institutional reform and new firm performance: more or ... · eberhart / eesley 8/2011 do not copy...
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DRAFT WORKING PAPER
Institutional Reform and New Firm Performance: More or Better Firms?
Robert N. Eberhart SPRIE Researcher
Stanford Program on Regions of Innovation and Entrepreneurship
Charles Eesley Assistant Professor
Department of Management Science and Engineering Stanford University
August 2011
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Introduction
What mechanisms drive superior new firm performance in the wake of institutional
reforms intended to increase the count of new firms? Entrepreneurship is now at the center of
many policy questions related to economic growth, employment opportunity then advancement
of science and the alleviation of poverty. There is a growing consensus that managing or at least
fostering an appropriate entrepreneurial habitat is important and that habitat affects the dynamic
of job growth through new company formation, (CTF). It is relevant to wonder if institutional
changes intended to create new and flourishing firms have the effect intended and what are the
mechanisms that drive changes in performance of new firms in the altered institutional
environment.
A new firm’s ability to flourish depends on the institutional environment within which it
was founded. Empirical research on institutional theory has demonstrated the impact of
institutions on the founding rates of new organizations (Thornton 1999; Russo 2001; Sine,
Haveman et al. 2005) and that certain individual characteristics are associated with a higher
likelihood of founding a firm (Sørensen 2007)a; 2007b, (Eesley 2010). Work in organizational
theory has also long been interested in how the prevailing institutional climate is related to
founding rates of new firms (Stinchcombe 1965); (Romanelli 1989).
The institutional environment can stimulate the formation of new firms, (Gompers,
Lerner et al. 2006). Institutional theories highlight the effects of institutions on organizations,
indicating that they shape the attractiveness of organizational forms, sectors, or practices and
result in shifts in aggregate founding rates over time (Sine and David 2003),(Baumol 1990;
Russo 2001). Institutions can affect the distribution of information about opportunities and this
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asymmetric information can give rise to heterogeneous new firms in terms of startup rates in
different industries, (Shane 2000). Moreover, different institutional arrangements can influence
the trajectory of new firms ((Barro 1996); (Peng and Zhou 2005). For example, formal
institutions such as the system of VC financing, (Davila, Foster et al. 2003), bankruptcy laws,
and informal institutions such as peer expectations, (Nanda and Sørensen 2008), can have a
significant influence on the decision to create a firm and the strategies employed to operate them,
(Eisenhardt and Schoonhoven 1990; Burton, Sorensen et al. 2002; Katila and Shane 2005)
Overall, the effects of institutional change on new firm formation rates and strategies have been
well studied. Scholars have paid less attention to the related questions linking performance to the
institutional settings, and so to bring a more complete understanding to the mechanisms of how
institutions affect the performance of nascent firms
In this paper we argue that the institutional environment alters the incentives of
individual decisions to start firms. In this, we are responding to calls in the literature to explain
the mechanisms of new firm growth to complement the already well-developed literature
documenting the amount of growth, (Davidsson, Achtenhagen et al. 2007), and to contribute to
studies of the intersection between entrepreneurship studies and institutional theory, (Tolbert,
David et al. 2010) Moreover, we are responding to calls for more empirical attention to data that
that can more directly explain and inform theories of the mechanisms by which institutions affect
new firm trajectories. (Sørensen and Chang 2006).
We examine these questions using data from Japan. This paper asks how a particular
institutional change in Japan, intended to encourage the formation of new firms, affected
mechanisms that alter the performance trajectory of new firms. We demonstrate that institutional
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changes that were designed to lower the costs and risks of entry did not alter the number and
variety of firms. To the contrary of predictions by a great deal of literature, we show that the
performance of new firms, after reforms, were materially improved suggesting that lowered entry
barrier may have either altered incumbent firm strategies, attracted individuals with greater
human capital, or that lowered entry barriers may have affected markets. Using data on 16,824
firms founded from 1950 to 2008 in Japan we test the idea that institutional reform can affect
entrepreneurial performance by altering the selection of individuals deciding to become
entrepreneurs in the context of incumbent form strategic resets while not changing the new firm
formation rate.
Cost of Entry in Japan
Entry costs affect the rate of new firm formation. Increased rate of return increases the
economic incentives for individuals to found new firm. Increasing costs of entry lower available
resource reserves and can thus discourage start-ups, (Evans and Jovanovich 1989; Klapper,
Laeven et al. 2006) while Numerous studies have demonstrated that financial constraints bind the
choices of potential entrepreneurs, (Buera 2009). Recent literature on entrepreneurial motivations
in Japan confirms that the level of personal assets are important in determining entrepreneurship
entry, (Masuda 2006). Further, changes in entry costs alter the opportunity cost thresholds that
have been shown to determine start-up rates, (Amit, Muller et al. 1995), because lowered entry
costs move up the opportunity costs of not starting firms for talented individuals making
entrepreneurship more likely. High entry costs can also alter the set of entrepreneurial
opportunities by exceeding expected and necessary capital costs in industries with low capital
intensity.
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Research demonstrates that even individuals with high financial assets such that capital
cost barriers are less important are deterred by potential costs of bankruptcy, (Lee, Yamakawa et
al. 2008). The risks of being an entrepreneur are of the loss - perhaps ruinous - of personal
capital and career reputation. Before 2003, company heads in Japan, for example, were subject to
complete personal liability and the inability to control their firm’s fate after declaring
bankruptcy. Consequently, entrepreneurs in Japan were deterred by bankruptcy risk,
alternatively directing their entrepreneurial efforts into “intrapreneurship”, that is, founding
business activities within an exiting company, (Harada 2005).
