High-Growth Firms
Facts, Fiction, and Policy Options
for Emerging Economies
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CONFERENCE EDITION
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High-Growth Firms
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High-Growth Firms
Facts, Fiction, and Policy Options for
Emerging Economies
Arti Grover Goswami, Denis Medvedev,
and Ellen Olafsen
Conference Edition
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The text of this conference edition is a work in progress for the forthcoming book, High-Growth Firms: Facts,
Fiction, and Policy Options for Emerging Economies. doi: A PDF of the final book,
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v
Contents
Preface ........................................................................................................................... xi
Acknowledgments .....................................................................................................xiii
Selected Abbreviations and Acronyms .................................................................. xv
Executive Summary ..................................................................................................xvii
1. The Appeal of High Growth ..................................................................................1
Definitions.......................................................................................................2
Incidence .........................................................................................................4
Jobs and Output Creation ............................................................................12
Linkages and Spillovers ................................................................................16
Annex 1A .......................................................................................................18
Notes ..............................................................................................................25
References ......................................................................................................27
2. Facets of High-Growth Events ...........................................................................31
Size and Age ..................................................................................................32
Sector and Location ......................................................................................39
Firms and Episodes .......................................................................................49
Annex 2A .......................................................................................................57
Notes ..............................................................................................................60
References ......................................................................................................62
3. What Makes for High Growth? ..........................................................................67
Productivity ...................................................................................................69
Innovation .....................................................................................................78
Agglomeration and Firm Networks .............................................................82
Managerial Capabilities and Worker Skills ..................................................87
Global Linkages .............................................................................................92
Financial Development ................................................................................98
Annex 3A .....................................................................................................102
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vi Contents
Notes ............................................................................................................104
References ....................................................................................................107
4. Searching for Winners .....................................................................................117
Programs and Instruments to Support Firm Growth...............................118
Selection of Beneficiaries ............................................................................126
Toward an Evidence-Based Approach to Supporting
High Firm Growth ..............................................................................133
Annex 4A .....................................................................................................148
Notes ............................................................................................................151
References ....................................................................................................154
List of Background Papers ...............................................................................165
Boxes
National Firm Data versus Enterprise Surveys ........................................................9
Firm Organization and High Growth ....................................................................50
Theories of Firm Growth ........................................................................................70
Productivity and Demand over the Firm’s Life Cycle ............................................76
Firms in Focus: Rappi, Colombia ...........................................................................83
Firms in Focus: Beijing Genomics Institute, China ...............................................91
Identifying Firm Leaders .........................................................................................93
Firms in Focus: Chaldal, Bangladesh ......................................................................93
Firms in Focus: AAA Growers, Kenya ....................................................................99
Firms in Focus: Hi-Tech Gears, India .....................................................................99
Communities, Networks, and Ecosystems ...........................................................119
National Programs to Support High Firm Growth in Mexico and
South Africa ......................................................................................................121
Public Facilitation of Equity Finance ...................................................................123
Endeavor’s Selection Process .................................................................................129
Measuring Cognitive Abilities ...............................................................................132
Competitiveness Policy Evaluation Lab (ComPEL) ............................................136
Cross-Border Incubation and Acceleration Initiatives ........................................145
Science, Technology, and Innovation Public Expenditure Reviews ....................146
Figures
Country Coverage of the Book ........................................................................... xviii
Incidence of High Growth ........................................................................................5
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Contents vii
HGF Incidence in National Data Sets and Enterprise Surveys ...............................9
HGF Incidence and per Capita Income .................................................................10
HGF Incidence and Industry Concentration or Growth ......................................11
HGFs Contribute Disproportionately to Employment Growth ...........................13
HGF Contributions to Employment Growth in Brazil and Mexico .....................14
HGFs Account for the Majority of Growth in Sales ..............................................15
Buying from or Supplying to HGFs Improves Firm Performance in Hungary ...... 17
HGFs Are More Likely to Be Young ........................................................................34
Most HGFs in Indonesia Are Medium-to-Large Firms .........................................36
HGFs Tend to Be Larger than Other Firms ............................................................37
HGFs in Turkey Are More Likely to Be Larger than Other Firms ........................38
Large HGFs in Indonesia Create a Disproportionately Greater
Number of Jobs ..................................................................................................38
HGFs in Hungary Are More Common in Knowledge-Intensive Sectors .............41
HGFs in Indonesia Are More Common in High-Tech Manufacturing…
but also in Some Low-Tech ....................................................................................42
HGFs Are Found in High-Tech and Low-Tech Industries Alike ..........................43
More Entrepreneurship Translates into More HGFs across Brazilian States .......46
HGFs Are More Common in the North of Mexico and in Large Cities ...............47
Reforms Increased the Concentration of HGFs in Ethiopia’s Capital City ..........48
Larger Micro-Enterprises in India Benefit More from Improved Connectivity ..... 49
HGF Growth in Indonesia Is Volatile and Lacks Persistence ................................51
HGFs Have Survival Probabilities Similar to Those of Non-HGFs ......................55
Firms Move in and out of HGF Status in Mexico .................................................56
Incidence of HGFs in Services Sectors ...................................................................57
Higher Initial TFP Is Associated with Subsequent High Growth
among Ethiopian Plants ..........................................................................................72
Future HGFs Outperform Other Hungarian Firms on Multiple
Dimensions of Productivity ....................................................................................73
Firm Performance in Hungary Improves during High-Growth Episodes ..........74
High-Growth Experience Boosts TFP Growth in Ethiopia, and
Particularly So for Top Performers .........................................................................75
The Overlap between Observed and “Efficient” HGFs Is Limited ........................77
The Fastest-Growing Firms in India Are Significantly More Innovative ............79
Innovation Increases the Likelihood of High Growth in India ............................80
R&D Activity in Mexico Correlates Positively with High Growth ........................81
HGFs in Ethiopia Are More Common in or Close to Agglomeration Centers ....... 82
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viii Contents
Agglomeration Increases the Likelihood of High Growth in Ethiopia
while Industry Concentration Reduces It .............................................................84
Policy Reforms Strengthened the Links between Agglomeration and
High Firm Growth in Ethiopia ...............................................................................85
In-Network Thai Firms Are Larger and More Likely to Experience
High Growth ............................................................................................................85
Participation in Networks Increases the Likelihood of High Firm
Growth in Thailand .................................................................................................86
Initial Higher Wages among Ethiopian and Mexican Firms Are Correlated
with High Growth ...................................................................................................88
The Relationship between HGF Status and Higher Wages Is Stronger for
Hungary’s High-Tech Sectors .................................................................................89
Employees and Managers of HGFs in Brazil Have Greater Human
Capital Endowments ...............................................................................................90
Future HGFs in Brazil Pay Substantially Higher Wages from the
Moment of Birth .....................................................................................................92
Hungarian Firms with Links to Global Markets Are More Likely to
Experience High-Growth Events ............................................................................95
International Exposure Is Positively Associated with High Growth in
Mexico and Tunisia .................................................................................................96
Foreign Exposure in India Increases the Likelihood of High Growth…
More So in Services ................................................................................................97
FDI Linkages Increase the Likelihood of High Growth in Mexico .......................98
Financial Development Improves Firm Performance in
Upper-Middle-Income Countries ........................................................................101
Results Framework for a Science, Technology, and Innovation Intervention ....125
High Performance versus High Program Impact ................................................127
Grants to Start New Businesses in Nigeria Benefited Women
More than Men .............................................................................................128
Policy Instruments to Support Firm Growth.......................................................134
Decomposition of Productivity Growth ..............................................................138
Map
Countries Covered by the Book .......................................................................... xviii
Tables
Correlations across HGF Definitions .......................................................................8
Data Sources and Descriptions ..............................................................................19
Firm-Year Observations for Constructing the Cross-Country
Comparable Sample ................................................................................................24
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Contents ix
World Bank Enterprise Surveys (WBES) Data Coverage ......................................24
High-Growth Improves Survival Odds, but Only Slightly ...................................53
Expanded Transition Matrix ...................................................................................59
Correlates of High Firm Growth: Summary of Chapter Results ..........................68
Background Paper Definitions and Key Correlates of HGFs ..............................102
Results Framework and Measurement for a Sample of
Growth-Oriented Interventions ...........................................................................126
List of 58 Targeted Interventions in 17 Developing Countries ..........................148
Intensity of Program Screening and Impacts ......................................................149
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xi
Preface
Productivity accounts for half of the differences in GDP per capita across countries.
Identifying policies to stimulate it is thus critical to alleviating poverty and fulfilling the
rising aspirations of global citizens. Yet productivity growth has slowed globally in
recent decades, and the lagging productivity performance in developing countries con-
stitutes a major barrier to convergence with advanced-country levels of income.
The World Bank Productivity Project—an initiative of the Vice Presidency for
Equitable Growth, Finance, and Institutions—seeks to bring frontier thinking on the
measurement and determinants of productivity, grounded in the developing-country
context, to global policy makers. Each volume in the series explores a different aspect
of the topic through dialogue with academics and policy makers, and through spon-
sored empirical work in our client countries. The first volume, The Innovation Paradox,
developed a blueprint for reshaping many aspects of innovation-related productivity
policies in developing countries. The second volume, Productivity Revisited, framed
cutting-edge thinking on measuring and understanding productivity dynamics within
the agenda of developing-country policy makers.
This, the third volume in the series, focuses on the disproportionate contribution to
overall growth by a relatively small share of firms that quickly scale their employment
and output and generate positive spillovers along the value chain (high-growth firms).
Policy makers across the world are keen to identify and support such firms, in an effort
to boost development. However, episodes of high growth are typically short-lived,
and the empirical support for the ability to successfully target these firms is, at best,
lukewarm. The analysis in this volume sheds new light on key features and drivers of
high-growth firms in developing countries and leads to rethinking of public policy
priorities to support firm growth.
William F. Maloney
Chief Economist
Equitable Growth, Finance, and Institutions
World Bank Group
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Other Titles in the World Bank Productivity Project
Productivity Revisited: Shifting Paradigms in Analysis and Policy. 2018. Ana Paula
Cusolito and William F. Maloney. Washington, DC: World Bank.
