Financial Deepening and Inclusive Growth in West Africa: Evidence from Panel Corrected Standard Errors (PCSE) Analysis

Financial Deepening and Inclusive Growth in West Africa: Evidence from Panel Corrected Standard Errors (PCSE) Analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Financial Deepening and Inclusive Growth in West Africa: Evidence from Panel Corrected Standard Errors (PCSE) Analysis Oluwatoba Oyedele Adeniwura, Abayomi Toyin Onanuga This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8799144/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study examines the nexus between financial deepening and inclusive growth in West Africa using balanced annual panel data for 15 countries over the period 2000–2023. Inclusive growth is measured using a composite index generated through Principal Component Analysis (PCA), following the UNCTAD (2022) multidimensional framework that incorporates indicators of economic performance, living conditions, and equality. Financial deepening is also captured through a PCA-based index aggregating credit to the private sector, money supply, gross national savings, and lending rates, reflecting the depth, accessibility, and efficiency of the financial system. The study employs Panel Corrected Standard Errors (PCSE) to address heteroskedasticity and cross-sectional dependence inherent in panel data. The results reveal that financial deepening exert significant positive effect on inclusive growth, supporting the McKinnon–Shaw hypothesis that deeper financial systems enhance broad-based economic participation. Control of corruption also exerts significant positive influence on inclusive growth, underscoring the importance of strong and transparent institutions in ensuring equitable distribution of economic gains. Conversely, foreign direct investment and inflation display negative but statistically insignificant effects on inclusive growth. The study contributes to the literature by adopting a multidimensional approach to inclusive growth and offers policy-relevant insights for promoting inclusive growth in West Africa. JEL Codes: G20; O40; D73; C23; O55 Financial Deepening Inclusive Growth Institutional Quality Panel Corrected Standard Error West Africa 1. Introduction The emergence of inclusive growth as a topical issue in the literature stems from a confluence of factors ranging from the imperatives of global economic integration to the necessity to address persistent socio-economic disparities globally (Arabiyat et al., 2020 ). Inclusive growth goes beyond mere economic expansion to encompass broader objectives of enhancing human welfare, reducing disparities and promoting social cohesion. It emphasizes the importance of ensuring wide distribution of growth benefits across the society, particularly among marginalized groups, women and rural populations (Afolabi, 2020 ; Olanrewaju et al., 2019 ; Ayinde & Yinusa, 2016 ). Although inclusive growth has gained widespread recognition globally as a strategy to ensure that all economic agents participate in and benefit equitably from economic expansion, its goal have yet to be fully achieved in the context of West Africa. In the region, significant proportions of the population are not included in the growth process and this has led to extreme poverty while the minority enjoys the region's wealth (Fall et al., 2020 ). In Africa, inclusive growth has emerged as a critical goal against the backdrop of persistent poverty, inequality and social exclusion (Kong et al., 2020). The region is characterized by a diverse mix of economies, ranging from low-income agrarian societies to middle-income oil-exporting nations. The continent's impressive economic growth rates in recent years have not translated into improvements in living standards (Nketia & Kong, 2021). Despite the region’s abundance of natural resources and potentials for economic growth, West Africa faces challenges of persistent poverty, inequality, and political instability (Cui et al., 2022 ). Several factors affect inclusive growth in developing countries. These factors include unequal distribution of benefits and limited access to finance (Olanrewaju et al., 2019 ; Ayinde & Yinusa, 2016 ; Migap et al., 2015 ). Financial deepening, which involves enhancing access to financial services such as savings, credit, insurance, and payment systems empower people, especially the economically active and motivate them to invest in economically productive activities. (Ehiedu et al., 2023; Afolabi, 2022 ). However, the benefits of financial deepening are often constrained in West Africa by persistent challenges such as limited access to formal banking services, as a large percentage of the population remains unbanked or inadequately served by financial institutions (Cui et al, 2023). Other than the absence of financial services, poor regulatory frameworks, and fragile financial systems, under-developed economies (particularly the informal sector) are a further impediment to the provision of financial services to marginalized populations (Ntow-Gyamfi et al, 2019 ). Although a growing body of empirical studies suggests that financial deepening supports inclusive growth, limited attention has been given to understanding how it specifically influences inclusive growth outcomes for marginalized groups within the region. (Afolabi, 2022 ; Cui Weng & Song, 2022). Previous studies on the link between financial deepening and inclusive growth have relied on the use of traditional indicator such as Gross Domestic Product (GDP), per capita income and poverty level in measuring economic progress (Nabi et al., 2022 ; Bacchetta et al., 2021; Aslam et al., 2021; Talah et al., 2020; Zafar et al., 2019 ), little has been done in using aggregate measures of inclusive growth specifically in West Africa. Meanwhile, using a single measure including the traditional indicators may not capture all the dimensions or component of inclusive growth. To address this measurement gap in the literature, UNCTAD ( 2022 ) approach to measuring inclusive growth involving three dimension comprising economy, living condition and equality component of inclusive growth was employed and aggregated using Principal Component Analysis to generate inclusive growth index. This ensured a balanced view on the measure of inclusive growth. This motivated this study to investigate how financial deepening affects inclusive growth in West Africa. In this study, the following research question was answered: Does financial deepening affect inclusive growth in West Africa? The significance of this study lies in its ability to help government and policymakers in West Africa to design well-informed financial strategies that promote economic development and assure that the benefits are fairly distributed to all members of the society. This study is structured into five sections. After the introductory section is followed by a review of relevant literature, then the methodology, while section four presents and discusses the empirical findings and the final section provides the conclusion and policy recommendations. 2. Literature Review The literature review section comprises of the conceptual review, theoretical review and empirical review. 2.1 Conceptual Review 2.1.1 Financial Deepening Financial deepening is a multifaceted concept that has been examined and defined by various scholars over the years. Ndebbio ( 2004 ) conceptualised financial deepening as the progress in the availability of financial assets within the economy. Nzotta and Okereke (2009) present a different perspective, suggesting that financial deepening reflects how effectively financial institutions can channel savings into productive investment activities. Kinyondo ( 2018 ) further expands the definition, emphasising that financial deepening involves increased financial service delivery across various societal levels. This entails not only increased accessibility to financial services but also efficient resource allocation, broadened opportunities through diversification, risk mitigation within financial systems and the enhancement of payment systems. Onuoha (2018) provides a comprehensive definition by pointing that financial deepening occurs when financial markets, instruments and entities are synergistically engage to mitigate contract enforcement, transaction, and information costs. This synergy fulfills five fundamental roles comprising: facilitating the exchange of goods and services, aggregating and channeling financial savings, gathering and processing information for efficient allocation, overseeing investments and enforcing corporate governance, and diversifying while mitigating risks (Okafora & Lilian, 2022 ). In another perspective, financial deepening is characterized as a strategy aimed at stimulating the activities of financial institutions, including the stock market, banking institution and foreign and domestic investments (Zafar et al., 2019 ). Okafor et al. ( 2021 ) elaborated on this, stating that financial deepening involves the expansion and enhancement of financial markets, intermediaries and institutions to mobilise financial resources, thereby fostering enhanced economic performance. Ajudua and Odishika ( 2022 ) contribute to the discourse by looking at financial deepening as the effective deployment of savings for investments by financial institutions through enhanced financial intermediation, thereby bolstering the competitive efficiency of financial markets. Within a deepened financial system, the cost of capital tends to be lower due to diverse financial instruments and efficient intermediation functions, compared to less developed financial sectors. An expanded financial sector mitigates risks faced by firms, fostering portfolio diversification and shielding the economy from fluctuations in international economic conditions (Nwaolisa & Cyril, 2019 ). Beyond wealth generation and economic growth, financial deepening facilitates increased access to financial services for the impoverished, lowering poverty rates and contributing to reduction in income inequality and entrepreneurial growth (Nwakobi et al., 2019 ). Financial deepening, often measured by indicators, such as money supply to GDP ratio, private sector credit, and the dimensions of financial markets, has been associated with numerous positive outcomes for economies. Demirguc-Kunt et al. ( 2017 ) highlight its role in promoting capital accumulation, facilitating investment in productive sectors and boosting economic growth. Countries with deeper financial systems tend to exhibit lower poverty rates and higher levels of income equality (Demirgüç-Kuntet al., 2001; Beck, 2013 ). This study follows the definition of financial deepening by Onuoha (2018), that financial deepening occurs when financial markets, instruments and entities are synergistically engage to mitigate contract enforcement, transaction, and information costs. This synergy fulfills five fundamental roles: facilitating the exchange of goods and services, aggregating and channeling financial savings, gathering and processing information for efficient allocation, overseeing investments and enforcing corporate governance, and diversifying while mitigating risks (Okafora & Lilian, 2022 ). 2.1.2 Inclusive Growth In development economics, the phrase inclusive growth is often used interchangeably with broad-based growth, shared growth, or pro-poor growth (Ianchovichina & Lundstrom-Gable, 2009). This amalgamation of terminology reflects the complex nature of inclusive growth. Ravallion and Chen (2003) posited that the inclusivity of growth is contingent upon a faster income growth rate experienced by poor households compared to the overall population. This perspective underscores the imperative of addressing income disparities to achieve inclusivity in economic expansion. Similarly, Ali and Son ( 2007 ) extended the definition by emphasising that inclusive growth enhances average opportunities accessible to the populace, signifying an increase in the social opportunity function. Zhuang (2007) conceptualised inclusive growth as "growth with equitable opportunities."This definition underscores the need to foster sustainable growth while concurrently expanding access to promote social inclusion of diverse populations. The emphasis on equitable opportunities in the definition, acknowledges the importance of not just growth but inclusive growth. Bhalla (2007) added another dimension to the discourse, emphasising the role of productive employment in defining inclusive growth. He asserts that mere job generation is insufficient without a simultaneous focus on augmenting labour productivity. In essence, Bhalla (2007) contended that inclusive growth revolves around fostering growth that encompasses the entire populace, ensuring that employment opportunities lead to meaningful economic participation. Habito (2009) aligned inclusive growth with economic expansion, as measured by the gross domestic product (GDP), concurrently reducing poverty levels. This perspective is further supported by Rauniyar and Kanbur (2010), affirming the interconnectedness of economic growth and poverty alleviation. Klasen (2010) introduces a crucial distinction, asserting that inclusive growth is a broader concept encompassing all societal segments, from the poor to the affluent. According to the Organisation for Economic Co-operation and Development (2014), inclusive growth represents an economic development process, where everyone has the opportunity to participate and the benefits of economic growth are equitably distributed to all people. This definition encapsulates various facets of living standards, including income, health, and employment, emphasising the multidimensional nature of inclusivity (Arabiyat et al., 2020 ). The European Commission (EC) (2020) contributes by linking inclusive growth to a robust labour market, economic, social, and territorial cohesion. Empowerment through heightened employment rates, strategic investment in skills, poverty alleviation efforts, and modernisation of labour markets, training, and social protection systems constitute the core elements of the EC's approach. This multifaceted strategy aims to enable individuals to navigate and adapt to societal changes, fostering the development of a unified society. This study adopts the definition of inclusive growth proposed by Ali and Son ( 2007 ), which views inclusive growth as a process that expands the average opportunities available to the population, signifying an increase in the social opportunity function. 