Discussion Papers In Economics
And Business

A nation without a corporate income tax: Evidence
from nineteenth century Japan
Kazuki Onji and John P. Tang
Discussion Paper 15-12

Graduate School of Economics andOsaka School of International Public Policy (OSIPP)
Osaka University, Toyonaka, Osaka 560-0043, JAPANA nation without a corporate income tax: Evidence
from nineteenth century Japan
Kazuki Onji and John P. Tang
Discussion Paper 15-12

May 2015

Graduate School of Economics andOsaka School of International Public Policy (OSIPP)
Osaka University, Toyonaka, Osaka 560-0043, JAPANA nation without a corporate income tax: Evidence
from nineteenth century Japan
Kazuki Onji and John P. Tang †May 2015

Abstract
This study provides evidence on tax distortion to organizational choices of firmusing historical data. We utilize the 1887 introduction of a personal income tax(PIT) in Japan as a quasi-experiment to examine tax-motivated incorporation. We
circumvent the data limitation in the 19th century by drawing on a firm-level dataset
constructed from genealogies of Japanese corporations. The sample is 3,203 firmyear observations spanning 1880-1892. We find that the introduction of PIT affected
the adoption of simpler types of corporations and increased the corporate share ofestablishments by about 3 percentage points. The evidence indicates the role of acorporate income tax as a backstop to maintain revenue performance of PIT.
JEL Classification: G34, H25, K34
Keywords: Tax Avoidance, Organizational Form, Business Incorporation†

Onji (corresponding author): Graduate School of Economics, Osaka University, 1 - 7 Machikaneyamacho, Toyonaka, Osaka, Japan, 560-0043. Email: kazuki.onji@econ.osaka-u.ac.jp; Tang: Research
School of Economics, Australian National University, Building 26, Canberra, Australia, ACT0200. Email:john.tang@anu.edu.auIntroduction
Firms’ choices over their organizational forms have tax consequences: whether a firmchooses to incorporate is such an ubiquitous issue for businesses that it is a staple topic
in finance textbooks (Hanlon and Heitzman, 2010). To policymakers and academics, theextent to which taxes affect incorporation decisions is an important consideration: taxmotivated incorporations can reduce government revenue by compromising the revenue
performance of a personal income tax (PIT).1 In understanding a tax system as a set ofinteracting tax laws, the organizational choice is a knot that ties PIT and a corporate
income tax (CIT), and is essential in evaluating and predicting impacts of tax policies(Cullen and Gordon, 2007).2 Earlier empirical studies (Gordon and MacKie-Mason, 1994;
Mackie-Mason and Gordon, 1997; Goolsbee, 1998) find small influences of taxes on organizational forms, indicating the possible dominance of non-tax factors: the limited
liability status and external finance considerations can dominate the decision to incorporate, while administrative simplicity and fewer disclosure requirements may lead others tochoose the sole proprietorship structure. However, later studies (Goolsbee, 2004; de Mooij
and Nicodme, 2008; Liu, 2014) raise concerns over the identification strategy in earlier
studies based on time series analysis of aggregate corporate share, and instead employ
panel data to take advantage of cross-section variation in tax rates across states or countries. These later studies show that the influence of taxes may in fact be larger thanpreviously thought, re-opening the debate on the magnitude of tax effects.
One alternative strategy, which provides clearer identification, is to utilize the introduction of PIT as a quasi-experiment. Absent PIT or CIT, the choice of organizational
form should be determined by non-tax factors only. The introduction of PIT changes
incentives, offering a sharp quasi-experimental setting to examine behavioral responses.
The tax incentive is salient, which Chetty (2012) stresses to be a characteristic importantin decision making. Although a simple idea, this strategy is difficult to implement: industrialized nations started to introduce PIT during the 19th century when official statistics
on corporations, let alone sole proprietors, are limited or non-existent.3 Our paper circumvents this data limitation by drawing on a new approach in economic history thatallows analysis of business activities during a period when official data do not exist. Using
firm-level data from genealogies of major corporations compiled by Yagura and Ikushima(1986), Tang (2011, 2013) examines the Japanese economy during the Meiji period (18681912). These data allow us to distinguish joint-stock corporations from sole proprietors
as well as other corporate forms, and to look at the response of taxpayers to the introduction of PIT in 1887. The sample of firms drawn from genealogies is a non-random
subset of the population of businesses that existed at the time, and larger firms are overrepresented. As such, the sample based on genealogies likely leads to an underestimation,
since the findings in the literature show smaller businesses tend to respond more strongly.
1de Mooij and Nicodme (2008) show that a shift from the personal to corporate tax base contributed
to the stability of revenue from corporate income taxes despite the tax competition that drove averagetax rates down in Europe.
2
Cullen and Gordon (2007) demonstrate that the progressivity of PIT may discourage entrepreneurship but in fact can encourage startups by sharing risk with the government.
3
Grossfeld and Bryce (1983) provide a historical account on the origins of income taxes in the U.K.,
Germany, and U.S. The earliest attempt was by the U.K. under the Pitt administration in 1799, introduced as a war tax. After an abolishment in 1816 upon the conclusion of the Napoleonic War, the Peeladministration re-introduced an income tax in 1842. The U.S. first introduced in 1862 also as a war tax
and repealed it in 1872. The 1894 Income Tax Act was found unconstitutional and did not went into
effect.

1

Nonetheless, the sample represents an important subset of firms, including those belonging to Japanese-equivalent of Rockefeller and Carnegie conglomerates, and the behaviorof large companies is of independent interests.
This study employs a quasi-experimental framework in examining 3,203 firm-year observations spanning 1880-1892. We utilize the time variation in tax incentives created by
the introduction of PIT and control for the macroeconomic environment and industryspecific trends. The baseline analysis treats the data as a cross-section and tests whether
the probability of a firm taking a corporate form changes discretely following the PIT
introduction. We implement a battery of robustness checks to assess the sensitivity of
estimates. First, to control for unobserved heterogeneity, we reformulate the data intoa panel dataset by aggregating firm-year observations by firm genealogy and industry.
Second, we consider the dynamic dependence using the panel dataset on industries toprovide estimates of dynamic panel regressions. Third, the identification of tax effects
relies on the before-after change, which could be confounded by unobservable time shocks.
We chiefly address this issue by including a set of macroeconomic variables to control forchanges in business conditions, but also consider alternative explanations.
The results suggest that the introduction of the PIT had significant influence on theincorporation decision. An estimate from the baseline specification implies that PIT
increased the incorporation rate in the sample by around 3.2 percentage points with a95-percent confidence interval of [1.2, 5.3]. In terms of marginal effects, with the top PIT
rate of 3 percent, our estimate suggests that a 1-percentage-point increase in a PIT rateincreases corporate share of firms by around 1 percentage point.4
Previous studies recognized large tax variations in the early 20th century U.S. andutilized them in analysis (Goolsbee, 1998; Liu, 2014; Romer and Romer, 2014). Our
study extends the historical studies on the tax distortion to organizational forms in several ways. We examine a period not covered in the previous studies, enabled by the newgenealogy-based data collection pioneered by Tang (2011, 2013).5 We also provide additional estimates on the taxpayer response from a setting outside the U.S. For example,
Goolsbee (1998) examines aggregate U.S. data over 1900-1939, which span the federal CIT
introduction in 1909 and the re-introduction of PIT in 1913 after a constitutional amendment, so the order of tax changes is opposite to ours. He finds statistically significant but
negligible impacts. Liu (2014) examines a state panel dataset drawn from U.S. census
data in the years 1909, 1914 and 1919, and finds a 1-percentage-point increase in PITleads to a 5.5-percentage-point increase in corporate share. As emphasized in previous
studies, modern day tax administration is much more sophisticated. That said, historicalevidence provides an important complement to scholarship that utilizes contemporary tax
laws. Moreover, the introduction of an income tax, whether personal or corporate, is anepochal event in any country’s history of public finance and therefore warrants careful
statistical documentation.6
4

