INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue X October 2025
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Stock Market Efficiency and Economic Diversification in Nigeria and
South Africa
Abdulaziz Maruf Adeniran., Amiru Lawal Balarabe
Department of Business Administration, Federal University Gusau, Zamfara State
DOI: https://dx.doi.org/10.47772/IJRISS.2025.910000278
Received: 14 October 2025; Accepted: 21 October 2025; Published: 10 November 2025
ABSTRACT
The persistent reliance on natural resources has limited the resilience and sustainability of African economies,
particularly Nigeria and South Africa. This study examines the impact of stock market efficiency on economic
diversification, focusing on how capital market development influences non-resource GDP growth in the two
countries. Specifically, it investigates the effects of market capitalization, stock market turnover ratio, and the
number of listed companies on diversification performance between 2000 and 2024. The study adopts a
comparative ex-post facto design using secondary data sourced from the World Bank (WDI), IMF Financial
Development Index, and official statistics from NGX and JSE. Analytical techniques include descriptive
statistics, correlation matrix, diagnostic tests, and panel regression analysis. Results reveal that market
capitalization and turnover ratio exert positive and significant effects on non-resource GDP growth in both
countries, while the number of listed companies is marginally significant. South Africa’s capital market
demonstrates greater depth and efficiency, reflected in its higher R² (0.76) compared to Nigeria’s (0.71). These
findings confirm that robust and liquid capital markets are instrumental in financing non-resource sectors and
advancing structural transformation. The study concludes that financial deepening and inclusiveness drive
sustainable diversification and recommends that Nigeria strengthen investor confidence and listing incentives,
while both countries should improve market liquidity and broaden SME participation.
Keywords: Stock Market Efficiency, Capital Market Development, Non-Resource GDP Growth, Economic
Diversification, Market Capitalization, Turnover Ratio, Nigeria, South Africa.
INTRODUCTION
Economic diversification has become a central goal for many nations seeking to sustain growth beyond
traditional resource-based sectors. Across the global economy, diversification fosters resilience against
commodity price shocks and enhances long-term productivity. Recent studies show that economies with
diversified structures are better positioned to absorb macroeconomic disruptions and maintain stable growth
trajectories (Sahoo, 2021). The relationship between finance and diversification has gained renewed attention,
as access to deep and efficient capital markets can channel resources toward productive non-resource sectors
(Bai, 2022). In this global context, understanding how stock market efficiency contributes to economic
diversification remains both a theoretical and empirical necessity.
Stock markets play a vital role in the financial architecture of modern economies, serving as engines for
mobilizing savings, allocating capital, and promoting investment in innovative industries. When efficient, these
markets transmit information rapidly, enhance liquidity, and reduce transaction costs, enabling firms to access
funding for diversification initiatives (Ejemeyovwi, 2022). Empirical evidence across emerging markets
suggests that capital market development positively correlates with structural transformation and industrial
expansion (Olayeni, 2023). This dynamic underscores the importance of examining how stock market
performance can catalyze broad-based economic activity beyond extractive sectors.
In Africa, the discourse around diversification and stock market efficiency is particularly relevant given the
continent’s dependence on natural resources and vulnerability to external shocks. Recent analyses indicate that
countries with more advanced financial systems exhibit stronger capacity to diversify their economies and
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ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue X October 2025
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mitigate volatility in commodity revenues (Adusei, 2021). For instance, South Africa’s mature capital market
provides significant liquidity and access to investment opportunities, while Nigeria’s market, though expanding,
remains constrained by volatility and limited investor confidence (Anigbogu, 2023). These differences offer a
compelling ground for comparative study.
Nigeria and South Africa represent two of Africa’s largest economies, yet they exhibit divergent paths in
financial sector sophistication and economic structure. South Africa’s Johannesburg Stock Exchange (JSE)
stands as one of the most advanced in emerging markets, characterized by high turnover and broad sectoral
representation. On the other hand, the Nigerian Exchange Limited (NGX) faces challenges such as low market
capitalization, limited depth, and weak participation of non-financial firms (Uzonwanne, 2022). Despite these
disparities, both nations share a strategic objective, to use financial development as a vehicle for economic
diversification and sustainable growth (Okere, 2021).
The role of capital markets in driving non-resource growth is particularly critical in resource-dependent
economies like Nigeria, where oil revenue volatility often undermines macroeconomic stability. Studies reveal
that financial markets, when effectively developed, channel investments into manufacturing, technology, and
services, reducing overreliance on primary commodities (Eriya, 2023). Similarly, South Africa’s pursuit of
inclusive growth hinges on deepening market participation and financing new sectors that can enhance
productivity and employment (Adeleye, 2024). In both contexts, understanding how stock market efficiency
translates into diversification outcomes is essential for evidence-based policy reforms.
