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Factors that affect Students’ performance in Science: An application using Gini-BMA methodology in PISA 2015 dataset

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  • Anastasia Dimiski

    (Department of Economics and Finance, University of Guelph, Guelph ON Canada)

Abstract

Existing theoretical and empirical evidence on the determinants of students’ performance is relatively short. Even more narrow is the literature that examines the impact of pre-primary education on students’ academic performance. Relying on the first-of-its-kind of the 2015 wave data from the Programme of International Student Assessment (PISA), the present study thoroughly discusses the associations between Students’ performance in Science and a set of variables that are classified into 14 categories, including attendance and non-attendance in pre-primary education. To implement this research question, Gini-BMA approach is employed, which accounts for theory uncertainty. It is found that, among the factors, attendance in pre-primary education (i.e. PC11) is a robust determinant of students’ performance in science. However, this result is supported only under the Gini methodology.

Suggested Citation

  • Anastasia Dimiski, 2020. "Factors that affect Students’ performance in Science: An application using Gini-BMA methodology in PISA 2015 dataset," Working Papers 2004, University of Guelph, Department of Economics and Finance.
  • Handle: RePEc:gue:guelph:2020-04
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    1. Levin, Andrew T. & Williams, John C., 2003. "Robust monetary policy with competing reference models," Journal of Monetary Economics, Elsevier, vol. 50(5), pages 945-975, July.
    2. Björklund, Anders & Salvanes, Kjell G., 2011. "Education and Family Background: Mechanisms and Policies," 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 3, pages 201-247, Elsevier.
    3. Erik Hanushek & Stephen Machin & Ludger Woessmann (ed.), 2011. "Handbook of the Economics of Education," Handbook of the Economics of Education, Elsevier, edition 1, volume 4, number 4, June.
    4. Li, Mingliang & Tobias, Justin, 2004. "Returns to Schooling and Bayesian Model Averaging: A Union of Two Literatures," Staff General Research Papers Archive 12011, Iowa State University, Department of Economics.
    5. Theo S. Eicher & Alex Lenkoski & Adrian Raftery, 2009. "Bayesian Model Averaging and Endogeneity Under Model Uncertainty: An Application to Development Determinants," Working Papers UWEC-2009-19-FC, University of Washington, Department of Economics.
    6. Theo Eicher & Jeff Begun, 2008. "In Search of a Sulphur Dioxide Environmental Kuznets Curve: A Bayesian Model Averaging Approach," Working Papers UWEC-2007-19-P, University of Washington, Department of Economics.
    7. Gary S. Becker, 1981. "A Treatise on the Family," NBER Books, National Bureau of Economic Research, Inc, number beck81-1.
    8. Gary Koop & Dimitris Korobilis, 2012. "Forecasting Inflation Using Dynamic Model Averaging," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 53(3), pages 867-886, August.
    9. Michael Baker & Jonathan Gruber & Kevin Milligan, 2008. "Universal Child Care, Maternal Labor Supply, and Family Well-Being," Journal of Political Economy, University of Chicago Press, vol. 116(4), pages 709-745, August.
    10. Eric A. Hanushek & Ludger Wössmann, 2006. "Does Educational Tracking Affect Performance and Inequality? Differences- in-Differences Evidence Across Countries," Economic Journal, Royal Economic Society, vol. 116(510), pages 63-76, March.
    11. Winford H. Masanjala & Chris Papageorgiou, 2008. "Rough and lonely road to prosperity: a reexamination of the sources of growth in Africa using Bayesian model averaging," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(5), pages 671-682.
