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“Decomposition of Differences in PISA Results in Middle Income Countries”. (2014). Ramos, Raul ; Nieto, Sandra.
In: IREA Working Papers.
RePEc:ira:wpaper:201408.

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  1. Ammermueller, A., 2007a. Poor background or low returns? Why immigrant students in Germany perform so poorly in the programme for international student assessment. Education Economics 15(2), 215–230.

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  12. Disclima (only 2009) The index of disciplinary climate was derived from students’ reports on how often the followings happened in their lessons of the language of instruction (ST36). Higher values on this index indicate a better disciplinary climate.
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  19. Häkkinen, I., Kirjavainen, T., Uusitalo, R., 2003. School resources and student achievement revisited: new evidence from panel data. Economics of Education Review 22, 329-335.

  20. Hanushek, E. A., 1986. The economics of schooling. Journal of Economic Literature 24, 1141-1177.
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  22. Hanushek, E. A., Kain, J. F., Markman, J. M., Rivkin, S. G., 2003. Does peer ability affect student achievement?. Journal of Applied Econometrics 18, 527-544.

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  24. Hanushek, E. A., Woessmann, L., 2011a, How much do educational outcomes matter in OECD countries?, Economic Policy 26 (67) , 427-491.
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  25. Hanushek, E. A., Woessmann, L., 2011b, The Economics of International Differences in Educational Achievement, in Handbook of the Economics of Education, vol. 3, 89-200.
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  26. Haveman, R., Wolfe, B., 1995. The determinants of children’s attainment: A review of methods and findings. Journal of Economics Literature 33(4), 1829–1878 Krueger, A. B., 2003. Economics considerations and class size. Economic Journal 113, 34-63.
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  27. Immigrant 2nd gen. Dummy variable: 1 if second-generation students (those born in the country of assessment but whose parents were born in another country), 0 if native students Language Dummy variable: 1 if language at home is a different language than the language of assessment, 0 if language at home is the same as the language of assessment Family1 Dummy variable: 1 if single-parent family, 0 if two-parent family Family 2 (only 2009) Dummy variable: 1 if other type of family, 0 if two-parent family Intscie (only 2006) The index of general interest in science learning was derived from eight items (ST21Q0108) using students’ responses. Positive scores indicate higher levels of interest in learning science.
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  28. In characteristics -0.124*** -0.198*** -0.0241 -0.0492*** -0.0497*** -0.135*** -0.215*** -0.123*** -0.120*** -0.200*** -0.0233 -0.0797*** Individual -0.021 -0.028 0.003 -0.005 0.000 -0.022 -0.027 -0.008 0.003 -0.011 -0.033 -0.033 Schools -0.088 -0.152 -0.022 -0.025 -0.026 -0.095 -0.171 -0.110 -0.114 -0.176 -0.262 -0.023 Teachers -0.015 -0.018 -0.005 -0.019 -0.024 -0.017 -0.018 -0.005 -0.008 -0.013 0.272 -0.024 Reading 2009 Difference escs75-escs25 -0.314*** -0.343*** -0.285*** -0.372*** -0.263*** -0.255*** -0.267*** -0.331*** -0.485*** -0.358*** -0.0846*** -0.204*** Diff. In coefficients -0.175*** -0.233*** -0.217*** -0.249*** -0.199*** -0.177*** -0.198*** -0.210*** -0.129*** -0.220*** -0.0366*** -0.140*** Diff.
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  29. Ldrshp (only 2009) The index of school principal’s leadership was derived from school principals’ responses about the frequency with which they were involved in the following school affairs in the previous school year (SC26). Higher values on this index indicate greater involvement of school principals in school affairs.
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  30. Lee, J-S, 2012. The effects of the teacher–student relationship and academic press on student engagement and academic performance, International Journal of Educational Research, 53, 330-340.
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  31. Meunier, M., 2011. Immigration and student achievement: Evidence from Switzerland. Economics of Education Review 30 (1), 16-38.

  32. Mislevy, R. J., Sheehan, K. M., 1987. Marginal estimation procedures. In: Beaton, A.E., Editor, 1987. The NAEP 1983-84 technical report, National Assessment of Educational Progress, Educational Testing Service, Princeton, 293-360.
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  33. Mislevy, R. J., Sheehan, K. M., 1989. Information matrices in latent-variable models. Journal of Educational Statistics 14, 335-350.
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  34. Motiv7 (only 2009) Dummy variable: 1 if student answered “in most lessons” or “in all lessons” to the item Q38_g “the teacher gives students the chance to ask questions about the reading assignment”, 0 if student answered “Never or hardly ever” or “in some lessons”.
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  35. Oaxaca, R., 1973. Male-Female Wage Differentials in Urban Labor Markets. International Economic Review 14 (3), 139-148.

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  37. Ramos, R., Duque, J. C., Nieto, S. (2012), Decomposing the Rural-Urban Differential in Student Achievement in Colombia Using PISA Microdata, IZA DP 6515.

