THE GLOBAL PRODUCTIVITY

SLOWDOWN, TECHNOLOGY

DIVERGENCE AND PUBLIC

POLICY:

A FIRM-LEVEL PERSPECTIVE

Dan Andrews *

Chiara Criscuolo +

Peter Gal *

*Economics Department +Directorate for Science, Technology and Innovation

Differences in GDP per capita mostly

reflect labour productivity gaps Percentage differences compared with the upper half of OECD countries, 2013

Source: OECD Going for Growth Database.

Weak productivity underpins the

collapse in OECD potential growth Contribution to potential per capita output growth

Source: OECD Economic Outlook 2016, Volume 1.

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1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Capital per worker MFP

Potential employment rate Active population rate

Potential per capita growth (%)

Pre-crisis: MFP story Post-crisis: K story

Optimists:

• Brynjolfsson

• McAfee

• Mokyr

• Jovanovic

• …

The slowdown has ignited a

spirited debate about prospects…

Pessimists:

• Gordon

• Cowen

• Thiel

• Fernald

• …

1. Technological factors

– Adoption and diffusion of general purpose technologies (Griliches, 1957; David, 1991; Jovanovic and Rousseau, 2005)

– A “return to normal” after a decade of exceptional IT-fueled gains (Fernald, 2014)

2. Rising resource misallocation (Gopinath et al., 2015)

3. Cyclical factors

– Demand conditions and monetary policy (Anzoategui et al., 2016)

– Weak credit post crisis (Riley, Bondibene and Young, 2015)

4. Measurement (Byrne, et al., 2016; Syverson, 2016)

Why did aggregate productivity

growth slowdown?

• The debate (e.g. Gordon vs Brynjolfsson) has centred on innovation prospects at the global frontier (GF) but we know little about GF firms.

• Our firm level analysis suggests:

1. Labour productivity (LP) at GF remained robust but laggard firms increasingly fell behind.

2. LP divergence reflects MFP divergence and possibly technological divergence, broadly defined

3. Some explanations: “winner takes all” dynamics; stalling diffusion; decline in market dynamism and increase in misallocation

4. Policy weakness potentially amplified MFP divergence and the productivity slowdown

Our contribution: bring more micro

evidence to a largely macro debate

1. Conceptual background

2. Data and measurement

3. Productivity divergence

4. Policy analysis: role of competition

5. Future research

Outline

CONCEPTUAL BACKGROUND

• Widespread heterogeneity in firm productivity (Bartelsman and Doms, 2000)

need to look beyond averages / aggregates

1. Neo-Schumpeterian growth (Aghion and Howitt, 2006)

a) The best (“global frontier”) firms innovate

b) These technologies diffuse to other firms

This raises within-firm productivity through catching-up

2. Reallocation via growth of productive firms and the

downsizing / exit of less productive ones (Caballero and Hammour, 1994)

Conceptual background:

What drives productivity growth?

DATA AND MEASUREMENT

Data Cross-country firm-level data Orbis

• Wide coverage

• 24 OECD countries, 1997-2014

• Both manufacturing and services

• Large and small firms

• Balance sheets and income statements

from several million company accounts • Collected and harmonized by Bureau van Dijk

• Main limitation:

• Coverage of (small) firms uneven

20+ employees subsample

Extensive robustness checks

Measurement

• Substantial work to translate balance sheet information to

economic measures • Deflation, PPP conversion, capital stock estimation, cleaning

• Several productivity measures derived • Labour-productivity, MFP variants

• Definition of global productivity frontier:

Firms with highest levels of productivity

• More precisely: top 5% of firms in terms of productivity for

each 2-digit industry

PRODUCTIVITY DIVERGENCE:

THE BEST VS THE REST

The global frontier: Who are they?

