While it is well understood that productivity growth is crucial for sustaining increasing income per capita over time, there is less consensus about how different factors contribute to it. Innovation is widely considered to play a key role, and the Industrial Revolution boasts a host of new technologies such as the steam engine and the spinning jenny. In light of this, previous research has focused extensively on the role that these new inventions played in the onset of sustained economic growth in parts of Western Europe in the late 18th and early 19th century. Nevertheless, a key limitation of previous studies was the level of data availability, restricting research to the level of countries or, at best, aggregate industrial sectors within countries. However, contemporaneous research has shown that firm dynamics are a key element of aggregate productivity growth. In particular, country-wide productivity tends to grow if resources are allocated to the most productive firms, i.e., if productive firms grow more quickly than less productive ones. To date, understanding how firm dynamics evolved during the Industrial Revolution and what effect this had on productivity growth has been inhibited by the lack of firm level data. This project aims at filling this important gap by building a novel dataset of French firms. The dataset will follow firms across time, in a number of different industries during the Industrial Revolution. This dataset will allow the investigators -- and future researchers -- to examine the transition from stagnation to ongoing growth in unprecedented detail.
This project takes an important step towards understanding how firm dynamics evolved during the Industrial Revolution by assembling an original dataset with comprehensive coverage of French firms for the period 1788-1847. The dataset will be unique in several dimensions: (1) it will cover firms in a wide set of industries, including highly innovative and less innovative sectors; (2) within industries, the data will cover firms along different stages of the production chain -- for example, in the cotton industry, data on spinning, weaving, and dyeing firms will be available; (3) since firm name and location are available, a panel-like structure can be created, allowing for the use of firm fixed effects and the study of entry and exit; (4) the fact that regional data (and firm location) are known can also be used to investigate agglomeration effects. The usefulness of the data collection in this project is not confined to studying productivity growth during industrialization. It will also be valuable to study the effects of trade integration, the role of misallocation of resources, as well as the relationship between social and institutional change and economic development.