Pierre-Alexandre Balland

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The R statistical software is increasingly used to perform analysis on the spatial distribution of economic activities. It contains state-of-the-art statistical and graphical routines not yet available in other software such as SAS, Stata, or SPSS. R is also free and open-source. Many graduate students and researchers, however, find programming in R either too challenging or end up spending a lot of their precious time solving trivial programming tasks. This paper is a simple introduction on how to do economic geography in R using the EconGeo package (Balland, 2017). Users do not need extensive programming skills to use it. EconGeo allows to easily compute a series of indices commonly used in the fields of economic geography, economic complexity, and evolutionary economics to describe the location, distribution, spatial organization, structure, and complexity of economic activities. Functions include basic spatial indicators such as the location quotient, the Krugman specialization index, the Herfindahl or the Shannon entropy indices but also more advanced functions to compute different forms of normalized relatedness between economic activities or network-based measures of economic complexity. By opening and sharing the codes used to compute popular indicators of the spatial distribution of economic activities, one of the goals of this package is to make peer-reviewed empirical studies more reproducible by a large community of researchers.

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