RESEARCH PAPER
Student Mobility and Sorting of Students
| 1 | Institute of Economics, Polish Academy of Sciences, Poland |
| 2 | Centre for Economic Performance, London School of Economics and Political Science, United Kingdom |
CORRESPONDING AUTHOR
Submission date: 2020-05-01
Final revision date: 2020-07-17
Acceptance date: 2020-07-21
Publication date: 2020-09-30
GNPJE 2020;303(3):5–34
KEYWORDS
JEL CLASSIFICATION CODES
ABSTRACT
This study investigates whether improving student mobility leads to greater sorting of students between schools and classes. I isolate an exogenous change in student mobility using the two-stage design of the Polish comprehensive education system and differences in school density across geographic areas. I construct a novel measure of student homogeneity based on Raven’s Progressive Matrix test score. One finding is that higher mobility leads to greater sorting of students between schools. Another, more novel, result shows that mobility also leads to higher sorting within a school (across classes). I provide suggestive evidence that demand for peer quality among students motivates school principals to create selective tracks within comprehensive schools.
REFERENCES (38)
1.
Ajayi Kehinde F. [2012], School Choice and Educational Mobility, Unpublished Working Paper, Boston University.
2.
Angrist J. D., Pathak P. A., Walters Ch. R. [2011], Explaining charter school effectiveness, Technical Report, National Bureau of Economic Research.
3.
Betts J. R., Shkolnik J. L. [2000], Key difficulties in identifying the effects of ability grouping on student achievement, Economics of Education Review, 19 (1): 21–26.
4.
Böhlmark A., Holmlund H., Lindahl M. et al. [2015], School choice and segregation: Evidence from Sweden, Technical Report.
5.
Brouwers S. A., Van de Vijver F. JR, Van Hemert D. A. [2009], Variation in Raven’s Progressive Matrices scores across time and place, Learning and Individual Differences, 19 (3): 330–338.
6.
Burris C. C., Allison K. E. [2013], Review of “Does sorting students improve test scores?”, Boulder, CO: National Education Policy Center.
7.
Card D., Rothstein J. [2007], Racial segregation and the black-white test score gap, Journal of Public Economics, 91 (11): 2158–2184.
8.
Chetty R., Friedman J. N., Rockoff J. E. [2014], Measuring the Impacts of Teachers I: Evaluating Bias in Teacher Value-Added Estimates, The American Economic Review, 104 (9): 2593–2632.
9.
Clotfelter Ch.T, Ladd H. F., Vigdor J. [2005], Who teaches whom? Race and the distribution of novice teachers, Economics of Education Review, 24 (4): 377–392.
10.
Collins C. A., Li Gan [2013], Does sorting students improve scores? An analysis of class composition, Technical Report, National Bureau of Economic Research.
11.
Dolata R. [2008], Szkoła, segregacje, nierówności, Wydawnictwo Uniwersytetu Warszawskiego.
12.
Duflo E., Dupas P., Kremer M. [2011], Peer effects, teacher incentives, and the impact of tracking: Evidence from a randomized evaluation in Kenya, The American Economic Review, 101 (5): 1739–1774.
13.
Epple D., Romano R. E. [1998], Competition between private and public schools, vouchers, and peer-group effects, American Economic Review: 33–62.
14.
Figlio D. N., Page M. E. [2002], School choice and the distributional effects of ability tracking: does separation increase inequality?, Journal of Urban Economics, 51 (3): 497–514.
15.
Friedman M. [1995], The role of government in education, Rutgers University Press.
16.
Friedman W. H., Lucas A. M. [2017], The importance of information targeting for school choice, American Economic Review, 107 (5): 638–43.
17.
Gibbons S., Machin S., Silva O. [2008], Choice, competition, and pupil achievement, Journal of the European Economic Association, 6 (4): 912–947.
18.
Herbst M., Herczyński J., Levitas A. [2009], Finansowanie oświaty w Polsce: diagnoza, dylematy, możliwości, Wydawnictwo Naukowe Scholar.
19.
Hoxby C. M. [2000], Does competition among public schools benefit students and taxpayers?, American Economic Review: 1209–1238.
20.
Hsieh Ch.‑ T., Urquiola M. [2006], The effects of generalized school choice on achievement and stratification: Evidence from Chile’s voucher program, Journal of Public Economics, 90 (8): 1477–1503.
22.
Jasińska A., Hawrot J., Humenny G., Majkut P., Konlewski M. [2013], Kontekstowy model efektywności nauczania po I etapie edukacyjnym – wyniki badania podłużnego w szkołach podstawowych, Technical Report, Instytut Badań Edukacyjnych.
24.
Jensen R. [2010], The (perceived) returns to education and the demand for schooling, The Quarterly Journal of Economics, 125 (2): 515–548.
25.
Kalogrides D., Loeb S., Béteille T. [2013], Systematic sorting: teacher characteristics and class assignments, Sociology of Education, 86 (2): 103–123.
26.
Kane T., Stephanie J., Riegg K., Staiger D. O. [2006], School quality, neighborhoods, and housing prices, American Law and Economics Review, 8 (2): 183–212.
27.
Kern N., Thukral R., Ziebarth T. [2012], A Mission to Serve: How Public Charter Schools Are Designed to Meet the Diverse Demands of Our Communities. Issue Brief, National Alliance for Public Charter Schools.
28.
Kremer M., Duflo E., Dupas P. [2011], Peer Effects, Teacher Incentives, and the Impact of Tracking,” American Economic Review, 101.
29.
Ladd H., Fiske E. [2000], When schools compete: A cautionary tale, Washington, DC: The Brookings Institution.
30.
Lucas M. E. [2004], What’s in a grade? School report cards and the housing market, American Economic Review: 591–604.
31.
MacLeod W. B., Urquiola M. [2009], Anti-lemons: school reputation and educational quality, Technical Report, National Bureau of Economic Research.
32.
Meghir C., Palme M. [2005], Educational reform, ability, and family background, The American Economic Review, 95 (1): 414–424.
33.
Nechyba T. J. [2006], Income and peer quality sorting in public and private schools, Handbook of the Economics of Education, 2: 1327–1368.
34.
Newlon E., Romano R. [2002], Ability tracking, school competition, and the distribution of educational benefits, Journal of Public Economics, 83 (1): 1–48.
35.
Raven J. [2000], The Raven’s progressive matrices: change and stability over culture and time, Cognitive Psychology, 41 (1): 1–48.
36.
Rothstein J. [2009], Student sorting and bias in value-added estimation: Selection on observables and unobservables, Education, 4 (4): 537–571.
37.
Szmigel M. K. [2013], Gimnazjum niejedno ma imię? – na podstawie wywiadów z dyrektorami. Doniesienie z badań jakościowych, Technical Report, XIX Konferencja Diagnostyki Edukacyjnej, Gniezno.
38.
Tiebout Ch. M. [1956], A pure theory of local expenditures, The Journal of Political Economy: 416–424.
RELATED ARTICLE
© 2006-2022 Journal hosting platform by Bentus
We process personal data collected when visiting the website. The function of obtaining information about users and their behavior is carried out by voluntarily entered information in forms and saving cookies in end devices. Data, including cookies, are used to provide services, improve the user experience and to analyze the traffic in accordance with the Privacy policy. Data are also collected and processed by Google Analytics tool (more).
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.