Warlords, Civil Wars, and Industrial Development
in Early Twentieth-Century China
Cong Liu∗
Very Preliminary. Please do not cite or circulate without permission
December, 2016
Abstract
This paper examines how political fragmentation affects industrial development. China was
a politically unified nation before 1912, but gradually divided by political chaos from 1912 to
1916. In 1916, the death of President Yuan finally led to political fragmentation. The originally
unified territory were de facto controlled by different warlords, who competed with each other
for larger territories. Using a newly constructed dataset, I conduct a difference-in-differences
analysis to examine the impact of this shock on industrial development, measured by the number
of newly established Chinese industrial firms. I find that political fragmentation was associated
with divergent growth paths in different regions. Counties ruled by big warlords experienced
substantially more establishments of industrial firms than the ones ruled by small warlords.
Narrative evidence suggests that worries about potential political riots might have played a
role. Facing high possibility of local riots, firms believed that big warlords were more likely
to provide a safe commercial environment. In addition, the overall number of firms increased
after political fragmentation, suggesting that a competing political environment might have
facilitated industrial development.
∗
School of Economics, Shanghai University of Finance and Economics. Email: [email protected]. I
thank Cihan Artunç, Shiyu Bo, Price Fishback, Yu Hao, Ashley Langer, Nan Li, Carol Shiue, John Wallis, Mo Xiao,
Se Yan, and workshop participants at Peking University, South China Normal University and Jinan IESR for useful
comments.
1
1
Introduction
Many developing countries are struggling with political riots. According to the Political Stability
and Absence of Violence/Terrorism indicator from the World Bank, more than 90 countries today
have weak political stability and likely to have political-motivated violence (Kaufmann, Kraay and
Mastruzzi, 2008). One consequence of civil wars or domestic instability is to divide a unified nation
into several political groups, i.e., from political centralization to political fragmentation. This
transition in political structure may lead to dramatic changes in economic performance.
This paper uses the experience of China from 1905 to 1927 to examine the impact of political
fragmentation on economic development. During this period, China was de jure united as one
country, yet after 1916, it was de facto controlled by different warlords. Warlords fought with each
other for larger territories. Narrative evidence suggests the transition from political unification
to fragmentation caused different paths of industrial development in different regions. Provinces
controlled by big warlords had faster growth in industrial development, since firms believed that
the investment would be safer these provinces (Du, 1991).
To quantitatively test this argument, I construct a new county-level dataset including newly
documented information about warlords and their fights. In this period, about 60% of the country
was occupied by three big cliques, including most of the northern and middle provinces, while the
southern provinces were controlled by a couple of small warlords. Within the 1687 counties in
my sample, nearly 200 of them experienced a battle. I use the information of newly established
Chinese industrial firms collected by Du (1991) as the outcome variable. This data is by far the
most comprehensive dataset about the industrial sector in early twentieth-century China in terms
of its time and span. This data was collected from multiple official reports, recording the entry
of domestic industrial firms at county level, including their entry year, industrial group, initial
capital, and founders from 1840 to 1927. Since most of these firms were founded by individual
Chinese merchants, their location choices had also considered local economic conditions. To control
for other local economic conditions, I also digitize other information that could have potentially
affected firms’ entry decisions, such as population in 1911, access to trade, and the location of
foreign settlements.
2
I perform a difference-in-differences analysis and find that areas controlled by big warlords
experienced substantially more increase in the entry of new domestic industrial firms. The effect is
about four more firms at provincial level, which is equal to half of the standard deviation and the
average number of firms entered in each province.
Since big warlords might have controlled more prosperous regions, the results may be contaminated by the omitted variables. I show that omitted variables cannot explain my results. First,
the parallel trends before the warlords era and were similar across regions. Second, using rural
labor wages and land values in sample counties from 1904 to 1933, I find that the trend in rural
economy was similar across different warlords, suggesting that areas controlled by big warlords did
not experience faster economic growth overall than areas controlled by small warlords.
I then explore the mechanisms through which big warlords affected industrial development.
Among competitive hypothesis, it is most likely that in the Warlord Era, different warlords provided
differentiated safety environment. firms chose regions controlled by big warlords, expecting a more
peaceful and stable commercial environment. However, they also responded to historical records
of warfare by avoiding regions that experienced more frequent civil wars over time. This finding
consistent as previous theories on that better protection or expectation on better protection of
property rights would increase investment (Besley and Ghatak, 2010).
Despite the benefits and growing industrial sector, further examination shows that the impact
was mostly restricted in urban areas. I use county-level survey on rural labor wages and rural land
values to examine the impact on the rural economy. The results show that economic growth in
rural areas occupied by different warlords had similar trends, and civil wars were likely to harm
rural economy.
Most historical studies criticized the warlord era for interrupting China’s economic development,
for warlords increased regional chaos, taxes and investment on war goods, while under-invested on
public goods (e.g., Sheridan, 1983; Ch’i, 1976). However, studies on economic growth in early
twentieth-century China also suggest that the industrial sector was booming and commercial activities were prosperous. According to Rawski (1989), the GDP per capita increased by 1.8-2.0% from
1914 to 1936, with the industrial sector grew by 8%. Warlords were also eager to maintain connections with local commercial elites in consideration of funding. Rawski thus draws the attention that
the negative impact of warlords on economic development during this period was enlarged. This
3
paper quantitatively examines this issue, finding that areas ruled by big warlords did experience
faster growth in the industrial sector, while the impact on rural areas were unclear. Given the
majority of the population lived in rural areas, the positive effect on total economic growth growth
seemed small and limited.