2.2 Theoretical Review This study is anchored on the Finance-Growth theory proposed by McKinnon and Shaw in the early 1970s. This theory expounds the importance of the accessibility of financial services in driving economic growth, as a well functioning financial system fosters investment, entrepreneurship, and efficient resource allocation within an economy by providing individuals and businesses with avenues for credit, savings, and insurance,wth (Demirgüç-Kunt et al., 2017). One of the key propositions of the Finance-Growth theory is the concept of a finance-led growth model. By mobilising savings and allocating them to productive investments, financial institutions contribute to the overall expansion of the economy. In this context, policies aimed at improving financial access, deepening capital markets, and strengthening regulatory oversight are critical for promoting inclusive growth (Ntow-Gyamfi et al., 2019 ; Yinusa et al., 2020 ). The equation that encapsulates the Finance-Growth theory is the finance-led growth model which is expressed as: \(\:Y=f(K,L,H,A)\) 1 In this model, 𝑌 represents the level of output, 𝐾 stands for physical stock, 𝐿 denotes the labour force, 𝐻 captures human capital, and 𝐴 reflects technological progress or total factor productivity. Essentially, output (𝑌) is determined by the factors of production: Capital (K), Labour (L), human capital (H) and technology (A). Moreover, the Finance-Growth Theory emphasizes how various indicators of financial development are closely linked to the pace and sustainability of economic growth (Acemoglu, 2002 ). This relationship can be captured through equations such as: G = g ( FD ) 2 Where: G represents inclusive growth and FD denotes financial development indicators, such as measures of access to credit, depth of financial markets, or efficiency of financial intermediation; indicating that improvements in financial access, market structure, or regulatory frameworks can lead to higher levels of economic growth. 2.3 Empirical Review on Financial Deepening and Inclusive Growth This sub-section focuses on the empirical review involving financial deepening and inclusive growth. Migap et al. ( 2015 ) studied inclusive growth and financial deepening in Nigeria based on World Bank Development Indicators and the Central Bank of Nigeria Statistical Bulletin for the years 1980–2015. The study used the Dynamic Ordinary Least Squares (DOLS) cointegration technique and concluded that financial deepening does not positively affect inclusive growth in Nigeria. Odeleye and Olusoji ( 2016 ) examined financial deepening and economic growth for the years 1981–2014 in Nigeria using several econometric analysis models. The study focuses on the extent of financial service provision and its relation to the alleviation of poverty, the improvement of welfare, and economic growth. The study state in a well-specified regression framework that Nigeria’s economic growth is positively affected by the money supply, the liquidity ratio, and the credit to the private sector. Qui (2017) examines financial deepening and economic growth in countries with a currency board system such as Hong Kong and Singapore/Malaysia and East Africa. The study digitised and systematically analyzed the currency boards’ financial data and corresponding ratios. The analysis concluded that financial deepening increased in tandem with economic growth during the years of currency board implementation in the selected countries. Using regression and secondary data, Maureen (2018) examines the effect of financial deepening on economic growth in Nigeria. The study notes that the ratio of money supply to GDP positively affects economic growth in Nigeria and emphasizes the importance of financial institutions in sustaining economic growth through the mobilisation of savings. Likewise, in the same context, Appiah et al. ( 2020 ) studied the effect of financial development and poverty reduction in five African emerging economies from 1995 to 2015. The study applied the Fully Modified Ordinary Least Squares (FMOLS) method and used liquid liabilities and domestic credit as proxies for financial development and concluded that the two proxies achieved some level of poverty reduction, whereas the economic growth and government expenditure proxies were insignificant. In a broader context, Sugiyanto and Yolanda ( 2020 ) examined the effect of financial deepening on economic growth, inequality and poverty in 73 countries for the period 1991–2015 using panel regression with interaction dummy variables. The findings indicated that financial deepening also facilitated economic growth, and a reduction in inequality and poverty in emerging markets and developing economies. These impacts differ by level of economic development and are more significant in advanced and emerging economies. For the period of 1984 to 2017, Yinusa et al. ( 2020 ) used asymmetric cointegration to analyse the phenomenon of institutional quality, financial development, and inclusive growth in Nigeria. While studying Nigeria, they focused on 34 years of annual time series. The key variables for the study were the natural log of per capita GDP of Nigeria (West and Central Africa, World Bank, Development Indicators) and credit to the private sector (Central Bank of Nigeria, Statistical Bulletin). The study found 34 years of annual time series data to demonstrate a stable and long-term relationship amongst the variables. The study also pointed out the unequal adjustment in the long-term equilibrium among institutional quality, financial deepening, and inclusive growth in Nigeria. Nketia and Kong (2021) reported a positive association between financial deepening and inclusive growth in a panel of 48 African economies over the period 2000–2019. Using Panel Quantile Regression with Fixed Effects alongside Dumitrescu and Hurlin causality tests, the study found that the combination of financial deepening and control of corruption is vital for the advancement of inclusive growth in middle income countries. Similarly, in the analysis of the growth of finance and inclusive growth in Nigeria, Ilemona and Ome ( 2021 ) applied time-series data for the period 1986–2019. The study employed the ARDL approach and the results showed that the money supply, private sector credit, and gross national savings support inclusive growth in Nigeria, while the lending rate hinders it. Using the IMF and World Bank databases, Cui et al ( 2022 ) used a Spatial Durbin Model and analyzed the association among financial inclusion, renewable energy consumption, and inclusive growth for 40 countries for the period of 2010 to 2020. The study examined the direct association among the aforementioned variables and the upgrading of industrial structure as a possible moderator of domestically renewable energy consumption and inclusive growth. The study found a positive and reinforcing relationship among the variables. In the same vein, Sarpong and Nketiah- Amponsah (2022) examined the dimension of financial deepening on inclusive growth in 46 countries of the Sub-Saharan Africa and accessed World Bank panel data on Global Financial Inclusion, Worldwide Governance Indicators, Poverty and Equity, and World Development Indicators for the period 2004–2018. Using the system GMM estimator of Arellano–Bover/Blundell–Bond, the study showed that the depth of financial services positively impacted inclusive growth and that a unit increase in the depth of financial services improved inclusive growth by 0.03. Afolabi ( 2022 ) examined the relationship between financial deepening and inclusive growth in Nigeria for the years 1981 to 2017 using the Auto-Regressive Distributed Lag (ARDL) model on the data from the Central Bank of Nigeria Statistical Bulletin and the World Bank Development Indicators. Aside from the high illiquidity that adversely affected inclusive growth, the study has shown positive contribution and significant influence of the financial deepening indicators to the inclusive growth in the short run and long run. From 1986 to 2020, Ajudua and Odishika ( 2022 ) used time series data to analyse the financial deepening and Nigeria’s economic growth. While using Nigeria as a case study and confirming stationarity using unit root tests, the study applied the ARDL and ECM methodologies and determined positively that economic growth was contributed to by the money supply, market capitalization and liquid liabilities. They, however, found that credit to the private sector and lending rates had no effect. Obunike-Ezeuli et al. ( 2024 ) assessed the financial deepening-poverty nexus in Nigeria from 1994 to 2022 using ARDL approach. The study found that financial inter-relation ratio contributes to poverty reduction while national income ratio exacerbates poverty. 3. Methodology This study examined the nexus between financial deepening and inclusive growth using annual panel data on 15 West African countries Africa (excluding Liberia due to unavailability of data) covering the period of 2000 to 2023 which is a period of twenty four (24) years. Thus with 15 countries in West Africa (after excluding Liberia due to unavailability of data) and time period of 24 years, the total observation of this study is three hundred and sixty (360) which is large enough for standard econometric estimation. The choice of this period is informed by the period in which inclusive growth gained prominence in many countries in Africa. The inclusive growth concept can be traced back to the Millennium Development Goals (MDGs) that were adopted in 2000, where the necessity for growth to be inclusive was emphasized before the widespread usage of the term and its adoption. The MDGs have since evolved into the United Nations Sustainable Development Goals (SDGs) particularly Goal 8, which promotes inclusive and sustainable economic growth, as well as full and productive employment for all. Equally, the choice of the period was informed by data availability as data on most of the components of the three categories of inclusive growth are only available from year 2000. To examine the effect of financial deepening on inclusive growth, ICG is proxied using a composite index generated through Principal Component Analysis (PCA). This index reflects a multidimensional understanding of inclusive growth by employing UNCTAD ( 2022 ) approach comprising indicators from economic performance (GDP per capita, agricultural productivity), living conditions (employment in agriculture, life expectancy), and equality measures (adult literacy, income inequality). Instead of including the individual financial indicators as separate regressors, a composite index of financial deepening (FID) was generated using Principal Component Analysis (PCA). This methodological approach aligns with the study by Ilemona and Ome ( 2021 ) on financial deepening and inclusive growth nexus in Nigeria. The FID index aggregates key indicators which are credit to the private sector (DOC), money supply to GDP (MS), gross national savings (SAV), and lending rates (LEND), capturing the depth, accessibility, and efficiency of the financial system. To broaden the scope and reflect relevant institutional and macroeconomic influences on inclusive growth, the model introduces control of corruption, inflation and foreign direct investment as intervening variables. According to Sanga and Aziakpono ( 2023 ) and Bandura ( 2020 ), control of corruption (COC) is included to account for governance quality, which plays a crucial role in determining equitable access to financial resources. According to Ajudua and Odishika ( 2022 ) and Liu et al. ( 2020 ), inflation (INF) and foreign direct investment (FDI) are also included as intervening variables, recognizing that macroeconomic stability and foreign capital inflows can significantly influence both financial sector performance and inclusive growth. These adjustments transit the theoretical function of Eq. 2 into a streamlined and policy-relevant empirical specification designed to address the effect of financial deepening on inclusive growth. The resulting functional model is expressed as: \(\:ICG\:=\:f\:(FID,\:COC,\:INF,\:FDI)\) 3 The transformation of the functional relationship into a Panel Corrected Standard Errors model is presented as follows \(\:{\:\:ICG}_{it}={\alpha\:}_{0}+{\alpha\:}_{1}{FID}_{it}+{\alpha\:}_{2}{COC}_{it}+{\alpha\:}_{3}{INF}_{it}+{\alpha\:}_{4}{FDI}_{it}+{\epsilon\:}_{it}\) 4 In equation (iv), \(\:{\:\:ICG}_{it}\) denotes inclusive growth for entity i at time t, the independent variables are FID it (financial deepening), COC it (Control of corruption), INF it (Inflation) and FDI it (Foreign direct investment) for country i at time t; The model includes β 0 as the intercept term, \(\:{\alpha\:}_{1}\) , \(\:{\alpha\:}_{2}\) , \(\:{\alpha\:}_{3}\) and \(\:{\alpha\:}_{4}\) are the coefficients for the respective independent variables. ε it as the error term capturing random shocks or unexplained variations in inclusive growth. The A priori expectation of each variables are presented in Table 1 . Table 1 A priori Expectation Variables Expected sign Trade Liberalisation (TRL) \(\:\frac{\varvec{I}\varvec{C}\varvec{G}}{\varvec{T}\varvec{R}\varvec{L}}>0\) Positive Domestic Credit (DOC) \(\:\frac{\varvec{I}\varvec{C}\varvec{G}}{\varvec{D}\varvec{O}\varvec{C}}>0\) Positive Foreign Direct Investment (FDI) \(\:\frac{\varvec{I}\varvec{C}\varvec{G}}{\varvec{F}\varvec{D}\varvec{I}}>0\) Positive Inflation (INF) \(\:\frac{\varvec{I}\varvec{C}\varvec{G}}{\varvec{I}\varvec{N}\varvec{F}}0\) Positive Control of corruption \(\:\frac{\varvec{I}\varvec{C}\varvec{G}}{\varvec{C}\varvec{O}\varvec{C}}>0\) Positive Source: Author’s Compilation, 2025 Table 2 Measurement of variables Variables Description Measurement Source Inclusive Growth Index (ICG) Aggregates of indicators from three categories which are economy (GDP per capita, Agriculture, forestry, and fishing, value added), living conditions (Employment in agriculture, Life expectancy at birth) and equality (Literacy rate, Gini index) UNCTAD (2023) Financial Deepening Index (FID) Aggregates of MS/GDP ratio, Domestic credit provided by financial sector, Gross savings, Lending interest rate WDI (2023) Inflation (INF) Consumer price index WDI (2023) Foreign investment (FDI) Foreign direct investment, net inflows (% of GDP) WDI (2023) Control of corruption (COC) Control of corruption: Estimate WGI (2023) Source: Author’s Compilations, 2025 The measurements of the variables are provided in Table 2 . 3.2 Estimation Procedure This study employed various estimation techniques to analyse the effect of financial deepening on inclusive growth. The pre-estimation test involves normality test, test for multicollinearity and unit root test. For the econometric analysis, Panel Corrected Standard Error (PCSE) was employed. The choice of employing PCSE was to address the issue of heteroskedasticity and cross-sectional dependence associated with cross-sectional studies into the analysis of the relationship. PCSE address this limitation by adjusting the standard errors in panel models, making them particularly suitable for studies with a large number of cross-sectional units (N) and relatively short time periods (T) (Zidi & Hamdi, 2024 ). 