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Skills for the 21st Century in LCR
May, 2011
B A N K T E A M : C R I S T I A N A E D O, I A N WA L K E R , PA B LO A C O S TA , A N A M A R I A OV I E D O, J AV I E R LU Q U E
C O N S U LTA N T S : T I M G I N D L I N G , G U I L L E R M O C R U C E S , L E O N A R D O G A S P I R I N I , G R E G V E R A M E N D I , N A N C Y
G U E R R A , K E N D O D G E , J O H N M I D D L E T O N
Outline
Context / motivation: LCR’s declining education earnings premia: is the education system to blame? Does it matter? What should we do about it?
Findings: Falling earnings premia Supply , demand and institutional factors underlying
the trend Should we worry?
Evidence on learning achievement and quality Evidence on the skill content of work and skill shortages.
Policy take-aways Reasons to be cheerful; Reasons for concern.
Future work
2
1. What has happened on education earnings premia?
3
Education earnings premia have declined…….
4
Evolution of education earnings premiums in LCR Coefficients on years of education variable from the Mincer-style monthly earnings regressions, full-time private
sector employees, basic OLS regressions
0.00
0.02
0.04
0.06
0.08
0.10
0.12
0.14
0.16
1990 1992 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Nicaragua El Salvador Peru Chile
…continuously for secondary; unevenly for tertiary (kink around 2003) ….
5
6
- Estimated earnings premiums by country, around 2008 Full-time private sector paid employees (asalariados), dependent variable is real monthly earnings.
i. OLS (not including parent's education as an explanatory variable)
Education Level Chile (2006)
Brazil (2008)
Costa Rica (2008)
Nicaragua (2005)
El Salvador (2008)
Colombia (2008)
Mexico (2008)
Peru (2008)
Uruguay (2008)
Years of Education 0.12 0.10 0.09 0.10 0.08 0.12 0.12 0.11 0.10 Vs. primary inc.
Primary comp. 0.11 0.26 0.12 0.29 0.11 0.21 0.19 0.15 0.20 Vs. primary comp.
Secondary tech. comp. 0.39 na 0.43 0.42 na na 0.69 na 0.40 Secondary ac. comp. 0.32 0.25 0.32 0.37 0.38 0.42 0.62 0.26 0.45 Vs. Secondary ac. Comp.
Non-univ. tertiary 0.44 na 0.25 0.31 0.42 0.43 0.30 0.37 0.53 University comp. 1.12 0.92 0.71 0.77 0.99 1.21 0.79 0.94 1.07
ii. OLS (including parent's education as an explanatory variable, data only for children living with parents)
Education Level Chile (2006)
Brazil (2008)
Costa Rica (2008)
Nicaragua (2005)
El Salvador (2008)
Colombia (2008)
Mexico (2008)
Peru (2008)
Uruguay (2008)
Years of Education 0.10 0.09 0.08 0.10 0.08 0.11 0.12 0.10 0.07 Vs. primary inc.
Primary comp. 0.07 0.21 0.07 0.30 0.14 0.16 0.21 0.16 0.18 Vs. primary comp.
Secondary tech. comp. 0.26 na 0.37 0.50 na na 0.63 na 0.26 Secondary ac. comp. 0.22 0.22 0.26 0.40 0.33 0.54 0.55 0.29 0.28 Vs. Secondary ac. comp.
Non-univ. tertiary 0.31 na 0.36 0.31 0.51 0.34 0.52 0.27 0.32 University comp. 0.93 0.71 0.66 0.72 0.78 0.97 0.77 0.78 0.73
Note: Regressions also control for potential experience, gender and region.
… but remain high, even when controlling for parents’ education
2. Understanding the trends: supply and demand factors
7
Educational expansion is transforming emerging cohort in LCR (25-35 non students)
8
23 20 16
15 1514
2721
18
2125
28
14 19 23
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1997 2003 2008
Colombia
14 16 17 16 16 15 16 15 15 15 14 13
36 37 37 35 36 35 34 34 33 30 32 31
21 20 19 21 20 19 20 21 21 22 21 21
15 14 13 14 13 14 14 13 13 14 15 15
13 12 13 14 15 16 16 17 17 19 18 20
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Costa Rica
Tertiary
Secondary comp.
Secondary inc.
Primary comp.
Primary inc.