This paper also relates to the literature about size and economic development. Size helps to
form the economic structure (Perkins and Syrquin, 1989) and determines the boundary of market
(Alesina et al., 2005). The history emphasizes the importance of size in determining long-term economic development (Rosenthal and Wong, 2011, Ko et al., forthcoming). This paper uses a unique
setting with political fragmentation and differentiated territory size affects economic performance.
2
Background
China experienced periodic political fragmentation in its history. The period 1911 to 1927 is
another typical period of such political fragmentation. For most of the years, the central government
existed in name only and warlords were the actual rulers of local affairs. Composed of Northern
(“Beiyang”) Warlords, Southern Warlords, and other small warlords, each of the warlords controlled
one or several provinces. They collected taxes, and invested for military or local construction. These
political parties or local rulers fought to control more regions to extract resources. The long-term
goal was to take over the central government in Beijing and later unite the nation (Ch’i, 1976).The
Warlord Era ended when the Kuomitang (KMT) unified the nation and took over the central
government in 1928. Political fragmentation persisted until the outbreak of WWII, but warlords’
power became much weaker.
2.1
1
Origins of Warlords and the Warlord Era
The Warlord Era was originated from local military at the end of the Qing dynasty, when the
central government lost control over local affairs. The Qing government used to be very strong
and kept more than 70% tax income. Since the nineteenth century, however, corruption gradually
eroded state’s funds about public goods and military maintenance. In the 1850s, when the Taiping
1
Warlords in this period in fact include Northern (“Beiyang”) Warlords, Southern Warlords, and the revolutionaries
from different parties. Since warlords and the revolutionaries had different political structure and ideology, in this
study, I only consider the period when warlords were the major players and occupied different regions in China.
4
Rebellion started, the original troops (the “Eight Bans” and the “Green Standard Army”) was
too weak to fight against the rebels. The central government had to seek for help from local
government by handing its political and financial power to provincial officials by allowing them to
keep tax revenue and build their own military.
Meanwhile, the government started to to train modern armies. Since 1840, the constant defeat
by foreign armies pushed the Qing government to train soldiers and generals under the western
system. In 1885, the then most powerful minister Li Hongzhang, who had been making efforts
to introduce western knowledge and institutions to China, founded the Tianjin Military School
(Tianjin Wubei Xuetang).2 This military school followed the German system to train military
officers. The majority of the later generals in Northern Warlords were educated there. Many other
warlords or military officials were trained in other similar schools.
The corps themselves, the “New Armies”, were the result of the Qing government’s last efforts
to modernize the military. Built in the 1894, the New Armies were trained under the German
system. Soldiers were strictly selected based on their age, height, and education levels. In 1907,
the Qing government set a plan to train thirty-six zhens of the “New Armies”. Zhen was a unit
with each of it consisted of two hunchenglv (brigate). Each hunchenglv had 4038 soldiers and
each zhen had 12,521 soldiers. In 1911, fourteen zhens and eighteenth hunchenglv (brigade) were
finished. Yuan Shikai, as the most powerful minister in the Qing after 1901, controlled six zhens
of armies with the best equipment in and around the capital in North China. These troops were
the starting points of the later Northern Warlords. Other troops distributed all over China and
became military power for other warlords later.
In addition to their origins, the attitude to the Republican Revolution divided warlords as well.
The years 1894 to 1911 also witnessed the rise of revolutionaries. More than 200 political parties
were formed and hundreds of uprisings started. With both both military officers and soldiers
received modern education facilitated their adoption of the new revolution ideas. Most of the
southern Warlords were supporters of the revolutionaries while the North Warlords were more
hesitated.
2
Li Hongzhang was the Vicery of Zhili (the capital province) and Minister of Beiyang (foreign issues in northern
China) in 1885.
5
In Oct 10, 1911, a group of soldiers in “New Armies” in Wuchang, Hubei province, started the
Wuchang uprising, which became the prelude of the later Xinhai Revolution that finally overthrew
the monarchy. Many southern military officers supported the rebels during the revolution. One
by one, southern provinces claimed to detach themselves from the central government and the
revolution finally went nationwide. When the Qing military failed to suppress the uprisings, the
Qing government asked Yuan Shikai, the leader of Northern New Armies (Now the Beiyang Armies),
for help. Controlling the well-equipped New Armies in the north, Yuan’s attitude was a key
determinant in the Revolution. Mr.Yuan used his power to gain large benefits. He promised to
help the revolutionaries to build the republic under the conditions that he became the president.
With the revolutionaries’ consensus, he then persuaded the Qing family to abdicate. In this way,
Yuan took over the control of the ROC and established Beijing, where he was fully in control, as his
capital. However, as previously discussed, political division originated from the form of the “New
Armies” already hided under the unification: Mr.Yuan controlled most of the northern provinces
while the southern provinces were still in hands of warlords or the revolutionaries. Such situation
of political division barely changed until the outbreak of the Second Sino-Japanese War in 1937.
This political disagreement led to several domestic warfare from 1912 to 1916, but all of them
lasted for a short time. In 1916, Yuan stepped further and proclaimed himself to be Emperor of
China. With national opposition, Yuan recalled his plan three months later and died due to uremia.