To be sure, this estimate is not of a structural parameter but is a reduced-form estimate, so thatfactors such as economic institutions in the 1880s Japan, sample characteristics, and a possible nonlinearity of responses in tax rates should be kept in mind in extrapolation and in comparison withexisting estimates.
5
Takahashi (1956) provides an early descriptive study on this topic, utilizing aggregate data from the
Meiji period.
6
Our study also adds to evidence provided by specific policy changes. Scholes and Wolfson (1991)
document an explosion of tax-favored S-corporations following the Tax Reform Act of 1986. Freedman
and Crawford (2010) document a rise in incorporation when the U.K. set the starting rate of CIT at 0
percent over 2002-2006, particularly for businesses with fewer than 10 employees.

2The remainder of this paper is organized as follows. Section 1 provides the institutional
background. Since this paper is the first application of genealogical data in examining
a topic in public economics, in Section 2, we elaborate on how drawing a sample fromgenealogies of present-day major firms affects the sample’s characteristics and consider
precautions needed to identify the tax effects. Section 3 presents an empirical analysis
including robustness check, and Section 4 concludes.

1

Institutional background1.1

Early income tax

The Meiji Japanese government replaced the feudal administration in 1867 and pushed
for industrialization to catch up with advanced nations. Initially, the new government
relied on a land tax to finance the modernization of the military and industries.7 Against
the backdrop of rising political demand to fund the navy and to raise taxes from industrialists, the introduction of a PIT was considered, at least since 1884 (Hayashi, 1965,
p. 299). The Ministry of Finance drafted and sent an income tax proposal to the Prime
Minister’s Cabinet in January 1887. On February 1887, the proposal was sent to the Senate (Genrōin) with some modifications, and the following month, the Income Tax Law(Shotoku Zeihō) was passed with implementation starting July 1887. Table 1 provides asummary of the main features of the early PIT, along with a reform in 1899. Initially,
tax rates ranged from 1 to 3 percent with a large exemption of 300 yen. The rate wassimple progressive, unlike the current PIT, so that taxpayers faced a notch of 3 yen at
300 yen in income.8 In the initial year, the total number of income tax filers amounted
to 0.3 percent of total Japanese population. As a comparison, the rates for U.S. personaltax in 1913 ranged from 1 to 7 percent and the personal exemption of 3,000 dollars. The
total number of tax filers amounted to 0.5 percent of the total U.S. population.
Dividend income was taxable but otherwise corporate income escaped taxation. We
consider local tax consequences later in this section. The main argument for excluding
corporate income was the protection of the nascent industrial sector. At senate meetings,
policymakers showed clear awareness of tax avoidance opportunities through incorporation, but opinions differed as to whether loopholes would be exploited.9 Businessmen at
the time would have understood the tax advantages to incorporation.10 The 1899 reform
added corporate income as an additional category (Type 1) in the Income Tax Law andlevied 2.5 percent tax on accounting incomes, which were far from standardized at thetime. Dividend income became exempt to avoid double taxation.
7

The tax base for the land tax was assessed land values that remained constant regardless of crop
yield. The land tax was therefore penalizing during the severe deflationary period in the early 1880s,
particularly for peasants. The tax policy debate at the time raised inequality as a motivation for a
tax reform. Tariffs, which governments of developing economies usually rely on to raise revenue, were
negligible since Japan had signed treaties with advanced nations that restricted tariff rates.
8
This amount was three times as much as a starting salary of a police officer and was US$228 basedon the average exchange rate in 1887 (Tōyō Keizai Shinpōsha, 1975, Table 156).
9
At a senate meeting held on February 22, 1887, a member of a council argued that noblemen weretypically owners of businesses and as such noblemen would not conduct petty tax avoidance. Anothercouncilman forcefully pointed that it is unfair to treat businesses run by one person versus multiple people
differentially (Orii and Yamamoto, 1990, pp. 77-78).
10
Letters written by a manager in Mitui zaibatsu from the early 20th century clearly show tax considerations were of first order importance in incorporating Zaibatsu companies. See, for example, Nakamura(2010).

3

The enforcement and administration of the early PIT was different from modern income taxes administered by tax specialists; the central government delegated the responsibility of assessment and collection to the county-level administration. A county-level tax
commission, in charge of assessment, consisted of personnel elected in a local election, andserved in part as a moderator between the administration and taxpayers. Since the suffrage at the local election depended on the amount of tax payments, committee members
were local personages and often overlapped with elected officers in local assemblies.11 The
tax committee checked tax returns submitted by taxpayers and also conducted investigation, assisted by the county administration. The early assessment appears idiosyncratic;
it is not until around 1893 that the administration started to ‘predict’ income on the basis of observable features and compared them with declared figures.12 The National Tax
Agency gradually took over responsibilities: The government established regional tax offices which took charge of tax collection in 1896, and the local offices assessed corporate
income (but not personal income) from 1899. The enforcement regime would have varied
considerably given the new administrative apparatus: The number of personal tax payers
increased by 75 percent in one year over 1898-99 despite the same personal exemption
amount.13 Given those weaknesses in administration, firms might have found it easier tosubstituted tax avoidance with tax evasion. Whether firms respond to tax incentives by
incorporating businesses is, however, an empirical question.

