Augmenting the availability of historical GDP per capita estimates through machine learning.

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 econo

SUBMITTER: Koch P 

PROVIDER: S-EPMC11441543 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature