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EconomicsAI Adoption and Labour Displacement in Developing Countries
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About This Research Topic Artificial intelligence adoption is no longer a distant prospect for developing countries; it is reshaping hiring and task allocation in Lagos factories and service firms today. Historically, developing economies have relied on abundant low-cost labour to drive structural transformation from agriculture to labour-intensive manufacturing and services. The rise of robotic process automation, AI-assisted customer service, predictive analytics, and generative AI since 2023 threatens that comparative advantage. At SCHOLARNESTHUB, we provide original, human-written research materials that bridge international theory and Nigerian evidence. This article on AI adoption and labour market displacement is crafted for students searching for economics project topics on AI and labour markets and business administration project topics . It moves beyond anecdotal reports from customer service, logistics, and financial services firms to provide firm-level quantitative evidence from 260 registered manufacturing and service firms in Lagos, with special attention to whether displacement differs between large and small firms. The central argument is that displacement is task-based and firm-size-dependent. Larger firms with diversified task structures and dedicated HR capacity can redeploy workers whose tasks are automated, a form of internal reinstatement, while smaller firms with narrower task structures cannot. This study tests that hypothesis using OLS, logit, interaction, and stratified models, offering policymakers a calibrated basis for skills reorientation and social protection. Main Abstract This study examines the effect of artificial intelligence adoption on labour market displacement among manufacturing and service firms in Lagos, Nigeria. The accelerating global diffusion of AI has raised concern that developing economies, which historically relied on labour-intensive pathways to structural transformation, may face more disruptive displacement than advanced economies experienced during earlier automation waves. Drawing on a cross-sectional survey of 260 registered manufacturing and service firms in Lagos, the study examines the relationship between firm-level AI adoption intensity and reported net employment change over the two years preceding the survey (2024-2026), extending analysis through a formal test of whether displacement differs between large and small firms. An ordinary least squares model is specified with net employment change as dependent variable and AI adoption intensity, firm size, sector, capital intensity, and workforce skill composition as explanatory variables, complemented by a binary logit model of reported job losses, a firm-size interaction specification, and fully stratified sub-sample regressions. Results show AI adoption intensity is negatively and significantly associated with net employment change, with effect concentrated among firms with higher initial share of routine, low-skill task employment. Firm-size interaction reveals displacement effect is significantly smaller among larger firms (≥50 employees), consistent with greater internal redeployment and retraining capacity. This pattern is robust to propensity-score-weighted comparison and alternative size threshold. The study concludes AI adoption is beginning to exert measurable, task-composition and firm-size-dependent displacement on formal sector employment in urban Nigeria and recommends skills reorientation policies, targeted social protection for displaced routine-task workers, and continued monitoring, with particular attention to smaller firms' limited internal redeployment capacity.
EconomicsGig Economy Impact on Informal Sector Employment in Africa
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About This Research Topic Across Sub-Saharan Africa, informal employment accounts for over 80 percent of total non-agricultural employment, and in Nigeria exceeds 90 percent for youth in rural areas, according to International Labour Organization (ILO) estimates. This structural dominance of informality has long been associated with absence of written contracts, social insurance and regulatory protection. Over the past decade, however, the rapid diffusion of app-based ride-hailing and delivery platforms such as Bolt, Uber and Glovo across Lagos has created a new labour market segment that sits ambiguously between formality and informality. Platform work is mediated by a corporate digital application with systematically recorded transactions and, increasingly, optional insurance or savings products, yet workers are classified as independent contractors without statutory protections. This hybridity has triggered global policy debate culminating in the ILO's 2026 Convention on Decent Work in the Platform Economy, the world's first binding treaty for gig workers, as reported by Strait Times coverage of the ILO treaty . Whether this model represents incremental formalisation or a technological repackaging of informal insecurity remains contested. For broader research context, see ScholarNestHub's labour economics collection and related studies on youth employment in Africa. Main Abstract This study examines the impact of the gig economy on informal sector employment in Africa