Multidimensional economic complexity and inclusive green growth
Viktor Stojkoski,
Philipp Koch and
Cesar Hidalgo
Additional contact information
Philipp Koch: TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - UT - Université de Toulouse - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement
Post-Print from HAL
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.
Keywords: Developing world; Economics; Environmental economics; Geography (search for similar items in EconPapers)
Date: 2023-04-21
References: Add references at CitEc
Citations: View citations in EconPapers (6)
Published in Communications Earth & Environment, 2023, 4 (1), pp.130. ⟨10.1038/s43247-023-00770-0⟩
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
Working Paper: Multidimensional Economic Complexity and Inclusive Green Growth (2023) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-04361715
DOI: 10.1038/s43247-023-00770-0
Access Statistics for this paper
More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD ().