The Dynamic Theory of Economic Complexity
Cesar Hidalgo and
Viktor Stojkoski
Papers from arXiv.org
Abstract:
Why do some activities grow faster in some economies than others? We develop a dynamic model of economic complexity in which output is determined by a weak-link production function and investment contributes to the accumulation of capabilities shared across activities. We test the model empirically by exploring two of its predictions. First, the model predicts that the capability stock at which the accumulation of a capability is fastest increases with the capability requirements of an activity. This implies a transition from unconditional to conditional convergence and a tunable conditional convergence regime. Second, shared capabilities provide a mechanism for path-dependent diversification (the principle of relatedness), including signs for the expected interaction terms between relatedness and complexity terms in regressions exploring growth by economy and activity. We evaluate these predictions using international trade, and sub-national industry data from the United States and Brazil, finding empirical patterns that are broadly consistent with both. Together, these results provide a dynamical foundation for economic complexity theory and help explain how capability stocks and shared capabilities shape differences in the growth of activities across economies.
Date: 2025-12, Revised 2026-11
New Economics Papers: this item is included in nep-tid
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
https://arxiv.org/pdf/2512.10672 Latest version (application/pdf)
Related works:
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:arx:papers:2512.10672
Access Statistics for this paper
More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().