His death not only left the country with a power vacuum, but also split up the Northern Warlords
group. Soon after Yuan’s death, Yuan’s generals were divided into two major groups: Anhui clique
and Zhili clique. Together with the Fengtian clique led by Zhang Zuolin, who supported Yuan
but relatively independent from Yuan and trained his own army, these three groups consisted of
the major Beiyang Warlords around 1919. Each leader ruled different regions but was not strong
enough to fully take Yuan’s place.
2.2
Differences among Warlords
The Northern warlords, or the Beiyang Warlords, were Yuan Shikai’s original supporters and
generals. They were split into several groups after Yuan’s death. Among these groups, the Anhui
clique, led by Duan Qirui, was the most powerful one. Other major warlords include the Zhili clique
(led by Cao Kun, later by Wu Peifu) and the Fengtian clique (led by Zhang Zuolin). Guominjun
6
(led by Lu Jianzhang first, later by Feng Yuxiang) and Yan Xishan also became important players
around the 1920s. Their ultimate goal was to control the whole country, but it proved to be difficult
with so many competitors. Even the short-term plan of occupying Beijing, the capital, was not
easy. The number of cabinets revealed this pattern. When a new warlord controlled Beijing, the
old cabinet was dismissed and a new cabinet took over. From 1916 to 1928, there were 24 cabinets
in total, with the average length of each is less than half a year. Table 1 listed the areas occupied
and active years of all major cliques. As the table shows, the Northern Warlords controlled most of
the northern part of China as well as the eastern middle provinces, such as Jiangsu and Zhejiang.
However, except for the Fengtian Clique, the ruling areas of the Northern Warlords varied over
time. In an extreme case, the Anhui clique was the the most powerful clique in 1916, yet lost all of
its territories after being defeated in the Zhili-Anhui war in 1920.
The Southern Warlords were located in Guangdong, Guangxi, Yunnan, and Sichuan. While
the Northern Warlords were close supporters of Yuan, the southern ones were usually neutral or in
favor of to revolutionaries.3 The first generation of the Southern Warlords were provincial governors
and generals at the end of Qing. Their positions mostly remained during the Xinhai Revolution.
Different from the Northern Warlords, the Southern Warlords had very close connections to the
revolutionaries. As Table 2 shows, except for Long Jiguang who fought against the revolutionaries,
all other warlords supported revolutionaries temporarily or permanently. Tables 1 and 2 list the
basic information of Northern and Southern warlords. The Anhui, Zhili, and Fengtian cliques had
greater ruling areas than other warlords and thus had more complicated political structure than
other warlords. This is the key difference I emphasize in my analysis.
Other small warlords include warlords in Henan, Guizhou, and other provinces. These warlords
were military leaders, occupying part of one province. Their troops usually originated from the less
trained or educated bandits. Difference in ideology was a major excuse of fights among Warlords
from 1911 to 1916. After 1916, fights focused on expanding territories and acquiring resources.
Merchants responded to local riots by flooding into areas that were less likely to experience
fights. As a result, firms were likely to locate in foreign settlements, where fights by Chinese
3
The south and north warlords were not strictly geographic locations. North includes three provinces in Northwestern China, Zhili, Henan, Shandong, Jiangsu, Zhejiang, Anhui, part of Shanxi, part of Hubei, Part of Jiangxi,
and part of Fujian. South includes Yunnan, Guizhou, Guangxi. Shanxi is an isolated province in the north, while
Guangdong in the south has several groups of political powers (Chen, 1980)
7
troops were less likely (Yan 1955; Du, 1991; Yuan, 2007). As a result, I need to control for foreign
settlements in my regression. In general, most narrative studies emphasize the general negative
impact of civil wars on economic development, yet how warlords’ industrial policies differed from
each other were not clear yet.4
3
Data
To quantitatively examine the impact of different warlords on industrial development, I need
information on warlords’ ruling areas over time. Since warlords started civil wars, it is also necessary
to document the location and timing of their fights. For the outcome variable, even provincial-level
industrial production is not available for every years. I finally use the number of newly established
industrial firms as a proxy for industrial development. In addition, the examined period witnessed
rapid flux in foreign capital and increase in foreign trade. Controlling for these shocks are necessary
since they are likely to affect domestic industrial firms as well.
Warlords were first on stage around the 1900s, yet they obeyed the central government and
remained as provincial agents for most of the times until the death of Yuan Shikai. Most warlords
stopped taking orders from the central government since Yuan’s death in 1916. In addition, the
first boom of private-owned industrial firms in China was due to the “New Policies” in 1905. Given
this background, I consider the period 1905 to 1927 in the main analysis.
Considering these issues and data available, I finally combine following information in the
baseline regression: areas ruled by warlords, the location and time of major battles in each civil
war, the location of treaty ports and foreign settlements, and the number of newly established
industrial firms.
The main independent variable is areas ruled by warlords. The ruling area is constructed using
the information Historical Atlas for Teaching Purpose of Chinese Revolutionary History (Yang,
1992). The current measure of ruling areas is a dummy variable that is equal to one if a province
was ruled by a big warlord. I also separate big warlords by considering their cliques. Figure 1 depicts
the areas ruled by warlords in 1916. Among all warlords, Anhui, Zhili, and Fengtian Warlords each
controlled more than two provinces. I define them as the big warlords. Other warlords were the
4
I plan to collect this information as supportive narrative evidence.
