Evaluation of potential mergers of the Provo-Orem MSA and the Ogden-Clearfield MSA with the Salt Lake City MSA

To: From: Michael Parker, Vice President of Public Policy, Salt Lake Chamber Pamela S. Perlich, Director of Demographic Research Juliette Tennert, Director of Economic and Public Policy Research Date: February 6, 2018 Subject: Evaluation of potential mergers of the Provo-Orem MSA and the Ogden-Clearfield MSA with the Salt Lake City MSA The Salt Lake Chamber requested that the Kem C. Gardner Policy Institute assess the criteria for and issues around combining the Salt Lake City and Provo-Orem metropolitan statistical areas (MSAs) into a single, larger MSA. The Chamber further requested we repeat this assessment process for potentially linking the Salt Lake City and Ogden-Clearfield MSAs. The Gardner Policy Institute examined the Office of Management and Budget (OMB) criteria for combining MSAs, and whether or when they will be met, as well as other economic linkages. The Institute also solicited input from Carrie Mayne of the Utah Department of Workforce Services, Theresa Foxley at the Economic Development Corporation of Utah, and Russell Cowley with the Six-County Association of Governments. Commuting flows between Utah County and Salt Lake County currently do not meet OMB requirements for the creation of an MSA. The closest they get to the 25 percent threshold is the 14 percent of working residents in Utah County who are employed in Salt Lake County. Flows between the Ogden-Clearfield MSA and Salt Lake County are closer to the threshold, with 20 percent of combined Box Elder, Davis, and Weber employed residents working in Salt Lake County according to the 2006 2010 ACS. Utah County is the largest in-state destination of Salt Lake County s production after itself, consuming 3 percent of Salt Lake s total private, nonfarm output. This is a closer tie than Salt Lake has with Tooele, its partner in the Salt Lake City MSA. Utah County is also the second-largest intercounty destination for Tooele County s output after Salt Lake. Similarly, Salt Lake is the largest intercounty destination of Utah County s production and the secondlargest intercounty destination of Juab s output. Davis and Weber are among the top five destinations for output from Salt Lake, Utah, Tooele, and Juab counties, and Box Elder is among the top 10 destinations for Salt Lake, Utah, and Tooele. Salt Lake and Utah counties are among the top three destinations for output from Davis and Weber and among the top five for Box Elder. Commuting Criteria MSAs are delineated by the OMB and are determined only by applying rules to data. Public opinion does not play a role in the delineation of MSAs. Each county in an MSA is classified by the OMB as either central or outlying, and an MSA may have multiple central or outlying counties. The requirement for two existing MSAs to merge is that at least 25 percent of workers living in the central county (or counties) of the outlying 1

region (MSA) commute to the central county (or counties) of the core MSA, or at least 25 percent of employment in the central county (or counties) of the outlying MSA comes from the central county (or counties) of the core MSA. The Provo-Orem MSA (Utah and Juab counties) and the Salt Lake City MSA (Salt Lake and Tooele counties) could be combined into one larger MSA if the central county of one MSA qualifies as outlying to the central county of the other MSA. As Utah County is the only central county of the Provo-Orem MSA, and Salt Lake County is the only central county of the Salt Lake City MSA, these are the only counties considered in the Salt Lake Utah analysis. For Utah County to qualify as outlying to Salt Lake County, either of these two conditions must be met: a) At least 25 percent of workers living in Utah County commute to work in Salt Lake County. b) At least 25 percent of employment