Indiana University SPEA Edward J. Bloustein School of Planning and Public Policy University of Pennsylvania AIR American University

Panel: College Choice and Major Choice

Friday, November 13, 2015: 8:30 AM-10:00 AM
Tuttle Center (Hyatt Regency Miami)

*Names in bold indicate Presenter

Panel Organizers:  Peter Hinrichs, Federal Reserve Bank of Cleveland
Panel Chairs:  Peter Hinrichs, Federal Reserve Bank of Cleveland
Discussants:  Jeffrey Smith, University of Michigan and Mark Long, University of Washington

Should Community College be Free? Supply and Demand in the Market for U.S. Higher Education
David Deming, Harvard University and Christopher Walters, University of California, Berkeley

Match or Mismatch? the Role of College Readiness, High School Peers, and Application Uncertainty on College Application Behavior
Kalena E. Cortes1, Sandra E. Black2 and Jane Lincove2, (1)Texas A&M University, (2)University of Texas, Austin

College Major Choices and Transitions Among First Generation Students
C. Lockwood Reynolds, Kent State University

Price Deregulation and Equality of Opportunity in Higher Education: Evidence from Tuition Deregulation in Texas
Rodney Andrews, University of Texas at Dallas and Kevin Stange, University of Michigan

This session would feature four papers on the issue of how students select which college to attend and the related issue of how students select their college major. The papers make use of a variety of data sets, settings, and methodologies, but they are united in their general topic of study and in their relevance for policy. The paper by David Deming and Christopher Walters uses data from the Integrated Postsecondary Education Data System (IPEDS) to estimate the effects on college enrollment choice and degree completion of (a) the price colleges charge students and (b) the amount of money colleges spend. When faced with limited resources, colleges may opt to either raise their prices or lower their spending. An important question for policy is which of these options would have less of an adverse impact on educational outcomes for students. The authors tackle this question with an identification strategy that makes use of variation in states’ budget situations and variation in tuition caps, and they find that spending by a college has a larger impact on enrollment and degree attainment than does an equivalent change in price. The paper by Sandra Black, Kalena Cortes, and Jane Arnold Lincove makes use of administrative data from Texas to study the determinants of college choice, focusing on the issue of the “match” between students and colleges. The authors estimate conditional logit models of college choice that takes into account a large variety of potential determinants of college choice. They are also able to exploit the Texas 10% Plan, which guarantees admission to any public university in the state to students who are in the top 10% of their high school, to study a group of students who would be automatically admitted to a certain set of colleges. The paper by Lockwood Reynolds also makes use of administrative data but shifts the focus from college choice to college major choice. This paper focuses specifically on first-generation college students. The author uses a large data set from an unnamed university to study how a variety of student-level characteristics affect major choice. The author is also able to study how characteristics of the various majors affect entrance into those majors. The paper by Rodney Andrews and Kevin Stange uses administrative data from Texas to study the impact of tuition on college choice and college major choice. Texas formerly gave the state legislature the authority to set college tuition within the state, but that authority is now delegated to individual institutions. Institutions also have the ability to charge different tuition levels for different majors. This policy change in Texas provides the variation necessary to estimate the effects of tuition on college choice and also on major choice. The authors do this with difference-in-differences models that compare programs with different tuition levels and also compare poor students to non-poor students. The session is diverse with respect to institutional affiliation, gender, and race/ethnicity and includes a mix of newer and seasoned APPAM participants.
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