This study investigates the trajectory of financial inclusion towards economic inclusion in Ghana. The aim is to track the dynamisms and the conduits through which financial inclusion translates into an inclusive-economic system in a way that becomes pro-poor and growth engendering. Specifically, the study i) examines the role that regulatory and institutional factors play in the attainment of broader inclusion in lower-income countries (LICs), with Ghana as reference case; ii) examines the means by which technological deepening contributes to drive towards an inclusive financial system in Ghana; iii) identifies firm attributes that are most significantly predisposed to the risk of exclusion from the use of formal financial services; iv) ascertains the most efficient means through which financial inclusion can impact on economic growth in Ghana; and v) scientifically assesses the means through which financial inclusion translates into economic inclusion at the household level. The raison d'être of financial intermediaries (FIs), is fundamental to our understanding of why financial exclusion exists and appears endemic in LICs. Past studies have failed to link the two. The complete understanding of why financial exclusion exists and appears dominant in LICs is embedded in the understanding of why financial intermediaries exist and operate. It becomes difficult to explain why exclusion exists if FIs are merely perceived as delegated monitors, risk managers and a coalition of information sharers. Profit-maximisation, which implies cost minimisation, suggests that intermediaries will refrain from serving those economic agents perceived to be associated with significant information asymmetry and transaction costs that characterise imperfect financial markets. This thesis, therefore, contributes to illuminating an understanding of why financial exclusion appears prevalent in LICs and demonstrates a means through which economic inclusion can emerge out of an inclusive financial system. Failure to establish these linkages tends to lead to financial policies that either lack theoretic groundings or miss the intended outcomes. Using multi-sourced datasets from reliable domains such as the World Bank (World Development Indicators, Gallup Poll Global Findex and Enterprise Surveys), World Governance Index, Transparency International, Heritage Foundation/Wall Street and the ICPSR (via Princeton University database) allows the underlying relationships to be investigated. The empirical investigations are based on the four key pillars/dimensions of financial inclusion (impact, quality, usage and access-IQUA). Econometric models are estimated using multiple regression analysis. Maximum likelihood estimation (MLE) process, Instrumental Variable Estimation (IVE) and Linear but semi-parametric models are employed in empirical estimations that lead to robust outcomes. The use of logistic regression, which is a family of binary models based on MLE process, underscores the concept of financial inclusion/exclusion itself being dichotomous in nature. That is, either an agent is included financially or otherwise. Again, the adoption of the generalised method of moment (GMM) model which is part of the IV estimation process recognises the problem of endogeneity and simultaneity that often characterise household-level data on financial accessibility and its impact. The findings indicate that financial inclusion does not occur in a vacuum, and the impact of institutional and infrastructural factors on a broader inclusion is critical. The study identifies key institutional factors, such as national-level governance, corruption perceptions, economic freedom, and economic and technological deepening, as playing crucial roles. The findings further suggest that rule of law (which ensures contract enforceability), political stability, regulatory quality, voice and accountability, all significantly influence financial inclusion positively. The study finds a positive impact of technology on financial inclusion. Specifically, the use of modern technological amenities, such as mobile phone and internet, can offer digitalised-based, branchless financial services which help reduce both information asymmetry and transaction costs for providing financial services. The findings further suggest that nonbank-based digitalised-financial services (DFS) provision appears non-discriminatory, compared with bank-based DFS. Again, the inclusion driven by bank-based DFS reduces over time, while nonbank-based DFS rises. This substitutability trend observed in this study defines the contemporaneous trade-off of bank-based DFS and nonbank-based DFS over time. Identification of the firm-level characteristics that either contribute to, or reduce their predisposition to risk of being excluded from the use of financial services is one of the key objectives that motivated this study. Using a logistic regression model as a link function and with a rich dataset from the World Bank Enterprise Survey on Ghana, the results suggest that firm age, size, sector of operation and ownership of website are key determinants of financial inclusion. The likelihood of exclusion among firms reduces with website ownership that helps reduce information and transaction costs associated with lending to information-opaque sectors such as SMEs. Similarly, the findings suggest that the retailing, matured and high-sales firms have a better chance of accessing lines of credit from financial intermediaries. Consistent with prior studies, risk of financial exclusion is found to be higher among SMEs than larger firms. Again, sole-proprietorship and partnership firms are found to have high-risk dispositions when it comes to credit constraints, compared with publicly listed companies. The study further reveals that certain key structural changes at national level that occurred specifically within the follow-up data collection period, account for the observed differences in the results of the two datasets used. The political change from the private sector-led administration (baseline) to the social democratic regime (follow-up), the discovery of oil in commercial quantities and the eight-month post-election hearing by the country’s Supreme Court were identified as having played a part in exerting latent impacts on financial exclusion/inclusion, especially among SMEs. Using a quantile regression model, the study contributes significantly to our understanding on the role financial development, inclusion and structure play in economic growth of developing economies. The results suggest that the banks’ growth-facilitating role is much stronger than that of the financial markets. Depth of financial inclusion (proxied by the amount of credit to the private sector), is found to be positively related to economic growth. This suggests that, for LICs, the growth-enhancing effect of finance thrives on the strength of financial institutions as it engenders wider inclusion. The results further suggest that the impact of a financial inclusion programme at household level depends largely on the quality of the process leading to its implementation. It reveals that donor- funded programmes implemented via donor-agencies have more positive poverty-reducing impacts on the beneficiaries than those implemented by government agencies. These findings have policy ramifications for LICs aiming for a broader and more inclusive financial system. That technological infrastructure and amenities significantly influence financial inclusion, suggests that developing countries aiming to achieve a financially inclusive society must pay attention to these institutional contexts with more emphasis on technological infrastructure. At the firm level, policy attention of donors, sector players and regulators needs to focus on the firm’s attributes that are predisposed to their exclusion from the formal financial sector, while strengthening policies for those that are inclusive-inducing. Policy and capacity building on enterprise growth and sustainability will be strategic in targeting the inclusion-inhibiting factors. Firm-level constraints that confront small, individually owned businesses when addressed will both ensure their inclusion in the formal financial system and, most importantly, their growth and sustainability. Tracking potential externalities that originate from structural changes and how that affects other sectors at the micro-level, must not elude policy attention. This way, mitigation measures will be fashioned to address any negative confounders while any unintended gains are consolidated. For donor agencies, a clear signal is given: channel pro-growth and poverty-reducing financial inclusion funds through financial intermediaries where wider inclusion can be guaranteed. The synergistic role of the implementation quality of a financial inclusion programme/policy is very important to ensure the desired impact at the household level. This is particularly important to the understanding of how access and utilisation, which define broader financial inclusion, would be incentivised. Policymakers, donors and researchers pursuing the agenda of financial inclusion need to pay attention to the wider institutional and environmental context within which broader inclusion is expected, as they do interact pari-pasu in creating a harmonized developmental trajectory. Poverty-reducing impacts of financial inclusion will then be guaranteed as financial inclusion translates into broader economic inclusion. This way, the trajectory of financial inclusion leading to economic inclusion is trackable to serves as a basis for inclusion policy formulation in LICs.