU’s contribution to downtown Richmond, and in one instance, a UCI cycling competition (aka Richmond 2015). The report on the cycling event indicated an economic impact of $161 million for the week-long event (which cost the city $20 million to secure).

No mention of a numerator, which in this case, is a $39.7 billion regional economy in 2015, up from $35.3 billion in 2010 – an organic increase of $4.4 billion over five years. The UCI event represented less than five tenths of one percent in potential economic activity.

But that footnote.

Chmura, whose president served on VCU’s Business School Advisory Board at the time, included the following statement in their economic impact report on the UCI event:

This estimate ..only captures the economic impact directly associated with Richmond 2015 participants and spectators. It does not take into consideration other factors that may have affected local businesses. For example, Virginia Commonwealth University cancelled its classes for a week, and some students left Richmond. Those factors are beyond the control of the Richmond 2015 organizers and were not incorporated into this analysis.

Chmura pretended that VCU did not closed its campus for two weeks in anticipation of the negative impacts of the event on campus life. But, having assessed the economic impact of VCU earlier, they could easily have looked at that study and suggested an offset of $50 million in economic activity for the VCU closure (this would produce a result significantly less than what was used to sell the city’s investment in the race).

A 10% Rule for Community Benefits Agreement Negotiations

I recently completed a case study of the Aggie Square project sponsored by the University of California, Davis next to a historic black community. The objective of the study was to answer a couple questions on how to measure and distribute economic benefits. My intended audience for the article was urban planners who have been asked to consider social equity in the planning process – but have not received objective standards from which to address this concern. In this article I lay out a proposed framework to measure the economic benefits of a project and suggest a pragmatic approach to identifying the portion of these benefits which could be shared. Then, for the case at hand, I measure what benefits were disclosed to the public and the amount that was eventually shared with the community. I’m looking forward to feedback on this approach from the peer-review process – and to eventually finding a home to publish this case study.

In the meantime, I’d like to share some of the noise I encountered during this case which often distracted me for short periods of time from my research questions. This is despite the sound advice from my methods professor who implored us to keep the questions on a sticky note on our computer screen.  In general terms, the noise that distracted me emanated from various strategic communications tactics employed by university communication specialists to promote the project and effectively hoard economic benefits for the university and its partners.  First, it was the publication of an economic impact report that touted immense benefits in raw numbers, while ignoring the relative insignificance of the impact in relative terms. Second, it was a series of made-up awards exchanged between city and university leaders and organizations driven by membership fees, to tout the excellence of all parties involved in driving the project. Finally, there were several instances where I documented leaders misrepresenting the project to their governing boards.

These noises were particularly irritating since I was attempting to test a framework which would give planners a tool to recommend a practical division of economic benefits – while seeing that the barrage of propaganda swirling around the case would make it professional suicide for a planner to suggest the tool.  I made note of this strategic noise during my study and circled back to its influence after I completed my findings and answered my initial research questions. Then, while drafting my conclusions I struggled with how to work around the professional suicide dilemma until I couldn’t. This led me to switch my audience for the article from planners to community activists.

My findings were that, for the first phase of the Aggie Square project, about $80 million in economic benefits could be shared with the community, approximately 60% of these benefits were disclosed in the public review process, and $10 million was eventually shared with the community. My recommendations shifted from suggesting how planners could be more transparent and propose more equitable splits, to how community activists could cut through the strategic noise and negotiate a better deal. I suggest activists use 10% of construction costs as a starting point to place a value on community benefits negotiations (communities netted a little over 1% from the Aggie Square Project). This is a proxy which cuts through the strategic noise and lack of transparency by planners and their leaders. Construction costs are readily available since they are the basis for the economic impact propaganda which often precede project advocacy. I worked backwards from my findings to peg the percentage at 10%.

Other recommendations that I suggest for community activists are to 1) Address misleading economic impact claims quickly by providing the media with the size of the regional economy – this will shrink the perception of the impact dramatically, 2) Fight upfront for a public interest model that provides communities funding to hire consultants to analyze and challenge claims of economic impacts and public subsidy requests by developers, and 3) If housing assistance is considered for part of the community benefits, ask for homeownership opportunities – not the opportunity to build equity for a rental housing developers.

More information on this current project of mine can be found under the Current Project tab. Also, I have a shorter version of this paper under my publications tab. In this draft essay I take a different slant on the study, comparing patterns of the planning process with Jim Crow era tactics.

