GGDC RESEARCH MEMORANDUM 147
Living standards in China between 1840 and 1912:
A new estimate of Gross Domestic Product per
capita
Ye Ma, Herman de Jong and Tianshu Chu
July 2014
university of
groningen
groningen growth and
development centre
Living standards in China between 1840 and 1912: a new
estimate of Gross Domestic Product per capita1
Ye Ma, Herman de Jong & Tianshu Chu2
Groningen Growth and Development Centre /
Research Institute of Economics and Management
Abstract
This paper investigates China’s economic development between 1840 and 1912. We look at
living standards and general economic trends in the late Qing dynasty and discuss the
reliability of existing estimations of per capita GDP. Secondly, we introduce a new estimate of
long-term growth. Our estimation provides for the first time a continuous time series of both
nominal and real GDP per capita for the period 1840-1912. We see this as a starting point for
further research on 19th century developments in levels of economic welfare and the
performance of the Chinese economy.
JEL classification codes: E23 E30 N15 N9
1
We are grateful to Harry Wu, Jan Luiten van Zanden and Bas van Leeuwen for giving us advice and suggestions about data
sources. In preparing the first draft, we have received valuable comments from many colleagues, including Pinghan Liang,
Dayong Zhang, and participants of the seminars at RIEM, Southwestern University of Finance and Economics, Chengdu, in
May 2012; participants of the Asian Historical Economics Society Conference at the Hitotsubashi University, Tokyo, 13-15
September 2012; and participants of the European Historical Economics Society Conference at the London School of
Economics, 6-7 September 2013. All errors are the responsibility of the authors.
2
Ye Ma, Groningen Growth and Development Centre, Faculty of Economics and Business, University of Groningen,
y.ma@rug.nl; Herman de Jong, Groningen Growth and Development Centre, Faculty of Economics and Business, University
of Groningen, h.j.de.jong@rug.nl; Tianshu Chu, Research Institute of Economics and Management, Southwestern University
of Finance and Economics, chutianshu@ymail.com.
1
1. Introduction
In this paper we present a new estimate of historical GDP and GDP per capita for the Chinese
economy in the 19th and early 20th century, i.e. in the late Qing Empire (1840-1912). During
this period, also known as the “years of troubles”, the Chinese population faced a combination
of wars, natural disasters, and economic reforms. Many scholars see this era as a break point in
China’s long-run economic development. On the one hand, it can be seen as a period of
economic distress, which stands in contrast with the relatively prosperous 18th century. On the
other hand, it has been viewed as a period in which new social and economic conditions began
to replace old ones (Brandt, Ma, and Rawski 2012, p.27). China’s economy lost its position as
the world’s largest economy, but became involved in international trade, started to open up its
domestic market, and imported new technology from the rest of the world (Maddison, 2007).
Recent studies of China’s development in the late 19th century support the long-lasting
influence of this era on China’s modern economy. Harry Wu concludes that China’s post-1949
state-led industrialization can be traced back by a development path that began in the late 19th
century (H. Wu, 2011). Keller et al. also attribute China’s present trade performance to its
experience in the 19th century, rather than exclusively to the 1978 reforms (Keller, Li, and
Shiue, 2012). Brandt et al. relate the resilience of the Chinese modern economy to its
performance in the 19th century, and argue that even in the mid-19th century, the economy was
so resilient that “it had the inbuilt capacity not only to withstand certain shocks but also to
restore stability in the wake of potentially destabilizing disasters” (Brandt et al., 2012, p.49).
Although recent studies have found some implicit linkages between the economy of the 19th
century and the present one, more evidence is still needed to firmly substantiate these claims.
Understanding China’s economic history has broader implications. As the world’s largest
economy in the past and the second largest today, China always had the power to affect the rest
of the world, but it also has been influenced by global developments. To obtain a complete
understanding of world economic development since industrialization, China’s economic
situation in the late 19th century is important. However, our knowledge about 19th century
China is still rather limited. We need e.g. more solid information on cyclical and long-term
movements in national income. Moreover, previous GDP estimations show contradictory
outcomes, which prevent us from getting a good understanding of the performance of the total
economy.
This paper intends to solve the main puzzles around the historical GDP estimates for the late
19th century. For this purpose, we reconstruct total production of the Chinese economy and
provide a new estimation of GDP, resulting in the first consistent time series for the period
1840-1912. The reconstruction necessarily will involve simplification and approximation, but
we see it as an important step in the study of the 19th century Chinese economy. The structure of
the paper is as follows: in section 2 we analyze several studies on historical GDP estimations
for the 19th century; in section 3 we elaborate on our own GDP estimation; section 4
summarizes the main findings and confronts them with earlier studies. The appendixes provide
a detailed explanation of our estimation procedures.
2
2. An overview of existing estimates of Chinese GDP per capita
This section summarizes the results of previous studies on Chinese historical GDP in the late
19th and early 20th century.3 The studies have been classified by us into two groups according to
the estimation methods used and we refer to them as macro and sector studies. We can also sort
these studies according to the estimation results: some studies provide an estimation for a
benchmark year (cross-section), others provide estimations for various years. This is shown in
Table 1 (a and b, respectively). In paragraph 2.2 we introduce two issues that need to be solved
before any in-depth investigation into the Chinese economy can take place. These questions are
related to the level and the growth rate of average national income respectively. Although it is
not easy to completely answer the two questions in one paper, we will try to solve some issues
and give suggestions for further research.
2.1 Macro and sector studies
Previous studies on China’s historical GDP provide us with benchmarks of income levels for
specific years and also time-series estimations of per capita GDP. Table 1 covers all the recent
historical GDP estimates for the period 1000-1933.
[Table 1]
We confine ourselves here to what we believe are the three most important studies. Firstly,
Chang (1962), cited in many studies, is the first GDP estimation for late 19th century China.
This study concludes that per capita GDP in the 1880s was about 7.4 silver tael in current
prices, i.e. prices of the 1880s. The estimation applies a sectoral value-added approach, which
roughly follows the familiar three-sector classification in national accounting: agriculture,
industry, and services. The GDP estimates for the total economy are obtained by adding up the
output value of all three sectors. Sector information is retrieved from historical documents and
previous estimations. For instance, Chang uses the amount of cultivated land recorded in
official documents to reconstruct agricultural output.4 We refer to this type of estimations as
sector studies.
The second study is by Angus Maddison, generating a historical GDP dataset and providing a
long-term trend of Chinese economic development. For the period 1840-1912 five level
estimates were produced for the years 1850, 1870, 1890, 1900, and 1913. The average level of
3
Names of authors working in North America and Europe and publishing in English are presented in Western style (e.g. Debin
Ma). Names of Chinese authors based in Asia and writing primarily in Asian languages appear in the East Asian fashion, with
the surname first and capitalized for clarity (e.g. WU Chengming). The purpose of the classification is to distinguish between
English and Chinese texts, so that the reader knows where we rely on translations.
4
The definition of food crops is related to the principal food components in the Chinese diet (see Appendix B).
3
the GDP per capita estimates is 554 international Geary-Khamis dollars in 1990 prices (GK
dollars of 1990). Maddison calculated real growth rates for the period 1820-1995 by linking
previous GDP estimations, such as the GDP level for 1890 from Chang (1962), and a 1933
estimate from Ou (1947) and Liu and Yeh (1965). From the Chinese GDP level of 1990 (in
international GK dollars), historical GDP per capita levels for the 19th century were generated
by a backward projection of the estimated rates of real growth. Maddison’s procedure thus
relies on existing GDP estimations for the total economy. We refer to this type of estimations as
macro studies. The macro and the sector approaches are intertwined in practice. For instance,
the macro approach can be based on GDP estimates from sector studies. Table 1a includes the
benchmark studies that Maddison employed in his estimation.
The third study that we mention here is a recent reconstruction by Broadberry, Guan and Li
(2013). Based on very detailed archival work, it is the first to provide a time series of per capita
GDP estimates covering three dynasties and more than 600 years of Chinese history. The
estimated average level of per capita GDP in the period 1600-1850, the early Qing Empire, was
715 international dollars in 1990 prices. In domestic currency the per capita average was 14.1
silver tael in 1840 prices (see Table 1). In their study, nominal GDP and real GDP in 1840
prices are estimated by using the sector approach. With an additional level estimate for the year
1840 in international dollars and a reconstruction of rates of real GDP growth, the authors are
also able to derive a time series of GDP estimates in international dollars for the early Qing
Empire. This outcomes of this sector study are more or less in line with Maddison’s estimation
for the per capita GDP level of 1850, which is about 600 GK dollars.
There are several GDP estimates for the period before 1850, 1850-1912, and the 1880s, but
expressed in different monetary units. Generally, the monetary unit “international dollars” is
comparable with the “GK dollars” used by Maddison. Both reflect a purchasing-power-parity
(PPP) adjusted value of official currencies. These internationally comparable monetary units
intend to measure and compare purchasing power of currencies across countries, by
considering not only market exchange rates but also domestic prices in different countries. We
will use the term “GK dollars” to emphasize the use of the Geary-Khamis PPP convertor
between the Chinese yuan and the dollar. The assumption is that there is no difference between
GK dollars and the international dollars as applied by Broadberry et al.
To compare the different estimates for the nineteenth century, the GDP values in terms of silver
tael need to be converted into GK dollars. Based on the official exchange rates between Qing
China and the U.S. and on the movement of the annual consumer price index for the U.S. from
1885 to 1990, the 1880s per capita GDP of China can be obtained, being 125.2 US dollars in
1990 prices (1990USD). By using the term “1990USD”, we emphasize that this value is
obtained through current market (silver) exchange rates. Chang also concludes that the level of
per capita GDP during the 1880s is about 32 Chinese yuan in 1930s prices. Following the
method in Fukao, Ma, and Yuan (2007), Chang’s 1880 estimate can be converted resulting in a
level of 337 international dollars. This is based on a PPP convertor. We find that the
exchange-rate-adjusted approach leads to serious underestimation; the resulted estimate here is
lower than one half of the bare-bones level of income (300 dollars). Still, the PPP-adjusted
4
estimate for the 1880s is over 35 percent lower than Maddison’s 1870 and 1890 estimate, 530
and 540 GK dollars respectively. It is hard to believe that the Qing economy decreased by over
35 percent and rebounded back to its initial level in the same decade.
Our conclusion is that a simple connection between the three estimations does not result in a
plausible understanding of the income level for late Qing China. Value conversion from silver
tael to international dollars clearly does not solve all the methodological differences between
the various estimations. The next section will discuss more extensively the problem of
inconsistency between previous estimations.
2.2 Why do we need a new estimate?
Table 2 compares per capita GDP estimates for the late 19th and early 20th century. It reveals the
discrepancies between the macro and the sector approach and the differences among sector
studies. These discrepancies make it difficult to get a good idea of the general living standards
in the late 19th and early 20th century. It is also difficult to generate plausible time-series
estimations that can be cross checked for certain years. We summarize these discrepancies into
two major points, leading to two questions that this paper intends to solve.
[Table 2]
The first point is related to the different outcomes of the level of per capita GDP before the
1890s. As mentioned above, the average per capita GDP estimate is around 550 GK dollars in
Maddison’s estimation, whereas the average is one third lower in the sector studies except
Broadberry et al. (2013). We need to check whether the approach of value conversion that we
apply to the 1880 estimates is a cause for the discrepancy in levels of GDP per capita between
the various macro and sector studies (See Table 1a). As said, this approach has been employed
by Fukao et al. (2007) to convert a GDP estimate in 1930 Chinese yuan to international dollars.
They derive a level estimate of 619 international dollars for 1934-6, which is 9 percent higher
than Maddison’s estimate for the 1930s of 570 GK dollars. If we apply a similar procedure to
translate Debin Ma’s level estimate for the 1910s (52.4 yuan), we arrive at 549.5 international
dollars. This is only 0.5 percent lower than Maddison’s estimate of 552 GK dollars (See Table
2). The approach of value conversion may explain some of the discrepancies, but it is not the
main reason behind the problem of inconsistency in the estimates for the period before the
1890s.
