The Walking Dead Zombie Firms and Productivity Performance in OECD Countries

1. THE WALKING DEAD? ZOMBIE
FIRMS AND PRODUCTIVITY
PERFORMANCE IN OECD
COUNTRIES
Dan Andrews
Deputy Head of Structural Policy Analysis Division,
OECD Economics Department
with Müge Adalet McGowan and Valentine Millot
http://www.oecd.org/eco/The-Walking-Dead-Zombie-Firms-
and-Productivity-Performance-in-OECD-Countries.pdf

2. 2. Are weak firms stifling
productivity growth?
5. Can we improve the
design of exit policies?
October 2016 October 2017
Exit Policies and Productivity
Growth
4. Can we improve the
measurement of exit
policies?
March 2016
1. How do we think about the exit margin,
productivity and policy?
3. What happens to the
workers when firms exit?
October 2016 April 2016 - March 2017
Coping with
Creative
Destruction:
Reducing the
Costs of Firm
Exit Policies and
Productivity
Growth: a
Framework for
Analysis
New cross-
country policy
indicators of
insolvency
regimes
The Walking
Dead?: Zombie
Firms and
Productivity
Performance in
OECD countries
New empirical
evidence of exit
policies and
productivity
growth

3. Background: Why are we worried?
Contributions to potential output per capita growth
(dY*) in the OECD
Source: OECD June 2016 Economic Outlook database; OECD calculations.
Collapse in dY* due to slowing
labour productivity (LP)
 Pre-crisis: MFP story
 Post-crisis: Capital story
Fears of structural slowing in LP
and that the legacy of the crisis
may permanently scar on dY*
Worst case scenario? The
emergence of “zombie firms”,
which depress investment and
reallocation patterns.
A lost decade? How likely is a
full-blown Japan-style scenario?

4. Zombie firms are a hot issue in the
press but do they really matter?
Why we haven’t dismissed it outright:
1. Policy conditions are conducive
in some countries:
 Impaired banking sectors, ultra
loose monetary policy
 Crisis-induced SME support not
yet withdrawn
 Weak insolvency regimes +
waning structural reform ambition
2. Micro-data evidence that the
efficiency of the exit margin
may be declining.
“Zombie” firms – much ado about
nothing?

5. TROUBLE ON THE EXIT MARGIN?:
SMOKING GUNS FROM MICRO-
DATA

6. Average of MFPR (Wooldridge) across each 2-digit sector (log, 2001=0)
Productivity dispersion is rising
Source: Andrews, D. C. Criscuolo and P. Gal (2016), “The Best versus the Rest: The Global Productivity Slowdown,
Divergence across Firms and the Role of Public Policy”, OECD Productivity Working Papers, No. 5.
Frontier
Frontier
Laggards Laggards

7. 5
6
7
8
9
10
11
12
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Spain Italy Other
But productivity-enhancing
reallocation is declining
Difference in capital growth between high and low productivity firms (%pts)
Source: Adalet McGowan, M., D. Andrews and V. Millot (2017), “The Walking Dead? Zombie Firms and
Productivity Performance in OECD countries”, OECD Economics Department Working Paper No. 1372.
Over time, it has become less likely that high productivity firms
expand and low productivity firms contract.

8. -0.6
-0.5
-0.4
-0.3
-0.2
-0.1
0.0
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)
0
4
8
12
16
20
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)
Rising entry barriers and declining
market contestability
Share of firms
Percent; average across 24 countries
MFPR relative to viable old firms
Log point differential
Higher MFP entry threshold,
marginal firms survive with ↓MFP
Fewer young firms, marginal firms
increasingly survive.
Source: Andrews, D. C. Criscuolo and P. Gal (2016), “The Best versus the Rest: The Global Productivity Slowdown,
Divergence across Firms and the Role of Public Policy”, OECD Productivity Working Papers, No. 5.

9. • What are the implications of the prolonged survival
of marginal firms for aggregate productivity?
• Continued survival of marginal firms could harm
aggregate growth via two key channels:
– Direct effect: lowers unweighted average productivity
– Indirect effects: market congestion 
• Stifles growth opportunities for healthier firms
• Deters entry of potentially innovative firms
Key questions

10. Lack of systematic cross-country evidence on the
prevalence and consequences of zombies:
 Academic literature is Japan-specific: Caballero, Hoshi &
Kashyap (2008); Peek & Rosengren (2005)
 Cursory exploration in other countries (BoE, BoK)
 Achayra et al (2016): “Whatever it takes”
 ECB’s OMT program indirectly recapitalized periphery
banks via sovereign bond holdings
 Under-capitalised banks used OMT windfall gains to direct
loans to zombies to avoid incurring losses on loan portfolio
 Lending triggered by OMT windfall gains did not directly
raise real activity but evidence of zombie congestion
Our contribution: towards systematic
cross-country evidence on Zombies

11. We use harmonised cross-country firm level
balance sheet data to explore the:
 Prevalence of zombie firms in different OECD
countries
 Implications of resources sunk in zombies for:
 Non-zombie firm performance: investment and
employment growth (Caballero et al., 2008) and
by firm age;
 Dynamic capital reallocation and aggregate MFP
(Foster et al., 2016).
Our contribution: towards systematic
cross-country evidence on Zombies

12. THE WALKING DEAD: NEW
CROSS-COUNTRY EVIDENCE ON
“ZOMBIE FIRMS”

13. • Largest firm-level dataset of companies worldwide
– Best coverage for developed EU countries (ESP, FRA, ITA, GBR, ..)
• Updated and longer time-series than previous versions
• Based on balance sheets and income statements,
contains information on
– Revenues (output); employment, assets and materials (inputs) and
financial conditions (indebtedness, profits)
• Data cleaning and filtering:
– Monetary variables are deflated using 2-digit industry deflators from
OECD STAN + national accounts
– Prices are expressed in industry PPP
Dataset – ORBIS

14. • Comparing coverage with official business demography (OECD
SDBS) and national accounts data
– Construction of weights by country*industry* firm size* year
• Construct key variables for analysis:
– Capital stock (from book values, implied gross investment then apply PIM)
– Productivity measures at the firm- and industry-levels: labour prod. and MFP,
using several methodologies: Solow, OLS and Wooldridge. (see Gal 2013)
– Zombie measures
• Sample used for analysis:
– Panel of 9 countries 2000-2013: BE, ES, FI, FR, GB, IT, KR, SE, SI
– Cross-section of 13 countries in 2013: AT, BE, DE, ES, FI, FR, GB, IT, LU,
KR, PT, SE, SI
Dataset – ORBIS

15. Approach 1: Persistent financial weakness:
A. Firms with interest coverage ratio<1 for 3
consecutive years (Bank of Korea)
B. Firms with negative profits (Bank of England)
C. Firms with negative value added
 We focus on incumbent firms aged ≥ 10 years
Methodology: how do we identify
zombie firms?

16. Methodology: how do we identify
zombie firms?
Approach 2: Firms receiving subsidized bank credit (Caballero et al., 2008):
• Actual interest repayments are less than an estimated benchmark 𝑅∗
based on the firm debt structure and market interest rates
𝑅𝑖,𝑡
∗
= 𝑟𝑠𝑡−1 𝐵𝑆𝑖,𝑡−1 +
1
5
𝑗=1
5
𝑟𝑙 𝑡−𝑗 𝐵𝐿𝑖,𝑡−𝑗
where 𝐵𝑆𝑖,𝑡 = short-term loans (less than one year) of firm i at the end of year t
𝐵𝐿𝑖,𝑡 = long−term debt (more than one year) of firm i at the end of year t
𝑟𝑠𝑡 = average short−term prime rate year t
𝑟𝑙 𝑡 = average long−term prime rate year t
• Pros: more directly linked to “evergreening” or “forbearance”; more
exogenous?
• Cons: data availability is more challenging relative to (1)
Baseline analysis is based on Approach (1A) but our results hold in a
smaller sample based on Approach (2). 1A and 2 highly correlated.