The Innovation Paradox: Developing-Country Capabilities and the Unrealized
Promise of Technological Catch-Up. 2017. Xavier Cirera and William F. Maloney.
Washington, DC: World Bank.
All books in the World Bank Productivity Project are available free at
xiii
Acknowledgments
This book was prepared by a team led by Arti Grover Goswami (World Bank Finance,
Competitiveness, and Innovation Global Practice), Denis Medvedev (World Bank
Finance, Competitiveness, and Innovation Global Practice), and Ellen Olafsen (World
Bank Finance, Competitiveness, and Innovation Global Practice) under the guidance
of Paulo Correa (Practice Manager, World Bank Finance, Competitiveness, and
Innovation Global Practice) and Ganesh Rasagam (Practice Manager, World Bank
Finance, Competitiveness, and Innovation Global Practice). Anabel Gonzalez and
Klaus Tilmes (Senior Adviser, World Bank Equitable Growth, Finance and Institutions
cluster) provided direction to the team during the initial stages of the book prepara-
tion. The team is indebted to Najy Benhassine (Director, World Bank Equitable Growth,
Finance and Institutions cluster), Mary Hallward-Driemeier (Senior Economic Advisor,
World Bank Equitable Growth, Finance and Institutions cluster), William F. Maloney
(Chief Economist, World Bank Equitable Growth, Finance and Institutions cluster),
and Ceyla Pazarbasioglu-Dutz (Vice President, World Bank Equitable Growth, Finance
and Institutions cluster), who linked the team to the World Bank Group’s overall strat-
egy and steered them in that direction.
The book’s findings and analytical insights draw on a set of background papers
commissioned for this report. The papers’ authors were Paulo Bastos and Joana Silva
(Brazil); Xavier Cirera, Roberto Fattal Jaef, and Nicolas Gonne (Côte d’Ivoire); Arti
Grover Goswami (Ethiopia); Balazs Muraközy, Francesca de Nicola, and Shawn Tan
(Hungary); Kay Kim and Siddharth Sharma (India); Ruchita Manghnani (India);
Esteban Ferro and Smita Kuriakose (Indonesia); Luis Sanchez Bayardo and Leonardo
Iacovone (Mexico); Marcio Cruz, Leila Baghdadi, and Hassen Arouri (Tunisia);
Itzak Atiyas, Ozan Bakis, Francesca de Nicola, and Shawn Tan (Turkey); Chanont
Banternghansa and Krislert Samphantharak (Thailand); Jose-Daniel Reyes, Arti Grover
Goswami, and Yahia Ziad Abuhashem (financial development); Johanne Buba, Julio
Gonzalez, and Deeksha Kokas (targeting entrepreneurs); and Sameeksha Desai, Ellen
Olafsen, and Peter Alex Cook (entrepreneurship policies). William R. Kerr provided
major contributions and insights on firm dynamics in the United States, Mulalo
Mamburu did so for South Africa, and Umut Kilinc for Turkey. Marcio Cruz made
substantial contributions to the analytical framework, while Anwar Aridi and Danqing
Zhu contributed to earlier versions of the book Yahia Ziad Abuhashem, Nuria Tolsa
Caballero, Peter Alex Cook, and Ndirangu Warugongo provided valuable research
13 31/10/18 7:01 pm
xiv Acknowledgments
assistance. Patricia Katayama, Rachel Fano, Alloysius Ocheni, and Susana Rey provided
production and logistical support. William Shaw organized, streamlined, and edited
the narrative.
The peer reviewers were Alex Coad (CENTRUM Católica Graduate Business School,
Lima, Perú), Alvaro Gonzalez (World Bank), Ivailo Izvorski (World Bank), David
McKenzie (World Bank), Esperanza Lasagabaster (World Bank), David Audretsch
(Indiana University), Donna Kelley (Babson College), and Fadi Ghandour (Aramex).
14 31/10/18 7:01 pm
xv
Selected Abbreviations
and Acronyms
BS backward spillover
FDI foreign direct investment
FS forward spillover
GDP gross domestic product
GQ Golden Quadrilateral
HGF high-growth firm
HS horizontal spillover
IFC International Finance Corporation
M&E monitoring and evaluation
MNE multinational enterprise
MSMEs micro, small, and medium enterprises
NBER National Bureau of Economic Research
NESTA National Endowment for Science, Technology and the Arts
NS-EW North-South-East-West
OECD Organisation for Economic Co-operation and Development
R&D research and development
ROA return on assets
RPQ relative prevalence quotient
STI science, technology, and innovation
SMEs small and medium enterprises
TFP total factor productivity
TFPQ total factor productivity, quantity based
TFPR total factor productivity, revenue based
VC venture capitalist
VS vertical spillover
WBES World Bank Enterprise Surveys
ZBTIC Zone de la Biotechnologie de l’Information et de la Communication
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16 31/10/18 7:01 pm
xvii
Executive Summary
The cover of this book features a painting by the Spanish surrealist artist Remedios Varo
(1908–1963), Papilla estelar (Celestial Pablum, also known as the Star Maker). Stars,
superstars, elephants, gazelles, gorillas, unicorns, and other monikers for high- performing
firms abound in the economic and financial literature, as well as in popular discourse.
Targeting such firms, in an effort to boost policy selectivity and efficiency, has become
an increasingly appealing goal for policy makers in high-income and developing coun-
tries alike. Yet the making of stars, a process by which a venture capitalist or policy
maker identifies high-potential businesses and puts in place processes and policies to
accelerate firm growth, remains mostly art rather than science. This is particularly true
for developing countries because the evidence base in this field has thus far been largely
limited to high-income economies.
What difference do high-growth firms (HGFs) make to growth, productivity, and
job creation in developing countries? How do they do it? And what is the appropriate
role for public policy? Inspired by these questions, this book sets out to quantify the
importance of HGFs for employment and output growth, considering both the dynam-
ics within HGFs and their impact on other firms in the economy (chapter 1). It explores
the key characteristics of HGFs, focusing particularly on those aspects that have been
or can be used as filters for policy action (chapter 2). The book then discusses a range
of likely correlates of the success of HGFs, including productivity, innovation, agglom-
eration and networks, skills and managerial experience, global linkages (trade and for-
eign direct investment [FDI]), and financial development (chapter 3). Finally, it reviews
the public policies used in developing countries to support the creation and scaling up
of HGFs and the evidence on the effectiveness of mechanisms to screen and identify
high-potential firms, concluding with a blueprint for a reorientation of public policies
aimed at facilitating firm growth (chapter 4).
The book’s insights are based on detailed analysis of high-quality longitudinal data
sets in Brazil, Côte d’Ivoire, Ethiopia, Hungary, India, Indonesia, Mexico, South Africa,
Thailand, Tunisia, and Turkey. The selection of countries reflects in large part data
availability, given that there are simply not many panel censuses or surveys of firms in
developing countries, and accessing the existing ones is often a challenge. Even so, the
data sets in this book cover all six World Bank regions as well as diverse income levels
and very different growth performances (figure ). Despite the heterogeneity of data
sources and underlying country characteristics, the main findings and conclusions
17 31/10/18 7:01 pm
xviii Executive Summary
tend to be quite robust across the various cases, supporting the general insights and
policy recommendations developed in the last chapter.
Why Are High-Growth Firms Important?
HGFs are powerful engines of job and output growth. Although HGFs make up just
3–20 percent of manufacturing and services firms in the countries studied in this book,
they create more than half of all new jobs and sales in these sectors taken together.
–3
–1
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3
5
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, 2
00
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7
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0 3,000 6,000 9,000 12,000 15,000
Income per capita, 2017 (US$)
FIGURE Country Coverage of the Book
MAP Countries Covered by the Book
IBRD 43999 | OCTOBER 2018
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Executive Summary xix
Another way to appreciate their disproportionate impact is to recognize that, in nearly
all cases, the net change in employment and output would have been negative without
the positive contribution of these firms (that is, in aggregate, non-HGFs destroy more
jobs than they create, and decline rather than grow in terms of sales). These dynamics
are similar to what has been previously observed across a range of high-income
economies, such as Sweden, the United Kingdom, and the United States. To paraphrase
Paul Krugman’s famous quote, high-growth firms are nearly everything when it comes
to determining an economy’s overall
In addition to their critical role in job and output growth, HGFs create positive
spillovers around them. Whereas evidence for horizontal (same sector) spillovers is
mixed—since HGFs may transfer knowledge or create networks, but also may raise
competition and push down prices—the evidence on vertical spillovers is stronger. In
the two countries where this book was able to follow HGF spillovers, being a buyer
from or a supplier to an HGF improved firm performance across a wide range of indi-
cators in Hungary and also, in some cases, in Turkey. These extraordinary abilities of
HGFs are what make them an interesting subject for academics and an attractive target
for policy makers keen to boost economic performance.
How Do Firms Grow?
A common view of a typical HGF is a small start-up in a high-tech sector that grows
quickly over a sustained period through some favorable quality inherent to the firm, for
example, a new advanced technology, a brilliant marketing innovation, or an extremely
capable staff. Thus, the policy challenge is framed as determining which firms have the
potential for high growth and providing these firms with access to financial and techni-
cal resources to realize this potential. However, the new analysis in this book, as well as
the economic literature it surveys, shows that this view is a misconception.
First, while HGFs tend to be younger than the average firm, most will have been in
business for at least a couple of years before embarking on a high-growth trajectory.
HGFs are not necessarily small either; many already are larger than the average firm at
the beginning of a high-growth episode and, depending on the definition, the average
HGF is anywhere from 4 percent larger to six times as large as an average firm after
three years of high growth. HGFs also do not appear in the same sectors across coun-
tries, and are not necessarily more common in high-tech industries. Finally, they oper-
ate across a range of locations, although proximity to infrastructure plays an important
role in facilitating high growth.
Second, the achievement of high growth in one period does not mean that firms are
more likely to grow rapidly in subsequent periods—evidence shows that HGFs mostly
turn out to be “one-hit wonders.” As many as 50 percent of firms that experienced a
high-growth event in the previous three years are likely to exit the market altogether in
the following three to six years, while fewer than 15 percent are likely to repeat a
19 31/10/18 7:01 pm
xx Executive Summary
high-growth episode—illustrating the short-lived and episodic nature of firm growth.
