Industrial Revolution. Why Britain? The Right Place (in the Technology Space) at the Right Time

Why Britain? The Right Place (in the Technology Space) at the Right Time. Carl Hallmann, W. Walker Hanlon, and Lukas Rosenberger. NBER, Jul 5 2022. https://conference.nber.org/conf_papers/f171957.pdf

Abstract: Why did Britain attain economic leadership during the Industrial Revolution? We argue that Britain possessed an important but underappreciated innovation advantage: British inventors worked in technologies that were more central within the innovation network. We offer a new approach for measuring the innovation network using patent data from Britain and France in the 18th and early 19th century. We show that the network influenced innovation outcomes and then demonstrate that British inventors worked in more central technologies within the innovation network than inventors from France. Then, drawing on recently-developed theoretical tools, we quantify the implications for technology growth rates in Britain compared to France. Our results indicate that the shape of the innovation network, and the location of British inventors within it, can help explain the more rapid technological growth in Britain during the Industrial Revolution.

Excerpts from the introduction:

In this study, we argue that there is one important British advantage that has been largely overlooked: the possibility that British inventors may have been working “at the right place” in the technology space. Our idea builds on emerging literature in growth economics which finds that innovation in some technologies generates more spillover benefits than innovation in others (Acemoglu et al., 2016; Cai and Li, 2019; Huang and Zenou, 2020; Liu and Ma, 2021). As a result, a country’s allocation of researchers across technologies can substantially impact the overall rate of economic growth. In particular, this literature shows that technological progress will be faster in economies where more research effort is focused on technologies that generate more spillovers for other technologies; in other words, technologies that are more central in the technology space. Translating these ideas into the context of the Industrial Revolution, we ask: did Britain experienced more rapid technological progress because British inventors were more focused on technologies, such as steam engines, machine tools, or metallurgy, that generated stronger spillover benefits for other technologies and were therefore more central in the technology space? In contrast, could it have been the case that Continental economies like France experienced slower technological progress because they specialized in developing technologies, such as apparel, glass, or papermaking, which were more peripheral in the technology space?1 Put another way, we aim to examine whether Britain’s differential growth during the eighteenth and early nineteenth centuries can be explained by the distinct position of British inventors in the technology space. By starting with ideas from modern growth economics, our analysis is less subject to the type of “post hoc, proper hoc” concerns that have been raised about some other explanations (Crafts, 1977, 1995). Moreover, we offer a theoretically-grounded quantification describing exactly how much of Britain’s differential growth experience can be attributed to this mechanism. These two features differentiate our study from most existing work that aims to understand Britain’s growth lead during the Industrial Revolution. To structure our analysis, we begin with a growth model, from Liu and Ma (2021), that incorporates an innovation network. In this network, each node is a technology type, while each edge reflects the extent to which innovations in one technology type increase the chances of further innovation in another. This model provides a framework for thinking about how the distribution of researchers across technology sectors relates to the growth rate in the economy. It also generates specific expressions that, given the matrix of connections across sectors, allow us to quantify how different allocations of researchers across technology sectors will affect growth. The upshot is that allocations in which more researchers are working in technology sectors with greater spillovers will generate higher overall growth rates than others. Therefore, the growth maximizing allocation of researchers will feature more researchers working in more central technology sectors: specifically, those sectors with higher eigenvalue network centrality. Furthermore, the model delivers precise analytical relationships that allow us to quantify the implications of different allocations of research effort for the rate of economic growth. To examine whether these forces operated during the Industrial Revolution, we utilize patent data for Britain, from 1700 to 1849, and for France from 1791-1844.2 These historical patent data cover a large number of inventors and their inventions, providing a rich source of information on innovation during the Industrial Revolution.3 We follow a long line of work, dating back at least to Sullivan (1989), using patent data to better understand innovation patterns during this period. A key challenge in our setting is measuring spillovers across technology categories. The innovation literature typically uses patent citations, but these are not available in our historical setting. Instead, we introduce a new approach based on the idea that if there are spillovers between