Peer-reviewed publications
For detailed citation information, check out my Google Scholar profile.
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Abstract: Can we use data on the biographies of historical figures to estimate the GDP per capita of countries and regions? Here, we introduce a machine learning method to estimate the GDP per capita of dozens of countries and hundreds of regions in Europe and North America for the past seven centuries starting from data on the places of birth, death, and occupations of hundreds of thousands of historical figures. We build an elastic net regression model to perform feature selection and generate out-of-sample estimates that explain 90% of the variance in known historical income levels. We use this model to generate GDP per capita estimates for countries, regions, and time periods for which these data are not available and externally validate our estimates by comparing them with four proxies of economic output: urbanization rates in the past 500 y, body height in the 18th century, well-being in 1850, and church building activity in the 14th and 15th century. Additionally, we show our estimates reproduce the well-known reversal of fortune between southwestern and northwestern Europe between 1300 and 1800 and find this is largely driven by countries and regions engaged in Atlantic trade. These findings validate the use of fine-grained biographical data as a method to augment historical GDP per capita estimates. We publish our estimates with CI together with all collected source data in a comprehensive dataset.
Link (Open Access), Interactive website, Data and code, Radio interview (in german)
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Abstract: Despite global efforts to harmonize international trade statistics, our understanding of digital trade and its implications remains limited. Here, we introduce a method to estimate bilateral exports and imports for dozens of sectors starting from the corporate revenue data of large digital firms. This method allows us to provide estimates for digitally ordered and delivered trade involving digital goods (e.g. video games), productized services (e.g. digital advertising), and digital intermediation fees (e.g. hotel rental), which together we call digital products. We use these estimates to study five key aspects of digital trade. We find that, compared to trade in physical goods, digital product exports are more spatially concentrated, have been growing faster, and can offset trade balance estimates, like the United States trade deficit on physical goods. We also find that countries that have decoupled economic growth from greenhouse gas emissions tend to have larger digital exports and that digital exports contribute positively to the complexity of economies. This method, dataset, and findings provide a new lens to understand the impact of international trade in digital products.
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Abstract: Did migrants make Paris a mecca for the arts and Vienna a beacon of classical music? Or was their rise a pure consequence of local actors? We use data on more than 22,000 historical individuals born between the years 1000 and 2000 to estimate the contribution of famous immigrants, emigrants and locals to the knowledge specialisations of European regions. We find that the probability that a region develops or keeps specialisation in an activity (based on the birth of famous physicists, painters, etc.) grows with both the presence of immigrants with knowledge about that activity and immigrants with knowledge in related activities. In contrast, we do not find robust evidence that the presence of locals with related knowledge explains entries and/or exits. We address some endogeneity concerns using fixed-effects models considering any location–period–activity-specific factors (e.g., the presence of a new university attracting scientists).
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Abstract: To achieve inclusive green growth, countries need to consider a multiplicity of economic, social, and environmental factors. These are often captured by metrics of economic complexity derived from the geography of trade, thus missing key information on innovative activities. To bridge this gap, we combine trade data with data on patent applications and research publications to build models that significantly and robustly improve the ability of economic complexity metrics to explain international variations in inclusive green growth. We show that measures of complexity built on trade and patent data combine to explain future economic growth and income inequality and that countries that score high in all three metrics tend to exhibit lower emission intensities. These findings illustrate how the geography of trade, technology, and research combine to explain inclusive green growth.
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Abstract: This study investigates the effects of Park & Ride (P&R) facilities, which aim to increase the attractiveness of commuting by public transport, on population growth in suburban areas. We employ a difference-in-differences approach to parking capacity extensions of seven P&R facilities outside the central business district of the city of Vienna between 2012 and 2016. Specifically, using fine-grained grid population data, we compare population growth in close distance to the P&R facility to population growth in surrounding municipalities. We find that the expansion of a P&R facility, which is located at least 20 min away from a main public transport station in Vienna, causes population growth of, on average, 1.6–1.9% in neighbouring municipalities compared to those where the P&R facility is located. This accounts for up to 15% of the total population growth in the respective regions between 2008 and 2019 and highlights the role of P&R facilities in fostering suburbanization and the suburban sprawl.
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Abstract: In economic literature, economic complexity is typically approximated on the basis of an economy’s gross export structure. However, in times of ever increasingly integrated global value chains, gross exports may convey an inaccurate image of a country’s economic performance since they also incorporate foreign value-added and double-counted exports. Thus, I introduce a new empirical approach approximating economic complexity based on a country’s value-added export structure. This approach leads to substantially different complexity rankings compared to established metrics. Moreover, the explanatory power of GDP per capita growth rates for a sample of 40 lower-middle- to high-income countries is considerably higher, even if controlling for typical growth regression covariates.
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Abstract: We introduce the Industry Space based on value-added exports as a complementary visualisation of economic development and structural cross-country differences to the established Product Space, which relies on gross exports. Since value-added exports disentangle global and national value chains, we argue they enable a more accurate and holistic depiction of an economy’s capabilities. Specifically, the Industry Space links 51 industries to each other based on the similarity in required capabilities. We emphasize the need for value-added exports by providing evidence that using gross exports significantly changes the similarities between industries. Applying the concept to comparative country case studies, we show that the Industry Space is a useful tool to investigate the economic structure between countries and over time.