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F E A T U R E D A R T I C L E
How do current and past mining activities
affect water security, health, and
economic opportunities?
Raymond Boadi Frempong1
|
David Stadelmann2
|
Djiby Racine Thiam3
1European School of Political and Social Sciences (ESPOL), Université Catholique de Lille, Lille, France
2University of Bayreuth, Bayreuth, Germany
3Water and Production Economics Unit, School of Economics, University of Cape Town, Cape Town, South Africa
Correspondence
David Stadelmann, University of
Bayreuth, Bayreuth, Germany.
Email: david.stadelmann@uni-bayreuth.
de.
Funding information
Deutsche Forschungsgemeinschaft (DFG,
German Research Foundation),
Grant/Award Number: EXC 2052/
1 - 390713894
Editor in charge: Gopinath Munisamy
[Correction added on 14 April 2025, after
first online publication: The article
classification has been updated in this
version.]
Abstract
This paper investigates the effect of mining activities on
health care, income and water deprivations in Africa.
By combining household data with mining locations,
we conducted an econometric analysis to assess the
impact of mining on self-reported water security,
health, and economic opportunities for 142,838 house-
holds. Our study utilizes the presence of active and
inactive mines to measure the effects of household
exposure to mining activities. We observe that proxim-
ity to active mining sites is associated with self-reported
improved water security, access to health, and eco-
nomic opportunities. Instrumental variable estimates
support a causal interpretation of our results. Specifi-
cally, households located within a 50 km radius of
active mines reported a 4% lower probability of lacking
clean water. Our findings also reveal that robust local
institutions not only enhance water security but also
mitigate the negative health impacts associated with
mine closures. These results suggest that strengthening
Received: 21 March 2024
Accepted: 26 December 2024
DOI: 10.1002/aepp.13510
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and
reproduction in any medium, provided the original work is properly cited.
© 2025 The Author(s). Applied Economic Perspectives and Policy published by Wiley Periodicals LLC on behalf of Agricultural & Applied
Economics Association.
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Appl Econ Perspect Policy. 2025;47:586–601.
wileyonlinelibrary.com/journal/aepp
local governance can amplify the potential benefits of
mining operations. Therefore, we recommend the
strengthening of local government institutions to foster
the resilience of vulnerable mining communities.
K E Y W O R D S
Africa, health, livelihood, mining, poverty, WASH
J E L C L A S S I F I C A T I O N
D7, L8
The World Health Organization's estimate that a third of Africans face water insecurity
(WHO, 2023) underscores a critical public health concern, given the direct linkages between
water, sanitation, and hygiene (WASH) and welfare indicators like health, education, income,
and poverty. MacAlister et al. (2023) highlight that around 13 African countries are in a state of
critical water insecurity, a situation that could be exacerbated by other existing conditions such
as growing urbanization, expansion of mining activities, climate change, water pollution, etc.
These conditions could derail the continent's progress toward achieving the Sustainable Devel-
opment Goals.
In this context, our paper delves into the impact of mining operations on water security,
health, and income opportunities in Africa while also examining the role of local governance in
this dynamic. Mining plays a significant role in many African economies, contributing approxi-
mately 28% to GDP, and minerals represent between 30% and 70% of the continent's total
exports (AFDB & ANRC, 2016; Signé & Johnson, 2021). Several African countries are well end-
owed with mineral resources (i.e., copper, diamond, gold, iron, silver, uranium, etc.), rep-
resenting critical inputs to manufacturing industries, mainly outside the continent. While
providing employment and supporting local communities through WASH projects, the mining
sector's interaction with water resources, in particular, poses water security and health risks
(Kunz, 2020). The industry's reliance on water for operations like dust suppression, equipment
washing, and cooling could pollute surface and groundwater, posing direct and indirect health
risks. Water pollution through acid mine drainage (AMD) is also a frequent negative effect asso-
ciated with weakly regulated mining practices. From exploration to closures, mining operations
have tangible impacts on water security, health, and income generation opportunities.