The Just Host: Addressing the wage structure problem in the tourism industry

Since the early 1990’s, tourism development has been promoted to replace employment lost to downsizing, outsourcing and automation in both urban and rural America. These efforts are actively supported by state and local chambers of commerce. However, despite the enthusiasm for tourism within city halls and business membership organizations, planning theorists have expressed concerns about the wage structure of the industry. Specifically, given the significant public investment in the industry, planners are being asked by some theorists to consider the distribution of economic benefits between labor and capital.

This dissertation explores this issue and concludes with a study focused on the origins and distribution of public economic benefits – areas that have received little attention to date. Using Power to Tax theory as a theoretical framework a strong relationship was established between hotel revenue per capita (a proxy for hotel taxes) and local government wages per capita. The study found no association between natural amenities and local government wages per capita, independent of the path through hotel revenue per capita. These findings suggest local government officials are enriching themselves by commodifying their commons (natural amenities) through the low-wage tourism industry.

Recommendations are made to Fainstein’s Just City planning model to advance a more equitable distribution of public economic benefits derived from natural amenities and the local residents toiling in the tourism industry.

Find the full dissertation here:

Self Report Accuracy in Local Economic Development Programs

Published in the November, 2020 issue of Economic Development Quarterly

Abstract: Local economic development programs are primarily aimed at increasing employment and tax revenues. Data on these programs are collected through self-report surveys conducted by the International City Managers Association and others. This study evaluates predictors of accurate self-reporting. Using agency theory as a theoretical framework, the study measures the quantity of internal reporting components and the quality of financial reporting and evaluates how these are associated with accurate self-reporting. As a control, the condition of the local economy is also evaluated. The findings indicate a statistically significant relationship between the quality of financial reporting and the strength of a local economy with accurate self-reporting. Recommendations to improve research in this area are for the Government Finance Officers Association and the International City Managers Association to work together, with the former creating standards for reporting on local economic development programs and the latter aligning its survey with these standards.

Community Wealth

I entered the Ph.D. program at VCU with an interest in studying the high-value (taxes)/low-wage industries that are favorites of politicians, city administrators and local economic development professionals (full disclosure: I was an economic development professional in a prior life). Before and during the program I focused much of my research, conference papers, blog posts, journal articles and dissertation on one such industry – the accommodation subsector. This was a comfortable place to start, as I had extensive public and private sector experience modeling that private and public benefits from the industry – including the real estate (asset) valuation component. As with retail development, the other big high-value/low-wage industry, local governments make somewhat of a Faustian bargain with tourism businesses to boost tax revenue, while allowing their residents working in the industry to fall into a tenuous safety net operated by others (Federal safety net programs and charity).

The questionable high-value/low-wage “economic development” drive by local governments led me to another area of interest – a consequence of relegating local business development to the low-value/low-wage service sectors.  This relegation manufactured a false dilemma between boosting wages in the tourism and retail sectors and promoting local businesses. The supposed dilemma is that you cannot raise wages on big retail and tourism businesses, which can afford to do so, without destroying the local businesses that do not have access to the same resources. Countering this false dilemma is the primary “so-what” element of my overall research project. I address this false dilemma, including the pretext, through a Community Wealth planning model.

This is my first version of my Community Wealth planning model.  I’m synthesizing my previous research, and current understanding of the literature, to create this initial model. Despite being a boomer I’m still a young scholar, and I recognize I have more to learn and assimilate as I pursue this research project. The purpose of this model is to situate planning and economic development decision-making in the proper context. I found in my role as a practitioner and as a Ph.D. student, that there was inaccurate or incomplete information used by planners and local government officials in four specific areas: 1) an understanding of the primary sources of community wealth, 2) how community wealth is accumulated and either retained or lost by the community, 3) how community wealth is distributed, and 4) how community wealth is measured.  None of these aspects is new, but in my model, I establish the relationship between each, and in doing so, can identify solutions to addressing the false dilemma that pits small businesses against living wages for their employees.

The diagram below illustrates the current version of my model and the elements of each of the four dimensions identified above. I will detail each of these elements in future posts and will revise and update the model as my thinking evolves. I hope to keep the model in single digits. The updates will be sporadic as I shift to journal articles and conference paper deadlines.

Blending Powers: Hamilton, FDR and the backlash that shaped the modern Congress

Now available in the January edition of the Journal of Policy History (Volume 33, Issue 1).