17. -0.30
-0.25
-0.20
-0.15
-0.10
-0.05
0.00
0
1
2
3
4
5
6
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Share of zombie firms (LHS) Labour productivity relative to non-zombie firms (RHS)
% log points
The rise of zombie firms
Firms aged ≥10 years with an interest coverage ratio<1 over 3 consecutive years
Unweighted average across selected OECD countries
Source: Adalet McGowan, M., D. Andrews and V. Millot (2017), “The Walking Dead? Zombie Firms and
Productivity Performance in OECD countries”, OECD Economics Department Working Paper No. 1372.

18. The prevalence and resources sunk
in zombie firms has risen
Firms aged ≥10 years and with an interest coverage ratio<1
over three consecutive years
Source: Adalet McGowan, M., D. Andrews and V. Millot (2017), “The Walking Dead? Zombie Firms and
Productivity Performance in OECD countries”, OECD Economics Department Working Paper No 1372.
0
5
10
15
20
25
2007
2010
2013
2007
2010
2013
2007
2010
2013
2007
2010
2013
2007
2010
2013
2007
2010
2013
2007
2010
2013
2007
2010
2013
2007
2010
2013
BEL ESP FIN FRA GBR ITA KOR SWE SVN
Number of firms Employment Capital Stock%

19. THE WALKING DEAD: ZOMBIE
FIRMS AND LABOUR
PRODUCTIVITY
BASELINE ANALYSIS

20. • In a world without zombies, incumbents hit by unfavourable
shocks exit, and are replaced by new entrants hit by
favourable productivity draws.
• In a world with zombies, subsidised incumbents don’t exit
when hit by unfavourable shocks (“sclerosis”). In turn:
– Congestion: non-zombies must compete with zombies for
scarce resources; zombies may even ↓ prices & ↑ wages to
compete aggressively
– Non-zombies bare all the adjustment to shocks: potentially
productive entrants decide not to enter and healthy incumbents
scrap expansion plans
– Entrants must clear a higher productivity threshold to
compensate for lower profitability caused by congestion
Channels: key features from model
in Caballero et al (2008)

21. Baseline specification taken from Caballero et al (2008):
• Y (k=3): 1-investment, 2-employment growth; 3-MFP
• nonZ is dummy=1 if firm is a non-zombie; =0 if zombie firm
• Z is the share of industry capital sunk in zombie firms
• X: Firm level controls (firm age, size etc)
• Country-industry-year fixed effects: cyclical shocks
• Standard errors clustered at country*industry*year level
Methodology: zombies and
“average” non-zombie performance
icstcsticstcsticsticst
k
icst XZnonZnonZY   1321 *
Predictions: β2<0 for K & E | β2>0 for MFP
• The presence of zombie will generate distortions for non-
zombie firms: depress K & E growth + widen the MFP gap

22. Zombie congestion and “average”
non-zombie firm performance
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 No. 1372.
Zombie measure: interest coverage ratio<1 over the past three years
and firms older than 10 years old
(1) (2) (3) (4) (5) (6)
VARIABLES log(I/K) dLog Emp MFP log(I/K) dLog Emp MFP
0.07372*** 0.06943*** 0.52738*** 0.06342*** 0.08335*** 0.57842***
(0.00288) (0.00172) (0.01198) (0.00794) (0.00479) (0.02918)
-0.13257*** -0.03759*** 0.47019*** -0.07791** -0.04757* 0.49190***
(0.01752) (0.01197) (0.10471) (0.03752) (0.02490) (0.17904)
Firm Age and Size Controls YES YES YES YES YES YES
Industry*Country Fixed Effects NO NO NO YES YES YES
Industry*Country*Year Fixed Effects YES YES YES NO NO NO
Observations 10,121,532 10,121,532 7,956,552 1,234,596 1,234,596 1,030,477
AdjR2 0.0193 0.0244 0.832 0.0152 0.0218 0.815
Non-zombie dummyi,t X Industry
zombie sharess,t
Non-zombie dummyi,t
A: Panel of 9 countries, 2003-2013 B: Cross section of 13 countries,

