Categories
Data Releases

IRS: Davidson County among national leaders in attracting residents from out of state

Davidson County was among the leaders nationally in attracting residents from out of state in 2017-2018, according to new data from the Internal Revenue Service (IRS).

Nearly 17,000 households representing an estimated 25,000 people (see methodology below) moved to Davidson County from other states in 2017-2018, accounting for the majority of all US-based moves to the county (61%). Davidson County’s net gain, or inflow-outflow, of an estimated 3,358 households from out of state ranked 16th among the 100 largest counties in the country. Maricopa County, AZ (Phoenix) had the largest net gain in households at 21,267, followed by Clark County, NV (Las Vegas) at 15,628, and King County, WA (Seattle) at 10,718. Denver and Wake County (Raleigh) rounded out the top five.

Since nominal change tends to favor large counties—i.e. more people, more moves—it can be helpful to normalize the data to account for differences in total population. Looking at net migration of households from out of state relative to total population, Davidson County jumps up to #7 (Denver is first). In other words, people moving to Davidson County from out of state are having a more significant impact on the size of the overall population here compared to the impact of out-of-state migration in most other large, growing counties.

Where are people coming from?

In terms of migration the top “donor” states to Davidson County ranked by inflow of households (with a minimum of 500) in 2017-2018 were:

  1. Florida 1,206
  2. California 1,152
  3. Texas 847
  4. Illinois 761
  5. Georgia 611
  6. New York 598
  7. Alabama 547
  8. Kentucky 508

In net terms (inflow-outflow) Davidson County gained the most households from Illinois (446), California (367), and Florida (337).

The top ten donor counties to Davidson County were:

  1. Rutherford County 2,183
  2. Williamson County 2,045
  3. Sumner County 1,239
  4. Wilson County 1,022
  5. Shelby County 606
  6. Montgomery County 481
  7. Cook County (IL) 465
  8. Los Angeles County (CA) 437
  9. Robertson County 364
  10. Cheatham County 344

The top ten donor counties from out of state were:

  1. Cook County (IL) 465
  2. Los Angeles County (CA) 437
  3. Fulton County (GA) 239
  4. Harris County (TX) 201
  5. Dallas County (TX) 197
  6. Jefferson County (AL) 181
  7. New York County (NY) 166
  8. San Diego County (CA) 160
  9. Maricopa County (AZ) 158
  10. Kings County (NY) 158

Nearly one out of every five households moving to Tennessee from other states went to Davidson County, followed by Shelby County (13%) and Montgomery County (8%).

Methodology

The IRS publishes annual data showing the number of tax returns, exemptions, and total adjusted gross income reported in each state and county and then matches addresses in consecutive years of filings to identify migrants. Analysts use these returns to estimate households and exemptions to estimate people, but they are not matched 1:1.

For example, multiple returns can be filed from the same address, and not all exemptions are people. Generally, returns are a more accurate proxy for households than exemptions are for people, which is why most analysts focus on returns when reporting the data. Time periods are expressed in hyphenated years (e.g., 2017-2018) due to tax filing deadlines. The 2017-2018 data set includes reported income earned in Tax Year 2017 only but could reflect a move in 2018 during the filing period for most returns, January-April 15, 2018. Since a move could occur at any time between when the Tax Year 2016 return was filed and when the Tax Year 2017 return was filed it must be expressed as two hyphenated calendar years.

Finally, not everybody is required to file a tax return, meaning the IRS data does not reflect the total population. Please see the user guide posted on the IRS website for a more detailed explanation of data limitations and appropriate interpretation.

Categories
Data Releases

Health care added nearly $11 billion to Nashville economy in 2018

The health care industry added nearly $11 billion to Nashville’s economy in 2018, according to newly available county-level statistics from the Bureau of Economic Analysis (BEA).

Nashville’s health care industry accounted for $10.996 billion in value-added to Davidson County’s gross domestic product (GDP) in 2018, according to my analysis of BEA’s data, or about $1.50 out of every $10 in total economic value. Health care is 15.3% of total GDP in Davidson County, which ranks first among the largest 100 county economies in the U.S., followed by Bronx (15.1%), Nassau (14.8%), and Kings (13.0%) in New York.

Health care’s inflation-adjusted growth rate of 2.8% in 2018 trailed the Nashville economy overall (4.6%), but the industry’s real value has more than doubled since 2001. Of counties with a health care industry valued at $10 billion or more, only Maricopa, AZ (Phoenix), and Santa Clara, CA, surpassed Davidson’s real growth rate (105%) during 2001-2018.

County-level GDP data is an important milestone for federal statistics programs, especially for counties, like Davidson, belonging to very large metropolitan statistical areas (MSAs), where parsing county-level trends is difficult. Jobs data has been available at the county level for a long time but provides only one indicator of local economic activity. Analysts have been lobbying for publicly available, county-level GDP data for quite some time.

So, on behalf of local analysts and economic developers everywhere, thanks to BEA for this important contribution to our understanding of local economies.

Categories
Politics

We’re missing a crucial piece of the manufacturing story, again.

