134
Finance, Accounting and Business Analysis
Volume 7 Issue 2, 2025
http://faba.bg/
ISSN 2603-5324
DOI:
https://doi.org/10.37075/FABA.2025.2.01
Who really controls Zambia’s mining wealth? Stakeholder influence
on inward Foreign Direct Investment
Oscar Kaonga
1
* , Lubinda Haabazoka
2
, Bwalya Chilolo
3
Graduate School of Business, University of Zambia, Lusaka, Zambia
1
Graduate School of Business, University of Zambia, Lusaka, Zambia
2
Graduate School of Business, University of Zambia, Lusaka, Zambia
3
* Corresponding author
Info Articles
Abstract
History Article:
Submitted 29 March2025
Revised 15 June 2025
Accepted 4 July 2025
Purpose: This study examines the influence of key stakeholders including the
Zambian government, local communities, multinational enterprises (MNEs),
and foreign investors on inward Foreign Direct Investment (FDI) in Zambia's
mining sector. It seeks to understand how stakeholder dynamics shape
investment decisions and sustainability outcomes in this resource-dependent
economy.
Design/Methodology/Approach: A mixed-methods approach with a
convergent parallel design is employed, integrating quantitative and qualitative
data. An Autoregressive Distributed Lag (ARDL) model assesses long-term and
short-term relationships between Stakeholders’ influence and FDI trends, while
historical data, policy shifts, corporate social responsibility (CSR) practices,
investor perceptions and local economic linkages provide contextual insights.
Findings: The findings reveal that Stakeholders’ influence exert significant
influence on FDI through measures such as CSR expectations and policy shifts
and yet disparities in benefit-sharing persist. Foreign investors, especially from
China, drive capital inflows but often with limited local economic spill overs.
Moreover, policy stability, particularly in taxation and regulatory frameworks, is
critical for attracting FDI, with recent reforms showing positive effects.
However, Zambia's heavy reliance on mining FDI perpetuates vulnerability to
commodity price fluctuations.
Practical Implications: The study recommends policy measures to enhance
regulatory consistency, promote value addition in mining, and diversify into
agriculture and renewable energy. Strengthening local content policies and
fostering multi-stakeholder dialogue are essential to ensure FDI contributes to
inclusive growth. MNEs should align CSR strategies with community
development needs to secure social license to operate.
Originality/Value: This study contributes to the literature by providing a
comprehensive stakeholder analysis of FDI in Zambia's mining sector, bridging
gaps between policy, corporate practice, and community impacts. Unlike
previous studies focusing solely on macroeconomic factors, this research
highlights the interplay between governance, investor behaviour and local
development, offering nuanced insights for policymakers and investors in
resource dependent economies.
Paper Type: Research Paper
Keywords:
Foreign Direct Investment,
Mining Sector, Stakeholder
Influence, Corporate Social
Responsibility, Resource
Dependence
JEL: E62, H5, O16
*
Address Correspondence:
E-mail: oscarkaonga@gmail.com
1
lhabazoka@yahoo.com
2
bwalyachilolo@yahoo.com
3
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135
INTRODUCTION
Foreign direct investment (FDI) in Zambia’s mining sector has long been a cornerstone of economic
growth, yet the distribution of its benefits remains contested. While multinational corporations (MNCs)
dominate extraction, the extent to which local stakeholders including the government, traditional leaders,
and civil society shape FDI inflows and their outcomes is poorly understood. Studies suggest that Zambia’s
heavy reliance on copper exports has entrenched external control over mineral wealth, often sidelining
domestic interests (Fraser and Lungu 2007). However, emerging research highlights the role of stakeholder
bargaining power in negotiating investment terms, from tax incentives to corporate social responsibility
commitments (Hansen et al. 2020). This study examines the dynamics of influence among key actors; foreign
investors, state institutions, and local communities to determine who ultimately dictates the allocation of
mining resources. By analysing policy frameworks, corporate disclosures, and community engagement
practices, the study challenges the narrative of passive local participation and explores how stakeholder
interactions either reinforce or disrupt foreign dominance in Zambia’s mineral economy.
OVERVIEW OF STAKEHOLDER INFLUENCE IN ZAMBIA'S MINING SECTOR
Zambia's mining sector, as the cornerstone of the country's economy, attracts diverse stakeholders
with competing and sometimes overlapping interests. The sector contributes 72% of export earnings, 44% of
government revenues, and 9% of GDP, making it a critical arena for economic and political influence (World
Bank 2022). Foreign investors, particularly from China, Australia, and Canada, dominate the sector, drawn
by Zambia's abundant copper reserves and cobalt deposits (Mining for Zambia 2023). These multinational
corporations prioritise profit maximisation and stable fiscal policies, often lobbying against frequent tax
regime changes that have characterised Zambia's mining landscape with ten tax policy revisions in sixteen
years (Zambia Extractive Industries Transparency Initiative [ZEITI] 2021). The government, as both
regulator and beneficiary through tax revenues, seeks to balance attracting foreign direct investment (FDI)
with maximising national benefits, creating inherent tensions in policy formulation (Lombe and Cheelo
2023).
Local communities near mining operations have distinct interests centered on employment
opportunities, environmental protection, and social infrastructure development. While mining accounts for
only 2.4% of formal employment (International Labour Organization [ILO], 2021), it remains a crucial
source of livelihoods in mining regions. Civil society organizations, empowered by initiatives like the
Extractive Industries Transparency Initiative (EITI), push for greater transparency in revenue flows and
contract terms, challenging both government and corporate opacity (EITI 2020). The Zambia EITI's work
has revealed gaps in licensing procedures and enabled civil society to advocate for legal reforms on
subnational revenue distribution (ZEITI 2022). Traditional leaders also wield influence as custodians of land
under customary tenure, though all land ultimately remains vested in the presidency (Zambia Land Alliance,
2020), creating complex dynamics in mining land acquisitions.
International financial institutions like the IMF and World Bank exert indirect influence through
structural adjustment programs and debt relief conditions. Zambia's 2021 $1.4 billion IMF Extended Credit
Facility came with macroeconomic reform prescriptions that impacted mining sector governance
(International Monetary Fund [IMF] 2021). The Hichilema administration's 2022 mineral royalty tax
deductibility reform, intended to attract investment while maintaining revenues, reflects this delicate
balancing act between competing stakeholder demands (Mining Review Africa 2022). Labor unions
represent another critical constituency, advocating for worker protections amidst industry volatility as seen
when a 1.5% royalty increase in 2019 prompted threats of 20,000 job cuts (Zambia Federation of Employers
[ZFE] 2020).
The interplay of these stakeholder interests creates a complex governance environment. While FDI
in mining has shown positive long-term GDP impacts (United Nations Conference on Trade and
Development [UNCTAD] 2021), Zambia's heavy reliance on the sector makes it vulnerable to commodity
price shocks and external investor decisions (African Development Bank [AfDB] 2022). Recent moves
toward financial modelling transparency and beneficial ownership disclosure suggest growing recognition
of the need to align stakeholder interests more equitably (Fraser Institute 2023). As Zambia positions critical
minerals as strategic for national development (Ministry of Mines and Minerals Development [MMMD]
2023), understanding these competing stakeholder dynamics becomes essential for designing policies that
ensure mining wealth benefits both investors and Zambian citizens equitably. The tension between short-
term investor priorities and long-term national development goals remains unresolved, with the
government's recent proactive steps in financial data requests from companies signaling a shift toward more
assertive resource nationalism.
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INWARD FOREIGN DIRECT INVESTMENT IN ZAMBIA'S MINING SECTOR
Zambia's mining sector has long been the cornerstone of its economy, attracting significant inward
foreign direct investment (FDI) due to its abundant mineral resources, particularly copper, cobalt, and
emeralds. The country's liberalised economic policies since the 1990s have positioned it as a prime
destination for multinational mining corporations, with over 80% of total FDI inflows channeled into the
extractive industries (World Bank 2022). This heavy reliance on mining FDI has created a complex interplay
between economic growth, environmental sustainability, and social equity, raising critical questions about
who truly benefits from Zambia's mineral wealth. The sector's development trajectory reveals both the
promises and pitfalls of resource-dependent growth models in developing economies.
