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 a previous post I reviewed the accuracy of reporting in local economic development programs. In this article, using the same 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.

As with my previous study on reporting accuracy, 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.

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. 

Reporting Accuracy in Local Economic Development Programs

This exploratory study finds significant inaccuracies in self-reported data in the International City Manager’s 2014 Survey on Local Economic Development. These inaccuracies hinder the use of the data in evaluating program results, and raise issues about previous scholarship that used this data exclusively without validation from secondary sources. This exploratory study was followed by another study looking at predictors of accurate reporting. This latter study is currently under peer-review. 

Defining the limits of local economic development programs has been a vexing problem for scholars and public officials. Every aspect of planning, organizing, operating, and reporting economic development programs is fraught with complications. Complications with planning local economic development programs start with defining and measuring realistic outcomes. Increasing jobs and tax revenues are two traditional goals, but these, as Paul Peterson and others argue, are typically beyond the resources or political strength of their institutions or elected leaders (Peterson, 1981, p. 4; United States Congress, 1975, p. 11). If increasing jobs is a priority, the challenge becomes balancing the needs of business, and the interests of employed and unemployed of the community  (Adua & Lobao, 2015; Lobao & Kraybill, 2014). If tax growth is a priority, overcoming barriers to intergovernmental cooperation  poses significant challenges (Kwon & Feiock, 2010).  Measuring and reporting effectiveness, particularly when it comes to job creation, is another test.  Past research on local economic development program outcomes finds little in the way of employment, income, or fiscal benefits (Feiock, 2002) or worse, spur zero- or negative-sum competition (Reese, 1991; Reese & Rosenfeld, 2004).  Reporting negative or contradictory results is problematic for public administrators tasked with producing successful economic development programs.  The pressure to report positive results, applied more broadly to all public programs, has sparked a separate stream of research, focused on the integrity of the information exchange between public officials and their principals (Bartik, 1994, p. 99; Musgrave & Musgrave, 1989, p. 99).

While past research on local economic development programs has studied the relationship between priorities, barriers to success, and programming (Reese & Fasenfest, 2004, p. 12; Warner & Zheng, 2013), a noticeable gap is an assessment of the accuracy of program results reported by local officials. Despite the wide use self-reported data from national surveys of local economic development programs in academic research, there is no known research testing the validity of claims of success (or failure) by survey respondents. This paper explores this gap with an inductive study of the accuracy of self-reporting successes and failures.

To assess the state of local economic development program reporting practices, responses by municipalities to an economic development survey conducted by ICMA are paired with data collected by the United States Census Bureau on employment and tax revenues from the same time period.  The ICMA surveys its members on a regular basis on government operations, facilities, technology, sustainability and economic development. The results of these survey are provided in summary form to members and the public, and the underlying data is available to purchase for research purposes. The data set used in this study is the most recent ICMA survey on local economic development (2014). The survey was distributed to ICMA’s 5,237 members and 23% responded (N: 1201).  The response rate reflects the deletion of eleven cases that were not identified with a government entity. Additional steps used to clean the ICMA data are detailed in the appendix. Approximately two-thirds of the respondents were municipalities – with the balance being counties, special governments, and non-profits (International City Managers Association, 2014). 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 (Peterson, 1981, p. 10).  Table 1 provides basic demographic comparisons between the municipal survey respondents (n=827) and all places within the United States. The ICMA participants are generally among the larger places/municipalities, but have relatively equal income per capita, and slightly higher income deficits per capita. Property taxes are generally higher, and sales taxes are lower (Table 1). The stratification of the participants by population, compared to all other places/municipalities, is approximate for populations above ten thousand (Table 2).

Table 1

 

Table2

The 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 and Type II programing; creating jobs, increasing the tax base, 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 3. The priorities of municipalities in the survey are generally 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 establishing environmental sustainability (42%), and social equity (25%) as priorities. As for success in meeting these priorities, just over 89% 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%.

Table3.JPG

Testing Accuracy of Claims of Success or Failure

The first part of the exploratory study compares secondary data on actual job growth (2010 to 2014) and actual tax base growth (2012-2014) with the claims of success or failures from the ICMA survey responses. No definitive secondary data sources were identified to verify claims of success, or failure, improving quality of life, or advancing environmental sustainability or social equity.  For job growth, unemployment and employment status was collected for each municipality from the American Community Survey (Table S2301) for 2010 through 2014  (U.S. Census Bureau, 2010, 2011, 2012b, 2013b, 2014b). Both measures of employment were used because it is not known how each jurisdiction measures job creation. Also, since it is unclear what time-frame respondents to the ICMA survey used for gauging success, rates of change were calculated for the periods, 2010 to 2014, 2011 to 2014, 2012 to 2014 and 2013 to 2014. Eight binary dummy variables were created, representing each of the four time-frames and the two measurements (employment rate and unemployment rate) with “0” representing no growth in employment or decrease in unemployment, and “1” representing growth in employment and a decrease in unemployment.  For tax growth, property and sales tax data was collected from the Census Bureau’s State and Local Government Finances survey for 2012 through 2014 (codes T01 and T09)(U.S. Census Bureau, 2012c, 2013b, 2014c).  The Bureau notes that this data set may include high sampling errors (U.S. Census Bureau, 2012a, 2013a, 2014a). Again, since it is not clear what time frame respondents were contemplating when making claims of success or failure, rates of change were calculated for the periods 2012 to 2014 and 2013 to 2014. Only two periods were used for tax revenues, because typically municipalities measure and report tax revenues on an annual or bi-annual basis. Two binary dummy variables were created, representing each of the two time-frames and the single measurements (change in tax collections) with “0” representing no growth in tax revenue and “1” representing growth in tax revenue.

After the ten dummy variables were created for both actual jobs and tax growth, they were cross-tabulated with binary dummy variables representing survey claims of success or failure. Municipalities are deemed to be accurate if claims matched actual results. For example, if a city claims no success growing jobs, and the job growth rate was negative, the city is deemed to be accurate. If a city claims some job growth success, but yet experienced negative employment growth, that city’s claim in the survey is designated as inaccurate. The results of this cross-tabulation are present ed in Table 4.  The accuracy of claims of success, or failure, by respondents increased with shorter time frames. For example, the accuracy of job claims using the unemployment rate, increased from 28% using a four-year period (2010 to 2014) to 75% using a one-year period (2013-2014). Similar improvement occurred using the employment rate, with 24% accuracy using a four-year period and 66% accuracy using a one-year period. The accuracy of tax revenue claims improved slightly, 71% to 74%, contrasting two- and one-year periods.

Table4.JPG

Evaluating Programs using Self-reported and Actual Data

The next step to explore the accuracy of survey data was to compare the effectiveness of local economic development programs using self-reported and actual data. For this analysis, a binary dummy variable was created with the ICMA data to measure success with a response of “none” being a “0” and responses of “somewhat successful” and “very successful” being a “1”. Measures for programs (tools/incentives) were developed by combining multiple responses from the ICMA survey through factor analysis. The factor analysis started with 48 items from the ICMA survey relating to programs. The items associated programs, measured on four-point Likert scales, were reduced through factor analysis to seven measures and tested for internal consistency (α). The measures created for programs used 24 of the 48 select 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 5). A consolidated description of all the program measures is provided in Table 6.

Table5

Table6

Binomial logistic regression was then used to test and compare the relationship between the programs (collectively) and the binary success variables using self-reported and actual data. The results of these models are presented in Tables 7 and 8.   In Table 7 a statistically significant relationship is found between the seven measures (collectively) and self-reported claims of success for both jobs and tax revenues. The investment measure was strongly associated with success with job growth (OR 1.824) and tax growth (OR 2.761).  With actual data (Table 8), no statistically significant relationship was found between the seven program measures (collectively) and actual success increasing jobs, decreasing unemployment or increasing tax revenues. This analysis used the period from 2013 to 2014 for the success measures. In summary, with self-reported data the relationship between programs and claims of success were statistically significant in some instances, but using actual data, the relationship between programs and results were not statistically significant.

Table7

Table8

Conclusions

The use of self-reported data in ICMA economic development surveys is problematic for public officials, community members and researchers. Alternative data, or validation methods must be employed to ensure the voracity of the self-reported data. Finding reliable alternatives to assess program results is important for public officials and community members as the information exchange between staff and the public is a critical part of the democratic process.

