IDEAS home Printed from https://ideas.repec.org/a/eee/jcecon/v40y2012i3p508-527.html
   My bibliography  Save this article

Educational scores: How does Russia fare?

Author

Listed:
  • Amini, Chiara
  • Commander, Simon

Abstract

This paper uses large multi-country datasets on educational scores – namely PISA and TIMSS – to examine the factors associated with educational outcomes. In particular, it distinguishes between individual and family background factors and those emanating from the school or institutional environment. Using pooled data as well as cross sectional evidence we look at the variation across countries before looking at within country variation in Russia. We find that both in the benchmark cross-country estimates, as also those using just Russia data, a number of individual and family variables are robustly associated with better educational outcomes. Institutional variables also matter – notably student–teacher ratios and indicators of school autonomy – but there are also some clear particularities in the Russian case.

Suggested Citation

  • Amini, Chiara & Commander, Simon, 2012. "Educational scores: How does Russia fare?," Journal of Comparative Economics, Elsevier, vol. 40(3), pages 508-527.
    • Handle: RePEc:eee:jcecon:v:40:y:2012:i:3:p:508-527
    DOI: 10.1016/j.jce.2012.02.006
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0147596712000212
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jce.2012.02.006?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Eric Hanushek & Ludger Woessmann, 2012. "Do better schools lead to more growth? Cognitive skills, economic outcomes, and causation," Journal of Economic Growth, Springer, vol. 17(4), pages 267-321, December.
    2. Daniel Münich & Jan Svejnar & Katherine Terrell, 2005. "Returns to Human Capital Under The Communist Wage Grid and During the Transition to a Market Economy," The Review of Economics and Statistics, MIT Press, vol. 87(1), pages 100-123, February.
    3. Hanushek, Eric A. & Woessmann, Ludger, 2007. "The role of education quality for economic growth," Policy Research Working Paper Series 4122, The World Bank.
    4. Sophia Rabe‐Hesketh & Anders Skrondal, 2006. "Multilevel modelling of complex survey data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(4), pages 805-827, October.
    5. Abhijit V. Banerjee & Shawn Cole & Esther Duflo & Leigh Linden, 2007. "Remedying Education: Evidence from Two Randomized Experiments in India," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 122(3), pages 1235-1264.
    6. Hanushek, Eric A. & Woessmann, Ludger, 2011. "The Economics of International Differences in Educational Achievement," Handbook of the Economics of Education, in: Erik Hanushek & Stephen Machin & Ludger Woessmann (ed.), Handbook of the Economics of Education, edition 1, volume 3, chapter 2, pages 89-200, Elsevier.
    7. Sims,Christopher A. (ed.), 1994. "Advances in Econometrics," Cambridge Books, Cambridge University Press, number 9780521444606.
    8. Shahrukh Rafi Khan & David Kiefer, 2007. "Educational Production Functions for Rural Pakistan: A Comparative Institutional Analysis," Education Economics, Taylor & Francis Journals, vol. 15(3), pages 327-342.
    9. Moshe Buchinsky, 1998. "Recent Advances in Quantile Regression Models: A Practical Guideline for Empirical Research," Journal of Human Resources, University of Wisconsin Press, vol. 33(1), pages 88-126.
    10. Rosalind Levacic & Stephen Machin & David Reynolds & Anna Vignoles & James Walker, 2000. "The Relationship between Resource Allocation and Pupil Attainment: A Review," CEE Discussion Papers 0002, Centre for the Economics of Education, LSE.
    11. Gyimah-Brempong, Kwabena & Gyapong, Anthony O., 1991. "Characteristics of education production functions: An application of canonical regression analysis," Economics of Education Review, Elsevier, vol. 10(1), pages 7-17, March.
    12. Andreas Ammermueller, 2007. "PISA: What makes the difference?," Empirical Economics, Springer, vol. 33(2), pages 263-287, September.
