productivity isn't everything, but in the long run it is almost … · 2019-12-12 · policies...

THE FUTURE OF PRODUCTIVITY

Christian Kastrop, Dan Andrews Policy Studies Branch, Economics Department OECD

… productivity isn't everything, but in the long run it is almost everything. Paul Krugman, 1994

New book:

out now!

Available at:

http://www.oecd.org/economy/the

-future-of-productivity.htm

Book + 5 page policy note +

technical paper + videos

Authors:

Muge Adalet McGowan

Dan Andrews

Chiara Criscuolo

Giuseppe Nicoletti

• Productivity: now more than ever

• Productivity: what’s wrong?

– Broken diffusion machine

– Misallocated resources

• Productivity: role of policy

• Productivity: what’s next?

Roadmap

I. Productivity: now more than ever

Differences in GDP per capita mostly

reflect labour productivity gaps

Productivity isn’t everything but in the long run its almost everything – Paul Krugman (1994)

Weak labour productivity underpins

the collapse in OECD potential growth Contribution to potential per capita output growth (% pts unless otherwise noted)

Source: OECD Economic Outlook 2016, Volume 1.

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

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

Business dynamism declined raising

concerns of a structural slowing Investment in Knowledge-Based Capital

Annual average growth

Productivity and innovation more than

jobs will be the key driver of growth

Ageing populations reduce scope to grow through an increasing labour force

Innovation and technology spillovers will increasingly drive growth

Increasing education and skills of workers will be key

Allocating resources to high productivity firms and matching skills to jobs will also be crucial 8

II. Productivity: what’s wrong?

• Widespread heterogeneity in firm performance

means we need to look beyond averages firm

level perspective is crucial.

• In a well-functioning economy, ideally:

1. Global frontier firms innovate and these technologies diffuse to other firms, raising within-firm productivity

2. Efficient reallocation to underpin the growth of productive firms, via the downsizing and exit of less productive firms

• But this doesn’t always happen, partly due to policy

weakness.

What drives productivity growth?

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

The breakdown of the diffusion

machine

Source: Andrews, D. C. Criscuolo and P. Gal (2016), “The Global Productivity Slowdown, Technology Divergence

and Public Policy: a Firm Level Perspective”, forthcoming.

Frontier

Frontier

Laggards Laggards

• Four structural factors can enable diffusion:

1. Global connections: trade, FDI, participating in GVCs, international mobility of skilled workers

2. Investments in knowledge based capital – R&D, managerial capital

3. Efficient allocation of resources, especially skills

4. Appetite for risk and experimentation

• Each factor is connected to competitive pressure in some way.

• Countries differ significantly in terms of these structural factors

What drives diffusion?

• OECD projections show a slowing in human

capital accumulation over coming decades

maximising human talent and its efficient use in

the workplace will be key.

• BUT the allocation of human talent in OECD

countries is far from perfect:

– Skill mismatch affects ¼ workers in the OECD

countries, with significant costs to productivity.

Maximising human talent is key

Skill mismatch as a constraint on

labour productivity

Source: Adalet McGowan, M and D. Andrews (2015), “Labour market mismatch and labour productivity:

evidence from PIAAC data ” OECD Economics Department Working Paper, No. 1209.

Skill mismatch, particularly over-skilling, is harmful for productivity because it constrains the ability of innovative firms to attract skilled workers and grow

III. Productivity: role of policy

Three areas for policy:

1. Pushing out the global frontier

2. Reviving the diffusion machine

3. More efficient resource allocation,

especially skills.

Note: #2 partly depends on getting #3 right

How to revive productivity growth?

• Key insight: firms at the global frontier are more likely to part of an MNE group and patent than other firms.

• Higher and more efficient public investment in basic research.

– Role for international co-operation wrt innovation an tax policy?

• Enabling experimentation of firms with new technologies and business models.

– Reduce barriers to firm entry and exit to enable high productivity firms to grow and low productivity firms to exit.

Pushing the frontier: keep the

innovation engine running

Policies shape the diffusion of new

innovations from the global frontier Estimated frontier spillover (% pa) associated with a 2% point increase in MFP

growth at the global productivity frontier

Source: Saia, A., D. Andrews and S. Albrizio (2015), “Public Policy and Spillovers From the Global Productivity Frontier: Industry Level Evidence”, OECD Economics Department Working Papers, No, 1238.

