Minding the Gap:
Language Standardization and the Great Divergence
Leonard Dudley, Sciences économiques, Université de Montréal
[email protected]
24 June 2015
Abstract
Why did China and the West switch roles in the development of new technologies
after 1600? Current explanations fail to make clear why innovation in the West was
confined to only a few regions while virtually no innovation occurred in comparable
areas of China. A missing consideration, this paper argues, is language standardization in
the West versus linguistic drift in China. As the complexity of new technologies rose,
cooperation of individuals with different skill sets became increasingly necessary. Until
1850, only Britain, northern France and the USA possessed large networks of people able
to communicate easily with one another. In China, standardization of the vernacular
awaited the revolutions of the twentieth century.
Key Words: innovation, cooperation, language, Europe, China
Paper to be presented at the Third Annual Symposium on Quantitative History, Beijing,
July 16-17, 2015
2
In the year 1600, China and the West resembled two ships passing in the night. China
was tacking slowly into port, its great inventions of the preceding millennia well behind
it. Europe, in contrast, was outward bound, soon to experience the storm of creative
destruction known as the Industrial Revolution. During the Middle Ages, Europeans had
invented few important technologies themselves, instead borrowing or rediscovering
Chinese inventions such as paper, the compass, gunpowder, cast iron and printing with
movable type (Mokyr 1990, 215-218). Then after 1700, several regions of the West
began to develop new technologies at a rate that was without precedent in world history.
Since in the meantime technological innovation had virtually ceased in China (Needham,
1969, 11), the result was a widening technological gap between East and West.
How might this astonishing role change be explained? Imagine ourselves at the
tipping point, sometime around the year 1600. At that moment, there were few incentives
to develop new techniques, either in Europe or in China. For example, an important
consideration was property rights. Although in both England and France there existed a
tradition for the sovereign to present requests for extraordinary taxation to representative
assemblies, there was no requirement that these bodies be convened regularly. Moreover,
there or elsewhere in the West, there was little to prevent the sovereign from
reinterpreting his or her customary rights so as to increase taxes arbitrarily without
legislative approval. In China, it was the arbitrary nature of taxation at the local level that
caused considerable uncertainty for property owners (Brandt et al., 2014, 75)
As for factor prices, in Europe the traditional sources of energy – wood, water power,
and animal and human effort – were still sufficiently inexpensive to be used efficiently in
manufacturing. The situation in China was comparable. Although the Chinese had been
smelting iron with coal since the mid-Tang dynasty, this production dropped off after the
Mongol invasions, though perhaps not as sharply as Hartwell (1967, 109, 145) described.
Similarly, neither society had a relative abundance of human capital. In England, male
literacy stood around 30 percent but female literacy was under ten percent (Cressy, 1980,
177). Literacy rates were somewhat higher in Germany but lower in France (Graff, 1991).
In China, the male literacy rate for a base level of say 400 characters of script was
3
probably higher than that in northern Europe, although relatively few Chinese women
were literate (Rawski, 1979, 3) (Baten et al., 2010, 353).
Previous studies have argued that in the West over the course of the seventeenth
century, each of these dimensions was transformed in a manner favorable to innovation,
while in China the situation at best remained unchanged. For example, in the case of
institutions, North and Weingast (1989) observed that the English Glorious Revolution of
1688 led to a series of reforms to protect property rights and the enforcement of contracts.
A complementary argument proposed by Mokyr (2002, 2009) and Mokyr and Voth
(2009) is that from the mid-eighteenth century, the European Enlightenment with its
emphasis on “useful knowledge” encouraged the application of mathematics and science
to satisfy social needs. Other hypotheses stressing the supply side of innovation are the
emphasis on Britain’s individualism, a result of culture for Landes (1998, 219) or of
genetics for Clark (2007, 188). In China, in contrast, Needham (1969, 327-328) argued, a
world-view incompatible with the precise study of the laws of nature limited the
application of scientific knowledge to production technologies. Also, under the Ming and
Qing, successive imperial governments struggled to provide public services because of a
declining revenue base (Brandt at al., 2014, 58).
With regard to factor prices, Pomeranz (2000, 62-63) suggested that Europe’s
advantage over China in access to inexpensive coal created a demand in the West for
energy-using technologies. Similarly, Allen (2009a, 34, 97) argued that in Britain, high
wage rates and cheap coal provided an incentive to devise production processes that
substituted inexpensive machinery and coal-based energy for labor and wood-based
energy. For Rosenthal and Wong (2011), QQ China’s lower wage rates were a result of
China’s lower degree of urbanization, itself a consequence of that civilization’s greater
internal peace compared to Europe. Finally, few would disagree with the position
advanced by Galor et al. (2009) that the formation of human capital has been a key to
economic development. Accordingly, advances in basic education to raise literacy rates
are part of the explanation of the West’s success.
4
There is a fundamental problem, however, with these explanations of the East-West
innovation gap that rely on differences at the level of societies as a whole. The difficulty
is that even in the innovating countries of the West, innovation tended to be confined to a
small number of regions. Some three-quarters of the important innovations cited by
historians of technology were developed in three narrow bands of territory containing the
main cultural centers of Britain, France and the USA. Other regions in the West with
similar institutions and factor prices, or higher levels of literacy failed to innovate during
the century and a half prior to 1850 (Mokyr, 2009, 239).
This paper argues that an important element is missing from previous explanations of
the Great Divergence. In both Western Europe and China in the year 1600, people from
different regions had trouble understanding one another. Recent studies of the mutual
intelligibility of dialects in both Scandinavia and China give us some idea of the
difficulties in communication when strangers from different regions met each other
(Gooskens, 2008) (Tang and van Heuven, 2009). Because of the growing complexity of
industrial technologies, innovation increasingly required the cooperation of individuals
with different skill sets. Yet if intelligibility was sufficiently low to inhibit collaboration
except with neighbors or family members, it was unlikely the required blending could
occur.
In the second half of the seventeenth century, these intelligibility barriers began to
break down in the West. Thanks to the efforts of printers, the initial signs of language
standardization at the national level appeared in the principal cultural centers of the West.
In England and France, the first monolingual dictionaries that were more than mere lists
of hard words to spell were published in 1658 and 1680 respectively. The early English
dictionaries were subsequently exported to America. It took another century or more
before equivalent dictionaries were published for the other languages of northern Europe.
It is worth noting that the first phase of Prussian industrialization described by Becker et
al. (2011) occurred only in the 1830s – roughly a half century after the publication of the
first monolingual German dictionary (in 1786). However, the first Chinese vernacular
dictionary with pronunciation appeared only in 1932.