The impact of mining on water security, health, and economic outcomes presents a complex
and multifaceted challenge. Unsurprisingly, mineral extraction is often associated positively
with water pollution in developing countries but also in developed regions (Cianciolo
et al., 2020; Kang et al., 2024; Mhlongo et al., 2018). At the same time, some studies suggest that
mineral resource extraction can exacerbate economic challenges, including poverty and
inequality (e.g. Brückner, 2010). Nevertheless, other research focusing on economic outcomes
offers more positive prospects, indicating that there are potential poverty-reducing and employ-
ment effects of resource extraction (Ekanayake et al., 2023; Gollin et al., 2016). Microlevel stud-
ies from different countries and regions suggest that mining activities can positively influence
poverty alleviation and have positive effects on health and job creation (Chavez, 2023; Fisher
et al., 2009; Ge & Lei, 2013; Yadav et al., 2019). Dietler et al. (2021) highlight the link between
mining and enhanced access to water and sanitation facilities. Cossa et al. (2022) suggest a
HOW CURRENT AND PAST MINING ACTIVITIES AFFECT WATER
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nonlinear effect of mining on child health, with initial improvements overshadowed by later-
stage insecurity and pollution. Diallo (2023) notes declining welfare post-mine closure, showing
the need for sustainable community support. Bertinelli and Bourgain (2023) also document that
residents in mining communities have a sense of structural disadvantage. Social trust is also
negatively affected by large-scale land and mining investments in Africa.
We contribute to the existing literature by examining the effects of both active and inactive
activities on individual welfare indicators (Dietler et al., 2021; Wegenast & Beck, 2020), specifi-
cally focusing on water quality, health, and income opportunities in Africa. We hypothesize
that conditional on other covariates of household welfare, mining activities in the vicinity of
households may increase income-generating opportunities. Notwithstanding, the impact of
mining on water security and health is ambiguous. On the one hand, mining poses challenges
related to pollution and potential direct health effects. On the other hand, investments and gen-
eral economic improvements driven by mining activities may also improve water security and
health, at least, as experienced by nearby households (Syahrir et al., 2021). We expect that min-
ing activities in areas with strong local government institutions will yield more positive out-
comes. This aligns with recent findings by Konte and Vincent (2021), who explored the local
effects of mining on the quality of public services and residents' optimism about future living
conditions in Africa, highlighting the moderating role of local institutions. Their results suggest
that residents of mining communities that exhibit low corruption levels experience the highest
rates of positive approval. Our study aims to systematically deepen the understanding of these
dynamics by focusing on the microlevel impacts of mining on self-reported measures of water
security, health, and income thereby adding a new perspective to the existing literature.
An additional contribution of our paper is its household-centric approach, utilizing lived
experiences of scarcities—water, medicine (health), and income—as indicators of overall house-
hold well-being. Thus, we explore the effects of mining on three welfare indicators. We argue
that these self-reported variables provide an accurate reflection of the actual deprivation experi-
enced by households. Leveraging a large sample of 142,838 households across Africa in 2005
and 2015, we investigate the impact of active mines in the vicinity of households on self-
reported access to clean water, and medicine, as well as whether households have gone without
income. We also compare the results for active mines with those for inactive mines. Addition-
ally, we place significant emphasis on the role of local governance and institutions, which prove
to be relevant in our analysis.
Our empirical analysis reveals that proximity to active mining sites is associated with
enhanced water security, better access to health care, and increased economic opportunities.
These findings remain robust even after controlling for factors such as employment status
and whether a household is located in an urban area. However, the effect is lower and some-
times insignificant when mines become inactive or are located farther from the household
(50–100 km). We also observe a decline in self-reported water security when mines cease
operations or are situated at greater distances. The positive effects of mining on income
opportunities persist even after mines cease operations, indicating that mining can have lon-
ger term benefits for income generation. The use of instrumental variable estimates supports
a causal interpretation of these relationships. By integrating this household-level data with
specific locations of mining operations, our analysis offers a more detailed and rebust exami-
nation of the relationship between mining and its effects on household welfare. This approach
allows us to shed light on the direct implications of mining activities on water security,
health, and income.
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Furthermore, we contribute to the literature on the importance of institutions for house-
hold welfare in Africa by examining the role of local institutional quality as perceived by
household members themselves. Existing evidence suggests that institutional quality may
moderate the impact of mineral resources on national poverty (Kansheba & Marobhe, 2022;
Oluwaseyi Musibau et al., 2022). This means that the quality of local governance may be rele-
vant in moderating the effects of resource extraction on community livelihoods. Local offi-
cials, due to their proximity to mining activities, are key in enforcing environmental
regulations and addressing mining-related community problems. Furthermore, the effective-
ness of local governance may affect the management and sustainability of essential services
and infrastructure, including water and health facilities. Diallo (2023) and Syahrir et al.
(2021) advocate for enhanced collaboration between mining companies and regional govern-
ments for post-mining sustainable community development to prevent the reversal of secured
economic and social benefits that took place during operations. Our results, based on
Afrobarometer surveys, show some moderation effects between active mining operations and
local institutions, in particular, active mines may help to reduce the negative effects of local
corruption on water security, health, and incomes.