Differences can be found not only between macro and sector studies but also between some of
the sector studies. Aside from Broadberry et al. (2013), LIU T. (2009) also reports estimates in
international dollars and gives another benchmark estimate for 1840 with a value of 318
international dollars. Although following the same procedures of value conversion, the two
estimations differ by a margin of 50 percent (See Table 1a and 2). We find that the margin is
5
caused by variations in nominal GDP/cap levels as well as by the different PPP-adjusted
exchange rates between silver taels and international dollars: 10.8 tael and 29.4 international
dollars/tael in LIU T. (2009); 12.95 tael and 46 international dollars/tael in Broadberry et al.
(2013). Therefore, in our data reconstruction two steps need to be included: a reconstruction of
nominal GDP (per capita) and an estimation of the PPP convertor.
The second question concerns the long-term development of per capita GDP between 1840 and
1912. Maddison’s estimation shows hardly any significant changes in GDP per capita in this
period. The economy seems to be stable at a level of per capita GDP of 500-600 GK dollars.
However, we get a different view of the economy when the estimates of the various sector
studies are connected (See Table 2, column 2). Per capita GDP started from a lower level of 318
dollars during the 1840s, but increased by 20-50 percent in the following decades, and finally
reached a level of 500-600 international dollars in the 1930s. However, on this basis alone we
cannot get a more detailed picture of the economy. For instance, the data in Table 2 cannot give
us information about the general economic trend during the first Opium War and the Taiping
Rebellion (in the 1840s-1850s). This is due to the problem of inconsistency between macro and
sector studies. A re-estimation of nominal and real GDP would be the first step to reveal more
detailed fluctuations in the economy and to arrive at a consistent understanding of the growth
pattern of the Qing economy in the period 1840-1912.
2.3 The Great Divergence and the economy of the late Qing Empire
Solving these discrepancies in China’s historical GDP will also help to understand the long-run
comparative development of the Western and Asian economies. In this section, we will touch
upon the discussion of the Great Divergence between Europe and China. The important issues
around the widening income gap between both regions are clearly related to the questions
mentioned above.
Maddison’s long-run estimations reveal that China’s per capita GDP was higher than that of
Europe before the early 15th century. After that the Chinese economy went into a long period of
stagnation, while some European economies began to take off, setting the stage for the
economic divergence between Europe and Asia. In Maddison’s research, the timing of the
divergence dates back to roughly the 16th century (Maddison, 2007). Pomeranz (2000)
estimates the timing of the great divergence much later, starting in the 19th century.
Recent studies show a potentially different picture of the long-run economic development in
pre-modern China. Broadberry et al. (2013) conclude in their estimation that around the 14th
century the Chinese economy had already fallen behind some European countries, such as
Italy, and the gap had become significantly large in the 18th century. So it largely pushes back
the starting period of the economic divergence. More importantly, it interprets the great
divergence as a process lasting for several centuries. But we have to remember that there are
shifts in the relative economic position of countries (Broadberry et al., 2013, p. 36, Table 6).
Although it was lower than the levels in Italy and the Netherlands, Chinese GDP per capita in
6
the 16th century is still comparable to that of England. After that, the Chinese economy
experienced a relative decline lasting for at least three centuries until the early 19th century,
being the end point of the estimation by Broadberry et al. Note, however, that in their
estimation the most dramatic relative economic decline actually happened in the 18th century,
which is generally seen as a rather favourable period for China, with a prosperous economy,
stable society, and an increasing population.
In the 19th century general circumstances were much worse in China. The era has been labelled
as the “Turbulent Century” in China’s historiography. This refers especially to the period after
1840. Table 3 compares the incidence of wars and natural disasters between the early and late
Qing Empire (1640-1840 and 1840-1912, respectively). The general societal circumstances
probably worsened significantly after 1840.
[Table 3]
During the second half of the Qing Empire, there were many wars and natural disasters.
Around 100 million people lost their lives during this period because of domestic turmoil,
floods, as well as famines. The most serious population loss probably occurred in the 1850s,
largely caused by the Taiping Rebellion from 1851 to 1864. Large parts of the wealthy southern
area of Qing China had been devastated and approximately 20-30 million people died of the
war and the famines and plagues that went with it. At the same time, the Nien Rebellion
(1851-1868) burst out in northern China coinciding with a massive flood of the Yellow River in
1851. The large decrease in silver reserves of the central government indicates that the Qing
state had lost a large part of its control power (see Table 3, line C.). Its capacity to support extra
expenditures, such as excess military spending and relief funds, had been weakened
considerably.
But there were also political and economic reforms, which may have improved the standard of
living of the survivors. From the 1860s, forced by a deterioration of tax income, the Qing state
officially permitted the settlement of Han Chinese in Manchuria (Maddison, 2007, p.36).5 In
this period, the area under cultivation in China actually increased. After the First and the
Second Opium war (1839-1842 and 1856-1860, respectively), the country was forced to open
several new ports to western trade and residence. One outcome of the forced exposure to
international trade was specialization in agricultural production, especially for some cash
crops. After the period of wars Qing China tried to incorporate technologies from the more
advanced European economies and an early industrialization may have started at that time.
Probably the Chinese economy recovered gradually from the wars under the so-called Tongzhi
restoration during 1861-1875. The Qing economy started to export cotton goods, soy beans,
ore, and timber only from the 1890s.
5
This part of northeastern China was always seen as the original place for the royal blood of the Qing Empire and was a
restricted place for common Han Chinese.
7
However, in the historical records we find no indication that points to a significant economic
improvement in the late 19th century. Brandt et al. (2012) speak of a paradox. They observe
economic reforms in this period, which should have benefited the economy. Any significant
and sustained economic growth, however, only took place a century later after the 1978
reforms. They characterize this with some understatement as the “delay of growth”.
Was there a tendency of decline and divergence of the Qing economy persisting in the 19th
century? Or can we trace signs of catch-up during this period? Was the level of output
sustainable, i.e. sufficient to be able to support the population with basic energy needs? These
questions justify a reassessment of the Chinese economy for this period.
3. A new estimation of historical GDP
In this section a reconstruction of Chinese GDP per capita is presented based on new
estimations of value added in the three major sectors of the economy. Details are provided in
Appendix B. Secondly, cross checks per sector will be offered to see whether these new
estimations are plausible. Finally, we discuss economic developments in late Qing China on the
basis of the new sector estimates.
3.1 The agricultural sector
Our reconstruction tries to cover China’s output of the major agricultural products during
1840-1912. As a typical agrarian economy, the country concentrated on crop production, such
as grains and textile fibers, rather than livestock products (Maddison, 2007, p.32). In order to
facilitate taxation, there are lots of official documents and records on crops. Two categories and
two types of crops are distinguished here. The two categories concern so-called basic-food and
non-food crops.6 The most important basic-food crop is rice, while cotton is an example of
non-food agricultural production. The type of crop discerns between the degrees of intensity of
land-use. Basic-food crops are mainly land-intensive, but fruits and vegetables are not.
Because we use different methods to calculate the value of crop production in different
categories and types, a summary of these crops and their categories is given in Appendix B,
Table B.1. In total, we have four groups of agricultural products and activities including cattle
farming.7 Adding up the four items results in an annual figure of total value added in the
agricultural sector.
The focus here is mainly on basic-food crop production because it is the most relevant to
6
Non-food crops are oil seeds, vegetables, and flowers. Here, we realize that soy beans and of course vegetables can also be
consumed as food, but we classify it as a non-food crop. First, in general Chinese do not consume soy beans as their principal
food, compared with rice and wheat; second, we follow the previous studies, where it has been calculated as a non-food crop,
for instance, XU and WU (2005, p.1098).
7
There are other ways of classification. The group of food crops in our classification is very similar to the category “cereals” in
Maddison’s research (Maddison, 2007, p.118). Perkins’ estimation uses “grain output” which includes the cereal group,
potatoes, and other tubers (Perkins, 1969, p.16-17). In Table B.1 we follow the same procedure and summarize the food crops
also as “grains”.
8
people’s living standards in China (Perkins, 1969, p.396). The estimation of crop production is
usually constrained by the unreliability of the information on cultivated area, yields, and
imports of new food crops (maize, Irish and sweet potatoes), especially for the 19th century
(Perkins, 1969). In our calculation we will deal with these issues accordingly.
3.1.1 The amount of land under cultivation
How much of the cultivated land area was used for crop production in the late 19th century? The
range of existing estimations of the total land area that was available for cultivation varies
between 0.8 billion and 2 billion mou, as is shown in Table 4 (1 mou = 666.5 square metres).
We believe that the most plausible level is ca. 1.2 billion mou. From the first land survey
organized by the People’s Republic of China (PRC) we know that the total land area available
for cultivation was around 1.6 billion mou in the 1950s. Another reliable survey which was
organized by the Republic of China shows that the level was around 1.4 billion mou in the
1930s. During the 1910s the level was around 1.2 billion mou (Perkins, 1969). See Appendix
B, Figure B.1.
[Table 4]
Based on the general level, a time series of cultivated land has been constructed. Figure B.1
shows our new estimation for cultivated land during 1840-1915. In this calculation, we rely on
three data sources: two benchmark estimates from recent historical studies and one time series
of cultivated land data from historical records. The two estimates are 1.15 billion mou in 1840
and 1.26 billion mou in 1914 (SHI, 1989; ZHANG Y., 1991). Both authors made amendments
on the official records from Qing China and the Republic of China respectively. To build a time
series, we also need reliable trends to link the two data points.
As is shown in the datasets compiled by YAN Zhongping, there was no increase in the
cultivated area in the main territory of the Qing Empire, except Manchuria, Xinjiang, and Tibet
(YAN Zhongping or Yen Chung-ping, 1955). Taking into account the immigration into
Manchuria from the middle part of China after the 1860s, we expect a mild increase in the total
area under cultivation. WU Hui provides a time series of the cultivated area from 1840-1915 in
the form of five-year averages, with special attention to Manchuria (see WU H., 1985, p.198,
although no detailed information on the data source are mentioned in this book). The general
level of this time series is higher than the two level estimates mentioned before, which we think
are more reliable. Therefore we use this third data source to provide estimations for the trend
only, and link it to the two data points for 1840 and 1912. The method and the calculation
procedure are explained in Appendix B.
Another issue here is the intensity of land-use during one year, e.g. in case of multiple
cropping, being the practice of growing two (or more) crops during a single growing season. To
9
estimate the actual land input involved in food crop production, it will be necessary to find out
how many times seeds were sown in one year, to calculate the multiple cropping ratio.8 The
ratio is neglected in many studies, but we add it to our estimation. The best solution is to find
the ratio for each food crop for each region. Here we rely on two levels mentioned in the
literature, 1.24 and 1.4 respectively (WU H., 1985, p.180; Maddison, 2007, p.36). We use the
average of 1.32 as an average for all food crops and for the country as a whole.
3.1.2 Average levels of yields
Next we turn to the estimation of yields per unit area of food crops. Official records about
yields per unit area began only in the 1930s. For the earlier period there is information in
regional documents, but they are too scattered to facilitate a good estimation for the whole
country. Two major data sources have been used for this: the first one is a study that covers a
period from the 1700s to the 1930s by LIU R. (1987); the second one is the official agricultural
survey for the 1930s, which is extensively discussed by YAN (1955). Appendix B gives the
ranges of the yields for different crops during the 1700s through the 1930s (See Table B.4).