    13. Dan D. Goldhaber & Dominic J. Brewer, 1997. "Why Don't Schools and Teachers Seem to Matter? Assessing the Impact of Unobservables on Educational Productivity," Journal of Human Resources, University of Wisconsin Press, vol. 32(3), pages 505-523.
    14. Sims,Christopher A. (ed.), 1994. "Advances in Econometrics," Cambridge Books, Cambridge University Press, number 9780521444590.
    15. Richard B. Freeman & Stephen Machin & Martina Viarengo, 2010. "Variation in Educational Outcomes and Policies across Countries and of Schools within Countries," NBER Working Papers 16293, National Bureau of Economic Research, Inc.
    16. Giorgio Brunello & Elena Crivellaro & Lorenzo Rocco, 2012. "Lost in transition?," The Economics of Transition, The European Bank for Reconstruction and Development, vol. 20(4), pages 637-676, October.
    17. Eide, Eric & Showalter, Mark H., 1998. "The effect of school quality on student performance: A quantile regression approach," Economics Letters, Elsevier, vol. 58(3), pages 345-350, March.
    18. Petra E. Todd & Kenneth I. Wolpin, 2003. "On The Specification and Estimation of The Production Function for Cognitive Achievement," Economic Journal, Royal Economic Society, vol. 113(485), pages 3-33, February.
    19. Cooper, Samuel T. & Cohn, Elchanan, 1997. "Estimation of a frontier production function for the South Carolina educational process," Economics of Education Review, Elsevier, vol. 16(3), pages 313-327, June.
    20. Robert Mislevy, 1991. "Randomization-based inference about latent variables from complex samples," Psychometrika, Springer;The Psychometric Society, vol. 56(2), pages 177-196, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lippmann, Quentin & Senik, Claudia, 2018. "Math, girls and socialism," Journal of Comparative Economics, Elsevier, vol. 46(3), pages 874-888.
    2. Riccardo Crescenzi & Alexander Jaax, 2017. "Innovation in Russia: The Territorial Dimension," Economic Geography, Taylor & Francis Journals, vol. 93(1), pages 66-88, January.
    3. Rabe, Birgitta & Nicoletti, Cheti, 2013. "School inputs and skills: complementarity and self-productivity," ISER Working Paper Series 2013-28, Institute for Social and Economic Research.
    4. Lucia Mangiavacchi, 2016. "Family structure and children’s educational attainment in transition economies," IZA World of Labor, Institute of Labor Economics (IZA), pages 303-303, October.
    5. Quentin Lippmann & Claudia Senik, 2018. "Math, Girls and Socialism," Working Papers halshs-01387272, HAL.
    6. Dilmaghani, Maryam, 2021. "The gender gap in competitive chess across countries: Commanding queens in command economies," Journal of Comparative Economics, Elsevier, vol. 49(2), pages 425-441.
    7. Amini, Chiara & Nivorozhkin, Eugene, 2015. "The urban–rural divide in educational outcomes: Evidence from Russia," International Journal of Educational Development, Elsevier, vol. 44(C), pages 118-133.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Amini, Chiara & Commander, Simon, 2011. "Educational Scores: How Does Russia Fare?," IZA Discussion Papers 6033, Institute of Labor Economics (IZA).
    2. Daniel J. Henderson & Léopold Simar & Le Wang, 2017. "The three s of public schools: irrelevant inputs, insufficient resources and inefficiency," Applied Economics, Taylor & Francis Journals, vol. 49(12), pages 1164-1184, March.
    3. Giambona, Francesca & Porcu, Mariano, 2015. "Student background determinants of reading achievement in Italy. A quantile regression analysis," International Journal of Educational Development, Elsevier, vol. 44(C), pages 95-107.
    4. Lounkaew, Kiatanantha, 2013. "Explaining urban–rural differences in educational achievement in Thailand: Evidence from PISA literacy data," Economics of Education Review, Elsevier, vol. 37(C), pages 213-225.
