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Math or Science? Using Longitudinal Expectations Data to Examine the Process of Choosing a College Major

  • Todd R. Stinebrickner
  • Ralph Stinebrickner

Due primarily to the difficulty of obtaining ideal data, much remains unknown about how college majors are determined. We take advantage of longitudinal expectations data from the Berea Panel Study to provide new evidence about this issue, paying particular attention to the choice of whether to major in math and science. The data collection and analysis are based directly on a simple conceptual model which takes into account that, from a theoretical perspective, a student's final major is best viewed as the end result of a learning process. We find that students enter college as open to a major in math or science as to any other major group, but that a large number of students move away from math and science after realizing that their grade performance will be substantially lower than expected. Further, changes in beliefs about grade performance arise because students realize that their ability in math/science is lower than expected rather than because students realize that they are not willing to put substantial effort into math or science majors. The findings suggest the potential importance of policies at younger ages which lead students to enter college better prepared to study math or science.

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File URL: http://www.nber.org/papers/w16869.pdf
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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 16869.

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Date of creation: Mar 2011
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Handle: RePEc:nbr:nberwo:16869
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  1. Cunha, Flavio & Heckman, James & Navarro, Salvador, 2004. "Separating uncertainty from heterogeneity in life cycle earnings," Working Paper Series 2005:6, IFAU - Institute for Evaluation of Labour Market and Education Policy.
  2. MONTMARQUETTE, Claude & CANNINGS, Kathy & MAHSEREDJIAN, Sophie, 1997. "How do Young People Choose College Majors?," Cahiers de recherche 9719, Universite de Montreal, Departement de sciences economiques.
  3. Todd Stinebrickner & Ralph Stinebrickner, 2001. "Time Use and College Outcomes," University of Western Ontario, Centre for Human Capital and Productivity (CHCP) Working Papers 20012, University of Western Ontario, Centre for Human Capital and Productivity (CHCP).
  4. J. Dominitz & C. F. Manski, . "Eliciting student expectations of the returns to schooling," Institute for Research on Poverty Discussion Papers 1049-94, University of Wisconsin Institute for Research on Poverty.
  5. Ralph Stinebrickner & Todd Stinebrickner, 2008. "The Effect of Credit Constraints on the College Drop-Out Decision: A Direct Approach Using a New Panel Study," American Economic Review, American Economic Association, vol. 98(5), pages 2163-84, December.
  6. Arcidiacono, Peter, 2004. "Ability sorting and the returns to college major," Journal of Econometrics, Elsevier, vol. 121(1-2), pages 343-375.
  7. Todd Stinebrickner & Ralph Stinebrickner, 2012. "Learning about Academic Ability and the College Dropout Decision," Journal of Labor Economics, University of Chicago Press, vol. 30(4), pages 707 - 748.
  8. J. Dominitz & C. F. Manski, . "Using expectations data to study subjective income expectations," Institute for Research on Poverty Discussion Papers 1050-94, University of Wisconsin Institute for Research on Poverty.
  9. Peter Arcidiacono & V. Joseph Hotz & Songman Kang, 2010. "Modeling College Major Choices using Elicited Measures of Expectations and Counterfactuals," NBER Working Papers 15729, National Bureau of Economic Research, Inc.
  10. Basit Zafar, 2009. "How do college students form expectations?," Staff Reports 378, Federal Reserve Bank of New York.
  11. Jeff Dominitz & Charles F. Manski, 2003. "How Should We Measure Consumer Confidence (Sentiment)? Evidence from the Michigan Survey of Consumers," NBER Working Papers 9926, National Bureau of Economic Research, Inc.
  12. Carneiro, Pedro & Hansen, Karsten & Heckman, James, 2003. "Estimating distributions of treatment effects with an application to the returns to schooling and measurement of the effects of uncertainty on college choice," Working Paper Series 2003:9, IFAU - Institute for Evaluation of Labour Market and Education Policy.
  13. Jeff Dominitz & Charles F. Manski, 2004. "How Should We Measure Consumer Confidence?," Journal of Economic Perspectives, American Economic Association, vol. 18(2), pages 51-66, Spring.
  14. Jeff Dominitz, 1998. "Earnings Expectations, Revisions, And Realizations," The Review of Economics and Statistics, MIT Press, vol. 80(3), pages 374-388, August.
  15. F. Thomas Juster, 1966. "Consumer Buying Intentions and Purchase Probability: An Experiment in Survey Design," NBER Books, National Bureau of Economic Research, Inc, number just66-2, March.
  16. Blass, Asher & Lach, Saul & Manski, Charles, 2008. "Using Elicited Choice Probabilities to Estimate Random Utility Models: Preferences for Electricity Reliability," CEPR Discussion Papers 7030, C.E.P.R. Discussion Papers.
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