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on Payment Systems and Financial Technology |
| By: | Hanin Khawaja (Department of Economics, New School For Social Research, USA) |
| Abstract: | The international monetary system (IMS) has long been interpreted through the lens of singularity, where global stability hinges on a single dominant currency fulfilling all core monetary functions—store of value, medium of exchange, and unit of account. This paper challenges that paradigm by introducing the concept of functional fragmentation. The IMS is evolving toward different currencies increasingly specializing in specific roles, without any single issuer monopolizing the system. The transformation draws on wholesale central bank digital currencies (wCBDCs) and distributed ledger technologies (DLTs), but also reflects deliberate institutional choices shaped by geopolitical tensions and the erosion of trust in dollar-centric infrastructure. The U.S. dollar is likely to maintain its primacy in global reserves, but new platforms are enabling regional currencies to gain ground in payments and settlement. First, emerging markets are building wCBDC-based networks designed to bypass traditional correspondent banking. Second, the European Union is advancing interoperability and financial infrastructure resilience to safeguard the euro’s regional role. Third, the USA and the UK, slower to adopt CBDCs, are leveraging regulatory frameworks around stablecoins to reinforce dollar dominance through fintech intermediaries. The implications for global liquidity, reserve strategies, and financial stability are profound, requiring renewed attention to institutional coordination and systemic design in a modular, post-hegemonic IMS. |
| Keywords: | International Political Economy, international monetary system (IMS), singularity, world money, central bank digital currency (CBDC), functional fragmentation |
| JEL: | E42 F02 F53 |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:new:wpaper:2514 |
| By: | Denis Nikitin; Johan Schmalholz; Carolina Bloch |
| Abstract: | This paper explores how retail central bank digital currencies (CBDCs) could enhance the delivery of social safety nets (SSNs). It assesses CBDC design features and their implications for payment administration and delivery. Findings suggest that using CBDCs solely as payment delivery solutions offers limited advantages over existing systems such as faster payment systems. However, leveraging CBDCs as payment administration platforms—with peer-to-peer transfers, decentralized ledger access, and advanced programmability—could transform SSN delivery by enabling agencies to automate transfers, operate independently from private financial intermediaries, and monitor transactions directly. These benefits come with significant challenges, including privacy concerns, compliance risks, and infrastructure requirements. The paper emphasizes that realizing CBDCs’ full potential for SSNs will depend on thoughtful integration with existing systems and a clear understanding of their comparative advantages. Aimed at social protection policymakers and finance specialists, it highlights the need for collaboration between CBDC developers and SSN administrators to ensure that digital currencies effectively support inclusive and efficient benefit delivery. |
| Keywords: | Central Bank Digital Currencies; Social Safety Nets; Payment Systems; Government Transfers; Fintech; Financial Inclusion |
| Date: | 2025–10–24 |
| URL: | https://d.repec.org/n?u=RePEc:imf:imfwpa:2025/211 |
| By: | Dirk Niepelt |
| Abstract: | We review the macroeconomic literature on retail central bank digital currency (CBDC), organizing the discussion around a CBDC-irrelevance result. We identify both fundamental and policy-related sources of relevance, or departures from neutrality. Bank disintermediation - the crowding out of deposits - does not, by itself, constitute such a source. We argue that the literature has primarily focused on policy-related sources of non-neutrality, often without making this focus explicit. From a macroeconomic perspective, CBDC is, at its core, a matter of monetary architecture, and political economy considerations are central to understanding CBDC policy design. |
| Keywords: | Monetary architecture, central bank digital currency, public money, private money, neutrality, lender of last resort. |
| JEL: | E42 E51 G21 G28 |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:ube:dpvwib:dp2509 |
| By: | Emilio Barucci; Andrea Gurgone; Giulia Iori; Michele Azzone |
| Abstract: | We analyse financial stability and welfare impacts associated with the introduction of a Central Bank Digital Currency (CBDC) in a macroeconomic agent-based model. The model considers firms, banks, and households interacting on labour, goods, credit, and interbank markets. Households move their liquidity from deposits to CBDC based on the perceived riskiness of their banks. We find that the introduction of CBDC exacerbates bank-runs and may lead to financial instability phenomena. The effect can be changed by introducing a limit on CBDC holdings. The adoption of CBDC has little effect on macroeconomic variables but the interest rate on loans to firms goes up and credit goes down in a limited way. CBDC leads to a redistribution of wealth from firms and banks to households with a higher bank default rate. CBDC may have negative welfare effects, but a bound on holding enables a welfare improvement. |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2510.21071 |