38 37 34 32 33
11 11 10 9 9
23 23 24 25 24
16 18 20 21 22
11 12 12 13 12
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1998 2001 2003 2006 2008
El Salvador
28 25 22 18 16 15 14 14 14 14
24 2320
20 20 19 17 16 18 16
2323
27 31 33 33 39 37 37 37
13 15 17 16 16 17 14 15 15 15
13 13 14 13 13 15 16 17 17 18
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1992 1994 1996 1998 2000 2002 2004 2005 2006 2008
Mexico
Tertiary
Secondary comp.
Secondary inc.
Primary comp.
Primary inc.
60 57 57 56 54 53 50 48 46 44 41 38 36
11 12 11 12 12 11 11 11 11 10 10 11 11
5 5 5 5 5 5 5 5 5 5 6 5 6
17 18 19 19 21 23 25 26 28 30 32 33 34
8 8 8 8 8 9 9 10 10 11 12 13 14
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1995 1996 1997 1998 1999 2001 2002 2003 2004 2005 2006 2007 2008
Brazil
23 21 20 16 15 12 10
12 12 1110 11
10 9
20 21 2017 16
1514
27 30 3334 36
37 40
18 15 16 22 22 26 27
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1990 1992 1994 1998 2000 2003 2006
ChileTertiary
Secondary comp.
Secondary incomp.
Primary comp.
Primary inc.
Mean years of education
9
But other regions are doing better
10
0%
20%
40%
60%
80%
100%19
50
1955
1960
1965
1970
1975
1980
1985
1990
1995
2000
2005
2010
Latin America and the Caribbean
No educ Primary Secondary Tertiary
0%
20%
40%
60%
80%
100%
1950
1955
1960
1965
1970
1975
1980
1985
1990
1995
2000
2005
2010
Eastern Europe and Central Asia
No educ Primary Secondary Tertiary
0%
20%
40%
60%
80%
100%
1950
1955
1960
1965
1970
1975
1980
1985
1990
1995
2000
2005
2010
Asian Tigers
No educ Primary Secondary Tertiary
0%
20%
40%
60%
80%
100%
1950
1955
1960
1965
1970
1975
1980
1985
1990
1995
2000
2005
2010
Advanced economies
No educ Primary Secondary Tertiary
… and we are still miles behind
11
67
89
10
11
Ave
rag
e ye
ars
of s
cho
olin
g fo
r 1
5+ p
opul
atio
n
1990 2010Year
Latin America and the Caribbean Advanced economies
East Asian Tigers Eastern Europe and Central Asia
Educational attainment 1990-2010
Demand shifters seem to be the main drivers of falling wage premia (Katz-Murphy aproach)
12
Changes in the Wage Premium and the Supply and Demand for Skilled (Tertiary Educated) vs. Unskilled (Other Educational Groups) Workers
Source: Own calculations based on microdata from household surveys. Details on sample years, survey and
methodology are available in Acosta, Cruces, Gasparini (2011).
σsu=2 σsu=31990s 2000s 1990s 2000s 1990s 2000s 1990s 2000s
Argentina 3.5 -2.4 4.6 2.4 11.5 -2.3 15.0 -4.7Bolivia 7.9 -4.6 -0.2 5.1 15.6 -4.1 23.5 -8.7Brazil -0.4 -3.2 1.6 4.4 0.8 -1.9 0.4 -5.1Chile 0.5 -1.9 3.1 1.1 4.1 -2.7 4.6 -4.7Colombia 2.5 -2.0 6.4 6.0 11.5 2.1 14.0 0.1Costa Rica 0.4 -0.2 4.0 3.4 4.9 3.0 5.3 2.8Ecuador -3.2 3.4 -3.0 -6.3El Salvador 1.7 -0.1 5.5 -0.3 8.9 -0.4 10.6 -0.5Honduras 0.0 -1.9 2.6 2.3 2.6 -1.4 2.6 -3.3Mexico 1.8 -2.8 3.6 2.2 7.2 -3.5 9.0 -6.3Nicaragua 3.5 -6.9 4.6 6.6 11.6 -7.2 15.0 -14.1Panama 0.3 -2.3 2.3 2.4 2.9 -2.2 3.1 -4.4Paraguay 0.8 -5.6 5.3 6.1 6.9 -5.2 7.6 -10.8Peru 0.6 -2.8 0.2 3.8 1.3 -1.8 1.9 -4.6Uruguay 2.2 -1.3 2.9 -0.8 7.3 -3.5 9.6 -4.8Venezuela 1.1 -4.8 3.9 4.2 6.2 -5.4 7.3 -10.3Mean 1.8 -2.9 3.4 3.3 6.9 -2.5 8.6 -5.4
Relative demand Relative demandRelative supplyWage premium
in Cono Sur…
13
Argentina Brazil
Paraguay Uruguay
-0.20
-0.15
-0.10
-0.05
0.00
0.05
0.10
0.15
0.20
0.25
-0.20
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.40
1.6019
86
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
Wag
e Pre
miu
m In
dex
Dem
and
and
Supp
ly In
dexe
s
Relative supply Relative demand Wage premium
