Transcript If You Pay Peanuts do You Get Monkeys? A Cross Country

NYU Abu Dhabi
Conference on Education Media and Human Development.
Quantitative Analysis of
Education Policy in the UK
Peter Dolton
Royal Holloway College, University of London and
Centre for Economics of Education, London School of
Economics
[email protected]
‘I’m giving
education just
one more try…
if I fail again,
I’m entering
politics!’
Outline
• Examples of Analysis (and failures of
analysis) of Policy in the UK (and data).
• My take on the ‘causal’ v ‘observational’
debate - IDENTIFICATION
• Brief follow up on the Andreas Scheicher
presentation on a paper I am writing.
Examples of Key Education Policy
Reform Questions
• What are effects of National Curriculum from
1988?
• What has been the effect of the Literacy and
Numeracy Hour?
• What is the effect of National KS tests at age
7,11, 13, 16, 18:
– Have educational standards been rising
– Has publication of school results encouraged
competition?
• What has been the effect of the Introduction of a
School Teacher Performance threshold on pay
in 2000?
Some outputs are easier to observe than others!
Recent Policy Questions
• Effect of Class size on outcomes
• Why boys are doing so much worse than
girls.
The proportion of boys and girls
achieving 5 good GCSEs
60
50
Boys
Girls
40
%
30
20
10
0
1975
1977
1979
Source: DfES (2003)
1981
1983
1985
1987
1989 1991
1993
1995
1997
1999
2001
2003
Data to Answer these Questions
Administrative Data on:
• National Pupil Database on every child
with all their scores on all KS tests.
• Database of Teacher Records.
• School level data on performance in KS
tests.
• Assorted other Admin data on House
Prices, (Land Registry), Deprivation etc
Other Data Sources
• Loads of good surveys – cohort data etc
• BUT
• NO LINK BETWEEN ADMIN DATA
• Hence impossible to find out which
teacher taught which class.
Some Real Effects of these
Policies Which we don’t need data
to tell us.
• Teaching to the test to push up school
scores.
• Educational ‘improvement’ by government
edict.
• Squashing of teacher initiative to teach –
9/11 example.
IDENTIFICATION
• OLS – observational
• RCT – ‘causal’
Many other techniques
• Panel, Longitudinal, Cohort, Spatial
• Statistical Matching
• Difference-in-Differences
• Regressional Discontinuity Design
• Instrumental Variables - LATE
• Often involve the creative use of:
• Some administrative change or rule like
Miamonides Rule (Angrist and Lavy)
• Changes in Policy
• Above techniques may give us as close an
estimate of causal effects as you are going
to get with RCTs.
If You Pay Peanuts do You Get
Monkeys? A Cross Country
Comparison of Teacher Pay
and Pupil Performance.
Peter Dolton[1]
Oscar D. Marcenaro-Gutierrez[2]
[1] Royal Holloway University of London & Centre for
Economic Performance, LSE.
[2] University of Malaga.
UK ADVERT
– Make a Difference – Become
a Teacher!!!!
‘To save
democracy,
is it? I have
been
hurling
stones
thinking it’s
about
teachers’
pay!’
What Makes a Good Teacher??
Not sure we really
know the answer
BUT
1. Central Motivation
• Why do teachers in Holland Earn 4 times
teachers in Israel (after allowing for PPP
adjustments)?
• Kids in some countries do 2-6 times as
well as kids in other countries.
• Is there a link between these 2 facts –
• If we take relative salary as a measure of
teacher quality, is it the case that kids
perform better?
Motivation cont’d
• Think of two possible basic causal
mechanisms:
• You pay teachers better gives them an
incentive to work harder and be more
effective in teaching kids.
• You pay teachers better and this raises
the status of the job and induces more
able young people to want to be teachers
in the future.
3. Data
We have new data to do this with
• OECD data on teachers salaries
• PISA, TIMSS data on pupil performance.