in Utah County (all people working in the county, no matter their residence) is supplied by workers who live in Salt Lake County. The two MSAs could also merge if Salt Lake County qualifies as outlying to Utah County. This would be possible by the same criteria, with the two counties reversed. For the Ogden-Clearfield and Salt Lake City MSAs to merge, similar criteria must be met, except that there are three central counties for the Ogden-Clearfield MSA: Box Elder, Davis, and Weber. Therefore, in order for the Ogden-Clearfield MSA to qualify as outlying to the Salt Lake City MSA: a) At least 25 percent of workers living in the combined Box Elder, Davis, and Weber county area commute to work in Salt Lake County. b) At least 25 percent of employment in the combined Box Elder, Davis, and Weber county area (no matter their residence) is supplied by workers who live in Salt Lake County. The two MSAs could also merge if the Salt Lake City MSA qualified as outlying to the Ogden-Clearfield MSA. The most recent delineation of MSAs was calculated using 2006 2010 American Community Survey data. We evaluated the 2006 2010 dataset to determine whether Utah County was close to qualifying as an outlying county of Salt Lake County. The data show that 29,021 residents of Utah County work in Salt Lake County. There are 207,623 working residents in Utah County. Thus, 14 percent of working residents in Utah County work in Salt Lake County, which is less than the 25 percent required to merge the two MSAs. The reverse direction considers the percentage of employment in Utah County accounted for by workers who live in Salt Lake County. There are 10,996 residents of Salt Lake County who work in Utah County. This is just 6 percent of the 188,547 people employed in Utah County (the place of residence does not matter for this denominator) and would not allow for a merging of the two MSAs. The alternative way the MSAs could merge requires Salt Lake County to qualify as an outlying county to Utah County, which is far less likely. Only 2 percent of Salt Lake County s working residents work in Utah 2

County (10,996 people of 490,265). The share of Salt Lake County employment accounted for by workers who live in Utah County is 5 percent (29,021 people of 559,285). In addition to commuting flows between the Salt Lake City and Provo-Orem MSAs, the Gardner Policy Institute analyzed flows between the Salt Lake City and Ogden-Clearfield MSAs. Since the Ogden-Clearfield MSA includes three central counties Box Elder, Davis, and Weber the relevant population is the combined employed labor force of all three counties. Based on 2006 2010 ACS data, 20 percent of combined Box Elder, Davis, and Weber employed residents worked in Salt Lake County (51,678 of the total 261,494 employed residents). This share is larger than the 14 percent of Utah County residents who work in Salt Lake County. In the reverse flow, 10,699 of the 220,853 workers in Box Elder, Davis, and Weber counties reside in Salt Lake County, accounting for only 5 percent of employment. As with the Salt Lake City and Provo-Orem MSAs, it is much less likely for the Salt Lake City MSA to qualify as outlying to the Ogden-Clearfield MSA than the reverse. Only 2 percent of Salt Lake County s working residents work in Box Elder, Davis, or Weber counties (10,699 people of 490,265). The percent of Salt Lake County employment accounted for by workers who live in the three-county area is 9 percent (51,678 people of 599,285). Although the 2006 2010 ACS was the latest one to have an associated Census Transportation Planning Products release, the Gardner Policy Institute also examined commuting flows from the more recent 2009 2013 ACS. The results were very similar to those from the earlier ACS, with differences of less than one percentage point. We projected 50 years of commuting rates from each of Utah s 29 counties to every other county (for a total of 841 rates). The rates between Utah and Salt Lake counties are shown in Figure 1, and are to be interpreted as the percentage of the employed labor force in the first county that works in the second. For each county, Figure 1: Percent of Employed Labor Force Commuting from the First County to the Second, Utah and Salt Lake Counties 30% 25% Utah to Salt Lake Salt Lake to Utah 20% 15% 10% 5% 0% 2010 2015 2020 2025 2030 2035 2040 2045 2050 2055 2060 2065 Source: Kem C. Gardner Policy Institute Utah Demographic and Economic Model. 3

