Abstract
This paper considers the possible contribution of spatial competition to the Industrial Revolution and the Great Divergence. Rather than exclusively focusing on the incentives of producers to adopt labor-saving technology, we also consider the incentives of factor suppliers’ organizations such as craft guilds to resist. Once we do so, industrialization no longer depends on market size per se, but on spatial competition between the guilds’ jurisdictions. We substantiate our theory’s claim of spatial competition being an important channel for industrialization (i) by providing historical evidence on the relation between spatial competition, craft guilds and innovation, and (ii) by showing that the calibrated model correctly predicts the timings of the Industrial Revolution and the Great Divergence.
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Notes
See, for example, Kremer (1993), Kelly (1997), Peretto (1998) and Desmet and Parente (2012). In addition to market size, other factors that have been shown to contribute to industrialization include natural resources (Pomeranz 2000), the demographic transition (Galor and Weil 2000), education (Galor and Moav 2002), and institutions (North 1981).
Other actors who also resisted industrialization and mechanization were large-scale landowners (see, e.g., Galor et al. 2009) and sometimes agricultural workers (see, e.g., the Swing Riots of 1830).
The use of industry profits to buy out craftsmen is meant to capture a variety of methods employed to break worker resistance. One such method was the poor laws, financed by local taxes and put in place to help displaced workers. Other methods included hiring private security to fortify factories, appealing to the judiciary to rule in the favor of industry on worker petitions, and lobbying the government to send out troops.
For a comprehensive list, see McCloskey (2010).
Another reason for considering Northwest Europe is that its total population is more comparable to China’s.
Bairoch et al. (1988) panel covers the period from 800 to 1850, with one observation per century until 1600, and two observations per century after that. It includes all cities that had a population of at least 5000 in one of the years for which there are observations.
In addition to the 18 provinces of China Proper, it also includes Xinjiang and four provinces-in-the-making north of the Great Wall: Shengjing (later Liaoning), Jilin, Heilongjiang, and Nei Menggu.
To be precise, Yue et al. (2007) do not report exact city sizes, but rather classify cities by size bins, with the first bin consisting of cities with 500–1000 inhabitants, and with the upper limit of each subsequent bin being twice its lower limit, until reaching 512,000. Thus, the bins consist of: 500–1000; 1000–2000; 2000–4000; ...; 256,000–512,000; and more than 512,000. Except for the highest bin, we use the mid-value of each bin to define the size of a city’s population. For the highest bin, we use city population data from 1900 from Eggimann (1999). Note that we cannot use Eggimann (1999) as an alternative source for our overall study of urbanization in China because of the high number of missing data: for 1850 Eggimann (1999) only has data on 62 Chinese cities, and by 1900 that number only increases to 85.
In order to compare China with England and Northwest Europe in 1776 and 1820, we have imputed population values for England and Northwest Europe assuming that city-specific growth rates between two consecutive years in the Bairoch et al. (1988) dataset were constant.
Using data for many countries, Jacks et al. (2011) find a value of 1.2 for the time period 1870–1913. Given the dearth of historical evidence, an alternative strategy is to use present-day evidence from developing countries as a proxy. Daumal and Zignago (2010) estimate an elasticity of 1.9 for Brazil. As a midpoint between these two estimates, we use \(\gamma =1.5\).
Interestingly, the Luddite riots also coincided with changes in spatial competition. Binfield (2004) argues that mill workers associated with the Luddites only turned anti-technology after the British government cut off trade with France via the Prince Regent’s Order in Council of 1811 in response to the Napoleonic War. Following the removal of this order in 1817, their resistance stopped and violence ended.
How one views guilds depends on which institutions were available in a particular time period. De la Croix et al. (2018) analyze the creation and transmission of knowledge under four institutions: the nuclear family, the clan, the guild and the market. They argue that guilds were superior to clans (though inferior to markets). They use this insight to explain why in the preindustrial period Western Europe, where guilds were prevalent, was more advanced than other regions of the world where clans or families were the main institution. We, instead, focus on the eve of the Industrial Revolution, and argue that the decline of guilds and the emergence of markets was key to industrial takeoff.
The importance of competition between unguilded and guilded areas for industrialization is consistent with the model by Holmes and Schmitz (1995).
For example, in the case of Kay’s Fly Shuttle used for the weaving of woolen cloth, 2&3 Philip and Mary c. 11 stated that “no clothier might own more than one loom, not let out looms for hire outside of a city, borough, market town or corporate town.”
Spatial competition between guilded cities was also important to understand technology adoption on the continent. For example, ’t Hart (1993) and Mokyr (1998) describe how in 1604 the city government of Leiden in the Netherlands refused to support the craft guilds’ pleas to ban a newly invented ribbon loom because it worried the industry would move to the nearby city of Delft, where guilds were weaker.
Of course, in the second half of the nineteenth century, we did see an emergence of worker power that superseded the city level in the form of national trade unions. However, by that time, the Industrial Revolution had become irreversible.
The database contains 516 named pre-1900 guilds of which 347 can be classified as either huiguan or gongsuo.
Since a household’s ideal variety depends on its location on the unit circle, \(\tilde{v}\) does not require a subscript i.
Strictly speaking, this assumption is not necessary since in a symmetric equilibrium each region would consume its own production of the agricultural good.
