1

Investire nel capitale umano: Il ruolo del rendimento dell’istruzione, delle finanze personali e della politica

b

universitaria

Hubert StraussBanca europea per gli Investimenti (BEI)

Workshop “Demand for Student loans in Italy”Verona, 27 novembre 2009

OECD Working Papers (forthcoming OECD Journal: Economic Studies 2009):

Joaquim Oliveira Martins, Romina Boarini, Hubert Strauss, Christine de la Maisonneuve and Clarice Saadi (2007) "The Policy Determinants of Investment

Pubblicazioni della ricerca OCSE

Maisonneuve and Clarice Saadi (2007), The Policy Determinants of Investment in Tertiary Education". WP 576

published in CESifo Economic Studies, Vol. 54(2)

Hubert Strauss and Christine de la Maisonneuve (2007), “The wage premium on tertiary education”. WP 589

Romina Boarini and Hubert Strauss (2007), “The Internal Rates of Return to Tertiary Education: New Estimates for 21 countries”. WP 591

published in Zeitschrift für Erziehungswissenschaft, Vol. 11(2) (in German)

2

Il concetto della ricercaInvestment in Tertiary

Education

Demand Supply

Returns to Education

Set-up of Education

supply

IndividualFinancingSystems

Labour market premia

Taxation Social benefits

Opportunity costs

Net direct costs

Labour market policies

Product market policies

Tax policies

Pension system policies

Labour market policies

Financial systems

Education policies

Tax policies

Labour market policies

Education policies

Education policies

Financial systems

POLICY LEVERS

Indice

• Determinants of investment in TE

• Trends in TE investment (graduation rates)

• Explaining graduation rates empirically

• Policies simulations

• Broad policy recommendations

3

I. I determinanti dell’investimento nel capitale umano attraverso

studi superiori (SS)

Issues:

• What are the main determinants of human capital that can be prelated to policies? Focus on:

• Private returns

• Financing systems

• Supply characteristics

Illustrazione: Tasso interno di rendimento degli SS (IRR)Real End of tertiary Retirem ent age 1

earnings education period

Earnings profile of a worker witha tertiary education degree 2

Upper-secondary Tertiary

Earnings profile of a worker witha secondary education degree 2

Tim e

Starting of working life

O PPC

DIRC

θ + P' PENS

DIRC : D irect costs of tertiary educationOPPC : Opportunity costs of not starting to work after secondary educationθ + P' : W age & em ployability prem ia associated with tertiary education (net of taxes and benefits)PENS : Retirem ent prem ia for tertiary education workers (net of taxes)

1. Assum ing the sam e length of work ing life.2. Assum ing partia l indexation of pension benefits.

CostsDirect Costsy Opportunitpremium pensionsNet premiumity employabilNet premium Net wage

1 +++

=− −RHe

R

4

Studi superiori: Premio sulla paga oraria lorda

161820

8090100

Premium on TE degree (right-hand scale)

per year of TE

Percentuale della paga media persone con esame di maturità, 2001

68

10121416

304050607080per year of TE

024

ESP

GRCAUTIT

ASW

EDEU NLD BEL FI

NDNKFR

ACANPO

LSW

ILU

XAUSGBR PR

TIR

LUSAHUN

01020

Premio ”occupabilità”: Probabilità di trovare lavoroEsempio: Donne, 2001

4

5

6

-1

0

1

2

3

4

OECD average

Absolute increase in the Employment Probability due to moving from Upper-secondary education to TE

Memo: Employment probabilities of an upper-secondary worker range from 65% to 98%

-2

1

ESP

SWI

LUX

ITA

AUT

IRL

DNK

NLD

USA

AUS

PRT

DEU

FRA

GRC GBR PO

LBE

LCA

NSW

EFI

NH

UN

5

Costo diretto privato degli studi superioriA. Baseline (Net tuition fees only)

14

24

34

44

54

64

Per cent

-16

-6

4

14

GRC DNK

AUT

FIN

DEU

PRT

BEL

IRL

FRA

SWE

ITA

ESP

NLD

HUN

GBR POL

AUS

USA

B. ... including grants for living expenses and loans

54

64

Per cent

Net private costs (incl. grants living expenses + loans never repaid)

