Inequality of Opportunity in Educational Achievements Cross-Country - PowerPoint PPT Presentation

Inequality of Opportunity in Educational Achievements Cross-Country and Intertemporal Comparisons P . Luongo University of Bari Inequality – Measurement, trend, impacts and policies UNU-WIDER Conference September 2014 P . Luongo (University of Bari) Inequality of Educational Opportunity September 2014 1 / 28

Outline Aim & Motivation 1 Model 2 Data 3 Results 4 Conclusions 5 Appendix 6 P . Luongo (University of Bari) Inequality of Educational Opportunity September 2014 2 / 28

Aim & Motivation Research questions Does the country ranking change when we switch the focus of the 1 analysis from average test scores to fairness? Is there any country that outperform in both the level and the 2 degree of fairness? There has been any change in the strength of the association 3 between socio-economic characteristics and students’ performances? P . Luongo (University of Bari) Inequality of Educational Opportunity September 2014 3 / 28

Aim & Motivation Motivations Education influences labour market participation, civic engagement, health status, earnings, social mobility, etc. (Blau & Kahn, 2005; Hanushek & Woessmann, 2010; among others). Intergenerational persistence in educational achievements (Marks, 2005; Macdonald et al. 2010; Ermisch et al. 2012) Inequality in educational attainments (Thomas et al. 2001; Morrison & Murtin, 2007) Inequality in educational achievements (Brown et al., 2007; Micklewright et al. 2007) P . Luongo (University of Bari) Inequality of Educational Opportunity September 2014 4 / 28

Aim & Motivation IEOp Existing evidences de la Vega & Lekuona (2013): PISA 2009 Gamboa & Waltenberg (2011) PISA 2006 & 2009, LAC Ferreira & Gignoux (2011) PISA 2006 What’s new? PISA 2012 1 Changes over time (PISA 2003, 2006, 2009, 2012) 2 How do the less advantaged students perform? 3 P . Luongo (University of Bari) Inequality of Educational Opportunity September 2014 5 / 28

Model Model Adapt to our framework the idea of measuring fairness through an ordered pair (Roemer, 2013): EduOpp = ( W EEOp , IEOp ) W EEOp : focuses on worst-off students IEOp : looks at the whole sample P . Luongo (University of Bari) Inequality of Educational Opportunity September 2014 6 / 28

Model Outcome function Test scores ( s ) depend only on circumstances ( c ) and effort ( e ) s i = f ( c , e ) c used to partition students into K ( j = 1 , ..., K ) types e correspond to the rank π occupied by each student in its own type distribution of test scores v j ( π ) : level of s for individuals in type j occupying the rank π P . Luongo (University of Bari) Inequality of Educational Opportunity September 2014 7 / 28

Model W EEOp � 1 W EEOp = min j ( π ) d π (1) 0 Class-ranked situations: W EEOp corresponds to the average score of the worst-off students (Roemer, 2013) Not class-ranked situations: W EEOp corresponds to the left-hand envelope of the distribution of CDFs (Roemer, 2013) Empirically this involves the estimation, for each country, of each type-specific CDF and their envelopes P . Luongo (University of Bari) Inequality of Educational Opportunity September 2014 8 / 28

Model IEOp Ex-Ante Approach: IEOp measured as between type inequality in mean outcome Parametric procedure s i = β k i + ε i Index of Inequality IEOp = var ( k , ˆ β ) var ( y ) P . Luongo (University of Bari) Inequality of Educational Opportunity September 2014 9 / 28

Data Dataset OECD PISA 2003: 41 countries PISA 2006: 57 countries PISA 2009: 74 countries PISA 2012: 65 countries Domains Mathematics Science Reading P . Luongo (University of Bari) Inequality of Educational Opportunity September 2014 10 / 28

Data Sample 2 stages sampling procedure Students aged between 15 years and 3 months and 16 years and 3 months enrolled in grade 7 or higher Raw test scores ( s ) scaled by using IRT and then standardized µ + ˆ σ s i = ˆ σ ( x i − µ ) where x i is the test score of student i , ˆ µ = 500 and ˆ σ = 100 are the arbitrary (final) grand mean and SD P . Luongo (University of Bari) Inequality of Educational Opportunity September 2014 11 / 28

Data Available Data PISA contains information on: Schools’ policies and practices Students’ background Students’ motivation Students’ learning style P . Luongo (University of Bari) Inequality of Educational Opportunity September 2014 12 / 28

Data Some empirical issues EduOpp = ( W EEOp , IEOp ) W EEOp focuses on the worst-off type: the omission of relevant circumstances determines a measure of “social welfare” UPWARD biased Intuition: when a new circumstance is added there is at least one additional type-distribution, conditional to a given value of the new circumstance, which is going to be at its left IEOp looks at the whole population: the omission of relevant circumstances determines a measure of inequality which is DOWNWARD biased; some variation is left unexplained and attributed to effort. As # of K ↑ ⇒ W EEOp ↓ and IEOp ↑ P . Luongo (University of Bari) Inequality of Educational Opportunity September 2014 13 / 28