23. • Using more exogenous measures of zombie firms in a
smaller sample of countries; i.e. firms receiving subsidised
credit (Caballero et al, 2008).
• Using different definitions of zombies based on interest
coverage ratio (different age and persistence thresholds;
excluding outlier firms such as very large SOEs).
• Using SDBS weights or excluding firms <20 employees, to
address ORBIS representativeness issues.
• Pre-crisis regressions and excluding Italy and Spain.
• Controlling for the share of old firms in the industry.
• Controlling for firm sales growth (Caballero et al. 2008).
• Different fixed effects structures and clustering techniques.
• Using employment sunk in zombie firms.
Results are robust to:

24. -1.2
-1.0
-0.8
-0.6
-0.4
-0.2
0.0
Employment
%
-2.0%0.0%
Employment
Old (>5 years old) Young (<=5 years old)
0
2
4
6
8
10
12
14
MFP gap with zombie firms
%
Zombie congestion particularly
penalises young firms
Impact of one standard deviation increase in the zombie capital
share on non-zombies by firm age
Evidence of rising MFP dispersion and barriers to entry may be
connected to the zombie phenomenon

25. The “average” firm is tenuous, given
widespread firm heterogeneity
Within-industry MFPR distribution moments, 2013
Log points; Unweighted average across industries
Within-industry
moment
Mean Std. Dev. IQ range
Median 5.785 1.841 2.258
IQ range 0.917 0.443 0.439
90-10 percentile range 1.844 0.778 0.867
95-5 percentile range 2.477 1.008 1.180
All firms
What if zombie congestion disproportionately constrains
the growth of more productive firms?
Widespread heterogeneity in firm productivity creates
scope for productivity-enhancing reallocation

26. • Canonical models of firm dynamics predict that conditional on
size, firms with higher MFP grow more quickly (Foster et al.,
2016; Decker et al., 2016; Cooper et al., 2007)
where:
• Firm MFP is the deviation from country-industry-year averages
• Z is the share of industry resources sunk in zombie firms
• Firm controls are firm age and size
• Country-industry-year fixed effects
• Standard errors clustered at country*industry level
Methodology: zombie congestion
and reallocation
𝐶𝑎𝑝𝑖𝑡𝑎𝑙 𝑔𝑟𝑜𝑤𝑡ℎ𝑖s𝑐𝑡
= 𝛿1 𝑀𝐹𝑃isct −1 + 𝛿2 𝑀𝐹𝑃isct −1 ∗ 𝑍sct
+ 𝛿3 𝐹𝑖𝑟𝑚 𝑐𝑜𝑛𝑡𝑟𝑜𝑙𝑠𝑖𝑠𝑐𝑡 −1 + 𝛿sct + 𝜖𝑖s𝑐𝑡

27. Zombie congestion and capital
reallocation
Source: Adalet McGowan, M., D. Andrews and V. Millot (2017), “The Walking Dead? Zombie Firms and
Productivity Performance in OECD countries”, OECD Economics Department Working Paper No. 1372.
Zombie measure: interest coverage ratio<1 over the past three years
and firms older than 10 years old
(1) (2) (3) (4)
VARIABLES K-share L-share K-share L-share
0.07819*** 0.08241*** 0.06458*** 0.06588***
(0.002) (0.002) (0.006) (0.004)
-0.14017*** -0.26720*** -0.09088*** -0.15578***
(0.018) (0.026) (0.034) (0.034)
Firm Age and Size Controls YES YES YES YES
Industry*Country Fixed Effects NO NO YES YES
Industry*Country*Year Fixed Effects YES YES NO NO
Observations 6,405,339 6,405,339 902,271 902,271
AdjR2 0.0308 0.0310 0.0211 0.0211
MFPi,t-1 X Industry zombie sharess,t
B: Cross section of 13 countries,A: Panel of 9 countries, 2003-2013
Zombie measure Zombie measure
MFPi,t-1
Zombie congestion slows down productivity-enhancing capital
reallocation – i.e. more productive firms are particularly harmed