In general, most studies assume that for the different crops the average yield in the 1930s is a
plausible estimate for the yield in the late 19th century. Before directly applying the estimates to
our calculation, we need to justify this by comparing the underlying circumstances between the
two periods, i.e. the late half of the 19th century and the 1930s. Both periods were characterized
by poor harvests because of the detrimental effects of wars and natural disasters. Setting the
result of a big harvest year at 100 percent and a normal harvest at 75, the level of output per unit
area was 50-60 during the 1840-1894 period, around 50 during 1894-1920, and 64 during
1927-1937 (LIU Y., 2001, p.25; LIU K., 2001, p.103). Although a complete comparison should
include details such as rainfall and temperature, we think that the impact of societal disorder
was much more significant. Looking at these estimates, is can be concluded that the yields
between the two periods were roughly similar; therefore we apply the yields of the 1930s to
estimate the yields for the late 19th century.
We assume that the yields were constant over time, except for rice, wheat, and corn. The
underlying assumption is that agricultural technology in the late 19th century was fixed. There
probably were some technological advances in the agricultural sector. However, considering
the negative societal and natural conditions displayed in Table 3, it is still safe to assume that
there was no broad technical progress. Thus, the only potential improvement on this estimation
would be an inclusion of weather and climate change. The unit yields of rice, wheat, and corn
are backwardly projected from their unit yields in the 1930s, using the annual harvest ratios
(CHEN, 1996, p. 419). Estimations of historical weather conditions were applied for the years
for which we found no harvest ratios in the official reports. After taking into account the
weather conditions, Figure B.2 shows relatively stable unit yields in the period concerned.
Probably the single most important contribution to agricultural production in the Qing Empire
is the introduction of new basic-food crops. To fight the problem of famine, the Qing governors
8
Multiple cropping ratio = Sown area in one year / Total cultivated area, from Maddison (2007), p.114, Table A.10.
10
encouraged the cultivation of sweet potatoes and maize. Specific adjustments to allow for these
two new crops were made (see details in Appendix B).
3.1.3 Cross checks of agricultural output
Based on these assumptions we calculated the annual output of food crops and levels per capita
during 1840-1912. On average, the per capita food output was 345 kilograms per year, with a
range between 305 and 366 kilograms. Figure 1a displays the annual trends of per capita food
output in the period concerned. The upper and lower limits were estimated by using the
maximum and minimum values of cultivated area and yields (see Appendix B, Figure B.1 and
Table B.4). Our results show that on average, the upper limit was 443 kilograms, while the
lower was 204 kilograms. Figure 1a shows an upward trend until 1870, after which a decline
set in. Presumably the economy gradually recovered from the First and Second Opium wars
(1851-1864) and then began to decline even before the Sino-Japanese war (1894-1895).
[Figure 1]
How can we verify whether this new estimation is plausible? Three cross checks of our
estimation of basic-food crop production will be given. First, our estimation of yields can be
compared with yields in other studies. In the present estimation, the annual output per unit area
was calculated at 114 kilograms in the late Qing Empire (annual output divided by the
cultivated area in mou). In previous studies, we find 128 kilograms in the Ming Empire and
183.5 kilograms in the Qing Empire (GUAN and Li, 2010, p.6; LIU R., 1987, p.109). In related
studies, the per unit area output in the second half of the Qing Empire was around 120-150
kilograms (Perkins, 1969; WU H., 1985; GUO, 1994, 1995).9 Because our upper limit is a level
of 120 kilograms, the present results might underestimate the total level of output.
Second, the estimated output level can be confronted with the results of previous studies. As
mentioned above, the average per capita output of food crops in the present estimation was 345
kilograms during 1840-1912. Deducting 40 percent of the total output for seeds, feed grains,
reserves, and alcohol production, the monthly per capita production was ca. 17.25 kilograms.
In Perkins (1969, p.398) the general annual level in the Qing Empire was around 250-375
kilograms. In WU H. (1985, p.192), the monthly per capita output in 1833 was 16.2 kilograms.
The estimated output per capita per year during the Qing Empire decreased from 576 kilograms
in 1753 to 314 kilograms in 1812 (WU H., 1985). In the middle of the Qing Empire, the level
was even lower than that in the 3rd century (WU H., 1985, p.191). Compared with previous
studies the present estimation seems plausible. It confirms the statement that Qing China’s
agricultural production per capita was much lower than in previous empires.
9
In general it consisted of rice, wheat, and beans in southern China, and of wheat and beans in the northern area. Historians
estimate the national level of composite yields using the ratios of cultivated land in the two parts of China as weights.
11
The final question is whether the estimated levels of food production in the late 19th century
could cover the minimum daily energy intake that is necessary to survive for a human being.
Grains, sweet potatoes, and maize were the main energy sources of food supply in Qing China.
Here we assume that the per capita output equals the per capita consumption. LIU R. (1987,
p.107) calculated the minimum food consumption per capita in the 18th century at 290
kilograms. On average, our estimation is 19 percent higher than this subsistence level.
The available daily energy consumption per capita is estimated by using the annual food
production in the period 1840-1912.10 Taking account of an energy loss of 20 percent of the
total daily intake, the average daily energy consumption was 2600 kcal, with a range between
2290 and 2760 kcal for the whole period. In fact, the average is rather close to the situation in
modern China, with 2970 kcal in the period 2005-2007.11 Even if we assume that the energy
loss was 40 percent, the average daily energy consumption was 1950 kcal, which is still higher
than the minimum requirement of 1800 kcal, used by the FAO. There are two other studies that
give energy estimations. From Buck’s survey data (Buck, 1930, 1937), the general range of the
daily energy consumption in the 1930s was 1823-4434 kcal, which supports our estimation. In
Chang (1962), the estimated daily energy consumption was about 1800 kcal in the 1880s,
which is much lower than our estimation but still supports our finding that the general
biological living standard that we measure for the 1880s was sustainable.
To sum up, based on the cross check of production capacity, our estimation is lower than the
level provided by previous studies. Based on the cross check of average energy consumption
levels, our calculations might possibly overestimate the available amount of food output. In
general, our estimation passes two cross checks. Our estimation of food crop production in the
late 19th century is plausible and supports sustainability.
For the remaining three categories of agricultural activities in Table B.1, value added in current
prices was estimated by a fixed ratio or proportion to the output value of basic-food crops (see
details in Appendix B, section 1.2-1.4). Figure B.5 presents the results. Average value added in
the agricultural sector during the period 1840-1912 is estimated at 11.25 tael per head of
population (in current prices), with a variation between 5.75 and 27.80 tael for the total period;
the average proportion of agriculture in total GDP was 75 percent. There was an annual
decrease of about 0.9 percent before the 1880s. This was followed by an increase of 4.2 percent
per year, mainly because of rising price levels. Low levels of value added were found in the
1850s and in the 1880s.
10
Energy data for the different food crops is from the Nutrient Data Laboratory, http://www.nal.usda.gov/
http://www.fao.org/fileadmin/templates/ess/documents/food_security_statistics/FoodConsumption
Nutrients_en.xls
11
12
3.2 The industrial sector
There are relatively few data sources for the collection of quantitative information for every
industry. The existing literature, however, allows us to obtain a coherent picture of this sector.
In our estimation, we direct our attention in particular to the early development of modern
industrial production. One of the major economic characteristics in the late Qing Empire was
the start of industrialization and the so-called self-reinforcing movement between 1860 and
1895. This movement was characterized by the spread of foreign technology and the start of
state-owned factories in the iron, coal, textile, and transportation equipment industries. Later
on industrial development broadened through the spread of private-owned factories. Some of
the former state-owned factories were taken over by private owners. After 1894, the
coexistence of modern factories and traditional handcraft workshops was common in many
industries. Although traditional production was still dominant, we believe that the new
situation of foreign technology transfer is an important aspect of China’s early
industrialization. Therefore, our estimation not only focuses on the development of the proto
industry, but also on the results of early industrialization.
In the 1920s, the modernized sectors can be estimated at 20 percent of total industrial
production (XU and WU, 2005, p.1051). In our definition, a modern factory in China in the late
19th century was characterized by new production technologies supported by European
machinery. In contrast, handcraft workshops kept the traditional way of production (see for the
same classification in Liu and Yeh, 1965). In practice, it can be difficult to make a distinction
between the two. Large and advanced workshops may have been just one step away from
modern factory production; on the other hand in factories without a well-trained labor force,
“new” production with novel technology may have existed only in name.
Our procedure goes in two steps. First, levels of value added in the traditional workshops and in
the factories using imported new technology are calculated for the years 1840, 1885, and 1920.
Next, we estimated a time series of output for both sectors. It shows that the proportion of
factory production in total industrial production increased from 5.4 percent in 1885 to 21.5
percent in 1920 (see Appendix B, Table B.7, column 1 for details). This indicates a rapid
increase of factory production in the early phase of industrialization.
3.2.1 Factory production
The reconstruction of value added produced in the modern factory system starts by making two
level estimates, for 1885 and 1920 respectively. These benchmarks are derived by adding up
the output of all major industries, as shown in Table B.7, column 1. We follow a procedure that
was used by Debin Ma (2008, p.367, Table 3) who estimated value added for the period
1914-1918 in the secondary and tertiary sector. Debin Ma projected the 1931-1936 industrial
sectors’ GDP levels backward to the period 1914-1918, using a growth rate estimated by
Rawski (1989). Here, we treat the year 1920 as the benchmark and back-project levels of value
added to 1885, using an average annual growth rate.
13
To estimate the annual growth rates during the period 1885-1920 we introduce a method based
on growth accounting (see details in Appendix B). In our Cobb-Douglas production function
we assume that the growth of the technology residual was close to zero at that time, because
technology was directly bought from the western world and took the form of capital
accumulation. Measuring growth means in this case that time series of capital and labor input
have to be estimated.
Two data sources have been combined to construct time series of capital input for factory
production. Table B.8, line 1, lists four estimates of capital input for 1885, 1894, 1913, and
1920, from XU and WU (2005, p.379 and p.1046). Their capital estimation includes
manufacturing industries, mining and production of basic metals using machinery,
transportation, and communication. They calculated the value of fixed capital on the basis of
quantity indicators, such as the number of spindles in textile mills, and tonnage of ships, etc.
For missing capital data they applied initial capital or net assets as proxies; for some industries
such as transport manufacturing, indicators like railway mileage or installed power-generating
capacity are applied as an approximation. They also distinguish factory production from
traditional workshops. To fill in all the missing data points between the benchmark years, we
added annual increments to initial capital during the period 1872-1912 (YAN, 1955, p.93-95).
Figure 2.4 shows that the rise in capital outlays accelerated after 1900.
With the estimated capital and labor inputs and the general price level for industrial products,
growth rates of factory production were calculated for the late 19th century (see details in
Appendix B). Per capita output in factory production increased from 0.07 tael in 1885 to 1.84
tael in 1920. Our own time series generates a growth rate of 10.9 percent, which is reassuringly
close to the average growth rate of 9.5 percent that we get if we only use the two benchmarks.
The average growth rate of factory production, however, did not affect the total growth rate of
GDP significantly, because the initial proportion in GDP was less than 3 percent. As mentioned
earlier, agricultural production took up a major part of the whole economy but had an annual
growth rate lower than 1 percent. The momentum of early industrialization in late Qing China
was overshadowed by the sheer size of the agricultural sector.
We can do some cross checks. First, the consistency of our estimation can be evaluated. As an
upper limit, we quote Liu and Yeh’s estimation for 1933, which is another study that makes a
distinction between value added produced in the modern and in the traditional sector. Since we
have not included their data in our estimations for the benchmarks, it can safely be used as a
cross check. Liu and Yeh conclude that the proportion of the value added created by new
factory production was 5.4 percent of GDP in 1933. In our estimation for the period 1884-1912,
the proportion was less than 2 percent. The net value added of modern factory production per
capita is estimated by Liu and Yeh at 2.16 tael in the 1930s, whereas our average is only 0.66
tael for the whole period and 1.43 for the year 1912. Therefore, the present reconstruction of
new factory production in the late 19th century may be an underestimation of the actual levels.
However, the increase of value added per capita may as well indicate a rapid process of
industrialization during the early 20th century.
