The relation between complexity and synergy in the case of China: different ways of predicting GDP growth in a complex and adaptive system

Inga Ivanova ()

Quality & Quantity: International Journal of Methodology, 2022, vol. 56, issue 1, No 10, 195-215

Abstract: Abstract The effectiveness of the Triple Helix model of innovations can be evaluated in bits of information using the TH indicator of synergy based on information theory. However synergy, measured in bits of information can’t be straightforwardly interpreted in economic terms. The present paper is an attempt to establish a connection between synergy and other growth relating economic measure, such as complexity indices. The synergy distribution among 31 Chinese territorial districts is compared with corresponding distribution of complexity. The latter are calculated with three different complexity measures and on different datasets. Synergy and complexity show substantial linear relationship with each other. These complexity measures are further tested with their ability to predict future GDP per capita growth using employment, income, and investment data for 31 territorial districts of China and 19 industries. The results of regression analysis suggests that the accuracy of growth forecast can be substantially improved when exploiting links of different origin in bipartite networks in comparison with export oriented approach.

Keywords: Economic complexity; Triple Helix; Synergy; Regression; Economic growth (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11135-021-01118-6 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:spr:qualqt:v:56:y:2022:i:1:d:10.1007_s11135-021-01118-6

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11135

DOI: 10.1007/s11135-021-01118-6

Access Statistics for this article

Quality & Quantity: International Journal of Methodology is currently edited by Vittorio Capecchi

More articles in Quality & Quantity: International Journal of Methodology from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().