Some firms move in and out of high growth, while others achieve high growth after a
decade or more of subpar growth performance. This evidence casts doubt on whether
high-growth—or any growth at all—is a permanent characteristic of any firm and sug-
gests instead that a “high-growth episode” is something that select few firms experience
at some point in their life cycles. Because all of the benefits of HGFs take place only
within these narrow windows, the fragile and elusive nature of high-growth events
means that targeting them may be neither feasible nor advisable.
What Could Give Rise to High Growth?
The findings in this book show that innovation, agglomeration and network econo-
mies, managerial capabilities and worker skills, global linkages, and financial develop-
ment contribute significantly to increasing the probability of a high-growth episode.
For instance, evidence from India shows that the link between innovation and firm
growth strengthens along the firm growth distribution, and operates via an interplay
between innovation and accessing foreign markets. Agglomeration and network econ-
omies offer learning and specialization opportunities due to greater firm density, which
in turn plays an important role in determining the likelihood of being an HGF. For
example, Ethiopian plants located in or close to large urban centers have a greater prob-
ability of attaining high-growth status compared with ones located farther away, while
in Thailand, firms that are more connected with others via ownership networks are also
more likely to experience high growth.
External market linkages—measured by a firm’s own exporting status, share of
exporters or FDI recipients in a given location or sector, or imports of technology—
significantly increase the probability of a high-growth event for firms in India, Hungary,
Mexico, and Tunisia. Firms that pay higher wages have a greater likelihood of subsequently
attaining high growth, and reflecting the key role that human capital plays in firm perfor-
mance. In particular, the contribution of founding managers and employees (as mea-
sured, for example, by experience in the formal sector, in a larger firm, and in management)
is found to be critical in determining future firm growth in Brazil. Finally, the likelihood
of attaining high growth also depends on firms’ ability to access finance, although given
the large number of other potential distortions in the business environment, the link can
only be robustly identified in countries with well-developed financial markets.
All these factors tend to be associated with higher firm productivity, and indeed
analysis in several countries reveals a direct link between firm productivity and the
likelihood of high growth. However, results from other countries are less encouraging,
highlighting a false equivalence between high growth and high productivity. Firms may
grow for a variety of reasons, reflecting high efficiency but also demand shocks, uncom-
petitive markets, or political connections (the second volume of the World Bank
Productivity Project, Cusolito and Maloney [2018]), presents the latest advances in
20 31/10/18 7:01 pm
Executive Summary xxi
productivity research). For example, data from Côte d’Ivoire indicate that there is little
overlap between a set of “efficient” HGFs (those firms that would attain HGF status if
resources across the economy were allocated according to firms’ productivity) and the
observed HGFs. These results show that productivity-limiting distortions not only
lower the overall incidence of high growth but also misallocate resources in a way that
allows less efficient firms to attain high growth—obscuring the relationship between
high growth and productivity. This offers a further nuance to the challenge of targeting
high-potential firms: in the absence of real-time data on firm productivity, using past
performance as a guide for supporting specific firms may exacerbate distortions rather
than reduce them.
Where Should the Authorities Direct Resources to
Support Firm Growth?
The search for the “right” firms to target is not new. However, the evidence presented in
this book shows that most public initiatives to identify and target HGFs are likely to be
misguided—buttressed by findings on the venture capital industry that show that even
in the hands of professional investors, success is most often random and most projects
lose money.
Existing efforts to support HGFs—identified through a review of 58 interventions
in 17 developing countries—are constrained by weak empirical foundations, poorly
articulated logical frameworks, and largely absent monitoring and evaluation systems
(including impact evaluations and cost-benefit analyses). Evidence also shows that it is
difficult to consistently identify high-potential firms before or at early stages of a high-
growth episode: the strike rate of predicting success for any set of methodologies,
including scoring by judges, predictive models, and machine learning approaches, is
between 2 and 12 percent. And the few characteristics that have some explanatory
power in predicting high growth, for example, age, gender, and IQ scores, can lead to
investment strategies that select the already better-off beneficiaries and may widen
rather than reduce existing inequities.
This book’s findings therefore suggest an important reorientation of policies to sup-
port firm growth from searching for high-potential firms toward the ABCs of growth
entrepreneurship: improving Allocative efficiency, encouraging Business-to-business
spillovers, and strengthening firm Capabilities. A large body of existing literature shows
that interventions aimed at supporting these ABCs are positively correlated with fur-
thering desirable outcomes such as firm productivity, while the evidence presented in
this book shows that they are also associated with a greater likelihood of a high-growth
episode. Policy makers wishing to reap the benefits of high firm growth may therefore
find greater returns in policies that support and encourage good practices such as
healthy firm entry, exit, and resource reallocation; improved access to finance and flex-
ible labor markets; better flows of knowledge across firms through tighter linkages to
21 31/10/18 7:01 pm
xxii Executive Summary
external markets, denser networks, and agglomeration; and stronger firm capabilities,
including innovation, managerial, and entrepreneurship skills.
In order to improve allocative efficiency, policy makers may wish to structure the
issue in terms of the standard productivity decomposition approaches, which consider
the three margins of entry, exit, and reallocation. Policies along the entry margin seek to
improve allocative efficiency by making it easier for new, potentially more productive
firms to enter the market. Conversely, policies along the exit margin seek to ensure that
less productive firms release their resources for more efficient use. Finally, policies along
the reallocation margin seek to improve the ability of existing firms to access resources
through more flexible factor and product market policies. For example, flexible labor
market policies that facilitate the ability of employees to bring their experience from
one firm to the next, as well as further steps in the financial reform agenda, can have
important positive implications for the ability of more efficient firms to grow.
To facilitate B2B spillovers through positive agglomeration economies, spatial poli-
cies can encourage more efficient land use, while transport policies can help reach spa-
tially optimal outcomes. Similarly, policies to attract high-quality FDI and connect
firms to export markets can encourage learning and quality upgrading, leading to a
greater likelihood of high firm growth. Direct instruments to facilitate knowledge
spillovers—such as science and technology parks, clusters, and network initiatives—
can also enhance the benefits of such connections for firm growth.
Policies to strengthen firm capabilities help firms innovate (which in the majority
of developing-country firms occurs in the absence of formal research and develop-
ment), improve managerial practices and access to technology, and acquire soft skills
that are being increasingly recognized as critical to firm success (even more so than
core business skills). Several types of instruments have been used to support the accu-
mulation of these capabilities, with varying success. Financial incentives include direct
instruments, such as vouchers, grants and matching grants, equity financing, and pub-
lic procurement, and indirect interventions, such as fiscal incentives and loan guaran-
tees. Inducement instruments and recognition awards, for example, prize competitions,
are nonmarket mechanisms to encourage efforts by firms and entrepreneurs to address
specific challenges. Government can offer various kinds of extension advisory services to
strengthen firms’ use of technology or to provide advice on business issues, including
the well-known examples of the Manufacturing Extension Partnership in the United
States, Fraunhofer Institutes and Steinbeis Centers in Germany, Japan’s Kohsetsushi
Centers and Productivity Centers, and SPRING and A*STAR agencies in Singapore.
Finally, incubators and accelerators provide access to physical space, advisory services,
mentorship, and perhaps access to finance at an early stage of a firm’s life cycle.
Given the wide menu and complexity of the available instruments, a key factor
determining success is the ability to match the instruments with the needs of firms and
the ability of public institutions to deliver these programs. In the first volume of the
22 31/10/18 7:01 pm
Executive Summary xxiii
World Bank Productivity Project, Cirera and Maloney (2017) develop the concept of
the “ capabilities escalator,” which helps match policy challenges with firm and institu-
tional capabilities, and provide some examples of practical applications of such an
approach.
In addition, three cross-cutting themes are a necessary condition to the success of
the ABCs of policy interventions. First, given the critical importance of accurately mea-
suring productivity and other variables that matter for policy choices, this book is also
a call for improving the quality and accessibility of firm-level data to enable evidence-
based decision making in developing countries. Second, there is an urgent need to radi-
cally expand the use of rigorous evaluations of policy interventions. Despite the large
number of initiatives underway to support firm growth, very few programs—whether
in developing countries or advanced economies—have undergone rigorous impact
evaluations or cost-benefit analyses. Embedding impact evaluations into program
design and implementation is critical to ensuring that public resources achieve the
desired outcomes efficiently and effectively. Third, institutional capabilities to imple-
ment policies need to be strengthened. In line with the “capabilities escalator” approach,
countries and agencies should gradually build their institutional capabilities to match
the ambition of policy instruments, which are currently often taken from high-income
countries without adaptation to local context. Ensuring that the relevant institutions
have the necessary human and financial resources and the right mandate, and com-
municate effectively in implementing the ABCs of growth entrepreneurship, will be
critical to the success of the new generation of policies to support firm growth.
Note
1. “Productivity isn’t everything, but in the long run it is almost everything” (Krugman 1994, 11).
References
Cirera, X., and W. F. Maloney. 2017. The Innovation Paradox: Developing-Country Capabilities and the
Unrealized Promise of Technological Catch-Up. Washington, DC: World Bank.
Cusolito, A. P., and W. F. Maloney. 2018. Productivity Revisited: Shifting Paradigms in Analysis and
Policy. Washington, DC: World Bank.
Krugman, P. 1994. The Age of Diminished Expectations. Cambridge, MA: MIT Press.
23 31/10/18 7:01 pm
24 31/10/18 7:01 pm
1
1. The Appeal of High Growth
High-growth firms (HGFs) are the dynamic core of an economy, set apart by their
disproportionate ability to generate output and create jobs. Evidence for high-income
countries shows that these firms form a small share of the total number of businesses—
often less than 10 percent—but account for more than half of the entire change in
employment and output. This chapter establishes the foundation for the overall book
by quantifying the contribution of HGFs to growth in developing countries, starting
with definitions of high growth and its incidence, and moving on to the importance of
HGFs in generating jobs and output and creating spillovers to non-HGFs.