| By: | Cheikh T. Ndour (Dakar, Senegal); Simplice A. Asongu (Johannesburg, South Africa) |
| Abstract: | Purpose – This study examines the relevance of information and communication technologies in the effect of gender economic inclusion on environmental sustainability. Design/methodology/approach – The focus is on a panel of 42 sub-Saharan African countries over the period 2005-2020. The empirical evidence is based on generalized method of moments. The environmental sustainability indicator used is CO2 emissions per capita. Two indicators of women's economic inclusion are considered: women's labour force participation and women's unemployment. The chosen ICT indicators are mobile phone penetration, internet penetration and fixed broadband subscriptions. Findings – The results show that: (i) fixed broadband subscriptions represent the most relevant ICT moderator of gender economic inclusion for an effect on CO2 emissions; (ii) negative net effects are apparent for the most part with fixed broadband subscriptions (iii) both positive ICT thresholds (i.e., critical levels for complementary policies) and negative ICT thresholds (i.e., minimum ICT levels for negative net effects) are provided; (iv) ICT synergy effects are apparent for female unemployment, but not for female employment. In general, the joint effect of ICTs or their synergies and economic inclusion should be a concern for policymakers in order to better ensure sustainable development. Moreover, the relevant ICT policy thresholds and mobile phone threshold for complementary policy are essential in promoting a green economy. Originality/value –The study complements the extant literature by assessing linkages between information technology, gender economic inclusion and environmental sustainability. |
| Keywords: | ICT, Gender inclusion; Environment sustainability; Sub-Saharan Africa |
| JEL: | C52 O38 O40 O55 P37 |
| Date: | 2024–01 |
| URL: | https://d.repec.org/n?u=RePEc:dbm:wpaper:24/003 |
| By: | Chun Chet Ng; Wei Zeng Low; Yin Yin Boon |
| Abstract: | Despite accounting for 96.1% of all businesses in Malaysia, access to financing remains one of the most persistent challenges faced by Micro, Small, and Medium Enterprises (MSMEs). Newly established or young businesses are often excluded from formal credit markets as traditional underwriting approaches rely heavily on credit bureau data. This study investigates the potential of bank statement data as an alternative data source for credit assessment to promote financial inclusion in emerging markets. Firstly, we propose a cash flow-based underwriting pipeline where we utilise bank statement data for end to end data extraction and machine learning credit scoring. Secondly, we introduce a novel dataset of 611 loan applicants from a Malaysian lending institution. Thirdly, we develop and evaluate credit scoring models based on application information and bank transaction-derived features. Empirical results show that the use of such data boosts the performance of all models on our dataset, which can improve credit scoring for new-to-lending MSMEs. Lastly, we intend to release the anonymised bank transaction dataset to facilitate further research on MSMEs financial inclusion within Malaysia's emerging economy. |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2510.16066 |
| By: | Emmanuel Boadi |
| Abstract: | This study proposes a hybrid deep learning model for forecasting the price of Bitcoin, as the digital currency is known to exhibit frequent fluctuations. The models used are the Variational Mode Decomposition (VMD) and the Long Short-Term Memory (LSTM) network. First, VMD is used to decompose the original Bitcoin price series into Intrinsic Mode Functions (IMFs). Each IMF is then modeled using an LSTM network to capture temporal patterns more effectively. The individual forecasts from the IMFs are aggregated to produce the final prediction of the original Bitcoin Price Series. To determine the prediction power of the proposed hybrid model, a comparative analysis was conducted against the standard LSTM. The results confirmed that the hybrid VMD+LSTM model outperforms the standard LSTM across all the evaluation metrics, including RMSE, MAE and R2 and also provides a reliable 30-day forecast. |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2510.15900 |
| By: | Simplice A. Asongu (Johannesburg, South Africa); Joseph Nnanna (Abuja, Nigeria) |
| Abstract: | This research investigates how enhancing remittances affects total factor productivity (TFP) dynamics in Sub-Saharan Africa. The Generalised Method of Moments (GMM) empirical strategy is adopted for the purpose of the study and the engaged TFP dynamics are: TFP, real TFP, welfare TFP and real welfare TFP. Significant net effects are not apparent from enhancing remittances for TFP, real TFP growth and welfare TFP while positive net effects are apparent on real welfare TFP. The unexpected findings are elucidated and policy implications are discussed. This study has complemented the attendant literature by assessing how growing remittances influence dynamics of TFP in Sub-Saharan Africa. |
| Keywords: | Economic Output; Remitances; Sub-Saharan Africa |
| JEL: | E23 F24 F30 O16 O55 |
| Date: | 2024–01 |
| URL: | https://d.repec.org/n?u=RePEc:dbm:wpaper:24/005 |
| By: | Sylvain B. Ngassam (Dschang, Cameroon); Simplice A. Asongu (Johannesburg, South Africa); Gildas T. Ngueuleweu (Dschang, Cameroon) |
