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Determinants of Grade 12 Pass Rates in the post- Apartheid South African Schooling System Haroon Bhorat and Morne Oosthuizen Development Policy Research Unit, University of Cape Town E-mail: hbhorat@commerce.uct.ac.za Website: www.commerce.uct.ac.za/dpru/. Background & Approach.
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Determinants of Grade 12 Pass Rates in the post-Apartheid South African Schooling SystemHaroon Bhorat and Morne OosthuizenDevelopment Policy Research Unit, University of Cape TownE-mail: hbhorat@commerce.uct.ac.zaWebsite: www.commerce.uct.ac.za/dpru/
Background & Approach • “There is no blueprint for a model school that can be reproduced and handed out to policymakers, and such a blueprint is unlikely to be developed in the near future” (Hanushek,1995) • Massive and Swift Fiscal Reallocation: • 1980s:R1.00 spent on White pupils, while expenditure on each African pupils stood at 19c • 1997: R1.00 spent on African pupils, 71 cents per White pupil.
Background & Approach • Achievement Production Function Approach. • Specifically: How do the different covariates simultaneously impact on (school) average Grade 12 pass rates? • Data principally drawn from the SRN 2000, Matric Results 2000 and Census EA-level data for 2001.
Econometric Approach • Through ordinary least squared (OLS) estimation, we derive a sample mean • The sample median can be derived through quantile regression approach by minimising the sum of the absolute residuals • Quantile Reg.: Estimation at different points in the conditional distribution of the dependent variable
Estimation Difficulties • School-level data, so no intra-classroom variation • Omitted Variable Bias [parental and teacher variables weak] • Measurement Error [Quality of DoE datasets] • Selection Bias [School drop-out rates] • Not true post-apartheid estimates
Key Results • Insignificance of pupil-teacher ratios in determining the mean or the median pass rate • Physical infrastructure: Almost all classroom resources insignificant in shaping pass rates. but very specific variables are significant, namely • Non-standard classrooms and Staff Accomm. • Knowledge Infrastructure critical. • Environm. factors e.g. crime, electricity & telecomm. Influential. • Classification Dummies are critical and reflect composite of important omitted variables • Household Variables: • Location & Asset Poverty insignificant • Dependency Ratios & Adult Years of Schooling Significant
Five Composite Results • The Pupil-Teacher Ratio is insignificant in explaining the performance of all schools – barring those in the 80th percentile upward. • Relative unimportance of Physical Classroom Resources. Boards, desks and seats have low explanatory power. • Caveat: Non-std. classrooms do matter • Knowledge Infrastructure, and access to services and utilities critical in explaining relative performance. • Teacher and Parental Characteristics matter. • significant results for onsite staff accommodation; adult years of schooling and the classification dummies • A core group of poorly resourced, rural-based high-performing former Homeland Schools – requires closer analysis
Key Relative Performance Results • Inherited Socio-Economic Factors are Insignificant i.t.o Relative Performance • P-T Ratio is Insignificant in Explaining Relative Performance • Non-Std. Classrooms & Platoons increase dispersion in pass rates • Administrative efficiency and knowledge infrastructure matter for reducing the performance gap • Classification Dummies: Very Strong Effect
[Early] Policy Suggestions • Know Which Portion of the Performance Spectrum you want to Influence, as Determinants are Different • Do not Invest in Reducing Classroom Size • Invest in Learning Infrastructure….but Invest wisely! • Investment in Knowledge Infrastructure will reap rewards • Try and Better Understand what is going on in Former Homeland Schools (Natural Experiments?) • Importance of Classification Dummies Suggests that many teacher, pupil characteristics are critical, and we need to understand what components impact on pass rates. • Socio-Economic Status Not As Critical as may have been assumed.