Just as in high-income countries, the chapter’s findings confirm that HGFs—
whether defined by absolute growth thresholds or relative top performers, and whether
using employment or revenue as the main variable of interest—are a small group in
emerging market economies. For the 11 developing countries covered by this book,
the share of HGFs according to one of the most common definitions (from the
Organisation for Economic Co-operation and Development [OECD]) varies between
3 and 20 percent, similar to the range observed in high-income countries. But the
diversity in size, growth, and overall level of development across these economies is
well above that of the group of high-income countries, suggesting that HGF incidence
may be more akin to a statistical regularity in the distribution of firm growth rates
rather than a function of per capita incomes, sectoral growth rates, or measures of
market concentration.
Although their share in the overall firm count is small, it is difficult to overstate the
importance of this group of firms to economic performance. More than half of all new
jobs and sales in the economies studied in this book are created by In fact, in
nearly all cases, net employment and output growth would have been negative without
the positive contribution of these firms (that is, the non-HGFs destroy more jobs than
they create, and decline rather than grow in terms of sales). Although the group of
firms making these disproportionate contributions to employment and to sales are
usually not the same (correlation coefficients between the two sets are or lower), to
paraphrase Paul Krugman’s famous quote, high growth is nearly everything when it
comes to determining an economy’s overall
In addition to their disproportionate contribution to jobs and output creation,
HGFs are capable of generating significant spillovers that benefit other firms. While
evidence for horizontal (same sector) spillovers is mixed—given that HGFs may
1 31/10/18 7:01 pm
2 High-Growth Firms
transfer knowledge and create networks, but also raise competition and push down
prices—the evidence on vertical spillovers, that is, benefiting from being a buyer from
or a supplier to an HGF, is stronger. These extraordinary abilities of HGFs are what
make them an interesting subject for academics and an attractive target for policy
makers keen to boost economic performance.
Definitions
HGF definitions could fill a small zoo with real and fantastical creatures. Birch (1981)
defines a “gazelle” (or HGF) as a firm that has at least $100,000 (roughly $250,000
today) in annual revenues and sustains 20 percent annual revenue growth over a four-
year period. SBA Office of Advocacy (2008) differentiates between mice (small firms
with fewer than 20 employees), elephants (large firms with more than 500 employees),
and gazelles by using employment as an indicator for growth; Nightingale and Coad
(2014) introduce “muppets” to contrast with gazelles, and Ferrantino et al. (2012) dis-
cussed “gazillas”—large firms that continue growing rapidly and make a large contri-
bution to employment growth. There are also “stars” (Ayyagari, Demirguc-Kunt, and
Maksimovic 2018; Furman and Orszag 2015) and “superstars” (Autor 2017; World
Bank 2019), defined as firms in the top tier of the distribution of returns on invested
capital, productivity, and market share. Finally, Lee (2013) defines “unicorns” as pri-
vately held start-up companies valued at more than $1 billion.
The various definitions of HGFs can be broadly grouped into three sets:
■■ The absolute definitions, such as Birch (1981) and the often-used OECD defini-
tion, set a minimum rate and duration of growth. According to the OECD-
Eurostat Manual on Business Demography Statistics (2007), an HGF is one that
(1) initially possesses 10 or more employees or that has at least four times
national per capita income in annual revenues, and (2) experiences average
annualized employment or revenue growth of greater than 20 percent over a
three-year period.
■■ The relative definitions classify HGFs as those in the top percentiles of firms in
the distribution of employment or revenue growth (Haltiwanger et al. 2017), or
top percentiles of firms in the distribution of the Birch index (United Kingdom,
Department of Business Innovation and Skills 2014).3
■■ The distributional definitions are based on specific properties of the distribution
of firm growth, most often attempting to identify a threshold in which the right
tail of the (usually Laplace) distribution of firm growth rates converts to a power
law distribution (Halvarsson 2013). They combine certain features of absolute
and relative definitions, but are computationally intensive to implement.
This book studies HGFs using high-quality longitudinal data sets in Brazil, Côte
d’Ivoire, Ethiopia, Hungary, India, Indonesia, Mexico, South Africa, Thailand, Tunisia,
and Turkey. The selection of countries reflects in large part data availability, since
2 31/10/18 7:01 pm
The Appeal of High Growth 3
tracking down HGFs requires wide national coverage and the ability to follow firms
over time, whereas panel surveys of firms in developing countries remain rare and
accessing the existing ones is often a challenge. Even so, the data sets used here cover all
six World Bank regions as well as diverse income levels and very different growth per-
formances (figure ).
To study HGFs in these countries, this book uses both absolute (OECD) and relative
(top 10 percent of firms by the Birch index) definitions of high The advan-
tages of the absolute definition are that it is simple, easy to apply, and ensures that the
set of HGFs in one country is similar (at least in terms of growth rates) to the set of
HGFs in another. The disadvantages are that the growth threshold is arbitrary and that
in some cases (for example, during economic downturns or in smaller surveys) there
may be too few, or no, HGFs because the right tail of the firm growth distribution thins
rapidly. Moreover, using the rate of growth (as in the OECD definition) biases the
sample of HGFs toward smaller firms that, even as a group, may contribute little
to economy-wide job creation but can achieve rapid growth by adding just a few
employees. To maximize cross-country comparability and minimize the variation in
including micro firms, this book (as in the OECD definition) imposes a minimum size
threshold of 10 employees for all countries (including the United States), except in
Côte d’Ivoire (where the cutoff is 5 employees), and Indonesia and Turkey (where the
data are only collected for enterprises with more than 20 employees).5
For the absolute high-growth indicator based on sales, this book similarly limits
observations to firms with 10 or more employees, rather than introducing yet another
(sales-based) threshold. However, there are two countries, India and Thailand, for
which no employment data are available. The case of India is simpler because the data
set is a sample of firms that are listed on the stock exchange and, by definition, these are
relatively large firms. In the case of Thailand, where the data set is composed of all reg-
istered firms, including some micro firms, this book uses an estimated cutoff that
approximates a distribution of firms with 10 or more
When comparing employment-based with revenue-based HGFs, studies for differ-
ent countries reach varying conclusions: the two sets identify similar firms in the
United States (Haltiwanger et al. 2017) but substantially different ones in the United
Kingdom (Du and Temouri 2015). Between the two options, this book emphasizes
employment-based definitions of high growth because creating good-quality jobs is a
major pathway for reducing poverty and boosting shared prosperity. Thailand and
India are two exceptions, where the book relies exclusively on a revenue-based defini-
tion because employment information is not available in the data sets used here
(annex 1A provides details on the data sets). Where relevant, the book also notes when
using revenue-based definitions leads to important changes in findings.
Unlike absolute definitions, relative concepts of HGFs ensure more balanced coverage
across countries. And the Birch index favors larger firms, so the HGFs are more likely to
3 31/10/18 7:01 pm
4 High-Growth Firms
have a significant impact on job creation. Nonetheless, the average growth rate of HGFs
in one country may differ substantially from that of HGFs in another, and in some cases
HGFs may grow very little if at all (for example, if all firms are contracting, then a relative
definition will assign HGF status to those firms that contracted the least).
In summary, the definitions of HGFs used in this book are as follows:
1. OECD. HGFs are firms that employ more than 10 workers (including owners
but excluding unpaid workers) and whose employment grows at an average
annual rate of 20 percent or more over a period of three consecutive As a
further robustness check, a variant of this definition imposes an additional
restriction that employment growth must be positive in each of the three years.
2. Birch. HGFs are firms that employ more than 10 workers (including owners but
excluding unpaid workers) and whose employment growth places them in the
top 10 percent of the Birch index of all firms in the economy, with the index
defined over a period of three consecutive As a further robustness check,
a variant of this definition imposes an additional restriction that employment
growth must be positive in each of the three years.
Incidence
Regardless of the specifics, all HGF definitions seek to identify firms that are high per-
formers and are “sufficiently” far apart from the average or median firm. As such, it is
perhaps not surprising that there is enough commonality across definitions and stud-
ies, at least when it comes to the incidence of high growth. For example, Bravo-Biosca,
Criscuolo, and Menon (2016), following the OECD definition, show that the share of
HGFs in 10 high-income economies varies between 3 percent in Austria and Norway to
some 6 percent in Spain, the United Kingdom, and the United States. Other studies
establish a similar if somewhat broader range: HGF incidence has been documented to
vary from less than 2 percent in Austria, Germany, Italy, the Netherlands, Norway, and
Poland (Goedhuys and Sleuwaegen 2010) to 5 percent in Finland (Deschryvere 2008),
6 percent in Sweden (Daunfeldt et al. 2013) and the United Kingdom (Anyadike-Danes
et al. 2009), up to 10 percent in the Republic of Korea, and between 5 and 15 percent in
the United States (Choi et al. 2017; Decker et al. 2014).9 Using a variation of the OECD
definition that requires annual growth of 20 percent per year or more and a minimum
threshold of 15 employees, Hoffmann and Junge (2006) and Petersen and Ahmad
(2007) find that HGFs account for 5–6 percent of all firms across 17 high-income
countries. Interestingly, the few available studies on developing countries also suggest a
similar range; for example, a study of 11 African nations using the World Bank’s
Enterprise Surveys finds that the HGF incidence for these economies is about 6 percent
(Goedhuys and Sleuwaegen 2010).
Figure plots the incidence of HGFs across the 11 country data sets analyzed in this
book and benchmarks the results against the United States. For each country and
4 31/10/18 7:01 pm
The Appeal of High Growth 5
FIGURE Incidence of High Growth
20
.3
Sh
ar
e
of
H
G
Fs
(%
)
7.
5
17
.3
3.
5
12
.0
19
.4
3.
1
18
.1 20
.6
9.
8
14
.8
22
.8
7.
6
17
.6
22
.8
4.
1
9.
7
13
.7
4.
8
0
5
10
15
20
25
Côte d’Ivoire Ethiopia Hungary India Indonesia Thailand
c. Share of HGFs, sales-based, OECD (%)
OECD1 OECD3OECD2
Sh
ar
e
of
H
G
Fs
(%
)
Sh
ar
e
of
H
G
Fs
(%
)
Sh
ar
e
of
H
G
Fs
(%
)
25
.1
8.
8
6.
5
15
.7
1.
7
8.
2
13
.7
1.
