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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: [email protected] Website: www.commerce.uct.ac.za/dpru/. Background & Approach. - PowerPoint PPT Presentation
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Determinants of Grade 12 Determinants of Grade 12 Pass Rates in the post-Pass Rates in the post-
Apartheid Apartheid South African South African Schooling SystemSchooling System
Haroon Bhorat and Morne Haroon Bhorat and Morne OosthuizenOosthuizen
Development Policy Research Unit, University of Cape Town
E-mail: [email protected]: www.commerce.uct.ac.za/dpru/
Background & ApproachBackground & Approach ““There is no blueprint for a model school that There is no blueprint for a model school that
can be reproduced and handed out to can be reproduced and handed out to policymakers, and such a blueprint is unlikely policymakers, and such a blueprint is unlikely to be developed in the near future”to be developed in the near future” (Hanushek,1995)(Hanushek,1995)
Massive and Swift Fiscal Reallocation:Massive and Swift Fiscal Reallocation:
1980s:1980s: R1.00R1.00 spent on White pupils, while spent on White pupils, while expenditure on each African pupils stood at expenditure on each African pupils stood at 19c19c
1997: R1.00 spent on African pupils, 71 cents per 1997: R1.00 spent on African pupils, 71 cents per White pupil.White pupil.
Background & ApproachBackground & Approach
Achievement Production Function Achievement Production Function Approach.Approach.
Specifically: How do the different Specifically: How do the different covariates simultaneously impact on covariates simultaneously impact on (school) average Grade 12 pass rates?(school) average Grade 12 pass rates?
Data principally drawn from the SRN Data principally drawn from the SRN 2000, Matric Results 2000 and 2000, Matric Results 2000 and Census EA-level data for 2001.Census EA-level data for 2001.
Descriptive Statistics: SchoolsDescriptive Statistics: SchoolsVariable/Former Department African White TotalMatric Pass Rate 48.39 95.14 55.47Pupil-Teacher Ratio 31.04 23.72 30.26Schools with User Fees 0.20 0.92 0.31Lowest Grade Offerred 7.88 6.34 7.6Non-std. classroom:learner ratio 0.0018 0.0006 0.0017Specialist classroom:learner ratio 0.004 0.028 0.008Principal Office 0.733 0.984 0.749Desks per learner 0.54 0.91 0.59At least 1 library 0.34 0.91 0.42Computer for Teaching & Learning 0.09 0.89 0.22Telecommunications 0.72 1.00 0.78Electricity for Lighting 0.71 0.98 0.73Sports Facilities 0.62 0.96 0.65Criminal Incident in Previous year 0.50 0.63 0.51Sample Size 4,019 565 5,610
Descriptive Statistics: Descriptive Statistics: EAsEAs
Variable/Former Dept.African
White Total
Share Rural 0.71 0.08 0.59Mean Household Size 4.75 4.37 4.69Children per Household 1.71 0.82 1.58Share of Informal Housing 34.67 4.42 29.6Share of Households Without: Piped Water 29.09 1.61 24.37Electricity 41.89 5.82 35.72Telephone 87.19 37.82 78.37Mean Years of Schooling for Adults 6.62 10.85 7.28
Matric Pass Rates,2000Matric Pass Rates,2000
0.0
5.1
.15
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r1_2
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ass
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05.0
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15.0
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0 20 40 60 80 100x...