5
Did language standardization in the West lead to more innovation, and if so, why? To
answer this question, Section 1 below describes an original data base of 117 important
innovations between 1700 and 1850, distinguishing between cooperative and noncooperative innovations. Section 2 presents a model of selective cooperation to explain
the creation of new technologies is then proposed. An empirical version permits
comparison of the institutional, factor-prices and human-capital approaches with the
language-standardization hypothesis. The innovation data are regressed on relative factor
prices, literacy and country fixed effects for 201 cities in Europe and North America.
Language standardization is measured by the date of the first monolingual dictionary.
Section 3 describes the results. For the West, coefficient estimates of the institutional
and factor-price approaches are somewhat fragile. However, with the inclusion of
measures of network size and degree of standardization, the models’ fit improves
considerably, especially for cooperative innovations. The estimated signs of the key
language-network variables are shown to be quite robust to changes in specification.
Section 4 discusses the pertinence of the supply and demand approaches for
explaining the decline in innovation in China after 1600. Initial levels of human capital
and relative energy prices do not seem to have differed greatly from those in England. As
for government policy, Lin (1995) argued that the imperial examination system diverted
China’s intelligentsia away from scientific pursuits toward literary endeavors. However,
Section 5 suggests that the problem may have been not too many but rather too few
people able to read and pronounce in standardized fashion the 3,000 to 4,000 Chinese
characters required to be considered literate. Moreover, increasing regional differences in
pronunciation of the koine or lingua franca, often led to problems of oral comprehension
among the elite (Rowe, 2009, 68).
The evidence presented here suggests that the dissemination of a standard vernacular
in the West during the eighteenth century greatly increased the probability of interactions
to create novelty. China would have to wait until the second half of the twentieth century
for similar conditions to favor innovation.
6
1. Two Classes of Western Innovations
At the heart of the Industrial Revolution in the West was an unprecedented outburst
of technological innovation. This section describes the data to be explained, namely, a set
of 117 important innovations in the West between 1700 and 1850.
Table 1 presents a summary of the principal innovations of the Industrial Revolution,
as identified by a panel of historians of technology. The authors in question were Donald
Cardwell (1991) of Britain, Maurice Daumas (1979) and his associates of France, Joel
Mokyr (1990) born in the Netherlands and living in the United States, and Akos Paulinyi
(1989), born in Hungary and residing in Germany. Of the total, 87 were mentioned by at
least two of these authors. The 30 others were noted by only one of them but were also
cited by the Encyclopedia Britannica.
To understand better the process of innovation, it is useful to divide these innovations
into two groups. A first group comprises 54 technologies that may be termed Cooperative
Innovations (CI). In each case, the available biographical information permits the
identification of both a principal and at least one unrelated collaborator who made a
significant contribution. From the biographies, there is an argument to be made that had
the other individual(s) not participated in the development of these cooperative
innovations, the technology would not have been successful. Sometimes the contribution
of the other person was technical, but at other times it was entrepreneurial or occasionally
financial. These CIs tended to be relatively complex, requiring the integration of distinct
areas of specialization. The nine technological breakthroughs in Table 1 that satisfy the
criterion of General Purpose Technologies as defined by Lipsey et al. (2005) were all
cooperative; namely, iron smelting with coke, the atmospheric engine, machine spinning
of short fibers, continuous-flow production, the production of sodium carbonate from
salt, machines tools for lock production, the automatic loom with perforated cards, the
steam locomotive, the electric telegraph, and the iron propeller-driven steamship.
The second category comprises innovations for which only a single inventor may be
identified; that is, the Non-Cooperative Innovations (NCIs). These inventions tended to
be relatively simple conceptually, remaining within the competence of a single
7
individual; for example, Kay’s flying shuttle, Lenormand’s parachute, and Perkins’s
machine to cut and head nails. Like the cooperative innovators, these independent
inventors depended on what Sunderland (2007, 166) described as “inter-businessman
trust” from networks of suppliers, employees and customers. That this trust was not
always forthcoming is shown by the difficulties of Kay, Hargreaves and Cartwright in
persuading users of their ideas to compensate them for their efforts.
One remarkable feature of Table 1 is that three present-day countries, namely,
Britain, France and the United States, developed 95 percent of the innovations studied.
Even more striking is that these three countries accounted for all of the CIs but only 90
percent of the NCIs. This result suggests that there may be some factor that is more
important for cooperating innovators than for independent inventors. Although the seed
drill, porcelain and the smelting of iron with coke had been developed previously in
China, almost all of the remaining innovations identified in Table 1 were unique to the
West. Moreover, neither China nor any other country developed any other industrial
technologies of similar importance during the century and a half under study.
We are left with the question: why were almost all of the key technologies of the
Industrial Revolution – breakthroughs that were both technologically unprecedented and
capable of multiple downstream applications – developed in the West rather than in
China? Might the explanation lie in the fact that the development of these techniques
required cooperation between strangers? If collaboration between unrelated individuals
was a necessary ingredient for the most important innovations of the Industrial
Revolution, we must then ask what conditions favored such cooperation.
8
2. Cooperating to Innovate
One of the first great inventions of the Industrial Revolution was the atmospheric
steam engine, developed around 1712 by Thomas Newcomen and John Calley (see Table
1). The fact that both men were educated Baptists from the same town in Devon suggests
that to invent such a complicated device, it was essential that the collaborators be able to
communicate easily in both written and spoken form. By the second half of the
eighteenth century, the standardization of English had proceeded sufficiently for James
Watt, a Scott, and Matthew Boulton, from the English Midlands, to collaborate
successfully in a famous series of improvements to the initial steam technology.
Milroy (1994, 20) identified two phases in this standardization of the English
language. Between 1400 and about 1650, there was an initial period of spontaneous
convergence toward a consensus of primarily phonetic norms at the regional level as
people from different communities interacted. Then for the following century and a half,
from about 1650 to 1800, language norms were imposed from above through the
publication of written standards in the form of dictionaries and grammar texts printed in
the capital. As a result, the variety used by a prestige group within London society
gradually became the norm for written communication. Standardization of the spoken
language followed, although important regional differences in pronunciation persisted
until the late nineteenth century (Stein, 1994, 4-6). In China, as we shall see, the second
of these steps did not begin until the twentieth century.
Let us try to formalize a possible link between language standardization and
innovation. Assume that there are two cities, with populations
and
respectively.