14
[Figure 2]
We can also check the reliability of the growth rates of industrial production that we have
found. Three figures (Figure 2.1-2.3) show that after the 1860s the economy experienced a
rapid increase in the imports of essential inputs for industrialization, such as machinery, coal,
and iron. The average growth rates were 10.2 percent for machinery imports between 1887 and
1916, 6.2 percent for coal imports in the period 1885-1920, and 4.7 percent for the iron, steel
and tin imports in the same period. These rates support the increase in output that we found. We
find that imports of these inputs accelerated after 1900, which looks quite similar to the
movement in capital inputs.
3.2.2 Cross checks for the total proto industrial sector
For the traditional manufacturing production during 1840-1920, use was made of
approximations that are shown in Table B.9. The question is whether we can rely on the general
trend given by the three existing benchmark estimates, which together implicitly indicate that
handcraft production decreased first, but then increased to an even higher level. This may be a
plausible development. But it is still difficult to support or reject the estimated trend because of
lack of data; more data research will be necessary. On average the net value in the proto
industrial sector during the period 1840-1912 was 1.61 tael per capita; the range was 0.52-3.41
tael; its average proportion in GDP was 10 percent; the average growth rate was 0.4 percent.
We have used an estimation for 1914-1918 from Debin Ma (2008, p.367, Table 3) as a cross
check. In his calculation, the per capita net domestic production of the industrial sector for
1914-1918 was 2.79 tael on average and its proportion in GDP was around 8 percent. The
present extrapolation based on the method explained before gives a level of 3.08 tael for the
period 1914-1918. Although still higher than Debin Ma’s estimate, our 1914-1918 estimate,
which is derived from a different method, is rather close. It supports our estimation for the
proto-industrial sector and the method used. However, we might overestimate net value added
for the entire sector. The estimate needs further improvements (see Appendix B, 2.3 for
details).
3.3 The service sector
Four sub-sectors have been included in our estimation for the service sector: public
administration, finance and housing, commercial activities, and the self-employed professions.
Here we concentrate on public administration, employing a new data source that distinguishes
15
our estimation for services from previous studies. For the three other sub sectors, we refer to
Appendix B for details (section 3.2-3.3).
3.3.1 Public administration
For a reconstruction of public administration we focus on government expenditure and
estimate its value added combining central government expenditure and the proportional share
of it in total governmental expenditure. The new dataset that we use in this section is compiled
from the historical document Hubu yinku huangce. As part of the governmental administrative
routine, the Qing state recorded in this document the annual central government income and
expenditure, and also its treasury reserves. The expenditure records mainly include military
spending, officials salaries, relief funds, administration costs, and royal funds. According to
SHI (2009), central government expenditure during the late Qing Empire was lower than 12
million tael, which had been the regular level in the early Qing Empire. But government
expenditure increased significantly after the Taiping Rebellion and after the Sino-Japanese
War.
We apply figures for the proportion of central government expenditure in the total government
expenditure of 13 percent before 1894 and 15 percent after 1894. These are much lower than
the level of 30 percent in the early Qing Empire (all figures based on SHI, 2009, p.102). This
may indicate the declining control power of the central government. To put this into a
long-term perspective: According to the official data from the China Statistical Yearbook
(2008), the proportion of central government expenditure in total government expenditure was
around 50 percent between 1978 and 1980 and about 25 percent in the recent decade.
In our estimation total government expenditure was also low; the per capita level was 0.27 tael
on average, and its proportion to GDP was 1.29 percent on average. According to the census in
1933, these levels were 1.1 tael per capita and 2.7 percent, respectively. In two previous studies
total government expenditure was estimated at 95 million tael in 1840 and 164 million tael in
the 1880s respectively (Chang, 1962; LIU T., 2009). However, our estimations are lower with
the 1840 level at 79.3 million tael, and the average level for the 1880s at 107.2 million tael
respectively. There can be two reasons for the difference: first, the original records that we used
may have covered only a part of central expenditure; second, we might have underestimated
the proportion of the central government expenditure in total government expenditure. Also
here further improvements will be necessary.
The documents show that in the late 19th century the Qing state was in great trouble to maintain
its normal operations. As displayed in Figure 3, the proportion of public income and
expenditure to GDP decreased significantly in the second half of the Qing Dynasty. For most
years in this period expenditure was higher than income. In others years, the Qing state barely
sustained its balance. It means that public savings decreased continuously and possibly failed
to recover until the end of the empire.
16
One could easily ascribe these difficulties to the wars after 1840. However, we believe that the
crisis actually started in the early Qing Empire before the international wars broke out. The
decrease of the public income/GDP ratio and the public expenditure/GDP ratio can be traced
back to the late 18th and early 19th century (see Figure 3). Moreover, the tension between the
central and local controllers was likely to intensify. In most years of the Qing Empire, the
central government collected 25 to 33 percent of the total government revenue to support its
regular expenditure and it held high reserves before 1800 (SHI, 2009). The annual reserves in
the state treasury reveal that the state lost its control. E.g., to put down the White Lotus
Rebellion (1796-1805), the Qing state exhausted nearly 70 percent of the treasury reserves,
which decreased from 70 million tael in 1795 to 20 million tael in 1798. During the entire late
Qing Empire, the reserves remained around 10-20 million tael and never got back to a level of
35 million tael which was the regular level of reserves in the early Qing Empire. The
proportion of central revenue in the total declined from 22 percent before 1850 to 14.7 percent
in 1903 (SHI, 2009, p.43, 63).
[Figure 3]
3.3.2 Cross checks for the total service sector
By adding up the four sub sectors, we obtain total value added in the service sector for the
period 1840-1912: on average it was 2.71 tael per head, with a variation between 1.91 and 4.88
tael in the total period. The proportion of services in total GDP was around 18 percent; the
average growth rate was about 1 percent.
Also here previous studies for specific years can be used to compare our time-series
estimations with. The per capita value in this sector was 2.9 tael in 1840 according to LIU T.
(2009) and 2.3 tael in the 1880s according to Chang (1962). In the present reconstruction, the
1840 estimate is 2.35 tael, and the average level for the 1880s is 2.42 tael, respectively 20
percent lower and 5 percent higher than the existing figures. At the end of the Qing Empire, the
value added from the service sector reached 4.76 tael per capita in 1912, while previous
estimates arrive at 7.3 tael for the period 1914-18 (Debin Ma, 2008) and 6.81 tael for 1933 (Liu
and Yeh, 1965). We may have underestimated the growth rates of the service sector after the
1880s since these are based on movements in the population (see Appendix 3.2).
3.4 Nominal and real GDP between 1840 and 1912
The level of total nominal GDP according to our reconstruction is 6.00 billion tael in 1840 and
14.59 billion tael in 1912. The per capita nominal GDP estimates for both years are 14.57 tael
and 33.75 tael respectively (see Figure 4a). Taking a simple average for the whole period, we
17
arrive at a per capita level of 15.42 taels of silver, with a variation between 9.46 to 35.39 tael.
The growth rate of nominal per capita GDP between 1840 and 1912 was 1.2 percent per year on
average.
The Chinese economy in the late 19th century consisted mainly of agricultural and service
activities, together between 83 and 95 percent of the total economy. The size of the proto
industrial sector was about 10 percent of GDP, but in the 1880s it was only 6 percent. This low
level is mainly caused by our use of the benchmark estimate for the proto industrial sector from
Chang (1962). In Maddison’s estimation for 1890, the percentage shares for the three sectors,
agriculture, industry, and services, were 68.5, 15.3, and 16.2, respectively (Maddison, 2007,
p.60). These figures were calculated by a backward extrapolation from the year 1933.
assuming a constant growth rate of sector GDP between 1890 and 1933 (p. 156), which is
highly unlikely. The percentage shares in our 1890s estimation are: 72.4, 8.1, and 19.5. These
differences show that there is room for more refinements in the calculation.
Figure 4a shows strong fluctuations in nominal GDP per capita during the 1850s-1860s and the
1900s-1910s. The main driving force is the price of rice. To give a better idea of the movement
of real GDP per capita, i.e. in volume terms, we need to adjust for price changes. To construct a
GDP deflator for the period 1840-1912, we compose a simple basket consisting of gold and rice
only, with weights of 28 percent and 72 percent respectively. 12 The price of rice is
representative for basic-food crops. The rice price in late 19th century China was volatile, while
the domestic price of gold in terms of silver was relatively stable (PENG, 1957; Wang, 1992).
The gold price is used as a proxy for the prices of non-agricultural products and services in the
economy. The weights of both items were established accordingly. The weight of the price of
rice is the average ratio of the value added of the agricultural sector in total GDP. We implicitly
assume that the gold price represents both industrial products and services. Adding other
commodities and services into the deflator, such as clothing and housing, will of course
produce a more precise indicator, reflecting the price behavior of more products. At this
moment, however, it is not possible to produce a better indicator because of lack of price series
for other products.13 Nevertheless, we believe that a simple deflator like the present one serves
our purpose to identify the broad trends in the movement of real GDP per capita.
In the period 1840-1912, real per capita GDP in 1840 prices is 14.53 tael on average, with a
variation between 12.53 and 16.38 tael for whole period. Figure 4b shows some major
movements in the trend. Real GDP decreased from an average level of 15 tael before the 1870s
to an average of 13 tael after the 1870s (in prices of 1840). Based on the beginning and end
points only we find a long-term annual decrease in GDP per capita of 0.08 percent. However,
an important turning point can be discerned around 1870. Before that year, GDP per capita
increased at an average annual rate of 0.35 percent. After 1870, there was a steady decline of
0.38 percent per year.
12
In a similar fashion, LIU T. used weights of 25 percent and 75 percent (LIU T. 2009, p.151).
There are estimations of general price levels for the late 19th century, such as WANG Y. (2005), but they only cover the
period after the 1860s. To avoid the problem of inconsistency, we define our own rice-gold price index for the total period.
13
18
[Figure 4]
How do these total economy estimates compare with other available estimates? In the
following we will confront our results with existing ones. LIU T. calculated a per capita level of
GDP in 1840 of 10.8 tael (LIU T., 2009, p.153). Our level estimate of 14.57 tael, is about 50
percent higher than his, which may indicate an overestimation in our results. Our estimation for
the 1880s is 11.78 tael, whereas Chang (1962) arrived at a level of 7.4 tael. The low figure of
Chang results from his low estimate of the area under cultivation. The minimum requirement
for a plausible GDP estimate is that people at least can survive on the estimated levels of per
capita GDP. It has been shown earlier that in the late Qing Empire food production could
support the daily energy requirement of the Chinese population. Here we infer the average
household budget in the Qing Dynasty. FANG X. (1996) estimates the average consumption
basket in the Qing Dynasty for a farmer family with five members living in the Jiang-Zhe
province. It covers food, cloths, rent, and fuel. He concludes that in the early Qing Empire the
level of annual household consumption was 32.6 tael and in the late Qing Empire 58.31 tael.
Following ZHANG Y. (2005), we add per capita education expenses to this estimation at an
amount of 1 tael or 5 tael per family. Thus, the estimated per capita consumption in the late
Qing Empire is 12.7 tael (63.31 divided by 5). This number probably overestimates the national
level because it relates to the rich Yangzi delta region. Furthermore price fluctuations in the
nineteenth century make it difficult to value this average consumption basket.
With a minimum level of 12.53 tael and an average above 14 tael in our real series, our
estimation of real per capita GDP from the production side is generally higher than the
estimated average consumption level. It follows that the aggregate output level was able to
sustain an above-minimum living standard for the population in the late 19th century.
The new reconstruction provides a time series of annual GDP estimates. The second check of
our new estimation is whether it is consistent with the general circumstances of the late Qing
Empire. As mentioned before, the 19th century is labeled in Chinese historiography as the
“years of troubles” or the “turbulent century”. Although real per capita GDP was high in the
1860s, the common theme in the historiography of the second half of the Qing Empire is one of
ongoing economic decline until the early 20th century. Our estimation of real GDP supports this
general opinion. The study of Baten, Ma, Morgan, and Wang (2010) using real wages and
historical demographic data is in line with our results. They conclude that from the mid-19th
century there was a decline of living standards in South China followed by a recovery in the
early 20th century.
