Abstract
The Fulbright program attracts applicants passionate about service and research abroad. Applicants apply to one country. To aid their decisions, competition statistics giving approximate probabilities of being awarded a scholarship are released for each country. This paper examines how competition statistics influence country choices. In aggregate, our results suggest that applicants are not swayed to apply to countries with low competition or deterred from countries with high competition. However, accounting for the difference in scholarship types and the macroeconomic context, there is strong evidence of opportunistic behavior by teaching applicants and for all applicants when the unemployment rate is high.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Notes
Other Fulbright US Student Program grants include Fulrbight-mtvU Awards to study musical culture, Fulbright Public Policy Fellowships to work in public offices alongside conducting research, and travel grants to supplement external funding for research. We do not include these programs in our research because statistics for them are unavailable.
We also perform the analysis using reported statistics only and results are similar though more difficult to interpret. In recent years, the IIE has started to present competition statistics as “Applications/Awards”, which further supports our use of reported and realized competition in our models.
While the Fulbright US Student Program sends Fulbrighters to about 140 countries, about 70 of those countries are included in “Regional Programs”. While applicants still apply to a particular country, grants are allocated on a regional basis. Statistics reported for the Regional Programs include the number of applications received for each country and the number of grants awarded and offered for the region as a whole. We compiled data for the 68 countries for which the Fulbright US Student Program provides country-specific data.
Population and GDP per capita data for Taiwan are not available from the World Bank; instead, we collected Taiwan’s data from Index Mundi.
As an alternative way to model growing or declining interest in a country, we considered using multiple lag terms for competition. However, we ultimately decided that including competition from the previous year only was the most accurate representation of signals received by potential applicants, since statistics from the previous year were the only statistics published throughout the years in our dataset.
While we believe a weighted regression is most appropriate for this regression, because it best approximates individual behavior with aggregate data, it is still worthwhile to estimate an unweighted model. Unweighted, the regression of Column 5 yields a statistically significant coefficient of −0.287 on ln(reported competition). While this result is suggestive of heterogeneity by applicant pool size, we did not find evidence of this heterogeneity in our weighted framework using models with interactions based on program size.
Although the coefficient on unemployment is insignificant, its negative sign suggests that competition decreases as unemployment increases. Further analysis of applications on unemployment and grants on unemployment tenuously suggest that both decrease when unemployment increases, but applications decrease more so.
While negative correlation between competition rates in subsequent years could appear to be mean reversion, we believe the effect is due to reported competition. First, the coefficient of interest in our preferred model is both small and insignificant. This coefficient would be non-zero and significant if mean reversion were the cause. Second, there is a significant correlation with an exogenous variable, US unemployment rate. Coefficients on exogenous variables would be insignificant in the case of mean reversion.
Another explanation for the difference in strategic application behavior between ETA and Research applicants could be the differences in language requirements. The Fulbright US Student Program either recommends or requires that applicants can speak the local language of some countries (other countries, for example Anglophone countries, do not have any language recommendation or requirement). After a cursory exploration, we could not make any conclusions about the effect of language requirements on competition. However, this was mainly limited by the size of our dataset. Future research could explore the effect of language requirements and how this effect varies between ETA and Research applicants.
References
Bar, Talia, Vrinda Kadiyali, and Asaf Zussman . 2009. Grade Information and Grade Inflation: The Cornell Experiment Journal of Economics Perspectives, 23 (3): 93–108.
Griffith, Amanda, and Kevin Rask . 2007. The Influence of the US News and World Report Collegiate Rankings on the Matriculation Decision of High-ability Students: 1995–2004. Economics of Education Review, 26 (2): 244–255.
Institute of International Education (IIE). 2013. Fulbright U.S. Student Program. Fulbright U.S. Student Program, http://eca.state.gov/fulbright (accessed July 15, 2013).
Kahneman, Daniel, Paul Slovic, and Amos Tversky . 1982. Judgment Under Uncertainty: Heuristics and Biases. New York, NY: Cambridge University Press.
Maher, Kathleen. 2012. Personal Communication, July 11.
McDonough, Patricia, Anthony Antonio, MaryBeth Walpole, and Leonor Perez . 1998. College Rankings: Democratized College Knowledge for Whom? Research in Higher Education, 39 (5): 513–537.
Monks, James, and Ronald G Ehrenberg . 1999. U.S. News & World Report’s College Rankings: Why Do They Matter. Change, 31 (6): 42–51.
Pope, Devin G. 2009. Reacting to Rankings: Evidence from “America’s Best Hospitals”. Journal of Health Economics, 28 (6): 1154–1165.
Price, Joseph . 2008. Gender Differences in the Response to Competition. Industrial and Labor Relations Review, 61 (3): 320–333.
U.S. Department of State. 2013. The Fulbright Program. Bureau of Educational and Cultural Affairs, http://eca.state.gov/fulbright (accessed July 15, 2013).
Acknowledgements
We thank Elizabeth Edmondson, Walter Jackson, Ae Rin Jung, Kathleen Maher, and Brigid Shipman for help in collecting data and understanding the Fulbright application process. We appreciate valuable comments from Amanda Griffith, Nicholas Logler, Kyle Montanio, Joe Price, and two anonymous referees. Thanks to Michelle Peach Lang for suggesting the title of the paper. This paper is a contribution of the Rhode Island Agricultural Experiment Station (#5361).
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Gill, C., Lang, C. Are Fulbright Applicants Idealists or Opportunists?. Eastern Econ J 42, 288–301 (2016). https://doi.org/10.1057/eej.2014.26
Published:
Issue Date:
DOI: https://doi.org/10.1057/eej.2014.26