we also projected the percentage of the employment in the first county filled by residents of the second. For Utah and Salt Lake counties, these are plotted in Figure 2. Projections were done using the UDEM model developed and maintained at the Kem C. Gardner Policy Institute, with 2010 starting rates strongly informed by the 2006 2010 ACS dataset. The projections are the official published baseline population and employment projections for Utah. None of the rates ever reach the 25 percent threshold, though labor force commuting rates from Utah to Salt Lake County approach that mark in 2045, only to decline later. Figure 2: Percent of Employment in First County Filled by Residents from the Second, Utah and Salt Lake Counties 16% 14% 12% 10% 8% 6% 4% 2% Utah from Salt Lake Salt Lake from Utah 0% 2010 2015 2020 2025 2030 2035 2040 2045 2050 2055 2060 2065 Source: Kem C. Gardner Policy Institute Utah Demographic and Economic Model. We then adapted this analysis to consider a potential merging of the Salt Lake City and Ogden-Clearfield MSAs. Since our projected commuting rates were for each county-to-county pair, in order to adapt for commuting between the three central Ogden-Clearfield counties and Salt Lake County, we also: a) Projected the employed labor force for each county b) Multiplied each county s projected employed labor force by the commuting rates to determine the county-to-county commuting employed labor forces c) Summed across the employed labor forces commuting from Box Elder, Davis, and Weber counties to Salt Lake County to determine the total MSA commuting employed labor force d) Summed across the full employed labor force (including non-commuters to Salt Lake County) to yield a total three-county employed labor force e) Divided the three-county employed commuting labor force by its total employed labor force to obtain the MSA-to-MSA commuting rates A similar logic was implemented for determining the percentage of Box Elder, Davis, and Weber employment filled by workers residing in Salt Lake County; except in this case, we considered jobs instead of employed labor force. Figures 3 and 4 provide the results. 4

Figure 3: Percent of Employed Labor Force Commuting from the First MSA Center of Employment to the Second, Ogden-Clearfield and Salt Lake City 25% Ogden-Clearfield to Salt Lake Salt Lake to Ogden-Clearfield 20% 15% 10% 5% 0% 2010 2015 2020 2025 2030 2035 2040 2045 2050 2055 2060 2065 Source: Kem C. Gardner Policy Institute Utah Demographic and Economic Model. Figure 4: Percent of Employment in the First MSA Center of Employment filled by Residents of the Second, Ogden-Clearfield and Salt Lake City 12% Ogden-Clearfield from Salt Lake 10% Salt Lake from Ogden-Clearfield 8% 6% 4% 2% 0% 2010 2015 2020 2025 2030 2035 2040 2045 2050 2055 2060 2065 Source: Kem C. Gardner Policy Institute Utah Demographic and Economic Model. We do not project the 25 percent threshold to be met, and so do not anticipate the Ogden-Clearfield MSA could be considered outlying to the Salt Lake City MSA. Thus, by current rules, they would not be eligible for combination into a single MSA. While current data and our projection model show that thresholds will not be met for combining the Provo- Orem and Salt Lake City MSAs, nor the Ogden-Clearfield and Salt Lake City MSAs, circumstances are changing rapidly at the intersection of Utah and Salt Lake counties. Our models may not capture important economic dynamics. For example, employment in the 17 cities from West Jordan, Midvale, and Cottonwood 5