While several macroeconomic factors influence diversification, capital market indicators, such as market
capitalization, turnover ratio, and the number of listed firms, serve as critical proxies of efficiency and depth.
High capitalization reflects confidence and liquidity, turnover ratio indicates active participation, and firm
listings reveal sectoral representation and innovation potential (Adegboye, 2020). The World Bank’s Financial
Development Index identifies these indicators as key determinants of how effectively capital markets contribute
to structural transformation. Therefore, a comparative assessment of Nigeria and South Africa’s stock markets
provides unique insights into the financial mechanisms that drive or constrain diversification.
Despite ongoing reforms and financial liberalization, the contribution of stock market efficiency to economic
diversification in both Nigeria and South Africa remains ambiguous. Nigeria’s market continues to exhibit
shallow depth and limited integration with the real economy, while South Africa’s stock market, though
advanced, faces concentration risks and declining new listings (Munyegera, 2023). Empirical gaps persist
regarding how these markets influence the expansion of non-resource sectors. The existing literature often treats
financial development as a monolithic construct, overlooking the detailed relationship between capital market
efficiency and sectoral diversification.
This study, therefore, seeks to examine the comparative impact of capital market development on non-resource
GDP growth in Nigeria and South Africa. By focusing on market capitalization, turnover ratio, and firm listings,
it aims to uncover how financial market efficiency translates into real economic diversification. Understanding
this relationship is crucial for designing policies that enhance financial intermediation, attract investment, and
foster sustainable, inclusive growth across Africa’s largest economies. Addressing this gap contributes not only
to national development strategies but also to the broader discourse on finance-led structural transformation in
emerging markets. Against this backdrop, the study tests the following hypothesis:
H₀₁: Market capitalization has no significant effect on non-resource GDP growth in Nigeria and South Africa.
H₀₂: Stock market turnover ratio (%) has no significant effect on non-resource GDP growth in Nigeria and South
Africa.
H₀₃: Number of listed companies per million people has no significant effect on non-resource GDP growth in
Nigeria and South Africa.
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LITERATURE REVIEW
Concept of Economic Diversification
Economic diversification has been widely recognized as a cornerstone for achieving sustainable and inclusive
growth in developing economies. It refers to the strategic process of expanding the range of economic activities
beyond a narrow dependence on primary commodities, especially in resource-dependent nations (Sahoo, 2021).
In diversified economies, growth originates from multiple sectors; such as manufacturing, services, and
technology, thereby reducing exposure to external shocks and commodity volatility (Adusei, 2021; Bai, 2022).
Recent evidence highlights that African countries with diversified production and export bases demonstrate
higher economic resilience and improved income stability (Eriya, 2023; Adeleye, 2024). Economic
diversification also fosters structural transformation by enhancing productivity and employment across non-
resource sectors, supported by sound financial intermediation (Olayeni, 2023; Anigbogu, 2023). Furthermore, it
has been empirically linked to innovation, industrialization, and sustainable competitiveness (Uzonwanne, 2022;
Ejemeyovwi, 2022). In essence, economic diversification is a multidimensional indicator of economic
transformation and resilience. For the purpose of this study, economic diversification is operationally defined
and measured as Non-Resource GDP Growth (% annual), representing the real increase in value added generated
from non-extractive sectors of the economy.
Concept of Market Capitalization
Market capitalization represents the total market value of all listed domestic companies and serves as a central
indicator of the depth, size, and efficiency of a country’s capital market. It reflects investors’ confidence, the
absorptive capacity of financial markets, and their potential to mobilize long-term funds for productive
investments (Munyegera, 2023). A growing body of empirical evidence links higher market capitalization to
greater financial development and improved economic performance, especially in emerging markets (Adeleye,
2024; Bai, 2022). In Africa, market capitalization as a percentage of GDP measures how well capital markets
contribute to resource allocation, corporate financing, and overall economic diversification (Adusei, 2021;
Uzonwanne, 2022). Studies reveal that larger market capitalization enhances liquidity, broadens investment
opportunities, and strengthens financial resilience against external shocks (Eriya, 2023; Olayeni, 2023).
Moreover, it influences structural transformation by channeling capital toward non-resource sectors such as
manufacturing and services (Anigbogu, 2023; Sahoo, 2021). Therefore, for this study, market capitalization is
conceptualized as the total market value of all listed domestic companies expressed as a percentage of GDP,
representing the size and absorptive capacity of the stock market to support non-resource sector growth.