8
small warlords. Most provinces experienced changes of rulers in the examined period, but in current
draft, I only use the distribution of warlords in the initial year of the Warlord Era, because big
warlords might have taken over more prosperous provinces, which would contaminate my estimation
results.
To document the civil wars, I digitize information mostly from descriptions in the Military History in the Republic of China (Jiang, 2009). This book describes the time, location, parties involved
and leaders in the army battles for major civil wars from 1911 to 1949. With the descriptions, I
am able to trace the location and time of major battles over time. To address concerns that some
battles may not be recorded in this description, I then compare this information with records from
other sources, namely the Historical Atlas in China’s Modern History (Zhang, 1984) and the Historical Atlas of China’s New Democratic Revolutions (Guo, 1993). In my current analysis, I only
consider battles from the Xinhai Revolution in 1911 to the Northern Expedition in 1927. There
are about 20 recorded civil wars, or regional fights in my current sample.
I then manually match county-level battle locations with county information from the China
Historical Geographic Information System (CHGIS) and Historical Atlas of China (Tan, 1987).
Among the 1699 counties recorded in the China proper areas in CHGIS, 424 counties were once
involved in civil war. I then group the samples based on the year a war took place and create the
war variable dummy variable that measures whether a civil war took place in a given county at
year t. In other words, the interpretation of the impact of war on trade is “if a war took place in a
county at a given year, what would be the impact on the local economy?”
To measure industrial development, I use a list of newly established Chinese industrial firms,
complied by Du (1991). This data source has by far the most complete coverage about the industrial sector before 1927. It collects name, established time, industry type, location, initial capital
invested, and founders of more than 4000 Chinese industrial firms collected from multiple official
reports. Since this data only focuses on Chinese firms, it simplifies the story by teasing out foreign
capital or foreign firms. Figure 2 depicts the trend of firms over time. The introduction of the
“New Policies” in 1905 led to the first boom of domestic industrial firms, which tripped the total
number of industrial firms established. After the warlord era, the number of new industrial firms
reached another peak.
9
To provide information about the impact of foreign settlements and trade, I also document
the number of foreign settlements, ports, and total trade at province level. The number of foreign
settlements was collected by Yan (1955) from official reports. The location and ports and total trade
come from the well-documented international trade from the China Maritime Customs. Managed
under the British bureaucratic system, the annual and decennial reports of China Maritime Customs
deliberately recorded both national and port-level information about trade flows, tariffs, and traded
commodities. In this preliminary analysis, I use port-level information about trade flows from the
annual reports of China Maritime Customs from 1911 to 1930 as the outcome variable.
Table 3 reports the summary statistics. The average number of firm established in each province
is 5.271, or 0.004 per capita. The average frequency of civil wars in each province is about half
a time per year, suggesting that military conflicts among warlords were in fact at regional level
and at small frequency. Each province on average had 0.51 ports and experienced 15 million
Haikwan Taels of international trade. The areas foreign settlements is about 0.027 million shi mu
per province. Table 4 reports summary statistics after separating small and big warlords. Big
warlords had substantially more firms, larger areas of foreign settlements, more trade flows, slight
more population, and less warfare. This baseline difference indicates that I need to control for
these factors in my analyses. After separating the results before and after the treatment year in
Tables 5 and 6, the divergent growth paths of the industrial firms appear. The provincial mean
of industrial firms in areas ruled by small warlords dropped from 2.097 to 1.522, while the mean
in areas ruled by big warlord increased from 7.23 to 8.5. Meanwhile, the value of trade flows kept
increasing in both two regions. The results from simple statistics suggest that the two regions had
differentiated trajectory for industrial firms that cannot be explained by closer connections with
the world market.
Finally, to examine the spillover effect of industrial development, I use data on rural labor wages
and rural land values from John Buck’s survey. These data come from a nationwide survey by John
Buck, who was a professor in the Department of Agricultural Economics at Nanking University
from the 1920s to the 1940s. He started a field survey project to examine multiple aspects of
Chinese society in the 1920s, asking his students to conduct surveys near their hometowns during
their vacations. By 1933, he and his students had already completed a nationwide dataset involving
16,786 farms and 38,256 farm families in 22 provinces, which covered most of the populated area.
10
The survey includes many variables describing climate, population, agriculture, health, farm labor
and other variables related to farm production (Buck, 1937). The original survey was at the
household level, but only the county level statistics were published and are still available.
The land value indices and labor wage indices were collected from recalled information.5 In
the published data the value in each county was normalized relative to the value in 1926. In the
regression analysis, I take logs and use county-level fixed-effects to take account of the impact of
normalization in each county.6
4
Baseline Results
The empirical analysis aims to quantitatively examine the effect of political decentralization
on industrial development, and establish the mechanism through which size affected industrial
outcomes.