Heights in Salt Lake County south to Eagle Mountain, Saratoga Springs, Lehi, American Fork, and Pleasant Grove in Utah County grew by 57 percent between 2010 and 2016. This region provided 40 percent of the state s new jobs over this period. Actions undertaken today with respect to land use planning, transportation investments, economic development, etc. particularly at Point of the Mountain will influence how these patterns change over time. For this reason, we recommend that we continue to track commuting trends and re-evaluate these estimates on an ongoing basis. The next official review of MSA boundaries will occur in 2018 and use the 2011 2015 American Community Survey 5-year estimates, specifically for commuting and employment. Economic Considerations Although economic linkages beyond commuting do not play a role in the official definition of an MSA, the following discussion assesses the interconnectedness of the Salt Lake City, Provo-Orem, and Ogden- Clearfield MSAs and the plausibility of considering them a single regional economy. The 29-county REMI PI+ model for Utah contains baseline trade flows from each county to every other county, including itself. 1 These represent the value of goods and services that are produced in an origin county and used or consumed in a destination county. Salt Lake and Utah counties largest trade flow destinations are themselves, accounting for 70 percent and 57 percent of total private, nonfarm output, respectively (see Table 1). For Tooele and Juab, the rest of the nation is the largest destination of output, followed by themselves. As a result, for these counties such self-trade represents a smaller share of total private, nonfarm output than it does in the larger counties. Looking at cross-msa connections, that is, between Salt Lake and Tooele on the one hand and Utah and Juab on the other, Utah County is the largest intercounty destination of Salt Lake County s production, consuming 3 percent of Salt Lake s total private, nonfarm output (see Table 1). This is a closer tie than Salt Lake has with Tooele, its partner in the Salt Lake City MSA. Tooele County sends almost 5 percent of its output to Utah County, the second largest intercounty destination after Salt Lake. The other county in the Provo-Orem MSA, Juab is the sixteenth largest intercounty destination for Salt Lake s output and the twelfth largest intercounty destination of output from Toole. Going the other way, Salt Lake is the largest intercounty destination of Utah County production, receiving 6 percent of the county s output, and Tooele is the sixth largest intercounty consumer of Utah County s output. Juab sends almost 6 percent of its output to Salt Lake, the second largest intercounty destination after Utah County, which consumes 13 percent. Tooele is again among the top 10 intercounty destinations, as the sixth largest consumer of Juab s output. These data show that there are significant economic linkages not only between the central counties of the two MSAs, Salt Lake and Utah, but also between the central counties and the outlying counties (Juab and Tooele) and between the two outlying counties. The Ogden-Clearfield MSA central counties of Davis, Weber, and Box Elder also have significant economic ties with the two other MSAs. Davis and Weber are among the top five intercounty destinations for output from Salt Lake, Utah, Tooele, and Juab counties, and Box Elder is among the top 10 destinations for Salt Lake, Utah, and Tooele. Similarly, Salt Lake and Utah counties are among the top three destinations for output from Davis and Weber and among the top five for Box Elder. Tooele is the seventh largest output 6

