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on Payment Systems and Financial Technology |
| By: | Michael Barczay; Mr. Shafik Hebous; Fayçal Sawadogo; Jean-François Wen |
| Abstract: | Mobile money has become a central digital alternative to traditional banking in developing countries, yet several African governments have introduced taxes on mobile money transactions. We develop a model that characterizes how such taxes affect payment choices and generate excess burden. The model predicts that taxation reduces mobile money use, with elasticities shaped by access to substitutes and transaction costs: banked users substitute into formal alternatives, while unbanked users face higher effective costs, making the tax regressive. Taxation also induces substitution into cash, raising informality. We empirically test these predictions using cross-country survey data and novel transaction-level data from Cameroon, the Central African Republic, and Mali. Results show sharp declines in mobile money usage, with stronger responses among the banked. Unbanked and rural users bear a disproportionate burden. We use the empirical estimates to gauge the excess burden of the tax, which we quantify at 35% of revenue—highlighting its significant efficiency cost alongside its regressive impact. |
| Keywords: | Mobile Money Tax; Financial Inclusion; Transaction Taxes |
| Date: | 2025–12–05 |
| URL: | https://d.repec.org/n?u=RePEc:imf:imfwpa:2025/255 |
| By: | Habib Badawi |
| Abstract: | This paper analyzes the intersection of presidential authority and cryptocurrency markets during Donald J. Trump's second term (2025-2029). We examine developments from 2024 through October 2025, focusing on how executive influence, family business ventures, and digital assets became intertwined in ways that blurred boundaries between public office and private profit. Using a mixed-methods approach that combines quantitative market data with qualitative institutional assessment, we identify politically linked digital assets as a distinct class characterized by reflexive valuations, asymmetric risk distribution, and systemic vulnerabilities. The Trump family's integrated cryptocurrency ecosystem reached peak valuations exceeding eleven billion dollars before collapsing by more than one trillion in market capitalization following a tariff announcement in October 2025. Results highlight conflicts of interest, failures in market microstructure, and the emergence of political finance as a monetizable phenomenon in the digital age. The study contributes to understanding how presidential signaling reshapes capital flows, how politically branded tokens function as quasi-currencies, and how sudden policy actions can trigger cascading liquidations across global digital asset systems. |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2512.03189 |
| By: | Yhlas Sovbetov |
| Abstract: | This paper examines factors that influence prices of most common five cryptocurrencies such as Bitcoin, Ethereum, Dash, Litecoin, and Monero over 2010-2018 using weekly data. The study employs ARDL technique and documents several findings. First, cryptomarket-related factors such as market beta, trading volume, and volatility appear to be significant determinant for all five cryptocurrencies both in short- and long-run. Second, attractiveness of cryptocurrencies also matters in terms of their price determination, but only in long-run. This indicates that formation (recognition) of the attractiveness of cryptocurrencies are subjected to time factor. In other words, it travels slowly within the market. Third, SP500 index seems to have weak positive long-run impact on Bitcoin, Ethereum, and Litcoin, while its sign turns to negative losing significance in short-run, except Bitcoin that generates an estimate of -0.20 at 10% significance level. Lastly, error-correction models for Bitcoin, Etherem, Dash, Litcoin, and Monero show that cointegrated series cannot drift too far apart, and converge to a long-run equilibrium at a speed of 23.68%, 12.76%, 10.20%, 22.91%, and 14.27% respectively. |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2511.22782 |
| By: | Kundan Mukhia; Buddha Nath Sharma; Salam Rabindrajit Luwang; Md. Nurujjaman; Chittaranjan Hens; Suman Saha; Tanujit Chakraborty |
| Abstract: | We study how the 2024 U.S. presidential election, viewed as a major political risk event, affected cryptocurrency markets by distinguishing human-driven peer-to-peer stablecoin transactions from automated algorithmic activity. Using structural break analysis, we find that human-driven Ethereum Request for Comment 20 (ERC-20) transactions shifted on November 3, two days before the election, while exchange trading volumes reacted only on Election Day. Automated smart-contract activity adjusted much later, with structural breaks appearing in January 2025. We validate these shifts using surrogate-based robustness tests. Complementary energy-spectrum analysis of Bitcoin and Ethereum identifies pronounced post-election turbulence, and a structural vector autoregression confirms a regime shift in stablecoin dynamics. Overall, human-driven stablecoin flows act as early-warning indicators of political stress, preceding both exchange behavior and algorithmic responses. |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2512.00893 |
| By: | Biais, Bruno (HEC Paris); Rochet, Jean Charles (University of Geneva); Villeneuve, Stéphane (University of Toulouse 1) |
| Abstract: | In our dynamic general equilibrium model, agents can invest in money and in a production technology exposed to shocks. If the government is non-benevolent and has a monopoly over money issuance it issues too much money, to finance excessive public expenditures. We study the effects of a cryptocurrency in limited supply but with crash risk. If the crash risk is not too large, competition from the cryptocurrency constrains the government's monetary policy. If the government is non-benevolent, this constraint improves citizens welfare, but if the government is rather benevolent competition from the cryptocurrency can lower citizens' welfare. |
| Keywords: | Cryptocurrency; Hyperinflation; Dynamic General Equilibrium; Denationalisation of money |
| JEL: | E42 |
| Date: | 2025–05–18 |
| URL: | https://d.repec.org/n?u=RePEc:ebg:heccah:1568 |
| By: | Hans Jarle Kind; Dirk Schindler; Guttorm Schjelderup |
| Abstract: | Digital Services Taxes (DSTs) and the OECD/G20 BEPS reforms are central pillars of current efforts to tax multinational digital platforms, yet their joint effects remain poorly understood. We develop a model of a platform that sells hardware to consumers and advertising to firms, with the two markets connected through cross-group network externalities. We show that a DST can have counterproductive effects: it may lower tax revenue in the implementing country, weaken downstream price competition, and reduce consumer surplus by inducing the platform to shift activity toward the untaxed side of the market. We further show that stricter transfer pricing regulation - a core element of BEPS - can paradoxically increase profit shifting when network effects are strong. |