The baseline regression estimates the effect of different warlords on the establishment of industrial firms. At county i, province j, and time t, I estimate the following regression equation
Eijt = α + βBigW arlords1916,j × P ost1916t + γConf lictijt + σi + θt + (4.1)
where BigW arlords1916,j is a dummy variable that denotes whether area i at year t was rulled
by big warlords. It equals to one if the area was controlled by the Fengtian Warlords, the Zhili
Warlords, and the Anhui Warlords.P ost1916t is a dummy variable that equals to one if year is
greater or equal to 1916. Conf lictijt is the frequency of civil wars in each county. The coefficients
σij and θt are county-level fixed effects and time dummies. The coefficient β denotes the effect of
big warlords on industrial development. If big warlords had differentiated impacts on industrial
development, I should observe β is different from zero.
I first check the parallel trend before the treatment took place, that is, Yuan’s death in 1916.
As Figure 3 shows, the two trends of industrial firms were relatively similar before Yuan Shikai was
on stage in 1912. After Yuan was on stage, there was a sign of divergence. This trend continued
after Yuan’s death in 1916. The first divergence in 1912 may reflect the fact that political division
5
For two counties (Gaolan in Gansu and Tonglu in Zhejiang), there are two observations for each year.
One limitation of the data is that there are some missing values in their report. Since all the missing values are
missed continuously, it minimizes the impact of this problem.
6
11
between the Northern and the Southern warlords already started at that time. In this case, if I use
1916 as the year when political fragmentation started, my estimation may be a lower bound of the
actual effect.
The OLS regression also raises concerns about omitted variables, that is, areas occupied by
big warlords might have been originally prosperous and thus experienced greater increase in the
establishment of foreign firms anyways. To address this concern, I interaction year dummies with
indicator for big warlords and control for year and provincial fixed effects.
Table 7 reports the baseline results.
Column (1) reports the results of the difference-in-
differences analysis. Column (2) and Column (3) consider the location of conflicts. The results
show that, if a county was ruled by big warlords, it would have had about 0.068 more new firms
established per county than areas by small warlords, suggesting that firms preferred areas ruled by
big warlords. In addition, merchants consider the possibility of fights. In Column (3), the coefficient of conflict is -0.185 and statistically significant, and the coefficient of conflict in the previous
period is still negative but not statistically different from zero, showing that the effect was fading
away as the war took place for longer time.
Narrative evidence shows that merchants tended to pick places that were less likely to experience fights in the future. In fact, when the potential of fights increased, firms would have issued
an announcement, expressing their concerns. Although lacking enough quantitative evidence, historians find that firms might have been deliberately located in foreign settlements to minimize the
threads from warfare (Yan 1955; Du, 1991; Yuan, 2007).
I then replace the P ostt dummy with a set of time dummies and run the following regression
equation
Eijt = α +
X
βt BigW arlords1916,j yeart + σi + θt + (4.2)
where BigW arlords1916,j as the meaning a before, but I replace the P ostt with a set of year
dummies. This equation allows me to examine the pre-trend before political fragmentation took
place and to trace how the effect on the entry of industrial firms differed over time.
12
Figure 4 reports the results. After controlling for time dummies and provincial-level fixed effects,
the years before 1916 witnessed similar behavior of the entry of industrial firms in areas ruled by
different warlords. Divergence shows up since the start of the Warlord Era.
5
Discussion
I have shown that big warlords were associated with better performance in the industrial sector.
However, this result may be contaminated by other factors that might also have affected industrial
development. For example, previous literature suggests that foreign settlements, initial provincial
population, and access to trade played an important role in promoting industrial development (Yan,
1955; Rawski, 1989). The baseline summary statistics also suggest different economic conditions
across these two regions. In addition, as the economic literature noticed, bigger territory often
means bigger market size (Alesina et al. 2005). Due to data limitations, I cannot quantify the
impact of these factors at the county level; instead, I rerun the regression at the provincial level to
control for these factors.
I also examine the differentiated impact of big warlords and across sectors. First, I consider the
differentiated impact of big warlords by separating them into Zhili, Fengtian, and Anhui groups.
This practice compares firms entry decisions under different big warlords and addresses potential
concerns on outliars. Second, I examine the impact on rural land values and labor wages for
potential effect on the rural economy.
5.1
Control for Other Socioeconomic Characteristics
Table 8 reports the regression results at provincial level. Columns (1) to (3) present the results
of the difference-in-difference analysis using the number of firms as the outcome variable. Columns
(4) to (6) report the effect on the number of per capita firms. Column (1) and Column (4) redo the
county-level regression using provincial-level data. Similar as previous results, the 5.095 increase
in the number of firms (or 0.00281 increase in per capita number of firms) is about the mean of
firms before the treatment started. As expected, adding more control variables largely decrease the
coefficient. In Columns (3) and (6) where I control for population and foreign settlements in 1910
13
time year dummies, the coefficients shrink to 3.523 and 0.00151, respectively, but still statistically
significant, suggesting that other factors explain about 40% of the difference across warlords.
5.2
Market Size
Big warlords and small warlord are different in dimensions other than the ability to protect
businesses. Although I have controlled for the essential baseline difference in population difference
and the access to foreign trade, there is some other factors that I cannot measure. Here I discuss
one factor in detail: the market size.
As the trade literature noticed, market size plays a key role economic development (Alesina et
al., 2005). If political fragmentation turned to economic fragmentation, for example, higher tolls
for trade across borders, it was possible that areas ruled by big warlords also had larger markets
that led to faster growing industrial sector.
The ideal data to address this concern is information on tolls or domestic tariffs, but this
data unavailable for now. The basic trend in the number of firms suggest that this is unlikely to
explain my results. As Figure 2 shows, the number of industrial firms was growing much faster
during political fragmentation than political centralization. If warlords increased tolls and divided
markets, I should observe the number of firms decreased instead of increased.