Initially their dialects are sufficiently different to prevent cooperation between their
residents. Now let a standardized language be introduced into their populations. The
number of new pairings, x, made up of one resident from each city made possible by this
development is given by:
.
9
If the proportion π of these potential partnerships leads to a successful innovation, the
total number of innovations, y, is:
y
.
Of course, not all of these innovations need take place in city 1. More realistically, we
assume that there may be congestion, represented by the parameters
and , when the
individuals from city 2 try to find partners in the city 1. Moreover, because of transaction
costs, the probability of a successful pairing will be a decreasing function of the distance,
d, between the two cities. The expected number of innovations in city 1 may then be
expressed as:
,
Take logs, we have:
or
, where
.
(1)
Equation (1) expresses the number of innovations produced after the introduction of a
standardized language as a Poisson distribution that has as explanatory variables the
logarithms of the population of two cities and the distance between them – in effect, a
gravity model of innovation.
Consider now how to integrate the supply and demand forces examined in previous
studies into the networking model of equation (1). Let us look first at the dependent
variable. Allen (1983), followed by Nuvolari (2004), noted that innovations within a
given country tended not to be spread evenly across its territory but rather clustered
around a few centers. This finding suggests that the unit of observation should be a region
within a state. Accordingly, we use count data that measure the number of innovations
that occurred in each of 201 urban regions in Western Europe and North America during
each fifty-year interval between 1700 and 1849.
10
If we could assume the probability of an innovation in the region of a given city to be
independent of the number of innovations near other cities in the same period, we could
use a Poisson distribution. However, a comparison of the variance of the dependent
variable (0.182) with its mean (0.065) suggests that zero observations are overrepresented. To allow for such over-dispersion, it is appropriate to use a variant of the
Poisson, the negative binomial specification:
y = exp (Xβ + ε + u),
(2)
where yijt is the number of innovations in city i of type j in period t, xijt is a vector of
explanatory variables, β is a vector of parameters,
is a random variable and exp (
)
follows a gamma distribution with parameters α and 1/α.
Consider next some possible explanatory variables. It is not obvious how to measure
the variables suggested in the various “supply-side” arguments. The degree of protection
of property rights, the degree of practicality of the society’s ideology and the importance
of individualism are all difficult to measure. Since the goal of this study is not to estimate
the effects of each of these influences but rather to correct for their impact on the
estimates of social-networking variables, it will be assumed that most such influences are
absorbed by the fixed-effects variables for Britain, France, Germany, Belgium, the
Netherlands, 1750 and 1800.
A second group of variables picks up the influence of demand conditions. Data for
eight urban regions and three periods permitted estimation of the following equation:
Energy price/Wage rate = 1.037 - 0.353*Coal – 0.472*Britain + 0.498*France
(0.054) (0.096)
(0.056)
(0.075)
- 0.172*1800, R2 = 0.917, Root MSE = 0.1683.
(0.067)
(3)
The figures in brackets are robust standard errors. Regions close to coal deposits could be
expected to have lower energy prices. There were important labor productivity
differences between England and France, and in 1800, real wages were generally higher
than over the previous century across northern Europe.
11
From the estimated coefficients and root MSE, values for the 579 missing observations of
Relative energy prices were then imputed by the stochastic-regression method.
As mentioned earlier, Galor st al. (2009) suggested that a greater stock of human
capital would stimulate innovation. The Literacy rate is an approximate measure of the
abundance of this factor. Estimates of signature rates of marrying couples at the regional
level are available for 281 of the 603 observations in the data set. With these data, it was
possible to estimate the following regression:
Literacy = 41.14 + 11.96*1800 – 7.50*Catholic + 20.61*Dissent
(1.400) (2.985)
(3.414)
(2.050)
+ 0.0086*DistRome - 0.0370*DistMainz + 18.57*Male – 4.41*Rural,
(0.00073)
(0.00262)
(0.899)
(1.233)
R2=0.842, Root MSE = 10.20,
(4)
where Dissent indicates a religion other than Catholic, Lutheran or Anglican, DistRome is
the distance from Rome in kilometers, DistMainz is the distance from Mainz, and Male
and Rural indicate that the measure applies to males or rural residents respectively. As
Cipolla (1969, 72-73) observed, other things being equal, Catholics tended to have lower
literacy rates while members of Dissenting religions had higher rates. Among Catholic
areas, those more distant from Rome, such as the Rhineland, had higher literacy.
Moreover since the printing press lowered the cost of reading matter, literacy would have
tended to increase with the diffusion of this invention outward from Mainz (Cipolla,
1969, 50). Finally, men tended to be more literate than women and urban residents more
so than those in the countryside (Cipolla, 1969, 75, 85). The missing observations were
again imputed by the stochastic-regression method. Finally whatever the model chosen it
is necessary to make an allowance adjustment for the scale of the region of observation,
expressed here by the log of the population of its main center, City population.
Now consider the determinants of the effectiveness of a language network in
encouraging innovation, as suggested by the model of equation (1). In addition to the
variable just mentioned, the log of the population of the rest of the society, Country
12
population, could also be expected to play a role. For most cities in the sample, the latter
variable was assumed to be captured by the population within the boundaries of the
corresponding present-day state (less that of the city in question). The United States was
an exception. At the beginning of the first two sub-periods, the thirteen colonies were a
part of the British Empire. Even after the American War of Independence, the two
countries remained important trading partners. At the end of the eighteenth century, over
half of British exports and a third of its imports were with the Americas, including a
small portion with British North America (Deane and Cole, 1962, 62). Accordingly,
Great Britain and the United States were assumed to form a single market.
A second possible networking variable is the degree of the country’s language. For
example, if Watt had been raised in the Scottish Highlands, it is unlikely that he would
have been able to speak and write Standard English in 1764. However, growing up in the
Lowlands, he had been exposed to the Anglicization of the Scottish school system that
had begun with the Schools Act of 1696. This legislation had provided for a school in
every Scottish parish that would teach reading and writing in Standard English (Herman,
2001, 22). Accordingly, a measure of standardization is Dictionary year, defined as the
year of publication of the country’s first monolingual dictionary (normalized with Britain
in 1658 equal to zero), as shown in Table 2 – a measure of the time at which a
standardized version of the vernacular language first appeared.
It remains for us to estimate the model of equation (2) for the West and to determine
whether the resulting estimates help explain the Great Divergence.
13
3. Results for the West
In Section 1, it was suggested that in the West, the relatively-complex innovations
which had two or more inventors may have been produced differently from the simpler
ones with a single inventor. This section compares the estimates of equation (2) these two
types of innovation.