-0.20-0.15-0.10-0.050.000.050.100.150.200.250.30
-0.20
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1981
1983
1985
1987
1989
1991
1993
1995
1997
1999
2001
2003
2005
2007
2009
Wag
e Pre
miu
m In
dex
Dem
and
and
Supp
ly In
dexe
s
Relative supply Relative demand Wage premium
-0.30
-0.25
-0.20
-0.15
-0.10
-0.05
0.00
0.05
0.10
0.15
-0.40
-0.20
0.00
0.20
0.40
0.60
0.80
1.00
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
Wag
e Pre
miu
m In
dex
Dem
and
and
Supp
ly In
dexe
s
Relative supply Relative demand Wage premium
0.000.050.100.150.200.250.300.350.400.45
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.40
1.60
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
Wag
e Pre
miu
m In
dex
Dem
and
and
Supp
ly In
dexe
s
Relative supply Relative demand Wage premium
The Andes…
14
Bolivia Chile
Peru Venezuela
-0.10
-0.05
0.00
0.05
0.10
0.15
0.20
0.25
0.30
-0.20-0.100.000.100.200.300.400.500.600.700.80
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
Wag
e Pr
emiu
m In
dex
Dem
and
and
Supp
ly In
dexe
s
Relative supply Relative demand Wage premium
-0.15
-0.10
-0.05
0.00
0.05
0.10
0.000.050.100.150.200.250.300.350.400.450.50
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
Wag
e Pr
emiu
m In
dex
Dem
and
and
Supp
ly In
dexe
s
Relative supply Relative demand Wage premium
-0.15
-0.10
-0.05
0.00
0.05
0.10
0.15
-0.10
0.00
0.10
0.20
0.30
0.40
0.50
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
Wag
e Pr
emiu
m In
dex
Dem
and
and
Supp
ly In
dexe
s
Relative supply Relative demand Wage premium
-0.30
-0.25
-0.20
-0.15
-0.10
-0.05
0.00
0.05
0.10
-0.60
-0.40
-0.20
0.00
0.20
0.40
0.60
0.80
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Wag
e Pr
emiu
m In
dex
Dem
and
and
Supp
ly In
dexe
s
Relative supply Relative demand Wage premium
…and Central America
15
Costa Rica Honduras
Mexico Panama
-0.05
0.00
0.05
0.10
0.15
0.20
-0.20
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.40
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
Wag
e Pr
emiu
m In
dex
Dem
and
and
Supp
ly In
dexe
s
Relative supply Relative demand Wage premium
-0.25
-0.20
-0.15
-0.10
-0.05
0.00
0.05
-0.60
-0.40
-0.20
0.00
0.20
0.40
0.60
0.80
1991
1993
1995
1997
1999
2001
2003
2005
2007
2009
Wag
e Pr
emiu
m In
dex
Dem
and
and
Supp
ly In
dexe
s
Relative supply Relative demand Wage premium
-0.05
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.40
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
Wag
e Pr
emiu
m In
dex
Dem
and
and
Supp
ly In
dexe
s
Relative supply Relative demand Wage premium
-0.30
-0.25
-0.20
-0.15
-0.10
-0.05
0.00
0.05
0.10
-0.20
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
Wag
e Pr
emiu
m In
dex
Dem
and
and
Supp
ly In
dexe
s
Relative supply Relative demand Wage premium
In both decades changes in skills demand reflect mainly “within” sector effects
16
Source: Own calculations based on household surveys. Details on sample years, survey and methodology are available in Acosta, Cruces, Gasparini (2011).
Minimum wages likely played a role in compressing secondary skill premia
17
Evolution of Real Minimum Wages, 1995-2007
Source: Oficina Internacional de Trabajo (ILO), Santiago office, "Evolucion de los salarios en America Latina," mimeo, Santiago, October 2008
0
50
100
150
200
250
300
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Argentina
Brazil
Chile
Colombia
Costa Rica
El Salvador
Mexico
Peru
Uruguay
…when the MW (blue line) trends up, secondary premium (red line) trends down
18
Comparing the real minimum wage index with secondary and university earnings premia