4. Results and Discussion 4.1 Principal Component Analysis In the process of constructing an Inclusive Growth Index (IGI), aggregates of indicators from three categories of inclusive growth which are economy (GDP per capita, Agriculture, forestry, and fishing, value added), living conditions (Employment in agriculture, Life expectancy at birth) and equality (Literacy rate, Gini index) were considered (UNCTAD, 2022 ). Given the inherent correlation among these indicators, using them individually in a single model could lead to redundancy and loss of information. Therefore, following the methodological approach of Wani ( 2022 ), Principal Component Analysis (PCA) was applied to derive a composite index. The PCA results presented in Table 3 indicate that the first principal component captures approximately 58.56% of the total variation, while the second component accounts for 16.27%, and the third explains 9.17%. Considering the high proportion of variance captured by the first principal component and exceeding the commonly accepted Kaiser criterion threshold of eigenvalues greater than 1 for component retention, this study utilizes the eigenvector values of the first principal component as weights to construct the Inclusive Growth Index, denoted as ICG. Table 3 Principal Component Analysis Results for Inclusive Growth Index (Eigen values Summary) N.umber Value Difference Proportion Cumulative Value Cumulative Proportion 1 3.5135 2.5372 0.5856 3.5135 0.5856 2 0.9764 0.4261 0.1627 4.4899 0.7483 3 0.5503 0.0619 0.0917 5.0402 0.8400 4 0.4884 0.2455 0.0814 5.5286 0.9214 5 0.2429 0.0143 0.0405 5.7715 0.9619 6 0.2285 --- 0.0381 6.0000 1.0000 Source: Author’s Computation, 2025 Given the inherent correlation among different proxies of financial deepening (such as MS/GDP ratio, Domestic credit provided by financial sector, Gross savings, Lending interest rate), incorporating them individually into an econometric model could lead to multicollinearity issues and the loss of critical information. To address this, the study employed PCA to construct a composite Financial Deepening Index (FID), following methodologies used in Meierrieks et al. ( 2011 ). Table 4 Principal Component Analysis Result for Financial Deepening Index Number. Eigenvalue. Difference. Proportion. Cumulative Value Cumulative Proportion 1 2.1809 1.1690 0.5452 2.1809 0.5452 2 1.0119 0.3214 0.2530 3.1928 0.7982 3 0.6905 0.5738 0.1726 3.8833 0.9708 4 0.1167 --- 0.0292 4.0000 1.0000 Source: Author’s Computation, 2025 The Principal Component Analysis (PCA) result for the Financial Deepening Index is presented in Table 4 . This revealed that the first two components have eigenvalues greater than 1. However, only the first component was retained for financial deepening index as it accounts for approximately 54.5 percent of the total variance across indicators. 4.2 Descriptive Analysis The descriptive analysis result is provided in Table 5 . For inclusive growth (ICG), the mean value suggest the level of inclusive growth in the region is low implying that a significant proportion of the populations are excluded in the growth process. However, the relatively high standard deviation (1.877) indicates considerable variability in inclusive growth across the sample. Financial deepening (FID) also suggest a mean of 9.01E-17, implying limited access to financial services of the populace in the region. With a high positive skewness (1.451) and kurtosis (5.842), indicating a distribution with frequent low values and occasional extreme high values. This suggests that financial deepening is uneven across West Africa, with some countries experiencing significant financial sector development while others lag behind. Table 5 Descriptive Statistics ICG FID FDI INF COC Mean 4.48E-16 9.01E-17 3.612627 6.325080 -0.583918 Median -0.238878 -0.284934 2.464783 3.890768 -0.679235 Maximum 6.050205 5.926800 32.41435 47.64287 1.155066 Minimum -3.341374 -2.627300 -11.19173 -3.502586 -1.597468 Std. Dev. 1.877047 1.478847 4.130567 7.698572 0.537615 Jarque-Bera 79.40889 247.6479 2111.073 848.8935 103.9720 Probability 0.000000 0.000000 0.000000 0.000000 0.000000 Obs. 360 360 360 360 360 Note : ICG: inclusive growth; FID: financial deepening; FDI: foreign direct investment; INF: inflation; COC: control of corruption Source: Author’s Computation, 2025 FDI has a mean of 3.613 with a standard deviation. of 4.130, reflecting moderate variability. The high positive skewness (2.391) and extreme kurtosis (13.856) suggest a distribution with frequent low values and rare extreme high values, indicating sporadic large FDI inflows. Inflation (INF) with mean of 6.325 and standard deviation of 7.698, indicate substantial variability across the region. The high positive skewness (2.190) and kurtosis (9.116) suggest a distribution with frequent low values and occasional extreme high inflation rates, possibly due to external shocks or supply-side constraints. Control of corruption (COC) has a mean of -0.584, indicating negative perceptions of corruption control in the region. The relatively low standard deviation (0.537) suggests less variability in these perceptions. The positive skewness (1.105) and kurtosis (4.430) indicate a distribution with frequent low values and occasional extreme high values, suggesting persistent governance challenges. 4.3 Results of Correlation Matrix of the Study Variables Table 6 Multicollinearity Result Variable VIF 1/VIF FID 2.13 0.4702 COC 1.85 0.5401 FDI 1.22 0.8176 INF 1.17 0.8516 Mean VIF 1.58 Source: Author’s computation, 2025 The result presented in Table 6 provide the multicollinearity test results using Variance Inflation Factor, as it is used to assess both the presence and the degree of multicollinearity by showing how much the variance of a regression coefficient is increased due to correlations among the predictors. Generally, a VIF value above 10 is considered a red flag, suggesting a strong correlation between that variable and others in the model, which can affect the reliability and clarity of the regression coefficients. The VIF values for all the above explanatory variables (FID, COC, TRL, FDI and INF) which range from 1.17 to 2.13 fell well below the conventional threshold of 10, suggesting that no severe correlation exists among them. These results imply that each explanatory variable contributes uniquely to the model’s predictive power without excessive redundancy from other variables. The low VIF values reinforce the model's robustness, ensuring that the estimated regression coefficients are reliable and can be meaningfully interpreted in relation to the dependent variable. The mean VIF of 1.58 further reinforces this conclusion, as it falls within an acceptable range. 4.4 Result of Cross Sectional Dependence . Test Table 7 Cross-section Dependence Test Variables CD-test. p-value. Correlation Absolute Correlation ICG 41.079 0.000 0.82 0.82 FID 19.439 0.000 0.39 0.64 FDI 3.451 0.001 0.07 0.25 INF 18.815 0.000 0.37 0.40 COC 2.435 0.015 0.05 0.38 Source: Author’s Computation, 2025 The cross-sectional dependence test result presented in Table 7 revealed strong evidence of cross-sectional dependence among the variable as CD-test statistic is significantly positive for all variables, with p-values below 0.05. This suggests that the variables exhibit significant interdependence across the panel countries, meaning that economic shocks, policies, or external factors affecting one country likely spill over to other countries in West Africa. 4.5 Unit Root Tests The panel unit root test was employed to assess whether the time series variables in the panel data set comprising multiple entities observed over time are non-stationary. Conducting these tests is crucial to ensure that subsequent statistical analyses produce reliable and meaningful results. In this study, the CIPS and the CADF test were applied to address potential cross-sectional dependence and avoid spurious outcomes. The result of unit root tests is presented in Table 8 and this revealed that most variables namely ICG, TRL, FDI, and COC are non-stationary at their levels but become stationary after first differencing. In contrast, FID, DOC, and INF are stationary at their levels. Table 8 Result of Unit Root Tests Variable CIPS. CADF. Order Level . First Diff .. Level . First Diff .. Stats. Stats. Stats. Stats ICG -2.072 -4.551*** -1.886 -3.104*** I(1) FID -2.566*** -4.933*** -2.191** -4.096*** I(0) FDI -2.416** -5.383*** -1.998 -3.382*** I(1) INF -3.028*** -4.931*** -2.849*** -4.042*** I(0) COC -2.043 -4.534*** -1.857 -3.300*** I(1) Note : ***, & ** denotes significance at 0.01 and 0.05 critical values respectively. Source: Author’s Computation, 2025 4.6 Heteroskedasticity Test Table 9 Heteroskedasticity Test Result Test Null Hypothesis Test Statistic (χ²) Df p-value Breusch-Pagan / Cook-Weisberg Test Constant variance (homoscedasticity) 3.82 1 0.0505 Source: Author’s . computation, 2025 The result of the Heteroskedasticity Test is presented in Table 9 , since the p-value (0.0505) of the Breusch-Pagan / Cook-Weisberg Heteroskedasticity Test is equal to the conventional 5% level of significance, the alternative hypothesis of heteroskedasticity cannot be rejected as there is likelihood of heteroskedasticity in the model. This result therefore informs the decision to employ Panel Corrected Standard Error to cater for the issue of heteroskedasticity. 4.7 Regression Result of the Study The Panel .Corrected Standard .Errors was used to analyse the effect of financial deepening on inclusive growth. Table 10 Financial deepening on Inclusive Growth Panels Corrected Standard Errors Variables Estimates FID 0.6611*** (12.12) COC 0.7497*** (5.71) INF -0.0355 (-1.05) FDI -0.0041 (-0.95) Constant -0.6711*** (5.20) Observations 360 R-squared 0.6944 Countries 15 Wald statistics 293.77*** Note : *** denotes significance at 0.05 critical values; ( ) represent t-statistics respectively Key : ICG: inclusive growth; FID: financial deepening; FDI: foreign direct investment; INF: inflation; COC: control of corruption Source: Author’s computation, 2025 The PCSE result presented in Table 10 revealed that financial deepening (FID) (α = 0.6611, z = 12.12) has a significant positive effect on inclusive growth. This indicates that a one percent increase in financial deepening is associated with a 0.6611% rise in inclusive growth. This implies financial deepening has positive effect on inclusive growth. This suggests that deeper financial markets and improved financial accessibility significantly enhance inclusive growth by increasing access to credit, encouraging investment and fostering economic participation. This outcome supports the McKinnon-Shaw Hypothesis, which suggests that financial deepening promotes inclusive growth by improving credit allocation, boosting investment efficiency, and encouraging broader access to financial services. The result is in line with the findings of Afolabi ( 2022 ) and Ilemona and Ome ( 2021 ), who reported that financial deepening significantly enhances credit availability for small and medium-sized enterprises (SMEs), thereby increasing economic participation among previously marginalized groups and fostering inclusive growth. On the other hand, the results contrast with Migap (2015), who found that financial deepening does not positively influence inclusive growth. The PCSE result indicates that control of corruption (α = 0.7497, z = 5.71) exerts significant positive effect on inclusive growth. In practical terms, a percentage increase in corruption control will bring about 0.7497 percent increase in inclusive growth. This emphasizes the important role of strong institutions and transparent economic management in promoting inclusive growth by ensuring that resources are distributed efficiently and fairly. This findings align with Li et al. (2023) who found that the interaction between financial development and corruption control significantly boosts inclusive growth outcomes in African economies, indicating that stronger governance frameworks help ensure that the benefits of financial deepening are widely shared. The PSCE result shows that foreign direct investment (FDI) has a negative effect on inclusive growth in West Africa, although this effect is statistically insignificant. This corroborate the findings of Nkoro and Uko (2022), who similarly observed that FDI can hinder inclusive growth, especially in contexts where the financial sector is underdeveloped and FDI is primarily directed toward capital-intensive industries that create few jobs and contribute little to broad-based economic progress. On the other hand, these results differ from those of Agyei and Idan ( 2022 ), who reported a positive impact of FDI on inclusive growth, highlighting the role of technology transfer, improved productivity, and expanded employment opportunities in driving this outcome. The findings suggest that while FDI has the potential to drive economic expansion, its impact on inclusive growth in West Africa remains limited, potentially due to inefficiencies in absorptive capacity, weak financial institutions and sectoral concentration of investments. The PCSE estimation results suggest that inflation (INF) exerts an insignificant negative effect on inclusive growth in West Africa. This observation is consistent with the findings of Udo et al. (2019), who also reported an insignificant negative effect of inflation on economic growth which weakens the ability of lower-income groups to benefit from economic expansion as high inflation tends to erode real incomes, increase uncertainty, and discourage long-term investments, particularly in economies where financial markets are underdeveloped. The plausible explanation is that, persistent inflation, even when statistically insignificant poses risks to achieving inclusive growth. The negative effect emphasizes the importance of maintaining macroeconomic stability through prudent monetary policies, inflation-targeting frameworks, and structural reforms aimed at enhancing productivity. Without effective inflation management, the goal of inclusive growth may be undermined by increased economic uncertainty and reduced consumer confidence. The Wald chi-square statistic (293.77) confirms the joint statistical significance of the explanatory variables. 