African Col/Ind New Total White
Figure 1: Matric Pass Rateby Former Department
Econometric ApproachEconometric Approach Through ordinary least squared (OLS) Through ordinary least squared (OLS)
estimation, we derive a sample mean estimation, we derive a sample mean The sample median can be derived The sample median can be derived
through through quantile regression quantile regression approach approach by minimising the sum of by minimising the sum of the absolute residualsthe absolute residuals
Quantile Reg.: Estimation at different Quantile Reg.: Estimation at different points in the conditional distribution of points in the conditional distribution of the dependent variablethe dependent variable
Estimation DifficultiesEstimation Difficulties School-level data, so no intra-classroom School-level data, so no intra-classroom
variationvariation Omitted Variable Bias [parental and Omitted Variable Bias [parental and
teacher variables weak]teacher variables weak] Measurement Error [Quality of DoE Measurement Error [Quality of DoE
datasets]datasets] Selection Bias [School drop-out rates]Selection Bias [School drop-out rates] Not true post-Not true post-apartheid apartheid estimatesestimates
Production Function Results Production Function Results (1)(1)
Dependent Variable: Matric Pass RateOLS Median[1] [3]
Pupil- Teacher ratio -0.002 0.005Independent 3.011* 1.826Lowest grade -0.264* -0.284*Non-std. classroom:learner ratio -89.044* -134.539*Specialist classroom:learner ratio -14.393 -22.578*Platoon School -1.442 -2.768Used for ABET -0.728 -0.582Principal’s Office -0.837 -0.596Accom. For Staff 3.462* 2.347*Tuckshop 0.840 0.843Boards per classroom -0.075 -0.079Seats per learner 0.346 -0.050Desks per learner 1.455* 1.094Overhead p.l 8.747 3.714Photocopier p.l 124.346 223.967
Production Function Results Production Function Results (1) (1) contd.contd.
Dependent Variable: Matric Pass Rate
OLS Median
[1] [3]Library 2.634* 2.330*Computer for teaching 10.392* 11.173*Computer for admin 6.680* 7.199*Phone 3.028* 3.889*Water Indoors -0.016 -0.328Electricity 2.591* 3.619*Sports facilities 2.477* 3.429*Crime Incident -2.663* -2.492*Col./Indian School 13.039* 16.208*White School 26.904* 29.159*New School 1.908* 3.258*
Production Function Results Production Function Results (1) (1) contd.contd.
Dependent Variable: Matric Pass Rate
OLS Median
[1] [3]
Rural 1.162 1.611
Household Size 0.134 0.137
Children per hh. -1.067* -0.603
Adult mean yrs of schooling 0.813* 0.726*
Poverty Index -0.182 -0.800
Sample Size 5014 5014
Pseudo R2 0.440 0.301
Key ResultsKey Results Insignificance of pupil-teacher ratios in Insignificance of pupil-teacher ratios in
determining the mean or the median pass ratedetermining the mean or the median pass rate Physical infrastructure: Almost all classroom Physical infrastructure: Almost all classroom
resources insignificant in shaping pass rates. resources insignificant in shaping pass rates. butbut very specific variables are significant, namelyvery specific variables are significant, namely Non-standard classrooms and Staff Accomm. Non-standard classrooms and Staff Accomm.
Knowledge Infrastructure critical.Knowledge Infrastructure critical. Environm. factors e.g. crime, electricity & Environm. factors e.g. crime, electricity &
telecomm. Influential. telecomm. Influential. Classification Dummies are critical and reflect Classification Dummies are critical and reflect
composite of important omitted variablescomposite of important omitted variables Household Variables: Household Variables:
Location & Asset Poverty insignificantLocation & Asset Poverty insignificant Dependency Ratios & Adult Years of Schooling SignificantDependency Ratios & Adult Years of Schooling Significant
Production Function Results Production Function Results (2)(2)
Dependent Variable: Matric Pass Rate
Percentile10th
(21.4%)25th
(33.6%)75th
(77.3%) 90th
(96.7%) Pupil- Teacher ratio -0.010 0.009 -0.015 -0.033*Independent -1.553 1.641 4.294* 2.705Lowest grade -0.166* -0.025 -0.248* -0.256*Non-std. classroom:learner ratio -219.887* -107.299* -19.379 44.605Specialist classroom:learner
ratio -8.166 -10.782* -2.251 6.828Platoon School -3.091 -4.275* 2.189 3.975*Used for ABET -1.008 -0.337 -0.399 -1.330Principal’s Office 0.551 0.800 -2.496* -1.157Accom. For Staff 1.890 1.320* 2.455* 2.352*Tuckshop 3.613* 0.672 -0.603 -1.129Boards per classroom -0.011 -0.085 -0.148 0.096Seats per learner 0.603 -0.172 -0.727* -0.277Desks per learner 1.022 1.301* 0.631 0.801Overhead p.l 6.958 5.399 3.535 22.054*Photocopier p.l -337.833* 152.276 529.648* 151.735
Pupil-Teacher Ratios Pupil-Teacher Ratios RevisitedRevisited
-.1-.0
50
.05
Coe
ffici
ent o
n P
upil-
Teac
her R
atio
0 .2 .4 .6 .8 1Quantiles
Quantiles OLS
Coefficient Estimates of Pupil-Teacher Ratio Impact on Grade 12 Pass Rates
Production Function Results Production Function Results (2) c(2) contd.ontd.