5.3
Differentiated Impact among Big Warlords
I also examine the differentiated effects of big warlords on industrial firms. In this way, I can
observe firms’ entry decisions under different big warlords and rule out the concern that the main
results may be driven by industrial development within one single big warlord’s territory. Table
9 presents the regression results. Columns (1) and (2) show the results on total number of firms.
Columns (3) and (4) show the results on the number of firms per capita. Columns (1) and (3) have
only the warlord dummies and difference-in-differences dummy variables. In these two regressions,
the impact of big warlords on the number of firms was similar for the Anhui and Fengtian warlords,
both around 3 to 4 firms per year. Yet since the Fengtian warlords had lower population in their
provinces, the impact on per capita firms was much higher. The cofficient of the Zhili warlords
had much greater magnitude but only marginally statistically significant. After controlling for
other variables in Columns (2) and (4), the Fengtian dummy dropped due to data limitations.
14
The magnitude for Zhili warlords became much smaller and comparable to the effect of Fengtian
warlords, suggesting that other variables played a role in industrial development in Zhili warlord’s
territory. Overall, these results show that the impact of big warlords were comparable.
5.4
Impact on Rural Areas
Finally, I examine the impact on rural areas. If changes in the urban economy had spillover
effect to rural areas or areas ruled by big warlords experienced economic growth in general, I should
observe positive impacts of big warlords on rural land values and labor wages as well. Table 10
reports the regression results using rural input prices. Column (1) and Column (3) report the
impact on rural land values. Column (3) and Column (4) present the effect on rural labor wages.
Column (1) and Column (2) control for county fixed effects and national shocks, and Column (2)
and Column (4) control for war shocks in previous year. In all regressions, whether controlled by
big warlords or not did not affect rural input prices, suggesting that big warlords’ ruling areas did
not experience overall economic development. In addition, civil wars tended to negatively affect
labor wages, probably due to its destructive effect on the rural economy.
6
Summary of Current Results
This paper examines the effect of political fragmentation on industrial development. Using
China’s experience in the early twentieth-century, I show that political fragmentation led to divergent growth paths. Regions ruled by big warlords experienced substantial more entry in industrial
firms than the ones ruled by small warlords. This result is likely due to the fact that firm owners
flooded into safe regions to avoid potential warfare.
In addition, this setting also allows me to compare China’s experience under political centralization versus political fragmentation. The economic history literature emphasized the importance
of competition in Europe’s technological progress and industrialization (Hoffman, 2015). The short
period of political fragmentation supported this view. Areas ruled by big warlords experienced
faster economic growth, due to competitions among warlords.
15
In the future, I plan to exploit variations in the change of warlords’ territories from 1916 to
1927 and compare the experience of same regions under different warlords’ control. I also plan to
collect data on taxes to quantitatively examine the possibility of market fragmentation.
16
References
[1] Alberto Alesina, Enrico Spolaore, and Romain Wacziarg. Trade, growth and the size of countries. Handbook of economic growth, 1:1499–1542, 2005.
[2] J.L. Buck and Institute of Pacific Relations. Land Utilization in China: A Study of 16,786
Farms in 168 Localities, and 38,256 Farm Families in Twenty-two Provinces in China, 19291933. International research series. University of Chicago Press, 1937.
[3] Zhirang Chen. Junshen zhengquan: jindai zhongguo de junfa shiqi. Shenghuo dushu xinzhi
sanlian shudian, 1980.
[4] Hsi-sheng Ch’i. Warlord politics in China, 1916-1928. Stanford Univ Press, 1976.
[5] China Maritime Customs. Returns of trade and trade reports, 1909-1930.
[6] Xuncheng Du. Minzu zibenzhuyi yu jiuzhongguo zhengfu (Domestic Capitalism and Old Chinese Government), 1840-1937. The Shanghai Academy of Social Sciences Press, 1991.
[7] Maitreesh Ghatak and Tim Besley. Property rights and economic development. Handbook of
Development Economics, 5:389–430, 2010.
[8] Philip T Hoffman. Why did Europe conquer the world? Princeton University Press, 2015.
[9] Daniel Kaufmann, Aart Kraay, and Massimo Mastruzzi. Governance matters viii: aggregate
and individual governance indicators, 1996-2008. World bank policy research working paper,
2009.
[10] Jiang kefu. Minguo junshi shi (Military history of the Republic of China). Chongqing chubanshe, 2009.
[11] Chiu Yu Ko, Mark Koyama, and Tuan-Hwee Sng. Unified China and Divided Europe. Forthcoming.
[12] Dwight H Perkins, Moshe Syrquin, et al. Large countries: the influence of size. Handbook of
development economics, 2(2):1691–1753, 1989.
17
[13] Thomas G Rawski. Economic growth in prewar China, volume 245. University of California
Press Berkeley, 1989.
[14] Jean-Laurent Rosenthal and Roy Bin Wong. Before and beyond divergence. Harvard University
Press, 2011.
[15] James E Sheridan. The warlord era: Politics and militarism under the peking government,
1916–28. The Cambridge History of China, 12:1912–1949, 1983.