Table 3 presents the results for the 54 Cooperative Innovations (CIs). In column (1) is
a specification capturing conventional supply and demand considerations. Assessing the
country fixed effects, we see that Britain and France were significantly more likely to
innovate than other Continental countries. On the demand side, we note that Relative
energy price and Literacy are also significant.
This pattern of results changes in column (2), when variables representing two
dimensions of language networks; namely, size and degree of standardization, are
inserted into the specification. Both Country population and Dictionary year are
significantly different from zero. The coefficient estimates suggest that Britain and
France were significantly more innovative than other Continental countries, and that the
Relative energy price was an important determinant of cooperative innovation. However,
the direct impact of Literacy is no longer statistically significant. Instead, the
considerable improvement in fit suggests that rising literacy rates are important primarily
indirectly, as a facilitator of language standardization which in turn favors cooperation.
These results help explain why between 1700 and 1850 Britain, France and the USA
accounted for all of the cooperative innovations.
Turn now to the non-cooperative innovations (those with a single inventor). We see in
column (3) that Britain and France again perform significantly better than Belgium and
the Netherlands, although the gap with respect to Germany is no longer significant. This
last result should not surprise us since Germany did have two non-cooperative
innovations. Relative factor prices are no longer important, but in this initial specification
Literacy is significant, as is the Enlightenment variable, 1750.
14
In column (4) the two language-network variables are added to the equation. The
country dummies and the Enlightenment variable are little changed. We find that
Dictionary year, the measure of language standardization, is significantly different from
zero but also significantly less in absolute value than in equation (3). Yet the inclusion of
this variable still knocks out Literacy. However, Country population, the measure of
network size, is no longer significant.
How might these last results be explained? Some minimal level of regional linguistic
standardization appears to have been required even for non-cooperative innovations.
Their creators had to be able to write and apply contracts with their employees, suppliers
and customers. To do so did not always require that the innovators have access to the
wide range of skills that only a large nation could supply. Nevertheless Britain, France
and the USA generated fully ninety percent of the non-cooperative innovations.
Methodological Issues
One of the issues that the specification of equation (2) raises is the possible
endogeneity of relative factor prices and the literacy rate. To test for the presence of
feedback from the innovation rate, the observed values of these variables were replaced
by instrumental variables estimated with equations (3) and (4) respectively. The resulting
estimates (not shown here) were almost identical to those in Table 3. This result should
not surprise us, since for the countries that accounted for 95 percent of the innovations
(Britain, France and the USA), the publishing of the first monolingual dictionary and the
initial sharp rise in literacy rates preceded the first important innovations by a half
century or more.
As mentioned in Section 2, most of the observations for two key independent variables
– Relative energy price and Literacy – were estimated by the stochastic regression
method. How were the estimates in Table 3 affected by the resulting measurement errors?
Because of this method of estimation, the measurement errors are uncorrelated with the
possibly poorly-measured observations. As a result, the estimated coefficients in Table 3
are unbiased and consistent. However, since the variances are not efficient, we will tend
to underestimate the level of significance of the resulting coefficients.
15
Yet another issue is the robustness of the estimates just presented. To assess the
importance of this problem, in Tables 4 and 5, the explanatory variables are divided into
two sets. The country and period secondary fixed effects appear in all of the 64
specifications of each table. For each of the six remaining primary variables, all 32
combinations of the five other primary variables were estimated. The column headed
“%Sig” in each table indicates the percentage of the resulting coefficient estimates that
were significant at the five percent level under a two-tailed test. Let us consider a variable
as robust if all of the estimates had the expected sign and all of the estimates were
significant. These robust variables are printed in bold face in the tables.
In Table 4, we see that for cooperative innovations, the negative country fixed effects
for Germany, Belgium and the Netherlands are all extremely robust. In contrast, Relative
energy price and Literacy are more fragile, with coefficients in at least half of the
specifications not significant at the five percent level under a two-tailed test. As for the
measure of language standardization, Dictionary year, it is always significant with the
expected negative sign. The other language variable, Country population, always has the
expected positive sign. Although almost a third of the estimates for this variable are not
significant at the 5 percent level, all pass at the 20 percent level (unlike Relative energy
price and Literacy). Since the measures of significance are conservative, we cannot easily
reject the hypothesis that cooperative innovation increases with network size.
Examining now the corresponding results for the non-cooperative innovations in Table
5, we find a similar pattern for the country fixed effects and the demand variables.
Moreover, once again Dictionary year is quite robust, although the mean of its coefficient
is considerably less in absolute value than for the cooperative innovations. It is interesting
to note that the Enlightenment variable, 1750, is also very robust. This result is consistent
with the hypothesis of Mokyr and Voth (2009) that innovators in all European countries
benefited from the dissemination of knowledge across international borders during the
latter half of the eighteenth century. Note however, that in results not presented here,
interaction terms between the country and period fixed effects were not significant.
Accordingly, this Enlightenment effect does not seem to have been more important in
Britain than elsewhere.
16
Complementing these robustness estimates is a series of sensitivity tests presented in
the Appendix. Together these results help explain why before 1850, countries without a
standardized language (Germany and Italy) or with a small number of native speakers
(Austria, Belgium, Denmark, the Netherlands and Switzerland) were unable to develop
innovations requiring the collaboration of two or more principals. The results also
suggest why non-cooperative innovations were also concentrated in Britain, France and
the United States, since even independent inventors depended on cooperation from local
networks of suppliers, employees and clients.
In the next section, we turn to China, asking whether institutions, relative energy
prices or literacy rates can explain its failure to develop important new technologies
during the West’s Industrial Revolution.
17
4. Supply and demand forces in China
Currently, there are two main sets of explanations for the "Needham Puzzle" of the
decline in Chinese innovation after the fifteenth century, one approach focusing on the
supply of inputs to the innovation process and the other on the effect of factor prices on
the demand for new technologies..
On the supply side, both Needham himself (1969) and Lin (1995) attributed the
Chinese decline to the society's inability to develop experimental methods. Whereas
Needham emphasized the incompatibility of Confucian philosophy with a mechanical
view of the world, for Lin the failure to innovate was due to the distorted incentive
structure created by the examination system for the imperial bureaucracy. In the modern
period, the resulting lack of scientifically-trained manpower became crucial, as scientific
discovery became increasingly essential for further technological innovation. Acemoglu
and Robinson (2012, 231) explained China's stagnation by its "extractive" institutions. As
Khalil (2012) has observed, however, institutions tend to be endogenous: they adapt to
the demands of the society. Initially, in the Early Modern period, institutions in England
and France were no more favorable to novelty than those under the Qing dynasty. One
must explain why institutions unfavorable to innovation were replaced in the West while
they persisted in China.