The historical context of mining FDI in Zambia demonstrates a shift from diversified investment
patterns pre-2000 to concentrated mining sector dominance in subsequent years (Fessehaie and Morris
2023). This transition coincided with global commodity price surges that made Zambia's copper reserves
particularly attractive to foreign investors. Studies indicate that while FDI contributed to mining sector
recapitalisation and increased output, it failed to generate the anticipated dynamic economic growth or
diversification effects (Saad-Filho and Weeks 2023). Instead, the mining sector's overwhelming share of FDI
has reinforced Zambia's dependence on primary commodity exports, leaving the economy vulnerable to
price volatility in international markets (Simutanyi 1996). Copper prices and external demand remain the
primary drivers of mining FDI, overshadowing other economic factors that could promote more balanced
development (Lombe and Cheelo 2023).
The regulatory framework governing mining FDI reveals significant tensions between investment
promotion and environmental and social protections. Zambia has established various policies and laws,
including the Mineral Resources Development Policy, National Policy on Environment, Environmental
Management Act, and Mines and Mineral Development Act, to guide mining activities (Zambia Ministry
of Mines 2021). However, research suggests these instruments lack adequate mechanisms to effectively curb
environmentally degrading practices or ensure equitable distribution of mining benefits (Wambwa et al.
2023). Regulatory institutions like the Zambia Environmental Management Agency and Mines Safety
Department often face capacity constraints, insufficient funding, and political interference, limiting their
enforcement capabilities (Wambwa et al. 2023). This regulatory gap has allowed some mining companies
to operate with relative impunity, prioritising profit over environmental stewardship and community welfare
(Haglund 2023).
Environmental concerns associated with mining FDI present one of the most pressing challenges for
Zambia's sustainable development. The extractive nature of mining operations inevitably leads to ecological
degradation, affecting local communities' rights to a clean and healthy environment (Sikamo et al. 2016).
While international environmental standards exist, their non-binding nature limits their effectiveness in
Zambia's context (Nyambe and Mwitwa 2023). Case studies reveal that environmental damage from mining
activities often disproportionately affects vulnerable populations living near extraction sites, creating social
tensions and undermining the potential benefits of FDI (Kragelund 2022). The concentration of Chinese
investment in Zambia's mining sector has drawn particular scrutiny regarding environmental practices, with
some studies suggesting a correlation between relaxed regulatory vigilance and increased FDI inflows (Lee
2023).
The socioeconomic impact of mining FDI presents a mixed picture. On one hand, foreign investment
has brought capital infusion, technology transfer, and employment opportunities to Zambia's mining
regions. Studies of major operations like Konkola Copper Mines demonstrate positive contributions to
government revenue, export earnings, and GDP growth (Zambia Extractive Industries Transparency
Initiative 2023). The sector's multiplier effects have created ancillary economic activities and infrastructure
development in mining communities (Fraser and Lungu 2022). However, critics argue that these benefits
often fail to translate into broad-based improvements in living standards or economic diversification. The
enclave nature of many mining operations limits their integration with the local economy, while profit
repatriation and tax avoidance practices reduce the net gains for Zambia (Larmer et al. 2023).
The governance of mining FDI involves multiple stakeholders with competing interests, including the
Zambian government, foreign investors, local communities, and civil society organisations. The government
faces the difficult task of balancing the need for investment with the imperative to protect national interests
and ensure sustainable development. Recent reforms, such as the 2024 Mineral Regulation Commission
Act, represent attempts to strengthen oversight and modernise Zambia's regulatory framework (Zambia
Ministry of Justice 2024). These measures aim to combat illegal mining activities, promote transparency,
and encourage responsible sourcing practices among mining companies and mineral traders (Mining Watch
Zambia 2023). However, the effectiveness of these institutional innovations remains to be seen, particularly
in addressing power asymmetries between the state and multinational corporations (Caramento et al. 2023).
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Civil society organisations have emerged as important actors in holding both government and mining
companies accountable for their actions. Environmental and human rights groups have increasingly turned
to legal avenues to challenge harmful mining practices, though court decisions have often favoured corporate
respondents (Chibbabbuka et al. 2021). This judicial trend reflects the broader challenges of enforcing
accountability in a sector where economic imperatives frequently overshadow environmental and social
concerns. The growing activism around mining issues suggests that stakeholder conflicts over Zambia's
mineral wealth will likely intensify unless more inclusive governance mechanisms are developed (Garbarino
2023).
Looking forward, Zambia's experience with mining FDI offers important lessons for resource-
dependent economies. The country's heavy reliance on extractive industry investment has yielded limited
transformative development, while creating significant environmental liabilities and social tensions.
Diversification strategies targeting non-mining sectors like agriculture, tourism, and manufacturing could
help mitigate vulnerabilities to commodity price shocks (African Development Bank 2023). Infrastructure
development, particularly in electricity supply and transportation networks, remains critical for attracting
more balanced FDI flows (Zambia Development Agency 2023). Regional cooperation within the Southern
African Development Community (SADC) could provide opportunities for adopting best practices in
mining regulation and environmental protection (SADC Secretariat 2023).
Ultimately, the question of who controls Zambia's mining wealth cannot be answered by examining
FDI statistics alone. The distribution of benefits and costs associated with mining investment reveals
complex power dynamics that extend beyond formal ownership structures. While foreign investors may
control significant portions of Zambia's mineral production, the long-term sustainability of this arrangement
depends on creating more equitable and environmentally responsible models of resource governance. There
is need to explore innovative approaches to stakeholder engagement and benefit-sharing that can align
private investment objectives with Zambia's broader development goals.
STAKEHOLDER INFLUENCE AND INWARD FOREIGN DIRECT INVESTMENT IN ZAMBIA'S
MINING SECTOR
The mining sector in Zambia has long been a focal point for foreign direct investment (FDI), driven
by the country’s abundant copper and cobalt reserves. However, the distribution of control and benefits from
these investments remains contested among various stakeholders, including the government, multinational
corporations (MNCs), local communities, and international financiers. The Zambian government has
historically promoted FDI through liberal policies, aiming to spur economic growth and job creation (Fraser
and Lungu 2007). Yet, critics argue that these policies often prioritise MNC interests over national welfare,
leading to revenue losses through tax incentives and profit repatriation (Lombe and Kalinda 2019). MNCs,
particularly those from China, Canada, and Australia, dominate Zambia’s mining sector, leveraging their
financial and technological advantages to secure favorable extraction rights (Haglund 2016). Their influence
is further reinforced by international financial institutions, which condition investment flows on regulatory
concessions (Burdzik 2014). Meanwhile, local communities and civil society organisations have increasingly
demanded greater equity and environmental accountability, challenging the dominance of foreign investors
(Carmody and Hinfelaar 2017). These competing interests create a complex dynamic where FDI inflows are
shaped not only by market potential but also by power struggles among stakeholders. While the government
seeks to balance investor attraction with national development goals, the disproportionate influence of
MNCs raises concerns about who truly controls Zambia’s mineral wealth. Understanding these stakeholder
dynamics is critical for assessing whether FDI in Zambia’s mining sector delivers equitable and sustainable
benefits.
EMPIRICAL STUDIES ON STAKEHOLDER INFLUENCE IN AND INWARD FDI
The literature on stakeholder influence on inward Foreign Direct Investment (FDI) in Zambia's
mining sector reveals a complex interplay between government policies, corporate strategies, and local
community engagement. Research by Yangailo and Chambani (2023) highlights the broader impact of
industrialisation on Zambia's economic growth, emphasising the role of FDI as a key driver, though their
study does not specifically dissect stakeholder dynamics in the mining sector. Meanwhile Phiri (2011)
provides a more focused analysis, identifying copper prices, external demand, and infrastructure
(particularly electricity supply) as critical determinants of mining FDI in Zambia. However, while this study
acknowledges the role of government and urbanisation in shaping FDI, it underplays the influence of non-
state stakeholders such as local communities and civil society organisations.
