Governance and economic growth in Africa: evidence from linear, nonlinear and dynamic panel analysis

Abstract In this paper, we study the impact (if any) of governance quality on economic growth in Africa, using a panel dataset of fifty countries during the period 2008–2017. For this purpose, we use the Ibrahim Index of African Governance (IIAG), which consists of four component indicators related to the (i) safety and rule of law, (ii) participation rights and inclusion, (iii) sustainable economic opportunity and (iv) human development. Instead of simply using its original formulation, which is based on equal weights, we also construct weighted average variants of the IIAG using four distance-based methods and Shannon entropy for such purpose. We then use these variants of the IIAG, including the equal weights formulation, to estimate alternative specifications of an econometric model relating governance quality and economic growth, conditional on several control variables, using fixed effects, linear and nonlinear and dynamic GMM. The results from the linear and dynamic GMM show that, regardless of the aggregation weights used for the IIAG, governance seems to have a significant positive impact on economic growth. On the other hand, in the fixed effects model, we find evidence for a non-monotonic relation, taking a U-shaped (convex) form indicating that countries may benefit from misgovernance.

Authors

Institutions

Publication Details

Journal
Empirical Economics
Published
2025-03-18
DOI
https://doi.org/10.1007/s00181-025-02726-z
Citations
5
Primary Topic
Economic Growth and Development
Type
article
Field-Weighted Citation Impact
16.23
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Governance and economic growth in Africa: evidence from linear, nonlinear and dynamic panel analysis

Giannis Karagiannis, Suzanna‐Maria Paleologou
5 citations
Empirical Economics
Economic Growth and Development
16.23
article

Governance and economic growth in Africa: evidence from linear, nonlinear and dynamic panel analysis

Giannis Karagiannis, Suzanna‐Maria Paleologou
article en
5 citations

Abstract

Abstract In this paper, we study the impact (if any) of governance quality on economic growth in Africa, using a panel dataset of fifty countries during the period 2008–2017. For this purpose, we use the Ibrahim Index of African Governance (IIAG), which consists of four component indicators related to the (i) safety and rule of law, (ii) participation rights and inclusion, (iii) sustainable economic opportunity and (iv) human development. Instead of simply using its original formulation, which is based on equal weights, we also construct weighted average variants of the IIAG using four distance-based methods and Shannon entropy for such purpose. We then use these variants of the IIAG, including the equal weights formulation, to estimate alternative specifications of an econometric model relating governance quality and economic growth, conditional on several control variables, using fixed effects, linear and nonlinear and dynamic GMM. The results from the linear and dynamic GMM show that, regardless of the aggregation weights used for the IIAG, governance seems to have a significant positive impact on economic growth. On the other hand, in the fixed effects model, we find evidence for a non-monotonic relation, taking a U-shaped (convex) form indicating that countries may benefit from misgovernance.

Empirical EconomicsVol. 69(1)
University of Macedonia (GR), Aristotle University of Thessaloniki (GR)
Openalex Percentile: Top 1%
Economic Growth and Development
16.23
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.