PRODUCT MARKET POLICIES, ALLOCATIVE EFFICIENCY AND PRODUCTIVITY

A CROSS-COUNTRY ANALYSIS

Jens Arnold, Giuseppe Nicoletti and Stefano ScarpettaOECD, Paris

Motivation

The long-standing process of economic convergence has come to a halt in the past decade

Because of the acceleration in growth in some of the affluent countries (e.g. the U.S.)…

…and persistent slowdown in many EU and Japan

At the same time, significant effort at policy reform in most countries

With policy convergence in many areas (macro, trade)…

…including in product market regulations2

Stylised Facts: Growth Accounting

GDP p.c. growth 1. Cross-country differences in have been large over the past two decades

2. And many countries have diverged from leading countries more recently

3. Developments in productivity growth are the main source of differences, more specifically:– ICT investment and contribution to productivity– Efficiency in use of inputs and innovation (MFP)

especially in ICT-producing and ICT-using industries– Productivity developments in market services crucial

Productivity Growth and Heterogeneity

• Recent literature has highlighted the importance of heterogeneity of industries and firms within industries

• Productivity developments depend on:

– Sectoral composition of the economy

– Average productivity of firms active in each sector at each point in time

Which in turn depends on:

• Productivity developments within existing firms

• Re-allocation of resources across firms: Entry, exit, differential growth of firms with different productivity

4

Stylised facts: Industry- and Firm-Level

Aggregate productivity growth highest where resources flow most easily to fast growing high productivity firms and industries

–Wide heterogeneity of productivity growth across industries

–ICT-intensive industries have driven aggregate performance over past decade

–Latecomers in ICT adoption may lack a competitive edge vis-à-vis early adopters

–Wide heterogeneity of productivity growth across firms

–Re-allocation of resources across firms with different productivities adds substantially to aggregate productivity growth (Bartelsman et al., 2009)

Industry-level evidence

Firm-level evidence

5

The Role of Regulation

• Extensive theoretical literature on the links between regulations , competition and productivity and output growth (reviews by e.g. Griffith and Harrison, 04; Crafts, 06; OECD

2003).

• Three interrelated channels can be identified:

– The reduction of slack through enhanced competition (e.g. Winston, 93; Vickers, 95, Blanchard, Giavazzi,03)

– Innovation and technology adoption (Poschke, 07; Aghion, Howitt, 98)

– Reallocation of resources (Restuccia, Rogerson, 07; Hsieh, Klenov, 06; Bartelsman et al. 08, 09)

6

Contribution of this paper

• What is the role of competition-enhancing regulatory reforms Product Markets (PMR) for Labor Productivity and Multi Factor Productivity (MFP)?

• And in particular: What is the role of the re-allocation channel for the link between PMR and Productivity?

Firm Heterogeneity is important for predictions

7

Measuring PMR Rigidities• Three main approaches to assess pro-competitive reforms:

– Look at the outcomes − changes in mark-ups; changes in concentration– Look at indicators of the stringency of regulations– Surveys of firms or experts

• We focus on regulatory indicators– Measure the degree to which policies promote or inhibit competition– Bottom-up approach based on detailed regulatory data

• Two primary sets of indicators:– The indicator of non-manufacturing regulation (NMR):

• Cover many non-manufacturing sectors (network industries, trade, business services)• Uses information on state control and regulations affecting entry & conduct• Focus here is mainly on entry barriers

– The indicators of Regulation Impact (RI)• Derived from NMR indicators• Cover 39 ISIC sectors in 21 OECD countries from 1975 to 2003

8

Recent Trends in PM Rigidities • Evidence on all OECD measures suggests extensive liberalisation of PM over

past two decades

• But at very different pace and depth across countries

• Cross-country dispersion in PM rigidities increased precisely at the time of the ICT shock

• Convergence towards liberal markets accelerated over past decade

• But many laggard countries liberalised only quite recently (e.g. continental Europe)

• In many of these countries crucial ICT-using sectors remain heavily burdened by regulation (e.g. retail and business services)

• Cross-border service trade still hampered by explicit barriers and heterogeneous service regulations

• Lack of integrated EU market for services an issue --> EU firms enjoying less economies of scale and scope than US ones