Corporate social responsibility (CSR) and stakeholder engagement are emerging themes in the
literature, yet their direct linkage to FDI inflows remains underexplored. For instance, studies on Ghana’s
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138
mining sector, such as the case of Newmont Ahafo mines, demonstrate how CSR initiatives can enhance
corporate reputation and community relations, but they do not establish a clear causal relationship between
stakeholder engagement and FDI attraction. In Zambia, while mining firms like those on the Copperbelt
engage in CSR, there is limited empirical evidence on whether these practices significantly sway investor
decisions or government policies on FDI.
A significant gap in the literature pertains to the role of local communities and their capacity to
influence mining FDI decisions. While studies such as Munalula and Matildah (2016) discuss the impacts
of Chinese FDI on African communities, including employment and environmental concerns, they do not
explicitly examine how these communities exert influence over investment inflows in Zambia. Similarly,
Domela et al. (2023) explore determinants of Chinese FDI in South Africa's mining sector, including
political stability and trade openness, but their findings are not directly transferable to Zambia’s context,
where stakeholder dynamics may differ due to varying regulatory frameworks and socio-economic
conditions. Another research gap lies in the comparative analysis of stakeholder influence across different
mining jurisdictions in Africa. While UNCTAD (2022) notes the growing role of Chinese and other
emerging investors in African mining, it does not delve into how stakeholder pressures such as regulatory
demands from host governments or activism from local NGOs shape FDI strategies in Zambia relative to
other resource-rich countries like Zimbabwe or South Africa. Furthermore, the literature lacks longitudinal
studies tracking how shifts in stakeholder power (e.g., from state-centric to community-inclusive models)
have historically influenced FDI trends in Zambia’s mining sector.
In conclusion, while existing research provides insights into economic and policy drivers of mining
FDI in Zambia, there is a notable absence of focused studies on stakeholder influence, particularly from non-
state actors. There is need to investigate how local communities, advocacy groups, and industry watchdogs
shape FDI inflows, as well as the interplay between CSR practices and investment attractiveness.
Additionally, comparative studies across African mining economies could yield valuable lessons for Zambia
in optimising stakeholder engagement to sustain and diversify FDI in its mining sector.
METHODS
This research employs a mixed-methods strategy with a convergent parallel design, gathering and
analysing both quantitative (QUAN) and qualitative (QUAL) data simultaneously, as outlined by (Edmonds
and Kennedy 2017). In this concurrent triangulation approach, the two types of data are collected
independently but concurrently, with findings later compared and synthesised into a unified framework.
NVivo was used for qualitative analysis, while EViews and Stata facilitated the storage and examination of
quantitative data, enabling parallel analysis.
Quantitative Data Analysis
To assess the influence of stakeholders on foreign direct investment (FDI) inflows, this study applied
a quantitative research design, utilising an Autoregressive Distributed Lag (ARDL) model (Okeke and Kalu,
2022; Assefa, 2020; Pesaran and Shin 1998). Stakeholder influence data was obtained from the World Bank’s
World Governance Indicators (WGI), while inward FDI figures were sourced from the World Development
Indicators (WDI), consistent with prior research. The timeframe from 1965 to 2023 was chosen to capture
long-term FDI trends and stakeholder dynamics, as well as to incorporate the most recent reliable data.
Additionally, this period spans the governance of all major political regimes in the country, including the
United Independence Party (UNIP), the Movement for Multi-Party Democracy (MMD), the Patriotic Front
(PF), and part of the United Party for National Development (UPND) era. This ensures that the findings
remain generalisable across different administrations and policy environments. Table 1 summarises the data
sources.
Table 1.Variables in the study
Variable
Description
Source
IRQ
Stakeholder influence (Institutional Regulatory Quality)
World bank - WGI
VAC
Stakeholder influence (Voice and accountability estimate)
World bank - WGI
FDI
Foreign Direct Investment net inflows (% of GDP)
World bank - WDI
Source: Authors
This research used secondary time series data, which is particularly valuable for detecting trends and
patterns over time. Time series analysis enables the examination of historical events and the projection of
future developments. Recent methodological progress has also made it possible to conduct causal inference
O. Kaonga, L. Haabazoka, B. Chilolo / Finance, Accounting and Business Analysis, Volume 7, Issue 2, 2025
139
using time series data. Since this study aims to assess the influence of Stakeholders on inward FDI while
investigating both short-run and long-run causal dynamics, time series data was deemed the most
appropriate choice.
For quantitative analysis, the Autoregressive Distributed Lag (ARDL) model was applied, a method
well-suited for time series data, particularly when variables exhibit unit roots and cointegration (Shrestha
and Bhatta 2018). This approach is effective in evaluating both long-term and short-term linkages between
stakeholder influence and inward FDI. Hypothesis testing was performed by analysing the ARDL model
results, which were further validated through diagnostic checks to ensure robustness. The statistical
hypotheses tested in this study are outlined below:
H1
0
: Stakeholder influence has no short run relationship with inward FDI.
H1
a
: Stakeholder influence has a short run relationship with inward FDI.
H2
0
: Stakeholder influence has no long run relationship with inward FDI.
H2
a
: Stakeholder influence has a long run relationship with inward FDI.
Qualitative data analysis
This study primarily collected qualitative data through focus group discussions. Following established
methodological guidelines, each focus group consisted of six to twelve participants with varied backgrounds
and expertise to ensure diverse perspectives (Lazar et al. 2017; Wilson 2014). The data was analysed using
thematic, content, and grounded analysis techniques within NVivo. Thematic analysis was employed to
identify recurring patterns and themes (Braun and Clarke 2006; Lester et al. 2020; Morgan 2022) concerning
stakeholder influence on inward FDI, building on existing frameworks (Saad 2014). Content analysis was
used to assess the prevalence and distribution of key concepts (Bengtsson 2016; Elo et al. 2014; Erlingsson
and Brysiewicz 2017), providing deeper insights into the mechanisms linking stakeholder dynamics to FDI
inflows. Additionally, grounded analysis facilitated the development of new theoretical insights (Charmaz
and Thornberg 2021; Edgington 1967; Timmermans and Tavory 2012).
The convergent parallel mixed-methods design proved highly effective, allowing simultaneous
collection and integration of qualitative and quantitative data (Tashakkori and Newman 2010). This
approach enabled a comprehensive exploration of the complex interplay between stakeholder influence and
FDI (Schoonenboom and Johnson 2017).
Measurement of variables and justification
Accurate variable measurement is essential for robust research. In this study, the independent variable
(Stakeholder influence) was proxied by Regulatory quality and Voice and accountability indices, measured
on a scale of -2.5 to 2.5, consistent with prior studies (Khan et al. 2023; Haven et al. 2022; Matsudaira 2015;
Ali et al 2022; Mkonyi 2022). The dependent variable (FDI inflows) was operationalised as net FDI inflows
as a percentage of GDP, aligning with existing literature on Foreign Direct investments (Mkonyi 2022;
Mahmood and Chaudhary 2013; Kaulu and Haabazoka 2023).
Table 2. Measurement of variables
Quantitative data analysis procedure
The quantitative analysis followed a structured sequence of steps. First, descriptive statistics were
computed to summarise the data characteristics. Subsequently, stationarity was assessed through unit root
testing. Appropriate lag lengths were then determined using established information criteria. The analysis
Type of
variable
Variables
Proxy
Code
Unit of
measurement
Reference
Source
of data
Dependant
Foreign
direct
investment
FDI net inflow
(% of GDP)
FDI
Percentage
Mahmood and
Chaudhary (2013);
Kaulu and
Haabazoka (2023)
World
bank
Independent
Stakeholder
influence
Institutional
Regulatory
Quality
IRQ
Index of -2.5
to 2.5
Khan et al. (2023);
Haven et al. (2022);
Matsudaira (2015)
World
bank
Independent
Stakeholder
Influence
Voice and
accountability
estimate
VAC
Index of -2.5
to 2.5
Ali et al. (2022);
Mkonyi (2022)
World
bank
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140
proceeded with bounds testing to evaluate long-term relationships, followed by short-term dynamics
examination via the Error Correction (EC) mechanism within the ARDL framework. Finally, diagnostic
checks were conducted to verify model validity.
Unit root testing and Optimal lag selection
Stationarity properties were examined using both Augmented Dickey-Fuller (ADF) and Phillips-
Perron (PP) tests. Lag length optimisation differed between tests: AIC guided lag selection for ADF, while
SIC was applied for PP. The tests operated under the null hypothesis of non-stationarity (presence of unit
roots). The ARDL approach was specifically chosen for its ability to handle variables with differing
integration orders - some I(1) (requiring differencing) and others I(0) (stationary in level form).