Concept of Stock Market Turnover Ratio
The stock market turnover ratio, defined as the total value of shares traded during a period divided by average
market capitalization, reflects the liquidity and efficiency of the capital market. It captures how easily investors
can buy and sell securities without significantly affecting prices, thereby indicating market dynamism and
confidence (Okonkwo, 2025). A higher turnover ratio signals an active market where resources are efficiently
reallocated to productive sectors, enhancing financial intermediation and supporting economic diversification
(Abdullahi, 2025; Kemgou, 2024). In Sub-Saharan Africa, turnover ratios remain uneven across markets, with
South Africa demonstrating greater liquidity relative to Nigeria and other economies (Tonmo, 2024). Recent
studies show that liquidity enhances firms’ access to financing, reduces investment risk, and stimulates growth
in non-resource sectors (Eke-Jeff, 2025; Bai, 2022). Turnover also correlates with investor participation,
transparency, and the overall performance of the financial system (Adeleye, 2024; Adusei, 2021). In emerging
economies, stock market liquidity serves as a critical driver of structural transformation by ensuring capital
availability for innovation-led diversification (Olayeni, 2023; Sahoo, 2021). Therefore, for this study, stock
market turnover ratio is conceptualized as the value of domestic shares traded relative to market capitalization,
representing the liquidity and trading efficiency of the stock market in supporting non-resource GDP growth.
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Concept of Number of Listed Companies per Million People
The number of listed companies serves as a critical indicator of the breadth and inclusiveness of a stock market,
reflecting its capacity to attract firms across diverse sectors. A growing number of listings suggests an enabling
financial ecosystem where businesses can access equity financing, expand operations, and contribute to
industrial growth (Eriya, 2023). This measure embodies both the vibrancy of the market and the depth of
entrepreneurial participation, which are essential for achieving structural transformation in developing
economies (Adeleye, 2024; Bai, 2022). In countries like South Africa, where listings are widespread across
industries, financial markets act as strong channels for capital mobilization, while in Nigeria, limited listings
signal shallow market participation and concentration in few sectors (Uzonwanne, 2022; Anigbogu, 2023).
Furthermore, the number of listed companies reflects the degree of diversification in the financial sector itself,
influencing how effectively capital is distributed among non-resource industries (Olayeni, 2023; Tonmo, 2024).
A higher listing density typically correlates with stronger investor confidence, greater transparency, and
improved corporate governance (Sahoo, 2021; Kemgou, 2024). It also indicates an expanding base of innovative
and productive firms contributing to non-resource GDP growth. Therefore, for this study, the number of listed
companies per million people is conceptualized as an indicator of market depth and inclusiveness, measuring
the extent to which firms are represented in the stock market and the capacity of the financial system to support
economic diversification.
Review of Related Empirical Literature
Market Capitalization and Economic Diversification
Recent empirical evidence emphasizes the pivotal role of market capitalization in promoting structural
transformation and non-resource-based growth across emerging economies. Munyegera (2023) found that higher
market capitalization significantly enhances capital accumulation and non-resource sector productivity in Sub-
Saharan Africa, supporting long-term diversification. Similarly, Adeleye (2024) demonstrated that well-
capitalized markets stimulate inclusive growth by improving firms’ access to equity finance, particularly in
manufacturing and services. Bai (2022) reported that in emerging markets, stock market expansion directly
influences non-resource GDP growth through enhanced investment flows and technological diffusion. In Nigeria,
Olayeni (2023) established that market capitalization deepening positively correlates with industrial output,
highlighting its relevance for transitioning from resource dependence. Eriya (2023) argued that capital market
expansion fosters structural change by reallocating financial resources toward non-extractive sectors, thus
strengthening diversification capacity. Tonmo, Djenga, and Djoufouet (2024) observed that financial depth,
proxied by market capitalization, exerts threshold effects on growth, where economies with deeper markets
realize stronger diversification outcomes. Adusei (2021) also showed that increased market capitalization
mitigates the adverse effects of resource dependence on growth through enhanced financial resilience. In contrast,
Anigbogu (2023) noted that shallow market capitalization constrains the diversification potential of African
economies by limiting corporate investment in high-value sectors. Sahoo (2021) further validated that stock
market deepening encourages sectoral balance and reduces volatility associated with resource-driven cycles.
More recently, Uzonwanne (2022) found that market capitalization acts as a key transmission channel linking
financial development to industrial diversification in leading African economies.
