IDEAS home Printed from https://ideas.repec.org/a/lde/journl/y2013i78p9-44.html

Differences in motivations and academic achievement

Author

Listed:
  • Luis Gamboa
  • Mauricio Rodríguez
  • Andrés García

Abstract

This paper provides new evidence on the effect of pupils’ self-motivation on academic achievement in science across countries. By using the OECD´s Programme for International Student Assessment 2006 (PISA 2006) test, we find that self-motivation has a positive effect on students’ performance. Instrumental Variables Quantile Regression is used to analyze the existence of different estimated coefficients over the scores distribution, allowing us to deal with the potential endogeneity of self-motivation. We find that the impact of intrinsic motivation on academic performance depends on the pupil’s score. Our findings support the importance of designing focalized programs for different populations that foster their motivation towards learning.

Suggested Citation

  • Luis Gamboa & Mauricio Rodríguez & Andrés García, 2013. "Differences in motivations and academic achievement," Lecturas de Economía, Universidad de Antioquia, Departamento de Economía, issue 78, pages 9-44.
  • Handle: RePEc:lde:journl:y:2013:i:78:p:9-44
    as

    Download full text from publisher

    File URL: https://revistas.udea.edu.co/index.php/lecturasdeeconomia/issue/view/1336
    Download Restriction: no
    ---><---

    Other versions of this item:

    Citations

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


    Cited by:

    1. José M. Cordero & Víctor Cristóbal & Daniel Santín, 2018. "Causal Inference On Education Policies: A Survey Of Empirical Studies Using Pisa, Timss And Pirls," Journal of Economic Surveys, Wiley Blackwell, vol. 32(3), pages 878-915, July.
    2. World Bank Group, 2016. "Education Sector Public Expenditure Tracking and Service Delivery Survey in Zambia," World Bank Publications - Reports 23884, The World Bank Group.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education

    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:lde:journl:y:2013:i:78:p:9-44. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Carlos Andrés Vasco Correa (email available below). General contact details of provider: https://edirc.repec.org/data/deantco.html .

    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.