DCO-ZXE089-20040200-jgfPP1 Czech Republic: key policy issues in schooling, training, and human capital development. Presenting at “Growth strategies –

DCO-ZXE089-20040200-jgfPP1

Czech Republic: key policy issues in schooling, training, and human capital development.

Presenting at “Growth strategies – Czech ambition and OECD experience OECD”, January 11, 2006

Daniel Münich, CERGE-EI, Prague ([email protected])


2

INITIAL NOTES

• This presentation

– focuses on qualitative, rather than on quantitative information,

– is stressing weak points, shortcomings, agenda for reform,

– presents personal academic opinions which are not necessarily fully in line with the governmental Strategy.


3

FAST DEMOGRAPHIC DECLINE (ongoing)

Age cohort sizes (Czech Republic in year 2005)

0

50,000

100,000

150,000

200,000

250,000

54 51 48 45 42 39 36 33 30 27 24 21 18 15 12 9 6

Age in year 2005

Co

ho

rt s

ize

Notes:

- Demographic decline is not spread equally across regions, districts, towns causing demand/supply discrepancies.

- Role of centralized funding scheme.

- Need for cross-border enrolments.


4


5

PRIMARY and SECONDARY SCHOOLING SYSTEM (simplified version)

13

12

11 GYMNASIUM SECONDARY TECHNICAL SECONDARY VOCATIONAL

10 SCHOOL SCHOOL

9 8 6 4 4 3 2 4 3

9

8 6 2nd stage

7

6 8

5

4

3

2 1st stage

1

BASIC SCHOOL


6

PRIMARY & LOWER SECONDARY SCHOOLING

• Governance– lack of comparable information about entrants and graduates limits

school accountability and effective interventions,

– limited school choice at the 1st grade (residential),

– quality is in question at the lower-secondary level,

– increasing but still low & egalitarian remuneration of teachers (high seniority, dominance of women, frequently after retirement).

• Curriculum – too focused on memorizing (lower-secondary level),

– new schooling act made grounds for more liberal curriculum,

– achievements in foreign languages remain weak; course-load to be increased but effectiveness is in question.


7

PRIMARY & LOWER SECONDARY SCHOOLING (continued)

• Selectivity – after 5th grade: escape option in poor schools, wrong incentives,

early selection,

– after 9th grade: 3-tracks.

• Special schools– “special schools” enrolling mainly Roma children abolished,

– new “community schools” have better resources but high concentration is still a problem,

– good experience with special personal/class assistants.


8

UPPER-SECONDARY SCHOOLING

• Three-tracks system

– extraordinary high upper-secondary school attainment,

– extraordinary low share of general programs, high share of vocational programs,

– historically determined regional imbalances,

– structure of schools partly corresponds to industrial structure, but…


9

DIFFERENTIALS BETWEEN UPPER-SECONDARY SCHOOL TYPES

Vocational Technical Gymnazia

Costs/pupil high medium, Low

Excess demand no medium high

Entry test scores low medium high

Exit test scores Low medium high

Labour market wage Low medium High

Unemployment rate high medium Low

College admission probability zero low High

Partic. in life-long learning minimal low Higher

Note: Obvious structural imbalances and inefficiencies.


10

UPPER-SECONDARY SCHOOLING (continued)

• Governance– information on achievements and value added is limited, no

regular nation-wide testing (under preparation) no comparison: cross-sectional, trends, international,

– admission mechanism overregulated leading to biased signals,

– transfer of large agenda to regional governments: pros & cons.

• Skills achievements– last information about graduates from 1999, no information at all

about vocational programs graduates (majority!, unemployment),

– international comparison of 15 years old pupils only (PISA 2003),

– limited access of boys to upper-secondary education due to structural imbalances,


11

TERTIARY SCHOOLING

• Access to education– ~33% of age cohort admitted, persistent surplus demand,– back-log of unsuccessful applicants,– relying on demographic decline (in the past and future),– high repetition, drop-out, and transition rates among students,– until 2006, almost no support to students with weak econ.

background,– Limited access of youth with weaker social background,– no support provided to private college students.

• Financing and governance– under-funded,– pure reliance/dependence on public funding,– structural imbalances (across fields/schools), and BA/MA levels– red line formula in financing,– schools autonomous in curriculum, financially overregulated,– “labour managed” schools (top school management is elected by

academics, staff and students).


12

TERTIARY SCHOOLING (continued)

• Lack of transparency– little information about quality of education (graduates); high

returns to college education is misleading indicator,

– quality is in question,

– relatively large mismatch between occupations and fields,

– confusion between quality and educational level,

– weak competitive pressures on schools (excess demand & public funding).


13

LIFE-LONG LEARNING

• On-the-job training– Participation remains low in international comparison,

– corresponding to the stage of economic development (?),

– participation increases with formal educational attainment,

– limited spatial access to college education when older.