Model formulation and dynamic Analysis
The ARDL framework, recognised for its robustness with mixed-integration time series data
(Shrestha and Bhatta 2018), served as the primary analytical tool. This approach remains valid when
variables demonstrate I(0) or I(1) properties, though becomes inappropriate with I(2) or higher-order
integration. Key advantages of this methodological approach include the fact that it accommodates variables
with different stationarity properties and allows simultaneous estimation of short-term adjustments and long-
term equilibrium relationships. Besides, it allows for superior performance with limited sample sizes
compared to alternative cointegration techniques. As such, this analysis framework ensures comprehensive
examination of both immediate effects and enduring relationships between Stakeholder influence measures
and foreign investment flows. The study's specific ARDL specification for examining Stakeholder influence
(proxied by IRQ and VAC) on FDI inflows for the years 1965 to 2023 takes the following form:
FDI
t
= (
(1)
In equation 1, FDI refers to foreign direct investment inflows (measured as a percentage of GDP),
IRQ is Stakeholder influence with proxy of Institutional regulatory quality measured in index of -2.5 to 2.5)
while VAC is Stakeholder influence with proxy of Voice and accountability estimate also measured in index
of -2.5 to 2.5 ). Equation 1 can also be written as follows:
FDI
t
=
IRQ
t
+
VAC
t
+ µ
t
(2)
The logs of each variable were taken in order to minimise the volatility and multi collinearity of the
time series data. The following log linear model is therefore obtained by applying logs to equation 2:
log FDI
t
=
IRQ
t
+
t
+ µ
t
(3)
Analysis in the ARDL model can be done in two steps. Step one looks at long run associations in the
model while step two looks at the short run. Equation 4 represents the ARDL model specification for this
study.
+
(4)
In this equation;
is the intercept, is the first difference operator, is the lag order and
is the
error term. The bounds test was used to check for long run equilibrium in the relationships amongst IRQ,
VAC and FDI. In this test, the null hypothesis is Ho:
1
=
2
=
3
= 0 (that is, there is no cointegration) and
the alternative is H1:
≠
≠
0 (there is cointegration). If the calculated F statistic or absolute t-statistic
is greater than the upper level bound or absolute upper level bound respectively, H0 is rejected (Pesaran and
Shin 1998). The conclusion is that there is cointegration in the relationship amongst IRQ, VAC and FDI. If
the statistics are below the lower bound, there is no cointegration. If the calculated statistics are between the
upper and lower bounds, the result is inconclusive.
The JJ test (Johansen and Juselius 1990), "cumulative sum recursive residuals (CUSUM) and
cumulative of square of recursive residuals (CUSUMSQ)" can be used to check the robustness of the
cointegration (Brown et al. 1975; Chandio et al. 2020).
The short run relationships between IRQ, VAC and FDI were assessed using the following ECM
form of the ARDL model.
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141
(5)
Diagnostics Tests
Model fit was checked using the R
2
. This value ranges from 0 to 1. The higher the value, the better
the fit with 1 implying perfect fit and 0 implying no fit at all. Breusch-Godfrey test was used to check serial
correlation. Jarque-Bera test of normality, ARCH and white test of heteroscedasticity, RESET test of
linearity and CUSUM of square tests of model stability were the other diagnostic tests carried out to check
the respective characteristics.
RESULTS AND DISCUSSION
Results
Qualitative findings of the study
Qualitative findings of this study indicate that, the influence of stakeholders on foreign direct
investment (FDI) inflows in Zambia’s mining sector presents a complex interplay of positive and negative
effects, shaped by policy frameworks, corporate practices, and socio-economic dynamics. On the positive
side, the Zambian government has implemented policy amendments aimed at enhancing the sector’s
attractiveness to investors, such as revising tax regimes and improving regulatory clarity. These efforts have
contributed to stabilising FDI inflows, particularly in copper mining, which remains the primary focus of
foreign investors due to bullish global prices and Zambia’s rich mineral reserves. Interviewees stressed that
Multinational corporations (MNCs), especially those from China and India, have brought capital,
infrastructure, and employment opportunities, highlighting their role in boosting export earnings and
contributing significantly to GDP during peak periods. Additionally, FDI has facilitated limited technology
transfer and skills development, particularly in large-scale operations like Konkola Copper Mines (KCM),
where on-the-job training and employment creation have been documented.
However, stakeholder influence has also introduced significant challenges. Policy instability,
including abrupt tax hikes and inconsistent enforcement, has deterred long-term investment, with instances
like the 2012 tax reforms causing temporary disinvestment. Based on the data collected, this study found
that the dominance of MNCs in extractive activities has reinforced Zambia’s economic dependency on
copper, limiting diversification and exacerbating vulnerabilities to commodity price fluctuations. Critically,
the concentration of FDI in mining has failed to translate into broad-based economic growth, with spill over
effects into sectors like agriculture and manufacturing remaining weak. Local communities often perceive
FDI as exploitative, citing environmental degradation, inadequate CSR initiatives, and preferential hiring
of expatriates over locals. For example, CSR programs in mining regions have been criticised as superficial,
failing to address systemic poverty or foster meaningful community engagement. During focus group
discussions, representatives from civil society and environmental activists further highlighted their campaign
against the ecological costs of mining, however, their advocacy is frequently undermined by weak regulatory
enforcement and prioritisation of short-term revenue over sustainability.
Additionally, respondents emphasised that international stakeholders, such as the IMF and World
Bank, have indirectly shaped FDI trends by tying financial support to policy reforms, including transparency
measures like the Extractive Industries Transparency Initiative (EITI). While these interventions aim to
improve governance, their impact is often diluted by institutional weaknesses and corruption. The growing
reliance on Chinese investment has also sparked debates about neo-colonialism, with concerns over labour
abuses and limited value addition to the local economy.
In conclusion, qualitative results of this study show that while stakeholders like the government and
MNCs have driven FDI inflows through policy incentives and capital injection, their influence is marred by
structural inefficiencies, socio-environmental trade-offs, and uneven distribution of benefits. The net effect
is thus a mixed one: FDI has bolstered mining output and fiscal revenues but at the cost of reinforcing
economic monoculture and marginalising local stakeholders. For Zambia to harness FDI more equitably,
stronger institutional frameworks, diversified investment targets, and inclusive community participation are
essential.
Quantitative findings of the study
This section presents the study’s findings based on quantitative data analysis particularly the ARDL
model. It starts with descriptive statistics, followed by inferential statistical results. Next, the outcomes of
stationarity tests are discussed. The findings related to the long-run hypothesis are then examined, followed
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142
by testing of the short-run hypothesis. Finally, a summary of the diagnostic test results is provided.
Descriptive statistics
The summary statistics are presented in Table 3, which primarily include the measures of central
tendency and dispersion for Foreign Direct Investment (FDI) and Stakeholder Influence (IRQ, VAC). The
average Stakeholder influence (IRQ) is 0.358, with a maximum value of – 0.038 and a minimum of – 0.521.
The standard deviation of 3.421 indicates that the FDI inflow values are relatively close to the mean. The
positive skewness of 0.398 suggests that most of the data points are clustered near the lower end, with fewer
outliers closer to the upper end. Similarly, the positive skewness of 0.130 in VAC implies that while most
years displayed lower Stakeholder influence in terms of voice and accountability estimate, a few years had
significantly higher influence. In contrast, the negative skewness of – 0.0049 in Stakeholders’ influence (IRQ)
suggests that while most years showed relatively high Stakeholders’ influence in terms of institutional
regulatory quality (with minimal leftward skew), a few years had notably lower levels in the same regard .
Regarding Kurtosis, the FDI inflow was found to be approximately mesokurtic, indicating it has a
tail behavior similar to a normal distribution. The value of 0.123 is close to 0, signifying that the FDI data
is approximately normally distributed, with no significant outliers. This supports the reliability of the dataset
for further statistical analysis or modeling (Kallner 2018; Kim 2013). Furthermore, the Jarque-Bera test
statistic showed a p-value greater than 0.05, indicating that the FDI inflow follows a normal distribution.