In the subsequent sections we first discuss the data and the empirical strategy. Then
we show how proximity to active and inactive mines affects water security,
access to
health, and economic opportunities. Next the analysis is extended to investigate the
effect of local institutions. The last section offers concluding remarks.
DATA AND EMPIRICAL STRATEGY
Data
Our study merges two data sources to obtain a unique dataset to explore the effect of mining on
water security, health, and income.
First, we obtain individual socioeconomic data from the Afrobarometer surveys. The
Afrobarometer surveys, conducted repeatedly across Africa, gather public opinion, perceptions
of welfare as well as deprivation indicators which are all self-reported. These surveys provide
consistent data on individual responses to questions related to water security, access to health,
and whether individuals have gone without income. We utilize data from survey rounds three
to six (2005–2015), chosen for their consistency which allows us to address our research ques-
tions. Our household data is geo-coded (see also Wild & Stadelmann, 2022) so that we can
establish where households live. This allows us to merge data from Afrobarometer consistently
with our second data source.
We obtain mining location information from the Africa-PowerMining project (World
Bank, 2018). The mining data comprises 435 records of mining operations across 28 African
countries, sourced from the United States Geological Survey. The Africa-PowerMining project
offers detailed information on each mining site, including the deposit name, location, and other
key characteristics. This dataset categorizes mines based on the nature of their production activ-
ity and whether they are active producers or past producers.
We merge our geo-coded mining data with the geo-coded Afrobarometer data on house-
holds obtaining a dataset with up to 142,838 observations.
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Dependent variables: Household water security, health, and income
We explore three different dependent variables that can all be seen as measures of deprivation
(or conversely, individual well-being) as reported by the survey participants.
Our first dependent variable, household self-reported water security, is quantified using a
binary measure. A value of one (indicating water insecurity) is assigned if a household has
experienced a lack of adequate clean water at least once in the past 12 months.1 During data
collection, respondents indicated the frequency of water scarcity their household faced, ranging
from “never” (0) to “always” (4). Those who reported “never” facing water scarcity are coded as
zero, signifying clean water security. This measure is relevant as water security can be directly
linked to health outcomes, with inadequate clean water access posing significant health risks.
Moreover, we examine the impact of mining activities on self-reported health. The health
variable is structured similarly to the water security measure.2 A household is considered
deprived of health if it has gone without medicines or medical treatment in the last 12 months.
Finally, we also explore economic opportunities by investigating whether a household was
marked by insufficient cash income in the last 12 months.3
Independent variables: Active and inactive mining operation
To assess the impact of mineral resource extraction on WASH and, more broadly, self-reported dep-
rivation, we measure a household's exposure to active and inactive mining operations. More pre-
cisely, we create a 50 km buffer around each household in the Afrobarometer dataset and count the
number of mining operations within this radius. We then extend this to a 50–100 km radius, for-
ming two distinct exposure variables for our first analyses: (1) the number of mining operations
within a 0–50 km radius, a standard distance used in Konte & Vincent. (2021), and (2) the number
within a 50–100 km radius, ensuring these two ranges are mutually exclusive. This allows us to
investigate the relationship between the concentration of mining activities and self-reported welfare.
We hypothesize that the effects of mining on household water security may vary with distance.
While mining can lead to environmental pollution in a wider area, the benefits, such as employ-
ment and access to health projects, might mainly benefit those in closer proximity to mines.
We also investigate inactive mines as an additional independent variable and compare the
results across our different dependent variables for both active and inactive mines. The influence
of mining on self-reported water security may also be contingent on the operational status of the
mines. Both active and inactive mines pose risks of polluting nearby water sources. However, the
community's capacity to mitigate these effects would be a function of the status of the mines.
Active mines might offer employment, enabling residents to afford clean water, and companies
might directly invest in WASH projects. In contrast, these benefits often disappear when mines
close their operations, leaving communities vulnerable to ongoing environmental hazards like
wastewater spillage or AMD. Therefore, distinguishing between active and inactive mines allows
us to differentiate these varying impacts on water security and overall community well-being.
Descriptive statistics
We systematically account for a range of control variables in our empirical analysis, including
schooling, whether a household resides in an urban area and employment status. This allows
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us to isolate the effect of active and inactive mines in the vicinity on our dependent variables of
interest.
Table 1 presents an overview of the variables used in our analysis and gives relevant descrip-
tive statistics. A list of countries included in our dataset is provided in Table A-XIII in the
Appendix. The incidence of perceived water poverty/insecurity is about 36% in the sample.