28. • Using more exogenous measures of zombie firms in a
smaller sample of countries; i.e. firms receiving subsidised
credit (Caballero et al, 2008)
• Using different definitions of zombie based on interest
coverage ratio (different age and persistence thresholds;
excluding outlier firms such as very large SOEs).
• Different productivity measures
• Using SDBS weights or excluding firms with less than 20
employees, to address ORBIS representativeness issues
• Pre-crisis regressions and excluding Italy and Spain
• Excluding zombie firms from the sample
• Different fixed effects structures and clustering techniques
Results are robust to:

29. THE WALKING DEAD: ZOMBIE
FIRMS AND LABOUR
PRODUCTIVITY
ECONOMIC SIGNIFICANCE

30. • Channels linking zombie congestion to aggregate growth:
1. Lower unweighted average productivity
2. Lowers within-industry dynamism
a) Stifles growth opportunities for healthier firms
b) Deters entry of potentially innovative firms
3. Less efficient between-industry reallocation
• We study the two counterfactuals:
– CF1: Reducing zombie K share to “best practice” level in
2013: How much scope is there for policy reforms targeted
at the exit margin to boost productivity?
– What if the zombie K-share had not risen after 2007? What
is the contribution of the rise in zombie congestion to the
productivity slowdown?
Zombie congestion and
productivity: economic signfiicance

31. 0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
0
5
10
15
20
25
ITA BEL PRT ESP DEU FIN LUX SWE KOR AUT GBR FRA SVN
Zombie shares (LHS) %Gains to productivity-enhancing capital allocation (RHS)
% %
CF1: Zombie congestion distorts
capital reallocation…
Impact of reducing zombie congestion to level observed in Slovenia
on productivity-enhancing capital reallocation
Difference in capital growth between high and low productivity firms (%pts), 2013
Source: Adalet McGowan, M., D. Andrews and V. Millot (2017), “The Walking Dead? Zombie Firms and
Productivity Performance in OECD countries”, OECD Economics Department Working Paper No. 1372.

32. … with significant costs to
aggregate MFP
Counterfactual gains to aggregate MFP from reducing
zombie capital share to industry best practice level, 2013
Source: Adalet McGowan, M., D. Andrews and V. Millot (2017), “The Walking Dead? Zombie Firms and
Productivity Performance in OECD countries”, OECD Economics Department Working Paper No. 1372.
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
ESP ITA SWE Average KOR GBR BEL FIN SVN FRA

33. • Channels linking zombie congestion to aggregate growth:
1. Lower unweighted average productivity
2. Lowers within-industry dynamism
a) Stifles growth opportunities for healthier firms
b) Deters entry of potentially innovative firms
3. Less efficient between-industry reallocation
• We study the two counterfactuals:
– CF1: Reducing zombie K share to “best practice” level in
2013: How much scope is there for policy reforms targeted
at the exit margin to boost productivity?
– CF2: What if the zombie K-share had remained at pre-crisis
levels? What is the contribution of the rise in zombie
congestion to the productivity slowdown?
Zombie congestion and
productivity: economic significance

34. CF2: Zombie congestion and non-
zombie performance
Source: Adalet McGowan, M., D. Andrews and V. Millot (2017), “The Walking Dead? Zombie Firms and
Productivity Performance in OECD countries”, OECD Economics Department Working Paper No. 1372..
Investment and employment loss of a typical non-zombie firm
due to a rise in the zombie capital share after 2007
-2
-1
0
1
2
3
4
5
6
7
ITA FIN ESP SWE BEL Average KOR FRA SVN GBR
Cumulative lost investment Cumulative lost employment%

35. If the zombie capital share had not risen from
2004 levels (i.e. adjustment dynamics remained at
their more responsive 2004 levels), then:
 Perhaps one-half of the deterioration in capital
allocative efficiency in ESP and ITA could have been
avoided; and
 The contribution of capital reallocation to aggregate
productivity could have been on average 0.7% and 1%
higher in ESP and ITA respectively.
CF2: Implications for MFP

36. THE WALKING DEAD: NEXT
STEPS AND LINKS WITH POLICY

37. Link newly sourced commercial data on firms entering
insolvency procedures to our firm level database to study:
• The disposal/restructuring of weak firms: are zombie
firms more likely to be liquidated in some countries than
others? Are restructuring procedures effective?
• The design of exit policies: are these cross-country
differences related to the policy environment, including
insolvency regimes? The role of bank forbearance?
• Aggregate implications: what types of reforms may
raise aggregate productivity growth via a better
functioning exit margin?
Future work: if zombies are
problem, what can we do about it?