Could it be that potential innovators in China were reacting rationally to factor prices,
but that these prices did not favor technological innovation? Pomeranz (2000, 62-66)
argued that since China’s major coal deposits were in the north while its industry was in
the south where wage rates were low, its entrepreneurs had little incentive to develop
labor-saving machinery. For Rosenthal and Wong (2011) China’s factor prices did not
favor labor-saving innovation. However in 1700, according to Allen (2009a, 101-102),
the real price of coal was only 30 percent higher in Canton than in London. Further north
in Suzhou, closer to the coal fields, the difference compared to London was presumably
smaller. As for wages, in the late seventeenth century, the real wages of agricultural
laborers in the Yangtze Delta and England were roughly equal (Allen, 2009b, 544). If so,
on the eve of the Industrial Revolution, the relative price of energy in the Yangtze Delta
18
was roughly comparable to that in southern England. If we may assume that this
approximate parity also applied to the coal-producing areas of Shanxi province compared
with central England, the Chinese had as much incentive as the English to replace labor
by coal-powered machinery. As mentioned in the introduction, literacy rates in the
seventeenth century were probably comparable in England and China.
In short, neither institutional differences nor discrepancies in relative factor prices
offer a convincing explanation for the absence of innovation in China during the
Industrial Revolution in the West. The next section asks whether linguistic divergence
can help solve the Needham puzzle.
19
5. Language Standardization in China
In this section, the language-networks approach used to explain innovation in the
West is applied to the case of technological stagnation in China.
Consider first the written language. The Chinese writing system is logographic, each
graph generally representing a morpheme, the smallest word or part of a word that still
has meaning. Most graphs are composed of a semantic element and a phonetic element.
However, because the spoken language had evolved much more rapidly than the written
language, by the early-modern period, the phonetic element no longer coincided with the
pronunciation of the composite graph (Norman, 1988, 68). Another challenge for the
reader was the existence of two writing systems, one a standardized structure used for the
literature of the Classical period (221 BC – 220 AD), and the other an evolving nonstandardized written vernacular used for letters, routine documents and literature for
popular consumption (Norman, 1988, 108).1 It is estimated that there were between 1,000
and 1,600 “vulgar” graphs in use (Hannas, 1997, 20) in the written vernacular.
With regard to literacy, in the seventeenth century perhaps half of the male population
may have been semi-literate, able to recognize at least 400 of the characters that they
might meet in their daily lives (Rawski, 1979, 3) (Baten et al., 2010, 354). However, only
about one percent of men were able to read the four thousand or more formal characters
necessary to understand Literary Chinese (Heijdra, 1998, 561).2 Beyond a certain
threshold, the marginal cost of learning new characters was simply too high for the vast
majority of the population.3
With regard to the spoken language, lack of standardization was also a problem. Under
the late Tang (618-907) and the Song (960-1279) dynasties, there had been a standard
koine for people who did not share the same dialect. From the thirteenth century onward,
1
As a result, the dominant medium for writing in China was Literary Chinese until well into the twentieth
century (Dong, 2014, 103).
2
In a comparison of 25 Chinese dynastic histories written before 1950, Cheng (2000, 111-112) found that
each contained between 4,000 and 8,000 different characters.
3
Lee et al. (1995, 253) showed that although Chinese children initially learn to read new words somewhat
more rapidly than their Americans counterparts, in the final three years of elementary school, American
children learn roughly five times as many new words as Chinese children.
20
this lingua franca was based on the dialect of the Jin and Yuan capital of Beijing
(Norman, 1988, 186-187). In conversation, educated people from different regions
communicated orally using this koine, known as guanhua, “official speech,” although it
was never formalized (Norman, 1988, 133). Even so, increasing differences in
pronunciation of this language of the “mandarins” often led to problems of
comprehension. In the 1720s, the Yongzheng emperor established Correct Pronunciation
Academies in the south in an attempt to standardize the Mandarin spoken by his officials.
However, this effort was soon abandoned (Dong, 2014, 131). There were seven major
groups of Chinese dialects, some of which had their own regional koines (Normal, 1988,
246). As different from each other as French, Spanish and Italian, these regional
vernaculars were not mutually intelligible (Crystal 1997, 314). Within each linguistic
zone, there was additional differentiation between regions, between classes and between
rural and urban residents (Brook, 1998, 644).
In northern China, the dialects were
varieties of the vernacular spoken by the residents of Beijing (Norman, 1988, 190). In the
center and south, the six other linguistic groups showed much greater variation (Norman,
1988, 187-188).
Was it more difficult for late-Ming Chinese than for their European contemporaries to
understand people from other regions of their society? The answer to this question
demands some measure of the mutual intelligibility of regional dialects in Europe and in
China prior to the Industrial Revolution. Unfortunately such information does not exist.
However, if we may assume that the degree of mutual intelligibility has not changed
greatly over the past three centuries, present-day measures of mutual comprehension of
spoken dialects offer some indication of the difficulty people had in understanding one
another prior to the diffusion of standard national languages.
The first two lines of Table 6 indicate the percentage of words in 17 non-Standard
Scandinavian dialects understood by young residents of Copenhagen. We see that
average comprehensions levels average from about one-half to one-third, depending on
the distance from Copenhagen. For two strangers addressing each other in these dialects,
conversation would appear to be difficult. The last two lines of the table indicate the
impact of national standardization programs. Danes exposed through the media of
21
neighboring Sweden and Norway likely have an approximate understanding of what they
hear. However, their exposure to the formal teaching of Standard Danish results in a
much higher degree of intelligibility. This latter result provides some indication that the
formal teaching of Standard English and French in the eighteenth century would have
greatly increased the mutual intelligibility of innovators such as Boulton and Watt who
came from different regions. Because of earlier standardization, Britain, France and the
United States would therefore have had a great advantage over other Continental
countries, especially in cooperative innovation.
Table 6. Intelligibility of Scandinavian dialects to young Danes from Copenhagen
according to distance and degree of standardization
Dialect
Distance (km)
Intelligibility (%)
Neighboring regions
301
48
Distant regions
956
35
Standard Swedish and Norwegian
628
62
0
99
Standard Danish
Source: Gooskens et al. (2008; 66, 74).