Net private costs (incl grants living expenses)

-16

-6

4

14

24

34

44

GRC DN

K

AUT

FIN

PRT

DEU

BEL

IRL

FRA

SWE

ITA

ESP

NLD

Net private costs (incl. grants living expenses)

Stima dell’IRR degli studi superiori

12

14 Men Women OECD average

per anno di studi (persone con studi compiuti), 2001%

4

6

8

10

12

0

2

4

ESPNLDGRCIT

ADEUHUNSW

EPO

LBE

LAUTFI

NCANFR

ADNKUSALU

XAUSPR

TSW

IGBRIR

L

6

Disponibilità del finanziamento individuale: Due sistemi

• Crude approximation of individual financing constraints (“average affordability”):( average affordability ):

•Family-based funding systems: Students “part of their

resources Householdearnings time-Partfunds PublicCostsLivingfeesTuition

+++

families” if anything, loans and grants available up to family income threshold (ex: FRA, DEU)

•Universal funding systems: Based on the individual generalized access to loans/grants (ex: AUS, SWE)

Indicatore medio dei vincoli di liquidità

40

45

50Costo medio degli SS / risorse totali (percentaggio)

Less affordable (+vincoli)

More affordable (–vincoli)

15

20

25

30

35

Average universal systemsAverage family-based systems

0

5

10

SWE

DNK

FIN

NLD

LUX

CAN

GBR US

AAU

SCZ

EDE

USW

IBE

LIR

LG

RC POL

SVK

ITA

FRA

AUS

ESP

HUN PR

T

7

Offerta degli SS: Struttura dell’indicatoreSUPPLY OF TERTIARY

EDUCATION (STE)

INPUT FLEXIBILITY (1/3) SUPPLY FLEXIBILITY (1/3) ACCOUNTABILITY (1/3)

Selection of students (1/3)

Budget autonomy (1/3)

Staff policy (1/3)

Number of students (1/3)

Profile of students (1/3)

In case of no

Sources of funding

(1/2)

Structure of spending

(1/2)

Hiring/Firing (1/2)

Wages (1/2)

Course content and exams (1/5)

Offer of short studies (1/5)

Student

Evaluation (1/2) Funding rules (1/2)

Institutional evaluation (1/3)

Stakeholder evaluation

Public i f ti

Public funding (1/2)

Private funding (1/2)

Numerus clausus

possibility for student

selection (1/3)

choice (1/5)

Regional mobility (1/5)

Existence of "Numerus

clausus" (1/5)

information (1/3)

NB: weights are in (.)

Indicatore complessivo dell’offerta SS(Sistema con centralizzazione massima=0 Sistema con massima autonomia/incitazioni=10)

8

9

10

2

3

4

5

6

7

Average

Colonne: Intervalli di confidenza

0

1

2

GR

CD

EUBE

L (F

r)TU

RFR

ASW

IIT

AN

LDN

OR

ISL

AUT

ESP

CAN

(Qu)

BEL

(Fl)

SWE

PRT

BEL

(D)

DN

KC

AN (M

a)C

AN (O

n)U

SA (F

ed)

HU

NKO

RIR

LFI

NC

AN (A

l)SV

KC

ZE JAP

MEX

GBR

CAN

(Sa)

USA

(Oh)

CAN

(BC

)C

AN (N

B)U

SA (T

x)AU

SN

ZL

Supply indicator, point estimate

8

II. Evoluzione dell’investimento negli studi superiori (SS)studi superiori (SS)

Laureati degli SS nell’OCSENuovi laureati (sin.), tutti i laureati (dir.), media OCSE, 1994-2004

6Flow of new tertiary graduates

% of population aged 20-29

4

5

6

MalesFemales

Stock of tertiary graduates% of population 25-64

5

10

15

20

25

30

MalesFemales

ISCED 5a-b, 6; based on graduates (2004) and time series of graduation rates.