About 38% of households reported not having access to medicine and medication, and income
levels were perceived as inadequate for about 65% of the sampled households. Regarding mines,
there are 0.27 mines in the 0–50-kilometer radius of a household and there is on average more
than one mine in the 0–100 km radius of a household. There are more active (0.24) than inac-
tive (0.03) mines in the immediate vicinity (0–50 km) of the household. About 39% of house-
holds in the sample are in urban areas. We also account for basic infrastructure variables in the
vicinity, as these may impact the self-reported dependent variables related to water security,
health, and income. Additionally, since these infrastructure variables might be influenced by
mining activities, we aim to ensure that our estimated effects of mining are independent of such
basic infrastructure factors by accounting for them in the empirical analysis.
TABLE 1
Descriptive statistics.
Variable
Mean
SD
Min
Max
Dependent variables
Household gone without clean water
0.36
0.48
0.00
1.00
Household gone without medicines (or medical treatment)
0.38
0.49
0.00
1.00
Household gone without a cash income
0.65
0.48
0.00
1.00
Independent variables (controls)
All mines within 50 km radius
0.27
1.39
0.00
32
All mines within a 50–100 km radius (ActiveMine)
0.79
3.30
0.00
52.00
Active mines within a 50 km radius
0.24
1.15
0.00
22.00
Inactive within a 50 km radius
0.03
0.39
0.00
13.00
Secondary school
0.49
0.50
0.00
1.00
Urban residence
0.39
0.49
0.00
1.00
The community has paved roads
0.47
0.50
0.00
1.00
Market in the primary enumeration unit
0.63
0.48
0.00
1.00
Clinic in the primary enumeration unit
0.58
0.49
0.00
1.00
Piped water in the primary enumeration unit
0.54
0.50
0.00
1.00
Electricity in the primary enumeration area
0.60
0.49
0.00
1.00
Male respondent
0.50
0.50
0.00
1.00
Age of respondent
36.98
14.61
18.00
130.00
Respondent is employed
0.37
0.48
0.00
1.00
Regional corruption (local councillors) score
2.39
0.37
1.18
3.66
Regional corruption (tax officials) scores
2.43
0.35
1.17
3.78
Region local disapproval score
2.50
0.35
1.14
3.81
Note: Own calculation, computed from the dataset with Afrobarometer 3–5 (2005–2015) and Africa-PowerMining project.
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Regarding demographics, there are as many males as female respondents in the sample. On
average, less than half (48%) of the sample have secondary school education. While most house-
holds live in rural areas, coverage of social amenities and infrastructure like markets, clinics,
piped-borne water, and electricity is more than half of the population. For example, 59% of
households have access to electricity, 54% have access to piped water, 63% live in communities
with markets, and 58% live in communities with clinics.
The indicators of regional institutional quality variables are a 1–4 scale where 4 represents
the worst score. Table 1 shows that for all three indicators, the average in the sample is greater
than two. This means that respondents tend to score their local government as somewhat cor-
rupt and exhibit a sentiment of disapproval toward their representatives. For instance, the dis-
approval score is 2.5 which is 0.5 points higher than the theoretical mean of 2.0.
Empirical strategy
We explore the effect of active and inactive mines on our main dependent variables water secu-
rity, health, and gone without income. Our main estimation equation is a linear probability
model, stated as follows:
WSit ¼ αþβ1ActiveMineit þβ2InactiveMineit þIND0
itβþPSU0
itΘþCþtþϵi
WS represents the household's i at time t welfare/deprivation indicator (gone without clean
water, medicine, and income). ActiveMine indicates the number of active mines within a speci-
fied geographical area near household i while InactiveMine indicates the number of inactive
mines in the same area near household i. We also vary the vicinity of the mines, that is, we
explore active (closed) mines in a vicinity of a 50 km radius as well as a 50-100 km radius
jointly. IND is a vector encompassing individual-level characteristics of the respondent, includ-
ing for example at least secondary education and employment status. The vector PSU includes
community-level controls, and C and t represent country and time-fixed effects, respectively. By
including country and time-fixed effects we aim to capture the aggregate effects of, for example,
macroeconomic shocks. Control variables represent all variables listed in Table 1.