| Abstract: | This research empirically analyzes the effect of social media on fragility. It goes beyond political grounds which oppose techno-optimistic to techno-pessimistic perceptions of the impact of social media to analyze its consequences on global, Security fragility, economic and social fragilities. The research uses annual data from a panel of 47 African countries for the period 2000–2018. Results reveal that the use of social media by the public to organize offline political actions has no outcome on global fragility. However, its use by elites for the same end accentuates global state fragility. This operates through Security and political fragilities. Fragility is negatively associated with higher civil society participation, education and democracy. The use of social media to organize offline political actions either by people or by elites in the context of higher civil society participation reduces fragility, while its use either by people or by elites in the context of higher educational level accentuates state fragility. The use of social media to organize offline political actions by people in the context of democracy boosts fragility but its use by elites in the same framework reduces fragility. There is a need to sensitize people, especially elites in Africa on the threats and opportunities of social media. There is also a necessity to develop a dynamic, well-educated and well-organized civil society and population in order to better valorize the opportunities that social media represents. |
| Keywords: | Social media, state fragility, security fragility, political fragility, economic fragility and social fragility. |
| JEL: | G20 O38 O40 O55 P37 |
| Date: | 2024–01 |
| URL: | https://d.repec.org/n?u=RePEc:dbm:wpaper:24/009 |
| By: | Stäcker, Daniel; Saha, Ria |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:dar:wpaper:157774 |
| By: | L. Randall Wray |
| Abstract: | This working paper integrates the credit money approach (associated with Post Keynesian endogenous money theory) with the state money approach (associated with Modern Money Theory) by drawing on Wray's 1990 book (Money and Credit in Capitalist Economies: The Endogenous Money Approach, Edward Elgar), his 1998 book (Understanding Modern Money: the Key to Full Employment and Price Stability, Edward Elgar), and his 2004 edited book (Credit and State Theories of Money: The Contributions of A. Mitchell Innes, Edward Elgar). New sources and interpretation of the history of money make it clear that there is no contradiction between state money and private credit money--each played a role in the creation of the modern monetary system. Indeed, today's system was created by bringing state money into the private money giro, thereby strengthening both. |
| Keywords: | credit money; state money; Modern Money Theory (MMT); Bank of England; fiat money; giro money; history of money; central bank; nominalism; origins of money |
| JEL: | B25 B52 E42 E58 E62 N11 N20 |
| Date: | 2025–02 |
| URL: | https://d.repec.org/n?u=RePEc:lev:wrkpap:wp_1076 |
| By: | Abdelaziz, Fatma; Abay, Kibrom A. |
| Abstract: | Despite growing enthusiasm about the potential of digital innovations to transform agrifood systems, adoption among smallholder farmers in Africa remains low and heterogeneous. While the proliferation of digital tools targeting smallholder farmers is encouraging, the vast majority remain at pilot stages, facing important demand and supply-side barriers to adoption. This paper evaluates alternative digital literacy interventions designed to address these demand-side barriers. Following a Training of Trainers (TOT) model, we designed and implemented a randomized control trial to test three variants of digital literacy training: standard classroom-based digital literacy training (T1), digital training complemented (preceded) by a video-based play (T2), digital training complemented (preceded) by a live community play (T3), and a control group (C). We find that all variants of digital training significantly increased the uptake and utilization of digital tools by smallholder farmers. Specifically, the standard digital training alone increased uptake by 20 percentage points and utilization by 26 percentage points. The interventions also significantly enhanced farmer trust in digital tools by 8–13 percentage points. Surprisingly, for some outcomes, the digital literacy training alone outperformed the combined approaches that incorporated edutainment nudges. We explore possible explanations, including group size effects and social influence dynamics during the plays. We also document heterogeneity in the impact of these interventions across farmers’ gender and age. Our findings offer insights for designing cost effective and scalable interventions to build digital capabilities and trust among smallholder farmers. |
| Keywords: | digital literacy; training; digital agriculture; smallholders; technology adoption; Egypt; Africa; Northern Africa |
| Date: | 2025–09–16 |
| URL: | https://d.repec.org/n?u=RePEc:fpr:ifprid:176520 |
| By: | Axel Gautier; Jean-Christophe Poudou |
| Abstract: | In many industries, platforms compete with incumbents that are open to all consumers, whereas platforms require user affiliation. Consequently, platforms face two layers of competition: for the market, to attract users, and in the market, to compete with incumbents. We develop a dynamic model integrating these layers, showing that as platform affiliation grows, in the market competition intensifies, pushing incumbents toward more aggressive pricing. Conversely, for the market competition diminishes, reducing the platform's incentive to compete aggressively. This interplay generates dynamic pricing behavior that can be non-monotonic over time, capturing the shifting incentives driving platform-incumbent competition across both dimensions. |