3

19941995

19961997

19981999

20002001

20022003

20040

19911992

19931994

19951996

19971998

19992000

20012002

20032004

9

Nuovi laureati degli SSpercentuale della popolazione di età 20-29, 2004

5

6

7

8

9

10

20041995 or first available year

Men

8

9

10

Women

0

1

2

3

4

TURMEX

GRCCZE

HUNSVK

PRTAUT ITA

DEUPOL

BELCAN

ESPSWE

NORUSA

NLD ISL FINAUS

FRADNK

GBRSWI

IRLJA

PNZL

KOR

0

1

2

3

4

5

6

7

TURMEX

GRCCZE

AUTDEU

SWISVK

HUNBEL ITA

NLD ESPCAN

FRAUSA

SWEPOL

AUSPRT

JAP

NOR FINDNK

GBR IRL ISLKOR

NZL

20041995 or first available year

III Stima del tasso di nuovi laureatiIII. Stima del tasso di nuovi laureati

10

Spiegare l’investimento negli SS

Estimate a reduced form equation modelling the investment in human capital with variables identifying either demand or supplyidentifying either demand or supply

Candidates for explanatory variables are:

Private returns (IRR)

Financing system/constraints

Institutional features of education systemsy

Gender, demography, business cycle, public funding, secondary-education outcomes

key assumption: IRR are pre-determined

RisultatiPooled model

(1)

Pooled model with country-specific time

trend

(2)

Pooled model with country-specific time trend and year fixed

effects(3)

Dependent Variable : pLog of graduation ratio

IRR 5.84*** 3.27*** 3.19***[0.77] [0.82] [0.85]

Supply indicator 0.17*** 0.20*** 0.21***[0.02] [0.03] [0.03]

Financial constraints -0.02*** -0.03*** -0.03***[0 00] [0 00] [0 00][0.00] [0.00] [0.00]

Output gap 0 -0.03*** -0.03***[0.01] [0.01] [0.01]

Female dummy 0.22*** 0.21*** 0.21***[0.04] [0.02] [0.02]

Constant 0.09 0 -0.21[0.12] [0.17] [0.22]

Observations 266 266 266

R-squared 0.54 0.84 0.85

11

IV. Effetto di varie politiche

Simulazioni:

• (I) Aumentare l’autonomia e il “render conto” delle università

• (II) Aumentare i tassi d’iscrizione all’università

• (Not shown: lowering marginal income tax rate; studying faster; more student part-time work)

Più autonomia e rendicontabilità:Effetto sulla percentuale di nuovi laureati

(%-age points)

3.5

4

1

1.5

2

2.5

3

Effect of aligning the STE indicator on the maximum in the sample (Australia).

0

0.5

GBRHUN ITA

CANAUT

FIN USA IRLPRT

SWEDNK

ESPNLD

BELFRA

DEUGRC

12

Aumentare i tassi d’iscrizione:Effetto sulla percentuale di nuovi laureati

(%-age points)

-0.5

0

3

-2.5

-2

-1.5

-1

Effect via the education returns

Effect via Financing Constraints

Increasing tuition fees up to the sample mean plus two standard deviations, to level slightly larger than in Australia.

-4

-3.5

-3

FINDNK IRL

SWEDEU

BELFRA

NLDGBRGRC

ESPCAN

AUT ITAPRT

HUNAUS

Overall effect

Tre suggerimenti principali

Make individuals aware of the cost and future returns of TE investment possibly by returns of TE investment, possibly by contributing to financing TE

Provide universal loan funding of TE based on the individual to ease liquidity constraints

Provide more autonomy and accountability to universities

13

Investire nel capitale umano: Il ruolo del rendimento dell’ istruzione, delle finanze personali e della politicha

b ( )

delle finanze personali e della politicha universitaria

Hubert Strauss (EIB)h.strauss@eib.org

Joaquim Oliveira Martins, Romina Boarini, Christine de la Maisonneuve (all OECD)

How to model the relation between human capital and its determinants?