Dependent Variable: Matric Pass Rate
Percentile
10th 25th 75th 90th
Library 1.812 2.568* 1.588* 1.260
Computer for teaching 9.807* 10.389* 9.201* 6.189*
Computer for admin 3.269* 5.128* 9.843* 9.478*
Phone 1.630 2.577* 3.517* 2.795*
Water Indoors 1.007 0.165 -0.351 0.095
Electricity 0.146 3.254* 3.499* 1.594*
Sports facilities 1.395 1.688* 4.095* 2.703*
Crime Incident -1.967* -2.059* -1.525* -2.847*
Col./Indian School 19.460* 18.568* 11.037* 5.536*
White School 47.229* 41.621* 16.967* 9.660*
New School 1.238 -0.747 3.258* 1.804
Production Function Results Production Function Results (2) c(2) contd.ontd.
Dependent Variable: Matric Pass Rate
Percentile
10th 25th 75th 90th
Rural 1.257 0.222 2.739* 1.223
Household Size 0.092 0.028 0.132 0.355*
Children per hh. -1.037 -0.540 -0.727 -1.529*
Adult mean yrs of schooling 1.009* 0.720* 0.905* 0.579*
Poverty Index -0.654 0.512 -0.483 0.495
Sample Size 5014 5014 5014 5014
Pseudo R2 0.237 0.275 0.303 0.220
Adult SchoolingAdult Schooling.6
.81
1.2
0 .2 .4 .6 .8 1y
quantiles OLS
Quantile and OLS Coefficients on Adult Schooling
Five Composite Results Five Composite Results 1.1. The The Pupil-Teacher RatioPupil-Teacher Ratio is insignificant in is insignificant in
explaining the performance of all schools – barring explaining the performance of all schools – barring those in the 80th percentile upward.those in the 80th percentile upward.
2.2. Relative unimportance of Relative unimportance of Physical Classroom Physical Classroom ResourcesResources. Boards, desks and seats have low . Boards, desks and seats have low explanatory power.explanatory power.
1.1. Caveat: Non-std. classrooms do matterCaveat: Non-std. classrooms do matter3.3. Knowledge InfrastructureKnowledge Infrastructure, and access to services , and access to services
and utilities critical in explaining relative and utilities critical in explaining relative performance. performance.