[16] Qixiang Tan. Zhongguo lishi ditu ji (di ba ce): qing shiqi (historical atlas of china: Volume 8,
the qing dynasty). Zhongguo ditu chubanshe, 1987.
[17] Yuan Weipeng. Juji yu kuosan (Concentration and Diffusion: Locations of China’s Early
Modern Industries). Shanghai University of Finance and Economics Press, 1955.
[18] Mu Yang. Zhongguo gemingshi jiaoxue ditaji (Historical Atlas for Teaching Purpose of Chinese
Revolutionary History). The Henan Education Press, 1992.
[19] Yan Zhongping. Zhongguo jindai jingjishi tongji ziliao xuanji (Selected Statistics in China’s
Modern Economic History). Kexue chubanshe, 1955.
18
Clique
Anhui
Zhili
Fengtian
Shanxi
Northwestern
Table 1: Major Beiyang Warlords since 1916
Leaders
Areas Occupied in 1912
Active Years
Duan Qirui
Zhejiang
Duan: to 1926
Shandong
Fujian
Henan
Shaanxi
Hunan
Shanghai
Feng Guozhang
Zhili
Feng: died in 1919
Cao Kun
Jiangxi
Cao: 1919 to 1924
Wu Peifu
Jiangsu
Wu: 1922 to 1926
Hubei
Suiyuan
Zhang Zuolin
Northeastern Provinces
Zhang Z: to 1928
Zhang Xueliang
Zhang X: 1928 to 1936
Yan Xishan
Shanxi
Yan: to 1949
Feng Yuxiang
Northwestern Provinces Feng: 1916 (separated from Zhili) to 1925
since 1921
1926 to 1946
Source: Lai (2005), History of Beiyang Warlords. Jiang (2009), Military History of the Republic of
China, vol. 1.
Warlords
Lu Rongting
The New Guangxi Warlords
Long Jiguang
Revolutionaries
Chen Jiongming
Tang Jiyao
Table 2: Southern Warlords
Provinces
Year in position Relationship with the revolutionaries
Guangxi
1913-1921
First support, then against
1923-1924; 1924Revolutionaries
Guangdong
1913-1918
Long: against
Most period
1920-1923
Chen: First support, then against
Yunnan
1913-1927
Mostly support
Source: Jiang (2009), Military History of the Republic of China, vol. 1.
Table 3: Summary Statistics (Provincial Level)
Variable
Mean
Std. Dev.
Firms
5.271
9.561
Firms (per capita)
0.004
0.009
Civil War
0.554
2.086
# Port
1.333
1.754
Areas osf Foreign Settlements in 1911 2872.681 12413.556
Trade Flows (million Haikwan Taels)
44.256
102.633
Population in 1910 (10,000 people)
2002.4
1262.833
19
N
513
415
323
726
726
726
462
Table 4: Summary Statistics (Provincial Level, Divided
Small Warlords
Variable
Mean
Std. Dev.
Firm
2.097
2.798
Firm (per capita)
0.001
0.001
Civil War
0.618
2.588
# Ports
0.882
1.492
Areas of Foreign Settlements in 1911
15.529
62.201
Trade Flows (million Haikwan Taels)
19.369
52.768
Population in 1910 (10,000 people)
1807.344
1267.154
by Warlords, 1905-1927)
Big Warlords
N
Mean
Std. Dev.
196
7.233
11.54
166
0.006
0.011
136
0.508
1.634
374
1.813
1.881
374 5908.404 17330.494
374
70.698
132.049
1241.973
198 2148.692
N
317
249
187
352
352
352
264
Table 5: Summary Statistics (Provincial Level, Divided
Small Warlords
Variable
Mean
Std. Dev.
Firm
2.88
3.156
Firm (per capita)
0.001
0.001
Civil War
0.083
0.347
# Ports
0.882
1.494
Areas of Foreign Settlements in 1911
15.529
62.284
Trade Flows (million Haikwan Taels)
14.6
39.519
Population in 1910 (10,000 people)
1807.344
1270.382
by Warlords, 1905-1916)
Big Warlords
N
Mean
Std. Dev.
83
5.652
6.916
74
0.005
0.01
48
0.242
0.805
187
1.813
1.883
187 5908.404 17355.234
187
46.795
64.144
99 2148.692
1244.341
N
141
117
66
176
176
176
132
Table 6: Summary Statistics (Procinvial Level, Divided
Small Warlords
Variable
Mean
Std. Dev.
Firm
1.522
2.357
Firm (per capita)
0.001
0.001
Civil War
0.909
3.175
# Ports
0.882
1.494
Areas of Foreign Settlements in 1911
15.529
62.284
Trade Flows (million Haikwan Taels)
24.138
63.059
Population in 1910 (10,000 people)
1807.344
1270.382
by Warlords, 1916-1927)
Big Warlords
N
Mean
Std. Dev.