9

Data used in the Analysis

• Industry-level data:– OECD Structural Analytical database (STAN)

– EU Klems data base, March 2007 release

• Firm-level data:– Amadeus data base by commercial provider BvD

– Used a random sampling technique to match the sample distribution to the population weights with respect to

• Sector composition

• Firm size groups

10

Regulations and Productivity: Evidence at the Industry-level

11

• Growing evidence based on a neo-Schumpeterian model– industry productivity depends on growth at the frontier; catch up to the

frontier (e.g. Aghion and Howitt, 2006)

• Evidence suggests a link between regulation and productivity• Nicoletti , Scarpetta 03; Conway et al. 06; Griffith et al. 06; Aghion,

Griffith, 06)

• Nicoletti and Scarpetta, 2003 and Conway et al, 2006 also found an indirect effect whereby regulation curbs catch-up process

• A recent study using EU-KLEMS found an effect in specific ICT industries – e.g. Post and Telecoms (Inklaar et al. 2008)

• Studies have used different data sets (OECD STAN, EUKLEMS) and different measures of regulation

• There is also empirical evidence on indirect channels to productivity via openness to foreign entry (Arnold et al., 2006)

A First Look at Industry-Level DataDistribution of productivity growth across country groups

0

1 0

2 0

3 0

- .0 5 0 .0 5 .1

DEU ESP FRA ITA G BR I RL U SA 4 Continental European Countries

vs.

3 English-speaking countries

Labour productivity growth purged of country, industry and period means, based on EU KLEMS.

A Correlation with Regulation?Distribution of productivity growth by strength of regulatory impact

0

1 0

2 0

3 0

4 0

-.05 0 .0 5

Hi gh re gu la t io n L o w re gu la ti o n

Labour productivity growth purged of country, industry and period means, based on EU KLEMS.

ICT vs. Non-ICT Industries

0

10

20

30

40

-.05 0 .05

High regulation Low regulation

0

10

20

30

40

-.05 0 .05

High regulation Low regulation

ICT Industries Non-ICT Industries

Labour productivity growth purged of country, industry and period means, based on EU KLEMS.

Productivity dispersion across firms

France

Electrical and optical equipment Telecommunications

Much of the increase in dispersion comes from top performers.

25th %ile

75th %ile

95th %ile

5th %ile

ICT-producing

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.

Productivity dispersion across firmsICT-producing

United Kingdom

Electrical and optical equipment Telecommunications

Productivity dispersion across firmsICT-using: retail distribution

France United Kingdom

Firms within Industries: How well do economies allocate resources across firms?

• Static view: Is resource allocation correlated with firm productivity?

Olley-Pakes productivity decomposition:

• Dynamic view: Do resources move efficiently across heterogeneous firms?

Do better firms grow faster?

∑ ∑ −−+=i i

iii PppNP ))(()/1(__

θθ

Simple Average Allocative Efficiency

18

Wide 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

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

19

A digression: evolution of OP cross term in transition economies

20

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

deco

mpo

sitio

n

Hungary: allocative efficiency over the transition(cross-term of the Olley Pakes decomposition, manufacturing)

6.5

7

7.5

8

8.5

9

1995 1996 1997 1998 1999 2000 2001-0.1

-0.05

0

0.05

0.1

0.15

0.2

0.25

total L productivity un-weighted L productivity Cross term (right scale)

Slovenia: allocative efficiency over the transition(cross-term of the Olley Pakes decomposition, manufacturing)

6.5

7

7.5

8

8.5

9

9.5

1993 1994 1995 1996 1997 1998 1999 2000 2001-0.2

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

total L productivity un-weighted L productivity Cross term (right scale)21

A Link to Regulation ?

-0.36 ** 0.34 -0.28 * -0.67 *** -0.41 *(0.15) (0.64) (0.15) (0.16) (0.24)0.016 0.595 0.072 0 0.092

Country-year FE Yes Yes Yes Yes YesIndustry FE Yes Yes Yes Yes Yes

N 849 629 220 242 607R2 0.20 0.20 0.36 0.36 0.18

Regulation Impact Indicator

Standard Errors in parentheses. *, **, *** indicate statistical significance at the 10, 5 and 1 percent levels, respectively. Agriculture, forestry, fishing, mining are excluded, as are public administration, education and health sectors.