0.00
0.50
1.00
1.50
2.00Brazil
University Secondary Real MW
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.40
1990 1992 1994 1996 1998 2000 2003 2006
Chile
University Secondary Real MW
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.40
1997 2003 2008
Colombia
University Secondary Real MW
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.40
1998 2000 2002 2004 2006 2008
Costa Rica
University Secondary Real MW
3. Should we worry?
19
Secondary expansion has not eroded learning attainment
20
- PISA results Math Read 2000 2009 2000 2009 Argentina 387 389
412 399
Brazil 334 386
391 412 Chile 383 421
409 450
Mexico 390 418
422 425 Peru 293 365
323 370
2003 2009
2003 2009
Uruguay 422 427
435 426
2006 2009
2006 2009
Colombia 370 381 385 413 Source: OECD
Better grade-age correspondence is an important trend …..
21
Average Grade Attainment in PISA 2000 2009 Argentina 9.6 9.4 Brazil 8.5 9.1 Chile 9.5 9.7 Mexico 9.4 9.5 Peru 9.3 9.8
2003 2009
Uruguay 9.5 9.4
2006 2009
Colombia 9.6 9.7 Source: Authors´ elaboration based on OECD.
…linked to improved equality of educational opportunity in many countries
22
… and contributing to improved PISA scores, apart from Argentina and Uruguay.
23
Importance of Grade Attainment on PISA Mathematics scores
Country BASE YEAR (BY) YEAR 2009 ADJUSTMENT % EXPLAINED BY
(STR_BY*SCORE_BY) (STR_09*SCORE_09) (STR_09*SCORE_BY)GRADE
STRUCTUREA B C (C-A)/(B-A)
Base year 2000Argentina 387 388 366 -2,100%Brazil 334 386 355 41%Chile 383 421 398 40%Mexico 390 418 392 7%Peru 293 365 312 26%Base year 2003Uruguay 423 427 415 -200%Base year 2006Colombia 370 381 373 27%
STR: Estimated structure
Tertiary quality also appears stable, based on analysis of earnings variance
24
Comparing the coefficient of variation of real monthly earnings to earnings premiums for workers with university education
0.000.200.400.600.801.001.201.401.601.802.00
1995 1996 1997 1998 1999 2001 2002 2003 2004 2005 2006 2007 2008
Brazil
Earnings Premiums for University Complete Education (Basic regressions, full-time paid employees)
Coefficient of Variation (for the earnings of those with a university complete education)
0.00
0.50
1.00
1.50
2.00
2.50
3.00
1990 1992 1994 1996 1998 2000 2003 2006
Chile
Earnings Premiums for University Complete Education (Basic regressions, full-time paid employees)Coefficient of Variation (for the earnings of those with a university complete education)
0.00
0.50
1.00
1.50
2.00
2.50
1997 2003 2008
Colombia
Earnings Premiums for University Complete Education (Basic regressions, full-time paid employees)
Coefficient of Variation (for the earnings of those with a university complete education)
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Costa Rica
Earnings Premiums for University Complete Education (Basic regressions, full-time paid employees)
Coefficient of Variation (for the earnings of those with a university complete education)
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.40
1.60
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
El Salvador
Earnings Premiums for University Complete Education (Basic regressions, full-time paid employees)
Coefficient of Variation (for the earnings of those with a university complete education)
0.00
0.50
1.00
1.50
2.00
2.50
1992 1994 1996 1998 2000 2002 2004 2005 2006 2008
Mexico
Earnings Premiums for University Complete Education (Basic regressions, full-time paid employees)
Coefficient of Variation (for the earnings of those with a university complete education)
But there ARE reasons to worry
East Asian trends look very different The quality gap for LAC in PISA scores
remains large LAC’s pattern of occupational expansion is
not at the cutting edge Signs of skill shortage and mismatch
25
Asian tigers: a contrasting pattern of increasing attainment AND premia
26
Based on PISA, LCR’s secondary quality gap remains big, versus OECD
27
Comparison of LAC countries and OECD in PISA*
* LAC line represents the average performance of Argentina, Brazil, Chile, Mexico, and Peru in PISA. Source: Own elaboration based on OECD.
