Transcript Explaining Education Returns and Racial Discrimination

Explaining Education Returns and Racial
Discrimination with Numeric competence,
confidence and school quality in South Africa
Gideon du Rand, Hendrik van Broekhuizen and Dieter von Fintel
Department of Economics, Stellenbosch University
PSPPD Project – April 2011
Programme to Support Pro-Poor Policy Development
A partnership between the Presidency, Republic of South Africa and the European Union
Motivation
• The role of education in economic development is
undisputed
• Identified as a binding constraint to growth in South
Africa
• Developing the appropriate skills for the needs of the labour
market
• Given South Africa’s high levels of (secondary)
enrollment and good access to education…
• What defines this binding constraint?
• The role of education quality?
• South Africa’s performance in international standardised tests
compares poorly with other developing countries
• Access to education is successful; access to quality education is still
limited
Programme to Support Pro-Poor Policy Development
A partnership between the Presidency, Republic of South Africa and the European Union
Motivation
• How much does an additional year of education increase
earnings?
• How much of this “value added” is the result of the quantity of
education?
• It is well-documented that at low levels of education returns are low,
and very high for post-secondary qualifications
• How much of the “value added” is the result of the quality of the
additional education received?
• Persisting inequalities in outputs of the schooling system, despite
fiscal equalisation
• How much of what we usually consider to be racial
discrimination in earnings is driven by school quality?
• In other words: is anti-discrimination legislation correctly
targeted towards the labour market, or is much of the root still in
the school system?
Programme to Support Pro-Poor Policy Development
A partnership between the Presidency, Republic of South Africa and the European Union
Data
• National Income Dynamics Study of 2008
• Rich survey in which income, sociodemographic
features are measured
• And more importantly a numeracy test
• Respondents completed a short test of numeric ability
• Represents inherent individual level ability in addition to the
cognitive value added by schools
• Sample selection issues dominate the estimation procedure
(discussed later)
• And information on historical matric performance of schools
• A less noisy measure
• Represents quality of schools which labour market participants
attended
Programme to Support Pro-Poor Policy Development
A partnership between the Presidency, Republic of South Africa and the European Union
Results – returns to numeric skills
The Numeracy Score Component of Marginal Returns
to Education – Black Population
Marginal Return to Education (%)
60%
50%
40%
30%
20%
10%
0%
5
5
6
7
8
9
10
11
12
13
14
15
16
Programme to Support Pro-Poor Policy Development
Returns to quality 2.59% 3.13% 3.59% 3.95% 4.23% 4.43% 4.53% 4.55% 4.48% 4.32% 4.07% 3.74%
A partnership between the Presidency, Republic of South Africa and the European Union
Returns to quantity 3.19% 4.52% 6.44% 8.93% 12.00% 15.66% 19.89% 24.70% 30.09% 36.06% 42.61% 49.74%
Results – returns to numeric skills
• Increasing returns to an additional year of
education, as usually found in South Africa
• From about 5% at primary level to about 45% for a
Bachelors degree
• Reflective of the skills shortage
• High return to scarce type of labour
• The numeric skills component ranges from
2.6% to 4.5%
• Suggests that quality and cognitive skill is important
in employers’ decisions
• And not just the demand for specific levels of
education
Programme to Support Pro-Poor Policy Development
A partnership between the Presidency, Republic of South Africa and the European Union
Results – labour market discrimination vs access to
quality schools
• Unexplained white-black wage premia
(discrimination) using different measures
80%
70%
60%
29.20%
50%
40%
30%
20%
10%
Due to quality
Remaining
7.60%
33.00%
39.70%
0%
Numeracy
School Quality
Programme to Support Pro-Poor Policy Development
A partnership between the Presidency, Republic of South Africa and the European Union
Results - discrimination
• Different results due to different samples
• Reduction of wage premium from
• 40.6% to 33% when controlling for numeric ability
• A fall of 7.6 percentage points (or about 19% of the discrimination
component)
• 69% to 40% when controlling for historical school quality measures
• A fall of 29 percentage points (or about 37% of the discrimination
component)
• Suggests that wage differentials are in part driven by natural
abilities and the value added by schools
• Though other factors remain
• Separate “labour market discrimination” and “access to
quality education” issues at play
Programme to Support Pro-Poor Policy Development
A partnership between the Presidency, Republic of South Africa and the European Union
Correspondence with other results
• Burger & van der Berg (2011)
• Simulated cognitive skills and decomposed wage gaps
• About 74% of unexplained wage gap (“discrimination”)
explained by school quality
• R10.70 of R14.44
• Far more important than educational attainment premia,
which contributes only R3.50 to wages, roughly a third of
what quality contributes
• These results add more emphasis to school quality than our
own
Programme to Support Pro-Poor Policy Development
A partnership between the Presidency, Republic of South Africa and the European Union
Van der Berg & Burger (2011)
Wage in Rand per hour (2000 Rand values)
R 25
R 23.83
R 20
R 10.70
R 15
R 3.74
R 3.74
R 3.50
R 3.50
R 3.50
R 5.89
R 5.89
R 5.89
+ Education
attainment
+ Unexplained
+ Education
quality
R 10
R5
R 5.89
R0
Black wage
= White wage
Programme to Support Pro-Poor Policy Development
A partnership between the Presidency, Republic of South Africa and the European Union
Results – Respondent Confidence
Revealed perceptions of abilities
• Some individuals chose to write easier/ more difficult tests than they
should have
• Underconfident have lower wages than the average
• Overconfident have highest and lowest wages
.2
.1
0
kdensity lwages
.3
.4
• Indicate perception must be backed up by actual ability – but confidence helps!
