Students and policymakers alike are calling for more data on former students’ labor market outcomes, such as post-college employment and earnings. The Obama Administration, U.S. Congress, and state governments are all tackling this issue.

The U.S. Department of Education’s updated College Scorecard includes—for the first time—median earnings for former students of particular institutions. A growing number of states have created websites that display the earning and employment outcomes of students in specific programs of study at specific degree levels. In addition, legislation introduced in Congress would create a student-level data collection that includes employment and earnings. The next few years may provide an important window for policy related to employment and earnings data.

As these data become more readily available, lawmakers may be tempted to use it to hold institutions accountable for students’ results in the labor market. This accountability could occur at the state level through outcomes-based funding or at the federal level, possibly by tying outcomes to Title IV eligibility. In principle, measuring outcomes over inputs is a positive development. However, without a strong policy foundation, this could create incentives to reduce access for low-income and underprepared students and unduly punish the open-access institutions that serve them.

In this new paper, CLASP recommends that post-college earnings data not be used for accountability at the institution level without taking into account differences between programs of study or college majors, student characteristics and institutional missions, variation in regional economies, students’ various college and employment pathways, and institutions’ mix of programs. This paper, informed by postsecondary education practitioners and workforce educators who are particularly attuned to the importance of post-college outcomes, presents five recommendations that policymakers should follow before they consider using earnings for high-stakes accountability purposes:

1)  Use program-level, not institution-level, data;

2) Take participant characteristics and/or institutional missions into account;

3) Index earnings to regional wage and economic benchmarks;

4) Disaggregate completers from non-completers; and

5) Take into account the social good of programs that may have low wages.

Each recommendation has its challenges, and more work is needed to identify the best approaches. However, if these five issues are not addressed, policymakers should strongly consider excluding earnings metrics from any accountability formula or framework.

Read the paper >>