We aim to investigate the impact of active and inactive mine proximity on water security,
health, and income. The literature presents mixed expectations regarding the sign of this coeffi-
cient with respect to our indicators. On one hand, studies like Wegenast and Beck (2020) have
identified the negative impacts of mining on food security among women in Africa. Addition-
ally, mineral resource extraction might lead to environmental degradation, such as water pollu-
tion and deforestation, potentially impairing access to water and fuel. On the other hand, the
mining sector is a major employer in Africa, suggesting that proximity to mines could boost
household earnings. Mines may also stimulate local economic activities through backward and
forward linkages, thereby positively influencing the local economy. As a result, the effect of
active mines cannot be predetermined and must be examined empirically. In fact, while mining
may lead to potential environmental damage, it is also possible that access to clean water
increases in the vicinity due to investments made in the area by mining operators. Similarly,
inactive mines may continue to pose challenges for water security while likely no longer provid-
ing economic opportunities.
Regarding empirical identification, we acknowledge potential measurement errors in the
mining variables. Our dataset primarily includes only registered commercial mines, but small-
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scale and unregistered mining operations are also widespread in many African countries which
may affect the interpretations of our results. Such unregistered operations can also impact water
security and household welfare. Many unregistered mines are often in the vicinity of registered
mines as this is where mineral resources exist. This fact also informs our identification strategy.
To address endogeneity issues, we focus on the number of mineral deposits in the area and use
this variable as an instrument for active mines. We use mineral deposits in the 0–50 km radius
of a household as well as mineral deposits in the 50–100 km radius as instruments for the main
explanatory variables (active and inactive mines, and mines within 0–50 km and 50–100 km) in
their respective models. The mineral deposits data is accessed from USGS (2023) and comprises
deposits of major nonfuel mineral commodities. Our instruments satisfy the requirements for
identification: Mineral deposits are linked to active mines, so the instruments are relevant pre-
dictors of active mining activity. At the same time, mineral deposits themselves are unlikely to
affect water security, health, and economic opportunities directly or via other variables as such
the exclusion restriction is likely to be fulfilled. Thus, mineral deposits are expected to affect
water security, health, and income of households through mining activities allowing us to iden-
tify the causal impact of mining on these variables. We estimate the effects of mining activities
on lived poverty with the Linear Probability and the Two-Stage Least Squares model for easier
interpretation. We show in Table A-X (See Appendix) that the main results are quantitatively
and qualitatively similar to the average marginal effect obtained from the Logit estimator.
THE EFFECT OF ACTIVE AND INACTIVE MINES:
EMPIRICAL EVIDENCE
Table 2 explores the effect of mining activities on household self-reported water security, access
to medicine during illness, and income. We measure exposure to mineral extraction with the
number of mining operations within the household's 0–50 km and 50–100 km radii. We directly
address potential endogeneity with a two-stage instrumental variable model. The Kleibergen–
Paap rk LM statistic for the models indicates that they are identified, and the instruments are
relevant. Moreover, the Kleibergen–Paap rk Wald test has an F-statistic of 13.044 which sug-
gests the instruments are not weakly correlated with the endogenous variables in all our esti-
mates. The table shows that mining operations have significant (causal) impacts on the three
dependent variables related to WASH. The effects vary with the distance to the active mining
sites. A concentration of mining activities within a 50 km radius of the household improves liv-
ing standards in the dimensions of access to water and medicine. A mining operation within
50 km reduces the probability of water insecurity and the probability of going without medi-
cine. However, exposure to mining activities within this radius appears not to have no signifi-
cant effect on household income poverty in the sample.
Mining operations within a 50–100 km radius increases self-reported deprivation with
respect to clean water. A possible reason for this is that mining companies sometimes mitigate
the polluting effects of their activities with community water projects which usually serve
households and individuals in their immediate vicinity. However, the adverse effect of mining
may spread beyond the immediate catchment areas. It is possible that an upstream operation
could pollute downstream waters for a considerable distance. Thus, while households in prox-
imity could have access to clean water because of the community social project, those in distant
locations may not have access to these interventions. For income poverty, the results in column
3 indicate that an additional mine in the 50–100 km radius reduces the probability of having
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inadequate income, while the effect of a closer mine is statistically insignificant. We believe this
finding could be explained by the nature of our mining sample, which consists of registered for-
mal companies only. The reality of mining operations is that there are usually small-scale
unregistered mining operations outside the concessions of the registered companies. There is a
likelihood for the activities of these small-scale artisanal mines to directly impact incomes in
the communities. Potentially, this effect could be higher, especially if the large-scale registered
mines operate in an “enclave” with minimal linkages with the surrounding communities.
