Toyota announced in late April that over the next three years it would relocate 3,000 jobs from Torrance, California, to Plano, Texas—a decision that in the big picture won’t have a huge impact on employment in America’s two largest states. But Toyota’s move is just one of many economic development wins for Texas, and it was a definite blow for California.
When we add up the movement of jobs—businesses relocating, closing, expanding, or contracting—from state to state and region to region, we can get a sense of which areas of the country are gaining a larger share of new jobs and which are falling behind.
We used shift share—a standard economic analysis method that’s available in Analyst, EMSI’s labor market research tool—to tease out the number of new jobs from 2010 to 2013 in each of the 50 most populous metros that can be traced to regional factors as opposed to national trends.
Post-recession, three of the five most competitive metropolitan statistical areas for job growth have been in Texas (Houston, Dallas, and Austin). Major California metros such as San Francisco and Los Angeles have also done well in the competitiveness department, but New York and other major centers of commerce (Chicago, Philadelphia, and Washington, D.C.) produced fewer jobs than expected.
Shift-share analysis, also referred to as “regional competitiveness analysis,” helps us distinguish between growth that is primarily based on big national forces (the proverbial “rising tide lifts all boats” analogy) vs. local competitive advantages. Read more on shift share in this article: Understanding Shift Share.
To generate our ranking, we summed the overall competitive effect for each detailed (6-digit NAICS) industry and added them together to yield a single MSA-wide number that indicates the overall competitiveness of the economy as compared to the total economy. We calculate the competitive effect by subtracting the expected jobs (the number of jobs expected for each MSA based on national economic trends) from the total jobs. The difference between the total and expected is the competitive effect. If the competitive effect is positive, then the MSA has exceeded expectations and created more jobs than national trends would have suggested. It is therefore gaining a greater share of the total jobs being created. If the competitive effect is negative, then the MSA is below what we would expect given national trends. In this case the MSA is losing a greater share of the total jobs being created.
How The 50 Largest Metros Fared
From 2010 to 2013, the Houston metro created more than 250,000 jobs—108,000 more than national trends would have projected. Those 108,000 jobs are due to the competitive effect, and the biggest industries that contributed to this better-than-expected performance were limited- and full-service restaurants, elementary and secondary schools, and engineering services. Houston added approximately 26,000 restaurant jobs over this time, when based on national trends it should have added around 17,500 (a cumulative competitive effect of 8,500).
Dallas and San Francisco had the next-biggest competitive effects, while Austin had the highest percentage of total 2013 jobs (6%) that stem from regional competitiveness. (After Austin, San Jose, San Francisco, and Houston had the largest percentages of jobs due to competitiveness).
New York, Chicago and Philadelphia, meanwhile, all produced more than 100,000 new jobs since 2010. But they showed a negative competitive effect, trailing national growth trends. The reasons?
- New York lost more jobs than expected based on national trends in finance (e.g., securities brokerage), manufacturing (e.g., pharmaceutical manufacturing), and health care (e.g., nursing care facilities).
- Chicago didn’t gain as many jobs as anticipated in manufacturing while government, hospitals, and insurance carriers bled jobs.
- And Philadelphia was hurt by larger-than-anticipated losses in education (e.g., local government and private elementary and secondary schools), commercial banking, and manufacturing.
|MSA Name||2013 Jobs||2010-2013 % Change||Job Change (2010-2013)||Expected Job Change Based on National Trends||Competitive Effect||% of Total Jobs Due to Competitive Effect||Competitive Effect Rank|
|Source: EMSI 2014.2 Class of Worker (QCEW Employees, Non-QCEW Employees, Self-Employed)|
|Houston-The Woodlands-Sugar Land, TX||3,030,835||9%||250,607||142,377||108,229||3.6%||1|
|Dallas-Fort Worth-Arlington, TX||3,370,536||7%||221,161||130,743||90,419||2.7%||2|
|San Francisco-Oakland-Hayward, CA||2,336,223||8%||165,768||80,549||85,219||3.6%||3|
|Los Angeles-Long Beach-Anaheim, CA||6,282,545||5%||283,664||207,318||76,345||1.2%||4|
|Austin-Round Rock, TX||929,439||10%||84,774||29,152||55,622||6.0%||5|
|Miami-Fort Lauderdale-West Palm Beach, FL||2,540,304||6%||134,588||83,934||50,654||2.0%||7|
|San Jose-Sunnyvale-Santa Clara, CA||1,040,777||10%||90,559||46,767||43,792||4.2%||8|
|Riverside-San Bernardino-Ontario, CA||1,432,813||6%||76,646||42,411||34,234||2.4%||10|
|Atlanta-Sandy Springs-Roswell, GA||2,518,948||5%||115,501||91,430||24,070||1.0%||16|
|Salt Lake City, UT||683,113||8%||48,366||24,762||23,604||3.5%||17|
|San Antonio-New Braunfels, TX||1,016,734||6%||56,115||32,666||23,451||2.3%||18|
|San Diego-Carlsbad, CA||1,561,332||4%||63,050||46,390||16,660||1.1%||20|
|Minneapolis-St. Paul-Bloomington, MN-WI||1,950,479||5%||89,146||79,625||9,520||0.5%||26|
|Oklahoma City, OK||650,768||5%||31,621||24,304||7,317||1.1%||27|
|Louisville/Jefferson County, KY-IN||642,197||5%||30,139||25,529||4,610||0.7%||28|
|Tampa-St. Petersburg-Clearwater, FL||1,235,174||4%||47,393||43,218||4,174||0.3%||29|
|Las Vegas-Henderson-Paradise, NV||908,848||4%||38,177||35,801||2,376||0.3%||30|
|Kansas City, MO-KS||1,063,294||3%||34,153||36,488||-2,335||-0.2%||34|
|Hartford-West Hartford-East Hartford, CT||657,660||2%||15,900||20,086||-4,187||-0.6%||35|
|New Orleans-Metairie, LA||591,537||2%||13,165||25,765||-12,599||-2.1%||40|
|Buffalo-Cheektowaga-Niagara Falls, NY||560,419||1%||7,118||20,315||-13,196||-2.4%||42|
|Milwaukee-Waukesha-West Allis, WI||865,543||3%||22,346||39,024||-16,678||-1.9%||43|
|Virginia Beach-Norfolk-Newport News, VA-NC||865,423||1%||6,298||26,104||-19,806||-2.3%||44|
|St. Louis, MO-IL||1,401,461||2%||25,188||54,779||-29,591||-2.1%||46|
|New York-Newark-Jersey City, NY-NJ-PA||9,456,368||3%||311,413||369,489||-58,076||-0.6%||49|
For more on EMSI’s employment data — available at the county, MSA, and ZIP code level — or to see data for your region, email Josh Wright. Follow EMSI on Twitter (@DesktopEcon) or check us out on LinkedIn and Facebook.