Depending on the parameter values, aggregate demand could in principle also depend on the locations and the prices of varieties that are farther away on the unit circle. If we assume that households can only choose between the closest variety to the left and the closest variety to the right of their ideal variety, then this is not a concern. However, in that case there may be corner solutions where the indifference condition does not hold. In the numerical section we check for this possibility.
This indifference condition applies to both the unskilled worker who are uniformly distributed around the unit circle and the skilled workers who are also uniformly distributed around the unit circle.
The fact that the modern technology does not require skilled workers applies to both the fixed and the variable workers. Additionally, we make assumptions on the parameter values that guarantee \(w_{a}(\kappa +\phi \dot{) }>w\)\(\kappa \), so that there is a a disadvantage associated with the modern technology.
In contrast to an increase in population, a decrease in iceberg costs actually leads to a decrease in the number of varieties produced by each region. Nevertheless, the price elasticity of demand still increases on account of the greater competition from producers of the other region.
Of course, as already discussed, there are other reasons why historically guilds might have formed in the first place, but they are not considered here. Thus, the question this paper addresses is: if skilled workers in a given industry and city-region did not form a guild earlier for some other reason, would they have an incentive to do so with the objective of resisting the adoption of the modern technology? Equivalently, if skilled workers already formed a guild for some other purpose, when would that guild turn anti-technology?
Note that the deviation condition (29) is the same whether we consider the deviation of one firm in a particular industry and city-region or whether we consider the deviation of all firms in that industry and city-region. There are two reasons for this result. First, the incentive for an Eastern firm to deviate only depends on its two Western-produced neighboring varieties, and second, each industry is measure zero, so that even if all firms in a given industry and city-region were to deviate, there would be no effect on aggregate income.
Strictly speaking, in our model the deviating industry would be the only one making profits, so that the limit on tax revenues from profits would be total profits, as in (30).
As a practical matter, resistance could also be overcome through the polity or the judiciary. If one assumes that this only occurs successfully if industry profits from adoption are big enough, either because industries need to lobby or because the polity becomes more favorable to adoption when the gains are large, then the results regarding the relation between spatial competition and innovation would be qualitatively unchanged. However, to keep things simple, we do not consider this alternative here.
If the elasticity of substitution is large enough, adoption by an entire industry might be sufficiently profitable to compensate existing workers even in the absence of inter-city trade. However, this result can be shown to be independent of market size, so that if adoption is profitable enough for one market size, it will be profitable for any market size. In such a case, we would never see guilds emerging, because there would never be a reason to resist adoption. Hence, without inter-city competition, we would be unable to explain the rise and decline of guilds. Results based on this and other alternative assumptions are available upon request.
Since we assume that the modern technology is always available, the definition of the ARTSE now requires the additional condition that no firm in no industry has an incentive to adopt the modern technology, i.e., \( \Pi ^{E^{\prime } }\le 0\).
We base our estimate on information of four different goods: grain, wine, luxury woolens and semi-worsted woolens. Masschaele (1993) finds that transporting grain in fourteenth century England added around 0.25% per km to the price. Based on data from the end of the sixteenth century, transporting wine from Chester to Smithills increased the price by 0.17% per km (Willan 1976). As for woolen products, Munro (1997) cites different studies. One is based on the writings of a Flemish merchant who exported luxury woolen from Bruges to Barcelona in the late fourteenth century at a cost of 0.02% per km. Another study reports a cost of around 0.01% per km for semi-worsted woolen products exported from Caen to Florence in the early fourteenth century. Taking these four numbers, we find an average transport cost of around 0.1% per km.
Clark (2001) reports wages for urban craftsmen, urban laborers and farm laborers. He defines the skill premium as the wage ratio of urban craftsmen to urban laborers. This is the same as the wage ratio of urban craftsmen to rural laborers, when adjusting for the cost-of-living differences between urban and rural areas.
Given this last target, it is not exactly correct to say that the model is calibrated exclusively to the pre-1600 period.
To be precise, this is just the ARTSE when there is no wage premium, the artisanal technology is \(A_{x}(1+\gamma )\), and the operating cost is \(\kappa +\gamma \).
An obvious question is why we did not set the population to the actual 1400 average city size in England. The short answer is that theoretically city size only matters to the extent that it affects firm size, so the relevant target is the firm size. Had we wanted, we could have set \(L_{1400}\) to the actual 1400 average city size. Matching firm size would then require adjusting the circumference of the variety circle. This would not change anything, but it would come at the cost of introducing one more parameter, so we refrain from doing so.
This conclusion only relies on the 1893 data from Yue et al. (2007), and hence does not depend on the imputation of city size data in earlier time periods.
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We benefitted from helpful comments from seminar participants at Brown, CEU, Cleveland Fed, Dartmouth, HEC, Houston, Humboldt, U Javeriana, LSU, Miami, Penn, Princeton, St. Louis Fed and Texas A&M. We thank Mark Henderson and Wolfgang Keller for help with the data on Chinese cities.
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Desmet, K., Greif, A. & Parente, S.L. Spatial competition, innovation and institutions: the Industrial Revolution and the Great Divergence. J Econ Growth 25, 1–35 (2020). https://doi.org/10.1007/s10887-019-09173-3
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DOI: https://doi.org/10.1007/s10887-019-09173-3
Keywords
- Industrial Revolution
- Great Divergence
- Craft guilds
- Spatial competition
- Inter-city competition
- Market size
- Endogenous institutions
- Innovation
- Adoption of technology