Ideally: estimate the demand and the supply of TE, but existing structural models (Epple et al., 2006; Hoxby, 2005; Rotschild and White, 1995) are neither relevant for all OECD countries nor empirically estimableEmpirical strategy: graduation rates driven by

Demand: Incentives (Becker, Freeman) + qualifications on market imperfections (borrowing and liquidity constraints)Supply: Institutional Features of TE Supply System

Caveat: neither control for the quality of the investment nor for the composition (i.e. types and fields of tertiary degrees)

14

Spending per student vs. investment outcomes: a mixed picture

Graduation ratios vs. costs per student, 2001

Gbr

I5 0

5.5

ratio

s

USA

Swi

Swe

EspPrt

Pol

Nld

Ire

H

Ger

Fra

Fin

Den

Can

Bel

Aut

Aus

3.0

3.5

4.0

4.5

5.0G

radu

atio

n r

Ita

Hun

Grc

1.5

2.0

2.5

0 5000 10000 15000 20000 25000

Expenditure

Wage premia of higher education90% confidence intervals of point estimators, 2001

D N K

D E U

C AN

B E L

AU T

AU S MenW om en

L U X

IT A

IR L

H U N

G R C

G B R

F R A

F IN

E S P

D N K

Cou

ntry

0 .0 0 0 .1 0 0 .2 0 0 .3 0 0 .4 0 0 .5 0 0 .6 0 0 .7 0 0 .8 0

U S A

S W I

S W E

P R T

P O L

N L D

A v e ra g e p re m iu m o v e r g ro s s h o u rly w a g e o f u p p e r-s e c o n d a ry d e g re e h o ld e r

15

What is the share of different fields? OECD average, in % of new tertiary graduates, 2004

30.0

35.0

MalesFem ales

10.0

15.0

20.0

25.0

0.0

5.0

Agriculture Education Engineering,manufacturing

andconstruc tion

Health andwelfare

Humanitiesand Arts

Sc ience Services Soc ialsc iences ,

business andlaw

Wage premia are fairly stable over time

MenPercentage point increase WomenPercentage point

i

30.0

40.0

50.0

60.0

70.0

80.0

200

30.0

40.0

50.0

60.0

70.0

80.0increase

0.0

10.0

20.0

1994 1995 1996 1997 1998 1999 2000 2001

DNK DEU GRC IRL PRT GBR USA

0.0

10.0

20.0

1994 1995 1996 1997 1998 1999 2000 2001

DNK DEU GRC IRL PRT GBR USA

16

Employability Premia of Higher Education, 2001

MenPercentage point WomenPercentage point

increase

-1.0

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0increase

Average

20

-1.0

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0increase

Average

Absolute increase in the Employment Probability due to moving from Upper-secondary to Tertiary Education

Memo: Employment probabilities of an upper-secondary worker range from 65% to 98%

-2.0

Irela

nd

Net

herla

nds

Hun

gary

Belg

ium

Switz

erla

nd

Fran

ce

Den

mar

k

Gre

ece

Luxe

mbo

urg

Swed

en

Spai

n

Aust

ria

Uni

ted

King

dom

Uni

ted

Sta

tes

Aust

ralia

Ger

man

y

Portu

gal

Finl

and

Can

ada

Pola

nd Italy

-2.0

Spai

n

Switz

erla

ndLu

xem

bour

g

Italy

Aust

ria

Irela

nd

Den

mar

k

Net

herla

nds

Uni

ted

Stat

es

Aust

ralia

Portu

gal

Ger

man

y

Fran

ce

Gre

ece

Uni

ted

King

dom

Pola

nd

Bel

gium

Can

ada

Sw

eden

Finl

and

Hun

gary

Marginal employment probability may vary over time

MenPercentage point WomenPercentage point

4.0

6.0

8.0

10.0

12.0

14.0

16.0

18.0

g pincrease

Belgium Germany IrelandItaly Netherlands SpainUnited States

Women

4.0

6.0

8.0

10.0

12.0

14.0

16.0

18.0

g pincrease

BelgiumGermanyIrelandItalyNetherlandsSpainUnited States

-2.0

0.0

2.0

1994 1995 1996 1997 1998 1999 2000 2001-2.0

0.0

2.0

1994 1995 1996 1997 1998 1999 2000 2001

17

Tuition fees are well below costs in many countries

Ratio of tuition fees to costs per student, selected O ECD countries

Ratio for public Institutions

50 0

60.0

70.0

%

0.0

10.0

20.0

30.0

40.0

50.0

Cze

ch R

epub

lic

Den

mar

k

Finl

and

Icel

and

Irela

nd

Nor

way

Slov

ak R

epub

lic

Swed

en

Fran

ce

Hun

gary

Sw

itzer

land

Turk

ey

Belg

ium

(Fl.)

Bel

gium

(Fr.)

Aus

tria

Spa

in

Italy

Can

ada

Uni

ted

Sta

tes

Aus

tralia

Kore

a

Ratio for private Institu tions180.0

%

0.0

20.0

40.0

60.0

80.0

100.0

120.0

140.0

160.0

Finl

and

Sw

eden

Bel

gium

(Fl.)

Belg

ium

(Fr.)

Aust

ria

Net

herla

nds

Uni

ted

King

dom

Icel

and

Nor

way

Fran

ce

Cze

chR

epub

lic

Uni

ted

Stat

es

Kor

ea

Aust

ralia

Estimates of private Internal Rates of Return (IRRs)

MenPer cent WomenPer cent

2.0

4.0

6.0

8.0

10.0

12.0

14.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

0.0

Spa

in

Italy

Net

herla

nds

Gre

ece

Ger

man

y

Hun

gary

Pol

and

Sw

eden

Bel

gium

Aus

tria

Finl

and

Fran

ce

Can

ada

Uni

ted

Sta

tes

Den

mar

k

Luxe

mbo

urg

Aus

tralia

Por

tuga

l

Sw

itzer

land

Uni

ted

Kin

gdom

Irela

nd

0.0

Italy

Aus

tria

Sw

eden

Ger

man

y

Net

herla

nds

Bel

gium

Spa

in

Hun

gary

Finl

and

Uni

ted

Sta

tes

Gre

ece

Den

mar

k

Fran

ce

Can

ada

Aus

tralia

Luxe

mbo

urg

Sw

itzer

land

Pol

and

Uni

ted

Kin

gdom

Por

tuga

l

Irela

nd

There are substantial private returns to Higher Education

18

Living and tuition costs in HE

6000

7000

8000Universal funding Family-based funding systems

In EUR at Purchasing Power Standards

1000

2000

3000

4000

5000Living costTuition cost

0

1000

Cana

daNe

ther

l.Fi

nlan

dSw

eden US

Denm

ark

Austr

alia

Luxe

mb. UK

Pola

ndCz

ech

Rep.

Slov

ak R

ep.

Hun

gary

Gre

ece

Port

ugal

Belg

ium

Ger

man

yIta

lySw

itzer

lIr

eland

Fran

ceSp

ain

Austr

iaResources available to HE students

25000

30000

Other resources

Universal funding Family-based funding

In EUR at Purchasing Power Standards

5000

10000

15000

20000Other resourcesMax. grants and loans

0

Luxe

mb.

Austr

alia

Finl

and

Neth

erl.

Cana

daDe

nmar

kSw

eden UK US

Pola

ndSl

ovak

Rep

.H

unga

ryCz

ech

Rep.

Port

ugal

Gre

ece

Spai

nIta

lyFr

ance

Austr

iaG

erm

any

Belg

ium

Irela

ndSw

itzer

l.

19

Impact of easing liquidity constraints on graduation ratios

3 0

3.5

ge p

oint

s

0.5

1.0

1.5

2.0

2.5

3.0Pe

rcen

tag

0.0

Denmark

Finland

Netherla

nds

Grece

German

y

Belgium Italy

Canad

a

Hungary

Austria

Irelan

d

France

United

States

United

Kingdom

Austra

liaSpa

in

Portug

al

Note: Effect of an alignment of the ratio of investment costs to financing resources on the minimum in the sample (this benchmark was preferred as the sample mean minus two standard deviations is below the minimum).

