2014.10.21 - naec seminar_skills-inequality-well-being
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SKILLS DISTRIBUTION, WAGE INEQUALITY AND SOCIAL
INEQUALITY
Dirk Van DammeOECD Directorate for Education and Skills (EDU)
New Approaches to Economic ChallengesSeminar, 21 October 2014
Marco PaccagnellaOECD Directorate for Education and Skills (EDU)
• Overall purpose of this seminar is to provide evidence on how the distribution of skills (and not only the average) relates to various outcome measures:– Wage inequality– Social inequality (Gini coefficient)– Economic output (GDP/capita)
The distribution of human capital matters
• Analysis of OECD Survey of Adult Skills (PIAAC) data (2012)– Focusing on numeracy as a critically
important foundation skill– Focusing on cross-country variation
The distribution of human capital matters
SKILLS AND WAGE INEQUALITY
• Marco Paccagnella
• EDU/SBS
• High levels of inequality are a huge political concern, especially in the midst of a prolonged recession
• Human capital is a crucial factor affecting the growth potential of an economy…
• …but how does it affect inequality?– Increasing returns to education?
– Skill-biased technical change?
– Which role for economic institutions?
Motivation
• Joint analysis of the distribution of skills (numeracy proficiency) and (labour) earnings
• Estimates of the returns to education and proficiency along the distribution of wages
• Decomposition of cross-country differences in wage inequality
This talk
• PIAAC: unique dataset with comparable individual-level information on education, proficiency, and wages
• Drawback: can’t look at the household level
• Preferred measure of dispersion: percentile ratios/differences
The data
• Consistent ranking of countries, irrespective of the indicator and the domain (literacy/numeracy)– High dispersion in US, FR, ES, CA– Low dispersion in JP, KR, SK, CZ
• Bottom-end inequality generally higher than top-end inequality
The distribution of proficiency
Inequality indices – Numeracy SkillsCountry CV 90th-10th 90th-50th 50th-10th
Australia 0.21 136.59 62.33 74.26Austria 0.18 121.24 55.95 65.30Canada 0.21 138.28 62.61 75.67Czech Republic 0.16 110.94 50.90 60.03Denmark 0.18 126.10 57.47 68.63Estonia 0.17 113.92 53.46 60.45Finland 0.18 127.65 59.21 68.44France 0.22 141.80 62.39 79.41Germany 0.20 133.09 59.10 73.99Ireland 0.21 129.33 59.28 70.05Italy 0.20 126.26 59.87 66.39Japan 0.15 110.05 50.89 59.17Korea 0.17 114.60 51.31 63.29Netherlands 0.18 125.11 53.97 71.14Norway 0.19 131.77 57.90 73.88Poland 0.20 127.86 59.20 68.66Slovak Republic 0.17 117.16 51.03 66.12Spain 0.21 129.61 57.08 72.53Sweden 0.20 132.84 58.74 74.10United States 0.23 144.84 66.66 78.18
Flanders (Belgium) 0.18 127.84 57.13 70.71England/N. Ireland (UK) 0.21 137.71 64.38 73.33 OECD Average 0.20 130.99 59.20 71.79
Dispersion in Numeracy
Inequality indices – Literacy SkillsCountry CV 90th-10th 90th-50th 50th-10th
Australia 0.18 122.28 55.04 67.24Austria 0.16 110.10 50.51 59.60Canada 0.18 125.56 56.20 69.36Czech Republic 0.15 102.34 47.06 55.28Denmark 0.18 116.25 49.88 66.38Estonia 0.16 111.84 50.99 60.85Finland 0.18 123.49 55.16 68.33France 0.19 123.94 54.03 69.91Germany 0.18 121.56 54.40 67.16Ireland 0.18 115.71 52.14 63.57Italy 0.18 113.74 53.68 60.05Japan 0.13 99.78 44.06 55.72Korea 0.15 103.81 46.31 57.49Netherlands 0.17 121.61 51.88 69.73Norway 0.17 115.30 49.98 65.32Poland 0.18 120.92 55.11 65.81Slovak Republic 0.15 99.37 42.89 56.49Spain 0.19 123.52 55.30 68.22Sweden 0.18 122.24 52.86 69.38United States 0.18 126.13 57.14 68.99entities Flanders (Belgium) 0.17 119.07 51.11 67.96England/N. Ireland (UK) 0.18 123.45 57.03 66.41 OECD Average 0.18 119.41 53.29 66.12