The third and most important cross check for our estimation can be found in Broadberry et al.
(2013). The authors provide a detailed GDP reconstruction covering the period 980-1840. They
treat 1840 as their reference year for the price level (see their Table 3, p. 33). Their GDP per
19
capita estimate for 1840 is 12.95 tael, which is 11-12 percent lower than our estimate of 14.57
tael for the same year. The difference stems mainly from the applied assumptions of the
input/output ratio for grain crops. Broadberry et al. assumed a ratio of 18 percent, which in our
view is abnormally high (Broadberry et al., 2013, p. 38). We based our calculation on a ratio of
about 10 percent, which is more in line with existing studies (see Appendix B. 1.1.3).
Unfortunately, it is not possible to reconstruct their estimation by using our assumption of the
input/output ratio. Therefore, we applied their assumption to our study for a robustness check.
If we use the input/output ratio of 18 percent instead if 10 percent, our new 1840 estimate
would decrease to 13.61 tael. This would already explain already half of the difference between
our estimate and that of Broadberry et al. Because most studies apply a level of 10 percent for
the late Qing Dynasty we feel confident that this is a proper input/output ratio to base our
calculations on. It would also imply that there is only a small difference between the two
independent level estimates for Chinese per capita GDP in 1840.
4. Conclusion: main findings and remaining issues
Let us summarize the results of our estimate of Chinese GDP. We have employed new methods
and data sources, but derived our new estimation also from earlier studies on historical GDP.
One of the aims of our estimation was to construct a consistent time series of GDP by
improving and linking existing studies. For the agricultural sector a new time series of the land
area under cultivation was estimated and we added a multiple cropping ratio; for the industrial
sector, we focused on value added of factory production and applied a new method to estimate
its growth rates with a Cobb-Douglas production function; for the service sector, a new data
source was used to estimate government expenditure. On the basis of this a time series of
historical GDP was constructed for the late 19th and early 20th century in nominal and real
terms.
A major problem in the reconstruction of historical GDP is that the degree of autarky in
pre-modern China was probably high. The issue is in fact similar to the neglect of non-market
work in calculating GDP nowadays. For a low-commercialized economy, a
market-value-based GDP calculation may therefore generate imprecise results, especially if
households use their backyard for home production. Later improvements and more cross
checks for upper limits will therefore be necessary.
Now we will come back to the two questions that we raised in the second part of the paper. To
solve the inconsistencies between the various level estimates, it was necessary to get plausible
nominal GDP estimates and PPP convertors. This paper has focused mainly on the estimation
of nominal GDP and less on the international comparison of levels of welfare. Therefore, we
cannot completely solve the first question. Concerning the reconstruction of nominal GDP/cap
levels, we believe that both Chang (1962) and LIU T. (2009) underestimated levels of Chinese
GDP per capita. The nominal per capita GDP estimate for 1840 in LIU T. (2009) is 10.8 tael,
while the estimate for the 1880s in Chang (1962) is 7.4 tael. We arrived at higher levels for
corresponding years: 14.57 tael in 1840 and 11.78 tael for the 1880s. Our new estimation will
20
probably also solve a large part of the differences between the macro and sector studies in Table
2, once we have reliable international currency converters. This is something for future
research.
Our paper mainly intends to solve the inconsistency problem of growth rate estimates by
providing a consistent time series of GDP in both nominal and real terms. We believe that the
present reconstruction improves our understanding of the economy in late 19th century China.
Figure 4b displays the graph of an economy that showed some per capita growth before the
1870s, but declined steadily afterwards until 1900. The economy started to recover in the
1910s, the end point of our reconstruction. The economic trends in our new estimation are
different from the stagnation that we see in Maddison’s estimation as well as from the pattern
of mild increase in the various sector studies. Maddison’s estimation indicates a turning point
in 1870. Per capita GDP declined from 600 GK dollars in 1850 to 530 GK dollars in 1870.
After that, the economy stagnated at a level around 550 GK dollars. Similarly, our estimation
indicates a turning point close to 1870, but instead our data show an economy that was in
ongoing decline after the 1870s. For the first half of the 19th century, we find relative stable real
GDP/cap levels. This is quite in line with the corresponding estimates by Broadberry et al.
(2013). On the other hand, our data present a different picture than the real wage data
calculated by Allen et al. (2009), indicating a slow rise of real earnings of workers in the late
19th and early 20th century. Our real per capita GDP calculations suggest declining living
standards for the Chinese population after 1870.
It is also useful to make a comparison between two periods of economic shifts: the war period,
1840s-1850s, and the recovery period, 1860s-1870s (see the two shaded areas in Figure 4a and
3b). For the war period, the present estimation reveals an economy with slightly increasing
levels of real GDP per capita but with considerable nominal fluctuations. For the recovery
period, our estimation shows mainly decreasing trends in both nominal and real GDP per
capita. The comparison may indicate that the negative effect of wars and rebellions on the
Chinese economy was only regional and therefore possibly overstated. One way to check how
much the whole country was affected by the wars in the 1840s and 1850s is by studying the
records of the granary storage. Except for the regions that were directly affected by the Taiping
Rebellion (1851-64), the granary storage in other regions in the period 1840-1855 was stable
and similar to the levels in previous years. Even for the regions close to the rebellion area, such
as the Jiangxi province, the decline of granary storage only started after 1855, when the
rebellion was already four years underway (Will and Wong, 1991). The agricultural production
and the function and responsibilities of the political system were not affected in the early years
of wars and rebellions. Even with a high level of societal instability, the economy was able to
avoid an immediate decline. The real decline was delayed until after the 1870s.
Our new estimation suggests that the ongoing economic decline in the final decades of the 19th
century intensified the process of economic divergence between China and the modernized
Western economies. Figure 4b indicates that average levels of real output increased and
remained at a higher level in the 1850s-1860s. These were the decades when the economy was
increasingly involved in international trade, when new economic policies were introduced to
21
encourage knowledge transfer from western countries and technology absorption. At the same
time government investments were made in defense-related industries and in industries such as
textiles, mining, iron, and shipbuilding. However, the economy shifted quite suddenly into a
decline during the so-called self-strengthening movement (1860-1894), with social, economic,
and political reforms that were intended to catch up to the richer nations in the world. A deeper
investigation into the Chinese economy in the 1860s and 1870s will help us to explain the lost
chance of catching up in the 1860s, the “economic difficulty” in the 19th century, and the
widening economic the gap vis-à-vis the West. Apparently opening up the economy came at a
cost.
Finally, our estimation provides a time series of GDP in current prices but also fixed-price GDP
estimates in silver taels of 1840. We believe that the real time-series may provide new avenues
for future research. First, we have not completely solved the first problem of inconsistency
between previous estimations. To compare our GDP estimates with estimates in international
dollars, a PPP convertor between silver taels and international dollars for late 19th century
China will be necessary. We can apply the PPP convertor for the 1930s estimated by Fukao et al.
(2007), but a new PPP convertor for the 1910s, that is before the monetary disruptions caused
by WWI, would be more optimal. Second, it is possible to improve on the estimation for the
traditional handcraft sector by including detailed sub-sectors such as food processing, mining,
and construction.
22
Table 1. Historical GDP per capita estimates in previous studies, 1000-1933
a. Benchmark estimations
Period
Benchmarks
Currency
Sector Studies
1800-1900
1800 1840
LIU LIU
R.,
T.,
1987 2009
6.7
1700
tael
Benchmarks
Currency
Macro studies
Broadberry
et al., 2013
1880s
Chang,
1962
Feuerwerker,
1969
1910s-1920s
1914-18
Perkins,
D. Ma,
1969
2008a
10.8
1840
tael
12.95
1840 tael
7.4
tael
39.3
1933 yuan
112.6
1957 yuan
52.4
1930s
yuan
35
yuan
(current)
318
1990
int.
dollars
594
1990 int.
dollars
411.6b
1990 int.
dollars
221.4c
1990USD
549.5b
1990 int.
dollars
129.2c
1990USD
(current)
337.1b
1990
int.
dollars
1920s
XU and
WU, 2007
1930s
1933
Ou,1947
1931-36
D. Ma,
2008e
1934-36
Fukao et
al., 2007
123.4
1957 yuan
57.4
1930s
yuan
60.5
1930s
yuan
242.6c
1990USD
601.9b
1990 int.
dollars
619
1990 int.
dollars
Liu and
Yeh, 1965
Perkins
and Zhao,
1975
46
yuan
(current)
59.8
yuan
(current)
482.4b
1990 int.
dollars
626.6b
1990 int.
dollars
1933
Maddison,
2010
579d
1990 GK
dollars
b. Time-series estimations
Period
Average
Currency
Average
Currency
Macro studies
1000-1933
1850-1913
Maddison, 2010
Maddison, 2010
566
554
1600-1850
Broadberry et al., 2013
715e
1990 GK dollars
14.1
1840 tael
Sector Studies
1750-1850
Broadberry et al., 2013
618e
1990 int. dollars
1640-1840
LIU T., 2009
1750-1840
LIU T., 2009
352f
317f
4
1600 tael
23
Source: See references, collected by the authors.
Most of the sector studies in Table 1a give results in terms of silver taels or Chinese yuan. We adjusted these estimates and presented them in terms of 1990 int. dollars
or 1990 USD. See the numbers with superscripts in Table 1a.
a
Here, the value represents net domestic product (NDP).
b
The calculation is based on Fukao et al. (2007) , p. 17, Table 8. For these PPP adjusted estimates, we use the term “1990 int. dollars”.
c
The calculation is based on the official exchange rates between China and the U. S. and the historical U.S. price levels. For these, we use the term “1990USD”.
The 1930s exchange rate: 1 U.S. dollar= 3.01Chinese yuan; 1 tael = 1.5 Chinese yuan .
The 1920s exchange rate: 1 U.S. dollar= 2.02 Chinese yuan.
d
The figure is not a direct benchmark estimate, but projected from Maddison’s 1990 estimation.
e
The figure is calculated from Broadberry et al. (2013), p. 34, Table 4.
f
The figure is calculated from LIU T. (2009), p. 153, Table 1.
Table 2. A comparison of average per capita GDP estimates in macro and sector studies, 1840s-1930s
Macro Studies
(1990 GK dollars)
1840s
1850s
1860s
1870s
1880s
Sector Studies
(1990 int. dollars)
Broadberry et al., 2013
318
594
(10.8 tael)
(12.95 tael)
600
594
530
337.1-411.6
(7.4 tael)
1890s
540
1900s
545
1910s
552
549.5
1920s
562
1930s
570
482.4-626.6
1933
579
482.4-626.6
Source: Collected and calculated by the authors. The range of estimates from the sector studies is derived from Table 1a.
24
Table 3. Conflicts, disasters and the state treasury in Qing China, 1840-1912
1640-1840
(Early Qing Empire)
1840-1912
(Late Qing Empire)
60
6
54
8
2646
15
2698
30
30
10
A. Number of conflicts
Total
Decadal average
B. Number of natural disasters
Total
Decadal average
C. Reserves in the state treasury
Average level (in million tael)
Source: Collected by the authors.
Table 4. Estimations of cultivated land area in various studies, Qing China, 1840-1912, in billion mou
Period
Average level
LIANG F.,
1980
(official data)
Perkins,
1969
WU H.,
1985
SHI,
1989
ZHANG Y.,
1991
ZHANG Y.,
1991
LIU F. and
WANG Y.,
1996
ZHOU R.,
2001
GE et. al., 2008
1851-1887
1873-1913
1840-1915
1840
1914
1851-1914
1840-1912
1840-1912
1873-1913
0.81
1.27
1.40
1.11
1.20
2.10
1.2
For a specific year
Source: Collected by the authors. 1 mou = 666.5 square metres
1.15
1.26
25
Figure 1. An estimation of food supply in Qing China, 1840-1915
a. Food crop production per capita in kilogrammes
b. Daily energy intake per capita in Kcal
Sources: See the text, estimated by the authors.