using a cross-sectional survey of 320 ride-hailing and delivery gig workers and conventional informal workers in Lagos, Nigeria. App-based platforms have expanded rapidly across major African cities, creating work that is digitally mediated and transaction-recorded yet performed by workers classified as independent contractors without social insurance or regulatory protections conventionally defining formal employment. The study investigates whether gig platform participation is associated with higher probability of exhibiting formal-sector-like characteristics, and examines earnings and job-security implications relative to conventional informal self-employment, extending analysis to test whether formalisation effects strengthen with gig work tenure and differ between ride-hailing and delivery sub-categories. Using binary logistic regression, the effect of gig platform affiliation, education, prior formal work experience and social insurance access on probability of formal-sector characteristics was estimated, complemented by OLS earnings regression, tenure-interaction specification and platform-type stratified regressions. Results show gig platform participation is positively and significantly associated with probability of exhibiting formal-sector-like characteristics, an effect that strengthens significantly with tenure, and is significantly larger among ride-hailing workers than delivery workers, plausibly reflecting more extensive optional insurance offerings by ride-hailing platforms in Lagos. Gig workers earn a statistically significant income premium relative to comparable conventional informal workers, though partially offset by longer average working hours. The study concludes gig economy is reshaping rather than simply replicating conventional informal employment in urban Nigeria, producing a hybrid, tenure- and platform-type-dependent employment category, and recommends differentiated regulatory framework tailored to platform work. Keywords: gig economy, informal employment, platform work, tenure effects, Africa, Nigeria, formalisation
EconomicseNaira and Monetary Policy Transmission in Nigeria: VAR Analysis
Elijah T
About This Research Topic Central bank digital currencies are moving from theoretical models to live monetary experiments, and Nigeria's eNaira offers the longest operational track record in Africa. Launched in October 2021 by the Central Bank of Nigeria, the eNaira was positioned not only as a financial inclusion tool but as a mechanism to deepen the formal payments system through which monetary policy operates. This article investigates whether that promise is materializing. In economies where cash dominance and shallow intermediation dilute policy signals, the interest rate channel often delivers slow and incomplete pass-through from the policy rate to retail lending rates. Nigeria has exemplified this pattern for two decades. The eNaira introduces a different layer of intervention – the payment infrastructure itself – potentially giving the central bank more direct visibility and influence over transaction flows. This study uses monthly data from April 2021 to June 2026 and a parsimonious Vector Autoregression comprising the Monetary Policy Rate, eNaira transaction volume, interbank call rate, average lending rate, and headline inflation. Impulse responses, forecast error variance decomposition, Granger causality, and Chow break tests around the July 2022 USSD integration provide a comprehensive assessment of whether CBDC adoption is associated with stronger monetary transmission. For readers new to monetary frameworks, our guide to monetary policy instruments explains the conventional channels before CBDC effects are layered in. Main Abstract This article examines whether central bank digital currencies can reshape monetary policy transmission, with evidence from Nigeria's eNaira from October 2021 to June 2026. Using monthly national-level data, we estimate a five-variable Vector Autoregression (VAR) that includes the Monetary Policy Rate (MPR), eNaira transaction volume, interbank call rate, deposit money bank average lending rate, and headline inflation. The framework allows us to evaluate the dynamic interaction between CBDC usage and the interest rate channel. We compute impulse response functions to trace how lending rates and inflation react to policy rate shocks when eNaira volume is included, and we use forecast error variance decomposition to quantify the relative contribution of CBDC usage to fluctuations in lending rates. Granger causality tests assess directional linkages, while a Chow structural break test examines whether pass-through strengthened after the July 2022 integration of USSD access for feature phones, which expanded eNaira reach beyond smartphone users. Findings show that eNaira transaction volume Granger-causes movements in the interbank rate and, more modestly, retail lending rates. The estimated pass-through from MPR to lending rates is stronger in the post-USSD period than in the initial post-launch window. Variance decomposition, robust to alternative Cholesky orderings, indicates that eNaira volume explains a growing yet secondary share of lending rate variability compared to the policy rate itself. The evidence suggests CBDCs possess genuine but design-contingent potential to enhance transmission in developing economies, with accessibility, interoperability, and usability as key mediators.