Abstract: President Franklin Delano Roosevelt shaped the role of the modern president in part with his relentless pursuit of grand policies and his ability to marshal historic legislation through Congress. In this article, I focus on one legislative tactic employed by FDR that has received little attention—the detailing of Executive Branch staff to select Senate committees. This tactic, effectively a blending of legislative powers, was used to implement FDR’s ambitious postwar domestic agenda as detailed in his Second Bill of Rights. I find that the tactic, used late in FDR’s presidency, was moderately effective, served as a substitute for the personal energy FDR applied to the presidency in his first term, and created a backlash that contributed to the adoption of the Legislative Reform Act of 1946. With these findings I conclude that FDR deserves credit as a transitionary figure for the modernity of Congress, as well as the presidency.

You can read the “Author’s Accepted Manuscript” here.

Community Wealth Shapes Local Economic Development Programs

Local economic development priorities say a lot about the wealth of a community. Municipalities with strong economies are less interested in jobs than those with a weak economy and are more likely to pursue environmental sustainability and social equity goals. Municipalities with weak economies focus primarily on the basics; jobs and tax revenues. The results, however, are the same; while there are statistically significant correlations between economic development programs and self-reported measures of success, when actual results are substituted, the statistical significance disappears. 

In this article, using a data set from the International City Manager’s Association (ICMA),  I focus on the alignment of economic conditions (barriers), local economic development priorities, programs and self-reported results.  This is the first exploratory study to test connections across the entire continuum from planning to results. Previous studies have focused only on a portion of this continuum.

Municipalities are the focus of this inquiry because of the consistency of their organization, roles, and responsibilities. Counties, special districts, and non-profits can be organized in a number of ways, making it difficult to compare survey results.  The complete ICMA survey instrument included 25 questions. Twenty-two of these questions were close-ended with a predetermined set of multiple choice answers. The number of multiple choice options in these close-ended questions ranged from 2 to 32. The questions involved planning (motivation, barriers, priorities), programs (tools and incentives), and claims of success. The menu of priorities included traditional (creating jobs, increasing the tax base) and Type II programming (quality of life, environmental sustainability, and social equity) . A summary of the responses from municipalities on priorities and claims of success is provided in Table 1. The priorities of municipalities in the survey are fairly consistent, with over 85% indicating that increasing jobs and the local tax base, along with improving quality of life are priorities. The responses are more varied for environmental sustainability (42%), and social equity (25%). As for success in meeting these priorities, just over 89% of municipalities claim some level of success with job growth, tax growth, improvement in the quality of life, and progress towards environmental sustainability. Claims of success on social equity are substantially less, dropping to approximately 76%.

Table 1

Organizing the Data for Analysis
Prior to analysis, the data was organized into four general categories consistent with the structure of the survey; 1) planning (motivation/ barriers), 2) priorities, 3) programs (tools/incentives), and 4) reporting. Measures for planning (motivation/barriers) and programs (tools/incentives) were developed by combining multiple responses through factor analysis. Priorities and reporting were based on individual responses from the survey. The factor analysis started with 79 items relating to motivation (10), barriers (21), and tools and incentives (48). The items associated with motivation, barriers and tools and incentives, all measured on four-point Likert scales, were reduced through factor analysis to 13 measures and tested for internal consistency (α).

The measures developed for the motivation category are “progressive agenda” (α: .725), constructed with four items, and “organizational change” (α: .698), constructed with three items (Table 2). Four measures were created for barriers to success using twelve items (3 for each measure). These measures are “development constraints” (α: .656), “weak economy” (α:.660), “strong economy” (α:.661), and “labor constraints” (α:.575) (Table 3). Finally, seven measures were created for tools and incentives using 24 items. These measures are “direct business support” (α:.792), “sustainability programs” (α:.732), “marketing” (α:.731), “finance” (α:.719), “investment” (α: .681), “contributions” (α: .664), and “assistance” (α:.703) (Table 4). A consolidated description of all the measures is provided in Table 5.

Table 2

Table 3

Table 4

Table 5

Testing Program Alignment
The next step to explore the survey data was to test the relationships between 1) programs (motivation/barriers) and priorities, 2) priorities and programs (tools/incentives),  3) programs (tools/incentives) and 4) reporting. The test between measures are organized along a planning-programming-reporting continuum (Figure 1).

