Employment Opportunities for Completers of a Higher Education Program

Core Technology Services (CTS) provides secure information management and technology services to North Dakota University System students, faculty, staff, and state residents. As an employee, CTS allocates approximately half of my time to Bismarck State College (BSC) as part of a shared services contract. I devote much of that time to compliance-related reporting, but I also participate in other projects for BSC. One of those projects was the Aspen Prize for Community College Excellence. Every two years, The Aspen Institute invites 150 community colleges to apply for the Aspen Prize. I say “apply” but it’s really a contest, because the prize is a million bucks.

We had a month to complete the application before submission in early December. The application was long and the questions incisive, with the responses heavily data-driven and strictly confidential. Each question became its own research project, and considering I was three months into the job, it became a bit of baptism by fire for me.

Without breeching confidentiality, the whole experience got me thinking about the relationship between the Integrated Postsecondary Education Data System (IPEDS) Completions survey, which I completed prior to working on the Aspen Prize, and employment outcomes for students. If a student graduates with a given degree, what is the likelihood that student will find employment in his or her area of study within the state of North Dakota?

Let’s look at the data.

Conceptually, to answer the question posed, we’ll need two components: (1) graduates, and (2) job openings. Theoretically, if job openings exceed graduates in a given field for a given year, then graduates should be confident about employment in their field of study. To find these two components, we’ll look at two different sources: The U.S. Department of Education and the Bureau of Labor Statistics.

The U.S. Department of Education runs the IPEDS, a series of data collection surveys mandated for institutions of higher education participating in certain Federal financial assistance programs. A major component of the IPEDS survey is the “Completions” survey, which tracks degrees or certificates awarded in a 12-month period, organized by Classification of Instructional Program (CIP) code. In other words, IPEDS tells us how many people graduated, in what field of study, and at what level.

The Bureau of Labor Statistics (BLS) studies and curates vast amounts of labor and economic data by national, state, county, and even metropolitan areas. Apart from simply curating the data, the BLS also makes projections. Of interest is the short-term (2 year) projection for North Dakota employment.

For this analysis, we’re going to use the base year of 2018, because at the time this project began, the 2019-21 projections were unavailable. We’ll need the 2017-18 Completions Survey from IPEDS, the 2018-2020 short term employment projections for North Dakota from the BLS, and the North Dakota Employment Projections 2016-26, also from the BLS. We require the latter because it provides additional information about entry level education requirements which the short-term employment projections do not. Since the occupations are coded differently with IPEDS using CIP codes and the BLS using Standard Occupational Classification (SOC) codes, we’ll need a fourth document called an “SOC-CIP Crosswalk,” available from the BLS.

First, a few limitations on this analysis. This is the view from 30,000 feet; certain factors, such as job location or years of experience required, lie beyond the scope of this analysis. The hope is to provide a few data-driven resources for the interested student or prospective student. Another limitation is in the coding of individual CIP programs and SOC job codes. These codes are ultimately a matter of human judgment. While guidance exists, the interpretation of the guidance ultimately comes down to a human decision. Additionally, the SOC-CIP Crosswalk is a “one to many” match, meaning that one SOC code might match to numerous CIP code. Let’s take the example of “General and Operations Managers.” See table 1 below:

Clearly, this SOC code covers a broad spectrum of managerial occupations, ranging from public administration to international business, and it’s impossible to say from the data provided by the BLS how many of the 640 projected openings should be attributed to each CIP code. But we can make an approximation using a simple allocation. Given the six CIP Codes associated with this SOC Code, we can divide the projected openings by the total CIP Codes for our allocation . See the table 2 below:

There are some obvious problems with the table above. For example, are there truly 315 fewer jobs than graduates for Business Administration and Management graduates? Probably not. But, keep in mind, we are looking at 1 out of 360 SOC codes from the BLS projection, and the CIP code for Business Administration and Management occurs 12 times in the projection. Given the duplication of the CIP codes, we require an allocation to avoid duplicating the projected job openings. The size of the data set helps to mitigate some of these issues, particularly when aggregating CIP codes into larger subgroups.

For example, Table 3, below, shows us the sum of allocated projected job openings across all SOC codes for the Business Administration and Management related CIP codes.

Even with the aggregated data, we’re seeing the limitations in CIP/SOC coding, cross-walking, and allocations creep in. For instance, CIP Code 52.0101, “Business/Commerce, General”, shows 271 job openings for 2 completers, while “Business Administration, Management and Operations, Other.” shows no job openings for 90 completers; however, in the aggregate, we’re seeing an excess of 210 projected jobs over completers. Granted, not all job openings cater to entry level job seekers, but for a student interested in graduating and moving directly into the workforce, Business Administration and Management seems like a promising area of study.

What about my area of study, Accountancy? See table 4 below.

Here, we’re seeing a more uniform one to many match than in Table 1. But we’re also seeing the coding limitations mentioned where Accounting and Finance shows a excess of projected jobs while Accounting is more or less equal in projected jobs versus graduates; however, if we aggregate Accounting as we did with Business Administration and Management, we see 220 completers for 420 projected yearly openings. Again, this seems like a promising area for the interested student.

Certain projections need careful interpretation. For example, consider completers of a bachelor’s degree in Psychology in Table 5 below.

On the face of it, table 5 doesn’t look very promising for job seekers. But as they say, the devil is in the details. Let’s look at table 6 which compares projected openings for Substance Abuse and Behavioral Disorder Counselors with completers.

Here we see that a student who is willing to diverge somewhat from a bachelor’s degree in Psychology – while remaining engaged in that field – faces a much more open job market following graduation. But what of those students with their hearts set on psychology? Let’s look at Table 7.

This table shows the excess of master’s level counseling job openings over 2018 completers of master’s level programs. Upon further analysis, it appears completers of a bachelor’s degree in Psychology (or another relevant prerequisite) who persist to the master’s level of completion enter a job market with ample employment opportunities. In fact, this table may understate the actual demand, because the BLS 2018-20 employment projections estimate an additional 20 job openings for SOC Code 21-1019, “Counselors, All Other,” which I did not include because I was unable to verify the education requirements with the BLS. Also, note the difference for Social work is only as it relates to SOC Code 21-1013, “Marriage and Family Therapists.”

While working on the Aspen Prize for BSC, I planned to put together an analysis of IPEDS and BLS data across the entire North Dakota University System. I hoped to assemble some data-driven resources that could help students and prospective students navigate the transition from student to worker.

That was six months ago.

As the COVID-19 pandemic swept across the world, governments responded by shutting down vast sectors of the economy to stop the spread of the virus. Social distancing became a household term overnight. Restaurants, bars, moving theatres, sporting events and many other businesses effectively shuttered until further notice. Everyone who could work from home, worked from home. Millions were laid off.

Now, as I sit in my basement, working from home and social distancing, it’s unclear what the future holds – except that the employment projections (and by extension my analysis) are certainly unreliable considering the economic upheaval we’re witnessing. Nevertheless, when we overcome this crisis, we’ll have new projections and a new analysis that helps future students make informed decisions.

Employment and Education resources used in this research:

Leigh Jacobs joined NDUS Core Technology Services as an Institutional Data Analyst in August of 2019. A native of Bismarck, North Dakota, he graduated from the University of Mary with a bachelor’s degree in Accounting before embarking on a career as an auditor. It was his role as a government compliance auditor that exposed him to data analytics. Learning how auditors were applying statistical analysis to Medicaid fraud detection helped him apply similar techniques to the field of oil and gas compliance auditing. He hopes to build on this foundation of data analytics throughout his career with the North Dakota University System.