5. Conclusion and Recommendations The finding of this study implies that, expanding access to financial services, particularly for marginalized groups, inclusive growth can be achieved in West Africa as financial deepening fosters credit availability and entrepreneurship. Furthermore, the findings of this study revealed that effective anticorruption measures improve opportunities and resource distribution, which in turn promotes broader socio-economic inclusion in developing regions. Based on the findings of the study, the following policy recommendations were made: Firstly, in line with the positive effect of financial deepening on inclusive growth, it is recommended that financial sector reforms should focus on expanding financial access to small and medium enterprises (SMEs) and rural populations. Also, financial policies that strengthen banking sector efficiency, digital financial inclusion, and credit accessibility should be prioritized to ensure that financial deepening translates into inclusive growth. Second, in line with the positive effect of control of corruption on inclusive growth in West Africa, it is recommended that the government should enact policies that improve corruption control by strengthening transparency, accountability and trust in economic institutions which ensures meaningful distribution of benefits of financial deepening to the populace within the region. This study has contributed to the existing body of knowledge in several important ways. Notably, while previous studies has largely focused on traditional measures such as GDP, per capita income, and poverty levels to assess the effects of trade liberalisation and financial deepening on inclusive growth (Nabi et al., 2022 ; Bacchetta et al., 2021; Aslam et al., 2021; Talah et al., 2020; Zafar et al., 2019 ), this study advanced the methodological frontier by employing the UNCTAD ( 2022 ) multidimensional approach. By incorporating the economic, living condition, and equality dimensions, the study provided a more balanced and comprehensive measure of inclusive growth, particularly within the context of West Africa, where such aggregate metrics have been scarcely applied. While previous cross-country analyses have often employed advanced estimation technique such as Panel ARDL, Panel VAR and Generalized Method of Moments which may not address necessary issues associated with cross-country analysis, specifically the cross-country dependence and heteroskedasticity issues which can lead to biased or inconsistent results. By employing the Panel Corrected Standard Errors (PCSE) technique, this study accounted for these statistical issues, ensuring more robust and policy-relevant findings for West African economies. Given the findings and limitations of this study, future studies can explore disaggregated sectoral analysis to understand how financial deepening affect inclusive growth across specific industries such as agriculture, manufacturing, or services in West Africa. This can offer more nuanced policy prescriptions tailored to sector-specific realities. Declarations Ethics approval and consent to participate Not applicable. Competing interests The authors declare that they have no competing interests. Funding The authors have received no funding. Author Contribution O.O.A wrote section 3-5A.T.O wrote section 1 and 2 Acknowledgement Not applicable Data Availability The data is available upon request. References Acemoglu, D. (2002) Directed technical change. The Review of Economic Studies , 69(4), 781–809. https://ideas.repec.org/a/oup/restud/v69y2002i4p781-809.html Adeleye, B. N., Adedoyin, F., & Nathaniel, S. (2020) The criticality of ICT-trade nexus on economic and inclusive growth. Information Technology for Development.. https://doi.org/10.1080/02681102.2020.1840323 Afolabi, J. A. (2022) Financial deepening, trade openness, and economic growth in Nigeria. Iranian Economic Review 2022, 26 (1), 237–254. DOI: 10.22059/ier.2020.77972 Afolabi, J. O. (2020) Impact of financial deepening on inclusive growth: An empirical study of Nigeria. Asian Journal of Economics and Empirical Research , 7 (1), 8–14. 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International Journal of Economics and Financial Issues , 14 (2), 196202. https://doi.org/10.32479/ijefi.15793 Footnotes West Africa comprises of 15 countries, including Benin, Burkina Faso, Cabo Verde, Ivory Coast, Gambia, Ghana, Guinea, Guinea-Bissau, Liberia, Mali, Niger, Nigeria, Senegal, Sierra Leone, and Togo represents a diverse and dynamic sub-region, ranging from low-income agrarian societies to middle-income oil-exporting nations with potential for growth Benin, Burkina Faso, Cabo Verde, Cote d'Ivoire, Gambia, Ghana, Guinea, Guinea-Bissau, Mali, Mauritania, Niger, Nigeria, Sierra Leone, Senegal and Togo Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8799144","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":587478842,"identity":"35f9deaf-ecb5-46dc-b2c0-6ab28bde6fcc","order_by":0,"name":"Oluwatoba Oyedele Adeniwura","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABFklEQVRIie3PsWqDQBjA8SsWXSyuJ9LLK3zhIEHMw0QEsyh5gQ4pgcvSdvYxMknHyFGzHHQ1W7M4tdBJWmhCz9sK1qZbKfc/8UC+H+chpNP9yabqkRkLtQEyNuhscRJRYyCXOf2ZoK/Ehl7irKLyac/43FldM8+++iBjSzT4/X5CkMUf1h0Ei3oGIeN+JgpJSqD+TZq7tyKmyI7jquuYKhnhMOeAqpB5iQnhepPm+ILxcIHtURcZVPNGkYEiR0ken2v30EOgSkxFoCUpk0R+8fpOGYpa/thxBkNRLIPDHaV+VtPgksXU/OYuZBvV7psIgGyXxS5rCBk70X73wibEsXjZef2uznH7Nk8dbzNefzOt0+l0/75Po4ZsJz8b8FYAAAAASUVORK5CYII=","orcid":"","institution":"Olabisi Onabanjo University","correspondingAuthor":true,"prefix":"","firstName":"Oluwatoba","middleName":"Oyedele","lastName":"Adeniwura","suffix":""},{"id":587478844,"identity":"08394efb-265b-4d97-8cf3-26e0b3f70797","order_by":1,"name":"Abayomi Toyin Onanuga","email":"","orcid":"","institution":"Olabisi Onabanjo University","correspondingAuthor":false,"prefix":"","firstName":"Abayomi","middleName":"Toyin","lastName":"Onanuga","suffix":""}],"badges":[],"createdAt":"2026-02-05 16:08:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8799144/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8799144/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102199548,"identity":"66e93a86-221d-4153-977c-5a2cb2fec12e","added_by":"auto","created_at":"2026-02-09 10:44:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1400633,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8799144/v1/9fc17395-8523-47cd-8d22-31a620c2aafe.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Financial Deepening and Inclusive Growth in West Africa: Evidence from Panel Corrected Standard Errors (PCSE) Analysis","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe emergence of inclusive growth as a topical issue in the literature stems from a confluence of factors ranging from the imperatives of global economic integration to the necessity to address persistent socio-economic disparities globally (Arabiyat et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Inclusive growth goes beyond mere economic expansion to encompass broader objectives of enhancing human welfare, reducing disparities and promoting social cohesion. It emphasizes the importance of ensuring wide distribution of growth benefits across the society, particularly among marginalized groups, women and rural populations (Afolabi, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Olanrewaju et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Ayinde \u0026amp; Yinusa, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Although inclusive growth has gained widespread recognition globally as a strategy to ensure that all economic agents participate in and benefit equitably from economic expansion, its goal have yet to be fully achieved in the context of West Africa. In the region, significant proportions of the population are not included in the growth process and this has led to extreme poverty while the minority enjoys the region's wealth (Fall et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn Africa, inclusive growth has emerged as a critical goal against the backdrop of persistent poverty, inequality and social exclusion (Kong et al., 2020). The region is characterized by a diverse mix of economies, ranging from low-income agrarian societies to middle-income oil-exporting nations. The continent's impressive economic growth rates in recent years have not translated into improvements in living standards (Nketia \u0026amp; Kong, 2021). Despite the region\u0026rsquo;s abundance of natural resources and potentials for economic growth, West Africa\u003ca class=\"FNLink\" href=\"#Fn1\" id=\"#FNLinkFn1\"\u003e\u003c/a\u003e faces challenges of persistent poverty, inequality, and political instability (Cui et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Several factors affect inclusive growth in developing countries. These factors include unequal distribution of benefits and limited access to finance (Olanrewaju et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Ayinde \u0026amp; Yinusa, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Migap et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Financial deepening, which involves enhancing access to financial services such as savings, credit, insurance, and payment systems empower people, especially the economically active and motivate them to invest in economically productive activities. (Ehiedu et al., 2023; Afolabi, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, the benefits of financial deepening are often constrained in West Africa by persistent challenges such as limited access to formal banking services, as a large percentage of the population remains unbanked or inadequately served by financial institutions (Cui et al, 2023). Other than the absence of financial services, poor regulatory frameworks, and fragile financial systems, under-developed economies (particularly the informal sector) are a further impediment to the provision of financial services to marginalized populations (Ntow-Gyamfi et al, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlthough a growing body of empirical studies suggests that financial deepening supports inclusive growth, limited attention has been given to understanding how it specifically influences inclusive growth outcomes for marginalized groups within the region. (Afolabi, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Cui Weng \u0026amp; Song, 2022). Previous studies on the link between financial deepening and inclusive growth have relied on the use of traditional indicator such as Gross Domestic Product (GDP), per capita income and poverty level in measuring economic progress (Nabi et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Bacchetta et al., 2021; Aslam et al., 2021; Talah et al., 2020; Zafar et al., \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), little has been done in using aggregate measures of inclusive growth specifically in West Africa. Meanwhile, using a single measure including the traditional indicators may not capture all the dimensions or component of inclusive growth. To address this measurement gap in the literature, UNCTAD (\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) approach to measuring inclusive growth involving three dimension comprising economy, living condition and equality component of inclusive growth was employed and aggregated using Principal Component Analysis to generate inclusive growth index. This ensured a balanced view on the measure of inclusive growth. This motivated this study to investigate how financial deepening affects inclusive growth in West Africa.\u003c/p\u003e \u003cp\u003eIn this study, the following research question was answered:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eDoes financial deepening affect inclusive growth in West Africa?\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eThe significance of this study lies in its ability to help government and policymakers in West Africa to design well-informed financial strategies that promote economic development and assure that the benefits are fairly distributed to all members of the society.\u003c/p\u003e \u003cp\u003eThis study is structured into five sections. After the introductory section is followed by a review of relevant literature, then the methodology, while section four presents and discusses the empirical findings and the final section provides the conclusion and policy recommendations.\u003c/p\u003e"},{"header":"2. Literature Review","content":"\u003cp\u003eThe literature review section comprises of the conceptual review, theoretical review and empirical review.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Conceptual Review\u003c/h2\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003e2.1.1 Financial Deepening\u003c/h2\u003e \u003cp\u003eFinancial deepening is a multifaceted concept that has been examined and defined by various scholars over the years. Ndebbio (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) conceptualised financial deepening as the progress in the availability of financial assets within the economy. Nzotta and Okereke (2009) present a different perspective, suggesting that financial deepening reflects how effectively financial institutions can channel savings into productive investment activities. Kinyondo (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) further expands the definition, emphasising that financial deepening involves increased financial service delivery across various societal levels. This entails not only increased accessibility to financial services but also efficient resource allocation, broadened opportunities through diversification, risk mitigation within financial systems and the enhancement of payment systems.\u003c/p\u003e \u003cp\u003eOnuoha (2018) provides a comprehensive definition by pointing that financial deepening occurs when financial markets, instruments and entities are synergistically engage to mitigate contract enforcement, transaction, and information costs. This synergy fulfills five fundamental roles comprising: facilitating the exchange of goods and services, aggregating and channeling financial savings, gathering and processing information for efficient allocation, overseeing investments and enforcing corporate governance, and diversifying while mitigating risks (Okafora \u0026amp; Lilian, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In another perspective, financial deepening is characterized as a strategy aimed at stimulating the activities of financial institutions, including the stock market, banking institution and foreign and domestic investments (Zafar et al., \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Okafor et al. (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) elaborated on this, stating that financial deepening involves the expansion and enhancement of financial markets, intermediaries and institutions to mobilise financial resources, thereby fostering enhanced economic performance. Ajudua and Odishika (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) contribute to the discourse by looking at financial deepening as the effective deployment of savings for investments by financial institutions through enhanced financial intermediation, thereby bolstering the competitive efficiency of financial markets.