THE ROLE OF POLICIES AND INSTITUTIONS FOR GOOD LABOUR MARKET PERFORMANCE IBM Chair, Labour Market...

THE ROLE OF POLICIES AND

INSTITUTIONS FOR GOOD LABOUR

MARKET PERFORMANCE

IBM Chair, Labour Market Course 20-24 November, Milan

Stefano ScarpettaDeputy Director for Employment, Labour and Social Affairs

[email protected]

Stefano Scarpetta, IBM Chair, Labour Market Course

• Lecture 1 (Tuesday): Economic growth and labour market – Economic growth across countries and over time– The role of labour market for promoting economic growth and the distribution of its

benefits– From an aggregate to a sectoral and firm-level perspective: the importance of labour

reallocation for productivity and output growth

• Lecture 2 (Wednesday): The role of policies and institutions for structural labour market outcomes

– Key policy and institutions affecting labour market outcomes– A model and an empirical analysis to assess the role of policy and institutions for LM

outcomes and their interactions

• Lecture 3 (Thursday): The role of structural policies and institutions for labour market resilience and resource allocation

– The role of policy and institutions for LM resilience– From a static to dynamics analysis of the labour market: job and worker flows,, effects

on productivity and workers

2

Overview of the course


• Familiarise students with the role of policies and institutions for good labour market performance over the business cycle

• Show how simple descriptive statistics and econometric analysis can be used to provide evidence-based policy assessments

• Show what can be learnt from making cross-country comparisons

3

Course objectives


• Born out of the Organisation for European Economic Cooperation (OEEC) which was set up after WWII to coordinate the Marshall plan

• Transformed into Organisation for Economic Cooperation and Development (OECD) in 1961 to promote policies for development (16 EUR, CAN + USA)

• Provides a forum in which governments work together to share experiences and seek solutions to common problems– Benchmarking (construction of comparable data), analysis &

policy advice

4

What is the OECD?


• Currently 34 full member countries, incl. CHL, MEX & TUR– Russia in accession process

• Enhanced engagement with major emerging economies: – BRA, CHN, IDN & IND

• Working relationships with over 70 developing and transition economies

• Policies to promote economic (“green growth”); boost employment ; raise living standards (“better lives initiative”); maintain financial stability; econ. dev. in other countries

5

From “rich-men’s club” to organisation with increasingly global reach

6

Lecture 1: Economic growth and the labour market– Economic growth across

countries and over time– The role of labour market for

promoting economic growth and the distribution of its benefits

– The role of labour reallocation for productivity and output growth


Stefano Scarpetta, IBM Chair, Labour Market Course 7

• Large cross-country differences in income per capita and output per worker

• Globally, these differences tend to persist over time (even though subsets of countries did converge)

• Overall cross-country dispersion or inequality has increased over time

• Distribution tends to be bi-modal or even tri-modal• But the dispersion has actually declined if

population size is taken into account (China, India)

Stylized facts


• Differences in incomes p.c. reflect starting conditions and, especially, differences in GDP p.c. growth rateso Very small differences in growth rates for long periods of time

can have dramatic implications for income p.c. levelso In fact economic historians agree that most of current differences

in levels depend on differences in growth rates over past 2 centuries

o And despite large differences in starting conditions after the 2nd WW sustained growth rates have allowed convergence in levels for most founding OECD countries and even for some non-OECD African and Asian countries

• Still, globally there are large cross-country differences in growth rates, and globally these have tended to become larger

Stylized facts

9

• Given cross-country differences in income levels and growth rates key issue is that of convergenceo Are growth patterns such that there is

convergence in income p.c. levels?o If so, is this a generalised phenomenon or is

it limited to clubs of countries?

