Pareto Improvements in the Contest for College Admissions / Kala Krishna, Sergey Lychagin, Wojciech Olszewski, Ron Siegel, Chloe Tergiman.

Format:

Book

Author/Creator:

Krishna, Kala.

Contributor:

National Bureau of Economic Research.

Lychagin, Sergey.

Olszewski, Wojciech.

Siegel, Ron.

Tergiman, Chloe.

Series:

Working Paper Series (National Bureau of Economic Research) no. w30220.

NBER working paper series no. w30220

Language:

English

Physical Description:

1 online resource: illustrations (black and white);

Place of Publication:

Cambridge, Mass. National Bureau of Economic Research 2022.

Summary:

College admissions in many countries are based on a centrally administered test. Applicants invest a great deal of resources to improve their performance on the test, and there is growing concern about the large costs associated with these activities. We consider modifying such tests by introducing performance-disclosure policies that pool intervals of performance rankings, and investigate how such policies can improve students' welfare in a Pareto sense. Pooling affects the equilibrium allocation of studentso colleges, which hurts some students and benefits others, but also affects the effort students exert. We characterize the Pareto frontier of Pareto improving policies, and also identify improvements that are robust to the distribution of college seats.

We illustrate the potential applicability of our results with an empirical estimation that uses data on college admissions in Turkey. We find that a policy that pools a large fraction of the lowest performing students leads to a Pareto improvement in a contest based on the estimated parameters. We then conduct a laboratory experiment based on the estimated parameters to examine the effect of such pooling on subjects' behavior. The findings generally support our theoretical predictions. Our work suggests that identifying and introducing Pareto improving performance-disclosure policies may be a feasible and practical way to improve college admissions based on centralized tests.

Notes:

Print version record

July 2022.