EconomicsMobile Money and Financial Inclusion in Rural Nigeria
Elijah T
About This Research Topic Walk into any rural market in Oyo State on a Tuesday morning and you will find tomato sellers, tailors, and motorcycle repairers doing something that would have been unthinkable a decade ago: checking account balances, settling debts, and receiving payments from family members in Lagos — all through a basic mobile phone. This is not a technology story. It is a story about access: who gets to participate in the formal economy, who gets left out, and whether mobile money is genuinely bending that curve in Nigeria's countryside. Nigeria has one of the largest unbanked populations on the planet. The EFInA Access to Financial Services survey consistently shows that rural exclusion rates outpace urban ones by a wide margin — a gap driven by sparse bank-branch networks, poor road infrastructure, irregular incomes, and low financial literacy. Successive Central Bank of Nigeria (CBN) strategies have tried to close this gap, with mobile money and agent banking listed as the flagship channels for doing so. This article is built on a primary household survey of 300 rural household heads across six communities in Oyo State. It examines whether mobile money adoption translates into meaningful financial inclusion, which other household characteristics matter, and — crucially — whether the gains are evenly distributed or concentrated among already-advantaged groups. The analysis uses binary logistic regression, sub-group comparisons by gender and age, and a probit robustness check to ensure the findings hold up under scrutiny. For students writing research proposals or dissertations on digital finance and development, the methodology and conceptual framing here directly mirrors the kind of rigour examiners expect. You will find a detailed treatment of the research design in the sections that follow. Main Abstract This study investigates how mobile money adoption affects financial inclusion among rural households in Nigeria, drawing on primary survey data from six communities in Oyo State. Despite years of policy effort, a substantial share of Nigeria's rural population remains outside the formal financial system — held back by geographic isolation, low incomes, and poor financial literacy. Mobile money has been positioned by the CBN's National Financial Inclusion Strategy as the channel best placed to bridge this gap at low cost. Using a cross-sectional survey of 300 rural household heads, the study estimates a binary logistic regression model in which financial inclusion — defined as current ownership and active use of a formal or semi-formal financial product — is the outcome variable. Mobile money adoption, education level, financial literacy, distance to the nearest bank branch, proximity to a mobile money agent, household income, age, and gender are entered as explanatory variables. A probit specification is used as a robustness check, and stratified regressions are run separately for male- and female-headed households and for younger and older age cohorts. The results show that mobile money adoption significantly raises the probability of financial inclusion, even after controlling for income, education, and geography. Financial literacy and proximity to an active agent also emerge as significant positive predictors, while distance to the nearest bank branch is negatively associated with inclusion. Crucially, the adoption effect is meaningfully larger for female-headed households and for younger household heads, indicating that mobile money may be doing its most important work precisely where the historical exclusion has been deepest. The study recommends accelerated agent-network expansion in underserved communities, targeted financial literacy programmes, and interoperability reforms to consolidate and extend these gains. Keywords: mobile money, financial inclusion, rural Nigeria, logistic regression, gender gap, agent banking, financial literacy
EconomicsCryptocurrency Regulation and Capital Flight in Developing Economies: Evidence from Nigeria
Admin
About This Research Topic Nigeria occupies an unusual position in the global cryptocurrency story. It is consistently named among the world's most active peer-to-peer crypto markets, yet its regulators have swung between silence, caution, outright restriction, and, most recently, structured licensing, all within little more than a decade. That back-and-forth is not just a policy curiosity; it goes to the heart of a question that matters enormously for developing economies: does regulating cryptocurrency actually reduce capital flight , or does it push money further underground? This article walks through the reasoning, the background, and the research design behind a study that set out to answer that question empirically, using Nigeria's own regulatory history as a natural test case. The short version is this: the character of regulation seems to matter more than its mere existence. A blunt, poorly explained restriction can drive transactions into channels that are even harder to see, while a clearer, rules-based licensing framework appears to be associated with less unrecorded outflow. The sections below unpack the background, the problem the study addresses, its objectives and guiding questions, why it matters, and what it does and does not attempt to cover, closing with a set of frequently asked questions for readers who want the quick version. Main Abstract This study investigates whether cryptocurrency regulation shapes the scale of capital flight in Nigeria, examined here as a representative developing economy, across the period from the first quarter of 2012 to the fourth quarter of 2023. A composite Crypto Regulation Index was built from the documented sequence of directives and circulars issued by Nigeria's monetary and securities authorities, tracking how regulatory stance moved from early caution, through an outright banking restriction on crypto-linked accounts, to a licensing-based framework for virtual asset service providers. Capital flight itself was estimated using the widely used World Bank residual method, and the analysis controlled for exchange rate volatility, the interest rate differential, inflation, trade openness, and institutional quality. Working with quarterly time-series data, the study applied the Autoregressive Distributed Lag (ARDL) bounds-testing approach to cointegration, a technique well suited to variables that are not all integrated in the same order, which unit root testing confirmed was the case here. The bounds test pointed to a genuine long-run relationship among the variables. In that long run, the Crypto Regulation Index carried a negative and statistically significant relationship with capital flight: as regulatory clarity and coherence increased, capital flight tended to fall, holding other factors constant. The interest rate differential and trade openness also mattered significantly in the long run, while exchange rate volatility, inflation, and institutional quality did not reach statistical significance once the other variables were accounted for. A correctly signed and significant error correction term indicated that roughly a third of any short-run deviation from this long-run relationship is corrected within a single quarter, and the estimated model passed the standard battery of diagnostic checks for heteroskedasticity, serial correlation, and non-normality. Taken together, the findings suggest that coherent, well-communicated cryptocurrency regulation, rather than blanket prohibition, is associated with reduced capital flight, plausibly because it narrows the incentive to route funds through unregulated peer-to-peer or offshore channels. The study recommends that Nigerian regulators lean toward clarity and phased licensing for virtual asset service providers rather than outright bans, and it flags disaggregated, transaction-level crypto data as an important resource for future research once such data becomes available.
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