Services only

Manufacturing only

Business Sector

Non-ICT using sectors

ICT using sectors

• Anti-competitive regulation reduces the allocative efficiency

• Effect is significant in services industries, and particularly in ICT-using industries

22

• Static view: Is resource allocation correlated with firm productivity?

Olley-Pakes productivity decomposition:

• Dynamic view: Do resources move efficiently across heterogeneous firms?

Do better firms grow faster?

∑ ∑ −−+=i i

iii PppNP ))(()/1(__

θθ

Simple Average Allocative Efficiency

Firms within Industries: How well do economies allocate resources across firms?

23

Different Abilities of Countries to Channel Resources towards More Productive Firms

‐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 

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

24

What’s happening to Firm Productivity?

• Explain MFP at the firm-level

(analysis hence based on incumbent firms)

• Adopt a neo-Schumpeterian growth framework:

• MFP at the firm level is an autoregressive distributed lag (ADL(1,1) process in which the level of MFP is co-integrated with the level of MFP of the frontier firms (F)

(Setup similar to Griffith et al. 2006)

icstctscstFcstFcsticsticst regulationAAAA εγγαααα ++++++= −−− 1312110 lnlnlnln

25

Some Possible Channels

• In which sectors are firms most affected? – Distinguish between ICT using sectors and others

• Which firms are most affected?– Distinguish between firms that are catching up to the

technology frontier and those that are not

– Further isolate high-performing firms that are catching up to the technology frontier

( ) icstctscsttFcs

ticsFcsticst regulation

AA

AA εγγααα ++++⎟⎟⎠

⎞⎜⎜⎝

⎛−−∆=∆ −

−

−13

1,

1,01 ln1lnln

Growth of frontier

Catch-up Product Market Regulation

26

Regulation and MFP at Firm Level

Leader Growth 0.19 *** 0.15 *** 0.26 *** 0.49 *** 0.70 ***0 0 0 0 0

Gap to the Leader -0.17 *** -0.16 *** -0.20 *** -0.09 *** -0.27 ***0 0 0 0 0

PMR -0.03 -0.09 ** -0.040.47 0.02 0.68 1 0.092

Catch-up firms: PMR -0.14 ***0.072 0

Non-catch-up firms: PMR -0.040.072 0.37

Dummy for catch-up firms 0.24 ***0.072 0

Catch-up firms close to -0.03 **0.072 0.03

Catch-up firms far from 0.000.072 0.87

Dummy for close to frontier 0.13 ***0.072 0

Country-year FE

N 173137 83654 89483 83654 72979R2 0.12 0.12 0.14 0.45 0.39

Non-ICT using sectors

ICT using sectors

Business Sector

Distinguishing top performers

Distinguishing catch-up firms

All regressions include fixed effects for country*year combinations and for industries.

Firm-level Regression Results

1. Anti-competitive regulation hampers TFP growth of firms in ICT-using sectors

2. Fast-growing firms in these sectors are particularly affected

3. High-performing enterprises suffer the most (àla Aghion et al. 04; 05 but cross-country)

4. Sensitivity analysis confirms these findings– Different MFP measures (OLS, Levinsohn Petrin, 03)

– Broader set of policy & institutional factors (LM, F development)

– Caveat: Future work will need to control for possible endogeneity of frontier growth 28

Concluding Remarks• Differences in investment in ICT and MFP growth in both ICT-

producing and, increasingly, ICT-using industries underpin growing disparities in growth across OECD countries

• Many EU countries have been hesitant in reforming key ICT sectors

• Delaying reforms not only reduced the scope of the creative destruction process but also weakened the incentives for adopting ICT capital

• In turn, slower productivity improvements in ICT-using services propagated to other sectors through higher prices and lower product quality

• More work is required to shed further light on the process of resource reallocation and firm-level productivity

29

Thank you.