• Frontier firms have more / larger • market shares

• capital intensity

• wages

• mark-ups

• patents

• share of MNEs

• Productivity gap is also higher in services

• Frontier is composed of various countries

… and more so in services than in manufacturing

Laggards

Frontier

Laggards

Rising labour productivity gap

between global frontier and laggards Average of labour productivity across each 2-digit sector (log, 2001=0)

Frontier

Average of MFPR (Wooldridge) across each 2-digit sector (log, 2001=0)

... largely reflects MFPR divergence

Frontier

Frontier

Laggards Laggards

Capital deepening plays

less of a role

... which may reflect “technological”

divergence Average of mark-up adjusted MFPR across each 2-digit sector (log, 2001=0)

Divergence remains after correcting

for mark-ups behaviour

Frontier

Frontier

Laggards

Laggards

Robust to:

• Different MFP measures and mark-up corrections

• Frontier definitions (Top 100, Top 10%)

• More sustained performance (3-year averages of productivity)

• More narrowly defined industries (3 and 4 digit)

• Retaining only groups and standalone firms

• Comparing frontier with official industry aggregates

• Longer period using industry-level data: increased divergence from the early 2000s compared to 1985-2000

Consistent with others’ findings:

• For the US using Census data (Decker et al, 2016)

and for financial returns (Furman and Orszag, 2016)

• MultiProd (Berlingieri et al, 2016)

• CompNet (ECB, 2016)

Productivity divergence…

Firm-level patterns consistent with

sectoral data

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Frontier firms

Laggard firms

Sectoral data

Average of labour productivity across each 2-digit sector (log, 2001=0)

PRODUCTIVITY DIVERGENCE:

STRUCTURAL DRIVERS

What does it mean? • Best provider takes most of the market

• Second-best takes significantly less

Proximate drivers?

• Very low marginal costs easier scalability (Brynjolfsson and McAfee, 2011)

– Both production / provision and transport / communication costs

• Network effects across consumers

• Larger markets increase incentives to innovate (Acemoglu and Lynn, 2004)

Structural drivers?

• Digitalization + rise of intangibles + globalization

How do we spot it?

• Look at sectors where these are most relevant: ICT services

Winner-takes-all dynamics?

Technological divergence:

winner takes all dynamics?

MFP divergence

ICT-intensive services

Non ICT-intensive services

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Frontier firms

Laggards

Top 10%

Top 2%

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Frontier firms

Laggards

Top 10%

Top 2%

Technological divergence:

winner takes all dynamics?

Sales divergence: growing market shares

ICT-intensive services

Non ICT-intensive services

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Frontier firms

Laggards

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Frontier firms

Laggards

Stronger MFPR divergence –

weaker aggregate MFP Industry aggregate MFP and within-industry MFPR gap (1998-2007)

Data averaged across 12 OECD countries and purged of industry and year fixed effects

The speed of convergence to the

frontier slowed, even before the crisis Convergence parameters estimated from a neo-Schumpeterian model

Dotted line: 95% confidence intervals

A: MFPR B: Mark-up adjusted MFPR

icstcts

j

isct

j

jj

ticst

j

j

icstFcsticst XDgapgapAA 413121 *lnln

Entry to the frontier has become more

entrenched amongst top firms

A: MFPR

B: Mark-up corrected MFPR

Manufacturing Services

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Manufacturing Services

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Proportion of frontier firms in time t according to their frontier status in t-2

Technological divergence: is declining

market contestability an issue? Share of firms

Percent

Entry rates using

business registers from DynEmp

Declining firm turnover: fewer

young firms, while marginal firms

increasingly survive.

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24

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Young firms (0-5 years)

Mature firms (6-10 years)

Non-viable old firms (older than 10 years)

Decline in entry is widespread

across countries

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1998-2000 2001-04 2005-08 2009-13

Technological divergence: is declining

market contestability an issue? Share of firms

Percent

MFPR relative to viable old firms Log point differential

Higher productivity threshold for

entry, while marginal firms survive

despite a collapse in their MFPR

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2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Young firms (0-5 years)

Mature firms (6-10 years)

Non-viable old firms (older than 10 years)

Declining firm turnover: fewer

young firms, while marginal firms

increasingly survive.