The first two lines of Table 7 present comparable present-day intelligibility rates for
residents of the Yangtze Delta city of Suzhou. As one would expect, with greater average
distances between regions than in Europe, comprehension levels are lower than in Table
6. Intelligibility is better for the varieties of Mandarin spoken across the north Chinese
plain than for the less closely-related dialects of the mountainous south. Nevertheless, we
may again infer that conversation between strangers would be difficult. The effect of an
informally learned koine is suggested in the third line of the table. The Beijing dialect is
close to but not identical to the Standard Chinese to which most of the respondents would
have been exposed through today’s media. The 64 percent intelligibility percentage thus
provides some idea of the impact of a koine learned in non-formalized fashion. Finally,
the bottom line indicates the impact of the absence of formal teaching of the local
22
vernacular. Residents of the Suzhou dialect area understood varieties of their own
vernacular no better than that of Beijing.
Table 7. Intelligibility of Chinese dialects to rural residents of the Suzhou area
according to distance and degree of standardization
Dialect
Distance (km)
Intelligibility (%)
Northern China
1245
37
Southern China
1001
24
Beijing
1155
64
Suzhou
approx. 50
65
Source: Tang and van Heuven (2009, 719).
In short, China had long reached the first or bottom-up stage in Milroy’s (1994, 20)
analysis of language standardization, with the emergence of “agreed norms in certain
dialect areas”. Why had China not proceeded to the second or top-down phase of
standardization with the imposition of a national standard? The answer lies in China’s
logographic writing system. Although movable type was a Chinese invention, because of
the nature of Chinese script with its thousands of complex characters, almost all printing
before the mid-nineteenth century was with hand-carved wooden blocks. Angeles (2014,
Table 1) has estimated that the marginal cost of carving a page of text in China using
block printing was some 15 times higher than setting the same text with movable type in
Europe. As a result, between 1522 and 1644, there were some 457,500 different book
titles produced in Europe, but only 6,618 in China (Angeles, 2014, 37). With a small
potential market and high production costs, publication of a vernacular dictionary was
simply not profitable for the private publishers who dominated the Chinese publishing
industry in the seventeenth century.
The first Chinese vernacular dictionary, with pronunciation based on Beijing
Mandarin, was published in 1932, two decades after the revolution that overthrew the
Qing imperial dynasty (Dong, 2014, 133). In 1956, the government of the People’s
Republic proclaimed Pùtōnghuà (Common Speech) based on the Beijing vernacular to be
23
the country's official language. In that same year the government issued a set of 515
simplified characters along with a Romanized script known as pinyin to indicate
pronunciation. Was it simply a coincidence that in 1982, a half century after the first
vernacular dictionary, a team directed by Wang Xuan patented China’s first important
industrial innovation in five centuries – a system for laser photocomposition of Chinese
characters (An, 2006)?
V. Conclusion
This study has provided empirical support for the inclusion of language
standardization in the West and its absence in China among the forces that caused the
East-West divergence in rates of innovation during the Industrial Revolution. A key to
the West’s success would appear to have been cooperation between those who
understood the needs of the market and those technically able to produce the desired
novelty. In Britain, northern France and the north-eastern United States, the emergence of
networks of citizens able to write and speak standardized languages proved favorable to
such cooperation between strangers. In China under the Qing dynasty, cooperation with
non-kin was handicapped by the lack of a standardized written and spoken vernacular.
24
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28
Data Sources
City population. Population estimates for European cities were from Bairoch et al.
(1988). Estimates for New York, Philadelphia and Boston were from Longman
Publishing http://wps.ablongman.com/wps/media/objects/244/250688/Appendix/12.pdf.
There were 46 cities at or near which one or more innovations occurred. To avoid
potential endogeneity, population and literacy were determined at the beginning of each
of the three half-century periods.
Country population. The source was Maddison (2007).
Coal. The identification of cities with coal deposits within 30 miles (50 km) was obtained
from Barraclough (1984: 201, 210-211).
Distances. The driving distance in kilometers to each city from Rome and Mainz was
obtained from Google Maps, https://maps.google.com/.
Catholic. Catholic Answers http://forums.catholic.com/showthread.php?t=640044.
Dissent. Darby and Fullard (1970, 127).
Ocean port. Hammond & Hammond (1992).
Language standardization. See Table 2. Note the dates of the first monolingual
dictionary of five countries were chosen arbitrarily. Cities in Belgium and Switzerland
were assigned the dates of French, Dutch or German dictionaries, depending on their
main languages. As for Scotland, by the year of Union with England, 1707, educated
Scots were growing accustomed to using English rather than the Scottish dialect for
formal communication (Herman 2001, 116). A similar argument applies to Ireland for
1800. In the case of the United States, the first settlers spoke the language of their home
regions. However, by the year 1725, the more popular English dictionaries were
beginning to be imported (Green, 1999, 285).
Literacy. Signature rates at marriage are not necessarily an accurate measure of people’s
ability to read and write (Mitch, 1999, 244). However, unlike the national publication
29
rates used by Baten and Luiten van Zanden (2008), differences in signature rates provide
an indication of changes in human capital at the regional level. By country, the sources
were England: Cressy (1980, 177); Scotland: Stone (1969, 121); France: Houdaille (1977,
68); Germany: Hofmeister et al. (1998); Italy: Reis (2005, 202); Netherlands: van der
Woude (1980, 257-264); United States: Graff (1991, 249).
Wage rates. Wage rates for eight European cities in the sample were from Allen (2001,
Table 2).
Prices of coal. Coal prices for the same cities were available in Allen (2009a, 99-100). To
the extent that factors were mobile within each country, these data provide sufficient
information to obtain reasonable estimates of relative factor prices by region.