\u003c/p\u003e \u003cp\u003eWithin a deepened financial system, the cost of capital tends to be lower due to diverse financial instruments and efficient intermediation functions, compared to less developed financial sectors. An expanded financial sector mitigates risks faced by firms, fostering portfolio diversification and shielding the economy from fluctuations in international economic conditions (Nwaolisa \u0026amp; Cyril, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Beyond wealth generation and economic growth, financial deepening facilitates increased access to financial services for the impoverished, lowering poverty rates and contributing to reduction in income inequality and entrepreneurial growth (Nwakobi et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Financial deepening, often measured by indicators, such as money supply to GDP ratio, private sector credit, and the dimensions of financial markets, has been associated with numerous positive outcomes for economies. Demirguc-Kunt et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) highlight its role in promoting capital accumulation, facilitating investment in productive sectors and boosting economic growth. Countries with deeper financial systems tend to exhibit lower poverty rates and higher levels of income equality (Demirg\u0026uuml;\u0026ccedil;-Kuntet al., 2001; Beck, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis study follows the definition of financial deepening by Onuoha (2018), that financial deepening occurs when financial markets, instruments and entities are synergistically engage to mitigate contract enforcement, transaction, and information costs. This synergy fulfills five fundamental roles: facilitating the exchange of goods and services, aggregating and channeling financial savings, gathering and processing information for efficient allocation, overseeing investments and enforcing corporate governance, and diversifying while mitigating risks (Okafora \u0026amp; Lilian, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.1.2 Inclusive Growth\u003c/h2\u003e \u003cp\u003eIn development economics, the phrase inclusive growth is often used interchangeably with broad-based growth, shared growth, or pro-poor growth (Ianchovichina \u0026amp; Lundstrom-Gable, 2009). This amalgamation of terminology reflects the complex nature of inclusive growth. Ravallion and Chen (2003) posited that the inclusivity of growth is contingent upon a faster income growth rate experienced by poor households compared to the overall population. This perspective underscores the imperative of addressing income disparities to achieve inclusivity in economic expansion. Similarly, Ali and Son (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) extended the definition by emphasising that inclusive growth enhances average opportunities accessible to the populace, signifying an increase in the social opportunity function. Zhuang (2007) conceptualised inclusive growth as \"growth with equitable opportunities.\"This definition underscores the need to foster sustainable growth while concurrently expanding access to promote social inclusion of diverse populations. The emphasis on equitable opportunities in the definition, acknowledges the importance of not just growth but inclusive growth. Bhalla (2007) added another dimension to the discourse, emphasising the role of productive employment in defining inclusive growth. He asserts that mere job generation is insufficient without a simultaneous focus on augmenting labour productivity. In essence, Bhalla (2007) contended that inclusive growth revolves around fostering growth that encompasses the entire populace, ensuring that employment opportunities lead to meaningful economic participation.\u003c/p\u003e \u003cp\u003eHabito (2009) aligned inclusive growth with economic expansion, as measured by the gross domestic product (GDP), concurrently reducing poverty levels. This perspective is further supported by Rauniyar and Kanbur (2010), affirming the interconnectedness of economic growth and poverty alleviation. Klasen (2010) introduces a crucial distinction, asserting that inclusive growth is a broader concept encompassing all societal segments, from the poor to the affluent. According to the Organisation for Economic Co-operation and Development (2014), inclusive growth represents an economic development process, where everyone has the opportunity to participate and the benefits of economic growth are equitably distributed to all people. This definition encapsulates various facets of living standards, including income, health, and employment, emphasising the multidimensional nature of inclusivity (Arabiyat et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The European Commission (EC) (2020) contributes by linking inclusive growth to a robust labour market, economic, social, and territorial cohesion. Empowerment through heightened employment rates, strategic investment in skills, poverty alleviation efforts, and modernisation of labour markets, training, and social protection systems constitute the core elements of the EC's approach. This multifaceted strategy aims to enable individuals to navigate and adapt to societal changes, fostering the development of a unified society.\u003c/p\u003e \u003cp\u003eThis study adopts the definition of inclusive growth proposed by Ali and Son (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), which views inclusive growth as a process that expands the average opportunities available to the population, signifying an increase in the social opportunity function.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Theoretical Review\u003c/h2\u003e \u003cp\u003eThis study is anchored on the Finance-Growth theory proposed by McKinnon and Shaw in the early 1970s. This theory expounds the importance of the accessibility of financial services in driving economic growth, as a well functioning financial system fosters investment, entrepreneurship, and efficient resource allocation within an economy by providing individuals and businesses with avenues for credit, savings, and insurance,wth (Demirg\u0026uuml;\u0026ccedil;-Kunt et al., 2017). One of the key propositions of the Finance-Growth theory is the concept of a finance-led growth model. By mobilising savings and allocating them to productive investments, financial institutions contribute to the overall expansion of the economy. In this context, policies aimed at improving financial access, deepening capital markets, and strengthening regulatory oversight are critical for promoting inclusive growth (Ntow-Gyamfi et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Yinusa et al., \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The equation that encapsulates the Finance-Growth theory is the finance-led growth model which is expressed as:\u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\(\\:Y=f(K,L,H,A)\\)\u003c/span\u003e \u003c/span\u003e 1\u003c/p\u003e \u003cp\u003eIn this model, \u0026#119884; represents the level of output, \u0026#119870; stands for physical stock, \u0026#119871; denotes the labour force, \u0026#119867; captures human capital, and \u0026#119860; reflects technological progress or total factor productivity. Essentially, output (\u0026#119884;) is determined by the factors of production: Capital (K), Labour (L), human capital (H) and technology (A). Moreover, the Finance-Growth Theory emphasizes how various indicators of financial development are closely linked to the pace and sustainability of economic growth (Acemoglu, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). This relationship can be captured through equations such as:\u003c/p\u003e \u003cp\u003e \u003cem\u003eG\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u003cem\u003eg\u003c/em\u003e(\u003cem\u003eFD\u003c/em\u003e) 2\u003c/p\u003e \u003cp\u003eWhere: \u003cem\u003eG\u003c/em\u003e represents inclusive growth and \u003cem\u003eFD\u003c/em\u003e denotes financial development indicators, such as measures of access to credit, depth of financial markets, or efficiency of financial intermediation; indicating that improvements in financial access, market structure, or regulatory frameworks can lead to higher levels of economic growth.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Empirical Review on Financial Deepening and Inclusive Growth\u003c/h2\u003e \u003cp\u003eThis sub-section focuses on the empirical review involving financial deepening and inclusive growth. Migap et al. (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) studied inclusive growth and financial deepening in Nigeria based on World Bank Development Indicators and the Central Bank of Nigeria Statistical Bulletin for the years 1980\u0026ndash;2015. The study used the Dynamic Ordinary Least Squares (DOLS) cointegration technique and concluded that financial deepening does not positively affect inclusive growth in Nigeria. Odeleye and Olusoji (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) examined financial deepening and economic growth for the years 1981\u0026ndash;2014 in Nigeria using several econometric analysis models. The study focuses on the extent of financial service provision and its relation to the alleviation of poverty, the improvement of welfare, and economic growth. The study state in a well-specified regression framework that Nigeria\u0026rsquo;s economic growth is positively affected by the money supply, the liquidity ratio, and the credit to the private sector.\u003c/p\u003e \u003cp\u003eQui (2017) examines financial deepening and economic growth in countries with a currency board system such as Hong Kong and Singapore/Malaysia and East Africa. The study digitised and systematically analyzed the currency boards\u0026rsquo; financial data and corresponding ratios. The analysis concluded that financial deepening increased in tandem with economic growth during the years of currency board implementation in the selected countries. Using regression and secondary data, Maureen (2018) examines the effect of financial deepening on economic growth in Nigeria. The study notes that the ratio of money supply to GDP positively affects economic growth in Nigeria and emphasizes the importance of financial institutions in sustaining economic growth through the mobilisation of savings. Likewise, in the same context, Appiah et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) studied the effect of financial development and poverty reduction in five African emerging economies from 1995 to 2015. The study applied the Fully Modified Ordinary Least Squares (FMOLS) method and used liquid liabilities and domestic credit as proxies for financial development and concluded that the two proxies achieved some level of poverty reduction, whereas the economic growth and government expenditure proxies were insignificant.\u003c/p\u003e \u003cp\u003eIn a broader context, Sugiyanto and Yolanda (\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) examined the effect of financial deepening on economic growth, inequality and poverty in 73 countries for the period 1991\u0026ndash;2015 using panel regression with interaction dummy variables. The findings indicated that financial deepening also facilitated economic growth, and a reduction in inequality and poverty in emerging markets and developing economies. These impacts differ by level of economic development and are more significant in advanced and emerging economies. For the period of 1984 to 2017, Yinusa et al. (\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) used asymmetric cointegration to analyse the phenomenon of institutional quality, financial development, and inclusive growth in Nigeria. While studying Nigeria, they focused on 34 years of annual time series. The key variables for the study were the natural log of per capita GDP of Nigeria (West and Central Africa, World Bank, Development Indicators) and credit to the private sector (Central Bank of Nigeria, Statistical Bulletin). The study found 34 years of annual time series data to demonstrate a stable and long-term relationship amongst the variables. The study also pointed out the unequal adjustment in the long-term equilibrium among institutional quality, financial deepening, and inclusive growth in Nigeria. Nketia and Kong (2021) reported a positive association between financial deepening and inclusive growth in a panel of 48 African economies over the period 2000\u0026ndash;2019. Using Panel Quantile Regression with Fixed Effects alongside Dumitrescu and Hurlin causality tests, the study found that the combination of financial deepening and control of corruption is vital for the advancement of inclusive growth in middle income countries. Similarly, in the analysis of the growth of finance and inclusive growth in Nigeria, Ilemona and Ome (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) applied time-series data for the period 1986\u0026ndash;2019. The study employed the ARDL approach and the results showed that the money supply, private sector credit, and gross national savings support inclusive growth in Nigeria, while the lending rate hinders it.\u003c/p\u003e \u003cp\u003eUsing the IMF and World Bank databases, Cui et al (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) used a Spatial Durbin Model and analyzed the association among financial inclusion, renewable energy consumption, and inclusive growth for 40 countries for the period of 2010 to 2020. The study examined the direct association among the aforementioned variables and the upgrading of industrial structure as a possible moderator of domestically renewable energy consumption and inclusive growth. The study found a positive and reinforcing relationship among the variables. In the same vein, Sarpong and Nketiah- Amponsah (2022) examined the dimension of financial deepening on inclusive growth in 46 countries of the Sub-Saharan Africa and accessed World Bank panel data on Global Financial Inclusion, Worldwide Governance Indicators, Poverty and Equity, and World Development Indicators for the period 2004\u0026ndash;2018. Using the system GMM estimator of Arellano\u0026ndash;Bover/Blundell\u0026ndash;Bond, the study showed that the depth of financial services positively impacted inclusive growth and that a unit increase in the depth of financial services improved inclusive growth by 0.03. Afolabi (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) examined the relationship between financial deepening and inclusive growth in Nigeria for the years 1981 to 2017 using the Auto-Regressive Distributed Lag (ARDL) model on the data from the Central Bank of Nigeria Statistical Bulletin and the World Bank Development Indicators. Aside from the high illiquidity that adversely affected inclusive growth, the study has shown positive contribution and significant influence of the financial deepening indicators to the inclusive growth in the short run and long run. From 1986 to 2020, Ajudua and Odishika (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) used time series data to analyse the financial deepening and Nigeria\u0026rsquo;s economic growth. While using Nigeria as a case study and confirming stationarity using unit root tests, the study applied the ARDL and ECM methodologies and determined positively that economic growth was contributed to by the money supply, market capitalization and liquid liabilities. They, however, found that credit to the private sector and lending rates had no effect. Obunike-Ezeuli et al. (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) assessed the financial deepening-poverty nexus in Nigeria from 1994 to 2022 using ARDL approach. The study found that financial inter-relation ratio contributes to poverty reduction while national income ratio exacerbates poverty.