Elections and mining taxation in Africa: evidence from a Spatial Durbin Model

Kalo Achille Sanou & Mahamady Ouédraogo

Journal of African Economies2026https://doi.org/10.1093/jae/ejag005article
AJG 2ABDC A
Weight
0.50

Abstract

Mining taxation is challenging and can be subject to electoral manipulations. On the one hand, mining lobbies may provide financial support for electoral campaigns in exchange for favorable tax policies. On the other hand, to appeal to the median voter, candidates may pledge tax reforms aimed at increasing domestic revenue. We test this hypothesis by estimating the effect of elections on the Average Effective Tax Rate (AETR) of gold mining in Africa. Using a Spatial Durbin Model (SDM) on a sample of 20 countries over the period 2000–2020, we find three key results. First, mining AETR exhibits spatial spillovers across the countries in the sample. Second, in accordance with our assumption, presidential elections negatively affect the AETR. The spillover effects on neighboring countries are positive, implying positive externalities on neighboring countries. Third, we show that the effect of electoral cycles differs depending on whether the race involves an incumbent seeking re-election, a non-incumbent candidate following a term-limited president or a non-incumbent stepping in after a political transition. The effect of elections is only significant when an incumbent faces a non-incumbent candidate. These results are robust to a number of robustness checks.

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https://doi.org/https://doi.org/10.1093/jae/ejag005

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@article{kalo2026,
  title        = {{Elections and mining taxation in Africa: evidence from a Spatial Durbin Model}},
  author       = {Kalo Achille Sanou & Mahamady Ouédraogo},
  journal      = {Journal of African Economies},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1093/jae/ejag005},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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