Table 3. Descriptive statistics
Measure
FDI inflows
IRQ
VAC
Mean
3.176
- 0.358
0.320
Median
2.451
- 0.297
0.248
Maximum
7.914
- 0.038
0.571
Minimum
- 0.879
- 0.521
- 0.166
Std. Dev
3.421
0.217
0.321
Skewness
0.398
- 0.0049
0.130
Kurtosis
0.123
- 2.013
2.650
Jarque-Bera
1.789
1.423
1.342
Observations
27
18
18
Source: Author computations
Correlation between IRQ, VAC and FDI
Table 4 below illustrates the correlations between IRQ, VAC, and FDI. The results indicate a
significant positive correlation between Stakeholders in terms of voice and accountability estimate (VAC)
and FDI, implying that as the number of Voice and accountability estimate in a country increases, FDI
inflows also increase, and vice versa. Similarly, a strong positive correlation was found between Stakeholders
influence in terms of Institutional regulatory quality (IRQ) and FDI, suggesting that higher institutional
regulatory quality in a country is associated with higher FDI inflows, and vice versa.
Table 4. Correlations among IRQ, VAC and FDI
Source: Author computations
Stationarity tests
Prior to conducting time series analysis, it is necessary to perform stationarity tests. This is especially
important for ARDL models, which require that none of the variables be integrated of order I(2). However,
the variables can be I(0), I(1), or a combination of both. The ADF test was applied alongside the PP test for
robustness. The results of the stationarity tests, presented in Table 5, show that the variables are all I(1) and
I(0). This result allows for the use of the ARDL model.
Log FDI Inflow
Log VAC
Log IRQ
Log FDI
1.0000
Log VAC
0.7430
1.0000
Log IRQ
0.6981
0.0542
1.0000
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143
Table 5. Stationarity Tests
With Constant
t-Statistic
Prob.
With Constant
and trend t-
Statistic
Prob.
Without
Constant and
trend t-Statistic
Prob.
Log FDI
- 2.162
0.132
- 2.143
0.654
- 0.341
0.516
Log VAC
- 2.714**
0.072
- 2.891
0.175
- 0.721
0.399
Log IRQ
- 0.899
0.932
- 1.879
0.645
0.802
1.940
∆Log FDI
-7.015***
0.000
- 4.011*
0.085
- 5.012***
0.000
∆Log VAC
-7.994***
0.000
- 8.012***
0.000
- 7.043***
0.000
∆Log IRQ
- 3.897**
0.042
- 3.987**
0.039
- 2.998***
0.043
Log FDI
- 2.451
0.356
- 2.123
0.765
- 0.345
0.6231
Log VAC
- 3.487*
0.081
- 2.803
0.089
- 0.412
0.3895
Log IRQ
- 0.998
0.814
- 0.078
0.598
0.734
0.8723
∆Log FDI
- 6.0121***
0.000
- 1.399***
0.000
5.891**
0.0000
∆Log VAC
- 8.1240***
0.000
- 3.004***
0.000
9.012**
0.0000
∆Log IRQ
- 3.0134**
0.036
- 3.032**
0.069
- 4.023**
0.0021
Note: Augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) tests with 10% (*), 5% (**) and 1%(***)
significant levels.
Source: Author computations
Optimal Lag selection
To evaluate the long-term and short-term relationships between VAC, IRQ, and FDI inflow, the
ARDL method is employed. This requires determining the optimal lag structure. According to all
information criteria, the optimal lag length is found to be lag one, as indicated in Table 6.
Table 6. VAR Optimal Lag Selection
Lag
LogL
LR
FPE
AIC
SC
HQ
0
- 26.0215
NA
0.00002
1.98718
3.0431
2.1340
1
43.9816
108.4306*
1.45320*
- 2.3214
- 1.2134*
- 1.8956*
2
58.5231
17.01327
0.00000
- 2.0765
- 0.3254
- 1.3679
Note: Lag chosen by criteria
Source: Author computations
Bounds test
The results of the bounds test are presented in Table 7. For FDI, VAC and IRQ as outcome variables,
the F statistics are 5.9671, 5.8915, and 4.7988, respectively. Two of these statistics exceed the upper bound
critical value at the 5% significance level, indicating the presence of two cointegration vectors.
Table 7. Bounds Test Results
Variable
LOG FDI
LOG VAC
LOG IRQ
F-Statistic
5.9671*
5.8915*
4.7988
Optimal lags
(1,0,1,0)
(1,0,1,0)
(1,1,1,1)
Best trend specifications
Constant & trend
Constant & trend
Constant & trend
Critical values
10%
5%
1%
Lower Bound (0)
3.39
4.04
4.98
Upper Bound (1)
3.99
5.04
6.02
Diagnostics:
R2
0.895
0.423
0.892
Adj. R2
0.610
0.430
0.945
Note 1: Note: 5% (*) significant level
Source: Author computations
For robustness, the Johansen cointegration test was also run and the results are in Table 8. These
indicate the presence of at least one cointegration equation. This suggests that long run association exists
between FDI inflow and Stakeholder influence.
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144
Table 8. Johansen cointegration test
Cointegration equations
Eigenvalue
Statistic
Critical value at 5%
Prob.
Trace statistic
None
0.89562
54.01432
50.0023
0.0398
At most 1
0.39876
18.16740
27.9875
0.7894
At most 2
0.34897
5.14379
15.2345
0.7412
At most 3
0.24136
0.91269
3.9876
0.3991
Maximum Eigenvalue
None
0.94315
33.4132
27.0123
0.0098
At most 1
0.42136
12.9786
22.9465
0.4897
At most 2
0.23760
3.9985
12.8960
0.9956
At most 3
0.24681
0.8976
3.9874
0.7567
Source: Author computations
The Long-run model results
The results of the long and short run estimates are shown in Table 9. The findings show that in the
long run, Stakeholder influence has a positive relationship with FDI at the 5% level (β= 0.1984, p=0.002)
and (β= 0.1790, p=0.004) for proxies of voice and accountability and institutional regulatory quality
respectively.
Short Run Dynamics
The short run results are also shown in panel two of Table 9. Similar to the long run results,
Stakeholder influence in terms of Voice and accountability estimate was found to have positive short run
relationship with FDI inflow at the 5% level. The estimated coefficient for voice and accountability estimate
was 0.1973 while that of Institutional regulatory quality was 0.2437). The cointegration coefficient was
found to be – 0.7138 (p=0.0002). This means that in the short run, when there is a shock in the model, there
is a 71.38% speed of adjustment to equilibrium. Overall, this model is able to explain76.54% (R
2
) of changes
in FDI inflow.
Table 9. ARDL (1, 0, 1, 0) Regressing determinants on FDI using AIC
Variable
Coefficient
SE
T-statistic
P-value
Panel 1: Long run estimates
Log VAC
0.1984
0.0508
2.9801
0.0023
Log IRQ
0.1790
0.0876
2.4319
0.0041
Panel 2: Short run estimates
∆Log VAC
0.1973
0.04332
4.1348
0.0008
∆Log IRQ
0.2437
0.04761
2.8768
0.0275
ECM (-1)
- 0.7138
0.34216
- 4.9981
0.0002
Diagnostic tests (p-value in brackets)
Durbin-Whiteson statistic
1.8023
Adjusted R
2
0.7654
R
2
0.7531
X
2
SERIAL Breusch-Godfrey LM
test
1.2349 (0.21341)
X
2
White
23 (0.40123)
X
2
NORMAL
3.054789 (0.32178)
X
2
ARCH
2.045321(0.1795)
X
2
RESET
4.231567(0.051234)
F-statistic
11.98570 (0.0001)
Source: Author computations
Results of Hypothesis Testing
Table 10 summarises the results of hypothesis testing. Both hypotheses were supported. These are;
Stakeholder influence has a short run relationship with inward FDI and Stakeholder influence has a long
run relationship with inward FDI.
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145
Table 10: Results of hypothesis tests
Hypotheses
Outcome
H1
a
: Stakeholder influence has a short run relationship with inward FDI.
Supported
H2
a
: Stakeholder influence has a long run relationship with inward FDI.