Figure 1

The first set of measures, representing motivation and barriers, was tested for correlation with priorities established by municipalities using binomial logistic regression. All five measures were grouped and tested against the five priorities. Table 6 provides the details of the analysis for all five models. In summary, all five models were found to be, overall, statistically significant. In terms of relationships between specific measures and priorities, a significant positive relationship was found between an economy with labor constraints (antecedent) and prioritizing job growth (OR 3.117), and between a progressive agenda (antecedent)` and prioritizing quality of life (OR 2.061), environmental sustainability (OR 4.143) and social equity (OR 3.698). A significant negative relationship was identified between a strong economy (OR .563) and development constraints (OR .510) in establishing job growth as a priority, and between a weak economy and establishing environmental sustainability (OR.641) or quality of life as a priority (OR .627). The organizational change measure had no significant connection to any of the five priorities.

Table 6

The next step was to test the five priorities with the seven programmatic constructs (tools and incentives). An Independent-sample T-Test was conducted for all possible pairings of priorities and tools and incentives. The results of this analysis are displayed in Table 7. Twenty-two of a possible thirty-five relationships were found to be statistically significant (p <.05). Sixteen of these, using Cohen’s d, had a small effect (>.20), and five had a medium effect (>.50). The strongest relationships were job growth (priority/antecedent) with direct support (d:.84), sustainability (d:.50) and finance (d:.60); environmental sustainability (priority/antecedent) with sustainability (d:.69); and social equity (priority/antecedent) with sustainability (d:.77).

Table 7
The final step in exploring the connections between measures was to analyze the relationship between program constructs (tools and incentives) and claims of success. For this analysis, a binary dummy variable was created to measure success with a response of “none” being a “0” and responses of “somewhat successful” and “very successful” being a “1”. Binomial logistic regression was then used to test the relationship between the tools and incentives measures (collectively) and the binary success variables for each of the five priorities. The results of the five models are presented in Table 8. All five models were found to be statistically significant. In terms of relationships between specific program measures and success, a statistically significant positive relationship was found between seven measures and claim of success. The investment measure was strongly associated with success with job growth (OR 1.824), tax growth (OR 2.761), quality of life (OR 3.231) and environmental sustainability (OR 2.616). Assistance was strongly associated with quality of life success (OR 2.046), sustainability was associated with success in environmental sustainability (OR 3.893) and social equity (OR 1.899).

Table 8

Figure 2 provides a diagram illustrating the statistically significant relationships for individual components of the binomial logistic models, and moderate effects (Cohen’s d) from the t-tests.

Figure 2

The above analysis of the ICMA data set reveals some internal connectivity between motivation, priorities, and organization (programs) consistent with past research. Municipalities with strong economies are less interested in jobs than those with a weak economy. And municipalities with weak economies are not likely to establish environmental sustainability as a priority. The pattern of data appears logical in this phase of the study – and consistent with past studies (Reese & Fasenfest, 2004, p. 12; Warner & Zheng, 2013). Weak economies focus on the basics, and progressive municipalities pursue environmental sustainability and social equity. The association of public investment (Investment) with results in several categories likely reflects the ability of the municipality to tie direct expenditures with tangible results through operating or capital budget processes.

This exploratory study reveals that local economic development priorities are as unique as the municipality where they are set. Unlike other disciplines in the public sector, finding common ground is difficult. Police departments have crime rates, fire departments have response times, and public works departments have common unit costs that are measurable and repeatable. Local economic development priorities and programs are a reflection of the wealth of a community and the struggle to build or maintain that wealth. Municipalities with strong economies are less interested in jobs than those with a weak economy and are more likely to pursue environmental sustainability and social equity goals. Municipalities with weak economies focus primarily on the basics; jobs and tax revenues. The results, however, are the same; while there are statistically significant correlations between economic development programs and self-reported measures of success, when actual results are substituted, the statistical significance disappears. 

About the author: Bill Farley has 30 years of experience in local economic and community development as a public official, entrepreneur and corporate executive. He is a former instructor of public policy and public finance at the University of Southern California Price School of Public Policy. He is currently advising organizations on local economic policy while completing a PhD in Public Policy and Administration at Virginia Commonwealth University. 

A Survey of Local Economic Metrics in Virginia

Local governments are a focus of economic planning ­– with varying degrees of state oversight. These entities, cities, counties, and unincorporated communities, are a logical focal point in part because they produce the most read and debated documents in government (annual operating budgets, long-term capital expenditure plans, financial statements, and general plans). These documents guide local officials, individuals, and community organizations on policies, programs and land-use decisions that shape the character of cities and counties. Interspersed in these documents are microeconomic policies that can play a significant role in defining the economic vitality of these communities.