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Methodology","content":"\u003cp\u003eThis study examined the nexus between financial deepening and inclusive growth using annual panel data on 15 West African countries\u003ca class=\"FNLink\" href=\"#Fn2\" id=\"#FNLinkFn2\"\u003e\u003c/a\u003e Africa (excluding Liberia due to unavailability of data) covering the period of 2000 to 2023 which is a period of twenty four (24) years. Thus with 15 countries in West Africa (after excluding Liberia due to unavailability of data) and time period of 24 years, the total observation of this study is three hundred and sixty (360) which is large enough for standard econometric estimation. The choice of this period is informed by the period in which inclusive growth gained prominence in many countries in Africa. The inclusive growth concept can be traced back to the Millennium Development Goals (MDGs) that were adopted in 2000, where the necessity for growth to be inclusive was emphasized before the widespread usage of the term and its adoption. The MDGs have since evolved into the United Nations Sustainable Development Goals (SDGs) particularly Goal 8, which promotes inclusive and sustainable economic growth, as well as full and productive employment for all. Equally, the choice of the period was informed by data availability as data on most of the components of the three categories of inclusive growth are only available from year 2000.\u003c/p\u003e \u003cp\u003eTo examine the effect of financial deepening on inclusive growth, ICG is proxied using a composite index generated through Principal Component Analysis (PCA). This index reflects a multidimensional understanding of inclusive growth by employing UNCTAD (\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) approach comprising indicators from economic performance (GDP per capita, agricultural productivity), living conditions (employment in agriculture, life expectancy), and equality measures (adult literacy, income inequality). Instead of including the individual financial indicators as separate regressors, a composite index of financial deepening (FID) was generated using Principal Component Analysis (PCA). This methodological approach aligns with the study by Ilemona and Ome (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) on financial deepening and inclusive growth nexus in Nigeria. The FID index aggregates key indicators which are credit to the private sector (DOC), money supply to GDP (MS), gross national savings (SAV), and lending rates (LEND), capturing the depth, accessibility, and efficiency of the financial system.\u003c/p\u003e \u003cp\u003eTo broaden the scope and reflect relevant institutional and macroeconomic influences on inclusive growth, the model introduces control of corruption, inflation and foreign direct investment as intervening variables. According to Sanga and Aziakpono (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) and Bandura (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), control of corruption (COC) is included to account for governance quality, which plays a crucial role in determining equitable access to financial resources. According to Ajudua and Odishika (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and Liu et al. (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), inflation (INF) and foreign direct investment (FDI) are also included as intervening variables, recognizing that macroeconomic stability and foreign capital inflows can significantly influence both financial sector performance and inclusive growth. These adjustments transit the theoretical function of Eq.\u0026nbsp;2 into a streamlined and policy-relevant empirical specification designed to address the effect of financial deepening on inclusive growth. The resulting functional model is expressed as:\u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\(\\:ICG\\:=\\:f\\:(FID,\\:COC,\\:INF,\\:FDI)\\)\u003c/span\u003e \u003c/span\u003e 3\u003c/p\u003e \u003cp\u003eThe transformation of the functional relationship into a Panel Corrected Standard Errors model is presented as follows\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\(\\:{\\:\\:ICG}_{it}={\\alpha\\:}_{0}+{\\alpha\\:}_{1}{FID}_{it}+{\\alpha\\:}_{2}{COC}_{it}+{\\alpha\\:}_{3}{INF}_{it}+{\\alpha\\:}_{4}{FDI}_{it}+{\\epsilon\\:}_{it}\\)\u003c/span\u003e \u003c/span\u003e4\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eIn equation (iv),\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\:\\:ICG}_{it}\\)\u003c/span\u003e\u003c/span\u003e denotes inclusive growth for entity i at time t, the independent variables are FID\u003csub\u003eit\u003c/sub\u003e (financial deepening), COC \u003csub\u003eit\u003c/sub\u003e (Control of corruption), INF\u003csub\u003eit\u003c/sub\u003e (Inflation) and FDI \u003csub\u003eit\u003c/sub\u003e(Foreign direct investment) for country i at time t; The model includes β\u003csub\u003e0\u003c/sub\u003e as the intercept term, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\alpha\\:}_{1}\\)\u003c/span\u003e\u003c/span\u003e, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\alpha\\:}_{2}\\)\u003c/span\u003e\u003c/span\u003e, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\alpha\\:}_{3}\\)\u003c/span\u003e\u003c/span\u003e and\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\alpha\\:}_{4}\\)\u003c/span\u003e\u003c/span\u003e are the coefficients for the respective independent variables. ε\u003csub\u003eit\u003c/sub\u003e as the error term capturing random shocks or unexplained variations in inclusive growth.\u003c/p\u003e \u003cp\u003eThe \u003cem\u003eA priori\u003c/em\u003e expectation of each variables are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eA priori\u003c/em\u003e Expectation\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eExpected sign\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTrade Liberalisation (TRL)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{\\varvec{I}\\varvec{C}\\varvec{G}}{\\varvec{T}\\varvec{R}\\varvec{L}}\u0026gt;0\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003ePositive\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDomestic Credit (DOC)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{\\varvec{I}\\varvec{C}\\varvec{G}}{\\varvec{D}\\varvec{O}\\varvec{C}}\u0026gt;0\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003ePositive\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eForeign Direct Investment (FDI)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{\\varvec{I}\\varvec{C}\\varvec{G}}{\\varvec{F}\\varvec{D}\\varvec{I}}\u0026gt;0\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003ePositive\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInflation (INF)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{\\varvec{I}\\varvec{C}\\varvec{G}}{\\varvec{I}\\varvec{N}\\varvec{F}}\u0026lt;0\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eNegative\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFinancial Deepening (FID)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{\\varvec{I}\\varvec{C}\\varvec{G}}{\\varvec{F}\\varvec{I}\\varvec{D}}\u0026gt;0\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003ePositive\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eControl of corruption\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{\\varvec{I}\\varvec{C}\\varvec{G}}{\\varvec{C}\\varvec{O}\\varvec{C}}\u0026gt;0\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003ePositive\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003cb\u003eSource: Author\u0026rsquo;s Compilation, 2025\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMeasurement of variables\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables Description\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMeasurement\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSource\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInclusive Growth Index (ICG)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAggregates of indicators from three categories which are economy (GDP per capita, Agriculture, forestry, and fishing, value added), living conditions (Employment in agriculture, Life expectancy at birth) and equality (Literacy rate, Gini index)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUNCTAD (2023)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFinancial Deepening Index (FID)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAggregates of MS/GDP ratio, Domestic credit provided by financial sector, Gross savings, Lending interest rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWDI (2023)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInflation (INF)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConsumer price index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWDI (2023)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eForeign investment (FDI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForeign direct investment, net inflows (% of GDP)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWDI (2023)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl of corruption (COC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControl of corruption: Estimate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWGI (2023)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003cb\u003eSource: Author\u0026rsquo;s Compilations, 2025\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe measurements of the variables are provided in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Estimation Procedure\u003c/h2\u003e \u003cp\u003eThis study employed various estimation techniques to analyse the effect of financial deepening on inclusive growth. The pre-estimation test involves normality test, test for multicollinearity and unit root test. For the econometric analysis, Panel Corrected Standard Error (PCSE) was employed. The choice of employing PCSE was to address the issue of heteroskedasticity and cross-sectional dependence associated with cross-sectional studies into the analysis of the relationship. PCSE address this limitation by adjusting the standard errors in panel models, making them particularly suitable for studies with a large number of cross-sectional units (N) and relatively short time periods (T) (Zidi \u0026amp; Hamdi, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Results and Discussion","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Principal Component Analysis\u003c/h2\u003e \u003cp\u003eIn the process of constructing an Inclusive Growth Index (IGI), aggregates of indicators from three categories of inclusive growth which are economy (GDP per capita, Agriculture, forestry, and fishing, value added), living conditions (Employment in agriculture, Life expectancy at birth) and equality (Literacy rate, Gini index) were considered (UNCTAD, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Given the inherent correlation among these indicators, using them individually in a single model could lead to redundancy and loss of information. Therefore, following the methodological approach of Wani (\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), Principal Component Analysis (PCA) was applied to derive a composite index.\u003c/p\u003e \u003cp\u003eThe PCA results presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e indicate that the first principal component captures approximately 58.56% of the total variation, while the second component accounts for 16.27%, and the third explains 9.17%. Considering the high proportion of variance captured by the first principal component and exceeding the commonly accepted Kaiser criterion threshold of eigenvalues greater than 1 for component retention, this study utilizes the eigenvector values of the first principal component as weights to construct the Inclusive Growth Index, denoted as ICG.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrincipal Component Analysis Results for Inclusive Growth Index (Eigen values Summary)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN.umber\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eValue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDifference\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProportion\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCumulative Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCumulative Proportion\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.5135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.5372\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.5856\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.5135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.5856\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.9764\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.4261\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.1627\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.4899\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.7483\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.5503\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0619\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0917\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.0402\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.8400\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.4884\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.2455\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.5286\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.9214\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.2429\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0405\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.7715\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.9619\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.2285\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0381\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.0000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.0000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cb\u003eSource: Author\u0026rsquo;s Computation, 2025\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eGiven the inherent correlation among different proxies of financial deepening (such as MS/GDP ratio, Domestic credit provided by financial sector, Gross savings, Lending interest rate), incorporating them individually into an econometric model could lead to multicollinearity issues and the loss of critical information. To address this, the study employed PCA to construct a composite Financial Deepening Index (FID), following methodologies used in Meierrieks et al. (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrincipal Component Analysis Result for Financial Deepening Index\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEigenvalue.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDifference.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProportion.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCumulative Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCumulative Proportion\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.1809\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.1690\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.5452\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.1809\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.5452\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.0119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.2530\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.1928\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.7982\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.6905\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5738\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.1726\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.8833\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.9708\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.1167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0292\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.0000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.0000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cb\u003eSource: Author\u0026rsquo;s Computation, 2025\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe Principal Component Analysis (PCA) result for the Financial Deepening Index is presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. This revealed that the first two components have eigenvalues greater than 1. However, only the first component was retained for financial deepening index as it accounts for approximately 54.5 percent of the total variance across indicators.