4.4. Teacher and Parental CharacteristicsTeacher and Parental Characteristics matter. matter. 1.1. significant results for onsite staff significant results for onsite staff
accommodation; adult years of schooling and the accommodation; adult years of schooling and the classification dummiesclassification dummies
5.5. A core group of poorly resourced, rural-based high-performing A core group of poorly resourced, rural-based high-performing former Homeland Schools – requires closer analysisformer Homeland Schools – requires closer analysis
Production Function Production Function Results (3)Results (3)
Dependent Variable: Matric Pass Rate
Inter-Quantile Range
90th - 10th 90th - 50th 50th - 10th
Pupil- Teacher ratio -0.023 -0.038 0.015Independent 4.257 0.878 3.379Lowest grade -0.09 0.028 -0.118Non-std. classroom:learner
ratio 264.493** 179.144 85.348Specialist classroom:learner
ratio 14.994 29.406 -14.411Platoon School 7.066** 6.743** 0.323Used for ABET -0.323 -0.748 0.426Principal’s Office -1.708 -0.561 -1.146Accom. For Staff 0.462 0.006 0.456Tuckshop -4.741* -1.972** -2.770**Boards per learner 0.107 0.175 -0.068Seats per learner -0.88 -0.227 -0.653Desks per learner -0.22 -0.293 0.072Overhead p.l 15.096 18.34 -3.243
Photocopier p.l489.568**
* -72.232 561.800*
Production Function Production Function Results (3)Results (3)
Dependent Variable: Matric Pass Rate
Inter-Quantile Range
90th - 10th 90th - 50th 50th - 10th
Library -0.552 -1.069 0.517Computer for teaching -3.618*** -4.984* 1.366Computer for admin 6.209* 2.28 3.929**Phone 1.165 -1.094 2.259***Water Indoors -0.912 0.49 -1.402Electricity 1.448 -2.025 3.474Sports facilities 1.308 -0.727 2.035***Crime Incident -0.88 -0.355 -0.525Col./Indian School -13.924* -10.671* -3.253White School -37.569* -19.499* -18.071*New School 0.567 -1.454 2.021Unspecified Sch. 5.223 -4.644 9.868***
Production Function Production Function Results (3)Results (3)
Dependent Variable: Matric Pass Rate
Inter-Quantile Range
90th - 10th 90th - 50th 50th - 10th
Rural -0.033 -0.388 0.354Household Size 0.263 0.218 0.046Children per hh. -0.491 -0.926 0.435Adult mean yrs of schooling -0.43 -0.147 -0.284Poverty Index 1.149 1.295 -0.146Constant 53.097* 37.318* 15.780*High Quantile R2 0.22 0.22 0.301Low Quantile R2 0.237 0.301 0.237
Key Relative Key Relative Performance Results Performance Results
Inherited Socio-Economic Factors are Inherited Socio-Economic Factors are Insignificant i.t.o Relative PerformanceInsignificant i.t.o Relative Performance
P-T Ratio is Insignificant in Explaining P-T Ratio is Insignificant in Explaining Relative PerformanceRelative Performance
Non-Std. Classrooms & Platoons increase Non-Std. Classrooms & Platoons increase dispersion in pass ratesdispersion in pass rates
Administrative efficiency and knowledge Administrative efficiency and knowledge infrastructure matter for reducing the infrastructure matter for reducing the performance gapperformance gap
Classification Dummies: Very Strong EffectClassification Dummies: Very Strong Effect
[Early][Early] Policy Policy SuggestionsSuggestions
Know Which Portion of the Performance Spectrum you Know Which Portion of the Performance Spectrum you want to Influence, as Determinants are Differentwant to Influence, as Determinants are Different
Do not Invest in Reducing Classroom SizeDo not Invest in Reducing Classroom Size Invest in Learning Infrastructure….but Invest wisely!Invest in Learning Infrastructure….but Invest wisely! Investment in Knowledge Infrastructure will reap Investment in Knowledge Infrastructure will reap
rewardsrewards Try and Better Understand what is going on in Former Try and Better Understand what is going on in Former
Homeland Schools (Natural Experiments?)Homeland Schools (Natural Experiments?) Importance of Classification Dummies Suggests that Importance of Classification Dummies Suggests that
many teacher, pupil characteristics are critical, and we many teacher, pupil characteristics are critical, and we need to understand what components impact on pass need to understand what components impact on pass rates.rates.
Socio-Economic Status Not As Critical as may have been Socio-Economic Status Not As Critical as may have been assumed.assumed.