To assess the current state of microeconomic policy-making and planning at the local level, I compared policy documents of the five largest cities in Virginia; Virginia Beach, Norfolk, Chesapeake, Richmond, and Newport News, along with the policy documents of a regional planning entity, the Hampton Roads Planning District Commission.

The documents reviewed for this analysis were the:

  • Virginia Beach Operating Budget
  • Virginia Beach Community Data Report
  • Norfolk City Operating Budget Message
  • Norfolk Demographic Report
  • Norfolk Economic Indicators
  • Chesapeake Operating Budget
  • Richmond Operating Budget
  • Richmond City-wide Service Evaluation[
  • Newport News Operating Budget
  • Hampton Roads Planning Development Council Regional Economic Development Strategy
  • Hampton Roads Planning Development Council Economic Forecast

Forty-one (41) economic measures (e.g., indicators, statistics, goals) from these six entities are entered in individual rows on the left-hand column of the table below (Table 1). Each entity is represented by an individual column to the right of these entries. If the entity uses the measure in the corresponding row, a symbol is provided to indicate if they have time series data (TS), static, or just one year of data (S), and whether or not they compare the data set with other jurisdiction (C).  It is worth noting, that not a single measure is used universally across all jurisdictions. The following measures are the most popular:

  • 5 of 6 entities use unemployment rate, total employed, poverty rates
  • 4 of 6 entities use median household income, per capita income, income by category
  • 3 of 6 entities use labor force by sector, education, public transportation use, taxable sales.

Table 1

In addition to the disparity of economic data used by these jurisdictions, only two, Richmond and Newport News imply that the stated measures were part of their goals. For the rest of the organizations, the information appears to be merely descriptive, and does not tie to any local policies. In fairness to the communities without economic goals, Richmond and Newport News did not provide any evidence that the goals were supported by unique programmed activities, beyond the classic business retention and recruitment efforts. It is worth noting that four of the five communities only use federal poverty level measures to measure lower incomes in their community. Richmond stood alone as the only community to provide a more realistic view of this segment. Richmond consolidated income data to identify the portion of their population earning less than a living wage, a much more accurate picture of the number of people in a community under economic stress, and a critical piece of information for shaping microeconomic policies and income support programs.

A Common Framework for Local Economic Development

Research and coordination of local economic development programs is hampered by this disparate approach to economic metrics. The professional association most likely to establish a common framework for the collection and analysis of microeconomic data is the Government Finance Officers Association (GFOA). This national organization establishes standards for information within an operating budget, and confers a distinguished budgeting award to those jurisdictions that comply with their standards.  Four of the five cities in my sample set have qualified for the GFOA distinguished budgeting award for over 21 years.

The current GFOA standard for economic data reveals why there is so much disparity in the data used by municipalities in this sample. The GFOA standard for community data, which is not mandatory for their award program, and the associated evaluation measures are as follows:

Standard: #C3: The document should include statistical and supplemental data that describe the organization, its community, and population.


Is statistical information that defines the community included in the document (e.g., population, composition of population, land area, and average household income)?

Is supplemental information on the local economy included in the document (e.g., major industries, top taxpayers, employment levels, and comparisons to other local communities)?

Unfortunately, the above standard and evaluation criteria do not provide sufficient detail to create a common framework for microeconomic data. Public finance officials should work with their local economic development colleagues to pursue a framework that GFOA could memorialize in their awards programs. This would improve the utility of economic metrics for regional governments, residents and researchers.

About the author: Bill Farley has 30 years of experience in local economic and community development as a public official, entrepreneur and corporate executive. He is a former instructor of public policy and public finance at the University of Southern California Price School of Public Policy. He is currently advising organizations on local economic policy while completing a PhD in Public Policy and Administration at Virginia Commonwealth University. 


Bradley, David. “Comparative Indicators to Other Hampton Road’s Cities,” January 13, 2015.

“City of Richmond Budget,” 2015.

“City of Virginia Beach Budget.” City of Virginia Beach, Welcome to Open Budget, 2016.!/year/default.

“GFOA Detailed Criteria Location Guide: Distinguished Budget Presentation Awards Program.” Government Finance Officers Association, 2016.