    12. Carlos M. Carvalho & Nicholas G. Polson & James G. Scott, 2010. "The horseshoe estimator for sparse signals," Biometrika, Biometrika Trust, vol. 97(2), pages 465-480.
    13. Jon Lorence & Anthony Gary Dworkin, 2006. "Elementary Grade Retention in Texas and Reading Achievement Among Racial Groups: 1994–2002," Review of Policy Research, Policy Studies Organization, vol. 23(5), pages 999-1033, September.
    14. Ley, Eduardo & Steel, Mark F.J., 2012. "Mixtures of g-priors for Bayesian model averaging with economic applications," Journal of Econometrics, Elsevier, vol. 171(2), pages 251-266.
    15. W. Steven Barnett, 1992. "Benefits of Compensatory Preschool Education," Journal of Human Resources, University of Wisconsin Press, vol. 27(2), pages 279-312.
    16. Gary S. Becker & Nigel Tomes, 1994. "Human Capital and the Rise and Fall of Families," NBER Chapters, in: Human Capital: A Theoretical and Empirical Analysis with Special Reference to Education, Third Edition, pages 257-298, National Bureau of Economic Research, Inc.
    17. Theo S. Eicher & Christian Henn & Chris Papageorgiou, 2012. "Trade creation and diversion revisited: Accounting for model uncertainty and natural trading partner effects," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(2), pages 296-321, March.
    18. Brian A. Jacob & Lars Lefgren, 2004. "Remedial Education and Student Achievement: A Regression-Discontinuity Analysis," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 226-244, February.
    19. Lidia Ceriani & Paolo Verme, 2012. "The origins of the Gini index: extracts from Variabilità e Mutabilità (1912) by Corrado Gini," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 10(3), pages 421-443, September.
    20. Jay Bainbridge & Marcia K. Meyers & Sakiko Tanaka & Jane Waldfogel, 2005. "Who Gets an Early Education? Family Income and the Enrollment of Three‐ to Five‐Year‐Olds from 1968 to 2000," Social Science Quarterly, Southwestern Social Science Association, vol. 86(3), pages 724-745, September.
    21. Kourtellos, Andros & Stengos, Thanasis & Tan, Chih Ming, 2013. "The effect of public debt on growth in multiple regimes," Journal of Macroeconomics, Elsevier, vol. 38(PA), pages 35-43.
    22. Jens Ludwig & Douglas L. Miller, 2007. "Does Head Start Improve Children's Life Chances? Evidence from a Regression Discontinuity Design," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 122(1), pages 159-208.
    23. Mathias Moser & Paul Hofmarcher, 2014. "Model Priors Revisited: Interaction Terms In Bma Growth Applications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(2), pages 344-347, March.
    24. William A. Brock & Steven N. Durlauf & Kenneth D. West, 2003. "Policy Evaluation in Uncertain Economic Environments," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 34(1), pages 235-322.
    25. Carneiro, Pedro & Heckman, James J., 2003. "Human Capital Policy," IZA Discussion Papers 821, Institute of Labor Economics (IZA).
    26. Becker, Gary S, 1985. "Human Capital, Effort, and the Sexual Division of Labor," Journal of Labor Economics, University of Chicago Press, vol. 3(1), pages 33-58, January.
    27. P. J. Brown & M. Vannucci & T. Fearn, 1998. "Multivariate Bayesian variable selection and prediction," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 60(3), pages 627-641.
    28. Jana Eklund & Sune Karlsson, 2007. "Forecast Combination and Model Averaging Using Predictive Measures," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 329-363.
    29. Western, Bruce & Jackman, Simon, 1994. "Bayesian Inference for Comparative Research," American Political Science Review, Cambridge University Press, vol. 88(2), pages 412-423, June.