For researchers, the use of self-reported data in ICMA surveys is compounded by past research that used this data exclusively to address research questions. ICMA, or equivalent survey data,  has been used to quantify the balance between pro-business policies social services (Adua & Lobao, 2015), determine the interaction of privatization, business attraction and social services (Lobao & Kraybill, 2014) assess the ability of poor cities to pursue local economic development (Lobao & Kraybill, 2009) and determine the economic climate where business incentives are deployed (Warner & Zheng, 2013; Zheng & Warner, 2010).  Researchers should be careful in citing these studies without checking to see how the ICMA data was used, and if it was validated by other sources.

Further study

The disparities between findings in the exploratory study using self-reported versus actual data generates the research question for further study; what are the predictors of accurate performance reporting in local economic development? There are two important reasons to address the accuracy of reporting from local economic development programs. First, access to accurate information about public programs is a critical safeguard of our democratic system. Murray Edelman summed it up this way, “Citizens who are informed about political development can more effectively protect and promote their own interests and the public interests”(Edelman, 1989, p. 382). For Paul Peterson, access to quality information is critical to a reasoned discourse on urban policy, “neither city residents nor city leaders are fools. On the contrary, they can be expected to think about their situations and take reasoned positions on the problems they face – within the limits of the information available to them (Peterson, 1981, p. xii).

I have completed a study with the subject research question. My methods and findings are currently under review by a peer-reviewed journal. I will post my results once I have passed the peer-review process. 


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. 

References

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Feiock, R. C. (2002). A Quasi-Market Framework for Development Competition. Journal of Urban Affairs, 24(2), 123–142. https://doi.org/10.1111/1467-9906.00118
International City Managers Association. (2014). Economic Development 2014 Survey Results.
Kwon, S.-W., & Feiock, R. C. (2010). Overcoming the Barriers to Cooperation: Intergovernmental Service Agreements. Public Administration Review, 70(6), 876–884.
Lobao, L., & Kraybill, D. (2009). Poverty and Local Governments: Economic Development and Community Service Provision in an Era of Decentralization. Growth and Change, 40(3).
Lobao, L., & Kraybill, D. (2014). Privatization, Business Attraction, and Social Services across the United States: Local Governments’ Use of Market-Oriented, Neoliberal Policies in the Post-2000 Period. Social Problems, 61(4).
Musgrave, R. A., & Musgrave, P. B. (1989). Public Finance in Theory and Practice (International). Singapore: McGraw-Hill-International.
Peterson, P. E. (1981). City Limits. Chicago and London: University of Chicago Press.
Reese, L. A. (1991). Municipal Fiscal Health and Tax Abatement Policy. Economic Development Quarterly, 5(1), 23–32. https://doi.org/10.1177/089124249100500103
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Reese, L. A., & Rosenfeld, R. A. (2004). Local Economic Development in the United States and Canada: Institutionalizing Policy Approaches. The American Review of Public Administration, 34(3), 277–292. https://doi.org/10.1177/0275074004264293
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U.S. Census Bureau. (2010). Employment Status (No. S2301). Washington D.C.
U.S. Census Bureau. (2011). Employment Status (No. S2301). Washington D.C.
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U.S. Census Bureau. (2014c). State and Local Government Finances. Washington D.C.
Warner, M. E., & Zheng, L. (2013). Business Incentive Adoption in the Recession. Economic Development Quarterly, 27(2), 90–101. https://doi.org/10.1177/0891242413479140
Zheng, L., & Warner, M. (2010). Business Incentive Use Among U.S. Local Governments: A Story of Accountability and Policy Learning. Economic Development Quarterly, 24(4), 325–336. https://doi.org/10.1177/0891242410376237

Tourism for taxes or good jobs?

Tourism is widely valued by cities across the United States. Public officials and their economic advisers champion the cause of tourism by using a variety of economic models to show how tourist spending gets converted to restaurant tabs and then to employee wages. In turn, these wages are used to buy groceries and consumables that bolster the economy. Driven by this logic, the multiplying tourist dollar has inspired public-private partnerships to develop hotels, attract visitors and build comfortable meeting spaces and entertainment venues for their enjoyment. A significant body of literature, primarily from neo-liberal economists, supports public investment in all aspects of tourism.

The enthusiasm for the tourist dollar within city halls and chambers of commerce is not without detractors. Such important urban theorists, as Susan Fainstein and David Harvey have raised concerns about the distribution of benefits within the tourism industry (subsectors that comprise the tourism industry are generally the lowest paid segment of any local economy). In The Just City (2010), Fainstein reflects on two decades of research on urban tourism and, given little movement toward a just end, suggests – somewhat in passing — that significant public subsidies given to private businesses within the tourism sector should empower residents and city planners to pursue policy options which achieve a fair distribution of economic benefits (Fainstein, 2010, p. 183). In the Rebel Cities (2012), Harvey observes the array of private rent-seekers trading on tourist attractions built and maintained with public investment. He considers this an appropriation of capital which belongs to the community (Harvey, 2012, pp. 105–106).

