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.

Evaluation:

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. 

Bibliography

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. http://budgetdata.vbgov.com/#!/year/default.

“GFOA Detailed Criteria Location Guide: Distinguished Budget Presentation Awards Program.” Government Finance Officers Association, 2016. http://www.gfoa.org/sites/default/files/BudgetDetailedCriteriaLocationGuideFY2015.pdf.

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

Jones, Marcus D. “Norfolk Budget Transmittal,” July 1, 2015. http://www.norfolk.gov/DocumentCenter/View/21868.

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. http://www.norfolk.gov/DocumentCenter/View/18168.

“Norfolk Economic Indicators.” City of Norfolk, September 10, 2015. http://www.norfolk.gov/DocumentCenter/View/22760.

“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 finish 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.