Headlines on the state of U.S. manufacturing are picking up again, which can only mean one thing: We must be approaching an election.

Automation. Trade agreements. China. Trump. Each provides a crucial storyline for the narrative in 2020. Well, maybe not that last one given the thorough debunking by Caroline Freund, Jonathan Rothwell, and others of the suggested link between manufacturing and the 2016 election results. But why let truth get in the way of a good story, as Twain put it. And, really, who wouldn’t want to hear from Twain about the state of affairs today.

Automation, trade policy, and foreign competition are all important aspects of the story, but there are others not getting their due. Of course, some lack of nuance in reporting should be forgiven. It can be difficult to get past the magnitude of top-line statistics that show the loss of about 2.5 million manufacturing jobs since 2002, according to data from Emsi, an Idaho-based labor market analytics firm. Details can get buried under the weight of that lede.

But look beneath those top-line statistics and an interesting story starts to emerge. One that Lawrence Mishel, Susan Houseman, and even people at the Congressional Research Service have tried to call attention to recently without much luck, at least not in the form of stories in the mainstream media. And that’s a shame because while it might not rise to the level of political fodder, this underappreciated aspect of the story could have far more important implications for labor market policy and the future of work in communities relying on manufacturing for a significant portion of local employment.

That missing piece of the story is the shift in payroll jobs from manufacturing companies to staffing firms. Yes, outsourcing has been a prominent feature of the narrative since at least the 1970s; it’s not a new storyline. But consider what’s happened during our record-setting period of economic growth since the last recession. The number of production workers on payrolls of manufacturing companies grew by less than 1% per year during 2009-2018. By contrast, the number of production workers employed by staffing or temporary help firms (NAICS 5613) increased by 72%. Put another way, we’re approaching the point where 1 out of every 12 production workers in the U.S. is now employed by a staffing firm, an increase of nearly 60% since 2009, according to my analysis of Emsi data.

That still pales in comparison to the 6.5 million production jobs at manufacturing firms, but outsourced labor is gaining ground. Manufacturing companies account for about 70% of all production jobs in the U.S. economy, but only an estimated 51% of net new production jobs created during 2009-2018. Staffing firms added 43% of those new jobs.

Mishel’s analysis does an excellent job of explaining another important aspect of this story: the wage gap. The median wage for production workers employed by manufacturing firms is about 35% higher than the median wage for production workers at staffing firms, which is just $26,690 annually, according to the Bureau of Labor Statistics (2018). Even at the 90th-percentile wage for the most skilled or experienced workers, the gap is still more than 30%. Mishel summarizes what a continuation of this trend could mean for how manufacturing is viewed through the lens of economic and workforce development policy:

“Contrary to some claims, there is a sizable manufacturing compensation premium…[but] there has been severe pressure on manufacturing firms to reduce pay and they have done so by reducing wages and by using staffing services firms as intermediaries. The result is that the compensation premium in manufacturing is substantially lower in recent years than it was in the 1980s. This suggests that those who advocate policies to expand manufacturing cannot take the pay premium for granted. Rather, they should create and promote policies to support compensation levels and the overall quality of jobs in manufacturing.”

Mishel is right, of course, but it’s a double-edged sword. On the one hand, the shift of jobs to staffing firms is eroding the wage premium. On the other hand, there is some evidence that suggests staffing firms may be keeping people out of long-term unemployment. During the decade of the 2000s in Michigan, for example, the manufacturing industry averaged about 44,000 employee separations per quarter, according to my analysis of Census data. Sixty-two percent of those separations resulted in persistent non-employment, defined as two or more quarters; 34% of those separated workers transitioned to other jobs. That ratio has since flipped. In 2017, 54% of manufacturing employee separations resulted in workers moving to other jobs and 43% resulted in persistent non-employment.

Lack of detailed industry data makes it difficult to say how many of those separations in Michigan resulted in workers transitioning from jobs at manufacturing companies to jobs at staffing firms, much less how many of those employees were production workers versus other types of occupations. But we do know based on averaging the most recent five years of available data, 2013-2017, that 23% of manufacturing employee separations in Michigan resulted in workers transitioning to jobs at companies classified in the parent industry for staffing and temporary help firms (NAICS 56 Administrative, Support, Waste Management and Remediation Services), up from an average of 18% in the early 2000s.

One thing is clear: We need more smart people in the weeds on this, focused on what this piece of the story means for workers and communities, especially in areas of the country specialized in, and therefore largely dependent on, manufacturing. On the policy front, what can we do to ensure that manufacturers have access to needed workers but at the same time protect temporary labor from further erosion of the wage premium and the uncertainty of contingent work? Can we strengthen the safety net in a way that boosts productivity for firms and positions temporary workers for higher-skill, higher-wage employment opportunities, assuming this trend will continue? What, if anything, are staffing firms doing to work together to address these challenges, particularly if they believe accelerating automation threatens their business model? Is our workforce development system prepared to respond?

Hopefully we won’t need to wait for the post-election explainers in 2021 for answers.