Table 1: Domestic Trade Flows of Private, Nonfarm Output From Salt Lake County From Tooele County From Utah County From Davis County From Weber County From Box Elder County Destination Share Rank Destination Share Rank Destination Share Rank Destination Share Rank Destinatio Share Rank Destination Share Rank Destination Share Rank Salt Lake 70.3% Tooele 26.7% Utah 57.4% Juab 14.2% Davis 60.9% Weber 52.7% Box Elder 21.7% Utah 3.2% 1 Salt Lake 9.8% 1 Salt Lake 6.0% 1 Utah 12.8% 1 Salt Lake 6.3% 1 Davis 7.8% 1 Cache 5.7% 1 Davis 3.0% 2 Utah 4.5% 2 Davis 1.4% 2 Salt Lake 5.5% 2 Weber 4.5% 2 Salt Lake 4.6% 2 Salt Lake 5.1% 2 Weber 1.3% 3 Davis 2.8% 3 Summit 1.3% 3 Davis 1.7% 3 Utah 1.6% 3 Utah 1.6% 3 Weber 4.9% 3 Summit 0.85% 4 Weber 1.7% 4 Weber 0.82% 4 Sanpete 1.4% 4 Summit 0.7% 4 Box Elder 1.3% 4 Davis 3.3% 4 Tooele 0.54% 5 Summit 0.83% 5 Wasatch 0.72% 5 Weber 1.0% 5 Cache 0.5% 5 Cache 1.2% 5 Utah 2.2% 5 Cache 0.33% 6 Cache 0.63% 6 Tooele 0.52% 6 Tooele 1.0% 6 Box Elder 0.5% 6 Summit 0.7% 6 Summit 0.8% 6 Box Elder 0.28% 7 Box Elder 0.59% 7 Cache 0.29% 7 Millard 1.0% 7 Tooele 0.4% 7 Tooele 0.4% 7 Tooele 0.6% 7 Wasatch 0.22% 8 Washington 0.26% 8 Juab 0.22% 8 Summit 0.90% 8 Morgan 0.3% 8 Morgan 0.3% 8 Washington 0.2% 8 Morgan 0.12% 9 Wasatch 0.25% 9 Sanpete 0.22% 9 Sevier 0.60% 9 Wasatch 0.1% 9 Wasatch 0.2% 9 Wasatch 0.2% 9 Duchesne 0.06% 10 Millard 0.22% 10 Box Elder 0.22% 10 Wasatch 0.39% 10 Duchesne 0.1% 10 Washington 0.1% 10 Morgan 0.2% 10 Sanpete 0.06% 11 Sanpete 0.17% 11 Duchesne 0.17% 11 Cache 0.38% 11 Washington 0.1% 11 Uintah 0.1% 11 Uintah 0.2% 11 Washington 0.06% 12 Juab 0.17% 12 Millard 0.16% 12 Box Elder 0.35% 12 Uintah 0.1% 12 Duchesne 0.1% 12 Duchesne 0.1% 12 Uintah 0.06% 13 Sevier 0.15% 13 Carbon 0.15% 13 Washington 0.33% 13 Millard 0.1% 13 Sanpete 0.1% 13 Carbon 0.1% 13 Millard 0.06% 14 Uintah 0.15% 14 Uintah 0.12% 14 Carbon 0.32% 14 Sanpete 0.0% 14 Carbon 0.1% 14 Millard 0.1% 14 Carbon 0.05% 15 Duchesne 0.15% 15 Sevier 0.12% 15 Emery 0.29% 15 Carbon 0.0% 15 Millard 0.1% 15 Sanpete 0.1% 15 Juab 0.05% 16 Carbon 0.13% 16 Emery 0.11% 16 Duchesne 0.25% 16 Sevier 0.0% 16 Sevier 0.0% 16 Iron 0.1% 16 Sevier 0.05% 17 Iron 0.13% 17 Washington 0.10% 17 Uintah 0.21% 17 Juab 0.0% 17 Iron 0.0% 17 Sevier 0.1% 17 Emery 0.03% 18 Morgan 0.11% 18 Morgan 0.09% 18 Iron 0.21% 18 Iron 0.0% 18 Juab 0.0% 18 Juab 0.1% 18 Iron 0.03% 19 Emery 0.09% 19 Iron 0.06% 19 Beaver 0.20% 19 Emery 0.0% 19 Emery 0.0% 19 Emery 0.1% 19 Beaver 0.02% 20 Beaver 0.09% 20 Beaver 0.05% 20 Morgan 0.08% 20 Beaver 0.0% 20 Beaver 0.0% 20 Beaver 0.1% 20 Grand 0.01% 21 Grand 0.03% 21 Grand 0.02% 21 Garfield 0.05% 21 Rich 0.0% 21 Rich 0.0% 21 Rich 0.1% 21 Rich 0.01% 22 San Juan 0.02% 22 San Juan 0.02% 22 Grand 0.05% 22 Grand 0.0% 22 Grand 0.0% 22 Grand 0.0% 22 San Juan 0.01% 23 Garfield 0.02% 23 Garfield 0.02% 23 San Juan 0.04% 23 San Juan 0.0% 23 San Juan 0.0% 23 San Juan 0.0% 23 Garfield 0.01% 24 Kane 0.02% 24 Rich 0.01% 24 Kane 0.03% 24 Garfield 0.0% 24 Garfield 0.0% 24 Kane 0.0% 24 Kane 0.01% 25 Rich 0.02% 25 Kane 0.01% 25 Wayne 0.03% 25 Kane 0.0% 25 Kane 0.0% 25 Garfield 0.0% 25 Wayne 0.00% 26 Wayne 0.01% 26 Wayne 0.01% 26 Piute 0.02% 26 Wayne 0.0% 26 Wayne 0.0% 26 Wayne 0.0% 26 Daggett 0.00% 27 Piute 0.01% 27 Piute 0.00% 27 Rich 0.01% 27 Daggett 0.0% 27 Daggett 0.0% 27 Daggett 0.0% 27 Piute 0.00% 27 Daggett 0.00% 28 Daggett 0.00% 28 Daggett 0.00% 28 Piute 0.0% 28 Piute 0.0% 28 Piute 0.0% 28 RoN 12.8% RoN 39.3% RoN 23.6% RoN 47.3% RoN 15.5% RoN 19.9% RoN 40.8% RoW 6.4% RoW 10.9% RoW 6.1% RoW 9.4% RoW 8.2% RoW 8.7% RoW 13.4% Total Output 100% Total Output 100% Total Output 100% Total Output 100% Total Output 100% Total Output 100% Total Output 100% RoN = rest of nation; RoW = rest of world. Source: Kem C. Gardner Policy Institute analysis of baseline data from the REMI PI+ v2.1 29-county Utah model. From Juab County 7