two technology categories, then inventors working primarily in one area will occasionally file patents in the other. In particular, we measure the extent of spillovers from technology category j to i based on the propensity of inventors who patent in j to subsequently patent in i. Since our approach is new, we validate it using modern data. Specifically, using U.S. patents from 1970-2014, we construct innovation networks using our approach as well as the citation-based approach used in modern studies. Comparing these networks shows that the two approaches generate networks that are extremely similar. This suggests that our method does a good job of recovering the underlying innovation network. Using our approach, we document technology networks in Britain and France that feature a dense central core of closely related—and mainly mechanical—technologies. One important question about our estimated networks is, do they reflect fundamental features of the underlying technologies or simply reflect the local innovation environment in each country? One way to test this is to compare the networks obtained from the two countries. If they are similar, they likely reflect fundamental technological features rather than idiosyncratic conditions. Conducting a direct comparison, however, is challenging because the two countries use very different technology categorizations. Therefore, it is necessary to construct a mapping of technology categories from one country’s categorizations to the other. To do so, we carefully identify a set of inventions that were patented in both countries. We can then use the categorization of these inventions in each system to construct a crosswalk between the technology categorizations used in the two countries. Using this mapping, we construct technology spillover matrices derived from French patents but in terms of British technology categories, or derived from British patents but expressed in French technology categories. This allows us to regress the entries of the technology matrices of one country on the entries of the other country. We find they are strongly positively related, despite the noise that is inherent in any mapping between different systems of technology categorization. This indicates that our innovation matrices not just reflect the local economic environment, but that a significant part of each represents an underlying ‘global’ network of technology spillovers. Next, we establish that the shape of the technology spillover network matters for innovation outcomes. As a first step, we follow existing work on modern patent data by analyzing how patenting rates vary across technology categories depending on the lagged knowledge stock in other categories, weighted by the strength of connections through the innovation matrix. Consistent with the theory, and the results in previous studies of modern data, we find a significant positive associations of patenting with the lagged network weighted knowledge stock, shrinking toward zero as lags increase. However, the lack of exogenous variation in the lagged knowledge stock means that this result could be due to common shocks that affect connected technology categories. Thus, in the second step, we provide evidence based on a source of quasi-exogenous variation in the timing of increases in the knowledge stock at some nodes of the innovation network. Specifically, we use the unexpected arrival of “macroinventions.” These are inventions which Mokyr (1990) describes as “a radical new idea, without a clear precedent, emerges more or less ab nihilo.” Using a list of 65 macroinventions from Nuvolari et al. (2021), we study whether the arrival of a new macroinvention in one technology category leads to a subsequent increase in patenting in downstream technology categories within the innovation network. Here, the identifying assumption is not that the location of macroinventions were random, but that the timing of their arrival at a given location was unpredictable within the time frame of analysis. Using pooled difference-in-difference and event study analyses for a time frame of ten years before and after the arrival of each macroinvention, we show that macroinventions are followed by significant increases of the patenting rates in technology categories sharing stronger (downstream) connections from the technology category of the macroinvention. In addition, we find no evidence of an increase in technology categories as a result of being upstream from the macroinvention technology category within the innovation network. This second result provides a valuable placebo check that provides additional confidence that our results are picking up the impact of spillovers through the innovation network. Next, we look at whether there are notable differences in the allocation of British and French inventors within the innovation network. In particular, we focus on whether British inventors were patenting in technology categories that were more central within the innovation network than French inventors. We do this by studying, within the sets of British and French patents whether foreign inventors (of British or French origin) were patenting in more central technology categories than domestic inventors. We find that among French patents, patents by British-based inventors were significantly more central compared to the average patents by French domestic inventors—and all other foreign inventors—, whereas among British patents, patents by French-based inventors were less