MATH READING
300
350
400
450
500
550
2000 2003 2006 2009
OECD (Non LAC) LAC
300
350
400
450
500
550
2000 2003 2006 2009
OECD (Non LAC) LAC
and LCR under-performs, relative to income level
28
ARGBRA
CHL
COL
MEX
PANPER
TTOURY
200
300
400
500
600
MA
TH S
CO
RE
-2 0 2 4 6LOG GDP PER CAPITA
2009 PISA MATH SCORE AND GDP PER CAPITA
ARG
BRA
CHL
COL
MEX
PANPER
TTOURY
300
350
400
450
500
550
MAT
H S
CO
RE
-2 0 2 4 6LOG GDP PER CAPITA
2009 PISA READING SCORE AND GDP PER CAPITA
LACLAC
LCR skill quotients are inferior to USA, for high end “new economy” skills (Autor- Levy-Murnane approach)
29
Distribution of skills in the labor force1
USA Brazil Costa Rica Mexico Nicaragua
El Salvador
Non routine Cognitive Analytical 3.04 2.81 2.80 2.76 2.66 2.65 Non Routine Cognitive Interpersonal 3.10 2.95 2.95 2.95 2.90 2.86 Routine Cognitive 3.13 3.05 3.03 2.94 2.93 2.99 Routine Manual 2.47 2.63 2.72 2.63 2.76 2.70 Non Routine Manual Physical. 2.31 2.55 2.58 2.60 2.70 2.62 1/ Scale 1 to 5. A score of 5 denotes high importance of skill.
Suggesting possibility that LCR skill use evolution reflects supply constraints….
30
Dynamic trends in skill distribution in Brazil, Costa Rica and Nicaragua compared with the USA
NRCA: Non Routine Cognitive Analytical, NRCI: Non Routine Cognitive Interpersonal, RC: Routine Manual, NRMP: Non Routine Manual Physical
303540455055606570
1980 2008
USA
NRCA NRCI RC RM NRMP
303540455055606570
1981 2009
BRAZIL
NRCA NRCI RC RM NRMP
303540455055606570
2001 2009
COSTA RICA
NRCA NRCI RC RM NRMP
303540455055606570
2001 2009
NICARAGUA
NRCA NRCI RC RM NRMP
Home country education quality correlates to immigrant graduate skill uses in US market
31
- Correlation of education quality in migrants’ country of origin and skill content of work done in the USA
Mexico
Costa Rica
El Salvador
Guatemala
Nicaragua
Panama Cuba
Dominican Republic
Argentina
Brazil
Chile
Colombia
Ecuador
Paraguay
Peru
Uruguay
2.8
2.9
33
.13
.23
.3A
nal
ytic
al s
kills
- s
cale
1 to
5
400 450 500 550 600 650SERCE SCORE
Includes only individuals with tertiary edu.
CONTENT OF LABOR FORCE BY COUNTRY OF ORIGINCOGNITIVTE SKILLS AND ANALYTICAL SKILL
Mexico
Costa Rica
El Salvador
Guatemala
Nicaragua
Panama
Cuba
Dominican Republic
Argentina
Brazil
Chile
Colombia
Ecuador
Paraguay
Peru
Uruguay
33
.05
3.1
3.1
53
.23
.25
Inte
rper
sona
l ski
lls -
sca
le 1
to 5
400 450 500 550 600 650SERCE SCORE
Includes only individuals with tertiary edu.
CONTENT OF LABOR FORCE BY COUNTRY OF ORIGINCOGNITIVTE SKILLS AND INTERPERSONAL SKILL
Enterprise survey evidence on time to fill skilled vacancies in LCR reinforces this message…
32
Average time to fill vacancy by regions of the world
… as does the evidence on time taken by innovative firms: a constrained sector?
33
Average weeks to fill vacancy by firm’s innovation status
3. Conclusions
34
Reasons to be cheerful LCR’s large education expansion hasn’t eroded
quality Downturns in skill premia likely reflect easing of
(relative) shortages (winning Tinbergen’s race) rather than erosion of quality (Katz-Murphy analysis)
Improved outcomes for children from poor backgrounds in some countries (EOI)
Reduced skill premia help reduce Ginis and poverty Institutional factors such as minimum wages have
helped, in most places Skill premia still high enough to stimulate demand
for secondary and tertiary education
35
Reasons to worry Big quality gap may be constraining path of
development East Asia still has rising premia in spite of higher
and faster growth of attainment: not the same thing?
LCR lags OECD by the equivalent of 2 years schooling @ age 15 (PISA).
Quality improving only slightly and due to better grade-age matches, not intra grade efficiency.
Shortage of New Economy skills may constrain growth at cutting edge: a second class continent?
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Future work Improving our understanding of skill – labor
market linkages Getting data with direct observations of skills,
beyond the “Big Five”. High end (New economy skills) Low end (social literacy skills)…. New skills surveys in FY 12 in Bolivia, Colombia, El
Salvador (MDTF, BNPP) Improving regulatory information in TVET
Benchmarking methodology designed Piloting underway in Argentina Rollout next year
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Thank you
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