It is important to highlight that our results remain robust both with and without the inclu-
sion of the large array of controls that we account for. Notably, our results regarding the effect
of mines on self-reported measures for water security, health, and income are not influenced by
whether individuals reside in more densely populated areas, as captured by our urban versus
rural dummy variable. Urban settings are often assumed to have better infrastructures, includ-
ing water and medical supplies. We also account for basic infrastructure within the enumera-
tion area where the household is surveyed, such as the presence of a clinic or piped water.
Crucially, our findings persist even when these controls are not included.
Table 3 provides further relevant insights by disaggregating the mines according to their
activity status, that is, the number of active and inactive (closed) mines in a vicinity of 50 km of
a household. In these models, we employ the number of nonfuel deposits within 0–50 and 50–
100 km as instruments for the two endogenous variables. First, the observation in Table 2
remains robust in these models too. Mining operations enhance household WASH by reducing
water, medicine, and income poverty in the immediate communities. Focusing on household
income, we further note that even though active and inactive mines are associated with lower
monetary poverty, the poverty-reducing impact is larger for inactive mines. This result supports
TABLE 2
Two-stage least square estimates of the effects of mining operations on water security, health, and
income (only active mines).
(1)
(2)
(3)
Gone without
water
Gone without
medicine
Gone without
income
All mines within 50 km radius
0.036***
0.016***
0.006
(0.005)
(0.005)
(0.006)
All mines within 50–100 km radius
0.005***
0.000
0.006***
(0.002)
(0.002)
(0.002)
Country fixed effects
Yes
Yes
Yes
Year fixed effects
Yes
Yes
Yes
Household controls
Yes
Yes
Yes
Community controls
Yes
Yes
Yes
N
142,838
142,838
142,838
Kleibergen–Paap rk LM statistic
8.769
8.769
8.769
[0.003]
[0.003]
[0.003]
Kleibergen–Paap rk Wald F statistic
13.044
13.044
13.044
Note: Robust standard error estimates are in parentheses. *p < 0.1, **p < 0.05, ***p < 0.01. Individual controls: respondent's age
sex and secondary school and employment status. Community controls: urban dummy, dummies for piped water, electricity,
clinic market. The complete estimation results are presented in Table A-I in Appendix.
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our explanation that in the absence of large, registered, and regulated companies, small-scale
artisanal miners operate in their stead. As an extension, their activities could have a more direct
and higher impact on the income level in the communities.
We interpret these results as offering new insights into the existing literature. Firstly, the
presence of both active and inactive mines appears to positively influence income generation
opportunities, as individuals report lower probabilities of having gone without income. Further-
more, we observe that active mines are positively associated with self-reported water security
and access to medicine. Households near active mines tend to show a lower probability of hav-
ing gone without clean water or medicine. This may be because active mines, beyond generat-
ing employment opportunities—which we control for—may also influence the broader
community and investment possibilities. While environmental impacts may still exist, access to
clean water, as reported by individuals, seems to increase. On the other hand, inactive mines
may pose a problem for perceived water security.
THE RELEVANCE OF LOCAL GOVERNANCE FOR THE
EFFECTS OF MINING
We delve into the influence of local institutional quality on how mining activities impact water
security, health, and income. In the realm of macroeconomic research, various studies have tra-
ditionally used indicators like trust, corruption levels, accountability, rule of law, democratic
governance, and judicial independence to gauge institutional quality (Acemoglu et al., 2005;
TABLE 3
Evidence from two-stage least square estimations: Effects of mines of on water security, health,
and income—comparing active versus inactive mines.
(1)
(2)
(3)
Gone without
water
Gone without
medicine
Gone without
income
Active mines within 50 km radius
0.027***
0.016***
0.018**
(0.005)
(0.004)
(0.009)
Inactive within 50 km radius
0.072
0.022
0.154*
(0.117)
(0.067)
(0.083)
Country fixed effects
Yes
Yes
Yes
Year fixed effects
Yes
Yes
Yes
Household controls
Yes
Yes
Yes
Community controls
Yes
Yes
Yes
N
142,838
142,838
142,838
Kleibergen–Paap rk LM statistic
2.965
2.965
2.965
[0.085]
[0.085]
[0.085]
Kleibergen–Paap rk Wald F statistic
7.716
7.716
7.716
Note: Robust standard error estimates are in parentheses. *p < 0.1, **p < 0.05, ***p < 0.01. Individual controls: respondent's
age, sex, and secondary school and employment status. Community controls: urban dummy, dummies for piped water,
electricity, clinic market. The complete estimation results are presented in Table A-II in Appendix.
