A Bayesian Model of Choice among Higher Education Institutions

by Stephen J. Carroll, Daniel A. Relles

Download

Download eBook for Free

FormatFile SizeNotes
PDF file 1.5 MB

Use Adobe Acrobat Reader version 10 or higher for the best experience.

Purchase

Purchase Print Copy

 FormatList Price Price
Add to Cart Paperback46 pages $20.00 $16.00 20% Web Discount

Addresses the problem of modeling students' choices among institutions of higher education. This study offers a methodological approach which obviates certain difficulties encountered in previous studies, where the primary tool of analysis has been conditional logit. A parametric model for P(j;i), the probability that student i chooses institution j is developed: the parameters of P(i;j), the distribution of student characteristics at institution j, are estimated via ordinary linear regression; Bayes' Theorem is then used to invert this. The regression models describe student ability, income, and distance from home as functions of the characteristics of chosen institutions. The approach is demonstrated with data that have been used in previous studies. The results show this model to have substantially greater predictive power than existing conditional logit models, while also being easier to use, more flexible, and less expensive to apply.

This report is part of the RAND Corporation report series. The report was a product of the RAND Corporation from 1948 to 1993 that represented the principal publication documenting and transmitting RAND's major research findings and final research.

Permission is given to duplicate this electronic document for personal use only, as long as it is unaltered and complete. Copies may not be duplicated for commercial purposes. Unauthorized posting of RAND PDFs to a non-RAND Web site is prohibited. RAND PDFs are protected under copyright law. For information on reprint and linking permissions, please visit the RAND Permissions page.

The RAND Corporation is a nonprofit institution that helps improve policy and decisionmaking through research and analysis. RAND's publications do not necessarily reflect the opinions of its research clients and sponsors.