1.2“Corporation” in the Meiji era

What did it mean to be a corporation in Japan during the Meiji period?14 The previous Edo period (1603-1867) had a flourishing commercial economy. By the beginningof the Meiji era, a well developed customary law enabled merchants to issue promissory notes. The archetype of modern corporations existed but most joint ventures werefamily-oriented (Miyamoto, 1990). To promote industrialization, the Meiji government
published textbooks on incorporation, coordinated merchants to form trading companies
in 1869, and organized national banks as joint-stock corporations. Absent formal regulation in most sectors, the various prefectural governments based administrative orders
about incorporation on the incorporation textbooks published by the central government.
However, most sectors were not regulated, so many aspects, such as investor liability andvoting rights of shareholders, were not well understood. For firms not in banking and key
industries, incorporation often amounted to notifying a local authority.15
While regulation at the national level was absent, prefectural governments stepped up
regulation since the mid-1880s. Osaka prefecture, for example, required new as well as
existing corporations to submit corporate charters, starting from February 1886. Fraud,in which a swindler collected funds from investors and fled, was common. The urgent
11

The Rules and Regulations for Prefectural Assemblies (Fukenkai Kisoku) of 1878 restricted thevoting right on local election to male who pays at or more than 5 yen in land tax. The first national
election was in 1890.
12
A record from a county in a sericulture district shows a committee based assessment on observables
such as land price, local business tax, wage, amount of loan extended (Orii and Yamamoto, 1990, pp.
334–335).
13(Tōyō Keizai Shinpōsha, 1975, Table 730)
14
Miyamoto (1990) and Nakamura (2010).
15
For example, in Tokyo Prefecture, firms notified a county office after incorporation, excluding thosein bridge and embarkment constructors, land/water transportation, insurance and banking (Nakamura,2010).

4need for order led to a drafting of the Commercial Code (Shōhō), but complaints delayed implementation until 1899, except for sections including corporate laws that were
promulgated in January 1893.
The Commercial Code of 1893 defined three types of corporation, and outlined requirements for organizing a corporation (Yoshida, 1998). First, investors in joint-stock
corporations (kabushiki gaisha) enjoyed limited liabilities, but needed to obtain approvalon articles of incorporation and also a licence to establish. Debtors to joint-stock corporations could request disclosure of balance sheets. Limited partnerships (gōshi gaisha)consisted of investors with partners with limited and unlimited liabilities while partnerships (gōmei gaisha) consisted of partners with unlimited liability. Requirements forfounding the latter two types were fewer; a company needed to register but not a licenceto establish. Responsibilities however became more stringent with the 1893 reform: anunlimited partnership was liable to cover losses within 2 years a partner’s departure, forexample. In sum, except for the regulated sectors, ‘corporation’ was loosely defined until
1893, when the partial implementation of the Commercial Code in 1893 finally establisheda proper guideline.

1.3

Local tax

Were there other taxes that might have discouraged, or encouraged, incorporation? At
the beginning of Meiji, the local administrations inherited taxes and levies from the Edo
period and local taxes varied considerably. Concerns about uneven tax practices, andthe sheer number of various levies, led the central government to coordinate prefecturelevel taxes by standardizing regulation. One of the main rules, set in 1878, concerned
those on the Business Operations Tax (Eigyō zei), which was a tax based on external
characteristics, such as sales, and levied mainly on merchants at its initial application.
This 1878 rule on the Business Operations Tax set an upper limit on the annual levy bybusiness category. For example, the maximum annual levy for a company (kaisha) andwholesalers was 15 yen while that for retailers was 5 yen (Hayashi, 1965). In an application in Saitama prefecture, the amount of tax was a step function of sales revenue. A
company in that prefecture was defined as a business with a shopfront financed by two
or more people that operated in commerce, manufacturing, transport, printing, contract
work, and money lending (Mizumoto, 1998, p. 42). Thus, except for wholesalers andretailers who were taxed regardless, incorporation triggered a tax liability and therefore
was disadvantageous. An amendment in 1880, however, abolished this categorization andset a uniform maximum tax at 15 yen, and made manufacturing plants liable for taxation
regardless of organizational form. Further, the 1882 amendment abolished the distinction
between commerce and manufacturing and sole proprietorship and corporation, respectively. By 1887, the tax disincentives for incorporation under the Business Operations
Tax had been removed.16
16

As a part of local government reforms, the central government permitted municipal and township/village administrations to levy surcharges on national taxes up to 50 percent of income tax liability
since April 1889. This reform on local government finance was a part of a broader administrative restructuring law passed in 1888. Corporations escaped this surcharge as they were exempt from income
taxation (Maruyama, 1985). For a locality that adopted a 50 percent surcharge, the national-local combined statutory top tax rates was 4.5 percent, providing an additional incentives for businesses residingin the locality to incorporate.

5

2

Data

2.1

SourceThe main data source is the collection of corporate genealogies edited by Yagura andIkushima (1986), who traced lineages of 1,089 corporations that were traded at the firsttier of the Tokyo Stock Exchange in 1984. In constructing genealogies, these businesshistorians drew from “autobiographical” accounts of corporate histories published by the
corporations themselves. These corporate “family trees” provide information such as adate of establishment, ownership type, industry classification, and geographical location,
but do not contain financial information. Like a genealogy of an individual family, a corporate genealogy traces corporate combinations and separations in form of mergers anddivision sales. As Tang (2011) emphasizes, the entries are not just those whose ultimate
descendent survived and prospered. The autobiographical accounts of each corporation’s
history provide a record of asset transfers from bankrupt firms in addition to firms thatwere taken over in mergers. Transfers of assets, such as factories or new equipment, were
notable events given their worth. The genealogies therefore include defunct firms whose
ancestries are also tracked. Since most reorganizations took place within an industry,firms listed on a given genealogy typically are in the same industry.17 The genealogies
record name changes, including those due to changes in organizational forms. Typesof organizational form include sole proprietorship (kojin kigyō), joint-stock corporation(kabushiki gaisha), limited partnership (gōshi gaisha), partnership (gōmei gaisha), limited
liability company (yūgen gaisha), mutual company (sougo gaisha), anonymous partnership (tokumei kumiai ), and government corporation (seifu kigyō).
The key advantage of the genealogical data is in providing firm-level observations,gathered under a systematic scheme, on organizational form for a period when aggregate data by organizational forms do not exist; aggregated data on types of corporation
are available only from 1894, after the partial implementation of the Commercial Code.
The genealogical data provide a good indicator of the overall movements in the economy: the Pearson’s correlation coefficient for the number of non-bank corporations in
the genealogies and the estimated number of non-bank corporations for the economy over
1899-1912 is 0.97 and is statistically significant at the 1 percent level.18 Moreover, thecorrelation coefficient for the number of all firms with real GDP over 1875-1912 is 0.93
and is statistically significant at the 1 percent level.19
It should be noted that the sample of firms from genealogies is a non-random subsetof the population of businesses that existed at the time. As such, the data have unique17
We computed the Herfindahl-Hirschman Index (HHI) from the count of industry classification within
genealogies using unbalanced panel of firms. HHI is a common measure of concentration, and takes values
between 0 and 1. HHI of 1 implies that all firms in a genealogy belongs to a same industry. The average
HHI is above 0.9 whether we use all available sample (1870-1912), restrict to the sample period (18801892), or drop genealogies with fewer than the median number of firms (11) during the sample period.
The average HHI is 0.67 among the top 10 percentile of genealogies in terms of firm count during thesample period, so larger genealogies tend to be more diverse but are still concentrated.
18
We obtained the number of Type 1 income taxpayers for 1899-1912 to approximate the number ofcorporations in the population. We then subtracted banks to obtain the number of non-bank corporations(Japanese Bankers Association, 2012). For the genealogies, we dropped banks, sole proprietors andanonymous partnerships from the original sample to obtain the number of corporations used for thiscomparison.
19
The data for GDP is the ‘Yamada series’ (Japan Statistical Association, 1987, Table 13-03). We used
price index from Nakazawa (2001) to deflate GDP. The number of firms in the genealogies is computedfrom the whole original dataset.