• Useful concepts here are absolute, conditional and club convergence


Stylized facts


Growth trajectories and convergence (1870-2000) (logs GDP per capita)

y = 0.0187x + 7.7087

6.000

6.500

7.000

7.500

8.000

8.500

9.000

9.500

10.000

10.500

1870

1880

1890

1900

1910

1920

1930

1940

1950

1960

1970

1980

1990

2000

USA

UK

FRANCE

GERMANY

ITALY

JAPAN

SWEDEN

Linear (USA)

y = 0.0187x + 7.7087

6.000

6.500

7.000

7.500

8.000

8.500

9.000

9.500

10.000

10.500

1870

1877

1884

1891

1898

1905

1912

1919

1926

1933

1940

1947

1954

1961

1968

1975

1982

1989

1996

USA

BRAZIL

RUSSIA

INDIA

CHINA

Linear (USA)

USA and selected OECD USA and BRICs

Leader

Source: Maddison (2003), data 1990 US$ PPPs

11

Convergence patterns and clubs (1962-2008)


12Stefano Scarpetta, IBM Chair, Labour Market Course

OECD 1970-1994: A Convergence Club

Australia

Austria

Belgium

CanadaCzech Rep.Denmark

FinlandFrance

Germany

Greece

Hungary

Ireland

Italy

Japan

Korea

Mexico

Netherlands

New Zealand

Norway

Poland

Portugal

Slovak Rep.

Spain

Sweden

Switzerland

Turkey

UK

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

-80 -70 -60 -50 -40 -30 -20 -10 0 10Gap in GDP per capita (%), 1970

Ga

pin

av

era

ge

gro

wth

ra

te (%

) 1

97

0-1

99

4

Convergence zone

Divergence zone


OECD convergence 1995-2006

Australia

Austria

Belgium

Canada

Czech Republic

Denmark

Finland

France

Germany

Greece

Hungary

Iceland

Ireland

Italy Japan

Korea

Mexico

NetherlandsNew Zealand

Norway

Poland

Portugal

Slovak Rep.

Spain Sweden

Switzerland

Turkey

UK

-1.5

-0.5

0.5

1.5

2.5

3.5

-80 -70 -60 -50 -40 -30 -20 -10 0 10Gap in GDP per capita (%), 1994

Ga

pin

av

era

ge

gro

wth

ra

te (%

) 1

99

5-2

00

6

Divergence zone

Convergence zone

14

GDP per capita

Labour productivity(output per hour worked)

Labour utilisation(hours worked per capita)

GDP per capita



Capital deepening (capital per

hour worked)

Multi -factorproductivity

Quality of capital

(vintage

and asset

composition )

Quality of labour

(skill mix )

Pure technicalprogress

GDP per capita



Hours workedper worker

Capital deepening (capital per

hour worked)

Multi -factorproductivity

Structural unemployment

rate

Labourforce

participation

Quality of capital

(vintage

and asset

composition )

Quality of labour

(skill mix )

Pure

technicalprogress

Employment rate

Determinants of GDP p.c. An overview


Industries Industries

Firms Firms

Allocation process


Growth decompositions

Simple decompositions of GDP p.c. (GDPpc):

Can also be expressed relative to benchmark country (0) :

pop. Active x part. force Lab. x rate) unempl. -(1 x p.w. Hours x prod.Hourly )1(

pop. Active x particip. forceLabour x rate Empl. x p.w. Hours x prod.Hourly

pop. Active x rate Employment x p.w. Hours x prod.Hourly

nutilisatioLabour ty x productiviHourly

6415

6415

6415

6415

6415

6415

Pop

Pop

Pop

LFu

E

H

H

GDPGDPpc

Pop

Pop

Pop

LF

LF

E

E

H

H

GDPGDPpc

Pop

Pop

Pop

E

E

H

H

GDPGDPpc

LULPHPop

H

H

GDP

Pop

GDPGDPpc

1GDPpc

GDPpc0

(1LPH

LPH0

) (1LU

LU0

)(LPH

LPH0

)


Growth decompositions

• Decomposition are mechanical but help to e.g.:– highlight proximate sources of cross-

country differences in GDP (productivity, hours worked, unemployment, participation and demographics)

– perform simple projections/simulations of future GDP scenarios (e.g. economic baseline for models), with assumptions/projections for each of the elements


Cross-country differences in GDP per capita GDP and productivity levels in US$ PPP, 2007Percentage gaps with respect to United States

Gap in GDP per capita = Gap in labour utilisation+Gap in GDP per hour worked


Simple growth decomposition

• A similar simple decomposition can of course be done for GDPpc growth rates (denoted with a hat):

where the cross term(s) can usually be ignored (and, hence, the ln operator can be used to derive growth rates).

• The next figures show that the main driver of

growth is labour productivity.