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  39. Research Institute of Applied Economics Working Paper 2014/08, pàg. 16 Regional Quantitative Analysis Research Group Working Paper 2014/04, pag. 16 16 Noell, J., 1982. Public and Catholic schools: A re-analysis of public and private schools. Sociology of Education 55, 123-132.
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  40. Research Institute of Applied Economics Working Paper 2014/08, pàg. 17 Regional Quantitative Analysis Research Group Working Paper 2014/04, pag. 17 17 7. Tables and figures Figure 1. Distribution of students’ scores in Science in 2006 and Reading in 2009 Distribution of students’ scores in Science in 2006 Distribution of students’ scores in Reading in 2009 0 .002 .004 .006 .008 200 400 600 PVSCIE Arab states C Asia C and E Europe E Asia Latin America W Europe kernel = epanechnikov, bandwidth = 11.6133 Kernel density estimate 0 .002 .004 .006 200 400 600 PVREAD Arab states C Asia C and E Europe E Asia Latin America W
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  41. Research Institute of Applied Economics Working Paper 2014/08, pàg. 27 Regional Quantitative Analysis Research Group Working Paper 2014/04, pag. 27 27 Table 5. Yun decomposition: differences in the probability of having Proficiency level 2 between high ESCS (q75) and low ESCS (q25) students JOR TUN AZE KGZ RUS TUR IDN THA BRA MEX NLD GBR Science 2006 Difference escs75-escs25 -0.371*** -0.305*** -0.229*** -0.234*** -0.230*** -0.371*** -0.335*** -0.419*** -0.471*** -0.444*** 0.0130 -0.232*** Diff. In coefficients -0.247*** -0.107*** -0.204*** -0.185*** -0.180*** -0.237*** -0.120*** -0.296*** -0.351*** -0.244*** 0.0363 -0.152*** Diff.
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  42. Respcurr School principals were asked to report whether “principals”, “teachers”, “school governing board”, “regional or local education authority”, or “national education authority” has a considerable responsibility for some tasks (2006: SC11Q07, SC11Q10, SC11Q11, SC11Q12, 2009: SC24Q07, SC24Q10, SC24Q11, SC24Q12. Positive values on this index indicate relatively more responsibility for schools than local, regional or national education authority Respres School principals were asked to report whether “principals”, “teachers”, “school governing board”, “regional or local education authority” or “national education authority” has a considerable responsibility for some tasks (2006: SC11Q01-Q06, 2009: SC24Q01-Q06). Positive values on this index indicate relatively more responsibility for schools than local, regional or national education authority.
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  43. Rubin, D. B., 1987. Multiple imputation for nonresponse in surveys, New York, Wiley.
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  44. Sander, W., 1996. Catholic grade schools and academic achievement. The Journal of Human Resources 31 (3), 540-548.

  45. Scapply (only 2006) Four items (ST34Q07, ST34Q12, ST34Q15, ST34Q17) measuring students’ reports on the frequency of teaching in science lessons with a focus on applications. Positive scores on this index indicate higher frequencies of this type of science teaching.
    Paper not yet in RePEc: Add citation now
  46. Schands (only 2006) Four items (ST34Q02, ST34Q03, ST34Q06, ST34Q14) measuring students’ reports on the frequency of hands-on activities in science lessons. Positive scores on this index indicate higher frequencies of this type of science teaching.
    Paper not yet in RePEc: Add citation now
  47. Scinvest (only 2006) Three items (ST34Q08, ST34Q11, ST34Q16) measuring students’ reports on the frequency of student investigations in science lessons. Positive scores on this index indicate perceived higher frequencies of this type of science teaching.
    Paper not yet in RePEc: Add citation now
  48. Sciprom (only 2006) School principals are asked to report what activities to promote students’ learning of science occur at their school (SC20Q01-Q05). Positive scores indicate higher levels of school activities in this area.
    Paper not yet in RePEc: Add citation now
  49. Smith, J., Naylor, R. A., 2005. Schooling effects on subsequent university performance: evidence for the UK university population. Economics of Education Review 24, 549-562.

  50. Somers, M. A., McEwan, P. J., Willms, J. D., 2004. How effective are private schools in Latin America?. Comparative Education Review 48(1), 48–69.
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  51. Stevans, L. K., Sessions, D. N., 2000. Private/public school choice and student performance revisited. Education Economics 8 (2), 169-184.

  52. Stim1 (only 2009) Dummy variable: 1 if student answered “in most lessons” or “in all lessons” to the item Q37_a “the teacher asks students to explain the meaning of a text”, 0 if student answered “Never or hardly ever” or “in some lessons”.
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  53. Studrel (only 2009) The index of teacher-student relations was derived from students’ level of agreement with the statements ST34. Higher values on this index indicate positive teacher-student relations.
    Paper not yet in RePEc: Add citation now
  54. Vandernberghe, V., Robin, S., 2004. Evaluating the effectiveness of private education across countries: A comparison of methods. Labor Economics 11(4), 487-506.

  55. Woßmann, L., 2003. Schooling resources, educational institutions and student performance: the international evidence. Oxford Bulletin of Economics and Statistics 65 (2), 117-170.
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  56. Woessmann, L., 2011. Cross-country evidence on teacher performance pay. Economics of Education Review, 30 (3), 404-418.

  57. Yun, M., 2004. Decomposing differences in the first moment. Economics Letters 82(2), 275-280.

  58. Zhang, L., Lee, K.A., 2011. Decomposing achievement gaps among OECD countries. Asia Pacific Education Review 12 (3), 463-474.
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