• PISA 2000, 2003, 2006 for Maths, Science
and Reading
• TIMSS 1995, 1999, 2003 Maths and
Science
Data cont
How do we measure teacher
salary?
• In terms of real PPP $
• Relative to country’s standard of living - In
terms of $PPP divided by GDP per head.
• Relative point in the income distribution of
the country. (Assuming Income is
lognormal, and we have Gini coeff and
Ave earnings)
Figure 1.a. Actual and fitted Upper Secondary school teachers’
salaries after 15 years experience in 2007 $ PPP (2005)
I
C H sra
ze u el
ch ng
R ary
ep
ub
Ic lic
el
an
G d
re
Po ece
rt u
ga
l
Ita
N F ly
ew ra
Ze nce
al
a
A nd
us
tri
a
U
SA
Sp
a
Fi in
nl
a
Ir nd
e
D lan
en d
m
ar
k
Ja
B pan
el
gi
um
K
G ore
N erm a
et a
he ny
rla
nd
s
Upper Secondary education
Actual Teachers salaries after 15 years
Fitted values
Figure 1.c. Actual and fitted Upper Secondary school teachers’
salaries after 15 years experience relative to the earnings
distribution of the whole population (2003)
N
or
w
a
A y
us
tri
Fr a
an
c
Ir e
el
an
d
Ita
H ly
un
ga
C
ry
ze
ch U
R SA
ep
ub
B li
N elg c
ew iu
Ze m
al
an
d
Sp
D a in
en
m
a
Fi rk
nl
a
Po nd
N rt u
et g
he al
rla
nd
s
Ja
G pan
er
m
an
y
K
or
ea
.4
.5
.6
.7
.8
Upper Secondary education
Actual Teachers salaries (percentile)
Fitted values
Teacher Salaries
We also have data on
• Starting
• After 15 years
• At top of scale.
AND
• Primary
• Lower Secondary
• Upper Secondary
Australia
Austria
Belgium
Brazil
Chile
Czech Rep ublic
Denmark
Finland
France
Germany
Greece
Hungary
Indonesia
Ireland
Italy
Jap an
Korea
M alaysia
Netherlands
New Zealand
Norway
Peru
Philip pines
Portugal
Sp ain
Sweden
Switzerland
Thailand
Tunisia
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
Turkey
UK
USA
Uruguay
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
0
.25 .75
.5
1
0
.25 .75
.5
1
0
.25 .75
.5
1
0
.25 .75
.5
1
0
.25 .75
.5
1
0
.25 .75
.5
1
Argentina
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
Figure 2. Relative position (percentile) of teachers’ salaries in the
earnings distribution of the pop’n (Upper Secondary Education)
Year
Percentile position of teachers (starting wages) in the earnings distribution
Percentile position of teachers (after 15 years) in the earnings distribution
Percentile position of teachers (top wages) in the earnings distribution
Data Conclusions
• Most countries pay their teachers between 5075%ile.
• Some countries have flat career salaries:
Denmark, Finland, Sweden, Peru
• Other significant advancement:
Austria, Belgium, France etc
• Some countries teacher wages are falling back:
Indonesia, Chile, Thailand, Australia
• Others teachers are being paid better:
Brazil, Czech, Uruguay
A Tu
rg ni
en sia
In B tin
d o ra a
z
M nes il
Th ex ia
U ailaico
ru n
Tuguad
rk y
C ey
h
Is ile
G ra
re el
e
Po It ce
rtualy
Spgal
a
N USin
H orw A
un a
Frgary
Ic an y
C De el ce
ze
a
ch nm nd
R a rk
ep U
A ublK
Swust ic
G e ria
e r de
m
Ir ann
Sw Be ela y
itz lgi nd
Sl erlaum
ov n
en d
A
J
N a i
N ethust pa a
ew e ra n
Zerlanlia
al ds
K and
Fi o r
nl ea
an
d
Figure 3.a. Standardised Average Scores (8th grade students) by
country (2006)
2
1
0
-1
-2
100
Figure 4. Score’s percentile at 8th grade students as a function of
teachers’ salaries after 15 years experience.