Institutional changes in Japan directly changed the environment and conditions under
which firms paid initial capitalization. In 2003, the formalities of starting new companies was
simplified and made much less costly with the introduction of the 1 yen minimum capital
requirement to become a corporation1. The preceding requirement was Y10,000,000 for a full
stock issuing corporation (kabushiki-kaisha), or Y3,000,000 for a limited firm called a yugen-
kaisha 2 and their minimum capital could not be immediately spent except in particular
circumstances. The law reducing the minimum capital to Y1 was aimed at increasing the rate of
new firms by lowering the capital that needed to be risked by the founders. Further, the change
enhanced the legitimacy of new firms. Forming a stock-issuing corporation (kabushiki-kaisha)
was viewed as a crucial distinction to create necessary legitimacy in Japanese commerce. As
1 In addition to other changes. 2 Of note, the company law of 2003 allowed the Y1 initial capitalization for new corporations (KK and YK) as long as the founder was founding a de novo firm and other requirements to ensure that “shell” corporations were not the outcome of this easing. It is notable that this law was extended and refined in 2006 with a comprehensive new Japan Company Law that, among many articles, abolished the yugen-kaisha, created new limited liability firms, and strengthened the codification if the 1Y capitalization requirement.
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such, most firms that sought substantial growth felt it necessary to form a kabushiki-kaisha
before reforms and were now enabled at a substantially lowered cost3, (Ohara 2009).
The benefits of a dramatically lowered capital requirement are simple to discern from the
point of view of the entrepreneur. It directly follows that less personal capital needs to be
invested at the riskiest stage of the firm and the return to entrepreneurship must increase as cash
invested is lowered. Moreover, in the absence of a minimum capital reserve, such money that is
invested can be immediately spent on organizational needs. Organization literature has
substantial support for this idea in the idea that liquidity constraints are important impediments to
entrepreneurial activity, (Holtz-Eakin, Joulfaian et al. 1994). Further, the less capital invested,
the lower the potential bankruptcy loss. Finally, lower capital costs, can enhance organizational
legitimacy, (Suchman 1995). By allowing constrained entrepreneurs to obtain business charters,
gain legitimacy from organizational form that may have been unobtainable before. This is
particularly apt with respect to Japan when the organizational form of a stock issuing company
(kabushiki kaisha), is an almost a certain prerequisite for a firm to establish commercial
relationships in most industries, (Ohara 2009).
HYPOTHESIS 1: Institutional reforms that lower entry costs increase the rate of new firm
formation
While this first claim is admittedly straightforward, if it cannot be confirmed it would
imply that the institutional reforms either have little effect or that other effects need to be
analyzed. Institutional effect might not only change the formation of firms but also change their
3 Only if the required capitalization of the firm for operational needs were less than the required initial capitalization before reform.
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dissolution. Next, we build upon this baseline hypothesis by examining whether extant firms are
more likely to dissolve after the bankruptcy reforms.
Bankruptcy Law Reform
The discouraging effects of bankruptcy risk imply that reduced burdens of bankruptcy are
should increase entrepreneurial activity by reducing the entrepreneurs’ exposure to risk,
especially personal risk. Entrepreneurs are more likely to found firms where the exposure to
personal asset loss is mitigated by legal exemptions, (Fan and White 2003). An additional
mechanism from the organizations literature argues that a threshold of performance and payoffs
is defined below which principals will act to dissolve the organization, (Gimeno, Folta et al.
1997). These mechanisms can compliment each other, The lowered expected cost of bankruptcy
encourages inefficient firms to exit, creating market opportunity in vacated niches for new firms
which are encouraged to enter by the lowered potential cost, (Lee, Yamakawa et al. 2008).
The risks of financial ruin through bankruptcy were altered in Japan with the passage of
laws reducing the exposure of entrepreneurs. Prior to that, several types of bankruptcies were
established in Japanese law. Liquidation (hasan-ho), and reorganization (kaisha kosei-ho),
similar to the U.S. Chapter 7 and 11 respectively were most commonly applied. Japanese law
also provided for a third type, the composition reorganization (wagi-ho) which was based in 19th
century German law and was a rehabilitation procedure that mandated the replacement of
managers, (Matsushita 2006). Not uncommon also, was an extra-legal procedure of private
reorganization that was especially prominent among very small firms. These procedures, even
rehabilitation and private agreements, usually meant the immediate replacement of the managers
and the loss of their interest in the firm. Unlike US procedures, the court or creditors would
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manage the firm during restructuring, (Xu 2007). Further, an informally governed but well
established system of contingent governance mandated the replacement of managers of firms in
financial distress by its financiers well before legal bankruptcy was attempted, (Aoki 1990).
Overall, there was a bleak prospect for the managers of a firm in bankruptcy. Liquidation or
reorganization in Japan sought to maximize recovery for the creditors, not rehabilitation of
management that substantially increased the risk of starting and managing a firm.
New bankruptcy procedures are more favorable to the creditor, (Helwege and Packer
2003). In 2003, as part of the overall effort to improve the business and start-up climate in Japan,
the rehabilitation form of bankruptcy (kosei kaisha-ho) was revised to allow retaining managers
during rehabilitations under court supervision. Also, private reorganizations were addressed to
create procedures of reorganization that allowed mangers to more actively participate in the
process. In 2004, the liquidation law (hasan-ho), was reformed to create a simpler and more
equitable distribution of residuals, (Matsushita 2006). Finally, the maximum liability that
directors and CEO’s were exposed to were reduced from unlimited personal exposure in many
cases, to limited assets at risk in most cases, (Schaede 2008). These reforms, taken together,
could potentially lower the risk of entrepreneurship by allowing a system of rehabilitation that
lets the entrepreneur survive in many cases and perhaps retain some of the residual.
The reduced capital requirement and bankruptcy costs should cause both the rate of new
formation and the rate of bankruptcy to increase. Notably, reforms in Japan may not generate the
growth of the number of firm but instead generate heterogeneity by increasing the number of
firms with high growth opportunities and increasing the number of failing firms, (Lee, Peng et al.
2007). So we hypothesize that:
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HYPOTHESIS 2: Institutional reforms that lower bankruptcy risks are likely to raise rate the
rate of bankruptcy as individuals controlling firms with marginal prospects of success face
lowered costs of exit.