Dispersion in Literacy
Distribution of Numeracy Proficiency0
.00
2.0
04
.00
6.0
08
.01
0 100 200 300 400 500
United States Czech RepublicFrance JapanOECD Average
FRANCEJAPAN
Distribution of (log) Hourly Wages
FRANCE
JAPAN
Skills and Wage Inequality
Top-end Inequality
Bottom-end Inequality
• Focus on groups defined by age and education
• Important to know how homogeneous such groups are in terms of proficiency and earnings
Within-group Dispersion
Skill Inequality Declines with Education
Wage Inequality Does Not
Skill Dispersion Increases with Age
As Does Wage Dispersion
• Unconditional Quantile Regression: Estimate the impact of changing the distribution of explanatory variable on the marginal quantiles of the outcome variable – wages, in our case
• If the estimated impact of a variable is larger at the top than at the bottom of the distribution, then an increase in that variable is associated with an increase in inequality
The Drivers of Wage Inequality
• We focus on the impact of years of education and numeracy
• At the same time, we control for basic socio-demographic characteristics
• This method also allow to decompose cross-country differences in wage inequality into “quantity” and “price” components
The Drivers of Wage Inequality
Basic Results
Cross-country Heterogeneity
Which Kind of Education?
Analysis at the Country Level
Analysis at the Country Level
Analysis at the Country Level
Analysis at the Country Level
Analysis at the Country Level
Analysis at the Country Level
Analysis at the Country Level
Analysis at the Country Level
Analysis at the Country Level
Analysis at the Country Level
Analysis at the Country Level
Analysis at the Country Level
Analysis at the Country Level
Analysis at the Country Level
• We take the United States as a reference country
• We ask how much of the higher level of inequality in the United States can be explained by differences in “quantities” (i.e. in the population distribution of certain characteristics) vs. “prices” (i.e. differences in the way such characteristics are rewarded in the labour market)
A Decomposition Exercise
• It is mostly an accounting exercise, which disregards “general equilibrium effects”
• It involves a number of arbitrary decisions (but results seem to be robust to those)
• As a consequence, should be taken with an appropriate degree of caution
A Decomposition Exercise
Country Raw Gap
90/10
Composition Effect Wage Structure Effect
Education Numeracy Total Education Numeracy Total
Australia 0.507 -0.022 -0.023 -0.074 0.459 0.060 0.581
Czech R. 0.624 0.035 0.024 0.068 -0.268 0.844 0.556
Denmark 0.701 0.009 -0.009 0.016 0.628 0.377 0.685
France 0.715 0.066 0.000 0.086 0.312 0.232 0.629
Germany 0.218 0.001 -0.018 0.019 0.662 0.191 0.199
Italy 0.441 0.114 -0.013 0.156 0.130 1.076 0.285
Japan 0.247 0.038 -0.030 0.010 -0.235 0.233 0.237
Korea -0.121 0.019 0.001 0.164 0.199 0.519 -0.286
Sweden 0.873 0.036 -0.024 0.020 0.382 0.241 0.852
Results – A Snapshot
• Composition effects seem to play a minor role– Proficiency has the “wrong” sign: most
countries are more proficient than the US
– Education has the “right” sign: most countries are less educated than the US
• Wage structure effects account for 30 to 90% of the observed gap
Results
• Can only speculate about relative importance of institutions vs. market forces
• In any case, policies can play a key role in shaping the evolution on inequality and its social impact