6

characteristics that become important when drawing inference. As t approaches 1984, thenumber of firms approaches 1,089 by construction. The share of corporations becomes 100
percent mechanically. We would be reluctant to draw inference from a sample close to thetime when the historians constructed the genealogies, out of concern for this mechanicalselection. The current sample is however from a century before the construction of thegenealogies and mechanical selection should not be an issue; mechanical selection should
lead to a decline in the number of firms, but we see an increase in firm numbers over the
Meiji period.
Another important characteristics is that genealogies are observed only for firms successful enough not only to become public corporations but also be listed at the first tier,which has tighter listing requirements and receive more investor attention. Reflecting thisselection, the data include major zaibatsu from the Meiji period such as Mitsui, Sumitomo,
and Mitsubishi. Genealogical data do not contain financial information, but qualitative
information suggests that the sample contains large companies from the period.20 Indeed, the incorporation rate gauged from tax statistics from 1899 is 1.3 percent, whilethat from the sample excluding banks is over 60 percent in that year, suggesting that the
sample predominantly draws from the formal sector.21 If initial capital affects survival
probabilities, joint-stock corporations, which are typically larger in size, would dominate
the sample over time. If so, the corporate share would increase over time even without
any tax incentives, though the inclusion of discontinued firms mitigate over-sampling of
successful firms to some extent. The effects of this sample selection through survivorship,
if any, would however be gradual, while the identification relies on an abrupt change at apoint in time. In the empirical analysis, we control for this possible influence by including
a trend term in the regression.
Lastly, and most relevant to the research question, the sample of large formal-sector
firms is likely to lead to an underestimation of tax effects. Previous studies indicate thatthe tax motive affects smaller firms, whose decisions are at the margin of incorporation,
more than larger firms. Liu (2014) finds corporate shares of employment respond less thanthose of firm count and Freedman and Crawford (2010) document that incorporation
rates increased among smaller firms but not larger firms in the UK’s experience with
the 0 percent starting rate. Thus, results based on a sample of genealogies of large
corporations would provide a lower bound on any tax effect and understate the impacts
in the population. Appendix Table A1 lists sources for other data.

2.2

SampleTo prepare the dataset, we convert the genealogical information into firm-year observations. We also drop banks given the industry’s specificity and exclude government corporations out of the same concern. We omit anonymous partners since they are pass-throughentities. There are no mutual companies between 1880 and 1892, so the sample consistsof sole proprietors, partnerships, limited partnerships, limited liability corporations, andjoint-stock corporations.
20

We also find via inspection that a list of 200 largest industrial firms in 1918 (Fruin, 1994, p.329)
overlaps with firms covered in the genealogy.
21
The number of taxpayers filing Type 1 income (6,133) divided by Business Operations Tax filers in1899 (475,917) (Tōyō Keizai Shinpōsha, 1975, Table 728, 730). Small businesses, such as second-handcloth shops, pawn shops and inns, as well as large businesses, such as banks, were liable for the Business
Operations Tax. Tax records from Nagano Prefecture in 1891 show, for example, rich farmers conducted
sericulture and money lending as sole proprietors (Orii and Yamamoto, 1990).

7

Of the remaining organizational types, joint-stock corporations are on average muchlarger than other types of corporations: The average size of paid-in capital for 1895 is 11
and 3 times as large as that of partnership and limited partnership respectively. The theory suggests that the tax incentives affect firms at the margin of incorporation (Gordon
and MacKie-Mason, 1994). Non-tax factors, such as the benefit of limited liability forinvestors, would likely dominate the choice of organizational form of a modern textile factory, for example, while a medium-size family businesses may not find a clear advantage
in incorporation. We therefore treat joint-stock corporations as one category, and combine partnership, limited partnership, and limited liability corporations into a separate
category, referred to as “other corporations”.
Figure 1 provides a preliminary examination, and shows the share of sole proprietors,
joint-stock corporations and other corporations for the entire Meiji period (1868-1912).
The solid vertical line indicates the introduction of PIT. The dotted vertical lines indicate
the timing of other major reforms: the partial implementation of the Commercial Code in
1893, Tax Reform of 1899, and a permanent extension of war taxes in 1906. Also indicated
are the timing of wars: the Civil War (February-September 1877), the First Sino-Japanese
War (August 1894-April 1895), and the Russo-Japanese War (February 1904-May 1905).
As the figure shows the sample consists predominantly of sole proprietors at the beginningof the Meiji period. The corporate share increased gradually throughout the period, andby the end of Meiji, the share of sole proprietors is about a third of the sample. This broad
trend is consistent with the rapid industrialization that took place particularly since the1890s. In 1887, the share of other corporations jumps by 4 percentage points while theshare of sole proprietors falls by 4.8 percentage points. In contrast, we do not see visible
changes for joint-stock corporations around the time. These patterns are consistent withthe conjecture that the PIT induced sole proprietors to incorporate their business into a
simpler corporate form.
Upon the partial implementation of the Commercial Code in 1893, the share of jointstock corporations jumped while the share of other corporations fell abruptly. This shiftsuggests that the Commercial Code affected the choice of organizational forms within thecorporate sector. The Tax Reform of 1899 did not appear to have had a large influenceon the choice of organizational forms, despite the introduction of the 2.5 percent tax
on corporate income. As Table 1 shows, the top marginal rate on personal income also
increased from 3 to 5 percent, countering the disincentives to incorporate. The lack ofa clear response at the aggregate level may be due to these countering tax incentives.
Temporary war taxes, implemented during the Russo-Japanese War, increased the progressivity of the PIT and applied the progressive rate to income earned by partnerships,
limited partnerships, and joint-stock corporations with 20 or fewer shareholders. Since its
permanent extension in 1906, the share of joint-stock corporations increased while thatof sole proprietorship fell, in line with the tax minimization motives.
In designing a quasi-experiment, we limit the sample period to 1880-1892 for thefollowing reasons. First, this period keeps regulatory environment relatively homogenous
across the pre- and post-PIT samples; the Commercial Code of 1893 had had a visible
impact, but in addition, the enforcement regime became more sophisticated over time as
discussed. Accounting for all relevant policy changes would render an empirical model
unnecessarily complex. Second, the sample spans a period of relative political stability
and falls between the Civil War and First Sino-Japanese War. The rise in corporateshare after the latter war may reflect an economic boom that followed. We chose theend year given the partial implementation of the 1893 Commercial Code. The choice of8

end year limits the number of post-reform years to six. We chose the beginning year tokeep the length of the pre-reform period comparable (7 years). Table 2 provides summary
statistics.