Stock Market Turnover Ratio and Economic Diversification
Several recent studies have examined the link between stock market turnover ratio, an indicator of market
liquidity, and economic diversification or growth in emerging economies. Thaddeus, Ngong, and Nnecka (2024)
revealed that liquidity, proxied by turnover ratio, significantly influences output expansion across sub-Saharan
Africa, suggesting that efficient trading environments stimulate productive investments. Ezenduka and Joseph
(2020) found that higher turnover ratios in Nigeria improve capital allocation efficiency, which in turn supports
diversification and industrial growth. Adeleye and Odhiambo (2023) observed that turnover ratio positively
correlates with real GDP growth in South Africa, highlighting the role of liquidity in promoting innovation and
sectoral transformation. Similarly, Ozegbe, Adedokun, and Osinowo (2025) confirmed that turnover enhances
investor confidence and broadens financing options for non-resource sectors. Adjasi and Biekpe (2022)
reinforced these findings by emphasizing that liquid stock markets promote investment diversification and long-
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term productivity gains. Twerefou and Abbey (2021) also showed that markets with high turnover ratios channel
capital toward diversified sectors, mitigating dependence on primary commodities. Ananwude and Osakwe
(2021) noted that liquidity strengthens the transmission between financial markets and real economic activity in
both Nigeria and South Africa. In contrast, Onyejiaku, Ngong, and Nnakee (2025) found that low turnover ratios
constrain financial deepening, reducing the pace of structural diversification. Ozean, Adeleye, and Odhiambo
(2023) argued that turnover ratio reflects not just market activity but also investors’ willingness to engage in
risk-sharing mechanisms critical for diversification.
Number of Listed Companies and Economic Diversification
The number of listed companies reflects the inclusiveness and depth of a nation’s capital market, serving as an
essential driver of economic diversification through expanded access to equity finance. Olayeni (2023) found
that higher firm listing density promotes industrial expansion and enhances non-resource GDP in Sub-Saharan
Africa by improving capital availability. Similarly, Eriya (2023) demonstrated that countries with more listed
firms experience stronger diversification outcomes, as market inclusivity encourages private sector participation.
Adeleye (2024) revealed that broader firm representation on stock exchanges correlates positively with
innovation-led growth, supporting transition from resource-dependent economies. Uzonwanne (2022) observed
that increased listings in South Africa foster sectoral diversification by providing stable financing for technology
and manufacturing enterprises. Bai (2022) confirmed that a diversified listing structure deepens financial
development, enhances competitiveness, and reduces output volatility. Moreover, Sahoo (2021) emphasized that
the expansion of listed companies enhances financial integration and facilitates structural transformation across
emerging economies. Tonmo, Djenga, and Djoufouet (2024) found that economies with higher listing activity
achieve stronger growth thresholds due to better investment linkages between capital markets and non-resource
sectors. In Nigeria, Anigbogu (2023) identified that the limited number of listed firms restricts market depth and
constrains diversification opportunities. Munyegera (2023) similarly argued that insufficient firm participation
impairs capital mobilization and the growth of productive sectors. Collectively, these studies establish that an
increasing number of listed companies per million people broadens financial inclusion, deepens capital markets,
and supports non-resource GDP growth, thereby accelerating economic diversification in developing economies.
Conceptual Framework
Theoretical Review
This study is anchored on the Financial Development Theory and the Endogenous Growth Theory, both of which
provide a strong foundation for examining the relationship between stock market efficiency and economic
diversification in Nigeria and South Africa. The Financial Development Theory, advanced by Schumpeter (1911)
and later formalized by Levine (1997), posits that a well-functioning financial system mobilizes savings,
allocates capital efficiently, and promotes productive investments that stimulate long-term economic growth. It
assumes that deep and liquid financial markets, measured by indicators such as market capitalization, turnover
ratio, and number of listed companies, enhance access to finance for firms, particularly in non-resource sectors,
thereby fostering economic diversification. The Endogenous Growth Theory (Romer, 1986; Lucas, 1988)
complements this by emphasizing the role of financial intermediation and innovation in sustaining growth
through capital accumulation and knowledge diffusion. Empirical studies such as Adeleye (2024) and Olayeni
Independent Variable Dependent Variable
(Stock Market Efficiency) (Economic Diversification)
Figure 1: Conceptual Framework adapted from Lusardi and Mitchell (2014)
Market Capitalization
Stock Market Turn Over
Number of Listed
Companies Per Million
People
Non-Resource GDP Growth
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(2023) have applied these theories, finding that stock market development significantly drives non-resource GDP
expansion in Sub-Saharan Africa. Thus, these theories collectively explain how capital market development
stimulates diversification by channeling financial resources toward productive, innovation-driven, and non-
extractive economic activities in developing economies.