• Lack of general skills– Lack of foreign language, IT, and team-work skills.

• Retraining (ALMP)– Small scale, dominance of short-term programs, no program

evaluation,

– high incidence of unemployment among vocational program graduates.


14

Slides which follow will not be presented and are made available for readers interested in empirical details.


15

STYLIZED FACTS

• Extraordinary high proportion of age cohorts attains at least upper-secondary education,

• 15 years old Czechs score slightly above average in PISA 2003,

• the system is viewed as highly selective (high variance in PISA scores),

• public schools dominate (~95%), private schools entered in early 1990s,

• small proportion of secondary-school graduates continues at a college (college supply gap),

• 3-tracks upper-secondary system : Gymnasia, Technical, Vocational schools.

• tracks differ in curriculum (well documented) and quality/demand (poorly documented),

• test scores at graduation differ across school types.


16

DIFFERENTIALS BETWEEN SCHOOLING TYPES

Note: great deal of test score difference between gymnazia and technical school graduates is due to school type and not due to selection and initial conditions.

Table 7: Aggregate Components of the Raw SAT Score Gap Between Vocational and Grammar Schools Students

Gap

Component Absolute% of the raw

gap% of avg. score in vocational schools

Raw gap 14.0 100.0 34.6Selection 2.5 18.0 6.2Endowment 4.6 33.1 11.4Intercepts 6.4 45.7 15.8Coefficients w/o intercepts -1.6 -11.3 -3.9Interaction 2.0 14.6 5.0


17

Distribution of admission probability [x-axis: admitted/applicants in %] (by school types)

Note: Dominance of vocational schools has declined slowly. Share of gymnasia grew slowly and remains low.

Pravdepodobnost [%]

GYM SOS SOU

0 50 100

0

.01

.02

.03

.04

Admission probability [%]

TechnicalGymnaziaVocational


18

Sha

re o

f pup

ils in

G

Share of pop. with higher edu0 .05 .1 .15

0

.05

.1

.15

.2

.3

.4

.5

Plots proportional to share of students in nonstate G

Sha

re o

f pup

ils in

G

Share of pop. with higher edu0 .05 .1 .15

0

.05

.1

.15

.2

.3

.4

.5

Plots proportional to share of students in nonstate GW/o Prague & Brno

Sha

re o

f pup

ils in

G

Share of pop. with higher edu0 .05 .1

0

.05

.1

.15

.2

SUPPLY GAP IN EARLY ’90s BEING FILLED BY NON-STATE SCHOOLS

X-axis: share of population with tertiary education

Y-axis: share of age cohort enrolled by public gymnasia

Lines: proportional relationships.

Circles: proportional to district size.


19

COMPARING PUPILS IN STATE AND PRIVATE SCHOOLS

____________________________________________________________ Education Education Grade PC mother father

____________________________________________________________Gymnasia Public 3.08 3.14 1.35 0.53 Private 3.20 3.32 1.47 0.63 ____________________________________________________________Technical schools Public 2.59 2.65 1.50 0.40 Private 2.65 2.71 1.58 0.45

Education: 2 ~ vocational, 3 ~ upper-secondary GCE, 4 ~ tertiaryGrade: at the admission, 1~best, 2~worstPC: proportion of pupils with PC at home

Comment: Compared to public gymnasia and technical schools pupils, private schools pupils have in average lower study aptitude and more educated parents (smarter?, wealthier?, willing to pay?).

Conclusion: Private schools filling supply gap served pupils who would otherwise end-up in public schools of inferior type. Public funding of education provided by non-state schools can increase access to education and decrease inequity.


20

PUPILS’ INITIAL SKILLS AND SKILLS GAINED (by school & ownership types).

Legend: X~ centile rank of initial skills (at the admission).Y~ average centile rank change during studies measured at graduation.

Top line: state gymnasia (highest value added) Middle line: private gymnasia Bottom line: state technical schools.

Ave

rage

cen

tile

rank

cha

nge

Initial centile rank

Gymnasia-state Gymnasia-private technical schools-state

0 .5 1

-.5

0

.5

1

Findings: Public gymnasia outperform non-state gymnasia (in terms of student’s rank improvement) but non-state gymnasia are still better than state technical schools (the only would-be alternative for non-state gymnasia students if these gymnasia would not exist). Note that vocational schools are not included due to lack of data (not collected!)

Conclusions: under some conditions, publicly financed private schooling can widen access to better education.


21

TRANSITION TO HIGHER SCHOOLING LEVEL

Negative trade-off between efficiency and equity does not necessary hold call for policy intervention.

