Research & Planning Home | WE Connect | Contact

Consumer Reports: Wyoming Career Assist

Employment, Earnings, and Hours Worked Five Years Before and Five Years After Graduation by Programs of Study


Customer cost and time investment make decisions about postsecondary enrollment among the most important in the lives of many people and their families. Many factors may influence an individual’s decisions regarding postsecondary education: what to study, where to enroll, and the level of degree to obtain. However, what is frequently unavailable to facilitate choice is information about the formal education process and the world of work most people enter coincidentally, and information about post-graduation employment and earnings. Forming reasonable expectations about the context of the education and work experience is essential to realistic strategies for educational success and goes well beyond information in the course catalogue. Currently in Wyoming, very few sources exist that link education and labor market outcomes. The Research & Planning (R&P) section of the Wyoming Department of Workforce Services produces reports in tabular and interactive graphic form, and supporting documentation allowing customers to better understand a great deal more about the career pathways between work and education leading to a greater probability of success in their chosen field of study.

With such an abundance of data provided in the tables, some fields and variables may be unclear to users; this introduction aims to provide explanation of the tables and decisions made during their development.

Background Discussion, What the Data Measure, and How They Can be Used

How important is pre-graduation work experience to the probability of post-graduation work in a field for which individuals trained? What proportion of students finance their education with work? How much do they work, and does work impede graduation? The first step in answering these and other complex questions involves assembling the relevant data and describing how work, training, and education fit together. As individuals progress from young adulthood into postsecondary education and the labor market, the alternative pathways available make measuring progress more complicated than it may first appear.

There is a growing body of literature describing the interaction between employment and participation in formal education and training programs. Typically, market outcomes are measured using worker earnings as reported to the state Unemployment Insurance (UI) program. Workers earn quarterly wage credits, which determine their eligibility for UI weekly benefit payments should they become unemployed. Quarterly wage credits are referred to as wage records.

Wage records in most states represent the level of compensation during a calendar quarter rather than a more familiar measure of earnings, such as an hourly rate of pay or monthly salary. Consequently, because the hire date and exit date from jobs can occur at any time during the quarter, the interpretation of wage records earnings measures is less than straightforward. When the goal for training programs is to earn a clearly defined family-sustaining wage, near term post-training wage records earnings levels prove difficult to interpret because people enter and leave jobs within a quarter, rather than at the beginning or end. One solution to the problem of interpretation is to focus on earnings with the same employer over a longer period of time; another solution is to develop or collect information on rates of compensation as part of administrative employment records.

The tabulations and interactive graphics referenced in this report include earnings using wage records, as well as hourly rates of compensation and the median number of hours worked per quarter. The availability of rates of compensation not only yields a more customary measure, it also allows us to ascertain the extent to which earnings change over time as individuals add human capital through maturity and as they shift hours from time spent in the classroom to time spent employed.

Researchers, and sometimes individuals and organizations with little formal education in the social and behavioral sciences, are increasingly accessing wage records, linking them to student files, and publishing average earnings post-training results. Often these calculations are carried out without reference to the socioeconomic context or human capital assets of training participants, leaving the results uninterpretable except by those whose imaginations are unimpeded by the possession of a relevant academic discipline. The tabular data presented along with earnings outcomes, such as post-graduation industry of employment, are among the most relevant contextual factors in establishing what outcomes mean. However, these tables by themselves are inadequate to anticipating future outcomes.

This report introduces consumers to tabulations and interactive graphics (see Figure 1) of student outcomes and pre-graduation work experiences. Popular terms refer to these longitudinal measures as the labor supply pipeline or components of career pathways. However they are referenced, what is clear is that most people work in their pre-graduation school years. As can be seen on page 160 of the table for the University of Wyoming 2008/09, 2009/10, & 2010/11 cohort, 73.7% of graduates with a bachelor’s degree worked a UI covered job for at least some time four years prior to graduation. For awards involving an older population of graduates, even greater proportions are found working. For the cohort of UW graduates in Dental Support Services and Allied Professions (CIP 5106), 56.9% were age 25 or older at the time of graduation and 80.4% were found working four years prior to graduation. Whether pre-graduation work experience (or on-the-job training, as can be seen in the tabular data) is highly important to post-graduation outcomes can be determined by forms of analysis beyond the descriptive tables presently available. However, it is clear that the work to date to bring the variables together in one data set is a pre-cursor to that analysis.

Because of the relatively small number (N) of students who graduate from a postsecondary education institution in Wyoming, graduates from three consecutive school years have been aggregated to form cohorts, such as the 2008/09, 2009/10, & 2010/11 cohort (see Box). Combining school years allows R&P to disclose more information and also see trends in the data over time that a small sample size (n) may not display. For example, as can be seen in the tables, where n is large, hours worked and the average hourly rate progress in a reasonable manner over time. On the other hand, when n is small, change over time is much more likely subject to rand, erratic, and inexplicable events from one period to the next.

