For the past 10 years, EMSI has provided structural labor market data via Analyst, a web-based labor market analysis tool used broadly by higher education, economic development, workforce development and business professionals. For the past couple of years we have been working with CareerBuilder to develop a solid database of job posting analytics that can help to nuance our labor market information. This has been a long and painstaking process to produce data that is solid, economically defensible, and conservative insofar as it is being used to make important decisions. In July, we will start to roll out this new data in Analyst, giving our clients the ability to address a much wider variety of issues. In this article, we summarize our approach in bringing together structural LMI and job postings and walk through two examples—data for software developers and welders.
Matt Yglesias recently made an insightful comment when summarizing the jobs report for Vox: “Measuring the economy in real time is hard. Ignoring the jobs report is foolish, but overreacting is equally foolish.” Case in point: In May, The Globe and Mail and other news outlets in Canada reported on a very real world example of this. The Canadian government used what turned out to be flawed job posting data that inflated the country’s job vacancy rate and was used in part to support the creation of the $3 billion Canada Job Grant.
The Conservative government has quietly adjusted its labour data to ignore job postings from Kijiji and similar websites, a change that essentially erases the dire warnings of labour shortages that Ottawa has used as justification for expanding the controversial temporary foreign worker program. With these sites removed from the source data, the government’s latest labour market report points to a job vacancy rate of 1.5 per cent, which is dramatically less than the 4 per cent vacancy rate Finance Canada warned of on budget day.
This story makes it clear: data certainly has an ability to tell a story. In this case, data was used to tell a false story that quickly led to some poor decisions. The article points out a crucial fact about job posting information: Lots and lots of companies might be advertising for jobs, which is a great indication of “intention to hire,” but this is very different from the number of people they actually hire. If you do not understand that distinction, and are primarily looking at the number of postings being pushed across hundreds of job websites for your employment figures, you could reach some very bad conclusions from that data if it isn’t nuanced with other perspectives. Given this, what exactly is data’s legitimate role? And how do we know we are working with reliable numbers?
For professionals working in higher education, public workforce investment, economic development, and strategic workforce planning, this is an all-too-familiar issue. We are tasked with basing many (if not all of) our decisions on data. This creates a tendency to rush in too quickly—to just get one’s hands on the data without asking where the data is coming from and ideally what it is telling us. Now more than ever we must know how to balance our approach and have access to the right data for our decisions.
Over the past year, we have spent a good deal of time discussing what defines a job and the differences between jobs from a labor market perspective and jobs from a hiring/recruitment perspective. The two perspectives are bolstered by two primary and very different datasets.
1. Structural LMI – Structural labor market data or information (LMI) helps us understand the total employment picture across all industries and occupations. It is data on people who are currently employed in specific industries and occupations, and it comes from government sources such as the Bureau of Labor Statistics and Census Bureau. These sources collect data via administrative records from employers (the BLS’s QCEW, for example, includes all workers covered by unemployment insurance), information from tax returns, or surveys. Most of this data is required to be reported to the government but also can lag six months to a year. The data is standardized across the entire nation, allowing researchers to perform in-depth analysis of our huge economy.
2. Job Postings – This is sometimes referred to as “real-time labor market data,” but we discourage the term because job postings really aren’t that representative of what is going on in the total labor market, real time or otherwise. Rather, job posting data is a metric for measuring job advertisements, and is therefore best used as an indicator of intention to hire or of the skills sought by employers. Data on hires and separations, known as job churn, is an excellent complement to job postings. Specifically, hires help us bridge the gap between structural LMI and job postings. A hire is counted whenever someone shows up on a company’s payroll when they didn’t show up in the previous quarter. EMSI’s data on hires is informed by Quarterly Workforce Indicators (QWI), an actual headcount of hirings that have taken place. (For more, read our comparison of QWI and JOLTS).
Our goal is to use both of these datasets, combining a strategic perspective about the structural economy with more tactical data about intention to hire in the labor market. If the essence of analysis is comparison, then these two datasets (further strengthened by job churn data) will help us make powerful comparisons for the sake of better decisions.
What kind of comparisons? Let’s look at trends for application software developers and welders, two occupations that represent very different parts of the economy. This data comes from EMSI’s new job postings analytics report and other parts of Analyst.