Finland
New Zealand
Korea
Netherlands
80
Australia
Japan
60
Sweden
Czech Republic
Iceland
Israel
Switzerland
Austria
UK
Denmark
France
40
Hungary
Belgium
Ireland
Germany
Portugal
Italy
Greece
Norway
USA
Spain
0
20
Turkey
10000
20000
30000
40000
Teachers' salaries (2007 USA$ PPP)
50000
60000
4. Econometric Estimation
• Teacher Salaries -> function of:
Supply of Teachers
Demand for Teachers
• Production Function for Pupil Outcomes:
function of : Teacher Hours,
Pupil Teacher Ratios
Educational Expenditure
GDP Growth
4. Econometric Estimation:
Identification
• Use panel data therefore:
• With fixed country effects we are arguing
that there are not systematic influences on
pupil outcomes which are:
– Not measured i.e. in u
– and correlated with teacher earnings.
• Then identification of ‘causal effects’ would
rely on changes.
Controls
•
•
•
•
•
•
•
Teaching Hours
Pupil/Teacher ratios
Fraction of Women
GDP growth
Educational Expenditure
Growth in size of teacher cohort.
Growth in size of pupil pop’n
5. Results
Teachers salaries vary across country:
• -ve With supply
• +ve with Pupil/teacher ratios
• -ve with size of pupil cohort.
Table 3.a. Estimates explaining the Standardised scores for each type of
Assessment, 8th grade students.
Teaching hours per year (hundreds)
Pupil/Teacher ratio
Women fraction of teaching staff (%)
Teachers' salaries after 15 years in 1000$ (deflated)
Percentile position of teachers (after 15 years)
GDP growth (%)
Year dummies: (reference year 1995)
1999
2000
2003
2005
Constant
Observations
F-statistic
R-squared Within
R-squared Between
R-squared Overall
Fixed Effects
Specific. I
Specific. II
0.0931***
0.0977**
(0.0348)
(0.0427)
0.0324
0.0295
(0.0214)
(0.0355)
0.0147**
0.0094
(0.0061)
(0.0213)
0.0307**
(0.0146)
3.7156***
(1.2548)
-0.0618**
-0.1346***
(0.0247)
(0.0476)
Random Effects
Specific. I
Specific. II
0.0629*
0.0914**
(0.0333)
(0.0430)
-0.0490*** -0.0883***
(0.0138)
(0.0235)
0.0030
-0.0193
(0.0053)
(0.0127)
0.0542***
(0.0092)
3.2153***
(1.1178)
-0.0035
-0.0049
(0.0226)
(0.0393)
1.4606***
(0.1952)
1.2679***
(0.1663)
1.2601***
(0.1735)
1.3378***
(0.1848)
-3.5052***
(0.5784)
211
1.4623***
(0.2258)
1.2700***
(0.2139)
1.3975***
(0.2033)
-4.4246***
(1.2483)
141
1.3961***
(0.1949)
1.0798***
(0.1676)
1.1417***
(0.1690)
1.1901***
(0.1812)
-2.5253***
(0.4918)
211
0.50
0.11
0.01
0.56
0.47
0.08
0.44
0.63
0.40
0.48
0.42
0.30
1.5708***
(0.2271)
1.5389***
(0.2358)
1.3221***
(0.2196)
-1.6493*
(0.8676)
141
Marginal Effects
• $5000 or 15% rise in teachers earnings
• OR
• 5% shift up the wage distribution for
teachers
• will mean .20 of a SD in test score and
hence around 8% rise in student
performance.
6. Implications
If we wish to improve pupil scores we need to:
• Pay teachers more – further up income distn
• Reduce pupil/teacher ratios
To reduce inequality of student performance we
need:
• Reduce pupil/teacher ratios
NOT Increase teaching hours as ambiguous effect.