Categories
Data Releases

Brace yourself, San Francisco

San Francisco is approaching a milestone, and not everybody is going to be happy about it: Average wages in San Francisco are approaching parity with Silicon Valley.

Average weekly wages in San Francisco grew by double-digits for the third quarter in a row on a year-over-year (YoY) basis in 2019Q2, according to data released yesterday by the U.S. Bureau of Labor Statistics. The average weekly wage in San Francisco was $2,430 in Q2, up 15.5% (nominal) from a year earlier, which led all large counties by a mile (Seattle was next among counties with at least 500,000 jobs at 6.6%). In fact, San Francisco has now achieved that feat for two quarters in a row. It was the only large county to reach double-digit average weekly wage growth on a YoY basis in Q1 (10.2%); Hamilton/Cincinnati was next at 5.9%.

Wage growth in the Bay Area and Silicon Valley is hardly breaking news. We got the latest reminder just last week with the release of 2018 per capita income data. But yesterday was noteworthy because we could look back when we have more data available and realize that the first half of 2019 was the start of a new chapter in the story about economic geography in the Bay Area and Silicon Valley, one in which the center of gravity for higher earnings shifts from Santa Clara to San Francisco. Citylab followers and their favorite economists have speculated about that for some time. The evidence might be tilting in their favor.

The gap between the average weekly wage in Silicon Valley and San Francisco narrowed to about 7% in 2019Q2, a difference of less than $200. That’s the first time the wage gap in Q2 has been in the single-digits since at least 2001. Why is Q2 significant? It’s not surprising to see the average weekly wage in San Francisco approach or even slightly exceed the average weekly wage in Silicon Valley in Q1, or occasionally Q4, due to the timing of bonuses paid in finance. There are larger numbers of finance jobs in southern California given the size of those counties, but San Francisco has the most significant finance cluster on the West Coast (a jobs LQ of 1.44 and wages LQ of 1.59, for the economists). But the numbers quickly flip back in favor of Silicon Valley in Q2, Q3, and usually Q4. The last notable narrowing of the wage gap in spring or summer was in 2009, and before that in 2002–but not to single-digits.

To understand how quickly things have shifted in the Bay Area labor market, consider how San Francisco compares to New York, historically where you would find the nation’s most highly compensated workers, on average. San Francisco’s recent track record of ludicrous speed wage growth resulted in wage parity, at the average, with New York for the first time in 2016Q3. Less than three years later the gap was 15% in favor of San Francisco.

Will 2019Q3 be the turning point in the story when San Francisco surpasses Silicon Valley? We will find out on February 20.

Categories
Data Releases

Five observations on 2018 PCI data for counties

A few thoughts on today’s release of 2018 income data for counties:

1) Income growth in Silicon Valley and the Bay Area continued at a mind-boggling pace. Among large counties with 500,000 or more in population five of the top ten ranked by real (inflation-adjusted) per capita income growth in 2018 are in California, led by Santa Clara and San Mateo at 4.5%. A reference point to the U.S. can help make the point in a different way. Real per capita income (PCI) in the U.S. was up about 1.9% in 2018. Nine large counties experienced real PCI growth that was more than double the U.S. rate–five were in Silicon Valley or the Bay Area.

1.a.) Season 6 is amazing so far.

2) Tulsa ranked #1 among large counties. It was the only one to reach 5% in real PCI growth in 2018. In fact, most of the state of Oklahoma appears to be doing well, at least according to PCI growth as a measure of economic well-being. The state’s two large counties ranked in the top twelve nationally (OKC was 12th at 3.4%) and real PCI grew in every one of the state’s larger counties with 50,000 or more residents, led by Washington at 8.3%.

3) The number of very high-income counties is growing, and the geographic concentration of those counties is shifting. In 2010 there were only five counties with PCI of $100,000 or more (in 2018 dollars). None were in California. Marin was the only CA county in the top ten; Santa Clara ranked 42nd. The number of counties with PCI of $100,000 or more grew from five in 2010 to nineteen in 2018. Three of the top ten were in California; Santa Clara went from 42nd to 15th. We now have one county with PCI of $250,000+ (Teton, WY), and New York may become the first large county to reach $200,000 when 2019 data is out.

4) I made this point over at the Capital of Texas Media Foundation research blog, where I write about Austin, but it’s worth repeating here. The pace of per capita income growth in some communities since the end of the last recession is astonishing. Twenty-two counties have seen real per capita income growth of at least 50% since 2010. Most of those counties have relatively few residents and are found in energy-driven local economies–10 of the 22 are in Texas and have fewer than 20,000 residents–but several large counties are on or are approaching that list as well, including Santa Clara (52%), San Mateo (48%), and SF (47%). Places like Denver (40%), New York (39%), and Seattle (38%) are not far behind.

5) It’s interesting how closely Los Angeles and Chicago are tracking. In 2018 PCI was about $62,000 in Los Angeles and Cook County, and it also grew at about the same rate that year (2.3%). In fact, it’s been very close since 2010, about 23% in Los Angeles and 22% in Cook. Both counties also experienced slight declines in population in 2018.