Trade and Technology Diffusion
Friday, Jan. 5, 2018 8:00 AM - 10:00 AM
- Chair: Felix Tintelnot, University of Chicago
The Spatial Diffusion of Knowledge
Dancing With the Stars: Innovation and Human Capital Accumulation Through Interactions
AbstractDoes interacting with others contribute to human capital accumulation? We try to answer this question by using a new panel dataset on European inventors matched to their employers and patents since the 1980s. We first document some key empirical facts in the data that motivate the key ingredients in our model. Most patents are the result of collaborative work. More interactions are very strongly correlated with higher subsequent productivities of inventors, especially interactions with superstars. We build an innovation-led growth model in which inventors can learn in two ways: by meeting other inventors, at an endogenously chosen rate, and through an exogenous, age-dependent process that can capture alternative learning channels, such as learning-by-doing. We estimate our model using indirect inference and obtain a very close fit to the data. Overall, the endogenous interaction channel among inventors accounts for almost 60% of overall economic growth.
Immigration, Growth and the Diffusion of Technology
AbstractDespite the extensive literature on the short-run consequences of immigration, the long-run effects of immigration have so far received less attention. This project aims to complement the literature by analyzing the long-run impacts of one the biggest migration episodes in modern time: the era of Mass Migration (1850-1913). While the arrival of immigrants can affect the local economy in various ways, we focus on the role of business creation and the importance of immigrants for the transmission of knowledge. In particular, we aim to analyze whether immigrants from the European continent brought novel ideas and technologies to the US and then used such ideas to start their own companies. The answer to this question is not only of historical interests but will also shed light on the extent to which technologies and knowledge are spatially mobile and whether entrepreneurs can play an important role in the diffusion process.
To measure the relationship between immigrants' knowledge, the extent of entrepreneurship and local
productivity, we propose a big data approach by digitizing and linking three types of historical data
1. Immigration Databases: The Hamburg Passenger List (1850-1934) & Castle Garden Immigration
2. The US complete-count individual-level demographic census data (1850 - 1940, every decade except
3. The Historical Census of Manufacturers (1860-1940, every decade): published statistics at the county
and city level
Our starting point are the official immigration records from the Hamburg Passenger Lists and Castle Garden Immigration Database. These databases contain detailed information on millions of immigrants who arrived in the US in the 19th and early 20th century. Importantly, these records contain information on the immigrants' occupations, their sector of employment and their last residence in Europe prior to their arrival in the US. We plan to use this information, together with existing information on spatial economic development in Europe, to impute the quality of immigrants' existing knowledge. Intuitively, immigrants
with work experience in a particular industry from the regions where that particular industry was vibrant were arguably more exposed to the frontier technology in that sector relative to other immigrants.
- A1 - General Economics