LULPHLULPHLULPHGDPpc

19

Growth in GDP per capita = Growth in labour utilisation


+Growth in GDP per hour worked

What drives cross-country differences in GDP per capita growth ?Total economy, percentage change at annual rate, 1997-2007


• In 2007, the ER reached record high (67%) and the UR stood at a 25 year low (5.6%). – A supportive macro-economic environment– Structural reforms in product and labour

markets– Increased labour force participation of women

and older workers

• By 2007, the key policy priority had shifted from combating UR to removing barriers to LFP – Limit the adverse consequences of population

ageing– Alleviate skill shortages

20

Labour market performance before the crisis


Labour market performance differs across countries…Employment rates in OECD countries (%), 1994-2007

30

40

50

60

70

80

90

TUR

POL

HU

NIT

AIS

RSV

KM

EXG

RC BEL

KOR

LUX

FRA

CZE

ESP

PRT

IRL

EST

DEU FI

NJP

NAU

TU

SAG

BR AUS

CAN

NLD NZL

SWE

NO

RD

NK

CHE

OEC

D G7

% 1994 2007


Large hike in unemployment rates, 2007 Q4 to 2011 Q3

Unemployment rate before the crisis, at its peak and its latest value* in percentage of total labour force, quarterly data

Countries are shown in ascending order by the unemployment rate at its peak.* Trough (peak) dates are defined as the start of the longest spell of consecutive increase (decrease) of the quarterly OECD harmonised unemployment rates since 2006 Q1. Source: OECD calculations based on OECD Main Economic Indicators Database.

Norway

Korea

Netherl

ands

Switzerla

ndAus

triaJa

pan

Luxe

mbourg

Austra

lia

Mexico

New Zea

land

Denmark

Czech

Rep.Isr

ael

German

y

Sloven

ia

United

Kingdo

m

Belgium

Canad

a

Icelan

dIta

ly

Finlan

d

Sweden

Poland

United

States

France

Chile

Hunga

ry

Portug

al

Turkey

Irelan

d

Slovak

Rep.

Greece

Estonia

Spain

OECD G7

Euro ar

eaEU-27

0

2

4

6

8

10

12

14

16

18

20

22

24Pre-cris trough Peak Latest


Youth have been hit especially hard during the crisisYouth (15-24/16-24) unemployment rate before the crisis, at its peak and its latest value* in percentage of youth

labour force, quarterly data

Countries are shown in ascending order by the youth unemployment rate at its peak.* Trough (peak) dates are defined as the start of the longest spell of consecutive increase (decrease) of the quarterly OECD harmonised unemployment rates since 2006 Q1. Source: OECD calculations based on the Short-term indicators from Eurostat and national labour force surveys.

0

5

10

15

20

25

30

35

40

45

50

55Pre-crisis trough Peak Latest

24

Sources of gaps in labour utilisation: Employment rate by socio-economic group


Prime-aged men

(25-54 years)

Immigrants(men)

Prime aged women (25-54 years)

Older workers(55-64 years)

Low skilled workers

Youth(15-24 years)

0

10

20

30

40

50

60

70

80

90

100

OECD Worst performing countriesBest performing countries

Percent of the population

30Stefano Scarpetta, IBM Chair, Labour Market CourseSource : OECD, Education at a glance, 2007.

Educational attainment, upper-secondary education in 2005

Percentage of population aged 25-34 and 45-54

0

10

20

30

40

50

60

70

80

90

100

25-34 45-54

Significant differences in the level of human capital across countries and over time


Human capital plays a significant role in boosting labour productivity…

Growth in GDP per person employedContribution to growth in GDP per person employed from changes in1:

Hourly GDP per efficient unit of labourHours workedHuman Capital

1. This is based on a simple quantitative decomposition: growth in GDP per person employed = (labour productivity adjusted for hours and human capital) + ( growth in average hours worked) + (human capital adjustment).

-2 -1 0 1 2 3 4 5

New Zealand

Netherlands

Canada

France

Germany

Italy

United Kingdom

United States

Australia

Denmark

Portugal

Norway

Sweden

Finland

Ireland

Per cent


…but skill-biased employment rates Percentage point change of the share of individuals with higher educational levels1 in total

1. Higher education levels refer to ISCED codes 5, 6 and 7.2. 1991-2000.

Aus

Aut

Bel Can

Dnk

Fin

Fra

Irl

Ita

Nld Nzl

Nor

Prt

Esp

Swe

Che

Tur2

Gbr

Usa

Deu2

0

3

6

9

12

15

0 3 6 9 12 15

Employment

Working-age population


Heterogeneity of productivity developments and resource reallocation

• Aggregate productivity levels mask large differences in productivity levels across industries and, within industries, across firms.