Effect of Reforms on Entrant Teams And Human Capital
Organizations literature has found that more experienced entrepreneurs are associated
with better performance trajectories after founding (Eisenhardt and Schoonhoven 1990). These
entrepreneurs bring greater social networks allowing the new firm to access more resources. In
addition, depth of industry experience or of long social and professional ties with cofounders is
shown to be associated with better organizational performance as has depth of experience in
entrepreneurially prestigious firms, (Burton, Sorensen et al. 2002).
Recent social trends in Japan’s environment could interact with the legal reforms to bring
a comparatively talented pool of potential entrepreneurs to start new firms after reforms. First,
opportunities for the highly educated in Japan in traditional employment channels are being
altered and limited by social changes(Schaede 2008). The institution of lifetime employment, the
primary employment channel for the most highly educated for much of then post-war period, has
virtually disappeared with only a small percentage of Japan’s entering workforce taking that type
of employment, (Vogel 2006). Secondly, Japanese firms are eschewing the more traditional
system of seniority employment and skirting stringent Japanese employment laws by relying on
temporary employment agencies for a greater percentage of their skilled managerial workforce,
(ACCJ 2010). Overall, these employment patterns are altering career trajectories bringing many
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more well-educated actors into small company and short tenured employment situations and
increasing the likely pool of nascent entrepreneurs given the reformed costs.
Recent graduates in Japan face similar traditional challenges and a changing labor market
in Japan that no longer offers lifetime employment(Conrad 2009). It seems reasonable then the
lowered capital barriers would be of particular relevance to female entrepreneur that can find
optimal opportunity in low capital industries. Since these individuals are asset-poor, capital costs
can be especially constraining. By removing the constraint of forming a Y10 million capitalized
company, then, a broader group of less advantaged entrepreneurs can be expected to start firms
with greater frequency.
Thus we propose that:
HYPOTHESIS 3a: Institutional reforms that lower bankruptcy risks increase the likelihood that
older, male individuals from prestigious universities will start new firms
HYPOTHESIS 3b: Institutional reforms that lower entry costs encourage females and younger
individuals to start new firms
Institutional Reforms and Firm Performance
Strategy literature suggests three mechanisms that may operate to increase firm
performance as the highly educated careerist start firms. First, individuals from prestigious
universities with subsequent career tracks in notable firms develop social networks that enable
them to have advantageous access to resources that assist a firm’s growth. It has been
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demonstrated in resource-based literature that the resources that accrue through social networks
are decisive in determining firm performance, and that the more the academic quality of an
entrepreneur’s education, the better firm performance, (Barro 2001). Second, industry
experience among top management and founders in an industry is associated with improved firm
performance(Dencker, Gruber et al. 2009) and good technical educations are associated with
firm and consequent economic growth, (Murphy, Shleifer et al. 1991). A third mechanism
particularly relevant to Japan is the greater acquisition of generalist skills that have been shown
to be associated with improve new firm performance, (Lazear 2005). Corporate career executive
in Japanese firms are given broad training in many organizational fields rather than the more
specialized career trajectories in the U.S. Overall, social networks, industry experience and
generalist training should operate in complementary fashion to give performance advantages to
new firms.
Organizational learning theory may also play a role in allowing new firms to become
established. Incumbent organizations may be entrenched in strategic responses as new firms
deploy novel strategies in a changed environment,(Hannan and Freeman 1984) (Sorensen and
Stuart 2000). In the wake of regulatory change that lowers barriers to entry, incumbent firms
have been shown to refocus their efforts internally on core business and thus reduce their
competitive challenge outside of their core business, (Haveman, Russo et al. 2001) and these
organizational responses are associated with reduced performance, (Barnett and Carroll 1995).
Incumbent retrenchment in the wake of new firm challenges from lowered barrier can thus be
decisive in allowing new firms to establish competitive positions from whence incumbents have
retreated or reduced their aggression. Overall, performance can be enhanced as new firms exploit
these opportunities.
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HYPOTHESIS 4: The entry of prestigiously educated individuals subsequent to institutional reforms lowering the costs of entry and the risk of bankruptcy raises the growth rate of firms founded after reforms
Method
Although limited to Japan and the institutional reform environment there, our paper adds
to the knowledge of institutional reform and its effect on new organizations by using a unique
dataset and because comparatively little work on entrepreneurship has been done outside of the
U.S. and the E.U. Our data covers from over a broad span of time, from 1950 through 2008,
gathered in person by a firm that depends on the accuracy of its information, Teikoku Data Bank.
A credit rating company’s data of this type is suited to the study of business growth since the
determinants of credit decisions, sales growth, leverage, management demographics are similar
to those most commonly used in entrepreneurial studies. Further, because we sample across
industries, we are in a unique position to analyze the differential effect of institutions across an
economy and between industries.
If the lowering of the costs of entry and bankruptcy risks measurably affected the
performance of new firms in Japan, we would expect the effect to obtain most convincingly in a
difference between Japan’s pre-reform and post-reform environment. We argued earlier that
lowered capital requirements have been shown to affect firm startup rate, and performance and
that less onerous bankruptcy consequences and rationality have been shown to affect startup
rates and performance. Thus, we selected 2003 as our focal reform date or pre and post-reform as
it coincides with the implementation of lowered capital requirements and with the culmination of
a two-year process of bankruptcy reforms.
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Data
To test our hypotheses we collected a database of newly formed, independent Japanese
firms. We employ the COSMOS database of the Teikoku Data Bank (KK), a commercial credit
rating firm in Tokyo that has demographic, financial and descriptive data on Japanese firms.
TDB is long-established firm (founded 1890) and one of the two largest firms in Japan providing
credit ratings to corporate clients for the primary use of evaluating supplier and customer credit
worthiness. COSMOS is especially useful for our analysis as TDB verifies its data by personal
interviews and audits for all surveyed firms when collecting its financial and demographic data.