Using the tables to make decisions about a course of study is complicated by the fact that some variables, such as gender and out-migration, are highly (non-randomly) associated with selected courses of study. What may be a reliable outcome for one gender may not be a reliable outcome for another. Moreover, it is also apparent that graduation by itself is not sufficient for the achievement of a particular outcome in the market. Graduates with a nursing degree who work in retail trade earn far less than graduates working in health care. Some fields of study require migration out of Wyoming to attain the highest level of earnings. Graduation by itself is insufficient to understanding employment and earnings outcomes, since it is clearly not the only associated variable. Confidently predicting the outcome of an educational pursuit is further complicated when the economy is neither as robust nor diversified as we would wish it to be. There are some steps which can be taken to add certainty to the decision making process. The primary link between the tables and greater certainty is the industry of employment following graduation (and secondarily, geographic location).

Tables of employment and earnings by industrial sector are published each calendar quarter by county.  These tables can be used to plot local trend lines in employment sectors that employ graduates. Links to these tables can be found at http://doe.state.wy.us/LMI/toc_202.htm and https://www.bls.gov/cew/.

To better understand the outcomes of training programs in the workforce, the Bureau of Labor Statistics and the National Center for Education Statistics developed a Classification of Instructional Programs (CIP) to Standard Occupational Classification (SOC) crosswalk1. The crosswalk allows users to explore the different training programs available and the occupations for which the training programs prepare students. Students and postsecondary education institutions may also make decisions based on the characteristics of the occupations, such as employment and average wage, associated with selected CIP codes. Occupations are matched to CIP codes using crosswalks to understand the occupational outcomes of students who graduated from different degree programs. The CIP to SOC crosswalk can be found at https://www.bls.gov/soc/soccrosswalks.htm.

Occupational Employment Statistics (OES) provide additional data to understand student outcomes. An occupation refers to a specific task or set of job tasks. Consider the occupation of roustabouts, oil & gas. The Standard Occupational Classification (SOC) manual defines the occupation as follows: “assemble or repair oil field equipment using hand and power tools. Perform other tasks as needed” (Office of Management & Budget, 2000, p. 173). A single occupation may be present in a variety of industries. For example, accountants, in addition to working in accounting firms, may also work for mining companies, hospitals, state or local government, and a host of other industries. Staffing patterns within industries can also provide more information for students on the differences in employment and wages of occupations among the different industries. Information on how occupations differ among industries can be found at http://doe.state.wy.us/LMI/
and other OES data can be found at http://doe.state.wy.us/LMI/OES_toc.htm and https://www.bls.gov/oes/.

Long- and short-term industry and occupational projections predict trends on industry or occupational future demand. Projections are useful when examining future growth or contraction of specific industries and occupations in Wyoming. Considering projections while examining data from R&P’s student outcome tables from five years prior to graduation and five years after graduation allows users a more advanced understanding of the results of decisions made regarding what to study in postsecondary education. For example, a substantial increase in annual wages occurs for Petroleum Engineers (CIP 1425) in all industries one year after graduation. This may appear to be an occupation that students should pursue to earn high wages; however, according to the 2014-2024 long-term occupational projections, the number of petroleum engineers in Wyoming is expected to decline by 120 jobs by 2024. Students who pursue petroleum engineering may be required to go out of state to find employment in their chosen field. The industry and occupational projections and articles discussing the projections can be found at http://doe.state.wy.us/LMI/projections.htm.

1National Center for Education Statistics and Bureau of Labor Statistics. (2011, March). Guidelines for Using the CIP-SOC Crosswalk. Retrieved January 25, 2017, from https://nces.ed.gov/ipeds/cipcode/resources.aspx?y=55 

This workforce product was funded by a grant awarded by the U. S. Department of Labor’s Employment and Training Administration. The product was created by the grantee and does not necessarily reflect the official position of the U. S. Department of Labor. The U. S. Department of Labor makes no guarantee, warranties, or assurances of any kind, express or implied, with respect to such information, including any information on linked sites and including, but not limited to, accuracy of the information or its completeness, timeliness, usefulness, adequacy, continued availability, or ownership. This product is copyrighted by the institution that created it. Internal use by an organization and/or personal use by an individual for non-commercial purposes is permissible. All other uses require the prior authorization of the copyright owner.


Definitions of Variables Used in the Five Year Pre- & Post-Graduation Tables

In order to provide the most information about graduates’ courses of study and at the same time preserve student confidentiality, each student cohort consists of three academic years combined. For example, the earliest cohort available in the tables graduated during the 2007/08, 2008/09, & 2009/10 academic years and the latest graduated during the 2012/13, 2013/14 & 2014/15 academic years. Combining the three school years allows R&P to minimize the problems of a small N and better see trends in the data over time. The tables provide information on the number of degrees awarded instead of the number of individuals with an award; therefore a student that obtained more than one degree during the cohort academic years is counted more than once.

The tables count degrees awarded at the University of Wyoming (UW), and the community colleges as a whole, and the community colleges as individual colleges. The tables then show student data by degree level. The degrees in the tables with UW data include Bachelor’s degree (page 1), Masters/Doctorate/Professional degree (page 110), and Post-Bachelor’s Certificate (page 152).