HETEROGENOUS PUPILS

Skills

Wealth

Location

Social background

HETEROGENOUS SCHOOLS

Type

Field

Quality

Costs

Location

EFFICIENCY (value added)

INEQUALITY

(skills, income)

Competition, Access / Equity, Market signals

MATCHING


22

PUPILS’ STUDY APTITUDE AND SCHOOL REQUIREMENTS Theoretical case

Study Aptitude

Distribution of Study Aptitude

Pupils in less demanding schools Pupils in highly

demanding schools

Pupils in less demanding schools who would gain more in highly demanding schools

Pupils in highly demanding schools who would gain more in less demanding schools

The overlap can be due to supply & demand imbalances, spatial mismatch, imperfect information, etc. plus specific preferences of some pupils.


23

Empirical case

Test A

GYM SOS SOU

0 200 400 600 800 1000

0

.002

.004

.006

Test B

GYM SOS SOU

0 200 400 600 800 1000

0

.002

.004

.006

Test C

GYM SOS SOU

0 200 400 600 800 1000

0

.002

.004

.006

Test D

GYM SOS SOU

0 200 400 600 800 1000

0

.002

.004

.006

Distribution of PISA 2003 test scores (A-Math, B-Problem Solving, C-reading, D-Natural Sciences) of 15-years old Czech pupils entering upper-secondary schools (GYM-gymnasia, SOS-technical schools, SOU-vocational schools.


24

Share of pupils enrolled in inferior school type A who outperform at least 25% of pupils enrolled in (superior) school type B.

Note: there is high discrepancy between skills and school types in case of boys at vocational and technical schools.

Voc vs. Tech Voc vs. Gym Tech vs. Gym

Boys in

small towns 0.327 0.027 0.329

big towns 0.398 0.065 0.401

Girls in

small towns 0.153 0.022 0.201

big towns 0.146 0.026 0.247


25

Shares of parents who have preferred other school type (w/o unfavourable conditions)

Small towns Big towns

Boys Girls Boys Girls

Gymnazia 0.13 0.09 0.08 0.11

Technical 0.17 0.23 0.14 0.24

Vocational 0.30 0.34 0.22 0.37


26

Share of parents who preferred other school (not available) by study aptitude, municipal size, school type.

Small towns Big towns

Quartile/Type Boys Girls Boys Girls

Gymnasia - 0.00 - -

2 - 0.03 - 0.07

3 0.11 0.10 0.03 0.04

4 0.15 0.06 0.09 0.07

Technical 0.12 0.21 0.10 0.17

2 0.14 0.12 0.10 0.19

3 0.08 0.11 0.09 0.21

4 0.03 0.03 0.05 0.04

Vocational 0.18 0.25 0.11 0.27

2 0.24 0.46 0.20 -

3 0.34 - 0.31 -

4 - - - -


27

ADMISSION SCHEME DESIGN: case of the Czech Republic

Step 1: Pupils gather info about schools in the neighborhood, past year excess demand

ROUND I

Step 2: Pupil (parents) chooses her 1st priority school and submits single application.

Step 3: Admission day (entry exam, interview, grades from the previous school levels)

Step 4: Admission decision (admitted/rejected)

ROUND II

Step 5: Gathering info about schools with remaining slots

Step 6: Admission day (entry exam, interview, grades at the previous school levels)

ROUND III, …etc until all applicants are placed.


28

ADMISSION SCHEME DESIGN: some problems

Those who failed in the 1st round face rather limited choice in the 2nd round.

1st round school choice is very risky

1st round school choice is traumatic decision

pupils with better informed parents (more educated) have advantage

Bad day risk

Strategic misrepresentation of school preferences

Actual demand (revealed) for schools does not reflect latent demand

widespread cases of justified envy (alphabet sorting)

loss of market signals (school management and policymakers)

adverse impact on competition and effective governance

Matching of pupils to schools is noisy

inefficiency (study aptitude, spatial location, fields)

and inequality (small vs. big towns, by gender)


29

TRANSITION TO HIGHER SCHOOLING LEVEL: summary

Pupils-Schools matching affects efficiency and equity

Transitions to higher educational level (all levels) are associated with unequal access to schooling and is source of growing skills inequality.

Unequal access to schooling is boosted by supply gaps.

Highly skilled (or wealthy) pupils are enrolled by better or more demanding schools and skill/economic inequality is amplified.

Persistent supply gaps are an outcome of administrative barriers on schools expansion/closures.

Barriers are based on various, well or poorly grounded policy intensions or interest groups interests.

Oversubscriptions more likely in the presence of heterogeneity (quality, type/field, spatially/administrative restrictions.

Assorted matching between students’ skills and differently demanding (study requirements) school leads to higher value added and therefore higher efficiency.

Transitions to higher schooling levels are fostering competition and efficiency.

Lack of comparative information about legal and effective mechanisms driving pupils-schools matching in most European countries.

Documents

DCO-ZXE089-20040200-jgfPP1 Czech Republic: key policy issues in schooling, training, and human capital development. Presenting at “Growth strategies –