Moreover, as Japan’s largest credit rating service, it maintains a set of nearly all operating firms
by capturing firms as they incorporate, and adds other, non-incorporated, firms by either survey
or when there is a credit inquiry from a client about a firm not yet in the database. Teikoku
Databank data has been used in academic studies of bankruptcy, (Schaede 2008), contrasts
between Silicon Valley and Japan, (Suzuki, Kim et al. 2002), and policy evaluation, (ACCJ
2010).
We use the 2009 edition of TDB’s “COSMOS 2” database, which contains 155,022 firms
founded from 1950 to 2009. These include; stock issuing firms (kabushiki kaisha 株式会社),
special non-stock issuing corporations (tokurei yugen kaisha 特例有限会社 ), limited
partnerships (goshi kaisha 合資会社 and godo kaisha 合同会社), and general partnerships,
(gomei kaisha 合名会社), all with incorporation dates during 1998 through 1st quarter 2008.
All firms in the dataset were formally incorporated, subsequent to founding, from 1998 through
the first quarter of 2009. Data is available annually and is presented cross-section for 2009. Data
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for sales, and profitability are presented in three-year panel format, for the most recent three
fiscal years.
We imposed several restrictions on the data. We reduced our data set to 44,000 firms by
eliminating firms that were spin-offs of parent firms or non-operating firms. Further, since they
were not new or entrepreneurial firms, we eliminated some 126 bank and bank holding
companies from this study. We added 12,701 more firms from TDB’s BANKRUPTCY database
founded over the same period to avoid bias of examining only surviving firms increasing our
initial sample count to above 56,000. Since all bankrupt firms had complete foundation date data
and inclusion of the entire bankrupt data would bias the results, we randomly selected a
proportionate amount of the bankrupt firms. Finally, we eliminated 12,610 firms that had
incomplete financial and foundation date data. Our final sample count is 16,824. A summary of
the sample counts is presented in Table 1, below. Since there was a substantial reduction in
sample size, from the initial COSMOS database, we conducted univariate comparisons between
the full data set and the final sort that we used. We find no significant differences between the
databases with the exception of the initial capital of starting firms. We control for initial capital
in our models and find either an immaterial or no significant effect in our models. The results are
in Appendix 1. Descriptive statistics are in Table 1, below.
Insert Table 1 Here
Dependent Variables
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Performance variables are products of a complex interplay of strategy and environment
and their value depends on the interests of the firm’s various constituencies and stage of growth.
We focus on sales growth to measure a firm’s performance conditional upon it founding date. In
organizational literature, performance is frequently measured by sales growth, (Hall 1987;
Eisenhardt and Schoonhoven 1990; Gersick 1994; Hmieleski and Baron 2009; Baum and Bird
2010). It is particularly suitable to assess firm growth for several reasons. It generally applies
across industries and circumstances as all for-profit firms need sales to survive and sales growth
of new firms is imperative, and broad applicability is desirable to asses comparisons across
industries,(Barnett and Carroll 1995). Second, it is the one metric that entrepreneurs themselves
will report as the one that they watch and the one they try to affect most, (Barkham, Gudgin et al.
1996)). Third, it can be argued that sales growth is antecedent or a necessary condition to other
common metrics such as employment or profitability or cash flow, (Davidsson, Achtenhagen et
al. 2007). Sales growth has been a preferred performance metric in literature examining small
firms in Japan. Scholars studying new manufacturing firms in Japan (Honjo 2004; Honjo and
Harada 2006), in their analysis of data from new manufacturing companies, use sales growth
rates to assess entrepreneurial success, as do analyses of Japanese hi-tech startups, (Igarashi and
Taji 2006). Consistent with these streams of literature, we selected the cumulative average
growth rate of revenue since incorporation, cagr, as our dependent variable.
To test the exit rates of firms proximate to bankruptcy reforms, we use the exit hazard
event of bankruptcy, exit03-09, as our dependent variable. The hazard of bankruptcy is easy to
measure and is comparable across firms, industries and contexts(Barnett and Carroll 1995). The
COSMOS database provides the bankruptcy date of affected firms as well as the foundation date.
Since our research focuses on a new firm’s trajectory conditioned by the institutional
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environment on its founding date, we code our variable with a firm entering the dataset in its
foundation year and a firm exits upon bankruptcy. This binary variable takes the value of 1 if
particular firm entered bankruptcy during 2003-2009, or surviving but founded before 2003, to
incorporate surviving firms and mitigate right censoring of the data.
Independent Variables
To examine the effect of firm foundation before and after reform, we examine the
institutional environmental effects on new firm growth with an independent variable, reform. We
measured whether a firm was founded in the reformed institutional environment using an
indicator variable if a focal firm was founded after 2002. To test whether the founder’s
university background effects foundation rates or performance, we used a binary variable,
prestige_univ, to indicate that a focal firm’s CEO graduated from one of Japan’s top ten
universities ranked by QS World University Rankings. The age of CEO’s, ceo_age is directly
measured as a continuous variable of the birth year, and an indicator variable, female, is used to
identify the gender of the CEO.
We also want to isolate the growth and profitability due to reforms from the growth that
occurs in new firms over time. Economics literature has found that younger firms, ceteris
paribus, tend to grow faster than older forms even when controlling for early exits (Evans 1987).
But the effect diminishes as age increases. Accordingly we included a control for the age of the
firm, firm-age and included its square firm-age2, to capture expected diminishing quadratic
growth compounded over time, (Angelini and Generale 2008). To account for macro-economic
and other temporal effects, we controlled for a firm’s industry based on the SIC code category,
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by constructing nine industry classes to capture explanatory industry types; construction,
industrial, hi-cap tech, lo-cap tech, services, and sales, using primary industries as a base. We
distinguish between hi-capitalization technology firms (electronics, computer manufacturing,
semiconductors, etc.) and low capital-intensive technology firms, (software, ecommerce,
research, etc.) Our classification starts with the Kaufman database definition modified to include
important technology categories. The relevant codes are in Table 2. 4
Insert Table 2 here
Strategy literature indicates that differing levels of resources, and managerial talent,
might condition new firm evolution, (Haleblian and Finkelstein 1993; Burton and Beckman
2007). Following this literature, to control for differing founding resources, we selected initial
capital, (adjusted for inflation with constant 2008 yen), capital_ini, and controlled for managerial
heterogeneity by including a variable for the credit rating of the firm5, credit_rating. Since the
founder can be replaced and the data reports the data on the current CEO, we control this with a
binary variable, founder, that takes the value of 1 if the CEO had been replaced since founding.