30
Table 1. 117 important innovations, 1700-1849
Country
Denmark
1700-1749
1750-1799
France
Loom coded with
perforated paper
(Bouchon, 1725;Lyon)
Loom coded with punched
cards (Falcon, 728;Lyon)
Steam-powered wagon (Cugnot,
1770; Paris)
Automatic loom (Vaucanson, 1775;
Paris)
Single-action press (Didot,
Proudon,1781; Paris)
Two-engine steamboat (Jouffroy
d'Abbans, 1783; Lyon)
Hot-air balloon (Montgolfier, 1783;
Paris)
Parachute (Lenormand, 1783;
Montpellier)
Press for the blind (Haüy, 1784;
Paris)
Chlorine as bleaching agent
(Berthollet, 1785; Paris)
Sodium carbonate from salt
(Leblanc, d’Arcet, 1790; Paris)
Visual telegraph (Chappe, 1793;
Paris)
Vacuum sealing (Appert, 1795;
Paris)
Paper-making machine (Robert,
Didot, 1798; Paris)
Illuminating gas from wood
(Lebon, 1799; Paris)
Germany
Porcelain (Tschirnhaus,
1707; Dresden)
Lithography (Senefelder, 1796;
Munich)
Great
Britain
Seed drill (Tull, 1701;
Oxford)
Iron smelting with coke
(Darby, Thomas, 1709;
Birmingham)
Atmospheric engine (Newcomen, Calley,1712;
Birmingham)
Pottery made with flint
(Astbury, 1720;
Birmingham)
Quadrant (Hadley, 1731;
London)
Flying shuttle (Kay, 1733;
Manchester)
Glass-chamber process for
sulfuric acid (Ward, White,
D’Osterman, 1736;
London)
Spinning machine with
Crucible steel (Huntsman, 1750;
York)
Rib knitting attachment (Strutt,
Roper, 1755; Birmingham)
Achromatic refracting telescope
(Dollond, 1757; London)
Breast wheel (Smeaton, 1759;
York)
Bimetallic strip chronometer
(Harrison, 1760; London)
Spinning jenny (Hargreaves, 1764;
Manchester)
Creamware pottery (Wedgewood,
Wieldon, 1765; Birmingham)
Cast-iron railroad (Reynolds, 1768;
Birmingham)
Engine using expansive steam
operation (Watt, Roebuck, 1769;
Glasgow)
Water frame (Arkwright, Kay,
1800-1849
Galvanometer (Oersted, 1819;
Copenhagen)
Automatic loom with perforated cards (Jacquard, Breton,
1805; Lyon)
Wet spinning for flax (de
Girard, 1815; Avignon)
Electromagnet (Arago, Ampère,
1820; Paris)
Water turbine (Burdin, 1824;
Saint-Étienne)
Single-helix propeller (Sauvage,
1832; Le Havre)
Three-color textile printing
machine (Perrot, 1832;
Rouen)
Water turbine with adjustable
vanes (Fourneyron, 1837;
Besançon)
Photography (Daguerre, Niepce,
1838; Paris)
Multiple-phase combing
machine (Heilmann, 1845;
Mulhouse)
Machines for tackle block
production (Brunel,
Maudslay, 1800; London)
Illuminating gas from coal
(Murdock, Watt Jr., 1802;
Birmingham)
Steam locomotive (Trevithick,
Homfray, 1804; Plymouth)
Compound steam engine
(Woolf, Edwards, 1805;
London)
Winding mechanism for loom
(Radcliffe, 1805; Manchester)
Arc lamp (Davy, 1808; London)
Food canning (Durand, Girard,
1810; London)
Rack locomotive (Blenkinsop,
Murray, 1811; Bradford)
Mechanical printing press
(Koenig, Bauer, 1813;
31
Country
1700-1749
rollers (Wyatt, Paul, 1738;
Birmingham)
Stereotyping (Ged, 1739;
Edingurgh)
Lead-chamber process for
sulfuric acid (Roebuck,
1746; Birmingham)
1750-1799
1769; Birmingham)
Efficient atmospheric steam engine
(Smeaton, 1772; Newcastle)
Dividing machine (Ramsden, 1773;
London)
Cylinder boring machine
(Wilkinson, 1775; Birmingham)
Carding machine (Arkwright, Kay,
1775; Birmingham)
Condensing chamber for steam
engine (Watt, Boulton, 1776;
Birmingham)
Steam jacket for steam engine
(Watt, Boulton, 1776;
Birmingham)
Spinning mule (Crompton, 1779;
Manchester)
Reciprocating compound steam
engine (Hornblower, 1781;
Plymouth)
Sun and planet gear (Watt, Boulton,
1781; Birmingham)
Indicator of steam engine power
(Watt, Southern, 1782;
Birmingham)
Rolling mill (Cort, Jellicoe, 1783;
London)
Cylinder printing press for calicoes
(Bell, 1783; Glasgow)
Jointed levers for parallel motion
(Watt, Boulton, 1784;
Birmingham)
Puddling (Cort, Jellicoe, 1784;
London)
Power loom (Cartwright, 1785;
York)
Speed governor (Watt, Boulton,
1787; Birmingham)
Double-acting steam engine (Watt,
Boulton, 1787; Birmingham)
Threshing machine (Meikle, 1788;
Edinburgh)
Single-phase combing machine
(Cartwright, 1789; York)
Machines for lock production
(Bramah, Maudslay, 1790;
London)
Single-action metal printing press
(Stanhope, Walker, 1795;
London)
Hydraulic press (Bramah,
Maudslay, 1796; London)
High-pressure steam engine
(Trevithick, Murdoch, 1797;
1800-1849
London)
Steam locomotive on flanged
rails (Stephenson, Wood,
1814; Newcastle)
Safety lamp (Davy, 1816;
London)
Circular knitting machine (M. I.
Brunel, 1816; London)
Planing machine (Roberts,
1817; Manchester)
Large metal lathe (Roberts,
1817; Manchester)
Gas meter (Clegg, Malam,
1819; London)
Metal power loom (Roberts,
Sharp, 1822; Manchester)
Rubber fabric (Hancock,
Macintosh, 1823; London)
Locomotive with fire-tube
boiler (Stephenson, Booth,
1829; Manchester)
Hot blast furnace (Nielson,
Macintosh, 1829; Glasgow)
Self-acting mule (Roberts,
Sharp, 1830; Manchester)
Lathe with automatic cross-feed
tool (Whitworth, 1835;
Manchester; Manchester)
Planing machine with pivoting
tool-rest (Whitworth, 1835;
Manchester)
Even-current electric cell
(Daniell, 1836: London)
Electric telegraph (Cooke,
Wheatstone, 1837; London)
Riveting machine (Fairbairn,
Smith, 1838; Manchester)
Transatlantic steamer (I. K.
Brunel, Guppy, 1838; Bristol)
Assembly-line production
(Bodmer, 1839; Manchester)
Multiple-blade propeller (Smith,
Currie, 1839; London)
Steam hammer (Nasmyth, 1842;
Manchester)
Iron, propellor-driven steamship
(Brunel, Guppy, 1844;
Bristol)
Measuring machine (Whitworth, 1845; Manchester)
Multiple-spindle drilling
machine (Roberts, 1847;
Manchester)
32
Country
1700-1749
1750-1799
1800-1849
Plymouth)
Slide lathe (Maudslay, 1799;
London)
Italy
Electric battery (Volta, 1800;
Como)
Switzerland
Massive platen printing press
(Haas, 1772; Basel)
Stirring process for glass (Guinand,
1796; Berne)
United
States
Continuous-flow production
(Evans, Ellicott, 1784;
Philadelphia)
Cotton gin (Whitney, Green, 1793;
Philadelphia)
Machine to cut and head nails
(Perkins, 1795; Boston)
Sources: see Section 1 of text.