30

AnnexFigures, tables and details

-2 -1 0 1 2 3 4 5 6

IRL

LUX

PRT

ESP

JPN

NLD

GBR

ITA

USA

BEL

AUS

FIN

DNK

FRA

DEU

SWE

GRC

CAN

GDP per capita growth

Contributions to GDP per capita growth from trend changes in:GDP trended per hours workedTotal hours/working-age populationWorking-age population/total population

1986-1995 1995-2006

-2 -1 0 1 2 3 4 5 6

IRL

LUX

GRC

FIN

ESP

GBR

SWE

AUS

NLD

CAN

PRT

USA

BEL

DNK

FRA

DEU

JPN

ITA

Decomposition of GDP per capita growth

Catch-up and convergence in OECD income levels, 1995-2006, relative to the United States

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 10

Gap in GDP per capita (%), 1994

Gap

in a

vera

ge g

row

th ra

te (%

) 199

5-20

06

Convergence zone

Divergence zone

Australia

Contribution of ICT capital to GDP growth, 1985-2006 and 2001-2006 (or closest year available)

percentage points

‐0.1%

0.0%

0.1%

0.2%

0.3%

0.4%

0.5%

0.6%

0.7%

0.8%2001‐2006 1985‐2006

Hourly productivity growth and its components

1985-2006

‐1.0%

‐0.5%

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

4.0%

contribution  of capital deepening MFP growth

Labour productivity growth

Productivity growth in total market servicesValue added per person employed , percentage change at annual rate

‐3

‐2

‐1

0

1

2

3

4% 2000‐2005 1995‐2000

Liberalisation in energy, transport and telecoms

0

1

2

3

4

5

6

Average regulation: EU countries

Average regulation: Non-EU OECD

1980 20032000199519901985

Dispersion of regulation: Non-EU OECD countries

Dispersion of regulation: EU

Burden of non-manufacturing regulationmanufacturing (norm)

00,10,20,30,40,50,60,70,80,9

Sweden

Netherland

s

Denmark

Ireland

Australia

United Stat

es

Finland

United Kingdom

New Zealand

Canada

Switzerla

ndSpain

Greece

Portugal

France

Norway

BelgiumJa

pan

Germany

Italy

Austria

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1

Irelan

dNeth

erlan

dsNew

Zeala

nd

Sweden

Denmar

kUnit

ed K

ingdo

m

Switzer

land

United

Stat

es

Austra

lia

Finlan

d

Fran

ce

Belgium

Canad

a

German

y

Spain

Portu

gal

Norway

Japa

n

Italy

Greec

e

Austri

a

ict producing ict using non-ict

ICT sectors contribute increasingly to labour productivity growth, 1990-04

-0,5

0,0

0,5

1,0

1,5

2,0

2,5

3,0

3,5

Irela

nd

Finl

and

US

A

UK

Sw

eden

Japa

n

Aus

tria

Den

mar

k

Ger

man

y

Fran

ce

Italy

Spa

in

Bel

gium

Net

herla

Por

tuga

l

ICT-producing ICT-using Non-ICT intensive Residual

90-95

96-04

Productivity dispersion across firms

FFrance

Electrical and optical equipment Telecommunications

Much of the increase in dispersion comes from top performers.

25th %ile

75th %ile

95th %ile

5th %ile

ICT-producing

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.

Productivity dispersion across firmsICT-producing

UUnited Kingdom

Electrical and optical equipment Telecommunications

Productivity dispersion across firmsICT-using: retail distribution

France United Kingdom

Regulation and productivity acceleration are negatively correlated

Australia

Austria

Belgium

Canada

Denmark

Finland France

Germany

Greece

Ireland

Italy

Japan

NetherlandsNew Zealand

Norway

PortugalSpain

Sweden

Switzerland

United Kingdom

United States

‐2.5

‐2.0

‐1.5

‐1.0

‐0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0

Regulation  in non‐manufacturing  sectors, 1980‐95 average

Correlation coefficient=‐0.4t‐statistic=‐1.91without Greece:Correlation coefficient=‐0.74t‐statistic=‐4.62A

nnual average

 percentage point acceleration

 in 

labour productivity grow

th 1996‐2005

 vs 1985

‐1995

– Productivity dispersion is related to PMR

– ICT-intensive sectors tend to have higher dispersion with fatter right tail (the gazelles) driving aggregate performance

44