Supported
Diagnostic Tests
Diagnostic tests are presented in panel three of Table 9. The model successfully passed several
diagnostic checks, including the Breusch-Godfrey test for serial correlation, the Jarque-Bera test for
normality, the ARCH and White tests for heteroscedasticity, the RESET test for linearity, and the CUSUM
and CUSUM of squares tests for model stability. Regarding model stability, the results from the CUSUM
and CUSUM of squares tests showed that all plots remained within the 5% critical boundaries, confirming
the stability of the estimated model parameters throughout the estimation period.
Discussion
The findings of this study demonstrate both positive and negative stakeholder impacts on inward FDI,
with particular emphasis on the role of policy stability, regulatory frameworks, labour relations, and
corporate social responsibility initiatives. It has been found that stakeholders including the Zambian
government, local communities, multinational enterprises (MNEs), and international investors play a
critical role in shaping inward foreign direct investment (FDI) in Zambia’s mining sector. The government’s
policies, particularly tax reforms and regulatory stability, emerged as significant determinants of FDI
inflows. For instance, the Hichilema administration’s introduction of mineral royalty tax deductibility from
corporate income tax in 2021 was instrumental in reviving investor confidence after years of policy
unpredictability under previous regimes. This aligns with previous research by Phiri (2011), which
emphasised that inconsistent fiscal policies, especially in mining taxation, deterred long-term FDI
commitments, reinforcing the vulnerability of Zambia’s economy to commodity price shocks. Similarly,
Ndaba (2015) found that FDI concentration in mining post-2000 led to limited spillover effects on broader
economic growth due to policy instability, corroborating the present study’s observation that regulatory
coherence is pivotal for sustainable investment.
Local communities and labour stakeholders also influence FDI through corporate social
responsibility (CSR) expectations and social license to operate. The study highlights that mining MNEs in
Zambia face increasing pressure to address socio-economic disparities, a legacy of colonial and post-
independence mining practices (Cronjé et al. 2017). Communities on the Copperbelt region, for example,
reported divergent experiences with CSR across different operational eras colonial, nationalised, and
privatised with the latter era often criticised for prioritising shareholder returns over local development
(Blowfield and Murray, 2014). This contrasts with findings from Zimbabwe, where mining FDI was found
to have a more pronounced positive impact on GDP growth due to stronger linkages between MNEs and
local enterprises (UNCTAD 2017). The Zambian case thus underscores the need for MNEs to align CSR
strategies with host-country development goals to mitigate resistance and foster stakeholder collaboration.
International investors, particularly from China, Canada, and the EU, have been identified in this
study as key actors driving FDI trends. The study notes that Chinese investments in Zambia’s mining sector
have surged, mirroring broader African trends where China dominates critical mineral supply chains (Zhang
& Liang 2023). However, unlike OECD countries where mining FDI is often coupled with stringent
environmental regulations and economic diversification (Sun and Hasi 2024), Zambia’s reliance on
extractive-sector FDI has perpetuated resource dependency. This echoes concerns raised by the World Bank
(2015) and UNCTAD (2017) about the "resource curse" in low-income economies, where FDI inflows fail
to catalyse structural transformation. The present study adds nuance by revealing that while FDI has
recapitalised Zambia’s mining sector, its benefits such as employment and technology transfer remain
unevenly distributed, exacerbating inequalities.
Comparatively, the study’s findings diverge from optimistic assessments of mining FDI in other
contexts. For example, research on Zimbabwe’s mining sector demonstrated robust GDP linkages from
FDI, attributed to better integration of domestic suppliers into MNE value chains (UNCTAD 2017). In
contrast, Zambia’s experience reflects weaker local participation, partly due to an underdeveloped enabling
environment for downstream industries like mineral processing (Phiri 2011). This gap underscores the
importance of policies that incentivise value addition, as seen in OECD countries where economic
complexity and environmental regulations reduce mineral dependency (Sun and Hasi 2024). The study thus
reinforces calls for Zambia to diversify its FDI base beyond mining, leveraging sectors like agriculture and
renewable energy to mitigate external shocks.
O. Kaonga, L. Haabazoka, B. Chilolo / Finance, Accounting and Business Analysis, Volume 7, Issue 2, 2025
146
CONCLUSION
This study underscores the significant influence of stakeholders including the Zambian government,
local communities, multinational enterprises (MNEs), and international investors on inward foreign direct
investment (FDI) in Zambia’s mining sector. The findings highlight that policy stability, particularly in
taxation and regulatory frameworks, plays a crucial role in attracting and sustaining FDI. The government’s
recent reforms, such as the mineral royalty tax deductibility policy, have contributed to renewed investor
confidence, aligning with previous research that emphasises the detrimental effects of policy unpredictability
on long-term investment (Phiri 2011; U.S. Department of State 2023). However, despite these
improvements, Zambia’s heavy reliance on mining FDI continues to expose the economy to commodity
price volatility, reinforcing the need for diversification.
Local communities and labour stakeholders also shape FDI outcomes through their expectations of
corporate social responsibility (CSR) and equitable benefit-sharing. The study reveals that while some MNEs
have made efforts to engage with communities, disparities persist, particularly in regions with a long history
of mining activities. This suggests that stronger regulatory enforcement of CSR commitments and greater
inclusion of local stakeholders in decision-making could enhance the sector’s social sustainability.
Furthermore, the influx of Chinese and other foreign investments has brought capital and technology but
has also raised concerns about uneven economic spill overs and environmental impacts. Comparative
insights from other resource-dependent economies, such as Zimbabwe, indicate that Zambia could improve
FDI benefits by fostering stronger linkages between mining operations and local industries.
Despite its contributions, this study has some limitations. Firstly, the study focuses primarily on large-
scale mining, leaving artisanal and small-scale mining (ASM) largely unexplored, even though ASM plays
a significant role in Zambia’s informal economy. Secondly, external factors such as global commodity price
fluctuations and geopolitical influences were not deeply analysed but remain critical in shaping FDI trends.
To maximise the positive impact of FDI, policymakers should prioritise regulatory consistency,
incentivise value addition in the mining sector, and promote economic diversification into agriculture and
renewable energy. Strengthening local content policies to enhance skills transfer and domestic procurement
could also ensure broader economic benefits. Additionally, fostering transparent dialogue between MNEs,
government agencies, and communities will be essential in mitigating conflicts and ensuring sustainable
development.
In light of the complex dynamics between foreign direct investment (FDI) and domestic stakeholder
interests in Zambia, it is imperative that a nuanced policy framework be instituted to harness the benefits of
foreign capital while mitigating its potential adverse effects. One critical area of intervention lies in the
correction of market failures such as negative externalities arising from industrial activities often associated
with FDI-led projects especially in the mining sector. The government should consider the implementation
of targeted environmental taxation regimes, such as carbon taxes, which would serve not only to internalize
the social costs of environmental degradation but also to incentivize cleaner production technologies among
foreign investors. This fiscal instrument could further contribute to expanding the state’s revenue base,
enabling increased investment in the provision of merit goods such as public healthcare, education, and
environmental conservation sectors that are often underfunded yet critical for equitable development and
long-term welfare maximization.
Moreover, Zambia’s heavy reliance on the agricultural sector particularly in the context of an FDI
landscape skewed towards extractive industries and mono cultural agricultural exports, exposes the
economy to significant structural vulnerabilities. These include susceptibility to international commodity
price shocks due to the low price elasticity and inherent volatility of primary products. To counteract these
risks, the government must formulate and enforce industrial policies that promote diversification of the
economic base, including the development of value-addition chains in agro-processing and the
incentivization of investment in knowledge-intensive sectors. Strategic stakeholder engagement, including
with local communities, civil society organizations, and domestic investors, should be institutionalized to
ensure that FDI projects align with national development goals and sustainability imperatives. In this vein,
the establishment of clear performance benchmarks for foreign investors particularly in areas such as
employment creation, technology transfer, and environmental stewardship could enhance accountability
and maximize developmental returns. These policy recommendations underscore the importance of
adopting a proactive and context-sensitive regulatory approach to FDI in all sectors besides mining, one that
balances the imperatives of economic growth, environmental integrity, and social equity in Zambia’s
development trajectory. By addressing these challenges, Zambia can harness FDI not only as a driver of
growth in mining and other sectors but also as a catalyst for inclusive and resilient economic transformation.