• Similarly, aggregate productivity growth reflects widely heterogeneous developments in productivity at the industry and firm level as well as reallocation of resources across them.

Differences in heterogeneity and reallocation processes contribute to explain cross-country differences in productivity growth.


Heterogeneity and reallocationSector-level decompositions of aggregate productivity growth

• Two related questions are of interest:– How much does each sector (or group

of sectors) contribute to aggregate productivity growth?

– What are the relative contributions of within sector growth and changes in sector composition to aggregate productivity growth?


Heterogeneity and reallocation Sector-level decompositions of aggregate productivity growth

Shift-share decomposition• Changes in aggregate labour productivity

reflect changes in productivity within each sector of the economy and shifts in its sectoral composition.

• Therefore, aggregate productivity growth can be accounted for in terms of sectoral contributions and intersectoral reallocation of resources.

• Such accounting can be done using so-called shift-share analysis.


Shift-share decomposition• Suppose you want to decompose changes in an

aggregate variable X relative to its level in a base year X0 into the two components (within each sector k and between sectors).

• We start from the identity:

• where sk is the share of sector k (measured in terms of employment in the case of labour productivity).


)( 000kk

kkk XsXsXX


Shift-share decomposition

• Adding and subtracting the sums of each of the cross-products

, and the own product ,

we get the shift share decomposition:

where – ΔX accounts for the within sector change,

– Δs accounts for the shift in sectoral composition (between effect) and

– the last is an interaction term, which can be interpreted loosely as an indicator of covariance: if it is positive, within and between effects act in the same direction.


XssXkkkk

kkkk

kkkk

k XXssXsssXXXX ))(()()( 0000000

k

kk Xs0 k

kk Xs 0 k

kk Xs 00


Shift-share decomposition• In growth terms, if X is productivity (i.e. Y/L) one divides both

sides by X0 to obtain:

• where y is the sectoral share of output in aggregate output Y and s is the sectoral share of labour in aggregate labour input L.

• Here the first term provides the within sector contribution to aggregate productivity growth and the second term indicates that the contribution of sectoral shifts depends on the ratio of sectoral to average productivity.

• Most of the changes in productivity over the periods considered originate in within industry efficiency improvements. But between effects can be important in some countries.


kkk

kk

kk

kkk

k XssX

XssyXX ˆ)()(ˆˆ 00

000


Shift and Share, all industries, 1994-2004

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6Within Between Cross


Shift and Share, services industries, 1994-2004

-1

-0.5

0

0.5

1

1.5

2Within Between Cross


• There is a growing evidence that the population of firms undergo significant changes over time, both through resource reallocation between existing firms and the process of firm entry and exit.

• The study of productivity, the role of within-firm productivity growth vs. the productivity growth induced by the reallocation of resources has been the focus of much recent research (see, e.g., Olley and Pakes (1996), Griliches and Regev (1995) and Foster, Haltiwanger and Krizan (2001,2002) Bartelsman, Haltiwanger, and Scarpetta (2004), Syverson (2004), Foster, Haltiwanger and Syverson (2008)).

• The impact of changing patterns of international trade on an economy is increasingly viewed through these lenses, with evolving trade relations changing the market structure and mix of businesses (e.g. Helpman, Melitz, and Yeaple, 2004).

• Substantial churning of firms, along with the reallocation of labor across continuing firms, implies that workers and firms incur in significant search and other adjustment costs (see, e.g., Mortensen and Pissarides, 1999; and Caballero and Hammour, 2000).

– As such, the efficiency of an economy in dealing with such reallocation is important not only for the productivity dynamics of the economy, but also for the dynamics of the labor market and in particular of unemployment.

• For all of these reasons, firm-level dynamics appear to be crucial for the relative success all market economies

Heterogeneity and reallocationwithin-industry heterogeneity and aggregate productivity growth


Firms heterogeneity: stylized facts

1. Size and growth: The probability of survival tends to increase with firm size; but, conditional on survival, the proportional rate of growth of a firm is decreasing in size (see Evans 1987a, 1987b; Dunne et al. 1988, 1989).