    5. Manquilef-Bächler, Alejandra A. & Arulampalam, Wiji & Smith, Jennifer C., 2009. "Differences in Decline: Quantile Regression Analysis of Union Wage Differentials in the United Kingdom, 1991-2003," IZA Discussion Papers 4138, Institute of Labor Economics (IZA).
    6. Angel López-Nicolás & Jaume García & Pedro J. Hernández, 2001. "How wide is the gap? An investigation of gender wage differences using quantile regression," Empirical Economics, Springer, vol. 26(1), pages 149-167.
    7. Vargas-Montoya, Luis & Gimenez, Gregorio & Fernández-Gutiérrez, Marcos, 2023. "ICT use for learning and students' outcomes: Does the country's development level matter?," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    8. de la Rica, Sara & Dolado, Juan J. & Llorens, Vanesa, 2005. "Ceiling and Floors: Gender Wage Gaps by Education in Spain," IZA Discussion Papers 1483, Institute of Labor Economics (IZA).
    9. Bernhard C. Dannemann, 2020. "Peer Effects in Secondary Education: Evidence from the 2015 Trends in Mathematics and Science Study Based on Homophily," Working Papers V-428-20, University of Oldenburg, Department of Economics, revised Feb 2020.
    10. Engzell, Per, 2017. "What Do Books in the Home Proxy For? A Cautionary Tale," Working Paper Series 1/2016, Stockholm University, Swedish Institute for Social Research.
    11. Juan J. Dolado & Vanesa Llorens, 2004. "Gender Wage Gaps by Education in Spain: Glass Floors Vs. Glass Ceilings," Working Papers wp2004_0403, CEMFI.
    12. Rosa Sanchis-Guarner & José Montalbán & Felix Weinhardt, 2021. "Home Broadband and Human Capital Formation," CESifo Working Paper Series 8846, CESifo.
    13. Francesco Ferrante, 2017. "Assessing Quality in Higher Education: Some Caveats," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 131(2), pages 727-743, March.
    14. Richards, John & Vining, Aidan R., 2015. "Universal primary education in low-income countries: The contributing role of national governance," International Journal of Educational Development, Elsevier, vol. 40(C), pages 174-182.
    15. Albrecht, James & van Vuuren, Aico & Vroman, Susan, 2009. "Counterfactual distributions with sample selection adjustments: Econometric theory and an application to the Netherlands," Labour Economics, Elsevier, vol. 16(4), pages 383-396, August.
    16. Z. L. Yang & Y. K. Tse, 2006. "Modelling firm‐size distribution using Box–Cox heteroscedastic regression," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(5), pages 641-653, July.
    17. Daniel Pollmann & Thomas Dohmen & Franz Palm, 2020. "Robust Estimation of Wage Dispersion with Censored Data: An Application to Occupational Earnings Risk and Risk Attitudes," De Economist, Springer, vol. 168(4), pages 519-540, December.
    18. Oka, Tatsushi & Qu, Zhongjun, 2011. "Estimating structural changes in regression quantiles," Journal of Econometrics, Elsevier, vol. 162(2), pages 248-267, June.
    19. Jörn-Steffen Pischke, 2007. "The Impact of Length of the School Year on Student Performance and Earnings: Evidence From the German Short School Years," Economic Journal, Royal Economic Society, vol. 117(523), pages 1216-1242, October.
    20. Jörn-Steffen Pischke, 2004. "The Impact of the School Year on Student Performance and Earnings: Evidence from the German short school years," CEE Discussion Papers 0034, Centre for the Economics of Education, LSE.

    More about this item

    Keywords

    Education; Russia; PISA; TIMSS;
    All these keywords.

    JEL classification:

    • H5 - Public Economics - - National Government Expenditures and Related Policies
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • I28 - Health, Education, and Welfare - - Education - - - Government Policy
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration
    • P5 - Political Economy and Comparative Economic Systems - - Comparative Economic Systems

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jcecon:v:40:y:2012:i:3:p:508-527. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/622864 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.