3

Analysis

3.1

Baseline modelTo estimate the effects of tax incentives, we utilize the introduction of PIT in 1887 as aquasi-experiment. Since the data suggest that the PIT encouraged the formation of othercorporations, we pool firm-year observations for sole proprietors and other corporations
from 1880-1892 and examine the likelihood of incorporation with the following linear
probability model:
ocit = α0 + α1 P ITt + x0it β + λj t + µk + uit ,(1)

where ocit is an indicator for firm i from time period t being other corporations (i.e.,
partners, limited partners, and limited liability corporations). P ITt is an indicator fortime period at and after 1887. The coefficient α1 captures the difference in the probabilities
of incorporation before and after the reform.
The identification of tax effects relies on the time variation in tax incentives since PIT
was at the national level. Since business conditions can confound the influence of taxes, weconsider several macroeconomic controls (xit ). In the early 1880s, a contractionary fiscal
policy induced a severe deflation, known as the Matsukata Deflation.22 The economy was
still recovering when the government introduced PIT. To account for possible businesscycle effects, we control for the real GDP growth rate. The impact of the business cycle
would have differed by industries, but we have information on industry-level output growthfor some, but not all, industries. To account for this, we consider the growth rate of thenumber of firms in the original sample as a proxy for industry growth, since the overallchanges in the number of firms in the original sample and the GDP growth are strongly
correlated (Tang, 2013). We also include the growth rate of the Tokyo stock price index.
Publicly-traded companies were small in number, particularly in the first years following
the foundation of the Tokyo and Osaka stock exchanges in 1878, but accounted for 30-40
percent of the total capital of joint-stock corporations, so the stock index captures thebroad trend in the formal sector.23 We control for real interest rates to account for accessto external finance.
An increase in incorporation rates over the Meiji period, shown in Figure 1, likely
reflects technological change. Table 3 presents changes in the shares of organizational
types by industry before and after the 1887 reform. Notably, the textile industry, which
underwent a large transformation by the introduction of Western-style factories, exhibits alarge decline in the share of sole proprietors across the periods (-31.7 percentage points).
Some of these increases in incorporation rates may be attributable to the survivorshipbias or mechanical increase as discussed earlier. We therefore consider industry-specificlinear time trends (λj ) to control for technological change and possible influences from
22
The economy in the late 1870s suffered from severe inflation after the Civil War of 1877. Finance
Minister Matsukata implemented deflationary fiscal policy to counter deflation.
23
In 1878, 1885, and 1915, 4, 24 and 151 firms were traded on the stock market respectively (Okazaki
et al., 2005).

9

the dataset construction. In addition, xit includes a vector of firm-level controls: reginaldummies, industry dummies (12 industries), and the number of years since the foundingof the oldest firm in a genealogy to which firm i belongs (‘genealogy age’).24 We consider
a specification with and without µk , a genealogy fixed effect. Firms within a genealogy
typically engage in similar operations, so a genealogy fixed effect should capture thecharacteristics of narrow industry not accounted for by the industry dummies. We allow
for a heteroskedastic error term.
3.1.1

Results

Columns 1-3 in Table 4 show estimates from the linear probability model using the pooled
firm-year sample. The specification in Column 1 includes a full set of macroeconomic
controls, an industry-specific time trend, and firm-level controls. The model fit seems
reasonable: industry-level trends, industry dummies, and regional dummies account formuch of the explained variation. The coefficients on genealogy age and squared age arestatistically significant. Their point estimates imply that a firm in an ‘older’ genealogy
tends to be a corporation, in line with the theory that businesses incorporate as theymature and their organizational structures become more complex.
Column 2 includes the dummy for the PIT introduction, which is significant at the
1 percent level. Column 3 adds genealogy fixed effects, and shows that the coefficienton P ITt is lower but is still highly significant. This point estimate implies that theshare of incorporation increased by 5.5 percentage points in this sub-sample that excludes
joint-stock corporations. This translates to a 3.2 percentage-point increase in the wholesample.25 Interestingly, the coefficients on genealogy age and its square change signs,
reflecting the influence of ‘new comers.’ That is, conditioning on a genealogy, observations
with older genealogies ages are from the latter sample period, which likely include new
business operations.

3.2

Robustness checks

3.2.1

Full sample

The baseline estimation dropped joint-stock corporations to focus on the choice between
a sole proprietorship and a non-joint-stock corporation. To see if this estimation strategy
affects the result, we estimate a multinomial logit model on a sample that includes jointstock corporations, following Wooldridge (2010):0
P (yit = m|zit ) = exp(zitβm )/[1 +3X0
exp(zitβ h )],(2)h=2where m indicates three outcome categories: (i) sole proprietorships, (ii) other corporations, (iii) and joint-stock corporations, with sole proprietorships as the base category
in the estimation. The vector z includes P ITt and a set of control variables, including x
from (1) and industry-specific linear time trends. As before, we allow for heteroskedastic
errors.
24

We combine regions with small number of observations.
0.055 divided by the share of firms other than joint-stock corporations in the pre-tax-reform sample(0.585).
25

10

Columns 4-5 in Table 4 present the results. The coefficient on P ITt is significant at the
1 percent level for other corporations but not for joint-stock corporations. To interpret themagnitude, we compute the difference in predicted probabilities. The result indicates thatobservations from the post-reform period are 6.5 percentage points more likely to become‘other corporation’ than observations from the pre-reform period. This is slightly higher
than the unconditional differences in probabilities between 1886 and 1887. Therefore, theresult is robust to the exclusion of joint-stock corporations.
3.2.2