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Descriptive Analysis\u003c/h2\u003e \u003cp\u003eThe descriptive analysis result is provided in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. For inclusive growth (ICG), the mean value suggest the level of inclusive growth in the region is low implying that a significant proportion of the populations are excluded in the growth process. However, the relatively high standard deviation (1.877) indicates considerable variability in inclusive growth across the sample. Financial deepening (FID) also suggest a mean of 9.01E-17, implying limited access to financial services of the populace in the region. With a high positive skewness (1.451) and kurtosis (5.842), indicating a distribution with frequent low values and occasional extreme high values. This suggests that financial deepening is uneven across West Africa, with some countries experiencing significant financial sector development while others lag behind.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive Statistics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eICG\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFDI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eINF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCOC\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMean\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.48E-16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.01E-17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.612627\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.325080\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.583918\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedian\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.238878\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.284934\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.464783\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.890768\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.679235\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMaximum\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.050205\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.926800\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.41435\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e47.64287\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.155066\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMinimum\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-3.341374\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-2.627300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-11.19173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-3.502586\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.597468\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStd. Dev.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.877047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.478847\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.130567\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.698572\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.537615\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eJarque-Bera\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79.40889\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e247.6479\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2111.073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e848.8935\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e103.9720\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eProbability\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.000000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.000000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.000000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eObs.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e360\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e360\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e360\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e360\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e360\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cb\u003eNote\u003c/b\u003e: ICG: inclusive growth; FID: financial deepening; FDI: foreign direct investment; INF: inflation; COC: control of corruption\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cb\u003eSource: Author\u0026rsquo;s Computation, 2025\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFDI has a mean of 3.613 with a standard deviation. of 4.130, reflecting moderate variability. The high positive skewness (2.391) and extreme kurtosis (13.856) suggest a distribution with frequent low values and rare extreme high values, indicating sporadic large FDI inflows.\u003c/p\u003e \u003cp\u003eInflation (INF) with mean of 6.325 and standard deviation of 7.698, indicate substantial variability across the region. The high positive skewness (2.190) and kurtosis (9.116) suggest a distribution with frequent low values and occasional extreme high inflation rates, possibly due to external shocks or supply-side constraints.\u003c/p\u003e \u003cp\u003eControl of corruption (COC) has a mean of -0.584, indicating negative perceptions of corruption control in the region. The relatively low standard deviation (0.537) suggests less variability in these perceptions. The positive skewness (1.105) and kurtosis (4.430) indicate a distribution with frequent low values and occasional extreme high values, suggesting persistent governance challenges.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Results of Correlation Matrix of the Study Variables\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMulticollinearity Result\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVIF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1/VIF\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFID\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.4702\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.5401\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFDI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.8176\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eINF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.8516\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean VIF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003cb\u003eSource: Author\u0026rsquo;s computation, 2025\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe result presented in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e provide the multicollinearity test results using Variance Inflation Factor, as it is used to assess both the presence and the degree of multicollinearity by showing how much the variance of a regression coefficient is increased due to correlations among the predictors. Generally, a VIF value above 10 is considered a red flag, suggesting a strong correlation between that variable and others in the model, which can affect the reliability and clarity of the regression coefficients.\u003c/p\u003e \u003cp\u003eThe VIF values for all the above explanatory variables (FID, COC, TRL, FDI and INF) which range from 1.17 to 2.13 fell well below the conventional threshold of 10, suggesting that no severe correlation exists among them. These results imply that each explanatory variable contributes uniquely to the model\u0026rsquo;s predictive power without excessive redundancy from other variables. The low VIF values reinforce the model's robustness, ensuring that the estimated regression coefficients are reliable and can be meaningfully interpreted in relation to the dependent variable. The mean VIF of 1.58 further reinforces this conclusion, as it falls within an acceptable range.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e\u003cb\u003e4.4 Result of Cross Sectional Dependence\u003c/b\u003e. \u003cb\u003eTest\u003c/b\u003e\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCross-section Dependence Test\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCD-test.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep-value.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCorrelation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAbsolute Correlation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e41.079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFID\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19.439\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFDI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.451\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eINF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18.815\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.435\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cb\u003eSource: Author\u0026rsquo;s Computation, 2025\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe cross-sectional dependence test result presented in Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e revealed strong evidence of cross-sectional dependence among the variable as CD-test statistic is significantly positive for all variables, with p-values below 0.05. This suggests that the variables exhibit significant interdependence across the panel countries, meaning that economic shocks, policies, or external factors affecting one country likely spill over to other countries in West Africa.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e4.5 Unit Root Tests\u003c/h2\u003e \u003cp\u003eThe panel unit root test was employed to assess whether the time series variables in the panel data set comprising multiple entities observed over time are non-stationary. Conducting these tests is crucial to ensure that subsequent statistical analyses produce reliable and meaningful results. In this study, the CIPS and the CADF test were applied to address potential cross-sectional dependence and avoid spurious outcomes.\u003c/p\u003e \u003cp\u003eThe result of unit root tests is presented in Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e and this revealed that most variables namely ICG, TRL, FDI, and COC are non-stationary at their levels but become stationary after first differencing. In contrast, FID, DOC, and INF are stationary at their levels.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResult of Unit Root Tests\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCIPS.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eCADF.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOrder\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eLevel\u003c/b\u003e.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eFirst Diff\u003c/b\u003e..\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eLevel\u003c/b\u003e.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eFirst Diff\u003c/b\u003e..\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStats.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStats.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStats.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStats\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eICG\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-2.072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-4.551***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.886\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-3.104***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eI(1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFID\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-2.566***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-4.933***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.191**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-4.096***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eI(0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFDI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-2.416**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-5.383***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.998\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-3.382***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eI(1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eINF\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-3.028***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-4.931***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.849***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-4.042***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eI(0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCOC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-2.043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-4.534***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.857\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-3.300***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eI(1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cb\u003eNote\u003c/b\u003e: ***, \u0026amp; ** denotes significance at 0.01 and 0.05 critical values respectively. \u003cb\u003eSource: Author\u0026rsquo;s Computation, 2025\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.6 Heteroskedasticity Test\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHeteroskedasticity Test Result\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTest\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eNull Hypothesis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTest Statistic (χ\u0026sup2;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDf\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBreusch-Pagan / Cook-Weisberg Test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConstant variance\u003c/p\u003e \u003cp\u003e(homoscedasticity)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e3.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0505\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cb\u003eSource: Author\u0026rsquo;s\u003c/b\u003e. \u003cb\u003ecomputation, 2025\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe result of the Heteroskedasticity Test is presented in Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e, since the p-value (0.0505) of the Breusch-Pagan / Cook-Weisberg Heteroskedasticity Test is equal to the conventional 5% level of significance, the alternative hypothesis of heteroskedasticity cannot be rejected as there is likelihood of heteroskedasticity in the model. This result therefore informs the decision to employ Panel Corrected Standard Error to cater for the issue of heteroskedasticity.