We controlled for macroeconomic effects by including a variable for per capita GDP, (in yen
constant dollars), GDP_PC. To control for competition that may suggest differing initial
conditions for the newly founded firms (CTF), we include the number of firms in an industry,
comp, as a control.
4 We determine whether an SIC code is coded tech following the Kaufman Survey of Small Business, that uses the proportion of resources a focal firm dedicates to research and development to determine if a company is a technology firm, Hadlock, P., D. Hecker, et al. (1991). "High Technology Employment: Another View." Monthly Labor Rview 114.. However, software companies and other common technology firms such as spacecraft manufacturers escape the definition. In the case of our data, software-programming companies are the largest firm-level category of new incorporations over the study period, not designating them as technology firms could introduce bias. To correct for the omission we assigned four additional SIC classifications to designate tech firms. These codes are listed in Table 2. 5 This is TDB’s credit rating. This rating is central to the business purpose of TDB and is similar to a credit score.
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Model Specification and Econometric Issues
We estimated a hazard model to examine whether reforms that lower bankruptcy risks are
likely to raise rate the rate of bankruptcy. We employed a proportional hazards model (Cox
1972), (equation 1), to avoid specifying the relationship between the bankruptcy likelihood and
firm characteristics and there is a rich literature proposing many such relationships, (Gimeno,
Folta et al. 1997) Moreover, the model allow us to understand our variables’ effect on the timing
of the bankruptcy event by estimating the probability of declaring bankruptcy conditional on
both the prior founding of the firm, and adjusts for right censoring of the data. In our approach,
firms become “at risk” at the time of their founding and exit the data – experience the “hazard” –
when they declare bankruptcy. The coefficients we report are hazard rations with a value of 1.0
or greater indicating the associated variable increases the probability of the hazard occurring for
a focal firm. The specification of the model is:
(1) where the vector X includes our founder characteristics firm level variables . λ(t | X) is the rate at
which founders will declare bankruptcy at any particular date, given that they have not gone
bankrupt up until that point in time. The estimation takes into consideration the “right censoring”
that occurs because not all firms experience the hazard of bankruptcy
To test 3a and 3b we use the logistic regression, as the dependent variable is binary. The
logistic regression is appropriate for linear regression models with binary outcomes and we are
testing the outcome of starting a firm or not, (equation 2). We take care to report our outcome as
odds rations whose value, and thus the marginal value of the partial coefficients does not depend
on the variables’ starting value, (Hoetker 2007). Our model is:
( ) ( )βλλ 'exp)(| XtXt o=
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P yi =1 xi =e(X '! )
1+ e(X '! )
!"#
$%&
, (2)
where X is a vector of individual characteristics and controls that may influence the decision to
start a firm, and yi takes the value of 1 if a firm is started during or subsequent to 2003.
To test for firm performance in H4, we use ordinary least squares. We use four models,
(table 7). Models one through three use the cumulative average growth rate since foundation
(cagr) as the dependent variable and net profit as a percent of sales is the dependent variable in
model four. Model one is the basic model with industry controls. Model two adds the
independent variables, and model three adds interactive effects. There is reason to be concerned
that secular economic conditions, though, will affect the variance of growth and value of the firm
from location to location and over founding years violating the ordinary least squares assumption
of homoskedastic, normally distributed errors. Accordingly, a robust corrected ordinary least
squares regression approach is appropriate for our data, (MacKinnon and White 1985).
Results
In spite of the abundant academic literature that suggests that the reforms in Japan ought
to increase the rates of new firm formation, there is scant evidence of this in private and public
data. The most frequently reported data on Japan’s startup rate is the Enterprise and
Establishment Census of Japan issued by the Ministry of Internal Affairs and Communications.
This census is part of a system of statistical business databases that include the Survey on
Service Industries, METI’s Census of Commerce and Census of Manufactures.67 This data
6 The EEC employs field surveys to count the number of new establishments and count the number of establishments that have closed. The survey, after 2004, is conducted every 28-months. The number of new and closed establishments are divided by 28 to
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confirms that, for the overall Japanese economy during our period of study, there is no evidence
that the startup rate of all new firms has changed since 1993, (Chart1). Moreover, our database of
newly incorporated firms also indicates no increase in independent incorporation rates from 1998
through 2007, (Chart 2.) Overall there is no evidence to contradict the body of official statistics
that the startup rates of new firms in Japan have remained steady or slightly declining.
Insert Chart 1- 2 here
However, an examination of the industry components of the data indicates changes in the
heterogeneous mix of firms during the time of our study. Chart 3 describes the startup rates per
industry and there is a long-term decline in the construction industry. This decline is following
the asset bubble collapse and subsequent business decline follow by austerity measures of the
Japanese government restricting building programs, (Vogel 2006). While the changes in the
Japanese construction industry are beyond the scope of this paper, it is notable that this decline
masks an increase in other sectors, notably the service sector. We suggest that the entry of
individuals into the service sector after capital barriers were removed were overcome by a long-
term downward trend in contraction firms caused by exogenous political events. However, we do
not find strong support for our hypothesis 1 that reforms increase the amount of startups.
Insert Chart 3 here
establish an average monthly amount and then multiplied by 12 to establish an average annual amount. In addition, the Ministry of Agriculture, Fisheries and Forestry also produces statistical databases; the Census of Agriculture and Forestry, and the Fishery Census 7Alternative methods to track the number of new firms is to study the filings of payroll tax liabilities reported by the Ministry of Health Labor and Welfare issues in the Annual Report on Employment Insurance Programs. In addition, business starts are counted by compiling new incorporations. The Ministry of Justice issues the National Tax Agency Annual Statistics Report. In this case, new employer tax registrations serve to indicate starts and are compiled on an annual basis.
