Measuring Economic Success for Economic Development

The views expressed are those of the author and do not necessarily reflect the views of ASPA as an organization.

By David Robinson
November 25, 2014

Metrics are essential to measure success for economic development. Reviewing simple measures of success (such as unemployment rate, poverty and personal income) in a silo without comparing a region’s economy to others creates a weak measure of success. Successful economic development is not redeveloping a community “eyesore” but creating additionally community wealth. How do we measure wealth creation?  Economists offer many alternatives for measuring wealth creation.

Per capita income is one measure. According to the Census Bureau, per capita income is the mean money income received in the past 12 months computed for every individual in a geographic area. A geographic area’s per capital income is derived by dividing the total income of all people 15 years old and over in a geographic area by the total population in that area. Money income is amounts reported separately for wage or salary income, net self-employment income and interest, dividends, or net rental or royalty income or income from estates and trusts. Funds from Social Security or Railroad Retirement income, Supplemental Security Income (SSI), public assistance or welfare payments, pensions constitute money income are also included.

A weakness of per capita income as a means to measure wealth creation is that receipts from capital gains—money received from the sale of some property and the value of income “in kind” from food stamps, public housing subsidies, medical care and employer contributions for individuals—are not counted. Neither are withdrawals of bank deposits, money borrowed, tax refunds, exchange of money between relatives living in the same household, gifts and lump-sum inheritances and insurance payments.

Per capita income measures may underreport totals because the data relies on answers to income questions based on memory. Even the Census Bureau admits underreporting tends to be more pronounced for income sources that are not derived from earnings, such as public assistance, interest, dividends and net rental income. However, per capita income of a region or state remains one of the best measures of wealth creation related to economic development. Regions creating high-wage jobs can increase the wages paid to workers in that industry sector and those high-wage jobs will have a high “multiplier effect.” This enable them to fund a wider range of low wage jobs that are the larger part of any regional and state economy.

Another measure of wealth creation is private, non-farm employment totals. Private, non-farm employment establishment is a single physical location where business is conducted or services/industrial operations are performed. Two or more activities conducted at a single location under common ownership are grouped together as a single establishment. Establishments with paid employees include all locations with paid employees any time during the year. Paid employment measures both full- and part-time employees on the payroll, paid sick leave, holidays and vacations. Proprietors and partners of unincorporated businesses are not included.

Private, non-farm employment is a good economic development measure as it removes the economic benefit of government, university, school and other public sector workers that operate based upon tax dollars. Economic development is the study of the use of public subsidies to incentivize private sector, high-wage job group that create wealth. Government institutions are of importance but they support economic development and do not create it. Private, non-farm employment data measures the success or failure of a community to develop those non-public sector jobs.

Another measure of economic development success comes from the Payroll Survey. The Payroll Survey is a monthly poll of 140,000 businesses and government agencies that measures employment, hours and earnings estimates for the nation, states and metropolitan areas by industry. The Payroll Survey identifies overall employment, which jobs and industries pay higher wages and which jobs and industries create wealth. However, a weakness of the Payroll Survey is that is estimates only non-farm wage and salary jobs and is not an estimate of all employed persons. It can count an individual with two jobs twice and it excludes employees in agriculture and the self-employed.

This and other federal government data sets enable regions and states to identify high wage jobs and industries to prioritize their public subsidies for economic development purposes. Only 15 percent of all U.S. jobs wages paying at least 50 percent more than the overall average wage. However, these high-wage jobs on average pay about twice the overall average. These high-wage jobs are concentrated in a minority of industrial sectors and high-tech scientific sectors.

Shift-Share Analysis

Another model used to measure economic success is the shift-share analysis. This approach compares local economic success with national economic success in industries of interest or the market overall. A community’s claim for economic success in the financial services market because of a 5 percent job growth rate is not as impressive if the financial services industry grew by a 10 percent rate nationally.

Shift-share analysis studies a region’s growth into segments by comparing the national economic growth rate with the growth or decline of employment in that industry at the local level. Shift-share studies look at how regions impact that growth or decline of employment in a specific industry. This analysis distinguishes between growth attributable to the national economy, growth attributable to the mix of faster or slower than average growing industries and growth attributable to local industries.

Measuring economic success based upon the shift share model is broken down into:

• Identification of at least two points of time to measure data.
• Research of local industry employment data and national industry employment data typically from the federal government’s Bureau of Economic Administration (BEA).
• Comparison of the local versus the national economic data.

The national growth share is calculated by multiplying the base year for each industry by the national average employment growth rate over the time period. Adding these results for each industry creates the national growth component for the local economy. The growth rate equals employment in year of interest minus employment in base divided by employment in base year.

This formula determines if a regional economy is growing at or below the national employment rate. The measure is against the national average of growth or decline.

Critiques of a shift-share analysis point to the unfairness of measuring the success or failure of a specific company or industry in a region. A region could be fortunate enough to have a CEO creating amazing results for his or her bank that is the true cause for a region’s success not a local economic development initiative.

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Author: The author wishes to acknowledge this article is an excerpt from his book, Economic Development from the State & Local Perspective, by David J. Robinson. 

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