The categories of degree level used for the community colleges include Academic, Occupational 1 Year, and Occupational 2 Year. An Academic degree is one that prepares students to transfer into a four-year program and work towards obtaining a bachelor’s degree and beyond (example on page 1) while an Occupational degree prepares the student to go directly into the workforce upon graduation (examples on page 95 and page 148). For example, graduates with a degree in education from a community college may transfer to UW and continue with school to get a bachelor’s degree while a graduate with a degree in welding may go directly into the workforce.

The Box below contains additional definitions of variables used in the tables.

Box: Definitions of Variables Used in the Five Year Pre- & Post-Graduation Tables
Year Relative to Graduation
The number of four-quarter groupings prior to and following graduation. E.g. If an individual graduates in May 2007 (2007Q2) then 1 year relative to graduation includes 2007Q3, 2007Q4, 2008Q1, and 2008Q2.
Degrees Awarded
The number of degrees obtained in a CIP code by the cohort at graduation. E.g. the number of degrees obtained during the 2007/08, 2008/09, & 2009/10 academic years.
% Female
The percentage of degrees awarded to females in the cohort at graduation. E.g. the percentage of degrees obtained by females during the 2007/08, 2008/09, & 2009/10 academic years.
% Age 25+
The percentage of degrees awarded to individuals aged 25 or older in the cohort at graduation. E.g. the percentage of degrees obtained by students age 25 and older during the 2007/08, 2008/09, & 2009/10 academic years.
The number of degrees matched to wage records in the year relative to graduation. An individual with more than one degree in the CIP and academic years will be matched to wage records the same number of times as degrees. This variable is listed for Wyoming & Partner States, Wyoming Only, and Partner States Only.
The percentage of degrees matched to wage records in the year relative to graduation. An individual with more than one degree in the CIP and academic years will be matched to wage records the same number of times as degrees. This variable is listed for Wyoming & Partner States, Wyoming Only, and Partner States Only.
Annual $
The annual median wage of degrees matched to wage records in the year relative to graduation. An individual with more than one degree in the CIP and academic years will be matched to wage records the same number of times as degrees. This variable is listed for Wyoming & Partner States, Wyoming Only, and Partner States Only. All wages are in 2015 real dollars, they have been adjusted to remove the effects of changes in prices and living conditions over the 10 year period.
Hourly $
The imputed median hourly wage of degrees matched to wage records in the year relative to graduation. An individual with more than one degree in the CIP and academic year will be matched to wage records the same number of times as degrees. This data is only available for the Wyoming workforce. All wages are in 2015 real dollars, they have been adjusted to remove the effects of changes in prices over the 10 year period.
Hrs Worked/ Quarter
The imputed average number of hours worked per quarter of degrees matched to wage records in the year relative to graduation. An individual with more than one degree in the CIP and academic year will be matched to wage records the same number of times as degrees. These data are only available for the Wyoming workforce. A person who works 520 hours is considered full-time.
CIP Code
A code system maintained by the National Center for Education Statistics (NCES) categorized by two-, four-, and six-digit levels of instructional programs. The purpose of the classification system is to support the accurate tracking, assessment, and reporting of fields of study and program completions activity. A complete listing of CIP codes can be found at https://nces.ed.gov/pubs2002/cip2000/.
Example of CIP Code Structure
2-Digit CIP: 510000 Health Professions and Related Programs
4-Digit: 510200 Communication Disorders Sciences and Services
6-Digit: 510204 Audiology/Audiologist & Speech Language Pathology/Pathologist
4-Digit: 513800 Registered Nursing, Nursing Administration, Nursing Research, & Clinical Nursing
6-Digit: 513801 Registered Nursing/Registered Nurse
In general, an industry refers to the type of firm for which a person works. Rather than grouping according to the final product or service, the North American Industry Classification System (NAICS*) categorizes firms based on production process. However, the final product or service is usually similar for establishments within an industry. NAICS code structure has a similar 2-Digit, 4-Digit, 6-Digit structure as CIP codes, however the UW/Community College student outcome tables only use the 2-Digit NAICS codes.
Example of NAICS Code Structure
2-Digit NAICS: 620000 Health Care and Social Assistance
4-Digit NAICS: 621000 Ambulatory Health Care Services
5-Digit NAICS: 62111 Offices of Physicians
6-Digit NAICS: 621111 Offices of Physicians (except Mental Health Specialists)
6-Digit NAICS: 621112 Offices of Physicians, Mental Health Specialists
Primary Industry
The industry in which an individual earned the highest wages during the reference quarter. Individuals may work in more than one industry, but their primary industry is the one in which they had the highest wages.
Partner States
Partner States are states with which R&P has a data sharing agreement and include Alaska, Colorado, Idaho, Montana, Nebraska, New Mexico, Ohio, Oklahoma, South Dakota, Texas, and Utah. A map of Wyoming and Partner States can be found at http://doe.state.wy.us/LMI/education_we_connect/Figure_1.png. An individual may work in two states in the reference quarter. The state in which they are counted is the one in which they earned the highest wages.


Tables and Figures

Outcomes by College, Degree Type, CIP Code, Area of Employment, and Year of Graduation

Updated July 14, 2017

Outcomes by Gender
Updated June 9, 2017

Previously Published Tables and Figures