“Hampton Roads Regional Economic Development Strategy.” Hampton Roads Regional Planning District, 2015.

Jones, Marcus D. “Norfolk Budget Transmittal,” July 1, 2015.

Lobao, Linda, and Curtis Stofferahn. “The Community Effects of Industrialized Farming: Social Science Research and Challenges to Corporate Farming Laws.” Agriculture and Human Values 25 (2008): 219–40.

“Newport News Operating Budget,” 2016.

“Norfolk Demographic Report.” City of Norfolk, July 2014.

“Norfolk Economic Indicators.” City of Norfolk, September 10, 2015.

“ODU Regional Economic Forecast,” 2015.

“Richmond Citywide Service Efforts and Accomplishments.” Office of the City Auditor, Richmond, Virginia, January 12, 2016.

Rethinking Metrics for Local Economic Development

The unemployment rate is too simplistic a measure to use for gauging the condition of a local economy. It masks the number of workers underemployed and those making less than a living wage. The workers suffering under the current economy are those local governments need to perform at high level.

Every chance I get I’m asking politicians about the metrics they use to evaluate their constituent’s local economy. The answers so far are not surprising. The unemployment rate is almost always the first mentioned. Local government officials lean on this statistic as well. While I was in Virginia taking courses for my PhD, I looked at 40 economic metrics tracked by six local governments in the Virginia Beach metropolitan area. While there was not one metric shared by all six, the unemployment rate was one of the few used by five of the six agencies.

The unemployment rate measures the number of residents who are looking for employment but have not yet succeeded in finding work. This is important information and it is readily available. However, it does not tell us how many working age residents have given up looking, whether residents are employed part-time or full-time, or whether they are making a living wage.  Collecting data on these more nuanced dimensions of employment is more difficult. Even more difficult, however, is trying to reconcile the nuanced and simplistic data when they diverge. Attempting to reconcile nuanced misery with simplistic success rarely advances ones administrative or political career.  So then, what could motivate a local official or politician to venture into advanced measures of local economic health, and what should they measure? I suggest the motivator could be protecting or increasing the local tax base, and the measure should be the living wage gap for residents working on the front-lines of high-tax producing businesses – brick and mortar retail and hotels.

The International City Manager’s Association (ICMA) surveys member organizations on a regular basis to determine local economic development priorities and programs. Increasing taxes is the top priority of municipalities, ahead of jobs, quality of life improvements, environmental sustainability and social equity. Cities employ several strategies to boost tax revenues. Promoting tourism can result in more hotel taxes and encouraging retail development can increase sales tax revenues.  Both sectors, however, face stiff external competition. Hotels face national and international competition and retailers battle numerous regional and on-line competitors. Employers understand the need to have quality employees on the front-lines. Employees working in these high-tax businesses are subjected to rigorous screening and performance standards. They must pass a psychological screening during the hiring process and face continuous job enlargement once on the job. Front desk employees at hotels must also work as custodians and wait staff, and retail cashiers must collect a quota of email addresses from customers while providing outstanding service. The effectiveness of these front-line employees determines the success of the business and the tax revenues generated for the local government. Both business and local government have a stake in the economic health of these front-line employees.

Collecting and synthesizing data to assess the economic health of front-line employees takes a few steps, and there is some estimating necessary in smaller counties and towns. But even if the results are more illustrative than precise, for local governments competing to preserve or expand their tax base, it represents a rare and important intersection of social equity and self-preservation. Only by knowing the economic health of these de facto local ambassadors and tax collectors, can a local government begin a dialogue on policies which could buttress this important segment of every local economy.  There are two measures that I’ll cover in this article. The first is measurement of the gap between actual wages and living wages for front-line employees. The second measure is the percentage of front-line workers making above a living wage.

Determining various measures of the living wage gap in a county requires three data-sets; 1) MIT’s Living Wage data base, 2) the Bureau of Labor Statistics’ (BLS) wage survey, and 3) income data from the Census Bureaus’ American Community Survey (ACS). MIT’s data is available for all counties and most cities. For the examples I’ve include in this article, I’m using data from 22 rural counties in southeast Iowa (Figure 1). I’ll detail the specific steps in a separate technical appendix, but for this article, much like your favorite cooking show, I’ll jump right from the ingredients to the finished product.