Urban interest in tourism, from a local economic development perspective, gained traction in the early 1990’s as cities struggled to retain traditional employers in central business districts. Fainstein joined with Dennis Judd and Lily Hoffman to compile two edited volumes on the topic; The Tourist City (1990) and Cities and Visitors (2003). The editors included low wages among a number of issues that planners should consider when developing a regulatory framework to guide the sector (Hoffman, Fainstein, & Judd, 2003, p. 9), although much of the burden for increasing wages was left to labor organizations and community organizers (Judd & Fainstein, 1999, p. 24). Twenty years removed from this spike in interest, Fainstein touched on tourism in The Just City (2010), again placing the burden of equitable wages on community organizers, while offering a new justification for action based on two decades of pubic investment in the sector, suggesting, “With the involvement of the state …comes the interests of nonowners of capital in limiting the discretion of investors and injecting concerns of justice into policy making (Fainstein, 2010, p. 183).”

Fainstein’s perspective is shared by heterodox economists, sociologists and urban theorists, but it remains a minority viewpoint across the full spectrum of academicians and practitioners (Ren, Pritchard, & Morgan, 2010, p. 887). The perspectives of neo-liberal economists dominate the field. Economists. like Larry Dwyer, focus on business profits with little or no priority given to the externalities associated with low wages within the industry. Dwyer et al’s voluminous text, Tourism Economics and Policy illustrates this point. With twenty-one chapters encompassing 855 pages, the authors declare there was not enough room to treat labor economics, or synthesize the fragments within the book that touched on economic sustainability (Dwyer, Forsyth, & Dwyer, 2010, p. 5,33). Others bypass labor to promote economic benefits to the community at large. Boley et al focus on promoting this point, suggesting governments consider “strategies to increase their residents’ attitudes toward tourism development,” and, “promote the indirect personal economic benefits of tourism, including tax burden relief and the services subsidized by tourism dollars” (Boley, McGehee, Perdue, & Long, 2014, pp. 46–47).

Most public officials have joined with neo-liberal economists in sidelining any policy discussions regarding the wage structure in the tourism industry. As an example, three of the largest states for tourism, California, Florida and Virginia, while actively promoting business interests within the industry, are silent on the wage structure of those working in the industry.

 

In Florida’s strategic plan for tourism, the stated goal is to maximize the economic impact of travel and tourism, with an objective to achieve $100 billion in tourism related spend by 2020 (Visit Florida, n.d.).

 

In the Commonwealth of Virginia, the responsibility for promoting tourism falls to the Virginia Tourism Corporation (VTC), a department under direction of the Governor. The corporation still operates under a vision plan adopted in 2002. The goal of the plan is to increase tourism market-share and annual visitor spending in Virginia, and the objectives are to 1) increase visitor volume, length-of-stay and spending in Virginia, and 2) increase tourism funding annually, including identification of new sources, to advance tourism marketing and development (Virginia Tourism Corporation, Commonwealth of Virginia, 2002).

 

In California, tourism officials set three goals in their 2012 strategic plan: 1) Garner 91% or better approval of a 2013 state-wide referendum on rental car assessments (they achieved 93%), 2) elevate legislators’ perceptions of the importance of the industry, and 3) raise consumer perceptions of California and increase media chatter with positive press articles that mention California and the economic benefits travel (Visit California, n.d.).

 

Strikingly, the missions, goals and objectives of all three states mention nothing of community benefits or employee wages, even though the accommodation sector is nested within the lowest paying industry sector in all three states (Table 1).
Table 1 Median wages by NAICS Sector in 2014 by Sector for Key States

Table 1

 

At the local level, the exclusion of wages from tourism development and promotion policies is also prevalent. A 2014 survey on local economic development conducted by the International City Managers Association (ICMA) found that among five potential priorities (tax base, jobs, quality of life, environmental sustainability and social equity) city officials placed increasing the local tax base first and addressing social equity (i.e., distribution of economic benefits) last. Of the 32 activities identified to address these economic development priorities, tourism promotion was ranked second, only behind quality of life investments (arts, culture, education and recreation) (International City Managers Association, 2014). The proximity of increasing revenues (tax base) as a priority, and tourism promotion as the means to this end is no coincidence.

