productivity isn't everything, but in the long run it is almost … · 2019-12-12 · Policies...
Transcript of productivity isn't everything, but in the long run it is almost … · 2019-12-12 · Policies...
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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
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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
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• Productivity: now more than ever
• Productivity: what’s wrong?
– Broken diffusion machine
– Misallocated resources
• Productivity: role of policy
• Productivity: what’s next?
Roadmap
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I. Productivity: now more than ever
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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)
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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
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1.0
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2.0
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-0.5
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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
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Business dynamism declined raising
concerns of a structural slowing Investment in Knowledge-Based Capital
Annual average growth
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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
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II. Productivity: what’s wrong?
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• 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?
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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
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• 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?
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• 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
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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
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III. Productivity: role of policy
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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?
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• 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
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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
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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.
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Maximum
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MaximumMaximum
Minimum
Minimum
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Minimum
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MinimumMaximum
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(POL)
(DEU)
(FRA)
(ITA)
(BEL)
(SWE) (AUT)
(SVK)
(NLD )(AUT)
(ITA)
(ITA)
(NLD )
(USA)
(CAN)(NOR)
(DNK)
(FIN)
(CAN)
(KOR)
(USA)
(KOR)(DNK)
(FIN)
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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.
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IV. Productivity: what’s next?
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• Zombie” firms and capital misallocation
– What is the role for policy-induced exit costs?
Some conjectures and future work
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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.
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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
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FIN ITA ESP SWE BEL Average KOR FRA SVN GBR
Cumulative lost investment Cumulative lost employment%
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• 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
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Spares
A1-A3. More of skills
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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.
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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.
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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.
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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
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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