7
16
.0 18
.2
7.
3
5.
7 7.
5
1.
4 3.
9
4.
6
17
.3
23
.7
6.
3
14
.0 17
.1
6.
5
21
.3
28
.2
11
.2
5.
2 6.
5
2.
7
0
10
20
30
Brazil Côte
d’Ivoire
Ethiopia Hungary Indonesia Mexico South
Africa
Tunisia Turkey United
States
a. Share of HGFs, employment-based, OECD (%)
OECD1 OECD3OECD2
b. Share of HGFs, employment-based, Birch (%)
Birch1 Birch2 Birch3
25
.0 3
0.
8
10
.7
5.
1
12
.5
1.
8 5
.9 9
.9
1.
3
29
.2 33
.1
11
.8
7.
6 9.
9
1.
6
13
.9
16
.1
12
.8 16
.8
5.
1
28
.0 3
4.
1
10
.7
20
.8 2
7.
6
10
.9
7.
7 9.
5
3.
4
0
10
20
30
40
Brazil Côte
d’Ivoire
Ethiopia Hungary Indonesia Mexico South
Africa
Tunisia Turkey United
States
d. Share of HGFs, employment-based, Davis, Haltiwanger, and Schuh 1996 (%)
Brazil Côte
d’Ivoire
Ethiopia Hungary Indonesia Mexico South
Africa
Tunisia Turkey United
States
0
5
10
15
Source: Elaboration using national survey and census data.
Note: OECD1 and Birch1 incidence are calculated as the number of HGFs high-growth firms (HGFs) in time t (based on either definition)
divided by the total number of firms with nonzero employment in time t. OECD2 and Birch2 are calculated as the number of HGFs in
time t (based on either definition) divided by the total number of firms with non-zero employment in time t and t−3 (only firms that are
three years of age or older are included in the numerator and denominator). OECD3 or Birch 3 are calculated as OECD1 or Birch1, with
the additional requirement that a firm can be classified as HGF only if it registers positive employment or sales growth in t, t−1, and
t−2. The Davis, Haltiwanger, and Schuh (1996) approach calculates growth rates as
( )
=
−
+
−
−
i,t
i,t i,t
i,t i,t / 2
3
3
g
L L
L L
, g
i,t
∈ [–2,2]. Firms that
employ more than 10 workers (including owners but excluding unpaid workers) are ranked by values of g
i,t
, from smallest to largest,
and those with values of g
i,t
above the 90th percentile are classified as HGF (that is, HGF
i,t
= 1 if g
i,t
> P 90(g
t
)). In each panel, incidence
is calculated for each year and then an unweighted average is computed over the entire sample period. See annex 1A for more details.
OECD = Organisation for Economic Co-operation and Development.
5 31/10/18 7:01 pm
6 High-Growth Firms
definition, the figure shows three sets of columns: the first column, labeled OECD1 (pan-
els a and b) or Birch1 (panel c), divides the number of HGFs by the total number of firms
in a given year (more precisely, it divides the number of firms that experienced a high-
growth episode between periods t–3 and t by the number of firms that are observed in
period t). This is perhaps the most intuitive measure, although it is clearly biased down-
ward because it includes all firms that started in periods t–2, t–1, and t in the denomina-
tor but not in the The second column, labeled OECD2 or Birch2, corrects
for this bias by limiting the denominator to firms that entered the market in t−3 or earlier,
ensuring that a three-year growth rate can be calculated for each firm in the sample. For
example, for a three-year window from 2015 to 2018, this metric would only cover firms
that have nonzero employment in both the starting and ending year. The final column,
labeled OECD3 or Birch3, imposes an additional requirement that firms must register a
nonnegative growth rate in each year during the three-year period, and divides this num-
ber by all firms operating in the current period (that is, uses the same denominator as
OECD1 or Birch1). For each country, the shares in each column are averaged over the
entire sample period to minimize the impact of business cycles, although the picture is
not very different from a common sample period of 2005–08, which captures most of the
data sets analyzed for this
Several insights emerge from figure . First, there is relatively limited variation in
the share of HGFs across countries, particularly when taking into account the wide
range of income levels and country characteristics of the economies considered, the
HGF incidence observed in developing economies is within the range reported in the
literature for high-income Second, there is no obvious relationship between
a country’s level of development (measured by per capita income) and the incidence of
high growth (see also the discussion later in this section). Third, firm entry and exit
play a large role in most countries; using the OECD2 or the Birch2 variant, which does
not consider recent entrants, substantially increases the incidence, and in one case,
Côte d’Ivoire, more than doubles it. However, as shown in panel d, which plots the
Davis, Haltiwanger, and Schuh (1996) growth rates that capture the entry and exit mar-
gins, the first two points remain valid regardless of how one accounts for the impact of
entry and exit. Fourth, firm growth is highly volatile; limiting the definition of HGFs
only to firms that do not experience negative growth brings down the incidence by half
or more, suggesting that most HGFs attain the threshold through a high-growth event
in just one year, or at most two The patterns are similar regardless of whether
one uses the absolute (OECD) or relative (Birch) definitions of high growth, although
the incidence calculated with the Birch definition is generally lower because the metric
is biased toward larger Fifth, similar to high-income countries, sales-based inci-
dence is well above employment-based incidence, suggesting that most firms find it
easier to increase sales than raise
How similar are the sets of firms captured by various definitions of high growth?
Studies usually find low correlation between absolute and relative growth in
6 31/10/18 7:01 pm
The Appeal of High Growth 7
indicators such as sales, employees, profit, productivity, equity, assets, and so on. For
example, using data on all firms registered in Sweden between 1994 and 1998,
Shepherd and Wiklund (2009) find that some pairs of growth measures were highly
correlated (for example, the growth of sales and of employees, defined in absolute
terms), while others were not (for example, the growth of sales and of assets, defined
in relative terms). Defining HGFs as the top 1 percent of the fastest-growing firms
in Sweden, Daunfeldt et al. (2013) find that firms selected on the basis of employ-
ment growth were inversely correlated with those selected on the basis of productiv-
ity growth. Similar findings hold for South Africa, for which Mamburu (2017) finds
that the correlation coefficients between the samples generated by 10 alternative
definitions of HGFs were generally in the – range. Their work identifies
18 different definitions based on growth or changes in levels or level of perfor-
mance. The overlap of those selected based on employment and those based on
value added are also fairly small. Thus, the firms that perform well on one dimen-
sion do not necessarily perform well on the other. The OECD definition, since it
covers so many more firms, has more overlaps than others although for most defini-
tions the overlap is less than 25 percent, often a lot less. The extent of the overlap is
a little greater with value added definitions; those with better value added perfor-
mance tend to do somewhat better on employment than vice versa. However, it is
clear that the choice of measuring firms based on employment or value added will
give largely different pools of
In the country data sets analyzed for this book, the exact definitions of high growth
(for example, OECD versus Birch) appear to be less important than the choice of the
underlying metric (employments versus sales). This is illustrated in table , which
shows the correlations across alternative definitions of HGFs for a select set of diverse
countries. In all instances, the correlation across definitions for the same set of metrics
(employment or sales) is much higher than the correlation across metrics.
Although results in figure allude to a lack of relationship between a country’s
level of development and its HGF incidence, it is difficult to formally test this hypoth-
esis with only 12 countries. As an alternative, this book uses the HGF incidence observed
in the World Bank’s Enterprise Surveys (WBES) to explore the relationship between
HGF shares and per capita income (HGF shares tend to be highly correlated across
national data sets and the WBES; see box for a more detailed discussion). Figure
plots the results for all developing countries, as well as showing them separately for
three main income groups. In all cases, there is no clear relationship between HGF
incidence and a country’s level of development.
While this finding may come as a surprise (for example, for policy makers who may
wish to target the HGF share of some benchmark country), it underscores a broader
point of the potential false equivalence between greater incidence of high growth and
healthy firm dynamics. Consider an example of two firms in different countries
7 31/10/18 7:01 pm
8 High-Growth Firms
receiving a positive demand shock. One firm, operating in a relatively distortion-free
environment, can instantly scale its operations and hire more workers to meet new
demand; in the data, this firm will show at most one year of rapid employment growth.
The second firm, operating under significant factor and input market constraints, can
only slowly add workers over time (growing from, say, 10 employees in year t to
12 workers in year t+1, from 12 to 15 in year t+2, and from 15 to 20 in year t+3). This
firm will be recorded in the data as HGF, even though it is clearly not operating as
efficiently as the first. Hence, it is possible that some rates of high growth over pro-
longed periods capture difficulties in adjusting to optimum scale and may therefore be
reflective of resource misallocation rather than efficient dynamics.
If per capita incomes do not drive the variation in HGF incidence, it may be the case
that sectoral variables play a role. For example, increased market concentration may be
associated with greater HGF incidence if it is indicative of “up-or-out” dynamics in
which unsuccessful firms exit or are bought out by more successful competitors who
TABLE Correlations across HGF Definitions
(partial correlation coefficients)
HGF Definition
OECD employment OECD sales Birch employment Birch sales
Côte d’lvoire
OECD employment 1
OECD sales 1
Birch employment 1
Birch sales 1
Ethiopia
OECD employment 1
OECD sales 1
Birch employment 1
Birch sales 1
Indonesia
OECD employment 1
OECD sales 1
Birch employment 1
Birch sales 1
Hungary
OECD employment 1
OECD sales 1
Birch employment 1
Birch sales 1
Source: Elaboration using national survey and census data.
Note: HGF = high-growth firm; OECD = Organisation for Economic Co-operation and Development.
8 31/10/18 7:01 pm
The Appeal of High Growth 9
BOX
National Firm Data versus Enterprise Surveys
Most of the data sets used in this book are drawn from national surveys and census data, gaining
in the depth of country coverage at the expense of cross-country comparability afforded by instru-
ments like the World Bank’s Enterprise Surveys (WBES). To test the comparability of the two
sources, figure plots the incidence of high-growth firms (HGFs) in the national surveys and
census data against the incidence calculated using the The solid green line in the figure is
a 45-degree line: when a point appears below the line, it means that high-growth incidence in
national surveys is lower than in the WBES.