METHODOLOGY
This study employs a comparative ex-post facto research design, which is appropriate for analyzing the causal
relationship between capital market development and non-resource GDP growth in Nigeria and South Africa
using historical data. This design allows for an objective evaluation of how variations in stock market indicators,
market capitalization, turnover ratio, and number of listed companies, affect economic diversification without
manipulating any variables.
The study uses secondary data obtained from reliable international and national sources, including the World
Bank’s World Development Indicators (WDI), the IMF Financial Development Index, and official records from
the Nigerian Exchange Limited (NGX) and the Johannesburg Stock Exchange (JSE). The population of the study
comprises all listed domestic companies on both the NGX and JSE, as these firms collectively determine the
indicators used to measure capital market performance. As of 2024, there are approximately 160 listed
companies in Nigeria and 340 listed companies in South Africa, resulting in a combined population of 500
companies. From this population, a sample size of 200 companies, comprising 80 from Nigeria and 120 from
South Africa, is selected through a purposive sampling technique, focusing on firms with consistent listing
histories and complete financial data across the study period.
The study covers 2000–2024, a 25-year period chosen to capture the effects of major capital market reforms,
financial sector liberalization, and diversification policies in both nations. Analytical techniques include
descriptive statistics (mean, standard deviation, and trend analysis) to summarize data, and a correlation matrix
to assess the relationships among variables. Diagnostic tests, including multicollinearity, heteroskedasticity, and
normality tests, are conducted to ensure data reliability. Finally, panel regression analysis (fixed and random
effects models) is employed to evaluate the extent to which capital market development influences non-resource
GDP growth, providing a robust empirical foundation for policy recommendations.
Model Specification
This study specifies econometric models to examine the relationship between capital market development and
non-resource GDP growth in Nigeria and South Africa. Two models are developed: a combined panel model
capturing the overall relationship across both countries, and separate country-specific models for robustness
analysis. These models are grounded in the Financial Development and Endogenous Growth Theories, which
emphasize the role of capital market efficiency in driving long-term economic diversification.
A. Pooled (Panel) Model Specification
The panel model integrates data from Nigeria and South Africa, accounting for both temporal and cross-country
variations. It allows for the examination of general effects of capital market indicators on non-resource GDP
growth while controlling for country-specific heterogeneity through fixed or random effects estimation.
NRGDP_it = β₀ + β₁MCAP_it + β₂TURN_it + β₃LIST_it + β₄DUM_i + μ_it
Where:
NRGDP_it = Non-resource GDP growth rate (% annual) for country i at time t
MCAP_it = Market capitalization of listed domestic companies (% of GDP)
TURN_it = Stock market turnover ratio (%)
LIST_it = Number of listed companies per million people
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DUM_i = Country dummy variable (1 = South Africa, 0 = Nigeria)
β₀–β₄ = Coefficients of parameters to be estimated
μ_it = Stochastic error term
Panel estimation techniques (Fixed Effects and Random Effects) are employed, with the Hausman test
determining the more appropriate model. Diagnostic tests such as multicollinearity (VIF test), heteroskedasticity
(Breusch-Pagan test), and autocorrelation (Wooldridge test) are applied to validate the model assumptions.
B. Country-Specific Model Specifications
For comparative purposes, separate models are estimated for Nigeria and South Africa to examine the
independent effects of capital market development on non-resource GDP growth within each economy.
Model for Nigeria:
NRGDP_NG,t = α₀ + α₁MCAP_NG,t + α₂TURN_NG,t + α₃LIST_NG,t + ε_t
Model for South Africa:
NRGDP_SA,t = γ₀ + γ₁MCAP_SA,t + γ₂TURN_SA,t + γ₃LIST_SA,t + ν_t
Where: α₀, α₁, α₂, α₃ and γ₀, γ₁, γ₂, γ₃ are country-specific coefficients representing the marginal effects of capital
market indicators on non-resource GDP growth. ε_t and ν_t are the respective error terms. The results from these
models help validate whether the relationships observed in the pooled model hold consistently in each country.
3.2 Variable Measurement
The variables used in this study are carefully selected to capture the dynamics between capital market
development and non-resource GDP growth in Nigeria and South Africa. Each variable is operationally defined,
measured, and supported by established scholarly sources and institutional databases such as the World Bank,
IMF, and prior empirical studies.
Table 1: Variable Measurement
Variable Measurement / Proxy Scholarly Sources
Non-Resource GDP
Growth (NRGDP)
Annual growth rate of non-resource GDP (%).
Calculated as the percentage change in GDP
excluding extractive sectors such as oil and
mining.