• Positive take-home message: investing in skills could raise earnings without causing increases in inequality
Tentative Conclusions / Interpretation
Country Gap 90th/10th
Composition Effect Wage Structure Effect Education Numeracy Total Education Numeracy Total
Australia 0.507 -0.022 -0.023 -0.074 0.459 0.060 0.581
Austria 0.536 0.046 -0.030 0.054 0.381 0.029 0.482Canada 0.275 0.007 -0.017 -0.022 0.427 0.065 0.297Czech R. 0.624 0.035 0.024 0.068 -0.268 0.844 0.556Denmark 0.701 0.009 -0.009 0.016 0.628 0.377 0.685
England/UK 0.392 0.028 -0.032 0.001 0.131 -0.162 0.391
Estonia 0.117 0.020 -0.013 0.009 0.543 0.276 0.109Finland 0.713 0.041 -0.011 0.061 0.051 0.386 0.652Belgium 0.684 0.028 0.010 0.111 0.321 0.585 0.572France 0.715 0.066 0.000 0.086 0.312 0.232 0.629Germany 0.218 0.001 -0.018 0.019 0.662 0.191 0.199
Ireland 0.381 -0.098 -0.004 -0.088 -0.058 0.168 0.469Italy 0.441 0.114 -0.013 0.156 0.130 1.076 0.285Japan 0.247 0.038 -0.030 0.010 -0.235 0.233 0.237Korea -0.121 0.019 0.001 0.164 0.199 0.519 -0.286Netherlands 0.475 0.004 -0.034 -0.027 0.602 0.143 0.502
Norway 0.743 -0.008 -0.023 -0.028 0.591 0.240 0.771Poland 0.285 0.019 -0.001 -0.065 0.027 0.435 0.350Slovak Rep. 0.263 0.011 -0.007 -0.004 -0.366 0.402 0.268
Spain 0.366 0.072 -0.002 0.084 0.116 0.620 0.282Sweden 0.873 0.036 -0.024 0.020 0.382 0.241 0.852
Results – 90/10 difference
Country Gap 90th/50th
Composition Effect Wage Structure Effect Education Numeracy Total Education Numeracy Total
Australia 0.269 -0.010 -0.012 -0.030 0.132 -0.375 0.299Austria 0.308 0.039 -0.006 0.068 -0.051 -0.254 0.239Canada 0.244 -0.005 0.005 -0.010 0.561 -0.036 0.254Czech R. 0.394 0.022 0.006 0.015 -0.389 -0.074 0.378Denmark 0.471 0.017 -0.002 0.018 0.010 -0.190 0.453England/UK 0.195 -0.002 -0.003 -0.002 0.323 -0.223 0.197
Estonia 0.094 -0.018 0.000 -0.024 0.482 -0.163 0.118Finland 0.378 0.022 0.004 0.041 -0.105 -0.130 0.337Belgium 0.390 0.019 0.012 0.073 -0.024 -0.046 0.317France 0.346 0.051 0.000 0.072 -0.076 -0.334 0.274Germany 0.276 0.001 0.003 0.040 0.123 -0.124 0.235Ireland 0.176 -0.017 -0.000 -0.003 0.135 -0.191 0.179Italy 0.240 0.063 -0.005 0.115 -0.080 0.047 0.124Japan 0.065 0.015 0.006 0.039 -0.117 -0.120 0.026Korea -0.080 0.000 0.008 0.116 0.259 0.152 -0.196Netherlands 0.323 0.005 0.023 0.036 0.045 0.059 0.287
Norway 0.428 -0.003 -0.003 -0.003 0.203 -0.194 0.432Poland 0.136 -0.002 0.002 -0.129 0.349 -0.074 0.264Slovak Rep. 0.145 0.006 -0.012 -0.028 -0.320 -0.292 0.173
Spain 0.187 0.011 -0.003 0.037 0.177 0.072 0.149Sweden 0.446 0.023 -0.018 0.007 0.027 -0.340 0.439
Results – 90/50 difference
Country Gap 50th/10th
Composition Effect Wage Structure EffectEducation Numeracy Total Education Numeracy Total
Australia 0.238 -0.011 -0.012 -0.044 0.328 0.435 0.282Austria 0.229 0.007 -0.024 -0.014 0.432 0.284 0.243Canada 0.030 0.012 -0.022 -0.013 -0.134 0.100 0.043Czech R. 0.231 0.012 0.018 0.053 0.120 0.918 0.177Denmark 0.230 -0.008 -0.007 -0.001 0.617 0.567 0.231England/UK 0.196 0.031 -0.029 0.003 - 0.192 0.061 0.194
Estonia 0.023 0.039 -0.013 0.033 0.061 0.439 -0.009Finland 0.335 0.020 -0.015 0.020 0.155 0.516 0.315Belgium 0.293 0.009 -0.001 0.038 0.346 0.631 0.255France 0.369 0.014 0.000 0.014 0.395 0.567 0.355Germany -0.057 -0.000 -0.021 -0.021 0.539 0.315 -0.036Ireland 0.205 -0.081 -0.004 -0.084 -0.193 0.359 0.289Italy 0.201 0.051 -0.009 0.041 0.209 1.029 0.161Japan 0.182 0.023 -0.035 -0.029 -0.119 0.353 0.211Korea -0.041 0.018 -0.007 0.048 -0.059 0.367 -0.089Netherlands 0.151 -0.001 -0.057 -0.063 0.557 0.084 0.214
Norway 0.315 -0.004 -0.020 -0.024 0.388 0.434 0.339Poland 0.149 0.021 -0.003 0.063 0.509 -0.542 0.086Slovak Rep. 0.118 0.005 0.005 0.023 -0.046 0.695 0.095
Spain 0.180 0.061 0.001 0.047 -0.061 0.549 0.133Sweden 0.427 0.013 -0.006 0.014 0.355 0.581 0.413
Results – 50/10 difference
SKILLS, SOCIAL INEQUALITY AND
ECONOMIC OUTPUT
• Dirk Van Damme
• EDU/IMEP
• How is the distribution of numeracy skills in the adult population related to overall social inequality as measured by the Gini coefficient?– And how are they related to economic
output as measured by GDP per capita
• And how are skills distributions in particular groups related to overall social inequality and economic output?
Questions
GiniGDP per capita
Mean score -.63 .11
Percentage of adults scoring at or below Level 2 .59 -.20
Percentage of adults scoring at Level 4 or 5 -.54 .36
Percentile difference 90th minus 10th percentile .35 .61
Percentile difference 75th minus 25th percentile .40 .59
Percentile difference 90th minus 50th percentile .47 .49
Percentile difference 50th minus 10th percentile .21 .65
Overview of country-level correlations of various numeracy distribution measures with Gini and GDP/capita
A higher mean numeracy score is positively related to higher social equality
245 250 255 260 265 270 275 280 285 2900.20
0.25
0.30
0.35
0.40
Australia
Austria
Canada
Czech RepublicDenmark
Estonia
Finland
GermanyIreland
ItalyJapan
Korea
Netherlands
Norway
Poland
Slovak Republic
Spain
Sweden
United States
Flanders (Belgium)
United KingdomR² = 0.388766537010996
Mean numeracy score
Gini coefficient
But a wide skills dispersion is not very strongly related to higher social inequality…
105 110 115 120 125 130 135 140 1450.20
0.25
0.30
0.35
0.40
Australia
Austria
Canada
Czech Rep Denmark
Estonia
Finland
GermanyIreland
ItalyJapan
Korea
Netherlands
Norway
Poland
Slovak Rep
Spain
Sweden
United States
Flanders
UK
R² = 0.119482758733097
Score point difference between percentile 90 and 10 on the numeracy scale
Gini
…while a wider skills dispersion relates positively with higher economic output
110 115 120 125 130 135 140 14515000
20000
25000
30000
35000
40000
45000
50000
AustraliaAustria Canada
Czech Rep
Denmark
Estonia
Finland
GermanyIreland
Italy
Japan
Korea
Netherlands
Norway
Poland
Slovak Rep
Spain
Sweden
United States
Flanders UK
R² = 0.366289883536397
Score point difference between percentile 90 and 10 on the numeracy scale
GDP per capita
A higher skills dispersion at the top of the distribution relates positively to higher social inequality…
50 52 54 56 58 60 62 64 66 680.20
0.25
0.30
0.35
0.40
Australia
Austria
Canada
Czech Rep Denmark
Estonia
Finland
GermanyIreland
ItalyJapan
Korea
Netherlands
Norway
Poland
Slovak Rep
Spain
Sweden
United States
Flanders
UK
R² = 0.225365468034165
Score point difference between percentile 90 and 50 on the numeracy scale
Gini
…as well as to higher economic output
50 52 54 56 58 60 62 64 66 6815000
20000
25000
30000
35000
40000
45000
50000
AustraliaAustria Canada
Czech Rep
Denmark
Estonia
Finland
GermanyIreland
Italy
Japan
Korea
Netherlands
Norway
Poland
Slovak Rep
Spain
Sweden
United States
Flanders UK
R² = 0.241261161380775
Score point difference between percentile 90 and 50 on the numeracy scale
GDP per capita
But the relationship between higher skills dispersion in the lower half and higher social inequality is much weaker…
58 63 68 73 780.20
0.25
0.30
0.35
0.40
Australia
Austria
Canada
Czech Rep Denmark
Estonia
Finland
GermanyIreland
ItalyJapan
Korea
Netherlands
Norway
Poland
Slovak Rep
Spain
Sweden
United States
Flanders
UK
R² = 0.0490393941452107
Score point difference between percentile 50 and 10 on the numeracy scale
Gini
…while there still is a strong relationship with economic output
58 63 68 73 7815000
20000
25000
30000
35000
40000
45000
50000
AustraliaAustria Canada
Czech Rep
Denmark
Estonia
Finland
GermanyIreland
Italy
Japan
Korea
Netherlands
Norway
Poland
Slovak Rep
Spain
Sweden
United States
Flanders UK
R² = 0.413273337293026
Score point difference between percentile 50 and 10 on the numeracy scale
GDP per capita
More low-skilled adults relates positively to higher social inequality…
35 40 45 50 55 60 65 70 750.20
0.25
0.30
0.35
0.40
Australia
Austria
Canada
Czech RepDenmark
Estonia
Finland
Germany Ireland
ItalyJapan
Korea
Netherlands
Norway
Poland
Slovak Rep
Spain
Sweden
United States
Flanders
UKR² = 0.347930052361252
Percentage adults scoring below Level 2 on the numeracy scale
Gini
…while more high-skilled adults relates negatively to social inequality
4 6 8 10 12 14 16 18 200.20
0.25
0.30
0.35
0.40
Australia
Austria
Canada
Czech Rep Denmark
Estonia
Finland
GermanyIreland
ItalyJapan
Korea
Netherlands
Norway
Poland
Slovak Rep
Spain
Sweden
United States
Flanders
UK
R² = 0.291572239929386
Percentage adults scoring Level 4 or 5 on the numeracy scale
Gini
GiniGDP per capita
Score-point difference 16-24 year-olds minus 55-64 year-olds
-.01 -.36
Score-point difference between adults with tertiary and lower than upper secondary education
.17 .43
Score-point difference 75th minus 25th percentile among adults with lower than upper secondary education
.19 .38
Score-point difference 75th minus 25th percentile among adults with upper secondary education
.30 .53
Score-point difference 75th minus 25th percentile among adults with tertiary-type A education
.36 .32
Score-point difference between adults with at least one parent who attained tertiary education and adults with neither parent who attained upper secondary education
.19 .25
Country-level correlations of various skills distribution measures among specific groups and Gini and GDP/capita
A higher skills distribution among mid-educated adults is positively related to economic output
50 52 54 56 58 60 62 64 66 6815000
20000
25000
30000
35000
40000
45000
50000
AustraliaAustria Canada
Czech Rep
Denmark
Estonia
Finland
GermanyIreland
Italy
Japan
Korea
Netherlands
Norway
Poland
Slovak Rep
Spain
Sweden
United States
Flanders UK
R² = 0.28104281737691
Score point difference between percentile 75 and 25 on the numeracy scale - upper secondary education attainment
GDP per capita
• A higher mean numeracy level, more high-skilled and less low-skilled are all related to less social inequality
• However, the width of the skills distribution don’t seem to matter a lot for social inequality
• But its shape matters: a wider dispersion in the upper half is related to higher social inequality
• A wider dispersion of skills seems also to be related to higher economic output
Tentative conclusions
• Improving skills of adults seems to be good for economic output, even when such policies widen the total skills distribution
• While this does not seem to harm social equality a lot, except when the better-skilled distance themselves from the median
• But leaving behind a large group of low-skilled adults is also bad for social equality
Tentative conclusions
Thank you !
[email protected]@oecd.org
www.oecd.org/edu/ceri www.oecd.org/site/piaac/ twitter @VanDammeEDU
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