26
Figure 2. Imports of industrial inputs and an estimate of capital input in Qing China, 1860-1920
2.3. Iron, steel, and tin imports, 1867-1920, in 1,000 tael
16
1915
1909
1903
1897
1891
1885
1867
1914
0
1911
0
1908
4
1905
4
1902
8
1899
8
1896
12
1893
12
1890
16
1887
16
1879
2.2. Coal imports, 1867-1920, in million tael
1873
2.1. Machinery imports, 1887-1916, in million yuan
2.4. Capital input in factory production, 1885-1920, in 10,000 yuan
30
25
12
20
8
15
10
4
1917
1912
1907
1902
1897
1892
1887
1882
1877
1872
0
1867
0
5
58
81
88
81
19
81
49
81
79
81
00
91
30
91
60
91
90
91
21
91
51
91
81
91
27
Source Figure 2: Collected and constructed by the authors.
Figure 2.1 is from CHEN Z. et al., 1957, p. 818. Figure 2.2 and 2.3 are from Hsiao, 1974. Figure 2.4 is constructed by the authors.
Figure 3. Public finance in Qing China, 1700-1912 (as a percentage of total GDP)
Source: Collected and calculated by the authors. The nominal GDP data before 1840 is derived from Broadberry et al., 2012, Figure 3. The data on public income and
expenditure is from SHI, 2009.
28
Figure 4. A new estimation of per capita GDP in Qing China, 1840-1912
a. Per capita GDP in current prices (in tael)
b. Per capita GDP in constant prices of 1840 (in tael)
Sources: See the text, estimated by the authors. The two shaded areas represent the war period, 1840s-50s, and the period of recovery, 1860s-70s.
29
Appendix A . Background facts and figures
Table A.1. Empires in Chinese history
Empires
Han Empire
Tang Empire
Song Empire
Yuan Empire (Mongol)
Ming Empire
Qing Empire (Manchu)
The early Qing Empire
The late Qing Empire
Republic China
Source: Cambridge history of China
Periods
206BC-220AD
618- 907
960- 1279
1271- 1368
1368- 1644
1644– 1912
1640- 1840
1840- 1912
1912- 1949
Table A.2. Major historical events in Qing China, 1796-1906
Wars
Political or economic reforms
White Lotus Rebellion
First Opium War
Second Opium War
Taiping Rebellion
Nien Rebellion
First Sino-Japanese War
Tongzhi restoration
Self-strengthening movement
The reform of 1901
1796-1805
1839-1842
1856-1860
1851-1864
1852-1868
1894-1895
1861-1875
1860-1894
1901-1906
Source: Cambridge history of China
Table A.3. Units of measurement used in the paper
Area
1 square kilometer= 1500 mou
Weight
1 jin = 500 grams
Exchange rates
1 Qing tael = 37.3 grams of silver.
Source: Perkins, 1969, p.1-2
30
Appendix B. A new estimation of historical GDP, 1840-1912
This appendix introduces and explains our GDP reconstruction. We present how we
estimated value added in the three sectors: the agricultural sector, the proto industrial
sector, and the service sector.
1. The agricultural sector
We have listed the major agricultural products and activities in Table B.1. In this section,
we will explain the calculation of the four categories of agricultural produce step by step
and concentrate mainly on the items in bold letters.
Table B.1. Four groups of agricultural products and activities
Groups
Main products and activities
1
Food crops that were
land-intensive
(Grains)14
2
Non-food
but land-intensive crops
Rice
Wheat
Millet
Kaoliang
Barley
Maize
Sweet potatoes
Other food crops
Soy beans
Cotton lint
Mulberry and silkworm (raw silk)
Oil seeds
Peanuts
Astragalus root
Opium poppy
3
Non-food crops that were
not land-intensive
Tea
Fruit and vegetable
Flower
4
Others
Cattle farming, fishery, and forestry
Source: Chang, 1962; LIU R., 1987; XU and WU, 2005.
Items in bold type are treated in detail in the text.
14
See also footnotes 5 and 6.
31
1.1. Food crops
Food crops were calculated from the production side, summarized by equation (1.1):
= ∑ (1.1)
, where Y is the gross value of food crop production measured in silver taels; A is the yield
per unit of the ith food crop in silver taels; K is the input of cultivated area for the ith food
crop (the crop area in a period); t is the year index. In total, we have eight food crops.
With the input/output ratio, we can then derive value added in food crop production. We
will first introduce how we reconstructed K, then A, and finally the input/output ratio.
1.1.1. Calculating land input K
We apply the following equation to estimate and construct a time series of K.
= ∗ ∗ (1.2).
The three parts in the above equation were reconstructed as follows.
1.1.1.1 The cultivated land area
We applied a method where we combined two level estimates and an interpolation
procedure where we fitted a trend line in between both level estimates. The procedure of
fitting the trend can be explained with a simple example. It contains only two unknown
data points, not the 71 data points which are actually calculated in the paper.
Suppose there is a four-year time series of the cultivated area (Y), referred to as the old
time series, and for which we know the relative level for each year, that is, the annual
change in area (see Table B.2). Suppose also, that we cannot use this series directly, since
its average level is not a robust estimator for the total area. Next, we calculate two new
levels for the total area available for cultivation (X). Now we have only level estimates
for year 1 and 4, denoted as E1 and E4 in Table B.2. To fill in the two missing data points,
X2 and X3, we “fit” the trend of the old time series into the new one by assuming the
same rates of annual changes between the two, denoted as W3 and W4 in Table B.2. Here,
we actually assume that the second-order differences across years are the same for the
two time series. We give the details of this method of fitting in Table B.2.
Taking the rates of annual changes from the old time series (W3 and W4), we reinterpret
and present the relationship between the different time points for the new time series. To
calculate X1 and X2, the only unknown is v2, which can be derived from the relationship
between E1 and E4 (see Table B.2, last column). Following the same procedure for more
years, we obtain the estimated time series of the cultivated area in Figure B.1. Here, the
32
old time series is from WU H. (1985) which provides annual changes for our estimation,
and the new time series we construct connects the 1840 and the 1914 estimate given by
SHI (1989) and ZHANG Y. (1991), respectively (See Table.4.). We also provide the
maximum and minimum levels from the existing literature.
Table B.2. An interpolation procedure for the reconstruction of the area under cultivation
The old time series
The new time series
Year Levels
Annual Rates of Annual changes
Levels
changes annual
changes
1
Y1
E1
2
Y2
V2
v2
X2 = v2* E1
=Y2/Y1
3
Y3
V3
v3 = v2* W3
X3 = v3* X2
W3
=Y3/Y2 =V3/V2
= (v2* W3)*(v2* E1)
= (v2)^2* W3* E1
4
Y4
V4
v4 = v3* W4
E4 = v4* X3
W4
=Y4/Y3 =V4/V3
= ((v2* W3)* W4)*( (v2* W3)*(v2* E1))
= (v2* W3)* W4
= (v2)^3*(W3)^2* W4*E1
Source: Constructed by the authors.
Figure B.1. The estimation of the cultivated area (after interpolation), 1840-1914, in billion
mou
1,6
1,2
0,8
The lower limits: LIANG (1980)
0,4
Our estimation
The upper limits: WU Hui(1985)
1912
1908
1904
1900
1896
1892
1888
1884
1880
1876
1872
1868
1864
1860
1856
1852
1848
1844
1840
0
Source: Calculated by the authors.
In our estimation, the starting point of 1.15 billion mou in 1840, is from SHI (1989). The end point
at 1.26 billion mou in 1914, is from ZHANG Y. (1991). See Table 4. The annual growth rates are
from WU H. (1985).
1.1.1.2 The proportion of basic-food crop cultivation
Not all the cultivated area was used for food production; and some non-food crops were
also intensive in land use, such as soy beans. In our calculation, we believe that the proper
proportion of the basic-food crop cultivation in the late Qing Empire was around 85%. By
33
surveying the existing literature, we find that the figure decreased in the course of time.
GUAN and D. Li use 92.35% as the plausible level for the Ming Empire (GUAN and Li,
2010, p.7). WU H. suggests that the proportion for the late Qing Empire should be below
85% (WU H., 1985, p.199). However, most studies apply a level of 90% for the early
Qing Empire (GUO, 1994; XU and WU, 2005; LIU T., 2009). We suppose that the eight
food crops in Table B.1 took up around 90% of the cultivated area in total. Based on this
assumption, we adjusted the proportions of the eight different food crops.
1.1.1.3 Relative proportions of different food crops
The two steps of our adjustments are documented in Table B.3. First, we take averages of
the three data sources from the 18th century to the 1930s, and apply these averages to the
period 1840-1912 (see Table B.3, column 1-3). Liu and Yeh also use the similar averages
in their estimation for 1933 (Liu and Yeh, 1965). For instance, the proportion of rice
cultivation was 29.7% in the 18th century, 29.3% in the 1910s, and 28.3% in the 1930s.
We apply their average of 29.1% in our calculation. Here, we assume that the proportions
did not change over time. In other words, we implicitly assume a fixed technology in the
use of the cultivated land during the period 1840-1912.
In a second step, we made adjustments for maize. We use the data collected by YAN
(1955), in which maize cultivation was 6% in the 1850s and 11% in the 1900s (YAN,
1955, p.359). We applied an average of 8.5% in our calculation.
Table B.3. The relative proportions of food crops used in previous studies and our
estimation, in %
LIU R., 1987 Perkins, 1969
1700-1800
1914-1918
29.7
29.3
18.9
24.5
11.34
4.2
11.7
9.9
9
8.5
3.6
5.58
1.8
1.8
3.96
11.5
90
95
Buck, 1930, 1937
the 1920s-1930s
28.3
16.3
9.4
4.7
4.4
3.7
2.4
3.7
72.9
Rice
Wheat
Millet
Kaoliang
Barley
Maize
Sweet potatoes
Other food crops
In total
Source: Collected by the authors.
a
For maize, we have followed the records in YAN (1955).
Our estimation
1840-1912
29.1
19.9
8.3
8.8
7.3
8.5a
2
6.4
90
1.1.1.4 The multiple cropping ratio
As mentioned in section 3.1.1, we apply a ratio of 1.32 in our estimation. Now we have
the amount of land input. Accordingly, we need to know the value of output per unit in
order to compute the gross value.
34
1.1.2. A calculation of the yield per unit (A)
A is the yield per unit measured in silver. For the ith food crop, we estimate A by equation
(1.3).
= × (1.3)
We will treat the two parts of the equation separately.
1.1.2.1. Yields per unit area
For rice, wheat, and corn, we backwardly project their unit yields in the 1930s to the late
Qing period, using the yearly harvest ratios (CHEN, 1996, p. 419). The harvest ratios
used in our estimation are mainly based on historical records of local reports about food
crop harvests. For instance, local magistrates reported to the emperor that the output of
wheat in a certain year was equivalent to 90 percent of a full harvest. Estimations of
historical weather conditions were applied in case of missing reports. We used official
statistical records for the unit yields in the 1930s (see Table B.4, column 3).
Next, the following two steps were taken in our calculation. First, for each food crop we
took the average between the maximum and the minimum among the previous
estimations (Table B.4, column 1-2). We use these averages as the yield estimates for the
period 1840-1912. In the second step we include sweet potatoes and other food crops. For
these two, we directly apply the estimations from WU H. (1985) and Liu R. (1987) (See
Table B.4, column 4).
Figure B.2. Unit yields of rice, wheat, and maize, in Jin per mou
300
200
100
Rice
Maize
Wheat
1840
1844
1848
1852
1856
1860
1864
1868
1872
1876
1880
1884
1888
1892
1896
1900
1904
1908
1912
0
Source: Calculated by the authors.