HOW CURRENT AND PAST MINING ACTIVITIES AFFECT WATER
595
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Corradini, 2021; Nawaz et al., 2014). These studies have provided valuable insights into the
broader implications of institutional frameworks.
However, a significant gap exists in the availability of such detailed institutional data at the
subnational level, particularly in the African context. We tap into individual perceptions and
opinions regarding the performance of local governments. The Afrobarometer surveys provide
a unique lens into local governance, covering aspects such as perceived corruption, trust in local
authorities, and their responsiveness to citizen concerns.
We construct a set of indicators to ascertain the quality of local government. These indica-
tors are derived from regional average scores on perceived corruption and public approval of
governance. These variables not only reflect the general perception of local governance but
also provide a nuanced understanding of how these governance aspects interact with and
influence the effects of mining operations on local communities, particularly in terms of
water security.
We analyze the link between institutional quality on the different indicators in Figure 1
(The underlying regression results are presented in Appendix A-III–A-IV). The figure provides
the coefficient of the respective institutional variables when explaining water security, health,
and income. For the estimation of the coefficient, we employ the same model and control vari-
ables as in Table 2. We observe a significant link between institutional quality and all our
dependent variables. We consistently estimate that institutional corruption increases the proba-
bility of water insecurity among African households. A unit increase in the corruption score for
local councillors is associated with about 0.10 higher probability of water insecurity in our sam-
ple. Similarly, households have a 0.10 higher probability of inadequate medicine for unit in
local councillor corruption and the probability of monetary poverty is also higher. Figure 1
shows a similar pattern for tax official corruption, only that, here we observe a higher effect on
monetary poverty. As an indicator of the overall performance of local government, local govern-
ment disapproval is also associated with poorer WASH outcomes – higher water insecurity and
0.10***
0.13***
0.05***
0.11***
0.13***
0.07***
0.07***
0.15***
-0.03***
Corruption (Local councilors)
Corruption (Tax officials)
Disapprove local government
-.1
0
.1
.2
-.1
0
.1
.2
-.1
0
.1
.2
(a) Gone without Water
(b) Gone without medicine
(c) Gone without Income
Corruption (Local councilors)
Corruption (Tax officials)
Disapproval local government
FIGURE 1
Effect of local government quality on WASH.
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health poverty. However, we find that the local government disapproval score is associated with
low-income poverty.
Next, we explore the relevance of local institutions in the mining-WASH nexus by introduc-
ing interaction terms between our measures for perceptions of households regarding local insti-
tutions and mining operations. This approach allows us to better dissect the interplay between
local institutional quality and mining activities, offering a more granular understanding of how
institutional factors at the local level can modulate the impacts of mining on water security
and, by extension, on the broader socioeconomic fabric of African communities. To keep the
analysis tractable, we limit the results to active and non-active mines within a 50 km radius of
the primary enumeration area. To conserve space, we illustrate the main findings from the
analysis in Table 4 for corruption among local councillors.
In Table 4 (See Table A-VI for the complete results), we find that institutional quality mod-
erates the effect of mining activities on household water security, health, and income in Africa.
Active mining operation plays a higher role in improving access to water, that is, reducing
water insecurity, and access to medicine and income, in regions with local councillors that are
perceived to be less corrupt. Conversely, adverse effects of mining on water security, health,
and income of inactive mines increases if local councillors are corrupt. This evidence is sugges-
tive that mining operations can make up for problems related to corruption in the case of active
mines. Indeed, without institutional support, mining communities deteriorate after the
TABLE 4
Mining operation and local councillor corruption: Analyzing moderation effects.
(1)
(2)
(3)
Gone without
water
Gone without
medicine
Gone without
income
Active mines within 50 km radius
0.078***
0.033**
0.026*
(0.011)
(0.010)
(0.012)
Corruption (local councillors)
0.106***
0.107***
0.073***
(0.005)
(0.005)
(0.004)
Active mines within 50 km radius*
0.035***
0.017***
0.015***
Corruption (local councillors)
(0.004)
(0.004)
(0.005)
Non-active within 50 km radius
0.078*
0.109**
0.063
(0.035)
(0.033)
(0.037)
Non-active within 50 km radius*
0.040**
0.047***
0.029*
Corruption (local councillors)
(0.013)
(0.013)
(0.014)
Country fixed effects
Yes
Yes
Yes
Year fixed effects
Yes
Yes
Yes
Household controls
Yes
Yes
Yes
Community controls
Yes
Yes
Yes
N
142,838
142,838
142,838
R2
0.069
0.103
0.142
Note: Robust standard error estimates are in parentheses. *p < 0.1, **p < 0.05, ***p < 0.01. Individual controls: respondent's
age, sex, and secondary school and employment status. Community controls: urban dummy, dummies for piped water,
electricity, clinic market. The complete estimation results are presented in Table A-VI in the Appendix.