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Individuals Selecting Entrepreneurship
We next focus on our propositions that differing populations are more likely to start new
firms after reforms. The results of our logit regression are reported in table 6, below. Support for
H3a is indicated by the greater than unity and significant odd ratio for the exec variable, and
similarly for H3b by the significant and greater than 1 coefficient for female and the less than
one and significant coefficient on ceo_age. Together, they indicate the greater likelihood of
executives, females, and younger individuals starting firms after the reforms of 2003. This is
brought into better relief in Chart 6. The chart compares the rates of entry in our database of
executives stratified by industry and indicates greater entry rates for prestigiously educated
founders after reform in all studies industry categories. The effect is greatest in the industrial and
high capital technology industries. Similarly, for female founders illustrated in Chart 7, females
enter all industrial segments - except finance - at a greater rate after 2003 and the effect is
greatest in low capital technology firms and service industry segments. Overall, we find support
for both of the hypotheses related to individuals starting firms. It appears that after reforms, the
prestigiously educated, females, and younger individuals formed an increasing proportion of
founders.
It is notable, though, that they emphasize their entry in differing industry segments. The
executives increasingly selected high capital requirement industrial and technology firms while
female and younger entrants emphasized lower capital industries such as services, software and
e-commerce.
Insert Table 6; and Charts 6 and 7 here
Table 8 reports multivariate models. Model one reports controls only. Model 2 is our hazard
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model testing the likelihood of bankruptcy and model 2 are the result of our logit model of the
likelihood of individual types starting firms. Models 4 and 5 report the OLS results on the
growth performance of new firms before and after reforms. Model 5 includes various two-
variable interactions. Considering the control variables first, results support findings in prior
literature. As expected, growth is negatively related to firms’ age and positively related to the
square of firm age suggesting diminishing growth as the firm ages, indicating expected growth
patterns in the literature in that younger firms grow faster than older firms. Also giving expected
result, improved growth is associated with firms with larger initial capital endowments and
judicious use of credit. Consistent with both practice and observations of new firms in Silicon
Valley, companies that replace their founding CEO’s seem to perform better. Overall, controls in
our model give expected results adding to the robustness of our model.
In support of our Hypothesis 2, firms are more likely to enter bankruptcy after reforms.
We assess the results of our hazard ratio test in model 2 by examining the coefficient on the
yr03_09 variable that is significantly greater than unity. In addition, there is a significant and
negative coefficient on the age variable indicating that the older the firm, the less likely is
bankruptcy. Our argument is that entrepreneurs with career alternative post bankruptcy will be
likelier to exit is supported by the greater than one hazard ratio on the prestige_univ variable
implying that those for the top ten universities in Japan were liker than others to declare
bankruptcy after reforms. These results are consistent with prior literature that bankruptcy risk is
greatest when the firm is young and with the Gimeno (Gimeno, Folta et al. 1997) argument that
resistance thresholds were lowered in the decision problem of entrepreneurs after costs of
bankruptcy were lowered and are even lower for individuals with good alternatives. It is notable
that technology firms are less likely to exit with bankruptcy than others. It is possible that public
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efforts to particularly support technology firms in Japan can explain this, (Whittaker 2001).
Firms founded after reforms grow faster growth than firms founded before reforms
controlling for age. Reform is positive and significant in models 4 and 5, and the entry of
prestigiously educated individuals is associated with this as the coefficient on the prestige_univ
variable is positive and significant as well as the interaction of reform with the top tem alma
mater is significant and positive in model 5. Consistent with our argument that highly
enfranchised individuals select entrepreneurship after reforms, the interaction between the
founder’s age and reforms is positive and significant. The greater than one and significant odds
ratio on female and less than one odds ratios on ceo_age in model 3 indicates that younger
individual and females are also likelier to found firms, however, only the prestigiously educated
are directly associated with better growth. Moreover, the positive coefficient on the interaction
between ceo_age and reform in model 5 suggests that improved growth is associated with older
founders. Interpreting these results, it seems that after reforms, the prestigiously educated,
females and younger individuals are more likely to found firms, but performance is associated
with the older and prestigiously educated. This implies that it is the incentives that tempt the
more enfranchised individuals to enter is likely to cause the improved growth that we observe
after reforms. Overall, we find that even after controlling for traditional factors affecting firm
growth, reforms in the institutional environment changed the calculation of potential
entrepreneurs, and with their entry firm performance increased.
High Performance
If prestigiously educated individuals start better growing firms as our results suggest,
perhaps they are also associated with exceptionally performing firms in terms of growth. Extra-
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ordinary growths is found with interesting Silicon Valley firms such as Google and Facebook,
and are similarly associated with Japanese firms such as Softbank and Rakuten. Academic and
practitioner observers seek these signal firms as indications of the entrepreneurial habitat health
of an economic domain, (Miller 2000). We tested this idea by defining a variable, hicagr, a
binary variable that take the value of 1 if a firms cumulative growth rate since founding is 2.5
standard deviations above the mean cagr and using a logit regression against our control and
explanatory variables. The results are presented in Table 9. We examine the coefficients (odds
ratios) on the prestigious university and founder age variables and find them to be significant and
confirm that older alumni of top ten universities increase the likelihood of a firm founded after
reform to be an extraordinary growth performer.
Insert Table 9 and Chart 8 here
Discussion and Conclusion
Our result support our arguments that institutional reforms can alter the incentives of
individuals selecting entrepreneurship to effect performance as they form new firms even in the
absence of increased new formation rates. Institutional theorists have argued that institutions
impact the founding rates of new organizations, (Russo 2001; Sine, Haveman et al. 2005).
Institutional changes that increase the legitimacy of a sector appear to result in increased
entrepreneurial opportunity and founding activity (Sine and David 2003). Yet, there is increasing
interest in how institutions help to shape the behavior and performance of new firms. While
increased entrepreneurial activity might be beneficial for society in the aggregate, we have little
theory or evidence that would predict whether or when institutional change results in higher
performing firms. If institutional change merely increases the founding rate, but we leave
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unexplored the performance impact, then it leaves open the possibility that the net result is
simply a transfer of revenue or jobs from older, incumbent firms to new entrants. We seek to
contribute to this literature by arguing that institutions, through their effects on the type of
individuals founding firms and the character of the firms created, has effects on venture
performance. We provide support for our hypotheses by examining whether institutional reforms
in Japan that were targeted at increasing the rate of entrepreneurship had an impact on the growth
rate of entrepreneurial firms.
The reforms in Japan subsequent to the beginning of a decade of economic stagnation in
1990 provide us with the natural experiment to examine our ideas. Prior to the reforms,
institutions once viewed as crucial to Japan’s economic growth and stability came to be viewed
as barriers. Japanese labor market rigidity (Conrad 2009), idiosyncratic venture capital systems
(Kenney, Han et al. 2002), adverse risk attitudes (Suzuki, Kim et al. 2002; Bird 2003), infrequent
university technology licensing, (Kneller and Shudo 2008), and inadequate legal and accounting
infrastructure in Japan (Hawkins 1993), reduced the viability of start-up potential in comparison
to Silicon Valley.
Supporting the idea that Japan’s economic climate as inhospitable to a dynamic
entrepreneurial dynamic are data suggesting that the startup rate in Japan is low and declining
when compared to other advanced economies. The Global Entrepreneurship Monitor, for
example, reports that Japan has the lowest rate of entrepreneurial activity among surveyed
countries. Although this conclusion has recently come under critical scrutiny suggesting that
GEM methodology understate startup rate is understated, (Acs, Desai, Klapper 2008). Moreover,
the economic trajectory of China created economic uncertainty in Japan as manufacturing
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industries realigned their strategies, moved their factories to China, and focused on smaller and
more specialized business lines while engaging in new employment practices, (Vogel 2006;
Schaede 2008). This continuing re-assessment of Japan’s entrepreneurial and innovation climate
increasingly became the subject of a national policy reform based on the idea that the legal and
institutional architecture of Japan was no longer relevant to a new economic logic.
Before reforms, both the prestigiously educated and female entrepreneurs were
infrequently observed in Japan prior to in comparison to Silicon Valley. In a survey firms
founded between 1990 and 2000 in Japan and Silicon Valley, female entrepreneurs comprised
28% of the surveyed entrepreneurs in Silicon Valley yet were only 4.5% in Japan. In educational
background, there were substantive differences with 62% of Silicon Valley entrepreneurs
holding post-graduate degrees in contrast to 32% in Japan, (Suzuki, Kim et al. 2002). This is
consistent with the prior literature before the reforms of 2003 that entrepreneurs in Japan shared
idiosyncratic demographics compared to the well-studied homogeneity of typical careerists there.
It is likely that social institutions in Japan can account for much of the observed
difference in entrepreneurial populations before reforms. In the case of Japan potential
entrepreneurs farther along a career trajectory than new graduates have a greater risk of lifetime
earning impairment by entry into new firm employment (Harada 2005). High capital
requirements can comprise a substantial portion of a family’s retirement savings as many in the
past relied on company pensions. Thus the risk of loss of both pension and savings is potentially
more catastrophic for older entrants than younger. While jobs with pension benefits are
becoming increasingly scarce, the reliance on saving is even more essential and the onerous
bankruptcy burdens before reforms may have discouraged more experienced potential
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entrepreneurs. Overall, the lowering of entry capital requirements and reform of bankruptcy laws
can directly affect the financial calculations of these nascent entrepreneurs and perhaps cause
larger proportion to found new firms.
Our results suggest that after the 2003 Japanese reforms lowering the amount of capital
required to found a firm and reducing individual bankruptcy liability, that the performance of
firms increased. The post-reform performance of younger, entrepreneurial firms was even more
positively affected. These results support the idea that these reforms facilitated better performing
firms. The institutional change might have either encouraged the entry of individuals who have
sufficient ability but were otherwise financially-constrained from founding firms or encouraged
individuals towards a higher risk, higher reward style of entrepreneurship that resulted in an
increase of young, high growth firms. Notably, our results show that firms did not take on
significantly greater risk after the reforms. Rather, the debt to equity ratio (a common measure of
financial risk) actually fell in the post-reform time period. Further analysis will seek to
disentangle these two more detailed mechanisms.
This paper contributes to literature on institutional theory by highlighting the impact that
institutions have on entrepreneurial firm performance. While we might have expected, based on
previous work that institutional reforms targeting entrepreneurship might reduce firm
performance through increased levels of competition, resulting from more entry and thus prices
closer to marginal cost, instead we find evidence for increased firm performance. We examine
reforms that lowered capital requirements and reduced the risks associated with bankruptcy. The
findings suggest that while these reforms may have lead to a more competitive market, the
overall impact was that individuals became more likely to found higher growth firms. We
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contribute to the emerging view that institutions help to shape the level of productivity of new
firms in the economy through their effects on individuals and their choices to become
entrepreneurs. The paper also contributes to the entrepreneurship literature by showing the
importance of the broader institutional environment at founding in shaping the performance
outcomes of entrepreneurial firms.
Our results also have important practical implications for policymakers. Many local,
state, and national governments are currently seeking to encourage more high growth
entrepreneurship in the expectation that it leads to job creation and GDP growth. Previous work
had either shown institutional mechanisms for increasing the rate of entrepreneurship with little
to no evidence that these new firms were high growth firms (Sine, Haveman et al. 2005);
Romanelli 1989). In fact, prior work had suggested that by attempting to encourage
entrepreneurship, policymakers might actually be encouraging wealthy, but low ability
individuals to found firms that were more poorly performing. Our findings point to specific
reforms undertaken in Japan, which had a particularly strong impact on increasing the growth
rate of entrepreneurial firms. This finding suggests institutional changes that appear to increase
the rate of high growth entrepreneurship.