-2
0
2
4
6
8
x
Underconfident
Overconfident
Realistic
Programme to Support Pro-Poor Policy Development
A partnership between the Presidency, Republic of South Africa and the European Union
Results – sampling issues
• Those who took numeracy tests were
• More educated
• Indicated that they were more confident in their writing
abilities
• More likely to search for jobs
• Those who provided school quality data were
• More educated
• Younger (as they had exited school more recently)
• All of these factors require corrections in the estimates
• Instrumental variables (not successful)
• Double Heckman estimates
Programme to Support Pro-Poor Policy Development
A partnership between the Presidency, Republic of South Africa and the European Union
Results – impacts of sampling
0.8
0.7
0.6
Working Age Population
0.5
Test Writers - no controls
for numeracy
Test Writers - Controlling
for Numeracy
TestWriters
Writers–-Controlling
Double
Test
Heckman
for
Numeracy and
0.4
0.3
0.2
Selection Issues
0.1
0
0
-0.1
5
10
15
20
Programme to Support Pro-Poor Policy Development
A partnership between the Presidency, Republic of South Africa and the European Union
1
3
Results – impacts of sampling
• Sample of test respondents had higher returns to
education
• Higher ability individuals took the test
• We do not capture the poorest part of ability distribution
• Hence numeracy does not appear to make a difference to
education returns initially
• …except if we account for sample selection issues
• Then we find the returns to quality that are reported earlier
Programme to Support Pro-Poor Policy Development
A partnership between the Presidency, Republic of South Africa and the European Union
Conclusions and Policy Implications
• High returns to higher levels of education are only
partially explained by school quality
• Suggests that skills shortage is dominated by a lack of
quantity of educated workers, though quality
nevertheless has an important role to play
• School quality matters to employers’ reward of workers
• Long-term labour market benefits to improving school quality
Programme to Support Pro-Poor Policy Development
A partnership between the Presidency, Republic of South Africa and the European Union
Conclusions and Policy Implications
• Racial discrimination (once controlling for educational
quantity differences)
• Has a large component that is explained by disparities in
school quality
• The extent differs by estimation strategy
• Ranges from 20-74%
• Even the lowerbound is a high figure
• Racial patterns of school outputs persist despite shifts in fiscal
allocations
• Suggests that at least some of the racial inequalities in wages is
determined long before individuals enter the labour market
• Therefore a combination of school and labour market policies
required
Programme to Support Pro-Poor Policy Development
A partnership between the Presidency, Republic of South Africa and the European Union
Conclusions and Policy Implications
• School vs labour market policies
• Educational attainment (at secondary level) has improved vastly already
• However, this has reduced labour market returns for this group, due to a
greater supply of this type of labour
• Bottleneck: progression to “high return” education (at the tertiary level)
• The “quantity” issue of a lack of highly skilled workers
• Constraint is that poor quality (at primary / secondary level) limits this
progression
• Not a labour market issue directly and should be addressed by education
policy
• Affirmative action should only address labour market disparities (and not
educational quality differentials)
• In the long-run, improvements in school quality will address some of the
labour market disparities and remove some of what we observe as
“discrimination”
Programme to Support Pro-Poor Policy Development
A partnership between the Presidency, Republic of South Africa and the European Union