Data Variables Students’ circumstances Gender Parental level of education ISCED ≤ 2 1 3 ≤ ISCED ≤ 4 2 ISCED ≥ 5 3 Parental job classification White collar 1 Blue collar 2 12types P . Luongo (University of Bari) Inequality of Educational Opportunity September 2014 14 / 28

W EEOp in Reading, 2012 P . Luongo (University of Bari) WEOp Reading 0 100 200 300 400 500 Author's elaborations on OECD PISA 2012 SVK 213 QRS 232 BGR 295 MNE 301 KAZ 302 QAT 302 PER 323 ARE 331 JOR 332 ROU 335 CZE 339 SRB 344 ARG 345 ISR 346 MYS 350 Inequality of Educational Opportunity TUN 354 SVN 355 URY 358 COL 360 BRA 365 LVA 371 IDN 371 CHL 377 Results LTU 378 RUS 384 SWE 389 HUN 390 MEX 390 CRI 393 THA 399 GRC 399 NOR 400 HRV 403 POL 411 QUB 412 BEL 419 LUX 421 ISL 424 FRA 425 DNK 426 QUA 427 ITA 430 TUR 432 FIN 433 LIE 435 EST 435 ESP 437 JPN 439 NZL 439 CHE 440 PRT 442 KOR 445 NLD 446 QUC 446 CAN 447 GBR 448 TAP 449 USA 449 DEU 452 AUS 453 IRL 468 September 2014 MAC 470 VNM 471 SGP 472 HKG 510 QCN 516 15 / 28

IEOp in Reading, 2012 P . Luongo (University of Bari) IEOp Reading 0 .1 .2 .3 Author's elaborations on OECD PISA 2012 MAC .0536 HKG .0631 KOR .0725 JPN .0733 QUA .0808 IDN .0851 GBR .0876 NLD .0926 CAN .0931 NOR .101 ISL .102 MEX .104 MYS .108 ESP .108 TUN .11 Inequality of Educational Opportunity IRL .113 SRB .114 USA .115 QRS .116 ITA .117 KAZ .117 RUS .119 COL .12 Results LIE .121 AUS .122 ARG .123 EST .125 VNM .125 SWE .125 SGP .127 QUC .129 NZL .133 BRA .134 QCN .134 CZE .134 TAP .135 QUB .136 CRI .138 DNK .14 CHE .142 FIN .147 HRV .149 FRA .15 LUX .151 BEL .153 QAT .157 TUR .158 GRC .161 PRT .165 POL .166 URY .166 ROU .172 DEU .172 ARE .176 PER .177 CHL .18 HUN .185 ISR .19 LTU .19 SVN .192 LVA .196 September 2014 MNE .196 JOR .213 SVK .213 THA .215 BGR .269 16 / 28

Results Average performance and IEOp in Reading, 2012 600 QCN 550 Average score in Reading HKG SGP JPN KOR QUC FIN CAN QUB TAP IRL NZL POL DEU EST AUS LIE NLD BEL FRA CHE NOR MAC VNM GBR 500 DNK USA CZE QUA LUX ISR PRT ITA LVA HUN SWE ESP ISL HRV QRS SVN LTU GRC OECD TUR RUS SVK 450 SRB THA ARE BGR CHL CRI ROU MNE MEX URY BRA JOR TUN 400 COL ARG MYS QAT IDN KAZ PER .25 .2 .15 .1 .05 IEOp Reading Author's elaboration on OECD PISA 2012 P . Luongo (University of Bari) Inequality of Educational Opportunity September 2014 17 / 28

Results Is there any “outperforming” country? b a QCN HKG 500 SGP VNM MAC IRL DEU AUS TAP USA CAN GBR QUC NLD KOR PRT CHE NZL JPN ESP EST LIE TUR FIN ITA QUA FRA DNK ISL LUX BEL POL QUB 400 WEOp Reading HRV NOR THA GRC OECD CRI HUN SWE MEX RUS LTU CHL LVA IDN BRA COL URY SVN TUN MYS ISR ARG SRB CZE ROU JOR ARE PER 300 QAT MNE KAZ BGR QRS d SVK c 200 .25 .2 .15 .1 .05 IEOp Reading Author's elaboration on OECD PISA 2012 P . Luongo (University of Bari) Inequality of Educational Opportunity September 2014 18 / 28

Results Geographical Pattern .25 IEOp Reading 2012 .2 .15 .1 .05 200 300 400 500 WEEOp Reading 2012 Western Europe North Africa and Asia Eastern Europe North America South America P . Luongo (University of Bari) Inequality of Educational Opportunity September 2014 19 / 28

Results Changes over time, 2003 – 2012 IEOp Increase IEOp Reduction 100 WEOp Increase HKG PRT DEU 50 TUN WEOp Reading IDN TUR USA MEX RUS LIE GBR THA ITA BRA CHE IRL POL JPN FRA BEL LUX OECD NZL DNK ESP MAC NLD AUS 0 NOR ISL URY HUN WEOp Reduction GRC SWE CAN CZE LVA -50 KOR FIN -.05 0 .05 .1 .15 IEOp Reding Author's elaboration on OECD PISA 2003 - 2012 P . Luongo (University of Bari) Inequality of Educational Opportunity September 2014 20 / 28