Presentation on age and education in the Russian labour market equation by Rostislav Kapeliushnikov (June 2017)

1. Age and Education in the Russian
Labour Market Equation
V.Gimpelson and R.Kapeliushnikov
Stockholm, 13.06.2017

2. Main Idea
• Age and education of the workforce shape quality of labour
supply and, therefore, affect productivity and growth
• Our analysis is focused on supply-side constraints for the Russian
labour market in the long-run (up to 2030)
• Two main challenges: the first – demographic (aging, etc); the
second – educational (risk of overeducation)
• Well-known that in the previous decades the Russian economy
benefited from a massive demographic dividend:
– the working-age population and employment rose;
– the dependency ratio was on decline;
– the fraction of the most productive workers in young prime-ages (25-39)
was on rise.
• There was also a significant educational dividend: huge inflow of
university diploma holders into the labour market
• In the next 15 years Russia is likely to have a demographic
penalty (instead of dividend )
• In addition, the further educational upgrading is unlikely

3. Our approach
• We look at the previous period (2000-2015) and think
of the next 15 years (2016-2030) through the lenses
of age and education
• We discuss the recent evolution of employment and
speculate on where the future trends can bring us to
• What are associated challenges to the Russian human
capital in 15 years? Will it become an engine of
growth or an obsolete and costly artifact?
• We provide two main messages:
1. negative trends in labour supply are
predetermined and any policy interventions may
mitigate them only partially
2. their impact will be smaller than many
alarmists (including World bank) predict (aging of the
total population vs. aging of the employment)

4. Main issues
• We examine changes in the age structure as they have already
occurred and as they are predicted for the future. Two particular age
brackets are of special interest: these are youth and pensionable
ages. The past period was marked by labor force growth in general as
well as by significant growth of the young prime-age (25-34) cohort
that contributed to economic growth. In the future, the total
employment is likely to shrink and the younger fraction may contract
drastically
• We look at how distribution of labor force by educational attainment
has changed and how it is likely to evolve in the future. The past
period was marked by rapid expansion of the labor force with the
tertiary education. In the future, similar growth is hardly possible –
the demand for such education is close to full saturation.
• We deal with the joint or cross-effects of age and education for the
previous period as well for the future. Does divide between young
and educated vs elder and low skilled evolve or may evolve in the
near future? What could be economic and social implications?

5. Data
• The Russian LFS, 2000-2015
• The Rosstat Demographic Forecast, 2017-2030
• Censuses of Population, 1989 and 2002
• Microcensus of Population, 2015
• The October Wage Survey, 2005-2013 (OZPP)
• The Russian Longitudinal Monitoring Survey
(RLMS), 2000-2016

6. Demographic constraints …
• The total population: 2000-2015 – no change; 2015-2030 – decline
by 4 mln (low); or no change (medium); or increase by 6 mln (high)
• The employed population: 2000-2015 – gains by about 7 mln; 2015-
2030 – expected losses by 7 mln or by 10% (medium) and return to
2000
• Reserves of inactive population for larger employment are not
great or do not exist
• Unemployment: already very low – 5.5%
• e/p ratio 25-54: 86% vs. the OECD average 76%
• e/p ratio 15-24: 32% vs. 41% (high levels of educational enrollment)
• e/p ratio 55-64: 48% vs. 58% (but the same as in many more
wealthy European countries with higher retirement age - France,
Italy, Austria, Spain)
• Raising retirement age by 5 years (males – 65; females – 60). Three
scenarios: Δ e/p ratio=… 1) 5 pp; 2) 10 pp; 3) 15 pp (higher than the
OECD average!). In the most optimistic case – addition of 1.2 mln
workers (i.e. adding even 15 pp to e/p ratios in the age groups
affected by pension reform does not change much)

7. Population trends: three scenarios of
the Rosstat demographic forecast

8. We can forecast employment imposing e/p
ratios for 2015 on the future population
Medium forecast scenario that assumes net migrant annual inflow about 320 th

9. Comparing e/p ratios

10. Demographic challenges ahead…
• Fears of employment aging – the age distribution will shift
rightwards, huge employment gap at young ages
• changes in the number of young prime age (25-39) workers:
2000-2015 – gains by nearly 5 mln; 2015-2030 – losses by about
10 mln  negative effect on productivity and innovation
• However, in 2000-2015 a share of young workers (15-24) dropped
by 5 pp and that of old workers (50+) jumped by 8 pp!
• In fact, radical aging of the Russian workforce has already
occurred!
• By contrast, in 2015-2030 fractions of both young and old workers
will not change! (No risk of high unemployment for old!)
• All changes will take place in the middle of age distribution: the
trade-off between 25-39 (decline by 10 pp) and 40-49 (increase
by 10 pp) – the latter is a high productivity group also!
• The paradox of population aging without employment aging has a
simple explanation: in 2015-2030, large increase (by 4 pp) in the
fraction of very old persons (70+) in the total population - with
almost zero e/p ratio (1.5%)!