Software Developers, Applications
The big picture: There are roughly 640,000 app developer jobs in the U.S. (counting employees and self-employed workers), a 14% increase since 2010 and a 23% increase since 2004. Nearly three-quarters of all app developers work in the 50 largest metros—and nearly a quarter can be found in four metros: New York, Seattle, D.C., and San Jose.
Those are some of the numbers we know by tapping into EMSI’s structural labor market data. With job posting analytics, we can also see that companies are very active in advertising jobs for app developers. The 50 largest metros had over 30,000 unique postings per month in the first part of 2014, actually down 14% from last year. And hires, while not keeping up with postings, have been robust, too: around 20,000 per month.
Note: The employment total of 464,949 shown below is for the 50 most populous metro areas; this represents 73% of all app developer jobs nationwide.
Now, here is what’s tricky about job posting data. We don’t know if 20 of these software developers got hired off of one posting or if a company made 30 postings and only hired five people. We also don’t know how many companies hired software developers without actually making a posting. The relationship here isn’t 1-to-1. (To gauge how much effort employers are putting into hiring for a position or positions, EMSI has developed a posting intensity metric; in the Baltimore MSA, where average monthly postings for app developers are up 12% from last year, the posting intensity is 65 out of 100. This indicates employers like Northrop Grumman are creating a higher-than-average number of postings.)
In addition, if we looked solely at postings, we’d see there’s a lot of activity in the nation’s biggest job markets. But we’d also see declining job posting activity from last year—which goes against the prevailing trends for app developers and almost every other computer occupation. Furthermore, if we looked only at postings, we wouldn’t catch that they outnumber hires by almost 2-to-1 (suggesting perhaps that the market can’t meet employer demand, which means the excess postings could represent real vacancies). Nor would we get a sense for the sheer number of developers in the workforce today, how the occupation has expanded over the last decade-plus, what industries employ these workers, how wages differ from region to region, among other important variables.
Welders
Compared to app developers, welders are far less represented in job postings. In the first part of 2014, the 50 largest MSAs had an average of just under 1,400 unique postings per month for welders, a 14% year-over-year increase from 2013. But the number of average monthly hires—part of job churn that’s below the surface and that EMSI now tracks—exceeded 7,000 in 2013 and early 2014.
This means that companies in the 50 most populous metros are hiring five times more welders than they’re posting for. Which makes intuitive sense if you consider that manufacturing and construction firms looking for welders aren’t as likely to post job listings online as, say, a tech company in San Jose looking for an app developer.
Houston has the most unique postings for welders, at 178 for the city and 264 for the metro area (which includes The Woodlands and Sugar Land). The Houston MSA shows an even larger ratio of hires to postings than the top 50 MSAs—there were six hires for every posting in the first part of 2014.
We can further contextualize these numbers with actual employment trends from Analyst: Houston has more than 17,000 jobs for welders, cutters, solderers, and brazers, 132% the national average and a 26% increase in employment from 2010 to 2014. That growth rate is more than two times higher than the national growth rate (12%), and median wages for welders ($18.01) in Houston are higher than the national average, too ($17.37).
Welding is a strong post-recession growth area, in Houston and nationally, with solid wages, lots of jobs and hires … and not so many job postings. Looking at one of these elements in isolation isn’t nearly as helpful as looking at all of them together.
Conclusion
EMSI’s goal is to give our customers the best, most up-to-date, and comprehensive data possible. This includes the robust structural labor market information we’ve been providing for years, as well as our new job posting analytics data that we’ve paired with job churn (the hires and separations happening below the surface). Structural LMI helps practitioners and decision-makers understand the big picture; it’s great for strategic planning. Job postings can indicate a company’s intention to hire or the skills sought by employers. They’re best used to answer four key questions:
Who’s hiring?
Who positions are employers looking for?
What skills do those people need?
How badly do employers want to hire?
For more information about EMSI’s job posting data coming in July, read our announcement and register for our webinar on July 10 at 2 p.m. EDT (11 a.m. PDT).
Have questions about the direction of EMSI data? Please contact Matt Gaither: mgaither@econmicmodeling.com. Follow EMSI on Twitter (@DesktopEcon) or check us out on LinkedIn and Facebook.