Are average years of education losing predictive power for economic growth? An alternative measure through structural equations modeling
- Henry Laverde-Rojas,
- ,
- Klaus Jaffe,
- Mario I. Caicedo
- Fundación Universitaria Konrad Lorenz,
- Universidad Simón Bolívar
Research Output:
Contribution to journal
Article
Peer-reviewOpen access
Sustainable Development Goals
- SDG 8 Decent Work and Economic Growth
Publication metrics
Metrics
SciVal
FWCI
0.36
SciVal
Author count
4
SciVal
Paper percentile
45
SciVal
Citations
14
PlumX, opens in new tab
Mentions
1
Citations
14
Social media
42
Captures
41
Abstract
The accumulation of knowledge required to produce economic value is a process that often relates to nations economic growth. Some decades ago many authors, in the absence of other available indicators, used to rely on certain measures of human capital such as years of schooling, enrollment rates, or literacy. In this paper, we show that the predictive power of years of education as a proxy for human capital started to dwindle in 1990 when the schooling of nations began to be homogenized. We developed a structural equation model that estimates a metric of human capital that is less sensitive than average years of education and remains as a significant predictor of economic growth when tested with both cross-section data and panel data.
Publication Information
Output type
Research Output:
Contribution to journal
Article
Peer-reviewOriginal language
EnglishArticle number
e0213651Pages from-to (Number of pages)
Pages e0213651Journal (Volume, Issue Number)
PLoS One (Volume 14, Issue 3)Publication milestones
- Published - 21/03/2019
Publication status
Published - 21/03/2019
ISSN
1932-6203Publication IDs
- ORCID: /0000-0002-0301-5641/work/55562363
- PubMed: 30897113
- Scopus: 85063356610
Funding Details
The authors wish to thank the academic editor and anonymous reviewers for their insightful comments and recommendations for enhancing the quality and rigor of this paper. The authors are indebted to Universidad Santo Tomás (Bogotá, Colombia), Fundación Universitaria Konrad Lorenz (Bogotá, Colombia), and Universidad Simón Bolívar (Caracas, Venezuela) for providing us with the facilities to conduct the analyses.
FundersFunding numbers
USB
-Fundación Universitaria Konrad Lorenz
-