Genealogy panel

We consider a panel regression analysis to account for unobservable characteristics. We
first take each genealogy as a panel unit, and use industry as an alternative panel unit in a
separate analysis.26 To construct a genealogy-level panel data, we aggregate observations
over genealogies after dropping banks and government corporations. We retain genealogies
with 5 or more observations spanning 1887 to ensure each panel unit has sufficient time
length, and we keep observations with gaps.27
We consider counts of each type of organization per genealogy-year, rather than shares,
since the number of firms within a genealogy is typically small, making data on shares
lumpy. Table 5 shows the tabulation by organizational types. The range for sole proprietor
and other corporation is [0, 4], but with heavy concentration in [0, 1]. Count is therefore
an outcome more suitable in a regression analysis. Thus, following Wooldridge (2010), we
employ the fixed-effect Poisson regression to fit model with count data. We assume thatthe number of firms that takes a certain organizational type in a given genealogy at any
point in time, conditional on observables and an unobserved fixed-component, follows a
Poisson distribution:f (numtypekt |z kt , ck ) = exp[−ck exp(z 0kt β)][ck exp(z 0kt β)]numtypekt /numtypekt !,(3)

where f (.) is a probability density function; k indexes genealogy. The outcome variable, numtypekt , is the number of firms that take an organization type (sole proprietorship,
other corporation, or joint-stock corporation) in genealogy k at time t. The vector z kt
includes P ITt and a vector of control variables from (2), excluding regional and industry dummies. The term ck accounts for time-invariant unobservable characteristics ofgenealogy k.
Since the genealogies differ in size, which naturally affects the count of organizational
types, we therefore consider incorporation rates by including the number of firms as an
exposure variable with a unit coefficient. In estimation, we drop genealogies with all zero
outcomes for a given organizational type, so the sample size varies by outcome analyzed.28
We cluster the standard errors within panel by genealogies.
Columns 6-8 show estimates from the fixed-effect Poisson regression on the countof firm type using the genealogy panel data. The coefficient on P ITt is significant at
26

We are unable to take firm as a panel unit since direct lineages are often difficult to derive fromgenealogies in case of mergers.
27
To be clear, while we drop banks in computing the outcome variable, we keep genealogies which
include banks as member.
28
To control for industry output growth, each genealogy needs an industry classification. We counted
the frequency of industry classifications within each genealogy over the sample period, and assigned theindustry with the highest count. Given that industry counts are concentrated within genealogy, thisapproach should provide a reasonable approximation.

11

the 5 percent level for sole proprietorship. The magnitude indicates that the numberof sole proprietors fell by 6.8 percent per genealogy, or by 0.053 firms per genealogy.29
The coefficient on P ITt is significant at the 1 percent level for other corporations. Thismagnitude implies that the number of other corporations increased by 84.9 percent, orby 0.048 firms per genealogy. The coefficient on P ITt takes a negative sign for joint-stock
corporations, but is not statistically significant. While the magnitudes of these estimates
are harder to interpret, in qualitative terms, the results are robust to controlling fortime-invariant unobservable effects.
3.2.3

Industry panel

The standard approach in previous studies is to use a panel regression on corporate shares
over aggregate unit, such as states. To see if a common framework changes the result, weaggregate the sample over 12 industries and examine corporate shares by industry-year in a
fixed-effects regression model. The present study differs in using a subset of population.30
While industry aggregation reduces the sample size substantially, these estimates provide
a basis for comparison with results from the literature. We cluster standard errors within
the panel and weight observations by the number of firms in industries.
Columns 9-11 show the result. In Column 10, the coefficient on P ITt in the model forother corporations is positive and significant at the 1 percent level. The result indicatesthat the share of other corporations increased by 5.8 percentage points in the post-reformperiod. The coefficients on P ITt are not significant for sole proprietorships and joint-stock
corporations. Since the number of observations is much smaller (N=156), the results likely
reflect a lack of statistical power.
3.2.4

Dynamic consideration

So far, the empirical framework implicitly assumed that the choice of organizational forms
does not depend on firms’ choices in the past. However, the decision likely exhibits timedependence for obvious reasons: firms would retain their current forms unless faced with acompelling reason to do so.31 To obtain a sub-sample of firms with a continuous identity,
we restrict the sample to observations with a single unit in a genealogy at a given time,and compute a transition matrix from each type (sp, oc, and kk) across adjacent years.
The probabilities of remaining in the same type across years typically exceeded 98 percent
in this sub-sample, indicating a strong dependence.32
The industry panel readily extends to a dynamic analysis. In addition to including
a lagged dependent variable in the fixed-effects estimation, we use difference and system
GMM estimation to incorporate a dynamic dependence while allowing for fixed effects anddynamic panel bias. For both difference and system GMM, we treat the macroeconomic
control variables as predetermined but not strictly endogenous; collapse the instruments
29

The sample average for 1880-1886 (0.782) multiplied by 0.068.
Unfortunately, we do not have information to construct other measures of corporate activity, suchas employment or output.
31
Examining time dependence is not as easy as it might first appear, since, once again, the identity ofa firm is not easily tractable due to mergers.
32
The transition matrix also indicated that firms tend to “move up” from simpler organizational
forms. A duration model may be more appropriate in modeling such behavior given this “irreversible”
tendency, but the limited longitudinal information at firm level precludes us from implementing suchmodel. However, since the off-diagonal elements were much smaller compared to the diagonal elements,
the dynamic dependency seems the first-order importance in modeling.
30

12

to avoid overfitting with numerous instruments (Roodman, 2009); use the one-step estimation procedure. We once again weight observations by the number of firms in theindustries, and cluster standard errors by industries.
Table 6 presents the main estimates, and all three models produce nearly identicalcoefficients on P ITt . As is well documented, the dynamic panel bias affects the lagged
dependent variable more severely compared to covariates (Judson and Owen, 1999; Flannery and Hankins, 2013). The coefficients on the lagged dependent variable are significant
at the 1 percent level across specifications, and are larger under the GMM estimates,suggesting a high dynamic dependence with a possible dynamic panel bias under the
fixed effects estimator. The similarity of the PIT coefficients across the three estimators,
however, suggests that the fixed-effects model is sufficient in assessing robustness. Although the specification tests for the GMM estimators indicate that the instruments arevalid with no second-order autocorrelation, the p-value for the Hansen test is 1, which is
symptomatic of over-proliferation of instruments despite adopting a recommendation tocollapse instruments. Our preferred estimates are therefore those in Columns 1-3. The
coefficient on P ITt for the share of other corporations is 0.044 and is significant at the 1
percent level. Compared to the static model, this estimate is about 25 percent lower, but
is higher than that suggestted by the baseline estimation employing the firm-level data.
Overall, the dynamic issue does not seem to warrant further probing.

3.3

Alternative explanation

While we have explicitly controlled for economic factors in the analysis, absent crosssection variation, the identification could be confounded by other changes in the economy.
Particularly, we have noted that local governments started issuing decrees on incorporation around the time of the PIT introduction. If the creation of local rules increased
the benefits of incorporation, perhaps through a better status of corporations, then an
improved legal environment, rather than the tax motives, may better explain a rise inincorporation in 1887.
To address this concern, we focus on Osaka prefecture which issued a local guideline
for establishing a corporation in February 1886. Osaka was a commercial center during
the Edo period and was the second largest local economy in the country at the time.
If the local rule was responsible for the surge in incorporation, we should observe theincorporation rate in Osaka increase from 1886. Panel B in Figure 2 shows shares of firms
in Osaka Prefecture by organizational types. The dashed and solid vertical line indicates1886 and 1887 respectively. The overall pattern is similar to that from the country
aggregate (Panel A), and no trend break is evident in 1886. The local guideline would
have somewhat contributed to clarifying legal requirements for incorporation (Nakamura,2010), but is unlikely to explain the jump in incorporation rate in 1887.

4

Discussion

Economic historians named the period spanning the PIT introduction the ‘First Surgeof the Corporate Sector’ (1886-1889) in Japan. Our study draws on a new data source
and utilize the discrete change in tax law as a quasi-experiment to examine tax-motivatedincorporation in 19th century Japan. The evidence shows that the introduction of PIT
was an important factor behind the surge. Our estimates, while lower than these fromthe most recent study by Liu (2014), would likely underestimate the true impact at13

the population level given the sample of prominent firms. In addition, our data aretaken from an economy less developed than the U.S. in the early 20th century, so the tax
administration in the late 19th century Japan would have been much weaker, possibly
enabling firms to substitute avoidance with evasion.33 That said, our results confirm
findings in the existing literature that tax incentives affect small firms disproportionately.
Specifically, the estimates show that the tax incentives affected the margin between sole
proprietorship and ‘simpler’ corporations but not joint-stock corporations.
More generally, our study demonstrats the role of the CIT as a backstop to the PIT,
also emphasized in recent studies (de Mooij and Nicodme, 2008; Liu, 2014). The early
PIT collected 70 percent of projected revenue in the first year (Hayashi, 1965), but the
portion of this shortfall attributable to tax-motivated incorporation is hard to gauge
from data available from the period under investigation. Rather, it would be relevant toexamine further how PIT and CIT affect each other’s revenue performance, as considered
in de Mooij and Nicodme (2008). We left several opportunities for quasi-experimentswith later tax changes unexamined in the paper, primarily because the advantage ofgenealogical data becomes less clear with the availability of aggregate statistics since themid-1890s. However, qualitative evidence from the latter period suggests the importanceof tax motives: well-documented correspondences by managers of Mitsui zaibatsu reveal
tax planning efforts that included a survey trip to Europe (Nakamura, 2010) and recordsof discussions from the National Assembly show a conscious development of anti-avoidance
policies in the latter period (Takagi, 2007). We leave these questions for further study.

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16

Table 1: Early income tax in Japan
1887

Schedule

Type 1
Corporate income

Type 2
Bonds

2.50%

2%

1

1

bracket (yen) rate (%)
300
1
1,000
1.5
10,0002
20,0002.5
30,0003

Number of brackets

5

Exemption

300

Excluded income

1899
Type 3
Other income
bracket (yen) rate (%)
300
1
.
.
.
100,000
5.5
12300

Corporate income
Real estate income

Dividend income

Taxpayers

Japanese

Resident of Japan

Family income

Aggregation

Aggregation

Source: Takagi (2007)

Table 2: Summary statistics
Variables

mean

sd

min

max

N

Joint-stock corporation = 1
0.42 0.49
013,203
Sole proprietor = 1
0.50 0.50
013,203
Other corporation = 1
0.08 0.27
013,203
Stock index growth-0.02 0.17 -0.40 0.46
3,203Real IR index
0.36 0.14 0.26 0.75
3,203
GDP growth
0.04 0.08 -0.06 0.17
3,203
Industry growth
0.09 0.16 -0.13 3.00
3,203
Age (/100)
0.34 0.59 0.01 3.07
3,203
Note: Firm-year observations covering 1880-1892 constructed fromthe genealogies. Banks are excluded from the sample. See text for
further details.

17

Table 3: Changes in the share of organizational type by industries and tax regimes
Sole proprietor

Other corporations

Joint-stock corporations

Industry

Before

After

Total

ChangeBeforeAfter Total Change

Before

After

Total

Changeprimary
retailmetal
machinery
chem etc
ceramic
foodbev
textilewood etc
transportotherfinance

0.900
0.872
0.811
0.651
0.734
0.692
0.500
0.530
0.302
0.272
0.174
0.135

0.861
0.850
0.619
0.657
0.588
0.525
0.422
0.213
0.232
0.178
0.191
0.174

0.878
0.860
0.690
0.654
0.640
0.590
0.455
0.308
0.257
0.216
0.184
0.155

-0.039-0.022-0.1920.006-0.146-0.167-0.078-0.317-0.070-0.094
0.017
0.039

0.000
0.000
0.000
0.048
0.109
0.031
0.045
0.052
0.151
0.029
0.000
0.108

0.040
0.049
0.000
0.157
0.096
0.129
0.100
0.194
0.343
0.118
0.059
0.104

0.022
0.026
0.000
0.110
0.101
0.090
0.077
0.151
0.276
0.082
0.032
0.106

0.040
0.049
0.000
0.109
-0.013
0.098
0.055
0.142
0.192
0.089
0.059
-0.004

0.100
0.128
0.189
0.301
0.156
0.277
0.455
0.417
0.547
0.699
0.826
0.757

0.099
0.101
0.381
0.185
0.316
0.347
0.478
0.593
0.424
0.704
0.750
0.721

0.100
0.114
0.310
0.236
0.258
0.319
0.468
0.540
0.467
0.702
0.784
0.738

-0.001-0.027
0.192-0.116
0.160
0.070
0.023
0.176
-0.1230.005-0.076-0.036

Total

0.545

0.458

0.495

-0.087

0.039

0.112

0.081

0.073

0.415

0.43

0.424

0.015

18

Table 4: Regression analysis(1)
SampleEstimator
Dependent variable
PIT Introduction
GDP growth
Industry growth
Stock index growth19

IR index
Age/100
Age/1002
Time
Constant
Fixed effects
PIT marginal effects(Unit)
Observations
R-squaredc
Number of panel
LL
LL 0

oc

(2)
(3)
pooled (sp, oc)
LP
oc

oc

(4)
(5)
pooled (all)
MNL
oca

kka

0.104** 0.055**(0.032) (0.018)
0.020
0.011
-0.011(0.134) (0.134) (0.074)
0.028-0.000-0.013(0.047) (0.046) (0.031)-0.0360.028-0.001(0.051) (0.053) (0.030)-0.019-0.0310.030(0.087) (0.088) (0.054)-0.057* -0.058*
0.029(0.025) (0.025) (0.107)
0.024* 0.024* -0.143**(0.009) (0.009) (0.052)
0.020*
0.006-0.002(0.008) (0.010) (0.004)-0.385* -0.163 -0.357**(0.169) (0.191) (0.133)
NO
NO
YESb