| Keywords: | platform competition, Uber economy, competition for the market, market affiliation |
| JEL: | L11 L13 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12218 |
| By: | Chi-Sheng Chen; Aidan Hung-Wen Tsai |
| Abstract: | This study presents a comprehensive empirical comparison between quantum machine learning (QML) and classical machine learning (CML) approaches in Automated Market Makers (AMM) and Decentralized Finance (DeFi) trading strategies through extensive backtesting on 10 models across multiple cryptocurrency assets. Our analysis encompasses classical ML models (Random Forest, Gradient Boosting, Logistic Regression), pure quantum models (VQE Classifier, QNN, QSVM), hybrid quantum-classical models (QASA Hybrid, QASA Sequence, QuantumRWKV), and transformer models. The results demonstrate that hybrid quantum models achieve superior overall performance with 11.2\% average return and 1.42 average Sharpe ratio, while classical ML models show 9.8\% average return and 1.47 average Sharpe ratio. The QASA Sequence hybrid model achieves the highest individual return of 13.99\% with the best Sharpe ratio of 1.76, demonstrating the potential of quantum-classical hybrid approaches in AMM and DeFi trading strategies. |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2510.15903 |
| By: | Simplice A. Asongu (Oxford, UK); Sara Le Roux (Oxford, UK) |
| Abstract: | The study investigates the role of governance (i.e., ‘voice & accountability’, political stability/no violence, regulatory quality, government effectiveness, corruption-control and the rule of law) in the incidence of short-term debt services on infrastructure development in the perspective of telecommunication infrastructure and access to electricity. The focus of the study is on 52 African countries for the period 2002-2021. The generalized method of moments is employed as estimation strategy and the following findings are established. Debt service has a negative unconditional effect on access to electricity and telecommunication infrastructure. Governance dynamics moderate the negative effect of debt service on infrastructure dynamics. Effective moderation is from regulatory quality and corruption-control for access to electricity and from government effectiveness, regulatory quality, corruption-control and rule of law, for telecommunication infrastructure. Policy implications are discussed. |
| Keywords: | Debt service, governance; information technology; access to electricity; Africa |
| JEL: | F34 H63 O10 O40 O55 |
| Date: | 2024–01 |
| URL: | https://d.repec.org/n?u=RePEc:dbm:wpaper:24/027 |
| By: | FUJIKI, Hiroshi |
| Abstract: | This paper examines the future evolution of cash demand in Japan, amid rapid demographic aging and the increasing adoption of cashless payments. Despite a decline in cash use for daily transactions, aggregate cash demand has remained stable, likely due to cash hoarding by older generations. Using survey data from 2021 that separates cash held for daily use and hoarding purposes by age group, we project cash demand through 2070. Our baseline scenario assumes constant cash-holding behavior by cohort, while an alternative scenario incorporates reductions reflecting the spread of cashless payments. Adjustments for the underrepresentation of high-cash-holding households are made using methodologies from the distributional national wealth literature, which employs Pareto distributions to align microdata with aggregate statistics. Results suggest that cash on hand (COH) will decline by 1.5%–2.4% annually, and cash at home (CAH) by about 1% annually. The rate of decrease in cash demand is faster than the population decrease of 0.7%, as we assume that future older individuals will hoard less cash than current older individuals, and future younger individuals will use less cash for day-to-day payment due to the spread of cashless payments. We find that a 1% rise in deposit rates would cause a 20% decrease in CAH demand, a much stronger effect than demographic aging. Finally, we discuss the implications for the Bank of Japan’s balance sheet, as declining cash demand could increase the Bank’s cost burden during monetary tightening. |
| Keywords: | cash demand, population aging, demographic changes, cashless payment methods, cash hoarding |
| Date: | 2025–08–26 |
| URL: | https://d.repec.org/n?u=RePEc:hit:hiasdp:hias-e-145 |
| By: | Michael S. Barr |
| Date: | 2025–10–22 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fedgsq:101989 |
| By: | Clara Punzi |
| Abstract: | The rapid growth of the digital platform economy is transforming labor markets, offering new employment opportunities with promises of flexibility and accessibility. However, these benefits often come at the expense of increased economic exploitation, occupational segregation, and deteriorating working conditions. Research highlights that algorithmic management disproportionately impacts marginalized groups, reinforcing gendered and racial inequalities while deepening power imbalances within capitalist systems. This study seeks to elucidate the complex nature of digital platform work by drawing on feminist theories that have historically scrutinized and contested the structures of power within society, especially in the workplace. It presents a framework focused on four key dimensions to lay a foundation for future research: (i) precarity and exploitation, (ii) surveillance and control, (iii) blurring employment boundaries, and (iv) colonial legacies. It advocates for participatory research, transparency in platform governance, and structural changes to promote more equitable conditions for digital platform workers. |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2510.19450 |