 


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. 

 

Citations:

Boley, B. B., McGehee, N. G., Perdue, R. R., & Long, P. (2014). Empowerment and resident attitudes toward tourism: Strengthening the theoretical foundation through a Weberian lens. Annals of Tourism Research, 49, 33–50. https://doi.org/10.1016/j.annals.2014.08.005

Dwyer, L., Forsyth, P., & Dwyer, W. (2010). Tourism Economics and Policy. Channel View Publications.

Fainstein, S. S. (2010). The Just City. Ithaca, New York: Cornell University Press.

Harvey, D. (2012). Rebel cities: From the right to the city to the urban revolution. Verso.

Hoffman, L. M., Fainstein, S. S., & Judd, D. R. (Eds.). (2003). CIties and Visitors; Regulating People, Markets and City Space. Maiden, MA: Blackwell.
International City Managers Association. (2014). Economic Development 2014 Survey Results.

Judd, D. R., & Fainstein, S. S. (Eds.). (1999). The Tourist City. Yale University Press.

Ren, C., Pritchard, A., & Morgan, N. (2010). Constructing tourism research; A critical inquiry. Annals of Tourism Research, 37(4), 885–904.

Virginia Tourism Corporation, Commonwealth of Virginia. (2002). Vision Plan for Virginia’s Tourism Industry. Retrieved from https://www.vatc.org/uploadedFiles/Administration/About/Administration_and_Finance/documents/VisionPlan.pdf

Visit California. (n.d.). Visit California’s Strategic Business Plan; 2001-2016.

Visit Florida. (n.d.). 2020 Strategic Plan. Retrieved from http://www.visitflorida.org/media/24818/2020-strategic-plan.pdf

Making a case for the Just Host

Blog ArticleMy current research looks at high tax, low-wage sectors from a local economic development perspective. First up is the hospitality sub-sector. I’ve presented some of this research at an academic conference and to fellow researchers during my PhD studies. In the months ahead, I will write about this ongoing research project, introducing elements that will eventually find their way into future conference presentations, journal articles, and eventually, my second book. I will also present data from some detours along the way.
I will be presenting an eclectic group of topics relating to tourism and wages. My research synthesizes literature from six distinct disciplines; urban studies, tourism studies, public administration, public choice theory, real estate economics, and wage theory. With my unique set of experiences and biases (see below) I will be building on the work of Susan Fainstein (The Just City) and David Harvey (Rebel Cities), and testing the theories of public choice economists.
As for my data, I have the benefit of a national survey of economic development professionals, living wage data from MIT, hotel performance data from HVS, and wage and local government revenue data from the U.S. Census Bureau. Initially, I will start with simple cross tabulations of this data to reveal intriguing patterns and relationships. Some of the comparisons will include living wages, hotel revenues, and local government taxes. Others will look at the accuracy of performance claims made by local economic development officials. Some comparisons will focus on Virginia, others the nation, and some on large tourism market. The data will define the scope.

 

I approach this research informed by experiences from my career as a practitioner, my recent stint writing about U.S. history, and my age, gender, class and ethnicity.  As a practitioner, I served as a local economic development professional and corporate real estate executive,  and ran my own real estate advisory company. In this last role I helped develop several business–class hotels.  My research project in American history introduced me to labor relations in the industrial age, policies and tactics of FDR, and the battle for full employment legislation between 1945 and 1946.  Finally, I’m a white male, raised in an upper-income family during the 60’s and 70’s. I faced no economic hardships in my youth.  I remember when community colleges were free and catalogs for four-year colleges had one or two paragraphs devoted to college financing. Later,  as I raised a family in mixed-income areas, I observed the dramatic increases in college tuition combined with a deterioration of wages for entry-level employment. I developed an appreciation, albeit second hand, for economic challenges I never faced. Given my personal experiences, my research focuses on the power structures where I was employed for many years. I will leverage my understanding of hotel economics, real estate, local government administration, and public finance to provide a unique perspective on how the economic benefits derived from tourism can be can be distributed in a manner that contributes to a sustainable local economy.

 

I look forward to any constructive criticisms that you may offer. I consider any critique a gift.


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.