35
Table B.4. The yields per unit for different food crops and our estimation, in Jin per mou
The yield estimates
Official records
Our estimation
in the existing literature
(Republic China)
The 1700s-1930s
The 1930s
1840-1912
Minimum
Maximum
Averages
Rice
162
261
208
Wheat
114
160
139
Millet
159
180
168
170
Kaoliang
160
190
182
175
Barley
133
191
167
162
Maize
152
193
178
Sweet potatoes
185
263
242
250a
Other food crops
63
180
160a
Sources:
For rice, the minimum is from the estimation for the 1910s (Perkins, 1969); the maximum is from
the estimation for the 1880s (Buck, 1930 1937).
For wheat, the minimum is from the estimation for the 1920s-1930s (LIU K., 2001); the
maximum is from the estimation for the Qing China before 1840 (LIU T., 2009).
For millet, the minimum is from the estimation for the 1930s (Perkins, 1969); the maximum is
from the estimation for the 1880s (Chang, 1962).
For kaoliang, the minimum is from the estimation for the 1930s (Buck, 1930 1937); the maximum
is from the estimation for the 18th century (LIU R., 198715).
For barley, the minimum is from the estimation for the 1930s (Buck, 1930 1937); the maximum is
from the estimation for the 18th century (LIU R., 1987).
The official data in column 3 is from YAN (1955), Liu and Yeh (1965), Perkins (1969), and
ZHANG Y. (1990).
a
For these two items, we use the estimation in WU H. (1985) and Liu R. (1987).
1.1.2.2. Prices
There are also two steps in our reconstruction of price information. First, we collected
time series of rice prices. We use the price in Yangzi delta to represent the country level,
since it takes the middle position in the prices of rice in six different regions and it is
comparable to the country-level price given by PENG, 1957 (see Figure B.3.). Second,
using the price ratios between rice and other food crops (PENG, 1957; LIU T., 2009), we
obtain the price series for other food crops. For example, we have three ratios from
previous studies: for rice, 1 shi = 150 jin; for wheat, 1 shi = 142 jin; wheat price per shi =
0.8* rice price per shi.16 We calculated the price ratio between wheat and rice at 0.84517.
15
The yield estimates in LIU R., 1987, are based on Liu and Yeh, 1965.
Jin is a Chinese weight unit, 1 jin = 500 grams.
Shi refers to an ancient Chinese volume unit for measuring grains. For different crops, the weights for one shi are
different.
17
We calculate the price ratio between rice and wheat as follows.
!"#$ %&
!"#$ *+/-.+ !"#$ *+
!"#$ *+
-.+'()" *+
234
=
=
×
= 0.8 ×
= 0.845
16
'()" %&
'()" *+/-.+'()" *+
'()" *+
-.+
!"#$ *+
256
36
Here, we assume that the price ratio between rice and wheat is constant over time. Figure
B.4 approximately justifies our assumption. The price ratio between wheat and rice in the
province of Shandong remained approximately constant in the late 19th century.
Figure B.3 Regional rice prices, 1840-1915, in taels per shi
Sources: The price data for Yangzi Delta is from Wang (1992), Table 1.1. The price data for other
provinces is from “Grain Price Table Between 1821 and 1912”18 and the Qing-era Grain Price
Database19. Ten-year averages are from PENG (1957), p. 459.
Figure B.4 Rice and wheat prices, Shandong Province, 1840-1911, monthly, in taels per shi
Sources: The price data is from “Grain Price Table Between 1821 and 1912”.
1.1.3. Calculating the input/output ratio
To derive value added in food production, we need an input/output ratio. Table B.5
contains several estimates used in previous studies. As explained in section 3.4, we apply
18
19
We are grateful to Bas van Leeuwen (Utrecht University) for kindly providing the price data.
http://140.109.152.38/
37
the ratio used by LIU T. (2009), 0.096.
Table B.5. The input/output ratios used in previous studies
Ou, 1947
Buck, 1930, 1937 LIU R., 1987
The 1930s
0.14
The 1920s-1930s
0.1
1700-1800
0.1
LIU T., 2009
1600-1840
0.096
Broadberry et al.,
2013
1640-1840
0.18
Source: Collected by the authors.
1.2 Non-food but land-intensive crops
The rest of the cultivated area was left for non-food crop production. As classified in
Table B.1, they are also land-intensive. In general, our method is as follows: first, we take
the most important crops and estimate their value; second, we estimate the relative
proportion of those selected crops in the entire group. We calculated these food items
from the consumption side, so we had to add exports and subtract imports.
We pick two items to simplify our calculation: cotton and raw silk. These two products
were respectively the main import and export goods for Qing China in the late 19th
century. The import of cotton and cotton goods took over 30 percent of total imports value
in the 1870s and 1880s. In the same period, the export of silk product amounted to around
25 percent of total exports (YAN, 1955, p. 76; XU and WU, 2005, p. 84). In 1913, the
import ratio of cotton and cotton goods was 32 percent, and the export ratio of silk
product was 25.3 percent (XU and WU, 2005, p. 722).
By studying the two products, we can cover a major part of the crop production in this
group. The price, domestic sale, and foreign trade data for the two products can be found
in YAN (1955), YAO (1962), Hsiao (1974), and XU and WU (2005). We interpolate
missing-data points.
Previous studies give us clues about the value proportion of the two products in this
category. The number was 26.8% in the 1910s (XU and WU, 2005, p.1098) and 21.4% in
the 1930s (Perkins and Zhao, 1975, p.385). The proportion of cotton and raw silk was
over 30% in the early Qing Empire (LIU T., 2009, p.147). We apply the average of the
1910s and the1930s, 24.1%, in our calculations. Using equation (1.4), we estimate the
value added for this category of agricultural product.
Value of Non-food but land-intensive crops
= (
::& + <-*=> )/24.1%
(1.4)
1.3 Remaining non-food crops
The rest of the non-food crop production was less intensive in land use. Applying the
same method as in the previous section, we take tea as the most important product. The
proportion of tea export in total exports was around 50% in the 1880s (YAN, 1955, p.76).
38
Even though its export proportion had decreased since the 1870s, tea was still the most
important export good for Qing China (XU and WU, 2005). The price and output (exports
and domestic sales) data can be found in YAN (1955), YAO (1962), Hsiao (1974), and
XU and WU (2005).
In previous sections, we have obtained the value of food crops, non-food but
land-intensive crops, and tea. By adding up the three categories, we have the main
agricultural products for per-modern China, defined by Ou (1947) and XU and WU
(2005). The ratio of the remaining agricultural non-food products to the main agricultural
products was 10.09% in the 1930s, estimated by XU and WU (2005, p.1099). Based on
this ratio and equation (1.5), we estimate the value added for this category of agricultural
product.
Value of the remaining non-food products
= C
D::E:* + &:&FD::EGH=<&EF&&*I:* + < J × 10.09%
+
<
(1.5)
1.4 Other agricultural production
Finally, we add other agricultural activities into the previous estimation, such as cattle
farming, fishery, and forestry. Based on Table B.6, we believe that they accounted for
about 12% of the value added in food crop production in the late Qing Empire as shown in
equation (1.6).
Value of other agricultural products= D::E:* × 12%
(1.6)
By adding up the four categories, value added in the agricultural sector was 4.13 billion
taels of silver in 1840; 11.34 billion taels of silver in 1912. Figure B.5 shows per capita
estimates in current prices.
Table B.6. The value of other agricultural production
LIU R., 1987
LIU T., 2009
Perkins, 1969
Ou, 1947
1700-1800
12%a
1640-1840
10%a
1910s
11%b
1930s
18.13%a
Broadberry et al.,
2013
Early Qing
12%b
Source: See the references, collected by the authors.
a
These ratios are relative to the main agricultural products which include food crops, non-food but
land-intensive crops, and tea.
b
These ratios are relative to food crops.
39
Figure B.5 Value added in the agricultural sector, per capita, 1840-1912 (in tael)
Source: Estimated by the authors.
2. The proto-industrial sector
The first step in our estimation is to separate factory production from handcraft
workshops. We do this for three benchmark years, 1840, 1885, and 1920 (see Tables B.7
and B.9). The total output values are respectively: 2254 million tael in 1840 (LIU T.,
2009); 485 million tael in 1885 (Chang, 1962); and 4029 million tael in 1920 (XU and
WU, 2005).
In fact, we only need to split the estimate for 1885 (Chang, 1962). XU and WU (2005)
already provide the value for the two types of production in 1920. There is no need to split
the estimate for 1840 as we assume that all industrial production was traditional by
nature; foreign technology entered China only after the 1860s. Chang (1962) does not
distinguish between the two types of production in his estimation for the 1880s.
Our separation for the 1885 estimate is based on the descriptive documents in XU and
WU (2005). After these adjustments, we obtain a new benchmark estimate for factory
production: 26.1 million tael in 1885.
40
Table B.7. Factory and handcraft workshop production in 1885 and 1920, in million tael
Total value of the industrial production in 1885
Factory
Handcraft workshop
Total
Manufacturing
Mining and manufacture of
basic metals
22
302
323.86
1.55
126.40
127.94
Transportation
2.00
30.00
32.00
Communication
0.77
0.00
0.77
Total
26.10
458.48
484.57
Proportion
5.39%
94.61%
100.00%
Factory
Handcraft workshop
Total
Manufacturing
Mining and manufacture of
basic metals
588.58
2840.39
3428.97
70.44
123.23
193.67
Transportation
189.18
199.51
388.69
Communication
15.86
1.70
17.56
Total
864.06
3164.82
4028.88
Total value of the industrial production in 1920
Proportion
21.45%
78.55%
100.00%
Source: Part A is mainly from Chang, 1962. Since it does not directly provide the value of the
two types of production, we make the separation here and list the value of the new production
according to XU and WU, 2005. Part B is from XU and WU, 2005, p.1051.
1 tael of silver=1.5 Chinese yuan in the 1930s.
2.1 The total value of factory production during the period 1885-1920
Our estimation of the growth rates applies growth accounting techniques, but is limited to
one sector. We make the following assumptions. Equation (2.1) is the assumed production
function with the property of constant returns to scale,
Valuet = Pt × Yt = Pt × AKtα Lt1−α
(2.1)
, where Value is the total value of the factory output; P is the general industrial price level;
Y is the factory output level; K is fixed capital input; L is labor input in factory production.
The parameters, α and A, are assumed to be constant for the period concerned.
We describe the data used in this section as follows. The dataset of the annual industrial
price levels during 1885-1920, i.e. { Pt } , ∀t = 1885, ......, 1920 , is from WANG Y., 2005,
p.471, Table.6. We have four data points of capital input and three data points of labor
input as listed in Table B.8. To deal with missing data, we use the initial capital inputs of
the new factories established annually as the increments (YAN, 1955, p.94). By
41
connecting the four points in Table.B.8, line 1, we get a rather smooth line of capital
inputs during 1885-1920 (see Figure 2.4). To obtain annual labor input, we assume that
the proportion of factory labor to the total population moved steadily over time. Then, we
construct the time series of capital and labor inputs during 1885-1920, i.e.
{K t , Lt } , ∀t = 1885,
......, 1920 .
Table B.8. Capital and labor input in factory production, 1885-1920
1885
1894
1913
1920
Capital input (in million yuan) (K)
29.64
121.55
1786.73
2579.29
Labor input (L)
90,140
693,890
413,040
Proportion of the population
0.02%
0.16%
0.09%
Source: Capital data are from XU and WU, 2005, p.379 and p.1046. Labor data for 1885 are
from XU and WU, 2005, p.379; for the period 1912-1920, data are from Lieu, 1936, p. 91.
Population data are from Maddison, 2010.