The results suggest that HGF incidence is highly correlated across the two data sources when
using the OECD definition (correlation coefficient ) and somewhat correlated when using the
Birch definition (excluding Brazil, the correlation coefficient is ). Moreover, in most cases the
share calculated using the WBES is higher than when using national-level data sets—and much
more so for the Birch definition of HGFs (with the exception of Brazil). This may be because the
WBES primarily target larger, registered firms, and as a result may oversample HGFs with more
than 10 employees (at least for the countries shown in the figure).
a. Table in annex 1A provides the relevant firm counts for the two data sources.
FIGURE HGF Incidence in National Data Sets and Enterprise Surveys
Source: Elaboration using WBES and national survey and census data.
Note: The figure uses OECD1 and Birch1 measures of high-growth firm (HGF) incidence (see the note to figure ). For both
national surveys and enterprise surveys, firms are excluded in all years in which they have fewer than 10 employees.
OECD = Organisation for Economic Co-operation and Development.
Brazil (2009)
Côte d’Ivoire
(2009)Hungary (2013)
Indonesia (2014) Tunisia (2013)
Turkey (2013)
0
5
10
15
20
25
0 5 10 15 20 25
N
at
io
na
l s
ur
ve
ys
Enterprise surveys
a. Share of HGFs, employment based, OECD (%)
Brazil (2009)
Côte d’Ivoire
(2009) Hungary (2013)
Indonesia (2014)
Tunisia (2013)
Turkey (2013)
0
5
10
15
20
25
30
8 10 12 14 16 18
N
at
io
na
l s
ur
ve
ys
Enterprise surveys
b. Share of HGFs, employment based, Birch (%)
9 31/10/18 7:01 pm
10 High-Growth Firms
FIGURE HGF Incidence and per Capita Income
0
10
20
30
Sh
ar
e
of
H
G
Fs
(%
)
Log GDP per capita, PPP
5
10
15
20
25
30
Sh
ar
e
of
H
G
Fs
(%
)
Log GDP per capita, PPP
Low- and middle-income countries Low-income countries
0
10
20
30
Sh
ar
e
of
H
G
Fs
(%
)
Log GDP per capita, PPP
Lower-middle-income countries
0
5
10
15
20
25
Sh
ar
e
of
H
G
Fs
(%
)
Log GDP per capita, PPP
Upper-middle-income countries
a. Employment-based, OECD
5
10
15
20
Sh
ar
e
of
H
G
Fs
(%
)
Log GDP per capita, PPP
Log GDP per capita, PPP
10
12
14
16
18
Sh
ar
e
of
H
G
Fs
(%
)
Low- and middle-income countries Low-income countries
8
10
12
14
16
18
Sh
ar
e
of
H
G
Fs
(%
)
Log GDP per capita, PPP
Lower-middle-income countries
10
12
14
16
18
20
Sh
ar
e
of
H
G
Fs
(%
)
Log GDP per capita, PPP
Upper-middle-income countries
b. Employment-based, Birch
Source: Elaboration using World Bank Enterprise Survey data.
Note: HGF = high-growth firm; OECD = Organisation for Economic Co-operation and Development; PPP = purchasing power parity.
10 31/10/18 7:01 pm
The Appeal of High Growth 11
absorb the labor and capital released by exiting firms. On the other hand, high rates of
entry and entrepreneurship (for example, due to a good business environment) may
simultaneously lead to a decline in market concentration and an increase in the share
of HGFs. Another channel could be the variation in sectoral rates of growth; to the
extent that HGF prevalence varies substantially across sectors (see the discussion in
the following chapter), heterogeneity in sectoral composition and growth rates across
countries may drive overall differences in the share of HGFs.
Empirical support for these channels in the countries analyzed for this book is, at
best, limited. Estimates using employment data in Brazil, Côte d’Ivoire, Ethiopia, and
Indonesia, and sales in India, show that higher industry concentration is generally posi-
tively associated with HGF incidence—except in Côte d’Ivoire and Brazil, where the
relationship is negative (figure ; all regressions include industry and year controls
so that the estimates are driven by changes in concentration across sectors rather than
the initial values). Sectoral growth patterns also do not appear to have a significant asso-
ciation with HGF shares, except in Indonesia where the relationship is strongly positive.
FIGURE HGF Incidence and Industry Concentration or Growth
Source: Elaboration using national survey and census data.
Note: The figure is a rope-ladder representation of estimated coefficients and 95 percent confidence bands from regressions of high-
growth firm (HGF) incidence (OECD, employment-based except for India where it is sales-based) on variables on the X-axis. Industry
concentration is measured with normalized Herfindahl indexes. Regressions are estimated separately for each country at a 4-digit
industry level, using national data sets (see annex 1A for data details). All regressions are estimated by ordinary least squares and
include industry and year fixed effects. Results are robust to including both types of sectoral characteristics in the same model as well
as their interactions. OECD = Organisation for Economic Co-operation and Development.
–
Es
tim
at
ed
c
oe
ffi
ci
en
t
Côte
d’Ivoire
Brazil Ethiopia India Indonesia Côte
d’Ivoire
Brazil Ethiopia India Indonesia
Industry concentration Industry growth
0
Effect of change in industry concentration or growth on HGF incidence
11 31/10/18 7:01 pm
12 High-Growth Firms
However, the sign and significance of the results are sensitive to the level of aggregation
(for example, whether they are estimated at the 4-digit or 2-digit industry level or
whether industry growth is measured using employment or sales).17
Jobs and Output Creation
The academic and policy interest in HGFs stems primarily from their disproportionate
contribution to jobs and output creation. In the United Kingdom, 6 percent of all firms
with 10 or more employees created 54 percent of jobs between 2005 and 2008 (Anyadike-
Danes et al. 2009).18 Likewise, in Sweden, 6 percent of the firms created 42 percent of
jobs over the same period (Daunfeldt et al. 2013),19 while in Finland fewer than 5 per-
cent of firms created 90 percent of jobs during 2003–06 (Deschryvere 2008). Defining
HGFs as the set of firms expanding their employment by more than 25 percent per year,
Decker et al. (2014) find that in the . HGFs constitute 10–15 percent of firms but
create 50–60 percent of output and jobs (Decker et al. 2014; Haltiwanger et al. 2017).20
Similar estimates on job gains for Canada (Quebec), France, Italy, the Netherlands,
and Spain were produced by Schreyer (2000), although exact definitions of HGFs in
this particular study varied by For example, HGFs account for more than
50 percent of job creation in France, nearly 65 percent in the Netherlands and close to
90 percent in Spain. When it comes to output growth, Daunfeldt, Elert, and Johansson
(2014) find that HGFs always contribute positively to sales growth in Sweden.
In quantifying the role of HGFs in job and output growth, it is important to distin-
guish between gross and net contributions (in the previous paragraph, Anyadike-Danes
et al. (2009), Daunfeldt et al. (2013), and Deschryvere (2008) report net numbers, while
Decker et al. (2014) and Schreyer (2000) report gross figures).22 The gross contribution
only considers firms that have added jobs or increased output during a (three-year)
period, and calculates the share of HGFs in total jobs or output created. By construc-
tion, this metric ranges between 0 and 100 percent and gives a sense of which firms
create new jobs or sales in the economy. The net contribution is the difference between
gross job or output creation and gross job or output destruction during the period.
This concept gives a complete picture of changes in employment or sales over a given
period, but can be more difficult to interpret. When using absolute definitions of high
growth such as the OECD’s, HGFs by default only create jobs but do not destroy
them—whereas other firms may either expand or contract. As a result, the net contri-
bution of HGFs can be greater than 100 percent (if HGFs create 100,000 jobs and the
rest of the firms destroy 50,000, for example) or even negative (if HGFs again create
100,000 jobs but the rest of the firms destroy 500,000). And with relative definitions of
high growth, all firms could hypothetically destroy jobs but HGFs could still make a
positive net In the case of Vietnam, for instance, Aterido and Hallward-
Driemeier (2018) find that high-performing firms contributed between 70 and
142 percent more to net job creation than all firms, depending on the definitions
used, while these firms account for only a small share of all firms.
12 31/10/18 7:01 pm
The Appeal of High Growth 13
Figure (panel a) shows the gross and net contributions of HGFs (OECD defi-
nition) to employment growth, focusing as before on firms with 10 or more workers
in manufacturing and services sectors. In Côte d’Ivoire, Ethiopia, and Indonesia,
HGFs make up less than 10 percent of the firm count yet create more than one-half
of all new jobs (panel a). In Hungary, HGFs account for 16 percent of firms but con-
tribute to nearly half of gross job creation. In Brazil and Turkey, they represent about
20 percent of firm population and yet generate nearly 60 percent of new jobs.
Moreover, the panel b of figure shows that, in all countries, firms other than HGFs
experienced a net decline in employment, so that the only net jobs generated were
those created by the HGFs.
FIGURE HGFs Contribute Disproportionately to Employment Growth
Source: Elaboration using national survey and census data.
Note: High-growth firms (HGFs) are defined using employment-based metrics. HGF incidence is defined as OECD1 (see the note to
figure ). Contributions are calculated for each year and then an unweighted average is computed over the entire sample period.
OECD = Organisation for Economic Co-operation and Development.
0
20
40
60
80
Brazil Côte d’Ivoire Ethiopia Hungary Indonesia Turkey
a. Contribution to gross job creation (%)
Incidence of HGFs (OECD) Contribution to gross job creation
−
−
−
−
−
−
−5
0
5
10
15
Brazil Côte d’Ivoire Ethiopia Hungary Indonesia Turkey
b. Contribution to net job creation (%)
HGFs (OECD) Non-HGFs
C
on
tr
ib
ut
io
n
to
g
ro
ss
jo
b
cr
ea
tio
n
(%
)
C
on
tr
ib
ut
io
n
to
n
et
jo
b
cr
ea
tio
n
(%
)
13 31/10/18 7:01 pm
14 High-Growth Firms
Similar conclusions hold across firm cohorts and industries, as shown by data from
Brazil and Mexico. Young Mexican non-HGFs experienced a decline in net employ-
ment across a range of cohorts and manufacturing industries, meaning that all job
creation by young firms in manufacturing was done by HGFs (figure , panel a). In
Brazil, HGFs and non-HGFs enter the market at approximately the same size, which
means that at birth, future HGFs make up just percent of employment of their birth
cohort (figure , panel b). However, because of their rapid growth—and exit of some
of the less dynamic firms—the share of HGFs in total cohort employment rises to more
than 36 percent 13 years later.