2. The firm life cycle: For any given size of firm, the proportional rate of growth is smaller the older the firm, but its survival probability is greater (see Foster et al. 2001; and International Journal of Industrial Organization, 1995).

3. Shakeouts: The number of producers in a given market tends first to rise to a peak, and later to fall to some lower level. (Klepper and Graddy, 1990; Klepper and Simons, 1993; Geroski, 1995).

4. Churning: There is a high pace of the reallocation of outputs and inputs across businesses (e.g. Geroski, 1995, Ahn, 2000 and Davis and Haltiwanger, 1999 for surveys of the literature).

5. Reallocation and Productivity: In well‑developed market economies, the evidence is overwhelming that the pattern of reallocation is productivity enhancing. (see e.g. Olley and Pakes, 1996, Griliches and Regev, 1995, and Foster, Haltiwanger and Krizan, 2001, 2002).


Theoretical models of firm heterogeneity

Several theories have been developed to explain these observed patterns of firm dynamics survival and growth. They generally relate to the process of ‘creative destruction’ (usually ascribed to Joseph Schumpeter).

– 1) and 2) are consistent with the passive learning models (Jovanovic, 1982): new entrants do not know their potential profitability. Learning leads new firms to expand, contract or exit the market. Cabral (1995 and 2003) assumes that firms must incur a sunk cost in building production capacity. Since small entrants have a higher probability of exit than large firms, it is optimal for them to invest more gradually, and thus experience higher growth rates if successful, than larger entrants.

– Shakeouts (3) is consistent with Jovanovic and MacDonald (1994) who argue that over time a new technology emerges which offers low unit costs but higher level of output per firm. The transition to the new technology involves a shakeout of first generation firms.

– Churning (4) is consistent with active learning models (Ericson and Pakes, 1995): here firms explore actively and invests to enhance profitability under competitive pressure; they grow if successful, shrink or exit if unsuccessful.


Productivity dispersion across firms in ICT-producing

France

Electrical and optical equipment Telecommunications

The figures present the distribution of labour productivity in each industry and year between the 5th and 95th percentiles. The upper bound of the grey bar represent the 75th percentile, the lower bound the 25th percentile and the line in the middle of each grey bar being the median. Labour productivity is measured as value added per worker in 100 thousands of 1995 Euros. Source: Authors’ calculations from AMADEUS database.

Much of the increase in dispersion comes from top performers.

25th %ile

75th %ile

95th %ile

5th %ile

Wide firm heterogeneity within industries (2)


• Average productivity levels/growth in the aggregate and in each industry depend on the dispersion of productivity levels/growth across incumbents and firms entering and exiting markets.

• That is:– efficiency levels/improvements within each firm,– allocation/reallocation of resources across firms with different

efficiency levels/growth– entry/exit of firms with different efficiency levels/growth

• There are several ways to decompose average productivity levels/growth into these different static and dynamic elements.

• Methods are similar to, albeit more complicated than, those used in shift-share analysis.

Heterogeneity and reallocationFirm-level decompositions of aggregate productivity


Job and worker flows(% of total number of jobs or workers)

Job reallocation, 1997-2004 Worker reallocation, 2000-2005

0

5

10

15

20

25

30

35

0

10

20

30

40

50

60

70

Source: forthcoming OECD Employment Outlook, 2009.


• Focusing on the reallocation channel, two interesting questions arise when comparing cross-country productivity performances:– Static efficiency of resource allocation. Is

resource allocation correlated with firm productivity? Have the most efficient firms the largest shares of the market?

– Dynamic efficiency of resource allocation. Do resources move efficiently across heterogeneous firms? Do better firms grow faster?