If entrepreneurship is the engine of economic growth and the perennial gale of “creative
destruction” referred to by Schumpeter (1934), it appears that the structure of institutions in
society plays an important role in determine how strong that gale is in the economy.
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Chart 1
Chart 3
Table 2 SIC Category Description Dataset
28 Chemicals Kauffman, STAJE 35 Industrial Machinery Kauffman, STAJE 36 Electronics (incl. Semiconductors) Kauffman, STAJE 38 Instruments, Test Equipment Kauffman, STAJE 372 Aircraft STAJE 376 Guided Missiles, Spacecraft STAJE 737 Software, Data Processing (incl. ISP’s) STAJE 871 Engineering Service STAJE 873 Research Centers STAJE
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
Entry 4.6 4.8 4.6 4.7 4.2 3.9 4.4 4.9 4.4 4.1 4 4.1 4.4 4.8 5 Exit 3.4 3.4 3.6 2.5 2.8 3.1 4 4 4.4 4.6 4.8 4.5 4.3 4.4 4.5
0 1 2 3 4 5 6
% annual change -‐ all employment
establishments
Japan Entry and Exit Rates Employment Insurance Data
0
0.1
0.2
0.3
0.4
0.5
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Percentage Share of Total
Industry Share of Startups -‐ Japan Primary
Construction
Industrial
Technology
Whole/Retail
Finance
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Table 3
No Foundation Date Foundation Date t-test H0=0, unequal var Curr-Prof 2541 1201 1.53 Curr-Sales 336 311 0.9432 Capital 12586 7221 4.79 Gender 1.08 1.07 1.46 CEO_DOB 1961.9 1961.6 0.963 For_own 0.002 0.002 -0.329 Employees 10.6 10.4 0.169
Chart 7
Table 7 Covariance Matrix
reform top_coll gender dob founder brcagr Age credit gdp_cagr capital tech reform 1.0000 top_coll 0.0331 1.0000 gender 0.0293 -0.0090 1.0000 dob 0.1452 -0.0248 -0.0217 1.0000 founder -0.0353 -0.0215 -0.0543 -0.0012 1.0000 brcagr -0.0364 0.0207 -0.0024 0.0128 -0.0204 1.0000 Age -0.4215 -0.0274 -0.0296 -0.3435 -0.3381 0.0123 1.0000 credit -0.1173 -0.0561 0.0013 0.0558 -0.0981 0.1387 0.2187 1.0000 gdp_cagr -0.6180 -0.0391 -0.0277 -0.2801 -0.1059 0.0280 0.7558 0.1654 1.0000 capital -0.0003 0.0353 -0.0122 -0.0122 -0.0453 0.0447 -0.0104 -0.0906 -0.0014 1.0000 tech 0.0282 0.0221 -0.0250 0.0250 0.0063 0.0041 -0.0528 -0.0108 -0.0403 0.0284 1.0000
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Table 8
MODEL Hazard 1 Logit 2 OLS 3 OLS 4 OLS 5
DV = MEANS bankrupt reform CAGR CAGR CAGR
firm_age 14.1 -.4794 *** -.1658 *** -.1658 *** -.099 *** firm_age2 .0042 *** .002 *** .0011 *** credit_rating 38.6 .0146 *** .0147 *** .0117 *** GDP_PC 3.9(MY) -.0007 -.005 *** -.003 *** capital_initial 12.9(MY) .0000008 *** .9999 ** .000002 ** .000002 ** .0000003 *** founder_CEO 8.8% -.3982 *** -.3344 *** -.1961 *** comp .9999 .0000001 .0000004 industrial .2601 1.239 .1565 .1139 .1398 * contruct .3271 .8076 -.1216 .0786 -.126 hi-capital tech .3898 1.335 -.0596 -.0696 .0287 lo-capital tech .0807 * .0554 -.1327 .0734 sales 1.574 * -.0156 -.0916 .0134 service 1.684 ** -.1142 ** .0568 -.0638 yr03-09 1.889 *** reform .6406 *** 5.057 *** prestige_univ 1.4% .3615 *** 2.186 *** .3338 *** -044 gender 6.4% .0624 1.24 ** -.0735 - -0265 ceo_age 48.7 .9643 *** .006 *** -.0005 ref X firm_age -8694 *** ref x col 1.261 *** ref x gen -.0589 ref x ceo_age .01254 *** . Constant NA NA 2.82 4.179 *** 2.546 F 62998 388.258 *** 273.34 *** 258.87 *** 397.22 *** R2 NA NA .2374 .283 .4010 N 16814 15399 11192 13190 12480 12480
8 Chi2
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Table 9 dv = hicagr odds ratio std. err. sig firm_age .7246 .3269 firm_age2 .8673 .0504 ** prestige_univ 2.386 1.254 * female .7419 .2506 ceo_age 1.012 .0081 * indus 2.206 1.871 constr 2.024 1.710 serv 1.846 1.543 tech .4278 .2206 * whole 3.243 2.699 retail 2.998 2.511 Log likelihood -463.961 No. of obs 14305 LR chi2 (12) 1493.83 *** Table 1
Sample Partition Count Ratio Initial COSMOS Data 155,022 Firms with company ownership or no operations for two years 112,745 0.73 Net Independent firms (extant) 42,277 Net Independent firms (bankrupt) 12,733
Firms with foundation date (extant) 12,822 0.30 Firms with foundation date (extant) 12,733 1.00 Random selection bankrupt firms 4002 0.31
Final Sample 16,824
dv = hiprof odds ratio std. err. sig firm_age .9899 .0258 firm_age2 1.0002 .0004 prestige_univ 3.147 1.179 *** female 1.474 .4222 ~ ceo_age .845 .0403 *** ceo_age2 1.001 .0004 *** indus .5454 .1967 * constr .1597 .0627 *** serv .6441 .2175 tech 1.643 .4665 * whole .1667 .0706 *** retail .3158 .1205 *** Log likelihood -826.648 No. of obs 14305 LR chi2 (12) 93.72 ***
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