1.200**
0.108(0.381)(0.214)0.294-0.012(1.145)(0.787)-0.0910.288(0.609)(0.339)0.532-0.066(0.734)(0.380)-1.471-0.810(1.166)(0.666)-3.153** -1.533**(0.552)(0.311)1.273** 0.664**(0.197)(0.129)0.086
0.074(0.103)(0.061)-6.461** -3.058*(2.378)(1.328)
NO

10.4
(%pt)
1,846
0.232

6.5
2.0
(%pt)
(%pt)
3,203
0.280

1,846
0.228

5.5
(%pt)
1,846
0.753

-2113
-2935

(6)

(7)
(8)
genealogy panel
FE Poisson

(9)

(10)
(11)
industry panel
FE

numsp

numoc

numkk

sharespshareoc

sharekk-0.068*(0.030)0.024(0.051)0.011(0.028)0.002(0.022)-0.001(0.001)0.849**(0.306)0.492*(0.242)-0.052(0.229)0.345+(0.206)-0.010(0.007)-0.027(0.039)0.034(0.075)0.021(0.063)-0.042(0.035)-0.002(0.001)-0.025(0.035)-0.029(0.041)-0.063**(0.015)0.031(0.021)0.001+(0.001)

0.058**(0.015)0.012(0.012)-0.002(0.010)0.010(0.011)0.000(0.000)-0.033(0.027)0.017(0.037)0.065**(0.015)-0.041(0.025)-0.001(0.001)-0.038+(0.022)0.060(0.111)

0.055(0.065)

YES

YES

YES

-0.026**(0.005)0.564**(0.094)YES

0.008*(0.003)0.015(0.057)
YES

0.018**(0.003)0.421**(0.073)
YES

-6.8
(%)
1,324
.
108
-1126

84.9
(%)
325
.
27
-188.4

-2.7
(%)
860
.
72
-750.5

-2.5
(%pt)
156
0.690
12

5.8
(%pt)
156
0.774
12

-3.3
(%pt)
156
0.575
12

Note: This table presents regression analysis on the base sample (Column 1-5) and panel data constructed from the sample (Column 6-11).
Column (1)-(3) presents OLS estimates on the indicator for other corporations in a sample that excludes joint-stock corporations. Column(4)-(5) presents a Multinomial Logit estimates (the base category is sp). Column (6)-(8) presents fixed-effects poisson estimates on the countof organizational types in a genealogy. Column (9)-(11) presents fixed-effects regression estimates on the share of organizational types in anTable 5: Frequency of type counts within genealogy-year

Count

Sole proprietor

Other corp.

Joint-stock corp.

0
1
2
3
4
5
6
7+

600
1,087
140
25
1
0
0
0

1,671
149
20
12
1
0
0
0

1,154
401
145
82
35
29
1
6

(32.4)(58.7)
(7.6)
(1.4)
(0.1)
(0.0)
(0.0)
(0.0)

(90.2)
(8.0)
(1.1)
(0.7)
(0.1)
(0.0)
(0.0)
(0.0)

Combined(62.3)(21.6)
(7.8)
(4.4)
(1.9)
(1.6)
(0.1)
(0.4)

0
1,360
212
125
71
54
12
19

Note: The sample is based on the panel of genealogies. Percent of column inparentheses.

Table 6: Dynamic panel regression using the industry panel
Estimator
Dep. var.
PIT Introduction
Lagged dep. var.

(1)
FE
sharesp(2)
FE
shareoc(3)
FE
sharekk(4)
DGMM
sharesp(5)
DGMM
shareoc(6)
DGMM
sharekk(7)
SGMM
sharesp(8)
SGMM
shareoc(9)
SGMM
sharekk-0.022(0.025)0.412*(0.141)

0.044**(0.010)0.462**(0.054)-0.024(0.022)0.378**(0.121)-0.023(0.025)0.455**(0.108)0.043**(0.009)0.547**(0.063)-0.023(0.021)0.452**(0.108)-0.022(0.026)0.455**(0.123)0.043**(0.010)0.518**(0.053)-0.023(0.022)
0.465**(0.092)

Observations
144
144
144
132
132
132
144
144
144
Number of panels
12
12
12
12
12
12
12
12
12
Sargan test (p-val.)
.
.
.
0.225
0.383
0.789
0.07670.315
0.751
Hansen test (p-val.)
.
.
.
1.000
1.000
1.000
1.000
1.000
1.000
AR(2) test (p-val.)
.
.
.
0.215
0.201
0.686
0.230
0.200
0.703
No. of instruments
.
.
.
45
45
45
59
59
59
Note: This table examines the robustness of results by including a lagged dependent variable in the industry
panel regression on the share of organizational type. Three estimators include fixed effects (FE), difference
GMM (DGMM), and system GMM (SGMM). For the GMM estimators, we treated the macroeconomic control variables as predetermined but not strictly endogenous, collapsed the instruments, and used the one-stepestimation procedure. Observations are weighted by the number of firms in the industries, and standard errors,
clustered at industry, are in parentheses. ** p < 0.01, ∗p < 0.05.

20

.8

Figure 1: Shares of firms by organizational types: All regions

Civil War

Russo War

0

.2

.4

.6

Sino War

1870

1880

1887 1890

joint stock corp.
sole proprietor

1900

1910

other corp.
estimation sample

Note: The sample of genealogical firms excluding banks. See text for more details. The Civil War,First Sino-Japanese War, and Russo-Japanese War is for 1877.2-9, 1894.8-1895.4, and 1904.2-1905.9
respectively.

21

Table A1: Variable list
Variable
Sole proprietor

Code
sp

Description
Indicator for observation i being asole proprietor

SourceAuthors’ computation based on
the genealogies

Joint-stock
corporations

kk

Indicator for observation i being a
joint-stock corporation

as above

Other
corporationsoc

Indicator for observation i being apartnership, limited partnership, or
limited liability corporation

as above

PIT
Introduction

pit

Indicator for observations with t at
or greater than 1887

as aboveIndustry growth

numgr

The growth rate of the number offirms in industry j.

as above

Ageage

The number of years since the foundation of the first firm in a genealogy until t.

as above

GDP growth

gdpgr

GDP growth rate, deflated by theprice level

Japan Statistical Association(1987),
Table
13–03)

Price level

priceindex Price level

Nakazawa(2001)

Stock index
growthstockgr

The growth rate of stock index.

as above

IR index

ririndex

Daily interest in 1/100 yen, deflated by the price level and indexed
to 1868

as above

22

Figure 2: Shares of firms by organizational types during the sample period
B. Osaka

0

0

.2

.2

.4

.4

.6

.6

.8

A. All regions

1880

1885
year
joint stock corp.

1890

1880

other corp.

1885
year
joint stock corp.

sole proprietor

sole proprietor

23

1890
other corp.