Entry and Exit Innovation policies

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

amplified the breakdown in diffusion Estimated contribution to the annual change in the MFP gap of the

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

Source: Andrews, D. C. Criscuolo and P. Gal (2016), “The Global Productivity Slowdown, Technology Divergence

and Public Policy: a Firm Level Perspective”, forthcoming.

Maximum

Maximum

Maximum

Maximum

Maximum

Maximum Maximum

Maximum

MaximumMaximum

Minimum

Minimum

Minimum

Minimum

MinimumMinimum

Minimum

Minimum

Minimum

Minimum

Minimum

MinimumMaximum

Maximum

(POL)

(DEU)

(FRA)

(ITA)

(BEL)

(SWE) (AUT)

(SVK)

(NLD )(AUT)

(ITA)

(ITA)

(NLD )

(USA)

(CAN)(NOR)

(DNK)

(FIN)

(CAN)

(KOR)

(USA)

(KOR)(DNK)

(FIN)

0.14

0.18

0.22

0.26

0.30

0.34

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Framework policies Housing policies Other policies

BelgiumProbability of mismatch

Skill misallocation is policy-induced

Source: Adalet McGowan, M and D. Andrews (2015), “Skill mismatch and public policy in OECD countries”

OECD Economics Department Working Paper, No. 1210.

IV. Productivity: what’s next?

• Zombie” firms and capital misallocation

– What is the role for policy-induced exit costs?

Some conjectures and future work

The rise of “zombie” firms

The share of financially weak incumbent firms over time

Firms which cannot cover their interest payments over three consecutive years

Source: Adalet McGowan, M., D. Andrews and V. Millot (2016), “The Walking Dead? Zombie Firms and

Productivity Performance in OECD countries”, OECD Economics Department Working Paper forthcoming.

Zombies congest markets and

reduce investment of healthy firms Investment and employment loss of a typical non-zombie

firm due to a rise in the zombie share after 2007

Source: Adalet McGowan, M., D. Andrews and V. Millot (2016), “The Walking Dead? Zombie Firms and

Productivity Performance in OECD countries”, OECD Economics Department Working Paper forthcoming.

-2

-1

0

1

2

3

4

5

6

7

FIN ITA ESP SWE BEL Average KOR FRA SVN GBR

Cumulative lost investment Cumulative lost employment%

• Zombie” firms and capital misallocation

– What is the role for policy-induced exit costs?

• The OECD Global Forum on Productivity.

Some conjectures and future work

Spares

A1-A3. More of skills

A1. Skill mismatch: combining self-

assessment with skill proficiency Use micro-data from OECD Survey of Adult Skills (PIAAC) to:

1. Create a quantitative scale of the skills required to perform

the job for each occupation using the literacy scores of

well-matched workers – those who neither feel they have

the skills to perform a more demanding job nor require

further training to perform their current job satisfactorily.

2. Use this scale to identify min and max threshold values

(e.g., based on the 10th and 90th percentile), which bounds

what it is to be a well-matched worker.

3. Workers with scores lower (higher) than this min (max)

threshold in their occupation are under (over) skilled.

A2. Over-skilling more prevalent than

under-skilling Percentage of workers with skill mismatch

On average, over-skilling is ~2½ times more likely than under-skilling

Source: Adalet McGowan, M and D. Andrews (2015), “Labour market mismatch and labour productivity:

evidence from PIAAC data ” OECD Economics Department Working Paper, No. 1209.

A3. Qualification mismatch

Percentage of workers with qualification mismatch

Source: Adalet McGowan, M and D. Andrews (2015), “Labour market mismatch and labour productivity:

evidence from PIAAC data ” OECD Economics Department Working Paper, No. 1209.

A4. Skill mismatch is symptomatic of

more general misallocation

Source: Andrews, D. C. Criscuolo and P. Gal (2015), “Frontier firms, technology diffusion and public policy: micro evidence from OECD countries”, OECD Productivity Working Papers No. 2.

How much higher would overall manufacturing sector labour productivity

be if NF firms were as productive and large as GF firms?

NF firms in Italy have productivity levels close to the GF but they are relatively small

… partly because scarce resources are trapped in many small and old firms

A5. MFP divergence 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

Source: Andrews, D. C. Criscuolo and P. Gal (2016), “The Global Productivity Slowdown, Technology Divergence

and Public Policy: a Firm Level Perspective”, forthcoming.

Frontier

Frontier

Laggards

Laggards