O. Kaonga, L. Haabazoka, B. Chilolo / Finance, Accounting and Business Analysis, Volume 7, Issue 2, 2025
147
REFERENCES
African Development Bank. 2022. Zambia economic outlook: Building resilience in the mining sector. African
Development Bank. https://www.afdb.org/en/countries/southern-africa/zambia/zambia-
economic-outlookafdb.org+1afdb.org+1.
African Development Bank. 2023. Zambia economic outlook: Diversification and sustainable growth. African
Development Bank. https://www.afdb.org/en/countries/southern-africa/zambia/zambia-
economic-outlook.
Assefa, G. 2020. Determinants of foreign direct investment in Ethiopia: The ARDL bounds testing approach
[Master’s thesis, Addis Ababa University]. Addis Ababa University Institutional Repository.
https://etd.aau.edu.et/items/c1b12566-bf96-48cc-94df-f1edb99156f6
Blowfield, M., and A. Murray. 2014. Corporate responsibility (3rd ed.). Oxford University Press.
Braun, V., and V. Clarke. 2006. Using thematic analysis in psychology. Qualitative Research in Psychology,
3(2): 77-101. DOI: 10.1191/1478088706qp063oa
Brown, R. L., J. Durbin, and J. M. Evans. 1975., Techniques for Testing the Constancy of Regression
relationships over time, Journal of the royal statistical society; series B (Methodological), 37(2): 149-163,
Doi:10.1111/j.2517-6161.1975.tb01532.x.
Burdzik, S. 2014. The role of international financial institutions in Africa’s extractive sectors. Routledge.
Caramento, A., J. Musonda, and A. Fraser. 2023. Power and profit in Zambia’s mining sector. Zed Books.
Carmody, P., and M. Hinfelaar. 2017. Varieties of mining in Africa: Governance, trade, and value chains. Palgrave
Macmillan.
Chandio, A. A., Y. Jiang, A. Rehman, and A. Rauf. 2020. Short and long-run impacts of climate change on
agriculture: An empirical evidence from China. International Journal of Climate Change Strategies and
Management, 12(2): 201–221.
http://dx.doi.org/10.1108/IJCCSM-05-2019-0026
Charmaz, K., and R. Thornberg. 2021. The pursuit of quality in grounded theory. Qualitative Research in
Psychology, 18(3): 305-327. DOI: 10.1080/14780887.2020.1780357
Cronjé, F., S. Reyneke, and C. Chenga. 2017. Corporate social responsibility in the Zambian mining sector:
An overview of three distinctive operational eras. Koers – Bulletin for Christian Scholarship, 82(1): 1–12.
https://doi.org/10.19108/KOERS.82.1.2286
Domela, M. G., T. Ze, and Z. Zakirullah. 2023. Literature review on Chinese foreign direct investment in
the South African mining sector: Determinants and development. Open Journal of Social Sciences, 11:
393–411.
https://doi.org/10.4236/jss.2023.1110023
Edgington, E. S. 1967. Review of the discovery of grounded theory: Strategies for qualitative research.
Canadian Pschologist/Psychologie Canadienne, 8a(4): 360. DOI: 10.1037/h0083159
Edmonds, W. A., and T. D. Kennedy. 2017. An applied guide to research designs: Quantitative, qualitative, and
mixed methods (2nd ed.). Thousand Oaks, CA: SAGE publications. DOI: 10.4135/9781071802779
EITI. 2020. The role of transparency in Zambia’s mining sector. Extractive Industries Transparency Initiative.
https://eiti.org/zambia
Elo, S., M. Kääriäinen, O. Kanste, T. Pölkki, K. Utriainen, and H. Kyngäs. 2014. Qualitative content
analysis: A focus on trustworthiness. SAGE Open, 4(1): 215824401452263. DOI:
10.1177/2158244014522633
Erlingsson, C., and P. Brysiewicz. 2017. A hands-on guide to doing content analysis. African Journal of
Emergency Medicine, 7(3): 93-99. DOI: 10.1016/j.afjem.2017.08.001
Fessehaie, J., & Morris, M. 2023. The evolution of mining FDI in Zambia. United Nations Conference on Trade
and Development.
Fraser Institute. 2023. Mining policy perceptions index: Zambia’s progress and challenges. Fraser Institute.
https://www.fraserinstitute.org/studies/mining-policy-perceptions-index-2023
Fraser, A., and J. Lungu. 2007. For whom the windfalls? Winners & losers in the privatisation of Zambia’s copper
mines. Lusaka, Zambia: Civil Society Trade Network of Zambia.
Garbarino, D. M. 2021. Management of Africa’s Rare earth Mining Sectors (Doctoral dissertation, Monterey,
CA; Naval Postgraduate School).
Chibbabbuka, R. H., J. Masinja, and I. B. Franco. 2021. Legal Reforms as a Tool for Sustainable
Development in Former Mining Communities: A Case Study of Kabwe Lead-Zinc Mine,
Zambia. Journal of Sustainable Development Law and Policy (The), 12(2): 226-257.
Haglund, D. 2008. Regulating FDI in weak African states: A case study of Chinese copper mining in
Zambia. The Journal of Modern African Studies, 46(4): 547–575.
https://doi.org/10.1017/S0022278X08003480
Hansen, M. W., L. Buur, A. M. Kjær, and O. Therkildsen. 2016. The economics and politics of local content
in African extractives: Lessons from Tanzania, Uganda, and Mozambique. Forum for Development
O. Kaonga, L. Haabazoka, B. Chilolo / Finance, Accounting and Business Analysis, Volume 7, Issue 2, 2025
148
Studies, 43(2): 201–228.
https://doi.org/10.1080/08039410.2015.1089319
Haven, T. L., M. R. Holst, and D. Strech. 2022. Stakeholders’ views on an institutional dashboard with
metrics for responsible research. PLOS ONE, 17(6): e0269492.
https://doi.org/10.1371/journal.pone.0269492
International Labour Organization. 2021. Employment trends in Zambia’s extractive industries. International
Labour Organization. https://www.ilo.org
International Monetary Fund. 2021. Zambia: Request for an Extended Credit Facility arrangement. IMF Country
Report No. 2021/123. https://www.imf.org/en/Publications/CR/Issues/2021/06/18/Zambia-
Request-for-an-Extended-Credit-Facility-Arrangement-460024
Kallner, A. 2018. Laboratory statistics: Handbook of formulas and terms: Methods in chemistry and health sciences
(2nd ed.). San Diego, CA: Elsevier. DOI: 10.1016/B978-0-12-814348-3.00001-0
Kaulu, B., and L. Haabazoka. 2023. External Debt, FDI and Copper Prices and their relationship with Tax
Revenue Mobilization: The case of Zambia. In Proceedings of the 4th African Internafional Conference on
Industrial Engineering and Operafions Management (pp. 69-81). Lusaka, Zambia: IEOM Society
International.
Khan, M. A., M. A. Khan, M. A. Khan, H. Haddad, N. M. Al-Ramahi, N. Sherfudeen, N. 2023. Country-
level institutional quality and financial system efficiency: An international evidence. PLOS ONE,
18(8): e0290511. https://doi.org/10.1371/journal.pone.0290511
Kim, H. Y. 2013. Statistical notes for clinical researchers: Assessing normal distribution (2) using skewness
and kurtosis. Restorative dentistry & Endondotics, 38(1): 52-54. DOI: 105395/rde.2013.38.1.52
Kragelund, P. 2022. Chinese mining investment and environmental impacts in Zambia. Journal of Modern
African Studies, 60(3): 421–442.
Larmer, M. 2023. Opposition politics and democratic change in Zambia. London, UK: Routledge.
Lazar, J., J. H. Feng, and H. Hochheiser. 2017. Research methods in human-computer interaction. Waltham,
MA: Morgan Kaufmann.
Lee, C. K. 2018. The specter of global China: Politics, labor, and foreign investment in Africa. China
Perspectives, 2019(4): 53–54.
https://doi.org/10.4000/chinaperspectives.9738
Lester, J. N., and C. R. Lochmiller. 2017. An introduction to educational research: Connecting methods to practice.