FIGURE HGF Contributions to Employment Growth in Brazil and Mexico
Source: Sanchez Bayardo and Iacovone 2018 for panel a; Bastos and Silva 2018 for panel b.
Note: NAICS code 31 includes food manufacturing, beverages and tobacco products, textile, apparel and leather and allied product
manufacturing; NAICS code 32 includes wood, paper, printing, petroleum and coal, chemicals, plastics and rubber, non-metallic min-
eral products; NAICS code 33 includes primary metal manufacturing, fabricated metals, machinery, computer and electronics, electri-
cal equipment, transport equipment, furniture and other manufacturing not included elsewhere. Together NAICS codes 31–33
constitute all manufacturing activities. HGF = high-growth firm; NAICS = North American Industry Classification System.
–
– –8 – 0 –
59
–20
–10
0
10
20
30
Em
pl
oy
m
en
t g
ro
w
th
(%
)
40
50
60
70
80
All 1994 1999
By cohort
a. Mexico, employment growth in the firms’ first 10 years
By industry
2004 NAICS 31 NAICS 32 NAICS 33
High growth Non high growth
b. Brazil, HGF employment share in the birth cohort
0
10
20
30
40
H
G
F
em
pl
oy
m
en
t s
ha
re
(%
)
0 1 2 3 4 5 6 7 8 9 10 11 12 13
Years after birth
% All firms % Birth cohort
14 31/10/18 7:01 pm
The Appeal of High Growth 15
FIGURE HGFs Account for the Majority of Growth in Sales
Source: Elaboration using national survey and census data.
Note: High-growth firms (HGFs) are defined using sales-based metrics. HGF incidence is defined as OECD1 (see the note to figure ).
Contributions are calculated for each year and then an unweighted average is computed over the entire sample period.
OECD = Organisation for Economic Co-operation and Development.
0
20
40
60
80
Côte d’Ivoire Ethiopia Hungary India Indonesia Turkey
a. Contribution to gross sales growth (%)
Incidence of HGFs (OECD) Contribution to gross sales increase
−
−
−
−
−
−20
−10
0
10
20
C
on
tr
ib
ut
io
n
to
n
et
s
al
es
g
ro
w
th
(%
)
C
on
tr
ib
ut
io
n
to
g
ro
ss
s
al
es
g
ro
w
th
(%
)
30
Côte d’Ivoire Ethiopia Hungary India Indonesia Turkey
b. Contribution to net sales growth (%)
HGFs (OECD) Non-HGFs
Just as with employment, HGFs also make a disproportionate contribution to out-
put growth. Using the OECD definition with sales-based metrics, figure shows that
HGFs account for some 8–22 percent of the total number of firms in Côte d’Ivoire,
Ethiopia, Hungary, India, Indonesia, and Turkey but contribute between 49 and
83 percent of the total change in output. And in five of the six cases—Côte d’Ivoire,
Ethiopia, Hungary, Indonesia, and Turkey—HGFs are the only positive contributors to
growth in output, with the rest of the firms in the economy experiencing a decline in
While that is not the case in India (perhaps because the data set is composed of
the more successful and large firms that are registered on the stock exchange), HGFs
there still account for nearly two-thirds of the total change in output.
15 31/10/18 7:01 pm
16 High-Growth Firms
Linkages and Spillovers
Beyond the boundaries of the firm itself, HGFs have been documented to bring wider
economic and social benefits, including facilitating the growth of other firms in the
same locality (Mason, Bishop, and Robinson 2009) and particularly in industrial clus-
ters (Stam et al. 2009; Brown 2011). Evidence from 43 industries in the Netherlands
over 12 years shows that a higher ratio of HGFs in a particular sector has a positive
impact on subsequent industry growth (Bos and Stam 2014). Their “pull factor” facili-
tates the convergence of less productive firms to the national frontier (Bartelsman,
Haskel, and Martin 2008) and, when markets for production inputs are competitive,
HGFs are able to increase overall efficiency by attracting resources away from less pro-
ductive firms (Haltiwanger et al. 2017).
A large literature has studied the spillover effect from the entry of multinational
enterprises (MNEs) (for surveys of this literature, see Görg and Strobl 2001; Görg and
Greenaway 2004; Crespo and Fontoura 2007; Meyer and Sinani 2009; Havranek and
Irsova 2011).25 A key distinction in this literature is between within-industry (horizon-
tal) and between-industry (vertical) spillovers, with several specific mechanisms for
multinational entry to affect the performance of domestic firms. One specific channel is
the transfer of soft technologies, such as management skills; for example, Javorcik (2004)
finds that contacts between partially foreign owned firms and their local suppliers in
Lithuania facilitate positive productivity Since similar logic and channels
may apply to linkages with HGFs, this book follows the FDI literature by differentiating
between three types of spillovers: horizontal, backward vertical, and forward vertical.
The horizontal spillovers (HS) measure for year t is the share of firms that have
become HGFs between year t and t + 3 in the same industry and region:
∑
=
∈
HS
HGF
N
jrt
i jr
it
jrt
where N
jrt
is the number of firms in industry j in region r and year t.
The forward and backward spillovers (FS and BS, respectively) measures show the
average share of HGFs in supplier and buyer industries in the region, weighted by the
volume of intermediate goods flows across industries:
FS
jrt
= S
m
a
mj
HS
jrt
and BS
jrt
= S
m
a
jm
HS
jrt
where a
mj
are the normalized coefficients from the input-output matrix representing
(domestic) intermediate goods flows from industry m to j. Because industries with
many HGFs may also have high FDI shares, confounding HGF spillovers with those
from MNEs, this book controls for backward and forward foreign presence by weight-
ing the share of foreign-owned firms by the same weights as that obtained from input-
output tables (following Javorcik 2004).
16 31/10/18 7:01 pm
The Appeal of High Growth 17
In Hungary, horizontal spillovers from the increased presence of HGFs tend to be
either insignificant or negative, suggesting that the competition generated by HGFs
may lead to lower revenues and profits for other firms (figure , panel a).27 By com-
parison, vertical spillovers from HGFs tend to be positive and significant (figure ,
panel b). A higher share of HGFs in supplier industries (forward spillovers) is associ-
ated with significantly faster growth in employment and revenue, likely due to improved
access to A higher share of HGFs in buyer industries (backward spillovers) is
associated with significantly larger increases in wages, productivity, and profitability
FIGURE Buying from or Supplying to HGFs Improves Firm Performance in Hungary
Source: Muraközy, de Nicola, and Tan 2018.
Note: The figures are rope-ladder representations of estimated coefficients and 95 percent confidence bands from a regression of the
growth rate in the variables on the X-axis (log differences between years t and t+3) on the value of the horizontal or vertical spillovers
in year t. Industry-year, region-year, and firm-level fixed effects are included in each estimate, and the regressions also control for
initial total factor productivity (TFP) employment, and exporting status. The sample includes years 2000, 2003, 2006, and 2009, and
observations exclude “singletons,” that is, when an observation is “dummied out” by the fixed effects. Standard errors are clustered
at both the industry-region-year and firm level.
–
–
0
–
–
0
Ba
ck
w
ar
d
Fo
rw
ar
d
Ba
ck
w
ar
d
Fo
rw
ar
d
Ba
ck
w
ar
d
Fo
rw
ar
d
Ba
ck
w
ar
d
Fo
rw
ar
d
Ba
ck
w
ar
d
Fo
rw
ar
d
Ba
ck
w
ar
d
Fo
rw
ar
d
Employment Revenue TFP Average wage Exporter Return on
assets (right
scale)
b. Vertical spillovers
–
–
–
–
–
0
–
–
–
–
–
–
–
0
Employment Revenue TFP Average wage Exporter Return on
assets (right
scale)
a. Horizontal spillovers
Es
tim
at
ed
c
oe
ffi
ci
en
t
Es
tim
at
ed
c
oe
ffi
ci
en
t
17 31/10/18 7:01 pm
18 High-Growth Firms
(return on assets), most likely through increases in demand that allow for greater
markups. These results are robust to alternative specifications and controlling for
growth and foreign share of vertically related industries, and suggest that the role of
HGFs is different from that of MNEs: whereas the FDI spillover literature generally
finds that backward linkages are more important than forward linkages, the results in
this book show that firms can benefit from increased HGF presence at both ends of the
value chain.
In the case of Turkey, the results are less As in Hungary, horizontal
spillovers are insignificant or in some cases negative for variables such as sales, employ-
ment growth, total factor productivity, and average wages of non-HGFs, while forward
spillovers of HGFs are positive and significant for employment growth. Unlike Hungary,
however, forward spillovers are negative for revenue, while backward spillovers are
small and
Annex 1A
The data sets used in this book represent the majority of available high-quality,
nationally representative longitudinal firm-level data sets in developing countries. They
include the Relação Anual de Informações Socials (RAIS) in Brazil, Censo Economico
(Industrial Censuses) in Mexico, Industrial Census in Côte d’Ivoire, Large and Medium
Manufacturing Industry Survey (LMMIS) in Ethiopia, the South African Revenue
Service and National Treasury Firm-Level Panel (SARSNT), India Human Development
Survey (IHDS) and India Prowess firm database compiled by the Centre for Monitoring
Indian Economy (CMIE), Thailand Department of Business Development tax return
database, Indonesia Annual Manufacturing Survey, Tunisian Repertoire National des
Enterprises (RNE), the Hungarian balance sheet and income statement panel col-
lected by the National Tax Authority (NAV), the Annual Industry and Service Statistics
(AISS) database by TurkStat, and the Entrepreneur Information System (EIS) by the
General Directorate of Productivity at the Ministry of Science, Industry and Technology
of Turkey. Table summarizes the main features of each of the data sets.