Next, we turn to the unknown parameters in equation (2.1), α and A. Because A is a
constant in our assumptions, it disappears from the growth rates according to equation
(2.1). We try to find the proper α for the period concerned, given the information from the
two point estimates of factory production in Table B.7. Rearranging equation (2.1) with
the year 1920 as the base year, we have equation (2.2).
ln
Value1885
P
K
L
= ln 1885 + α ln 1885 + (1 − α ) ln 1885
Value1920
P1920
K 1920
L1920
(2.2)
Using the data from Table B.7, column 1 and Table B.8, column 1 and 4, we derive the
parameter α by equation (2.2), which equals 0.48.
We obtain equation (2.3) by putting the parameter α into equation (2.2). Then, we
calculate the annual growth rates during 1885-1920, denoted by g.
gt = ln
Valuet
P
K
L
= ln t + 0.48*ln t + (1 − 0.48)*ln t
Value1920
P1920
K1920
L1920
, where { Pt , Kt , Lt } , ∀t = 1885, ......, 1920
(2.3)
By equation (2.3), we construct the time series of the total value of the factory production
during the period 1885-1920, i.e. {Valuet } , ∀t = 1885, ......, 1920 . Figure B.6 shows our
results in current prices.
42
Figure B.6. Total value of factory production, 1885-1920, in million tael
1000
800
600
400
200
0
58
81
09
81
59
81
00
91
50
91
0
1
9
1
5
1
9
1
0
2
9
1
Source: Constructed by the authors.
2.2 Total value of handcraft production during the period 1840-1920
Starting from the three benchmark estimates in Table B.10, line 2, we assume that the per
capita value in traditional workshops moved steadily during 1840-1920. With the
estimated traditional output per capita and population data, we can derive a time series of
the total value of traditional production during the period concerned.
2.3 The proportion of net value
Ou (1947) shows that in 1933 the net value proportion for mining and metal manufacture
was around 50%; for textile manufacturing it was around 29%-30%; for ceramics
manufacturing it was 60%. In general, we take 40% for the industry to calculate value
added. Later improvements are necessary because the choice of the ratio here is a rough
average and takes no account of shifts in the structure of output. Finally, we have a time
series of value added in the proto industrial sector, from 0.9 billion taels of silver in 1840
to 1.2 billion tael of silver in 1912. Figure B.7 shows per capita estimates in current
prices.
Table B.9. Total value of traditional production, 1840-1920
LIU T., 2009
Chang, 1962
XU and WU, 2005
1840
1885
1920
Total value
20
2250
458.48
3164.82
(in million tael)
Per capita levels
5.46
1.23
6.71
(in tael)
Source: Collected by the authors. Population data is from Maddison, 2010.
20
LIU T. (2009) gives the net value directly, i.e. 900 million tael. We use the net value ratio, 40%, to obtain the total
value.
43
Figure B.7. Value added in the proto industrial sector, per capita, 1840-1912 (in tael)
30
25
20
15
10
5
1840
1845
1850
1855
1860
1865
1870
1875
1880
1885
1890
1895
1900
1905
1910
0
Source: Estimated by the authors. We keep the same scale as used in the figure of the agricultural
sector, Figure B.5.
3. The service sector
In this sector, we include four economic activities: public administration, finance and
housing, professional work, and commercial activities.
3.1 Public administration
Here, we mainly have to deal with the missing data problem in the archival data from SHI
(2009, p.222-253). In general, we put the average for an emperor period into the missing
data points in between the specific period ruled by the emperor. For the missing data
during 1821-1850, we impute the average expenditure under the Daoguang Emperor
(1821-1850), which was 11 million tael. Figure B.8 shows the archival records and the
estimates after an interpolation for central government expenditure. Using the proportion
of central government expenditure in the total government expenditure, we obtain the
value for this subsector (See section 3.3.1).
3.2 Finance, housing, and other professional work
We calculate the value of the early financial sector based on the three benchmark
estimates in Table B.10, including real estate and renting. For simplicity, we assume
constant annual growth rates for per capita values in this subsector during 1840-1933.
With the population data, we derive a time series of the net value. The same assumption
and method is applied to estimate the value created from professional work based on
Table B.11.
3.3 Commercial activities
For commercial activities, we refer to wholesale and retail trade. We use a ratio to derive
44
the value added in this subsector. In Chang’s estimation, the commercial/non-commercial
ratio was 0.086 in the 1880s (Chang, 1962); in Maddison’s estimation, it was 9.7% in
1890 (Maddison, 2007, p.254); in Ou’s estimation, it was 10.7% in 1933 (Ou, 1947,
p.12); for Liu and Yeh, it was 10.4% in 1933 (Liu and Yeh, 1965, p.66). Based on their
estimates, we suppose that the ratio was around 9% during 1840-1912. For
non-commercial activities, we refer to the agricultural and industrial production.
Equation (3.1) is used to calculate the value of this subsector.
Value of commercial activities = (
<.H=H + &EH*L ) × 9%
(3.1)
Adding up the four subsectors, we get the value added levels in the service sector: 0.97
billion tael of silver in 1840 and 2.06 billion taels of silver in 1912. Figure B.9 shows per
capita estimates in current prices.
Figure B.8. Central government expenditure, 1840-1912, in million tael
Source: Constructed by the authors.
Table B.10. The net value in the financial and housing sector, 1840-1933
LIU T., 2009
Chang, 1962
Liu and Yeh, 1965
1840
1880s
1933
Net value (in million Tael)
320
238.6
826.7
Per capita levels (in Tael)
0.78
0.64
1.65
Source: Collected by the authors. Population data are from Maddison, 2010.
Table B.11. The value added from professional work, 1840-1933
LIU T., 2009
Chang, 1962
Liu and Yeh, 1965
1840
1880s
1933
Net value (in million Tael)
115
241.3
226.7
Per capita levels (in Tael)
0.279
0.645
0.453
Source: Collected by the authors. Population data are from Maddison, 2010. LIU T.’s estimation
for professional work follows Chang’s estimation. Liu and Yeh’s estimation for the value from
personal services is cited in the above table.
45
Figure B.9. Value added in the service sector, per capita, 1840-1912 (in tael)
30
25
20
15
10
5
1840
1845
1850
1855
1860
1865
1870
1875
1880
1885
1890
1895
1900
1905
1910
0
Source: Estimated by the authors. We keep the same scale as used in the figure of the agricultural
sector, Figure B.5.
4. Nominal and real per capita GDP in the Chinese economy 1840-1912
By adding up the above estimates for the three sectors, we obtain a new estimation of
nominal GDP. With the population data from Maddison’s research and the estimated GDP
deflator from section 3.4 in our paper, we calculate real per capita GDP. We present our
estimation of nominal and real GDP in Table B. 12.
Table B.12. Nominal and real GDP per capita for Qing China, 1840-1912, in tael. Real GDP/cap
in prices of 1840
Per capita
GDP
Value added per capita
Agricultural
Proto industrial
sector
sector
GDP
deflator
Per capita
GDP
Service
sector
1840
1841
1842
current prices
14.57
15.51
15.43
current prices
10.03
10.84
10.84
current prices
2.18
2.15
2.11
current prices
2.35
2.52
2.48
1.00
1.02
1.01
1840 prices
14.57
15.24
15.26
1843
1844
1845
1846
13.68
13.84
13.33
11.88
9.31
9.52
9.09
7.75
2.07
2.03
2.00
1.96
2.30
2.28
2.24
2.17
0.93
0.96
0.92
0.82
14.76
14.38
14.47
14.47
1847
1848
1849
1850
12.14
12.38
13.32
14.04
8.07
8.28
9.20
9.89
1.92
1.88
1.85
1.81
2.15
2.22
2.27
2.34
0.83
0.84
0.91
0.97
14.56
14.69
14.65
14.54
46
1851
12.99
9.03
1.77
2.19
0.90
14.39
1852
1853
1854
1855
1856
1857
1858
1859
1860
1861
1862
1863
1864
1865
1866
1867
1868
1869
1870
1871
1872
1873
1874
1875
1876
1877
1878
1879
9.46
9.56
9.51
9.82
10.21
15.36
16.38
14.24
11.29
17.36
23.09
21.87
22.49
17.20
18.29
14.93
13.07
13.71
14.33
13.27
12.82
12.10
11.48
10.86
11.29
12.16
14.44
12.54
5.75
5.90
5.95
6.30
6.69
11.40
12.41
10.47
7.73
13.34
18.59
17.53
18.10
13.29
14.32
11.24
9.58
10.16
10.80
9.87
9.49
8.86
8.33
7.70
8.12
8.96
11.08
9.43
1.73
1.70
1.66
1.62
1.58
1.54
1.51
1.47
1.43
1.39
1.36
1.32
1.28
1.24
1.21
1.17
1.13
1.09
1.06
1.02
0.98
0.94
0.90
0.87
0.83
0.79
0.75
0.72
1.98
1.97
1.91
1.91
1.93
2.42
2.46
2.30
2.13
2.62
3.15
3.02
3.11
2.67
2.76
2.53
2.35
2.46
2.47
2.38
2.35
2.30
2.25
2.30
2.34
2.41
2.61
2.39
0.63
0.64
0.65
0.68
0.68
1.04
1.08
0.96
0.75
1.13
1.46
1.36
1.39
1.10
1.14
0.93
0.80
0.85
0.89
0.83
0.80
0.78
0.78
0.72
0.72
0.83
0.97
0.83
15.01
14.92
14.62
14.51
14.93
14.73
15.17
14.84
15.07
15.39
15.82
16.13
16.17
15.70
16.00
16.00
16.38
16.20
16.17
15.95
16.04
15.54
14.71
15.09
15.60
14.72
14.91
15.15
1880
1881
1882
1883
10.86
9.99
11.48
12.34
7.86
7.10
8.50
9.32
0.68
0.64
0.60
0.57
2.32
2.25
2.38
2.45
0.73
0.67
0.78
0.84
14.92
14.85
14.73
14.76
1884
1885
1886
1887
1888
1889
1890
1891
11.57
11.09
12.90
12.78
11.93
12.90
13.80
12.96
8.65
8.22
9.79
9.59
8.72
9.53
10.26
9.34
0.53
0.52
0.59
0.66
0.73
0.81
0.89
0.96
2.39
2.36
2.52
2.53
2.47
2.57
2.65
2.66
0.81
0.78
0.92
0.93
0.86
0.92
1.02
0.95
14.35
14.30
14.08
13.80
13.87
14.02
13.47
13.68
1892
1893
1894
13.49
13.86
13.77
9.82
10.05
9.80
1.02
1.10
1.17
2.66
2.70
2.80
1.00
1.03
1.03
13.44
13.51
13.36
47
1895
14.79
10.58
1.24
2.97
1.07
13.78
1896
1897
1898
1899
1900
1901
1902
1903
1904
1905
1906
1907
1908
1909
1910
1911
1912
average
max
min
15.31
15.23
18.77
17.50
17.60
17.00
21.66
21.54
21.85
17.56
19.56
23.80
24.92
21.98
25.49
35.39
33.75
15.42
35.39
9.46
10.98
10.81
13.88
12.67
12.64
12.01
16.14
15.91
16.10
12.06
13.78
17.54
18.47
15.69
18.83
27.80
26.24
11.26
27.80
5.75
1.31
1.41
1.50
1.61
1.69
1.76
1.89
1.99
2.08
2.17
2.27
2.39
2.47
2.53
2.61
2.71
2.75
1.45
2.75
0.52
3.02
3.01
3.38
3.22
3.27
3.23
3.63
3.63
3.67
3.33
3.51
3.87
3.98
3.75
4.05
4.88
4.76
2.71
4.88
1.91
1.17
1.15
1.46
1.35
1.34
1.30
1.60
1.60
1.60
1.40
1.49
1.77
1.80
1.57
1.76
2.46
2.45
13.12
13.25
12.83
12.92
13.09
13.08
13.51
13.42
13.70
12.53
13.14
13.42
13.83
13.99
14.49
14.41
13.78
14.53
16.38
12.53
Source: Constructed by the authors.
48
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