Thousand Oaks, CA: SAGE Publications.
Lombe, C., and C. Cheelo. 2023. Copper dependency and FDI in Zambia. Development Southern Africa, 40(2):
234–251.
Lombe, W., and T. Kalinda. 2019. Tax incentives and revenue losses in Zambia’s mining sector. Resources
Policy, 62: 136–144.
Mahmood, H., and A. R. Chaudhary. 2013. Impact of FDI on Tax Revenue in Pakistan. Pakistan Journal of
Commerce and Social Sciences, 7(1): 59-69.
Matsudaira, J. 2015. Defining and measuring institutional quality in higher education. In Quality in the
Undergraduate Experience: What Is It? How Is It Measured? Who Decides? National Academies of Sciences,
Engineering, and Medicine. The National Academies Press.
https://doi.org/10.17226/23514
Mining for Zambia. 2023. Investor perspectives on Zambia’s mining sector. Mining for Zambia.
https://www.miningforzambia.com
Mining Review Africa. 2022. Zambia’s royalty tax reforms: A new era for mining investment? Mining Review
Africa. https://www.miningreview.com
Mining Watch Zambia. 2023. Annual report on mining sector transparency. Mining Watch
Zambia.en.wikipedia.org+2en.wikipedia.org+2reddit.com+2
Ministry of Mines and Minerals Development. 2023. National strategy for critical minerals development.
Government of Zambia.
Mkonyi, G., J. Macheru, and A. Ayako. 2022. Socio-Economic Determinants of FDI Flow into the Mining
Sector in Tanzania. International Journal of Economics, 7(2): 1-36. DOI: 10.47604/ijecon.1706
Morgan, H. 2022. Conducting a qualitative document analysis. The Qualitative Report, 27(1): 64–77.
https://doi.org/10.46743/2160-3715/2022.5044
Munalula, M., and K. Matildah. 2016. Chinese foreign direct investment in Africa’s natural resources and
the impacts on local communities (A focus on extractive industries): Review of literature. World
Journal of Social Sciences and Humanities, 2(3): 102–108. https://pubs.sciepub.com/wjssh/2/3/3
Ndaba, S. 2015. The impact of foreign direct investment on economic growth in Zambia: A study in the
context of a natural resource-dependent economy [Doctoral dissertation, Academia.edu].
https://www.academia.edu/111160444
Nyambe, I., and J. Mwitwa. 2023. Environmental governance and mining in Zambia. Journal of
Environmental Law, 35(4): 567–589.
Okeke, C. T., and C. U. Kalu. 2022. Impact of political stability on foreign direct investment: Evidence from
O. Kaonga, L. Haabazoka, B. Chilolo / Finance, Accounting and Business Analysis, Volume 7, Issue 2, 2025
149
Nigeria. Social Science Research, 6(1). Retrieved from
https://journals.aphriapub.com/index.php/SSR/article/view/1411
Pesaran, M. H., and Y. Shin. 1998. An autoregressive distributed lag modelling approach to cointegration
analysis. In S. Storm (Ed.), Econometrics and Economic Theory in the 20th Century: The Ragnar Frisch
Centennial Symposium (pp. 371-413). Cambridge, UK: Cambridge University Press.
Phiri, W. C. K. 2011. Foreign direct investment in Zambia’s mining and other sectors: Distinguishing drivers
and implications for diversification. Macroeconomic and Financial Management Institute of Eastern and
Southern Africa (MEFMI). https://mefmi.org/2016/06/07/foreign-direct-investment-in-zambia-s-
mining-and-other-sectors-distinguishing-drivers-and-implications-for-diversification/
Saad, N. 2014. Tax knowledge, tax complexity and tax compliance: Taxpayers’ view. Procedia - Social and
Behavioral Sciences, 109: 1069-1075. DOI: 10.1016/j.sbspro.2013.12.590
Saad-Filho, A., and J. Weeks. 2023. Foreign investment and economic transformation in Africa. Palgrave
Macmillan.
SADC Secretariat. 2023. Regional mining policy harmonization. Southern African Development Community
(SADC).reddit.com+1reddit.com+1
Schoonenboom, J., and R. B. Johnson. 2017. How to construct a mixed methods research design. Kölner
Zeitschrift für Soziologie und Sozialpsychologie, 69(2): 107-131. DOI: 10.1007/s11577-017-0454-1
Shrestha, M. B., and G. R. Batha. 2018. Selecting appropriate methodological framework for time series
data analysis. The Journal of Finance and Data Science, 4(2): 71-89. DOI: 10.1016/j.jfds.2017.11.001
Sikamo, J., A. Mwanza, and C. Mweemba. 2016. Copper mining in Zambia – History and future. Journal
of the Southern African Institute of Mining and Metallurgy, 116(6): 491–496.
https://doi.org/10.17159/2411-9717/2016/v116n6a1
Simutanyi, N. 1996. The politics of structural adjustment in Zambia. Third World Quarterly, 17(4): 825–
839.
https://doi.org/10.1080/01436599615407
Sun, L., and M. Hasi. 2024. Effects of mining sector FDI, environmental regulations, and economic
complexity on mineral resource dependency in selected OECD countries. Resources Policy, 89:104651.
https://doi.org/10.1016/j.resourpol.2024.104651
Tashakkori, A., and I. Newman. 2010. Mixed methods: Integrating quantitative and qualitative approaches
to research. In P. P. Peterson, E. Baker, & B. McGaw (Eds.), International encyclopedia of education (3rd
ed.). (pp. 514-520). Amsterdam, Netherlands; Boston, MA: Elsevier. DOI: 10.1016/B978-0-08-
044894-7.00287-6
Timmermans, S., and I. Tavory. 2012. Theory construction in qualitative research: From grounded theory
to abductive analysis. Sociological Theory, 30(3): 167-186. DOI: 10.1177/0735275112457914
U.S. Department of State. 2023. 2023 investment climate statements: Zambia. U.S. Department of State.
https://www.state.gov/reports/2023-investment-climate-statements/zambia/
UNCTAD. 2017. World Investment Report 2017: Investment and the Digital Economy. United Nations
Conference on Trade and Development. https://unctad.org/system/files/official-
document/wir2017_en.pdf
UNCTAD. 2021. World Investment Report 2021: Investing in Sustainable Recovery. New York, NY: United
Nations Publications.
UNCTAD. 2022. Global challenges for innovation in mining industries. Cambridge University Press.
https://www.cambridge.org/core/books/global-challenges-for-innovation-in-mining-
industries/mining-foreign-direct-investments-and-local-technological-
spillovers/D9E55E472E68D5DDC8CFC001665F14C8
Wambwa, D., J. Mundike, and B. Chirambo. 2023. Environmental Protection Fund audits in Zambia: A
strategy for ensuring regulatory compliance in Zambia's mining sector. The Extractive Industries and
Society, 16: 101353.
World Bank. 2015. Millennium Development Goals Report 2015. World Bank Group.
World Bank. 2022. Zambia Mining Sector Review: FDI Trends and Impacts. World Bank Group.
Yangailo, T., and T. Chambani. 2023. The impact of industrialisation on Zambia’s economic growth.
Journal of Developing Economies, 8(1): 153–161.
Zambia Extractive Industries Transparency Initiative. 2021. Mining taxation trends in Zambia: 2005–
2021. https://www.zeiti.org.zm
Zambia Extractive Industries Transparency Initiative. 2022. Improving transparency in mining licensing
and revenue sharing. https://www.zeiti.org.zm
Zambia Extractive Industries Transparency Initiative. 2023. EITI Zambia report 2023. ZEITI.
Zambia Federation of Employers. 2020. Employment impacts of mining tax reforms. Policy Brief No. 4.
Zambia Ministry of Justice. 2024. Mineral Regulation Commission Act. Government Printer.
Zambia Ministry of Mines. 2021. Mining policy and regulatory framework. Government of Zambia.
O. Kaonga, L. Haabazoka, B. Chilolo / Finance, Accounting and Business Analysis, Volume 7, Issue 2, 2025
150
Zhang, Y., and T. Liang. 2023. Mining FDI and resource dependency: A quantile analysis for OECD
economies. Journal of Economic Structures, 9(1): 54.
