NYU Abu Dhabi
Conference on Education Media and Human Development.
Peter Dolton
Royal Holloway College, University of London and
Centre for Economics of Education, London School of
Economics
Peter.Dolton@lse.ac.uk

‘I’m giving education just one more try… if I fail again,
I’m entering politics!’

• 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.

• 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!

• Effect of Class size on outcomes
• Why boys are doing so much worse than girls.

60
50
40
% 30
20
Boys
Girls
10
0
1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003
Source: DfES (2003)

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

• Loads of good surveys – cohort data etc
• BUT

• NO LINK BETWEEN ADMIN DATA
• Hence impossible to find out which teacher taught which class.

• Teaching to the test to push up school scores.
• Educational ‘improvement’ by government edict.
• Squashing of teacher initiative to teach –
9/11 example.

• 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.

Peter Dolton [1]
Oscar D. Marcenaro-Gutierrez [2]
[1] Royal Holloway University of London & Centre for
Economic Performance, LSE.
[2] University of Malaga.

‘To save democracy, is it? I have been hurling stones thinking it’s about teachers’ pay!’

• 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?

• 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.

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

• 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)
Upper Secondary education
Is ra el
H ung
Cz ec h ary pub lic
Re
Ic el and
G e re ec
Por tuga l
Ita ly
Fra nc
Z e
N ew ea la nd
A us tri a
U
SA
Spa in
Fi nl and
Ire la nd
D enm ark n
Ja pa
Be lgi um
K or ea
G erm
N et any he rla nds
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)
Upper Secondary education
Nor w ay
Aus tri a
Fra nc e
Ire land Ita ly
Hung ary
Cz ec
US
A h
Re pub lic
Be lgi um
Ne w
Ze al and in
Spa
De nm ark
Fi nl and
Por tuga
Ne l the rla nds n
Ja pa
Ge rm any
Kor ea
Actual Teachers salaries (percentile) Fitted values

We also have data on
• Starting
• After 15 years
• At top of scale.
AND
• Primary
• Lower Secondary
• Upper Secondary

5 .5
5 .5
5 .5
5 .5
5 .5
5 .5
Figure 2. Relative position (percentile) of teachers’ salaries in the earnings distribution of the pop’n (Upper Secondary Education)
Argentina 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
Turkey UK USA Uruguay
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
Graphs by Country

• Most countries pay their teachers between 50-
75%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

2
Figure 3.a. Standardised Average Scores (8th grade students) by country (2006)
1
0
-1
-2
Tu ni
A rg sia en tin a
Bra
In do zi l ne sia ex
M
Th ic ai o la
U ru nd gu ay
Tu rk ey
Ch ile
Is ra el
G re ec e
Ita
Po ly rtu ga l
Sp ai n
U
N
SA orw
H ay ga ry
Fra nc
Ic el
D e an en m
Cz ec d arkUK h
Re pu bl
A ic us tri
Sw a ed en
G erm an
Ire y la
Be nd lg
Sw itz iu m an erl
Sl ov d en ia
Ja
A
N pa us et
N n tra he ew lia rla
Z nd s ea la nd
K ore
Fi nl a an d

Figure 4. Score’s percentile at 8th grade students as a function of teachers’ salaries after 15 years experience.
Finland
New Zealand
Australia
Japan
Korea
Hungary
Czech Republic
Sweden
Austria
UK
Iceland
France
Portugal
Italy
Greece
Norway
USA
Spain
Israel
Ireland
Belgium
Germany
Denmark
Turkey
Netherlands
Switzerland
10000 20000 30000 40000
Teachers' salaries (2007 USA$ PPP)
50000 60000

• 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

• 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.

• 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

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, 8 th
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 Random Effects
Specific. I Specific. II Specific. I Specific. II
0.0931*** 0.0977**
(0.0348) (0.0427)
0.0629*
(0.0333)
0.0914**
(0.0430)
0.0324
(0.0214)
0.0147**
(0.0061)
0.0307**
(0.0146)
0.0295
(0.0355)
0.0094
(0.0213)
3.7156***
(1.2548)
-0.0490*** -0.0883***
(0.0138) (0.0235)
0.0030
(0.0053)
-0.0193
(0.0127)
0.0542***
(0.0092)
3.2153***
(1.1178)
-0.0618** -0.1346*** -0.0035
(0.0247) (0.0476) (0.0226)
-0.0049
(0.0393)
1.4606*** 1.5708*** 1.3961*** 1.4623***
(0.1952) (0.2271) (0.1949) (0.2258)
1.2679*** 1.5389*** 1.0798*** 1.2700***
(0.1663) (0.2358) (0.1676) (0.2139)
1.2601*** 1.3221*** 1.1417*** 1.3975***
(0.1735)
1.3378***
(0.2196) (0.1690)
1.1901***
(0.2033)
(0.1848) (0.1812)
-3.5052*** -4.4246*** -2.5253*** -1.6493*
(0.5784) (1.2483) (0.4918) (0.8676)
211
0.50
0.11
0.01
141
0.56
0.47
0.08
211
0.44
0.63
0.40
141
0.48
0.42
0.30

• $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.

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.