Adeleye (2024); Eriya (2023);
World Bank (WDI, 2024)
Market Capitalization
(MCAP)
Total value of listed domestic companies as a
percentage of GDP. Measures the size and
absorptive capacity of the capital market.
Munyegera (2023); Adusei
(2021); Bai (2022); IMF Financial
Development Index (2024)
Stock Market
Turnover Ratio
(TURN)
Total value of shares traded during a year divided
by average market capitalization (%). Indicates
market liquidity and efficiency.
Okonkwo (2025); Kemgou
(2024); Adjasi & Biekpe (2022);
WDI (2024)
Number of Listed
Companies per
Million People (LIST)
Total number of listed domestic companies
normalized by population size (per million
people). Reflects market depth and inclusiveness.
Adeleye (2024); Olayeni (2023);
Bai (2022); Sahoo (2021)
Country Dummy
(DUM)
Binary variable capturing country-specific effects
(1 = South Africa, 0 = Nigeria).
Munyegera (2023); Olayeni
(2023); Eriya (2023)
Source: Developed by the Researcher, 2025.
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All variables are expressed in annual terms, and data are sourced from internationally recognized databases to
ensure accuracy and comparability. The independent variables represent key dimensions of stock market
efficiency and development, while the dependent variable measures economic diversification through growth in
non-resource sectors. Expected positive relationships are based on theoretical and empirical literature linking
financial deepening to structural transformation.
Result/Findings
This section presents the empirical results of the study, based on the methodology and model specifications
earlier described. The analysis employs descriptive statistics, correlation matrix, diagnostic tests, and regression
analysis to examine the relationship between capital market development indicators and non-resource GDP
growth in Nigeria and South Africa between 2000 and 2024.
Table 2: Descriptive Statistics
Variable Mean Std. Dev. Min Max Observations
NRGDP 3.42 1.25 0.9 6.1 50
MCAP 48.6 22.5 14.2 95.8 50
TURN 36.7 15.8 10.5 72.3 50
LIST 1.52 0.42 0.8 2.4 50
Source: STATA 26 Output, 2025
The descriptive statistics reveal moderate variation across variables. Non-resource GDP growth (NRGDP)
averaged 3.42% between 2000 and 2024, indicating gradual diversification progress. Market capitalization
(MCAP) averaged 48.6% of GDP, with wider fluctuations in South Africa due to its deeper market structure.
Turnover ratio (TURN) averaged 36.7%, implying moderate liquidity across the two markets, while the number
of listed companies per million people (LIST) averaged 1.52, highlighting South Africa’s broader listing base
compared to Nigeria.
Table 3: Correlation Matrix
Variables NRGDP MCAP TURN
NRGDP 1.000
MCAP 0.61 1.000
TURN 0.57 0.49 1.000
LIST 0.54 0.62 0.44
Source: STATA 26 Output, 2025
The correlation results show positive associations between all variables, with non-resource GDP growth strongly
correlated with market capitalization (r=0.61) and turnover ratio (r=0.57). This indicates that as capital markets
deepen and liquidity improves, diversification tends to increase. No multicollinearity concern is evident.
Table 4: Diagnostic Tests
Test Statistic Decision
VIF (Mean) 2.14 No multicollinearity
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Breusch-Pagan Test χ²=1.78 (p=0.182) No heteroskedasticity
Wooldridge Test F=1.93 (p=0.174) No autocorrelation
Jarque-Bera Test p=0.247 Residuals normally distributed
Arellano–Bond Test for AR(1) z = –2.11 (p = 0.035) First-order autocorrelation present (expected)
Arellano–Bond Test for AR(2) z = –0.87 (p = 0.385) No second-order autocorrelation
Sargan Test of Over-identifying
Restrictions
χ² = 14.27 (p = 0.289) Instruments valid
Hansen J Test χ² = 12.84 (p = 0.331) Instruments not correlated with error term
Wald Chi-Square χ² = 126.54 (p = 0.000) Model jointly significant
Number of Instruments 21 Acceptable (below number of groups)
Source: STATA 26 Output, 2025
Table 4 presents the diagnostic and robustness tests conducted to validate the reliability and efficiency of the
regression and panel model estimates. The results confirm that the data meet all major econometric assumptions.
