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Economic Geography in R: Introduction to the EconGeo package

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  • Pierre-Alexandre Balland

Abstract

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.

Suggested Citation

  • Pierre-Alexandre Balland, 2017. "Economic Geography in R: Introduction to the EconGeo package," Papers in Evolutionary Economic Geography (PEEG) 1709, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised May 2017.
    • Handle: RePEc:egu:wpaper:1709
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    File URL: http://econ.geo.uu.nl/peeg/peeg1709.pdf
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    1. Yang, Dong & Li, Chengkun & Li, Lu & Lai, Kee-hung & Lun, Venus Y.H., 2022. "Maritime cluster relatedness and policy implications," Transport Policy, Elsevier, vol. 128(C), pages 76-88.
    2. Giuseppe Coco & Daniele Simone & Laura Serlenga & Sabrina Molinaro, 2023. "Risk awareness and complexity in students’ gambling," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 40(3), pages 971-994, October.
    3. Mariane Santos Françoso & Ron Boschma & Nicholas Vonortas, 2024. "Regional diversification in Brazil: The role of relatedness and complexity," Growth and Change, Wiley Blackwell, vol. 55(1), March.
    4. Abbasiharofteh, Milad & Kogler, Dieter F. & Lengyel, Balázs, 2023. "Atypical combinations of technologies in regional co-inventor networks," Research Policy, Elsevier, vol. 52(10).
    5. Pierre-Alexandre Balland & Ron Boschma & Julien Ravet, 2019. "Network dynamics in collaborative research in the EU, 2003–2017," European Planning Studies, Taylor & Francis Journals, vol. 27(9), pages 1811-1837, September.
    6. De Noni, Ivan & Ganzaroli, Andrea & Pilotti, Luciano, 2021. "Spawning exaptive opportunities in European regions: The missing link in the smart specialization framework," Research Policy, Elsevier, vol. 50(6).
    7. Dieter F. Kogler & Ronald B. Davies & Changjun Lee & Keungoui Kim, 2023. "Regional knowledge spaces: the interplay of entry-relatedness and entry-potential for technological change and growth," The Journal of Technology Transfer, Springer, vol. 48(2), pages 645-668, April.
    8. Zhaoyingzi Dong & Yingcheng Li & Pierre-Alexandre Balland & Siqi Zheng, 2022. "Industrial land policy and economic complexity of Chinese Cities," Industry and Innovation, Taylor & Francis Journals, vol. 29(3), pages 367-395, March.
    9. Stefan Apostol & Eduardo Hernández-Rodríguez, 2023. "Digitalisation in European regions: Unravelling the impact of relatedness and complexity on digital technology adoption and productivity growth," Papers in Evolutionary Economic Geography (PEEG) 2317, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Aug 2023.
    10. Matheus E. Leusin & Bjoern Jindra & Daniel S. Hain, 2021. "An evolutionary view on the emergence of Artificial Intelligence," Papers 2102.00233, arXiv.org.
    11. Matheus Eduardo Leusin, 2022. "The Development of Al in Multinational Enterprises - Effects upon Technological Trajectories and Innovation Performance," Bremen Papers on Economics & Innovation 2201, University of Bremen, Faculty of Business Studies and Economics.
    12. Matteo Laffi & Ron Boschma, 2022. "Does a local knowledge base in Industry 3.0 foster diversification in Industry 4.0 technologies? Evidence from European regions," Papers in Regional Science, Wiley Blackwell, vol. 101(1), pages 5-35, February.
    13. F. Colozza & R. Boschma & A. Morrison & C. Pietrobelli, 2021. "The importance of global value chains and regional capabilities for the economic complexity of EU-regions," Papers in Evolutionary Economic Geography (PEEG) 2139, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Dec 2021.
    14. Carla Carolina Pérez-Hernández & Blanca Cecilia Salazar-Hernández & Jessica Mendoza-Moheno & Erika Cruz-Coria & Martín Aubert Hernández-Calzada, 2021. "Mapping the Green Product-Space in Mexico: From Capabilities to Green Opportunities," Sustainability, MDPI, vol. 13(2), pages 1-25, January.
    15. María Guadalupe Montiel-Hernández & Carla Carolina Pérez-Hernández & Blanca Cecilia Salazar-Hernández, 2024. "The Intrinsic Links of Economic Complexity with Sustainability Dimensions: A Systematic Review and Agenda for Future Research," Sustainability, MDPI, vol. 16(1), pages 1-26, January.
    16. Jason Deegan & Tom Broekel & Rune Dahl Fitjar, 2021. "Searching through the Haystack:The Relatedness and Complexity of Priorities in Smart Specialization Strategies," Economic Geography, Taylor & Francis Journals, vol. 97(5), pages 497-520, October.
    17. Eduardo Hernandez-Rodriguez & Ron Boschma & Andrea Morrison & Xianjia Ye, 2023. "Functional upgrading and downgrading in global value chains: Evidence from EU regions using a relatedness/complexity framework," Papers in Evolutionary Economic Geography (PEEG) 2316, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Jul 2023.
    18. Nils Grashof & Stefano Basilico, 2023. "The dark side of green innovation? Green transition and regional inequality in Europe," Papers in Evolutionary Economic Geography (PEEG) 2314, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Jun 2023.
    19. Pintar, Nico & Scherngell, Thomas, 2022. "The complex nature of regional knowledge production: Evidence on European regions," Research Policy, Elsevier, vol. 51(8).
    20. Belmartino, Andrea, 2022. "Green & non-green relatedness: challenges and diversification opportunities for regional economies in Argentina," Nülan. Deposited Documents 3697, Universidad Nacional de Mar del Plata, Facultad de Ciencias Económicas y Sociales, Centro de Documentación.
    21. Roberto Antonietti & Chiara Burlina, 2023. "Exploring the entropy-complexity nexus. Evidence from Italy," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 40(1), pages 257-283, April.
    22. Apa, Roberta & De Noni, Ivan & Orsi, Luigi & Sedita, Silvia Rita, 2018. "Knowledge space oddity: How to increase the intensity and relevance of the technological progress of European regions," Research Policy, Elsevier, vol. 47(9), pages 1700-1712.

    More about this item

    Keywords

    Economic Geography; Economic Complexity; Evolutionary Economics; Network Science; R; EconGeo package;
    All these keywords.

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