Impact of a decrease of marginal tax rates on graduation ratios

3.5

poin

ts

0.5

1

1.5

2

2.5

3

Perc

enta

ge p

0

Greece

Irelan

d

Austra

lia

United

States

Spain

Austria

Portug

al

United

Kingdo

m

Canad

aIta

ly

Franc

e

Netherl

ands

Sweden

Belgium

Denmark

Finlan

d

German

y

Hunga

ry

Note: Effect on graduation ratios of decreasing marginal tax rates by 5 percentage points.

20

Econometric Estimates: DetailsBASELINE Col.(1) Col.(2) Col.(3) Col.(4) Col.(5) Col.(6) Col.(7) Col.(8)

Dependent Variable : Log of graduation ratio Tertiary Graduation

Rate (log) Wage Premia System explanatory variablesIRR 3.19*** 1.65 3.50*** 2.69** 2.10* 2.54*** 1.97* 3.95*** 2.77** 4.96*** IRR

[1.02] [1.04] [0.96] [1.11] [1.12] [0.86] [1.04] [1.05] [1.08] [1.65]Supply indicator 0.21*** 0.12*** 0.21*** 0.24*** 0.17*** 0.09** 0.23*** 0.17*** 0.20*** 0.18*** Supply Flexibility Indicator

[0.02] [0.04] [0.02] [0.03] [0.05] [0.05] [0.02] [0.03] [0.02] [0.03]Financial constraints -0.03*** -0.02*** -0.03*** -0.02*** -0.01*** -0.02*** -0.03*** -0.04*** -0.03*** Financial Constraints

Table 4 Graduation ratios Regressions ResultsAssumption: exogenous IRR Assumption: endogenous IRR

System of simultaneous equations

[0.00] [0.00] [0.00] [0.00] [0.00] [0.00] [0.00] [0.00] [0.00]Output gap -0.03*** -0.04*** -0.04*** -0.03*** -0.03*** -0.01 -0.04*** -0.03*** -0.02**

[0.01] [0.01] [0.01] [0.01] [0.01] [0.01] [0.01] [0.01] [0.01]Female dummy 0.21*** 0.21*** 0.18*** 0.21*** 0.22*** 0.21*** 0.21*** 0.21*** 0.21*** 0.23*** Female dummy

[0.02] [0.02] [0.03] [0.02] [0.03] [0.02] [0.02] [0.02] [0.02] [0.02]Family-based funding systems -0.43*** 0.44*** -0.07*** Stock of Tertiary Human Capital

[0.07] [0.08] [0.01]

Students working part-time 0.03*** 0.03*** PISA score (standard deviation)[0.01] [0.00]

Share of Students in Private Institutions 0.01*** -0.02** Tertiary Graduation Rate (log)[0.00] [0.01]

PISA score (mean) 0.01*** 0.01*** EPL (regular workers)[0.00] [0.00]

PISA score (standard deviation) 0.02*** -0.01*** EPL (temporary workers)[0.00] [0.00]

Upper-Secondary Degree Holders Ratio 0.30** -0.05*** Bargaining Coordination[0 15] [0 01][0.15] [0.01]

Share of Foreign Students 0.88* 0.02* Trade openness[0.45] [0.01]

Ratio of expenditure in tertiary education (per student) to GDP per capita 0.26***[0.05]

Constant -0.21 -0.09 -1.72** -0.52** 0.01 -5.05*** -2.33*** 0 0.25 -2.11*** 0.17*** Constant[0.20] [0.26] [0.77] [0.20] [0.36] [1.61] [0.44] [0.20] [0.20] [0.44] [0.03]

Observations 266 266 266 266 266 266 266 266 266 266 266 Hansen-Sargan testR-squared 0.85 0.85 0.85 0.86 0.82 0.86 0.86 0.86 0.86 0.9 0.73 Chi2(4) : 5.51All the specifications include country-specific trends and year dummies.Standard robust errors in brackets* significant at 10%; ** significant at 5%; *** significant at 1%Source : OECD calculations.