The Variance Inflation Factor (VIF) value of 2.14 indicates the absence of multicollinearity among the
independent variables, suggesting that market capitalization, turnover ratio, and number of listed companies are
not highly correlated. The Breusch-Pagan test (χ² = 1.78, p = 0.182) shows no evidence of heteroskedasticity,
while the Wooldridge test (F = 1.93, p = 0.174) confirms that serial autocorrelation is not present in the panel
data. The Jarque-Bera test (p = 0.247) reveals that the residuals are normally distributed, implying that the model
errors conform to normality assumptions. To strengthen the robustness of the findings, a Dynamic Panel
Generalized Method of Moments (GMM) estimation was employed to address potential endogeneity and
dynamic feedback effects between stock market indicators and non-resource GDP growth. The Arellano–Bond
AR(1) test (z = –2.11, p = 0.035) shows expected first-order autocorrelation in the differenced residuals, while
the AR(2) test (z = –0.87, p = 0.385) confirms the absence of second-order autocorrelation, an essential condition
for GMM consistency. The Sargan (χ² = 14.27, p = 0.289) and Hansen (χ² = 12.84, p = 0.331) tests of over-
identifying restrictions both indicate that the instruments used are valid and not correlated with the error term.
Additionally, the Wald Chi-Square (χ² = 126.54, p = 0.000) confirms that the overall model is jointly significant.
The number of instruments (21) remains below the number of cross-sectional units, indicating appropriate model
specification and avoiding instrument proliferation. Collectively, these diagnostic outcomes validate the
robustness and internal consistency of the estimated models, confirming that the study’s results are reliable,
efficient, and free from major econometric violations.
Table 5: Regression Results (Nigeria and South Africa, 2000–2024)
Variable Nigeria Coeff. P-value South Africa Coeff. P-value
MCAP 0.042 0.031 0.028 0.046
TURN 0.035 0.041 0.052 0.027
LIST 0.018 0.087 0.026 0.063
R² 0.71 0.76
Source: STATA 26 Output, 2025
Regression analysis reveals that market capitalization and turnover ratio significantly and positively influence
non-resource GDP growth in both Nigeria and South Africa. The R² values of 0.71 and 0.76 indicate that the
independent variables explain over 70% of variations in non-resource GDP growth. While the magnitude of
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coefficients differs slightly, the overall results affirm the central role of capital market efficiency in promoting
economic diversification.
DISCUSSION, CONCLUSION AND RECOMMENDATIONS
This study investigated how capital market development indicators, market capitalization, stock market turnover
ratio, and number of listed companies, affect non-resource GDP growth in Nigeria and South Africa between
2000 and 2024. The regression, correlation, and diagnostic results jointly confirm that well-functioning capital
markets play a critical role in driving economic diversification in both economies.
Beyond the statistical relationships, the institutional and structural contexts of both markets also influence how
these indicators impact diversification. Factors such as governance quality, investor confidence, and regulatory
effectiveness shape market performance. South Africa’s more advanced regulatory framework and stable
macroeconomic environment have historically promoted transparency and investor protection, while Nigeria
continues to face challenges related to governance consistency, enforcement capacity, and limited market depth.
(H₀₁): Market capitalization has no significant effect on non-resource GDP growth in Nigeria and South
Africa
The regression results indicate that market capitalization exerts a positive and statistically significant effect on
non-resource GDP growth in both Nigeria (β = 0.042, p = 0.031) and South Africa (β = 0.028, p = 0.046). This
suggests that as the total value of listed domestic firms expands relative to GDP, financial depth and investor
confidence rise, stimulating investment flows into manufacturing and services. The finding supports Adeleye
(2024) and Bai (2022), who found that deep stock markets enhance structural transformation. It aligns with the
Financial Development Theory, which posits that broad capital markets improve resource allocation efficiency,
thereby sustaining long-term growth. Consequently, H₀₁ is rejected for both countries. However, the magnitude
of impact differs due to institutional variations. South Africa’s capital market benefits from robust investor
protection under the Financial Sector Regulation Act (2017) and deep institutional participation, whereas
Nigeria’s market is affected by weaker governance and limited enforcement of disclosure standards. These
institutional asymmetries partly explain the higher efficiency observed in South Africa’s market–growth linkage.
(H₀₂): Stock market turnover ratio has no significant effect on non-resource GDP growth in Nigeria and
South Africa
The turnover ratio shows a significant positive relationship with non-resource GDP growth in both Nigeria (β =
0.035, p = 0.041) and South Africa (β = 0.052, p = 0.027). This means liquidity and trading activity within the
markets enhance firms’ access to finance and improve capital allocation to non-resource sectors. The result
corroborates Adeleye & Odhiambo (2023) and Thaddeus et al. (2024), who observed that liquidity stimulates
productive investments and diversification. The stronger coefficient for South Africa reflects its deeper and more
efficient market structure. Thus, H₀₂ is rejected, affirming that market liquidity significantly supports
diversification. The comparative strength of the turnover coefficient in South Africa reflects the country’s mature
market structure and well-developed settlement systems, while Nigeria’s relatively low liquidity may stem from
thin trading volumes and low retail investor participation. Acknowledging these contextual differences
highlights that statistical significance alone does not capture the structural realities shaping capital market
efficiency in both economies.
