Abstract
Using aggregate data from 31 Organization for Economic Co-operation and Development (OECD) countries covering periods from 1982 to 2017, this study examines the notion that the level of product complexity is a good determinant of economic growth in the long run. We use the impulse-response function (IRF) computed from the consistent generalized method of moment panel vector autoregressive (GMM pVAR) model to estimate the response of the real output growth to a change in the economic complexity index. The IRF shows that the economic complexity index has a significant impact on economic growth; a 1 standard deviation shock to the economic complexity index at time 0 contributes around 2.34 percentage points to the average rate of growth of output within the first period. The point estimates are positive and significant up to the third period. The cumulative IRF shows that the aggregate impact on economic growth is about 4.4% in the long run. Compared to some widely used innovation proxies such as the gross expenditure on research and development and secondary school enrollment, the economic complexity index performs relatively better in our model in determining economic growth in the long run.
Original language | English |
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Pages (from-to) | 1-16 |
Number of pages | 16 |
Journal | Sage Open |
Volume | 11 |
Issue number | 3 |
DOIs | |
Publication status | Published - 1 Jul 2021 |
Externally published | Yes |
Bibliographical note
Creative Commons CC BY: This article is distributed under the terms of the Creative Commons Attribution 4.0 License(https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages
(https://us.sagepub.com/en-us/nam/open-access-at-sage).
Publisher Copyright:
© The Author(s) 2021.
Keywords
- capital accumulation
- economic complexity
- endogenous growth
- Granger causality
- panel vector autoregression