11. Employment change over age groups,
2000-2015

12. Employment change over age groups,
2015-2030

13. Educational challenges ahead…
• Prospective over-education emerges as a long-term challenge
• Since the mid of 1990-s – the educational boom: the number of
students enrolled in institutions of higher education increased by
2.6 times (doubling for males and tripling for females!)
• On the demand side - rising returns to the human capital, the
organizational change that demands higher education
• On the supply side - deregulation of the educational system
(increase in the number of institutions, emergence of the private
universities and colleges, expansion of the educational programs
on the fee basis, etc)
• The proportion of workers with tertiary education increased from
40% (in the late Soviet period) to 70% now (proportion of workers
with higher education – from 16% to more than 37%!)
• But: the low-educated workforce does not exist anymore
• In the cross-country context Russia emerges as an obvious outlier

14. Distribution of the Total and Employed Population by
Educational Attainment, 1989, 2002 and 2015, %
Highest level attained Total Population Employed Population
1989 2002 2015 1989 2002 2015
University complete 11.3 16.2 25.8 14.6 23.3 34.6
University incomplete 1.7 3.1 2.8 1.3 3.0 2.8
Technical colleges 19.2 27.5 31.1 24.3 35.7 34.7
Vocational schools 13.0 12.8 9.2 17.8 15.3 9.8
Upper secondary 17.9 17.7 17.9 20.8 16.2 14.3
Lower secondary 17.5 13.9 9.7 13.5 5.6 3.6
Primary and lower 19.4 8.8 3.5 7.8 1.0 0.2
Total 100 100 100 100 100 100

15. Percentage of population that has attained tertiary
education and GDP per capita, 2015
y = 9,9626x - 68,831
R2
= 0,3806
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
8,0 8,5 9,0 9,5 10,0 10,5 11,0 11,5 12,0
log GDP per capita, PPP, 2015 (constant 2010 international $)
Percentageofpopulationaged25-64thathasattainedtertiary
education,%,2015
Russia

16. Economic outcomes of educational boom
• Can (and how) the growing army of educated workers be
absorbed?
• When supply of educated labour exceeds demand, a few
reactions are possible:
– 1) jump in UN;
– 2) fall in relative wages;
– 3) downward occupational mobility
• For workers with higher education risk of UN is still small (no
sign of deterioration!)
• Returns to schooling peaked to 9% in the early 2000-s but
then lost 2.5 pp. The same for premiums for higher education:
decline from 77% to 55% (RLMS based estimates)
• Why?
– 1) increased competition among university and college graduates can
depress their relative wages;
– 2) expansion of the tertiary education can affect its quality negatively
(rising fraction of the part-time students as an example);
– 3) higher enrollment easies access to low ability students

17. Unemployment Rates by Gender and Educational
Attainment, 2015, %
Highest level attained Total Males Females Disc.
rate
University complete 3.4 3.4 3.4 0.2
Technical colleges 4.5 4.8 4.3 0.6
Vocational schools 5.8 5.7 6.0 0.8
Upper secondary 8.6 8.2 9.2 1.3
Lower secondary 13.4 13.7 12.9 3.3
Primary and lower 21.3 19.9 23.8 5.9
Total 5.6 5.8 5.3 0.7

18. Premiums to higher education, RLMS, 2000-2016, %
(the reference group - upper secondary education)
70,4 70,1
77,1 76,1
60,0
68,7
57,8 58,8
62,3 62,8 62,8
54,9
50,5
60,7
66,0
57,1
54,0
0
10
20
30
40
50
60
70
80
90
100
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
%
0
10
20
30
40
50
60
70
80
90
100
%
Males Females Total

19. Economic outcomes of educational boom
• The alternative (OZPP) source does not show this slide-down:
returns to schooling stay stable at 10% and premiums for higher
education remain at 75%
• Though both datasets have their own disadvantages the OZPP
estimates seem to be more reliable. But even lower (RLMS
based) estimates give high pay-off to higher education
• Was there the downward occupational mobility?
• In general, the occupational change went in the “correct”
direction – workers moved from lower skilled to better skilled
occupations
• Growth in demand for high-skilled workforce exceeded growth
in its supply
• In 2000-2015, the fraction of “overeducated” workers declined
by 10 pp and is now about 30% ( US, Canada, Spain)
• This is higher than in many developed countries but (for workers
with university diploma) is under the OECD average (20%)