    30. Dumas Christelle & Lefranc Arnaud, 2010. "Early schooling and later outcomes : Evidence from pre-school extension in France," THEMA Working Papers 2010-07, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    31. Levine, Ross & Renelt, David, 1992. "A Sensitivity Analysis of Cross-Country Growth Regressions," American Economic Review, American Economic Association, vol. 82(4), pages 942-963, September.
    32. Berlinski, Samuel & Galiani, Sebastian & Gertler, Paul, 2009. "The effect of pre-primary education on primary school performance," Journal of Public Economics, Elsevier, vol. 93(1-2), pages 219-234, February.
    33. James Heckman & Rodrigo Pinto & Peter Savelyev, 2013. "Understanding the Mechanisms through Which an Influential Early Childhood Program Boosted Adult Outcomes," American Economic Review, American Economic Association, vol. 103(6), pages 2052-2086, October.
    34. Elizabeth U. Cascio, 2009. "Do Investments in Universal Early Education Pay Off? Long-term Effects of Introducing Kindergartens into Public Schools," NBER Working Papers 14951, National Bureau of Economic Research, Inc.
    35. Sheldon Danziger & Jane Waldfogel, 2000. "Investing in Children: What do we know? What should we do?," CASE Papers case34, Centre for Analysis of Social Exclusion, LSE.
    36. Theo S. Eicher & Chris Papageorgiou & Adrian E. Raftery, 2011. "Default priors and predictive performance in Bayesian model averaging, with application to growth determinants," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(1), pages 30-55, January/F.
    37. Blau, David & Currie, Janet, 2006. "Pre-School, Day Care, and After-School Care: Who's Minding the Kids?," Handbook of the Economics of Education, in: Erik Hanushek & F. Welch (ed.), Handbook of the Economics of Education, edition 1, volume 2, chapter 20, pages 1163-1278, Elsevier.
    38. Esping-Andersen, Gosta & Garfinkel, Irwin & Han, Wen-Jui & Magnuson, Katherine & Wagner, Sander & Waldfogel, Jane, 2012. "Child care and school performance in Denmark and the United States," Children and Youth Services Review, Elsevier, vol. 34(3), pages 576-589.
    39. Berlinski, Samuel & Galiani, Sebastian & Manacorda, Marco, 2008. "Giving children a better start: Preschool attendance and school-age profiles," Journal of Public Economics, Elsevier, vol. 92(5-6), pages 1416-1440, June.
    40. Vatcharin Sirimaneetham & Jonathan Temple, 2006. "Macroeconomic policy and the distribution of growth rates," Bristol Economics Discussion Papers 06/584, School of Economics, University of Bristol, UK.
    41. Sheila B. Kamerman & Michelle Neuman & Jane Waldfogel & Jeanne Brooks-Gunn, 2003. "Social Policies, Family Types and Child Outcomes in Selected OECD Countries," OECD Social, Employment and Migration Working Papers 6, OECD Publishing.
    42. Sala-i-Martin, Xavier, 1997. "I Just Ran Two Million Regressions," American Economic Review, American Economic Association, vol. 87(2), pages 178-183, May.
    43. Alissa Goodman & Barbara Sianesi, 2005. "Early education and children's outcomes: low long do the impacts last?," Fiscal Studies, Institute for Fiscal Studies, vol. 26(4), pages 513-548, December.
    44. Cunha, Flavio & Heckman, James J. & Lochner, Lance, 2006. "Interpreting the Evidence on Life Cycle Skill Formation," Handbook of the Economics of Education, in: Erik Hanushek & F. Welch (ed.), Handbook of the Economics of Education, edition 1, volume 1, chapter 12, pages 697-812, Elsevier.
    45. Janet Currie, 2001. "Early Childhood Education Programs," Journal of Economic Perspectives, American Economic Association, vol. 15(2), pages 213-238, Spring.
    46. P. J. Brown & M. Vannucci & T. Fearn, 2002. "Bayes model averaging with selection of regressors," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(3), pages 519-536, August.
    47. Arthur Charpentier & Ndéné Ka & Stéphane Mussard & Oumar Hamady Ndiaye, 2019. "Gini Regressions and Heteroskedasticity," Econometrics, MDPI, vol. 7(1), pages 1-16, January.