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8

12

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24

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Young firms (0-5 years)

Mature firms (6-10 years)

Non-viable old firms (older than 10 years)

PRODUCTIVITY DIVERGENCE:

ROLE OF POLICY

Pro-competitive product market reforms can promote the

diffusion of frontier technologies by:

1. Sharpening the incentives for incumbent firms to adopt

better technologies.

2. Raising managerial quality, which is complementary to

adoption.

3. Reducing entry barriers: young firms possess a

comparative advantage in commercialising leading

technologies.

4. Raising returns to “innovation” in downstream

manufacturing sectors via input-output linkages.

5. More efficient resource reallocation.

Competition, innovation and

diffusion

The pace of deregulation in

services has slowed

The restrictiveness of product market regulations

Notes: The horizontal line in the boxes represents the median, the upper and lower edges of each boxes reflect the 25th and

75th percentiles and the markers on the extremes denote the maximum and the minimum across countries.

A: Network industries B: Professional Services

Slower product market reform:

a larger increase in the gap

Selected industries; annual average change over time and across countries

Note: The figure shows the annual change in the (log) MFPR gap between the frontier and laggard firms and

the change in the (log) PMR indicator. Technical services refer to architecture and engineering.

Higher MFP divergence when

market reforms in services lagged

(1) (2) (3) (4)

0.205*** 0.231*** 0.332*** 0.311**

(0.065) (0.083) (0.103) (0.132)

Country fixed effects YES NO YES NO

Industry fixed effects YES YES YES YES

Year fixed effects YES NO YES NO

Country X year fixed effects NO YES NO YES

Observations 458 458 376 376

R-squared 0.201 0.323 0.327 0.463

Y: Δ MFP gap Y: Δ Mark-up corrected MFP gap

Δ Product Market

Regulations,c,t

Notes: Cluster robust standard errors (at the industry-year level) in parentheses. *** p<0.01, ** p<0.05, * p<0.1 Both the

MFP gap and the PMR indicator are measured in log terms. The MFP gap is calculated at the country-industry-year level,

by taking the difference between the global frontier and the average of log productivity of non-frontier firms.

MFP divergence and product market regulation in services

Estimation method: five-year long differences (1998-2013)

tcstsctcs

ld

tcs

ld

tcs

ld EPMRMFPgap ,,,,2,,10,,

2.3% 2.3% 2.4%

3.8% 3.9%

1.7%

1.0%1.4%

1.7% 1.7%

0%

1%

2%

3%

4%

5%

Transport Energy Retail Legal andaccounting

services

Technicalservices

Observed increase in gap

Increase in gap due to slow deregulation

Sluggish market reform effort in

services amplified MFP divergence Estimated contribution to the annual change in the MFP gap of the

slower pace of reform relative to the fastest reforming industry (telecoms)

MFP divergence was perhaps inevitable due to structural changes in the

global economy but policy could have worked harder

• The slowdown in aggregate productivity growth

masks an increasing divergence between GF

and laggard firms:

– Structural trends in the global economy unleashed

winner takes all dynamics and made adoption more

difficult.

– Thus, MFP divergence was partly inevitable but the

policy framework didn’t sufficiently adapt to these

structural trends

– Evidence of declining market contestability is a real

worry

Summary

• “Zombie” firms and firm exit in ECO

– The prevalence and resources trapped in marginal firms has risen, with adverse effects for investment, capital reallocation (MFP) and potential growth. “The Walking Dead”

– Insolvency regimes and productivity performance

• Distributed microdata projects in STI

– DynEmp (23 countries):

• New evidence on the growth dynamics of start-ups and incumbents and its link to productivity

– MultiProd (18 countries):

• Investigates productivity patterns and the extent to which different policy frameworks can shape productivity

• Productivity heterogeneity and Misallocation

• Granularity

• Wage inequality: “The Great Divergence(s)”

Ongoing work

• Future work

– Complementary factors (e.g. management, skills)

– The role of digitalisation

– Antitrust regulation need to be strengthened?

– Lobbying blocking penetration of ICT and new

business models in services

– Intellectual property regimes need updating?

Areas for future work

THANK YOU