• The static efficiency issue can be addressed using a decomposition of productivity proposed by Olley and Pakes (2004):

where P is productivity and θ is firm’s market share


i i

iiii

ii PppNPP ))(()/1(__

Simple Average Allocative Efficiency


Differences in allocative efficiency, especially in services

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

FIN BEL PRT FRA ESP ITA SWE GBR

Manufacturing Services

ki

ki

P

OP

Contribution of resource allocation to sectoral MFP levels (Based on Olley-Pakes productivity decomposition)


Evolution of allocative efficiency during the transition -- Eastern Europe, manufacturing(weighted averages of industry level cross terms from OP decomposition)

-0.2 -0.1 0 0.1 0.2 0.3 0.4 0.5

00-01

95-96

98-99

95-96

98-99

95-96

00-01

95-96

92-93

00-01

95-96

Est

onia

Latv

iaR

oman

iaS

love

nia

Hun

gary

cros

s-te

rm o

f OP

dec

ompo

sitio

nA digression: evolution of OP cross term in transition economies


• Focusing on the between/reallocation channel, two interesting questions arise when comparing cross-country productivity performances:– Static efficiency of resource allocation. Is

resource allocation correlated with firm productivity? Have the most efficient firms the largest shares of the market?

– Dynamic efficiency of resource allocation. Do resources move efficiently across heterogeneous firms? Do better firms grow faster?


Stefano Scarpetta, IBM Chair, Labour Market Course-3

-2.5

-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

ESP FRA ITA GBR 54

Different Abilities of Countries to Channel Resources towards More Productive Firms

Least productive

Most productive

Average

Grow

ing fasterG

rowing slow

er

Growth of real value added by productivity quartiles

(relative to average of country/sector/year group)

ESP FRA ITA GBR


The decomposition of productivity growth

• Foster, Haltiwanger and Krizan (2001): in this decomposition, each

term is weighted by beginning of the period market shares as follows:

• the first term is the within component; the second is the between component, the third term is the cross component, while fourth and fifth are the entry and exit component, respectively.

)()(

)(

ktkitXi

kitktitNi

it

Ciititkt

Cikititit

Cikit

t

PpPp

pPppP


Within-firm productivity growth makes the bulk of overall productivity growth

-0.5

0.0

0.5

1.0

1.5

Argentina: 1995-2001. Chi le: 1985-1999. Colombia: 1987-1998. Es tonia: 2000-2001.Finland: 2000-2002. France: 1990-1995. West Germany : 2000-2002. Korea: 1988 & 1993.Latv ia: 2001-2002. Netherlands : 1992-2001. Portugal: 1991-1994. Slovenia: 1997-2001.Taiwan: 1986, 1991 & 1996. UK: 2000-2001. USA: 1992 & 1997.Exc luding Braz il and Venezuela.

Labor Productivity - Five-Year Differencing, Real Gross OutputFHK Decomposition Shares - Manufacturing

Within Between Cross

Entry Ex it Firm Turnover(i )


… but technology matters

-1.5

-1

-.5

0

.5

1

Chile: 1983-1999. Es tonia: 1998-2001.Latv ia: 1999-2002. Romania: 1998-1999.

Labor Productivity - Five-Year Differencing, Real Gross OutputFHK Decomposition Shares - Low Tech Industries

Within BetweenCross Entry

Exit


… but technology matters

-.5

0

.5

1

1.5

Argentin

aChile

Colombia

Es tonia

Finla

nd

France

Korea

Latvia

Netherla

nds

Slovenia

Taiwan UK

USA

Argentina: 1993-2001. Chi le: 1983-1999.Colombia: 1985-1998. Es tonia: 1998-2001. Indones ia: 1993-1995. Latv ia: 1999-2002.Romania: 1998-1999. Slovenia: 1995-2001.

Labor Productivity - Five-Year Differencing, Real Gross Output

FHK Decomposit ion SharesMedium Low, Medium High and High Tech Industries

Within Between

Cross EntryExit


• The main conclusions from this firm-level analysis are:– Within-firm efficiency improvements have been the main driver of

productivity growth in most OECD countries– Aggregate improvements due to reallocation of resources across

sectors and, within each of them across firms have played an important role especially in most dynamic industries, such as ICT-related ones

• Each of these channels of productivity improvements operates in different ways:– Within-firm effects are driven by elimination of slack, technology

adoption and innovation.– Between firm effects are driven by the ability to allocate resources

(i.e. labour and capital) to the most efficient firms or industries– Turnover effects depend on the ability of new firms to enter

markets and experiment as well as on the ability of the economy to get rid of inefficient firms


THE ROLE OF POLICIES AND INSTITUTIONS FOR GOOD LABOUR MARKET PERFORMANCE IBM Chair, Labour Market...

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