38. Public policy, the exit margin and
aggregate productivity growth
Aggregate productivity
growth
Market exit of non-
viable firms
Internal restructuring
by viable firms
More productive
firms expand
Strength of market
selection
Resource reallocation
from exiting firms
Efficient
insolvency
regimes
Competitive pressures
Product market
regulations
Public support schemes
Financial regulation
Fiscal distortions
Stance of monetary policy
Corporate governance
Enviromental regulations
Rule of law
Employment protection
legislation
Active labour market policies
Financial development
Housing market policies
Intellectual property markets
Size contingent policies
Judicial
efficiency

39. 0
5
10
15
20
1998 2000 2002 2004 2006 2008 2010 2012 2014
Bank NPLs to Total Loans
Zombie Capital Share
%
Italy
Zombie congestion and NPLs are
connected, especially in Italy
(1) (2)
2002-2013 2002-2004 to 2011-2013
0.015*** 0.017**
(0.005) (0.007)
GDP Growthc,t-2 YES YES
Country Fixed Effects YES YES
Time Fixed Effects YES YES
Observations 78 31
AdjR2 0.617 0.554
Dependent Variable: Zombie Capital Share
NPLc,t-2

40. Specific features of insolvency
regimes and productivity growth
Intensive margin
Reallocation effect
Future within firm
productivity
Specific features of insolvency regimes
Restructuring of
viable firms
Exit of non-viable
firms
Creditors ability to initiate restructuring + +
Availability of a stay on assets + +
Possibility and priority of new financing over
unsecured creditors
+ - +
Retention of incumbent management during
restructuring
"+/-" +
Possibility to “cram-down” a restructuring
plan on dissenting creditors
+ +
Limited involvement of courts + +
Design of priority rules, favouring objectives
other than the efficient exit of firms
- - -
Availability of a "fresh start" + + +
Extensive margin
Selection effect
World Bank indicators do not fully
capture these design features
Source: Adalet McGowan, M and D. Andrews (2016), “Insolvency regimes and productivity growth: A
framework for analysis”, OECD Economics Department Working Papers, No. 1309.

41. 2. Are weak firms stifling
productivity growth?
5. Can we improve the
design of exit policies?
October 2016 October 2017
Exit Policies and Productivity
Growth
4. Can we improve the
measurement of exit
policies?
March 2016
1. How do we think about the exit margin,
productivity and policy?
3. What happens to the
workers when firms exit?
October 2016 April 2016 - March 2017
Coping with
Creative
Destruction:
Reducing the
Costs of Firm
Exit Policies and
Productivity
Growth: a
Framework for
Analysis
New cross-
country policy
indicators of
insolvency
regimes
The Walking
Dead?: Zombie
Firms and
Productivity
Performance in
OECD countries
New empirical
evidence of exit
policies and
productivity
growth

42. ALMPs can help re-integrate
workers displaced by firm exit
D. Andrews and A.Saia (2016), “Coping with Creative Destruction: Reducing the Costs of Firm Exit”,
OECD Economics Department Working Paper, No 1353.
Impact of higher spending on ALMPs on the re-employment
probability
Impact of increasing spending ALMP to 1 % of GDP , by reason for job loss
0
3
6
9
12
15
Firm closure Other involuntary reason
Reason for job loss in period t-1
Percent

43. 0
5
10
15
20
25
Low Entry Barriers Average Entry Barriers High Entry Barriers
Impact of ALMPs on re-employment according to the level of entry barriers
Percent
Reducing entry barriers boosts the
effectiveness of ALMPs
Impact of increasing spending ALMP to 1 % of GDP on the re-
employment probability
D. Andrews and A.Saia (2016), “Coping with Creative Destruction: Reducing the Costs of Firm Exit”,
OECD Economics Department Working Paper, No 1353.