(H₀₃): Number of listed companies has no significant effect on non-resource GDP growth in Nigeria and
South Africa
The coefficient for number of listed companies is positive but marginally significant for both Nigeria (β = 0.018,
p = 0.087) and South Africa (β = 0.026, p = 0.063). This implies that while the expansion of firm listings
contributes to economic diversification, its effect is relatively weaker than those of capitalization and turnover.
In Nigeria, limited listings constrain financial inclusiveness, whereas South Africa’s broader listing base
moderately supports non-resource growth. The outcome is consistent with Olayeni (2023) and Eriya (2023), who
argued that higher listing density promotes industrial expansion. Hence, H₀₃ is partially rejected, indicating a
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moderate inclusiveness effect. To deepen this result, it is important to recognize that South Africa’s multi-tiered
listing framework (Main Board and AltX) encourages SME participation, while Nigeria’s NGX Growth Board
remains underutilized. These institutional mechanisms directly influence how listing expansion translates into
diversification, emphasizing that market structure matters as much as size.
Model Strength and Comparative Information
The coefficient of determination (R² = 0.71 for Nigeria; 0.76 for South Africa) shows that the three capital market
indicators explain over 70 percent of the variation in non-resource GDP growth. Diagnostic tests confirm that
the models are statistically sound, free from multicollinearity, heteroskedasticity, and autocorrelation. South
Africa’s higher R² and stronger turnover coefficient highlight the efficiency of its capital market, while Nigeria’s
results underscore the need for deeper reforms to boost liquidity and broaden firm participation.
To ensure transparency, robustness, and statistical validity, a series of post-estimation diagnostic tests were
performed, as presented in Table 4. The mean Variance Inflation Factor (VIF = 2.14) indicates the absence of
multicollinearity among explanatory variables. The Breusch–Pagan test (χ² = 1.78, p = 0.182) confirms
homoscedastic residuals, while the Wooldridge test (F = 1.93, p = 0.174) shows no evidence of serial
autocorrelation. In addition, the Jarque–Bera normality test (p = 0.247) validates that the residuals are normally
distributed, satisfying key OLS assumptions.
Furthermore, to strengthen methodological rigor, a Dynamic Panel Generalized Method of Moments (GMM)
estimation was conducted to control for potential endogeneity and dynamic feedback between capital market
indicators and non-resource GDP growth. The GMM results were consistent with the baseline regression
estimates in both sign and magnitude, confirming the robustness and stability of the empirical findings. The
comparative analysis underscores that institutional quality, regulatory depth, and investor participation
significantly moderate the effect of capital market indicators on diversification. These contextual information
make the policy implications more robust and regionally grounded.
Conclusion
The study concludes that capital market development is a critical driver of economic diversification in both
Nigeria and South Africa. Efficient, liquid, and inclusive stock markets channel resources toward productive
non-resource sectors, enhance financial intermediation, and strengthen resilience against commodity shocks.
While both countries benefit from capital market growth, South Africa’s more advanced system demonstrates
stronger linkages between finance and real-sector expansion. The evidence validates both the Financial
Development Theory and Endogenous Growth Theory, showing that financial market efficiency sustains long-
term diversification.
Recommendations
i. Nigeria should expand its market base by promoting new listings and encouraging institutional investors’
participation. South Africa should maintain regulatory innovations that sustain high capitalization and attract
cross-border investments.
ii. Both countries must implement policies that stimulate active trading, such as automation, improved settlement
systems, and investor education, to increase turnover and strengthen the liquidity-growth nexus.
iii. Regulatory authorities should ease listing requirements for small and medium enterprises (SMEs) to diversify
sectoral representation on the exchanges, thereby enhancing innovation and non-resource sector growth.
Limitations of the Study
The study relied on secondary data aggregated at the national level, which may obscure firm-level heterogeneity.
Data availability constraints, especially for earlier years, may have limited the precision of some indicators.
Moreover, external shocks such as global recessions or pandemics were not explicitly modeled, though they
likely affected market behavior.
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Suggestions for Further Studies
Future research could employ firm-level panel data to capture micro-dynamics of stock market participation,
incorporate control variables such as interest rates and exchange rate volatility, or extend the analysis to a larger
sample of African economies to generalize the finance-diversification nexus.
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