In previous posts in this series we looked at how the nation’s largest metro areas have grouped themselves into different cohorts with very different growth trajectories. We discussed changes in the broader economy that are causing this separation and we discussed how a talented workforce is key to a metro’s economic growth. Today we will focus the types of jobs that contribute to the Great Separation.
We have two choices when looking at detailed employment data, industry based and occupation based. Industry based is most commonly used and is determined by the employer. Say I work at a large hospital. I could be a nurse, or a surgeon, but I could also be an accountant in the billing department or a food server in the cafeteria. Regardless of my actual job, I and everyone else who works at this hospital work in the health care industry.
Occupation data works in the opposite direction. If I am an accountant, I am counted as an accountant whether I work for a hospital, manufacturer or an accounting firm. Since occupation data accounts for the actual work being done, we will use it to see if there are certain types of work our top performing metros specialize in.
To measure the level of specialization in our metro areas will calculate the occupation location quotient. The location quotient simply the share of jobs in a given occupation in a metro relative to the share of jobs in the same occupation nationwide. So, for instance, if a metro has 10 percent of its jobs in sales occupations and nationally 10 percent of jobs are also in sales, that location quotient (LQ) is 1 (10 percent / 10 percent). A LQ of 1 is the national norm. A LQ greater than 1 means the metro has a specialization in that occupation. A LQ below 1 tells us the metro lacks in this occupation.
The chart below shows the location quotient for our 6 metro groups in each broad occupation category. The bigger the location value for each metro cohort, the greater the level of specialization in those occupations. Our highest performing metro cohort, the Great 8, have very high location quotients in computer-mathematical occupations and design-entertainment-sports-media. The Great 8 also lead in business-financial and architecture-engineering although the gap is much smaller.
The second cohort, the Stalwarts, also specialize in computer-math as well as management occupations.
One other outlier of note is the Middle Ground cohort’s location quotient in legal occupations of 1.43. Washington D.C. with their legal occupations LQ of 2.8 are mostly responsible for this.
The occupations that the higher performing metros specialize in (computer, engineering, design etc.) share a couple of traits.
First, most of these occupations require some specific, technical skills. They are not learn “on-the-job” occupations and would typically require post-secondary training. This aligns with our last post when we looked at education. These jobs are driving the economy where the talent level is greatest.
Secondly, these occupations are typically found in industry sectors that are traded. A traded sector is one where the customer can be anywhere in the world. If you create software, design logos or bridges you can export your good or service to the outside market and import profits (wealth). This grows your regions GDP. In contrast, jobs in the local sector primarily sell to local consumers (think restaurants, repair services or retail). The local sector is vital to the region, but it does not generally bring new dollars into the local economy.
There is a lot of data here but by way of summary, having a pool of educated, technical workers allows the top performing metros to specialize in key, traded industry sectors that export high valued goods and services and import new wealth. You can get the raw data for this analysis here.
Next up we will take a detailed look at 6 metros (one from each cohort) and see what the detailed data tells us.