20. Premiums to higher education, NOBUS (2003) and
OZPP (2005-2013), %
(the reference group - upper secondary education)
85,1
75,1
72,9
76,3 75,7
71,8
78,9
56,3 55,4
63,6 63,2
60,2
90,6
97,4
93,3 91,9 91,9
88,8
0
10
20
30
40
50
60
70
80
90
100
NOBUS-03 OZPP-05 OZPP-07 OZPP-09 OZPP-11 OZPP-13
%
Males Females Total

21. Occupational structure of employed population,
2000 and 2015, %
2000 2015
Managers 4.4 8.6
Professionals 15.6 20.4
Technicians 15.2 15.3
Clerks 3.4 2.9
Service workers 11.8 14.5
Skilled agricultural workers 6.3 3.4
Craft workers 16.3 13.1
Plant and machine operators 13.5 12.2
Elementary occupations 13.5 9.6
Total 100 100

22. Dynamics in Demand and Supply of High-Skilled Workforce,
2000–2015, % (2000 = 100%)
Increases: Managers = +120%; Professionals = +46%;
Associate professionals = +12%; VUZ = +65%; SSUZ = +10%
0
20
40
60
80
100
120
140
160
180
200
220
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
%
0
20
40
60
80
100
120
140
160
180
200
220
%
Managers Professionals
Technicians Labor force with higher education
Labor force with technical college diploma

23. Proportion of Workers with Tertiary Education Employed in
High-Skilled Jobs (ISCO 1-3), Russia and OECD, %
25-34 35-44 45-54 55-64 25-64 Change, pp
Russia-1
2015 71.0 72.2 70.1 66.9 70.6 25/64: +12.5
2000 54.8 56.4 61.9 64.2 58.1 25/34: +16.2
Russia-2
2015 82.4 86.8 87.7 84.9 85.2 25/64: +0.1
2000 83.5 84.4 87.3 85.0 85.1 25/34: -0.9
OECD
2006 79 82 85 86 82 25/64: -2
1998 80 85 87 88 84 25/34: -1

24. Educational challenges ahead…
• Our forecast of prospective educational composition assumes
that all students graduate before 30
• Two scenarios:
– 1) further educational upgrading has already stopped so that incoming
cohorts have the proportion of university graduates as the group 25-29 in
2015;
– 2) incoming cohorts will have this proportion higher by 5 pp
• The total number of workers with higher education increases
from current 27 mln to 29.5 mln by 2030 (1st sc) and to 31 mln
(2nd sc)
• The proportion of workers with higher education would grow
from current 37.4% to 43.6-45.4% by 2030
• Growth is likely to be uneven: losses by 2.5 mln in 25-39 and
gains by 4 mln in 40-49 (likely changes in relative wages to the
benefit of those who are younger)
• Higher risk of underutilization of the human capital and falling
returns to education (avoided so far) are highly likely

25. Number of Workers with Higher Education (Complete
and Incomplete) by 5-year Age Groups, 2000, 2015 and
2030, Actual and Prospective Estimates, million
0
1
2
3
4
5
6
15-19 20 – 24 25 – 29 30 – 34 35 – 39 40 – 44 45 – 49 50 – 54 55 – 59 60 – 64 65 – 72
millionpersons
2000 2015 2030 (basic) 2030 (upgrading)

26. Main conclusions
• Big challenge: shrinking employment – loosing up to
10%
• Rising dependency ratio and labour costs
• Paradox of aging population without aging employment
• But since the age distribution shifts rightwards, huge
employment gap at the productive ages
• However, without negative impact on productivity?
• Undersupply of low-skilled and oversupply of high-
skilled labour
• Diploma decease (social and political tensions)
• Serious threat to economic growth
• There is no clear understanding what to do with it
• No simple fix (pension reform is not a panacea!)
• Politicians prefer to ignore the problem

27. Potential solutions
• Addressing the issue of early exit from the labour force:
- Pension reform including rise in retirement age
- Retraining of older workers
- Removing discriminatory attitudes toward older workers
- More flexible employment for older workers
- Heath issues
• Filling the gap in younger labour force:
- Migration
- Economic restructuring and reallocation of younger
workers to more efficient use
- More flexible employment for youth
• Keeping human capital up-to-date:
- Education and training over the life course
- Investments in quality of education
- Making the educational system more adaptive to
occupational changes in labour demand
• Maintaining demand for human capital:
- Friendly institutions for job creation
- Focus on human capital intensive sectors
- Keeping labour market flexible

28. The mission is almost impossible:
- we do not know how to solve
these issues
- incentives for reforms have been
absent so far