HOW CURRENT AND PAST MINING ACTIVITIES AFFECT WATER
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active life of the mine (Diallo, 2023; Syahrir et al., 2021). Once mines are inactive, the negative
effects of local corruption seem to prevail. Figure 2 illustrates the results: active mining sites in
the vicinity of a household decrease the likelihood of having gone without water, medicine, and
income as perceived corruption increases while the opposite holds for inactive mines. Thus,
active mining operations seem to help to reduce the negative effect of corruption.
The relationships and moderation effects found in Table 4 can also be observed for other institu-
tional variables such as perceptions of corruption of tax officials and disapproval of local gover-
nance. Results for all other institutional variables are similar and we present them in the Appendix.
CONCLUSIONS
This paper examines the impact of mining operations on individual welfare, specifically in
terms of self-reported water security, health, and income in Africa. Mining has been widely
scrutinized in the literature for its potential dual role: while it can support local economies and
community projects, it also poses risks to water resources and health due to potential pollution
from operations. A common perception is that mining negatively affects access to clean water.
However, whether these effects on clean water are substantiated when analyzing individual-
level data remains an open research question. By employing a household-centric approach, we
investigate the microlevel impacts of mining on self-reported water security and health across
142,838 African households from 2005 to 2015.
In line with the literature, we find evidence that proximity to active mining sites is associ-
ated with increased economic opportunities. Households report significantly lower probabilities
of having gone without income when living closer to mines. Contrary to common perceptions,
we also find evidence that self-reported access to clean water and medicine improves near
FIGURE 2
Moderation effects of local institutions on the effect of mining activities on WASH.
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active mines. However, these benefits diminish when mines close or as the distance from the
mines increases. A possible explanation for these results is the reduction in community support
that mining corporations typically provide to their surrounding communities during active
operations. The lack of effective environmental management protocols after the closure of the
mines may contribute to worsening water quality after operation.
Importantly, our investigation also underscores the critical role of local governance in the
context of mining. Issues such as water insecurity, health shortages, and low incomes—partly
stemming from deficiencies in local governance—are moderated by mining activities. In this
way, we also emphasize the broader relevance of strong institutions, particularly in communi-
ties that tend to be comparatively vulnerable. In fact, strong local governance may reduce the
likelihood of illegal mining activities in inactive mines which have been associated with nega-
tive environmental and health impacts.
In conclusion, while mining contributes significantly to African economies, its impact on
water security and health is complex and influenced by local governance. Sustainable manage-
ment and collaboration are essential to harness the benefits of mining while mitigating its risks
and long-term impacts. The current study relies on registered and regulated mines, therefore
the effects we observed could represent the lower bound of mining effects in WASH. Small-scale
artisanal miners have been documented to step in after the closure of commercial mines. Due
to a lack of monitoring and supervision, their activities have been reported to pollute large
water bodies. Future studies could, therefore, focus on the activities of these small-scale miners
using a similar empirical setup.
ACKNOWLEDGEMENTS
Raymond B. Frempong and David Stadelmann acknowledge funding from the Deutsche
Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence
Strategy - EXC 2052/1 - 390713894. All authors thank the Rosenberg International Forum on
Water Policy, the guest editors of the Special Issue: Unpacking Water Management Complexity
in Agriculture in the Global South, and the two anonymous reviewers for helpful comments.
Open Access funding enabled and organized by Projekt DEAL.
ORCID
Raymond Boadi Frempong
https://orcid.org/0000-0002-4603-5570
David Stadelmann
https://orcid.org/0000-0002-1211-9936
ENDNOTES
1 The question employed is: Over the past year, how often, if ever, have you or anyone in your family: Gone
without enough clean water for home use? [0–4].
2 The question employed is: Over the past year, how often, if ever, have you or anyone in your family: Gone
without medicines or medical treatment? [0–4].
3 The question employed is: Over the past year, how often, if ever, have you or anyone in your family: Gone
without a cash income? [0–4].
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SUPPORTING INFORMATION
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How to cite this article: Frempong, Raymond Boadi, David Stadelmann, and Djiby
Racine Thiam. 2025. “How Do Current and Past Mining Activities Affect Water Security,
Health, and Economic Opportunities?” Applied Economic Perspectives and Policy 47(2):
586–601. https://doi.org/10.1002/aepp.13510
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