Introduction: This Policy Brief examines eight Metropolitan Statistical Areas (MSAs) across the country in terms of changes in three measures—population, private-sector employment and public-sector employment over the 10-year period 2015 to 2025.
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Jobs in both private and public sectors are shown in relation to the MSA population. The analysis was undertaken to determine if different MSAs had substantially different changes in per capita employment and whether the level of government jobs had any relationship to private-sector gains.
Four MSAs are in Right-to-Work (RTW) states and four are in non-Right-to-Work (NRTW) states. The MSAs in NRTW states include Rochester, N.Y.; Toledo, Ohio; St. Louis, Mo.-Ill. and Pittsburgh. MSAs in RTW states are Fort Wayne, Ind.; Omaha, Neb.-Iowa; Knoxville, Tenn. and Charlotte, N.C.-S.C. National data is also provided as a backdrop for MSA comparisons.
A summary of results for the averages of the performances of the NRTW and the RTW MSAs and the U.S. are shown in the following table. All figures are 10-year (2015 to 2025) percentage changes for population, private-sector employment and public-sector employment.
| 10-year percentage change | |||
| Population | Private-sector employment | Public-sector employment | |
| RTW MSAs | 13.7 | 15.9 | 8.9 |
| NRTW MSAs | -0.7 | 2.8 | -1.9 |
| U.S. | 6.6 | 12.7 | 6.7 |
MSA population and private-sector employment
The RTW MSAs were led by Charlotte with population growing 22 percent over the ten years and private-sector employment growth of 27 percent. The Knoxville MSA had a rapid 21 percent private-sector employment gain. Fort Wayne posted an 11 percent private jobs increase while Omaha lagged the other RTW MSAs with a very slow 4.5 percent private-sector employment gain over the 10 years, even though population climbed 11 percent. Fort Wayne was close to the U.S. growth, posting a gain of 11 percent in private-sector jobs while population climbed 8.4 percent.
Among the MSAs in the NRTW states, only St. Louis managed a population gain and that was miniscule at 0.1 percent. Pittsburgh’s population was down 1.1 percent; Toledo’s fell 1.3 percent and Rochester’s was lower by 0.5 percent.
In terms of private-sector employment, the four MSAs in NRTW states had an average gain of 2.8 percent over the 10-year period, led by St. Louis’s 6.4 percent rise. Rochester’s was weakest, posting a meager 0.6 percent gain, followed by Toledo at 1.6 percent. Pittsburgh saw a small pickup of 2.6 percent over the period.
None of the NRTW MSAs posted percentage employment gain close to the U.S. increase of 12.7 percent.
Government-sector employment
The ratio of government employment (all government employees, federal, state and local, including education) to population (expressed as employees per 1,000 residents) ranged widely across the MSAs in this sample. For the four RTW MSAs, the average ratio of government-sector employment to population was 62 per 1,000 in 2015 and 60 per 1,000 in 2025, a decline of 3.2 percent. The MSAs in RTW states had ratios of government employment-to-population in 2015 ranging from 49 per 1,000 in Fort Wayne, 63 per 1,000 in Charlotte and 68 per 1,000 in both Omaha and Knoxville. By 2025, each MSA had seen the ratio of government employment-to-population decline—Fort Wayne posted 47 per 1,000, Knoxville and Omaha saw 65 per 1,000 and Charlotte was 61 per 1,000.
In 2015, the MSAs in NRTW states had ratio of government-sector jobs to population that ranged from a low of 49 per 1,000 residents in Pittsburgh, followed by St. Louis (57 per 1,000), Rochester (73 per 1,000) and Toledo (75 per 1,000). The average of the four MSAs in 2015 was 64 per 1,000 residents. For 2025, St. Louis had dropped slightly to 56 per 1,000, Rochester was still 73 per 1,000, Toledo saw small drop to 74 per 1,000 and Pittsburgh held at 49 per 1,000. In total, the group average fell a miniscule 1.6 percent.
Note that it is possible that some small percentage of the federal and state employees in the MSA government employment totals could be residents of counties not included in the MSAs. By the same token, some residents of the MSAs could be employed outside the MSA. But there is no readily available official data on this issue.
Overall, comparing the two sets of MSAs in this sample, the 2015 four-MSA average of government-sector jobs to population is very close at 64 per 1,000 residents in the NRTW MSAs and 62 per 1,000 for the RTW MSAs. By 2025, the gap had widened slightly as both averages decreased, to 63 per 1,000 in NRTW MSAs and 60 per 1,000 in RTW MSAs, respectively.
Discussion
An important point to note is the comparison of the RTW and NRTW MSAs with the national statistics. Over the 10 years 2015 to 2025, the U.S. population climbed 6.6 percent; private-sector employment was up by 12.7 percent, almost twice as fast as population growth. Government-sector employment at 6.7 percent tracked closely with population growth.
The MSAs in this study located in RTW states had unweighted average population growth of 13.7 percent, private-sector employment grew 15.9 percent and government jobs climbed 8.9 percent. Note that weighted-population and employment growth for the RTW sample would probably be even faster in light of Charlotte MSA’s much larger size in the RTW MSAs.
Meanwhile, the NRTW MSAs studied had an average population loss of 0.7 percent. Private-sector employment rose an average of 2.8 percent while government-sector employment fell 1.9 percent during the time frame.
Despite significant differences in performance among each group of MSAs, the conclusion is inescapable. For regionally important MSAs across the country, being in a RTW state has, on average, advantages for both population and job growth. This pattern has persisted for many years. Obviously, not every RTW state or every MSA in a RTW state is more successful than all MSAs in NRTW states.
However, Allegheny Institute Policy Briefs over the past 30 years has shown, time after time, this pattern of RTW MSAs and states generally being more economically successful than NRTW MSAs and states is borne out by comparative data analysis.