In Brazil, the Relação Annual de Informações Sociais (RAIS) is a labor census gath-
ering longitudinal data on the universe of formal workers and firms in manufacturing
and services sectors during 1994–2014. RAIS contains administrative social security
records for employees and employers and is collected by the Ministry of Labor. It pro-
vides information on workers’ demographics (age, gender, and schooling), job charac-
teristics (occupation, wage, hours worked), as well as hiring and termination dates. It
also includes information on a number of firm-level characteristics, notably number of
employees, geographical location (municipality), and industry code (according to the
5-digit level of the Brazilian National Classification of Economic Activities). Unique
identifiers (tax identification numbers) for workers and firms make it possible to fol-
low them over time. The data also make it possible to separately identify the firm and
18 31/10/18 7:01 pm
The Appeal of High Growth 19
TA
B
LE
1
A
.1
D
at
a
S
ou
rc
es
a
nd
D
es
cr
ip
ti
on
s
C
ou
nt
ry
P
er
io
d
S
ou
rc
e
S
ou
rc
e
ty
pe
Ty
pe
o
f fi
rm
s
co
ve
re
d
Fi
rm
s
iz
e
th
re
sh
ol
d
H
G
F
de
fin
it
io
n
m
et
ri
cs
D
at
a
co
ve
ra
ge
Br
az
il
19
94
–2
01
4
Re
la
ça
o
A
nn
ua
l d
e
In
fo
rm
aç
oe
s
So
ci
ai
s
(R
A
IS
)
La
bo
r c
en
su
s
Fo
rm
al
w
or
ke
rs
a
nd
fi
rm
s
–
Em
pl
oy
m
en
t
M
an
uf
ac
tu
rin
g
an
d
se
rv
ic
es
Cô
te
d
’Iv
oi
re
20
03
–1
2
Co
nfi
de
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ia
l r
eg
is
tr
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of
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pr
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es
of
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e
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m
ai
nt
ai
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by
th
e
N
at
io
na
l S
ta
tis
tic
s
In
st
itu
te
(In
si
tit
ut
N
at
io
na
l d
e
la
St
at
is
tiq
ue
, I
N
S)
In
du
st
ria
l c
en
su
s
Fo
rm
al
s
ec
to
r (
al
l r
eg
is
te
re
d
fir
m
s)
–
Em
pl
oy
m
en
t a
nd
s
al
es
M
an
uf
ac
tu
rin
g
an
d
se
rv
ic
es
Et
hi
op
ia
19
96
–2
00
9
La
rg
e
an
d
M
ed
iu
m
M
an
uf
ac
tu
rin
g
In
du
st
ry
S
ur
ve
y
(L
M
M
IS
)
co
nd
uc
te
d
by
th
e
Et
hi
op
ia
n
Ce
nt
ra
l S
ta
tis
tic
al
A
ge
nc
y
(C
SA
)
In
du
st
ria
l c
en
su
s
Fi
rm
s
th
at
u
se
p
ow
er
-d
riv
en
m
ac
hi
ne
ry
10
e
m
pl
oy
ee
s
or
m
or
e
(in
pr
ac
tic
e
a
fe
w
fi
rm
s
ha
ve
fe
w
er
th
an
1
0
w
or
ke
rs
)
Em
pl
oy
m
en
t a
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s
al
es
M
an
uf
ac
tu
rin
g
H
un
ga
ry
20
00
–1
5
N
at
io
na
l T
ax
A
ut
ho
rit
y
(N
AV
) f
ro
m
co
rp
or
at
e
in
co
m
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x
st
at
em
en
ts
Ce
ns
us
A
ll
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le
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b
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pi
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–
Em
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m
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M
an
uf
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rv
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es
In
di
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19
90
–2
01
3
In
di
a
Pr
ow
es
s
fir
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ab
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by
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re
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M
on
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In
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(C
M
IE
)
O
th
er
: P
ub
lic
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m
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ni
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uf
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g
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d
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rv
ic
es
La
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e,
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ed
fi
rm
s
Fi
rm
s
th
at
h
av
e
th
ei
r
an
nu
al
s
ta
te
m
en
ts
p
ub
lic
ly
av
ai
la
bl
e
(u
su
al
ly
li
st
ed
o
n
st
oc
k
ex
ch
an
ge
)
Sa
le
s
M
an
uf
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rin
g
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d
se
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ic
es
In
do
ne
si
a
19
90
–2
01
4
In
do
ne
si
a
A
nn
ua
l M
an
uf
ac
tu
rin
g
Su
rv
ey
Su
rv
ey
Ce
ns
us
o
f f
or
m
al
m
an
uf
ac
tu
rin
g
pl
an
ts
20
e
m
pl
oy
ee
s
or
m
or
e
Em
pl
oy
m
en
t a
nd
s
al
es
M
an
uf
ac
tu
rin
g
M
ex
ic
o
19
93
, 1
99
8,
20
03
, 2
00
8,
20
13
Ce
ns
o
Ec
on
óm
ic
o
(In
du
st
ria
l
Ce
ns
us
, f
ro
m
th
e
N
at
io
na
l
St
at
is
tic
s
A
ge
nc
y,
IN
EG
I)
Ce
ns
us
(h
el
d
ev
er
y
fiv
e
ye
ar
s)
A
ll
fir
m
s
(fo
rm
al
a
nd
in
fo
rm
al
)
–
Em
pl
oy
m
en
t
M
an
uf
ac
tu
rin
g
(T
ab
le
c
on
tin
ue
s
on
th
e
fo
llo
w
in
g
pa
ge
.)
19 31/10/18 7:01 pm
20 High-Growth Firms
TA
B
LE
1
A
.1
D
at
a
S
ou
rc
es
a
nd
D
es
cr
ip
ti
on
s
(c
on
ti
nu
ed
)
C
ou
nt
ry
P
er
io
d
S
ou
rc
e
S
ou
rc
e
ty
pe
Ty
pe
o
f fi
rm
s
co
ve
re
d
Fi
rm
s
iz
e
th
re
sh
ol
d
H
G
F
de
fin
it
io
n
m
et
ri
cs
D
at
a
co
ve
ra
ge
So
ut
h
A
fr
ic
a
20
08
–1
5
(b
ut
w
e
on
ly
us
e
da
ta
fr
om
2
00
9
on
b
ec
au
se
20
08
is
n
ot
re
lia
bl
e)
So
ut
h
A
fr
ic
an
R
ev
en
ue
S
er
vi
ce
an
d
N
at
io
na
l T
re
as
ur
y
Fi
rm
-L
ev
el
Pa
ne
l (
SA
RS
-N
T)
O
th
er
:
A
dm
in
is
tr
at
iv
e
Co
rp
or
at
e
in
co
m
e
ta
x
an
d
va
lu
e-
ad
de
d
ta
x
re
gi
st
er
ed
en
tit
ie
s
–
Em
pl
oy
m
en
t
M
an
uf
ac
tu
rin
g
an
d
se
rv
ic
es
Th
ai
la
nd
20
04
–1
5
D
ep
ar
tm
en
t o
f B
us
in
es
s
D
ev
el
op
m
en
t t
ax
re
tu
rn
d
at
ab
as
e
Ce
ns
us
A
ll
ne
w
re
gi
st
er
ed
fi
rm
s
si
nc
e
19
99
a
nd
a
ny
s
ur
vi
vi
ng
re
gi
st
er
ed
fi
rm
s
be
fo
re
1
99
9
–
Sa
le
s
M
an
uf
ac
tu
rin
g
an
d
se
rv
ic
es
Tu
ni
si
a
19
96
–2
01
5
Re
pe
rt
oi
re
N
at
io
na
l d
es
En
te
rp
ris
es
(R
N
E)
Ce
ns
us
A
ll
re
gi
st
er
ed
p
riv
at
e
fir
m
s
–
Em
pl
oy
m
en
t
M
an
uf
ac
tu
rin
g
an
d
se
rv
ic
es
Tu
rk
ey
20
06
–1
6
Th
e
En
tr
ep
re
ne
ur
In
fo
rm
at
io
n
Sy
st
em
(E
IS
),
pr
ov
id
ed
b
y
th
e
G
en
er
al
D
ire
ct
or
at
e
of
P
ro
du
ct
iv
ity
at
th
e
M
in
is
tr
y
of
S
ci
en
ce
,
In
du
st
ry
a
nd
T
ec
hn
ol
og
y.
Ce
ns
us
Ev
er
y
es
ta
bl
is
hm
en
t t
ha
t
em
pl
oy
ed
m
or
e
th
an
o
ne
em
pl
oy
ee
a
nd
o
pe
ra
te
d
m
or
e
th
an
a
y
ea
r d
ur
in
g
th
e
pe
rio
d
fr
om
2
00
6
to
2
01
6
–
Em
pl
oy
m
en
t
M
an
uf
ac
tu
rin
g
an
d
se
rv
ic
es
Tu
rk
ey
20
05
–1
4
A
nn
ua
l I
nd
us
tr
y
an
d
Se
rv
ic
e
St
at
is
tic
s
(A
IS
S)
b
y
Tu
rk
St
at
Ce
ns
us
A
ll
fir
m
s
(fo
rm
al
a
nd
in
fo
rm
al
)
–
Em
pl
oy
m
en
t
A
ll
bu
si
ne
ss
s
ec
to
rs
,
ex
ce
pt
fo
r a
gr
ic
ul
tu
re
an
d
fin
an
ci
al
s
ec
to
r
U
ni
te
d
St
at
es
19
90
–2
01
3
Lo
ng
itu
di
na
l B
us
in
es
s
D
at
ab
as
e
(L
BD
) b
y
th
e
U
ni
te
d
St
at
es
C
en
su
s
Bu
re
au
Ce
ns
us
A
ll
no
n-
fa
rm
e
st
ab
lis
hm
en
ts
w
ith
a
t l
ea
st
o
ne
p
ai
d
em
pl
oy
ee
–
Em
pl
oy
m
en
t
M
an
uf
ac
tu
rin
g
on
ly
(s
er
vi
ce
s
ex
cl
ud
ed
in
th
e
an
al
ys
is
fo
r t
hi
s
re
po
rt
)
20 31/10/18 7:01 pm
The Appeal of High Growth 21
the establishment. Although the RAIS data cover segments of the public sector, the
analysis in this book is restricted to the priva