destination for Davis, Weber, and Box Elder, while Juab is 17th or 18th. The three existing Wasatch Front MSAs share significant economic linkages, particularly across the largest counties of Weber, Davis, Salt Lake, and Utah. Pros & Cons Aside from the commuting and other economic considerations for combining MSAs, there are both benefits and costs that would come with a larger region. A larger MSA would aid economic development and recruitment efforts, making the region eligible to compete for larger, higher-profile projects with MSA size requirements. Had Salt Lake, Tooele, Utah, and Juab counties been a single MSA, it would have improved the region s prospects in the competition for Amazon s HQ2. In Moody s Analytics rankings of metropolitan regions for HQ2, the Salt Lake City MSA came in 11th out of 65. Combining the Provo-Orem and Salt Lake City MSAs would have improved the region s business environment and human capital scores enough to raise it to first place. However, there would be a loss of data granularity with a larger region, as what is now reported for two or three, somewhat different MSAs would be reported for just a single MSA. For example, Current Employment Statistics data from the Bureau of Labor Statistics are reported only by state and MSA. While county-level estimates are created for the CES, they are less reliable. Membership in a larger MSA would not likely affect the smaller, more rural Juab, Tooele, and Morgan counties. A June 2004 report by the U.S. General Accounting Office found that some federal agencies are required by statute to use metropolitan statistical areas to allocate program funds and implement other aspects of their programs. In other instances, federal agencies are not required to use metropolitan statistical areas by statute, but elect to do so. 2 For some of these programs, membership in an MSA is a criterion of program eligibility. Since no counties would change their MSA status under a merger of the Salt Lake City and Provo- Orem or Ogden-Clearfield MSAs, eligibility for these programs would not be affected. For other programs, payments are determined with reference to relevant MSA-wide measures, such as median incomes or average labor costs. Combining MSAs would affect these amounts to varying degrees, with some counties benefitting and others possibly seeing payments decline. For example, the median family income in the Salt Lake City MSA is $74,749 versus $70,203 in the Provo-Orem MSA. The median family income of a combined Salt Lake City Provo MSA would be somewhere between these two. Family income in the Ogden-Clearfield MSA is quite close to that of Salt Lake City. Conclusion While current OMB rules based on commuting flows do not support the creation of a Salt Lake City Provo MSA, there are significant economic ties among the four counties of the existing MSAs. More compelling may be the commuting flows between the Ogden-Clearfield MSA and Salt Lake County, which are quite close to the OMB s 25 percent threshold, though not expected to surpass it. There are also significant economic ties between the Salt Lake City and Ogden-Clearfield MSAs. Commuting data from the 2011 2015 American Community Survey will be used to determine the 2018 MSA definitions. 8

1 REMI uses a gravity model to estimate trade flows. This model considers output and demand in each region, differences in production costs, national output and demand, and a simple measure of the distance between any two regions. 2 U.S. General Accounting Office, Metropolitan Statistical Areas: New Standards and Their Impact on Selected Federal Programs, GAO- 04-758, p. 17; available from www.gao.gov/cgi-bin/getrpt?gao-04-758. Note: This memo was a collaborative effort by researchers at the Kem C. Gardner Policy Institute, with contributions from Mike Hollingshaus, Demographer; Mallory Bateman, State Data Center Coordinator; John Downen, Senior Research Analyst; and Natalie Young, Research Analyst. 9