Figure 1: Southeast Rural Iowa Counties (Outlined in Red)

Figure 1 Map for Metric.jpg

MIT’s data base provides living wages for several combinations of adults and children. For this article I’ll present a living wage gaps for a single individual and a two-income family with two children. For actual wage data, I’ve selected six front-line classifications in the retail and hotel industries; cashier, retail sales, cook, waitstaff, food production, front desk, and housekeeper. This equals approximately 11% of a local workforce and may account for upwards of 30% of local tax collections. Table 1 provides a chart of the living wages for each county, Table 2 provides wage percentiles for each of the classifications for all southeast Iowa. The wage gap for each classification is calculated by expanding the wage distribution from a first, to a one hundredth percentile, and then using the living wage to determine the collective wage gap, as well as the percentage of employees making more than a living wage. See Figure 2 for an illustration of this calculation.

Table 1

Table 2

Figure 2: Living Wage Gap Example

Figure 1 for Metric Article

For these 22 counties in rural southeast Iowa, with a combined population of 520,000 and a workforce of 250,000, the percentage of workers earning a living wage is highest for retail staff, with 45% to 57% earning a living wage, and lowest for wait staff at between 12% and 22%.  Cumulatively, the wage gap for the selected front-line employees in these 22 counties is $61 million using a single person model, and $271 million using a two adult, two child household model. Table 3 provides a chart of the living wage gaps by county, alongside, for context, per capita income and an aggregate income for all residents of each county.

Table 3

The data collected and synthesized for these living wage metrics reveal significant stress on the front-line employees collecting sales tax and serving visitors to the community. The living wage data here can be used to start a dialog on the potential value of reducing stress on key front-line employees, the stakes for local government pursuing this goal, and the type of public policies which could achieve this end. For most, this would be an uncomfortable conversation, particularly while the unemployment rate is at historical lows. This is because we have been conditioned to equate unemployment with economic health in our communities, but as this data shows, that is not always the case.

My purpose for this article is to encourage local governments to deemphasize the use of unemployment rates to measure local economic development, present sub-living wages in a new light and to identify a logical coalition of business and government to address the living wage issue for specific sectors. This is clearly a radical notion and the policy options to pursue such a course are largely uncharted. For that reason, I want to conclude with some cautionary advice and then follow with a few ideas on specific and practical program options. My cautionary advice is this, first, I would be careful to develop separate solutions for national corporations and local businesses. The nationalization of our economy has given substantial advantages to national retailers. Also, the profits of national retailers do not stay in the community like local businesses. A two-class solutions needs to be considered – one for national corporations and one for local businesses.  Second, I would set a long horizon to implement changes, allowing programs to be eased in during cycles where there is the least impact. This is how private investors build wealth, and the same tactic can be used by disciplined local governments. Third, I would develop separate programs for retail businesses and hotel operations. Hotels have an equity component that retail owners do not. Put another way, retail buildings are disposable and little value that can contribute to absorbing program interventions, whereas hotels have significant equity to contribute to a desired outcome. The frailty of retail is evident in the epidemic of business closings and building vacancies because of increasing on-line sales. The resilience of hotels is evident in rarity of permanent closings.

The program options I recommend to bolster the economic health of private employees on the front-line of local revenue collections are based on other traditional economic development programs. Local governments offer tax rebates, allocate new tax revenues and contribute public infrastructure improvements in return for achieving specific economic outcomes. All these options could be used in public-private partnership to develop and enhance the economic security of the front-line workforce. A targeted living wage ordinance, coupled with the above tax sharing programs, could also be employed to fairly distribute the burden of economic security for front-line employees.  The public share of the burden can be adjusted based on the class (national or local) and type of business (retail or hotel).  National corporations and hotel properties can shoulder a greater share of the burden.

Local governments have a stake in the economic security of residents, and particularly those on the front-lines of businesses producing tax revenues.  The unemployment rate has little utility for assessing the economic health of these residents. Additional data and analysis are necessary to make a true assessment of wages for these front-line employees, and to create a foundation for exploring program options to address this important aspect of local economic development. Raising tax revenues is the top priority of local economic development programs across the county, and the active engagement of local governments in advancing economic security of key employees through public-private partnerships, using traditional tax sharing schemes, is strategy worth exploring.

About the author: Bill Farley has 30 years of experience in local economic and community development as a public official, entrepreneur and corporate executive. He is a former instructor of public policy and public finance at the University of Southern California Price School of Public Policy. He is currently advising organizations on local economic policy while completing a PhD in Public Policy and Administration at Virginia Commonwealth University.