| By: | Ana Lleó-Bono; Ines Lee; Eileen Tipoe; Christopher Rauh |
| Abstract: | This paper examines whether increasing individuals' awareness of their own confidence can influence financial behaviour. In a pre-registered online experiment with nearly 3, 000 U.S. adults, we test the effects of a novel metacognitive intervention: personalised feedback on implicit confidence about one's financial abilities, as measured by a custom Implicit Association Test (IAT), paired with an explanation of the importance of self-confidence in financial abilities. Treated participants show a significant reduction in "don't know" responses on financial literacy tests and their performance in an incentivised investment task significantly improves: treated participants are less likely to make clearly dominated choices, more likely to select efficient allocations, and choose portfolios closer to the efficient frontier. These effects persist two weeks later in a follow-up survey with obfuscated framing. Heterogeneity analyses show stronger effects for females and for participants who understate their confidence (i.e. whose reported confidence is lower than what their IAT suggests). |
| Keywords: | confidence, financial literacy, onfidence awareness, personal finance, survey experiments |
| JEL: | D14 D83 D91 G11 G53 |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:bge:wpaper:1522 |
| By: | Andres Garcia-Medina |
| Abstract: | Covariance matrices estimated from short, noisy, and non-Gaussian financial time series-particularly cryptocurrencies-are notoriously unstable. Empirical evidence indicates that these covariance structures often exhibit power-law scaling, reflecting complex and hierarchical interactions among assets. Building on this insight, we propose a power-law covariance model to characterize the collective dynamics of cryptocurrencies and develop a hybrid estimator that integrates Random Matrix Theory (RMT) with Residual Neural Networks (ResNets). The RMT component regularizes the eigenvalue spectrum under high-dimensional noise, while the ResNet learns data-driven corrections to recover latent structural dependencies. Monte Carlo simulations show that ResNet-based estimators consistently minimize both Frobenius and minimum-variance (MV) losses across diverse covariance models. Empirical experiments on 89 cryptocurrencies (2020-2025), using a training period ending at the local BTC maximum in November 2021 and testing through the subsequent bear market, demonstrate that a two-step estimator combining hierarchical filtering with ResNet corrections yields the most profitable and balanced portfolios, remaining robust under market regime shifts. These findings highlight the potential of combining RMT, deep learning, and power-law modeling to capture the intrinsic complexity of financial systems and enhance portfolio optimization under realistic conditions. |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2510.19130 |
| By: | Alberto G. Musalem |
| Abstract: | St. Louis Fed President Alberto Musalem gave welcoming remarks to open the two-day conference. Held at the St. Louis Fed, the conference was co-sponsored by the Federal Reserve Banks of Boston, Philadelphia and Richmond. |
| Keywords: | credit access; low-and moderate-income (LMI); financial services |
| Date: | 2025–10–22 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fedlps:101995 |
| By: | Pattravadee de Favereau de Jeneret; Ioannis Diamantis |
| Abstract: | This study investigates whether Topological Data Analysis (TDA) can provide additional insights beyond traditional statistical methods in clustering currency behaviours. We focus on the foreign exchange (FX) market, which is a complex system often exhibiting non-linear and high-dimensional dynamics that classical techniques may not fully capture. We compare clustering results based on TDA-derived features versus classical statistical features using monthly logarithmic returns of 13 major currency exchange rates (all against the euro). Two widely-used clustering algorithms, \(k\)-means and Hierarchical clustering, are applied on both types of features, and cluster quality is evaluated via the Silhouette score and the Calinski-Harabasz index. Our findings show that TDA-based feature clustering produces more compact and well-separated clusters than clustering on traditional statistical features, particularly achieving substantially higher Calinski-Harabasz scores. However, all clustering approaches yield modest Silhouette scores, underscoring the inherent difficulty of grouping FX time series. The differing cluster compositions under TDA vs. classical features suggest that TDA captures structural patterns in currency co-movements that conventional methods might overlook. These results highlight TDA as a valuable complementary tool for analysing financial time series, with potential applications in risk management where understanding structural co-movements is crucial. |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2510.19306 |