Underlined innovations were cooperative.
Single-engine steamboat
(Fulton, Livingston, 1807)
Milling machine (North, 1818;
New York)
Interchangeable parts (North,
Hall, 1824; New York)
Ring spinning machine (Thorp,
1828; Boston)
Grain reaper (McCormick,
Anderson, 1832; Philadelphia)
Binary-code telegraph (Morse,
Vail, 1845; New York)
Sewing machine (Howe, Fisher,
1846; Boston)
Rotary printing press (Hoe,
1847; New York)
33
Table 2. Year of first monolingual dictionary
Country
Austria
England
Belgium (French)
Belgium (Flem.)
Denmark
France (north)
France (south)
Germany
Ireland
Italy
Year
1868
1658
1680
1864
1833
1680
1815
1786
Author(s)
Otto Back et. al.
Edward Phillips
Christian Molbech
Pierre Richelet
Johann Christoph
Adelung
1800
1897
Netherlands
1864
Scotland
Switzerland (Fr.)
Switzerland
(German)
United States
1707
1680
1786
1728
Emilio Broglio &
Giovan Battista Giorgini
Marcus and Nathan
Solomon Calisch
Nathan Bailey
Publication
Österreichisches Wörterbuch
The New World of English Words
Same as France (north)
Same as Netherlands
Dansk Ordbog
Dictionnaire français
Standardization delayeda
Grammatich-kritisches Wörterbuch
der hochdeutschen Mundart
Year of Union with England
Nòvo vocabolario della lingua
italiana secondo l'uso di Firenze
Nieuw Woordenboek der
Nederlandsche Taal
Year of Union with England
Same as France (north)
Same as Germany
An Universal Etymological English
Dictionary
a
South of a line from St. Malo to Geneva, standardization occurred through the integrating effects of
the revolutionary and Napoleonic Wars (Graff, 1991, 193).
Note: Other early dictionaries fail to reflect the existence of a standardized written vernacular.
Robert Cawdrey’s Table Alphabeticall (1604) was a list of hard words to spell. Josua Maaler’s, Die
Teütsch Spraach (1561) was devoted to Swiss and Upper German vocabulary. The Accademia della
Crusca’s dictionary of Italian (1612) was intended to provide a prescriptive norm to which writers
were advised to conform. Kornelius Kiliaan’s (1599) Etymologicum used Latin to explain Dutch
words, as did Jean Nicot’s (1606) Trésor de la langue françoise for the French language.
34
Table 3. Negative binomial regressions for Western innovations
Cooperative
Group
Fixed effects
Variable
(1)
Britain
-0.018
France
0.391
Non-cooperative
(2)
(3)
(4)
-4.575**
0.695
-0.634
-5.378**
0.637
-0.926
Germany
-17.239**
-17.128**
-2.045**
-2.073**
Belgium
-17.126**
-15.868**
-16.235**
-17.604**
Netherlands
-17.842**
-11.594**
-17.084**
-17.190**
1750
0.960
0.320
0.571**
0.674**
1800
-0.410*
-1.536
-0.791
-0.101
-3.285**
2.148**
-1.571
-1.103
0.165
3.850**
0.740
-0.893**
-0.495
-0.516
1.215**
1.020**
0.970**
Demand
Relative energy price
Literacy
Ocean port
2.777*
-0.179
Scale
City population
1.148*
Language networks
Country population
1.736**
-0.011
Dictionary year
-3.297**
-0.929**
Constant
2.948**
8.465**
1.331
3.386
α
2.015**
1.204
1.926**
1.795*
Log pseudolikelihood
-80.389
-72.538
-126.188
-71.66
Time-series cross-section of 201 cities for 1700-1749, 1750-1799 and 1800-1849.
Dependent variable: number of cooperative innovations in region of city j in period t.
Number of observations: 603.
Standard errors are adjusted for five clusters in country.
* Coefficient significantly different from zero at 0.05 level, two-tailed test.
** Coefficient significantly different from zero at 0.01 level, two-tailed test.
Coefficients in bold face in column (2) are significantly different from corresponding
estimates in column (4), at 0.05 level, two-tailed test.
35
Group
Fixed effects
Table 4. Robustness check for cooperative innovations, 1700-1850
Variable
Mean AvgSTD
%Sig
%+
%AvgT
Britain
France
Germany
Belgium
Netherlands
1750
1800
Demand
Relative energy price
Literacy
Ocean port
Scale
City population
Language networks
Country population
Language standard’n
Obs
-1.08
-2.74
-17.61
-16.95
-15.46
1.03
0.14
0.46
0.97
1.18
1.64
1.64
0.66
0.87
75
58
100
100
100
36
19
39
13
0
0
0
100
50
61
88
100
100
100
0
50
6.06
5.07
15.00
11.26
10.47
1.71
1.30
64
64
64
64
64
64
64
-2.28
3.03
-0.01
1.29
1.83
0.73
50
47
13
0
97
47
100
3
53
2.65
2.34
0.84
32
32
32
1.16
0.36
100
100
0
3.31
32
1.61
-3.38
0.76
0.47
69
100
100
0
0
100
2.20
8.23
32
32
36
Table 5. Robustness check for non-cooperative innovations, 1700-1850
Group
Variable
Mean AvgSTD
%Sig
%+
%AvgT
Fixed effects
Britain
0.47
0.71
31
50
50
3.59
France
-0.88
0.88
38
19
81
2.44
Germany
-2.01
0.22
100
0
100
13.64
Belgium
-16.44
1.13
100
0
100
14.56
Netherlands
-16.26
1.16
100
0
100
14.12
1750
0.96
0.24
100
100
0
4.09
1800
0.44
0.56
27
80
20
1.11
Demand
Relative energy price
-0.44
1.98
0
50
50
0.42
Literacy
1.56
1.87
25
100
0
1.10
Ocean port
-0.14
0.41
6
50
50
1.00
Language networks
City population
0.95
0.12
100
100
0
8.58
Country population
0.07
0.16
22
72
28
0.91
Language standard’n
-1.21
0.25
100
0
100
11.73
Obs
64
64
64
64
64
64
64
32
32
32
32
32
32