    48. Min, Chung-ki & Zellner, Arnold, 1993. "Bayesian and non-Bayesian methods for combining models and forecasts with applications to forecasting international growth rates," Journal of Econometrics, Elsevier, vol. 56(1-2), pages 89-118, March.
    49. Burhan, Nik Ahmad Sufian & Kurniawan, Yohan & Sidek, Abdul Halim & Mohamad, Mohd Rosli, 2014. "Crimes and the Bell Curve: The Role of People with High, Average, and Low Intelligence," MPRA Paper 77314, University Library of Munich, Germany.
    50. Martin Feldkircher & Stefan Zeugner, 2009. "Benchmark Priors Revisited: On Adaptive Shrinkage and the Supermodel Effect in Bayesian Model Averaging," IMF Working Papers 2009/202, International Monetary Fund.
    51. Justin L. Tobias & Mingliang Li, 2004. "Returns to Schooling and Bayesian Model Averaging: A Union of Two Literatures," Journal of Economic Surveys, Wiley Blackwell, vol. 18(2), pages 153-180, April.
    52. Ley, Eduardo & Steel, Mark F.J., 2007. "Jointness in Bayesian variable selection with applications to growth regression," Journal of Macroeconomics, Elsevier, vol. 29(3), pages 476-493, September.
    53. Xavier Sala-I-Martin & Gernot Doppelhofer & Ronald I. Miller, 2004. "Determinants of Long-Term Growth: A Bayesian Averaging of Classical Estimates (BACE) Approach," American Economic Review, American Economic Association, vol. 94(4), pages 813-835, September.
    54. Marcel Carcea & Robert Serfling, 2015. "A Gini Autocovariance Function for Time Series Modelling," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(6), pages 817-838, November.
    55. Mussard, Stéphane & Ndiaye, Oumar Hamady, 2018. "Vector autoregressive models: A Gini approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 1967-1979.
    56. Giambona, Francesca & Porcu, Mariano, 2018. "School size and students' achievement. Empirical evidences from PISA survey data," Socio-Economic Planning Sciences, Elsevier, vol. 64(C), pages 66-77.
    57. Liang, Feng & Paulo, Rui & Molina, German & Clyde, Merlise A. & Berger, Jim O., 2008. "Mixtures of g Priors for Bayesian Variable Selection," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 410-423, March.
    58. Magnuson, Katherine A. & Ruhm, Christopher & Waldfogel, Jane, 2007. "Does prekindergarten improve school preparation and performance?," Economics of Education Review, Elsevier, vol. 26(1), pages 33-51, February.
    59. Leamer, Edward E, 1985. "Sensitivity Analyses Would Help," American Economic Review, American Economic Association, vol. 75(3), pages 308-313, June.
    60. Yipeng Tang, 2019. "Immigration Status and Adolescent Life Satisfaction: An International Comparative Analysis Based on PISA 2015," Journal of Happiness Studies, Springer, vol. 20(5), pages 1499-1518, June.
    61. William T. Gormley, Jr. & Ted Gayer, 2005. "Promoting School Readiness in Oklahoma: An Evaluation of Tulsa's Pre-K Program," Journal of Human Resources, University of Wisconsin Press, vol. 40(3).
    62. Lerman, Robert I. & Yitzhaki, Shlomo, 1984. "A note on the calculation and interpretation of the Gini index," Economics Letters, Elsevier, vol. 15(3-4), pages 363-368.
    63. Behrman, Jere R & Birdsall, Nancy, 1983. "The Quality of Schooling: Quantity Alone is Misleading," American Economic Review, American Economic Association, vol. 73(5), pages 928-946, December.
    64. Begun, Jeffrey & Eicher, Theo S., 2008. "In search of an environmental Kuznets curve in sulphur dioxide concentrations: a Bayesian model averaging approach," Environment and Development Economics, Cambridge University Press, vol. 13(6), pages 795-822, December.
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    More about this item

    Keywords

    students’ performance; pre-primary education; Gini regression coefficient; BMA methodology; PISA.;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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