central compared to the average patent by British domestic inventors. The pattern indicates that British inventors were more likely to work in central technology categories than French inventors. As more central nodes have stronger spillover connections to other technology categories, the more central locations occupied by British inventors are consistent with a greater “bang for the buck” of British innovation on the aggregate rate of technological progress. Finally, we quantify the growth implications of the observed innovation network and different allocations of inventors in Britain and France through the lens of the model. Existing estimates for Britain suggest that industrial production grew by between 3 and 3.5% during the first half of the nineteenth century (Broadberry et al., 2015). In France, estimates indicate growth rates of between 1.7 and 2.5% in the same period (Crouzet, 1996; Asselain, 2007). (Preliminary) Results from our quantification exercise show that differences in the allocation of inventors across technology categories led to a technology growth rate in Britain that was between 0.5 and 2.9 percent higher than the French technology growth rate. Thus, our results indicate that Britain’s more advantageous position in the innovation network can explain a substantial fraction, and possibly the entire difference, in growth rates between the British and French economies during the first half of the nineteenth century. In sum, the evidence presented in this paper shows that Britain benefited from an advantageous distribution of inventors across technology sectors during the Industrial Revolution, and that this difference meaningfully contributed to Britain’s more rapid industrialization. Our analysis takes as given the differences in the distribution of inventors across sectors. Thus, our mechanism complements explanations for the British advantage during the Industrial Revolution, in particular those that can explain why British inventors were more likely than the French to work on technologies that happened to be more central 4 within the innovation network, in particular mechanical technologies. For example, it could be that Britain’s practical Enlightenment tradition and well-developed apprenticeship system (Mokyr, 2009; Kelly et al., 2014) contributed to the British inventors’ greater ability for working on mechanical technologies, or that high wages and access to cheap coal steered British inventors to focus on labor-saving mechanical devices (Allen, 2009). Put differently, the contribution of our paper lies in demonstrating that Britain was at the right place in the technology space at the right time, rather than explain why it was there but France was not. In addition to improving our understanding of one of the most important questions in economic history, our study also contributes to work by growth economists on the importance of innovation networks. Relative to studies in this area (cited above), we offer two main contributions. First, we offer new methods that can help researchers study innovation networks further back in history, when standard tools such as systematic patent citations are unavailable. This opens up the possibility of studying the influence of innovation networks in different contexts or over longer periods. Second, our analysis of macroinventions provides additional, more causal, evidence that innovation networks matter for technology development. Third, our application demonstrates empirically the value of recent theoretical advances integrating innovation networks into economic growth models. Our work builds on a long line of literature using patent data to examine innovation during the Industrial Revolution and into the nineteenth century. Early papers in this area include Sullivan (1989) and Sullivan (1990). More recent work includes MacLeod et al. (2003), Khan and Sokoloff (2004), Moser (2005), Khan (2005), Brunt et al. (2012), Nicholas (2011), Nuvolari and Tartari (2011), Moser (2012), Bottomley (2014b), Bottomley (2014a), Burton and Nicholas (2017), Khan (2018), Bottomley (2019), Nuvolari et al. (2020), Nuvolari et al. (2021), Hallmann et al. (2021), and Hanlon (2022). Relative to this extensive literature, we are the first to study the role of innovation networks in influencing inventive activity during the Industrial Revolution.

1 Hallmann et al. (2021) show that technological leadership in invention of Britain relative to France varied across technologies, with Britain leading, besides others, in steam engines and textile technologies, and France leading, besides others, in papermaking and shoemaking. Mokyr (1990, Chapter 5) provides a historical overview on British technological lead or lag in invention relative to Continental Europe.

2 Both of these were periods during which the patent systems were largely stable. We end just before the major British patent reform of 1852 and the French patent reform of 1844.

3  Of course, not every useful invention was patented, as (Moser, 2012) has shown. 

4   A stable institutional environment and well-developed patent system may have contributed in shifting inventors from technologies that can be protected by secrecy toward technologies as mechanical devices that are easily reverse engineered and thus profit the most from patents (Moser, 2005). However, as both Britain and France had strong patent protection, it is unclear how this mechanism could explain the differential focus of British vs. French inventors on mechanical devices.