113
8.5
14.092
92
0.007
0.011
88
0.653
1.931
187
1.813
1.883
187 5908.404 17355.234
187
94.600
172.366
99 2148.692
1244.341
N
176
132
121
176
176
176
132
20
Table 7: The Effects of Warlords on Industrial Firms (County Level Regressions)
(1)
(2)
(3)
VARIABLES
# Firm
# Firm
# Firm
P ost1916 × BigW arlord1916
0.0668***
(0.0274)
0.0658**
(0.0268)
-0.294
(0.187)
0.0574***
(0.00731)
0.0574***
(0.00733)
0.0677***
(0.0254)
-0.185*
(0.0988)
-0.138
(0.124)
0.0574***
(0.00791)
27,846
0.003
1,638
Y
Y
27,846
0.005
1,638
Y
Y
26,208
0.005
1,638
Y
Y
Conflict
L.Conflict
Constant
Observations
R-squared
Number of counties
County FE
Year FE
*** p<0.01, ** p<0.05, * p<0.1. Robust standard errors are
in parentheses. The dependent variable is the number of new
industrial firms each year. BigWarlord1916 is a dummy variable
that equals to one if a region was ruled by Anhui, Zhili, and
Fengtian cliques in 1916.
21
22
496
0.163
31
Y
Y
5.095**
(1.926)
5.700***
(0.806)
282
0.364
18
Y
Y
Y
Y
4.267***
(1.068)
-590.9
(400.2)
Y
282
0.778
18
Y
Y
Y
3.523***
(0.939)
2.222
(4.193)
399
0.091
21
Y
Y
0.00281***
(0.000929)
0.00760**
(0.00356)
399
0.110
21
Y
Y
Y
Y
0.00208***
(0.000716)
0.145
(0.214)
Y
282
0.629
18
Y
Y
Y
0.00151***
(0.000434)
0.00122
(0.00151)
*** p<0.01, ** p<0.05, * p<0.1. Robust standard errors are in parentheses. The dependent variable in
Column (1) to (3) is the number of new industrial firms each year. The independent variable in Column (4)
to (6) is the number of industrial firms per year. BigWarlord1916 is a dummy variable that equals to one if a
region was ruled by Anhui, Zhili, and Fengtian cliques in 1916. Control A are control variables that change
over time, including the lagged number of wars took place in a given province and he total value of trade
aggregated to provincial level in million Haikwan taels. Control B are time-invariant variables, including #
Port is the number of ports in each province, foreign settlement in each province, and population in 1910.
Observations
R-squared
Number of prov id
Prov FE
Year FE
Control A
Control B×year
Control B×i.year
Constant
P ost1916 × BigW arlord1916
Table 8: The Effects of Warlords on Industrial Firms (Province Level Regressions)
(1)
(2)
(3)
(4)
(5)
(6)
VARIABLES
# Firms # Firms # Firms Avg # Firms Avg # Firms Avg # Firms
Table 9: The Effects of Warlords on Industrial Firms (Province Level Regressions, Separated by
Warlords)
(1)
(2)
(3)
(4)
VARIABLES
# Firms # Firms Avg # Firms Avg # Firms
P ost1916
Anhui × P ost
Zhili × P ost
F engtian × P ost
Constant
Observations
R-squared
Number of prov
Prov FE
Year FE
Control A
Control B×i.year
-1.015***
(0.354)
3.787**
(1.506)
9.689
(6.243)
3.360***
(0.781)
4.065***
(0.611)
-2.367
(3.376)
3.954***
(1.212)
2.576**
(1.049)
513
0.140
31
Y
Y
282
0.780
18
Y
Y
Y
Y
1.877
(4.587)
-0.000439***
(0.000151)
0.00157**
(0.000620)
0.00335*
(0.00188)
0.00700*
(0.00341)
0.00323***
(0.000287)
-0.00162
(0.00128)
0.00157**
(0.000552)
0.00139***
(0.000456)
415
0.048
21
Y
Y
282
0.629
18
Y
Y
Y
Y
0.00118
(0.00162)
*** p<0.01, ** p<0.05, * p<0.1. Robust standard errors are in parentheses. The dependent variable in Column (1) to (3) is the number of
new industrial firms each year. The independent variable in Column
(4) to (6) is the number of industrial firms per year. Anhui, Zhili, and
Fengtian are dummy variables that equal to one if a region was ruled
by Anhui, Zhili, and Fengtian cliques in 1916. Control A are control
variables that change over time, including the lagged number of wars
took place in a given province and he total value of trade aggregated to
provincial level in million Haikwan taels. Control B are time-invariant
variables, including # Port is the number of ports in each province,
foreign settlement in each province, and population in 1910.
23
Table 10: Test: The Impact of Size on Rural Input Prices
(1)
(2)
(3)
(4)
VARIABLES
log(land) log(land) log(wage) log(wage)
BigW arlord1916
0.0478
(0.0748)
4.012***
(0.0865)
0.0492
(0.0751)
0.140
(0.106)
4.011***
(0.0869)
4.149***
(0.0713)
-0.0321
(0.0566)
-0.175**
(0.0875)
4.150***
(0.0712)
1,030
0.660
Y
Y
1,030
0.661
Y
Y
993
0.666
Y
Y
993
0.668
Y
Y
L.Civil War
Constant
Observations
R-squared
County FE
Year FE
-0.0301
(0.0567)
*** p<0.01, ** p<0.05, * p<0.1. Robust standard errors are
in parentheses. The dependent variable is rural land values
or labor wages in natural log form. BigWarlord is a dummy
variable that equals to one if a region was ruled by Anhui, Zhili,
and Fengtian cliques. L.Civil War is lagged number of wars took
place in a given province.
24
Figure 1: Warlords in 1916
Figure 2: Number of Industrial Firms
25
Figure 3: Warlords and Firms
Figure 4: Warlords and Firms
26