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.7 Regression Result of the Study\u003c/h2\u003e \u003cp\u003eThe Panel .Corrected Standard .Errors was used to analyse the effect of financial deepening on inclusive growth.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab10\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 10\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFinancial deepening on Inclusive Growth\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003ePanels Corrected Standard Errors\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEstimates\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFID\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.6611***\u003c/p\u003e \u003cp\u003e(12.12)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCOC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.7497***\u003c/p\u003e \u003cp\u003e(5.71)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eINF\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.0355\u003c/p\u003e \u003cp\u003e(-1.05)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFDI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.0041\u003c/p\u003e \u003cp\u003e(-0.95)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eConstant\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.6711***\u003c/p\u003e \u003cp\u003e(5.20)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eObservations\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e360\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eR-squared\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.6944\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCountries\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWald statistics\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e293.77***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003e\u003cb\u003eNote\u003c/b\u003e: *** denotes significance at 0.05 critical values; ( ) represent t-statistics respectively\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003e\u003cb\u003eKey\u003c/b\u003e: ICG: inclusive growth; FID: financial deepening; FDI: foreign direct investment; INF: inflation; COC: control of corruption\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003e\u003cb\u003eSource: Author\u0026rsquo;s computation, 2025\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe PCSE result presented in Table\u0026nbsp;\u003cspan refid=\"Tab10\" class=\"InternalRef\"\u003e10\u003c/span\u003e revealed that financial deepening (FID) (α\u0026thinsp;=\u0026thinsp;0.6611, z\u0026thinsp;=\u0026thinsp;12.12) has a significant positive effect on inclusive growth. This indicates that a one percent increase in financial deepening is associated with a 0.6611% rise in inclusive growth. This implies financial deepening has positive effect on inclusive growth. This suggests that deeper financial markets and improved financial accessibility significantly enhance inclusive growth by increasing access to credit, encouraging investment and fostering economic participation. This outcome supports the McKinnon-Shaw Hypothesis, which suggests that financial deepening promotes inclusive growth by improving credit allocation, boosting investment efficiency, and encouraging broader access to financial services. The result is in line with the findings of Afolabi (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and Ilemona and Ome (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), who reported that financial deepening significantly enhances credit availability for small and medium-sized enterprises (SMEs), thereby increasing economic participation among previously marginalized groups and fostering inclusive growth. On the other hand, the results contrast with Migap (2015), who found that financial deepening does not positively influence inclusive growth.\u003c/p\u003e \u003cp\u003eThe PCSE result indicates that control of corruption (α\u0026thinsp;=\u0026thinsp;0.7497, z\u0026thinsp;=\u0026thinsp;5.71) exerts significant positive effect on inclusive growth. In practical terms, a percentage increase in corruption control will bring about 0.7497 percent increase in inclusive growth. This emphasizes the important role of strong institutions and transparent economic management in promoting inclusive growth by ensuring that resources are distributed efficiently and fairly. This findings align with Li et al. (2023) who found that the interaction between financial development and corruption control significantly boosts inclusive growth outcomes in African economies, indicating that stronger governance frameworks help ensure that the benefits of financial deepening are widely shared.\u003c/p\u003e \u003cp\u003eThe PSCE result shows that foreign direct investment (FDI) has a negative effect on inclusive growth in West Africa, although this effect is statistically insignificant. This corroborate the findings of Nkoro and Uko (2022), who similarly observed that FDI can hinder inclusive growth, especially in contexts where the financial sector is underdeveloped and FDI is primarily directed toward capital-intensive industries that create few jobs and contribute little to broad-based economic progress. On the other hand, these results differ from those of Agyei and Idan (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), who reported a positive impact of FDI on inclusive growth, highlighting the role of technology transfer, improved productivity, and expanded employment opportunities in driving this outcome. The findings suggest that while FDI has the potential to drive economic expansion, its impact on inclusive growth in West Africa remains limited, potentially due to inefficiencies in absorptive capacity, weak financial institutions and sectoral concentration of investments.\u003c/p\u003e \u003cp\u003eThe PCSE estimation results suggest that inflation (INF) exerts an insignificant negative effect on inclusive growth in West Africa. This observation is consistent with the findings of Udo et al. (2019), who also reported an insignificant negative effect of inflation on economic growth which weakens the ability of lower-income groups to benefit from economic expansion as high inflation tends to erode real incomes, increase uncertainty, and discourage long-term investments, particularly in economies where financial markets are underdeveloped. The plausible explanation is that, persistent inflation, even when statistically insignificant poses risks to achieving inclusive growth. The negative effect emphasizes the importance of maintaining macroeconomic stability through prudent monetary policies, inflation-targeting frameworks, and structural reforms aimed at enhancing productivity. Without effective inflation management, the goal of inclusive growth may be undermined by increased economic uncertainty and reduced consumer confidence.\u003c/p\u003e \u003cp\u003eThe Wald chi-square statistic (293.77) confirms the joint statistical significance of the explanatory variables.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusion and Recommendations","content":"\u003cp\u003eThe finding of this study implies that, expanding access to financial services, particularly for marginalized groups, inclusive growth can be achieved in West Africa as financial deepening fosters credit availability and entrepreneurship. Furthermore, the findings of this study revealed that effective anticorruption measures improve opportunities and resource distribution, which in turn promotes broader socio-economic inclusion in developing regions.\u003c/p\u003e \u003cp\u003eBased on the findings of the study, the following policy recommendations were made: Firstly, in line with the positive effect of financial deepening on inclusive growth, it is recommended that financial sector reforms should focus on expanding financial access to small and medium enterprises (SMEs) and rural populations. Also, financial policies that strengthen banking sector efficiency, digital financial inclusion, and credit accessibility should be prioritized to ensure that financial deepening translates into inclusive growth. Second, in line with the positive effect of control of corruption on inclusive growth in West Africa, it is recommended that the government should enact policies that improve corruption control by strengthening transparency, accountability and trust in economic institutions which ensures meaningful distribution of benefits of financial deepening to the populace within the region.\u003c/p\u003e \u003cp\u003eThis study has contributed to the existing body of knowledge in several important ways. Notably, while previous studies has largely focused on traditional measures such as GDP, per capita income, and poverty levels to assess the effects of trade liberalisation and financial deepening on inclusive growth (Nabi et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Bacchetta et al., 2021; Aslam et al., 2021; Talah et al., 2020; Zafar et al., \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), this study advanced the methodological frontier by employing the UNCTAD (\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) multidimensional approach. By incorporating the economic, living condition, and equality dimensions, the study provided a more balanced and comprehensive measure of inclusive growth, particularly within the context of West Africa, where such aggregate metrics have been scarcely applied. While previous cross-country analyses have often employed advanced estimation technique such as Panel ARDL, Panel VAR and Generalized Method of Moments which may not address necessary issues associated with cross-country analysis, specifically the cross-country dependence and heteroskedasticity issues which can lead to biased or inconsistent results. By employing the Panel Corrected Standard Errors (PCSE) technique, this study accounted for these statistical issues, ensuring more robust and policy-relevant findings for West African economies.\u003c/p\u003e \u003cp\u003eGiven the findings and limitations of this study, future studies can explore disaggregated sectoral analysis to understand how financial deepening affect inclusive growth across specific industries such as agriculture, manufacturing, or services in West Africa. This can offer more nuanced policy prescriptions tailored to sector-specific realities.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCompeting interests\u003c/strong\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThe authors have received no funding.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eO.O.A wrote section 3-5A.T.O wrote section 1 and 2\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e \u003cp\u003eNot applicable\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data is available upon request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAcemoglu, D. 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DOI:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.32327/IJMESS.9.3.2020.10\u003c/span\u003e\u003cspan address=\"10.32327/IJMESS.9.3.2020.10\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZafar, M.W., Shahbaz, M., \u0026amp; Hou, F. (2019) Dynamic linkages between globalisation, financial development and carbon emissions: Evidence from Asia Pacific Economic Cooperation countries. \u003cem\u003eJournal of Cleaner Production\u003c/em\u003e, 228. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jclepro.2019.04.210\u003c/span\u003e\u003cspan address=\"10.1016/j.jclepro.2019.04.210\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZidi, M., \u0026amp; Hamdi, H. (2024) A Panel Corrected Standard Error (PCSE) framework to estimate capital structure and banking performance within the Tunisian context. \u003cem\u003eInternational Journal of Economics and Financial Issues\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e(2), 196202. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.32479/ijefi.15793\u003c/span\u003e\u003cspan address=\"10.32479/ijefi.15793\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Footnotes","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWest Africa comprises of 15 countries, including Benin, Burkina Faso, Cabo Verde, Ivory Coast, Gambia, Ghana, Guinea, Guinea-Bissau, Liberia, Mali, Niger, Nigeria, Senegal, Sierra Leone, and Togo represents a diverse and dynamic sub-region, ranging from low-income agrarian societies to middle-income oil-exporting nations with potential for growth\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBenin, Burkina Faso, Cabo Verde, Cote d'Ivoire, Gambia, Ghana, Guinea, Guinea-Bissau, Mali, Mauritania, Niger, Nigeria, Sierra Leone, Senegal and Togo\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Financial Deepening, Inclusive Growth, Institutional Quality, Panel Corrected Standard Error, West Africa","lastPublishedDoi":"10.21203/rs.3.rs-8799144/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8799144/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study examines the nexus between financial deepening and inclusive growth in West Africa using balanced annual panel data for 15 countries over the period 2000–2023. Inclusive growth is measured using a composite index generated through Principal Component Analysis (PCA), following the UNCTAD (2022) multidimensional framework that incorporates indicators of economic performance, living conditions, and equality. Financial deepening is also captured through a PCA-based index aggregating credit to the private sector, money supply, gross national savings, and lending rates, reflecting the depth, accessibility, and efficiency of the financial system. The study employs Panel Corrected Standard Errors (PCSE) to address heteroskedasticity and cross-sectional dependence inherent in panel data. The results reveal that financial deepening exert significant positive effect on inclusive growth, supporting the McKinnon–Shaw hypothesis that deeper financial systems enhance broad-based economic participation. Control of corruption also exerts significant positive influence on inclusive growth, underscoring the importance of strong and transparent institutions in ensuring equitable distribution of economic gains. Conversely, foreign direct investment and inflation display negative but statistically insignificant effects on inclusive growth. The study contributes to the literature by adopting a multidimensional approach to inclusive growth and offers policy-relevant insights for promoting inclusive growth in West Africa.\u003c/p\u003e\n\u003cp\u003eJEL Codes: G20; O40; D73; C23; O55\u003c/p\u003e","manuscriptTitle":"Financial Deepening and Inclusive Growth in West Africa: Evidence from Panel Corrected Standard Errors (PCSE) Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-09 10:44:09","doi":"10.21203/rs.3.rs-8799144/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"33eb53a2-403e-4a66-a19e-974d99ab1565","owner":[],"postedDate":"February 9th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-06T09:38:37+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-09 10:44:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8799144","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8799144","identity":"rs-8799144","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}