| Keywords: | digital platforms, digital services tax, BEPS, profit shifting |
| JEL: | F23 H26 H25 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12302 |
| By: | Robin Ng |
| Abstract: | This paper examines how two-sided platforms develop their recommender systems to be precise about value-for-money. On each platform, more precise recommendations generate ranking and screening effects: they steer demand toward high value-for-money products, intensifying price competition among firms which drives out lower-quality firms. Thus, more precise recommendations benefit consumers but reduce platform’s per-transaction revenue. A monopolist platform still prefers precise recommendations, as this expands demand. Competing platforms choose even more precise recommendations. However, when consumers search across platforms or recommender systems are overly complex, recommendations become less precise. This shows that market power is only one potential explanation for 'ensh*ttification'. |
| Keywords: | Digital economy, Recommender systems, Two-sided platforms |
| JEL: | D21 L10 L86 |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:bon:boncrc:crctr224_2025_718 |
| By: | Carlo Gola; Valentina Cappa; Patrizio Fiorenza; Paolo Granata; Federica Laurino; Lorenzo Lesina; Francesco Lorizzo; Gabriele Marcelli |
| Abstract: | This paper deals with the governance of systems based on distributed ledger technology (DLT). This technology enables the creation of a shared electronic archive accessible via the internet, in which information is stored in a secure and irreversible manner. The updating and management of the ledger takes place without resorting to a trusted third party. The absence of traditional organizational and governance structures makes DLT management complex. The work provides a conceptual framework to understand DLT technology and analyzes its governance, both for open (permissionless) systems and for those with limited access (permissioned). Different approaches are suggested for the application of governance rules, including for DLT with entirely algorithmic governance. The study describes the difference between management and governance tokens, having respectively administrative and property rights, which facilitate the direction and control of DLTs. Finally, the governance structure of two DLTs is described: Ethereum and Polkadot. |
| Date: | 2024–04 |
| URL: | https://d.repec.org/n?u=RePEc:liu:liucec:2024-17 |
| By: | Wenbin Wu; Kejiang Qian; Alexis Lui; Christopher Jack; Yue Wu; Peter McBurney; Fengxiang He; Bryan Zhang |
| Abstract: | We curate the DeXposure dataset, the first large-scale dataset for inter-protocol credit exposure in decentralized financial networks, covering global markets of 43.7 million entries across 4.3 thousand protocols, 602 blockchains, and 24.3 thousand tokens, from 2020 to 2025. A new measure, value-linked credit exposure between protocols, is defined as the inferred financial dependency relationships derived from changes in Total Value Locked (TVL). We develop a token-to-protocol model using DefiLlama metadata to infer inter-protocol credit exposure from the token's stock dynamics, as reported by the protocols. Based on the curated dataset, we develop three benchmarks for machine learning research with financial applications: (1) graph clustering for global network measurement, tracking the structural evolution of credit exposure networks, (2) vector autoregression for sector-level credit exposure dynamics during major shocks (Terra and FTX), and (3) temporal graph neural networks for dynamic link prediction on temporal graphs. From the analysis, we observe (1) a rapid growth of network volume, (2) a trend of concentration to key protocols, (3) a decline of network density (the ratio of actual connections to possible connections), and (4) distinct shock propagation across sectors, such as lending platforms, trading exchanges, and asset management protocols. The DeXposure dataset and code have been released publicly. We envision they will help with research and practice in machine learning as well as financial risk monitoring, policy analysis, DeFi market modeling, amongst others. The dataset also contributes to machine learning research by offering benchmarks for graph clustering, vector autoregression, and temporal graph analysis. |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2511.22314 |
| By: | Kamal Paykan (Department of Mathematics, Tafresh University, Tafresh, Iran) |
| Abstract: | This paper proposes a reinforcement learning--based framework for cryptocurrency portfolio management using the Soft Actor--Critic (SAC) and Deep Deterministic Policy Gradient (DDPG) algorithms. Traditional portfolio optimization methods often struggle to adapt to the highly volatile and nonlinear dynamics of cryptocurrency markets. To address this, we design an agent that learns continuous trading actions directly from historical market data through interaction with a simulated trading environment. The agent optimizes portfolio weights to maximize cumulative returns while minimizing downside risk and transaction costs. Experimental evaluations on multiple cryptocurrencies demonstrate that the SAC and DDPG agents outperform baseline strategies such as equal-weighted and mean--variance portfolios. The SAC algorithm, with its entropy-regularized objective, shows greater stability and robustness in noisy market conditions compared to DDPG. These results highlight the potential of deep reinforcement learning for adaptive and data-driven portfolio management in cryptocurrency markets. |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2511.20678 |
| By: | Hiroaki Chiba-Okabe; Joshua B. Plotkin |
| Abstract: | We study the behavior of for-profit institutions that broadcast reputations to foster trust among market participants. We develop a theoretical model in which buyers and sellers are matched on a platform to engage in transactions involving a moral hazard: sellers can either faithfully deliver goods after receiving payment, or not. Although the buyer does not know a seller's true type, the platform maintains a reputation system that probabilistically assigns binary reputation signals. Buyers make purchase decisions based on reputation signals, which influence the payoffs to sellers who then adapt their type over time. These market dynamics ultimately shape the platform's profit from commissions on sales. Our analysis reveals that platforms inherently have an incentive for rating inflation, driven by the desire to increase commission. This introduces a second layer of moral hazard: the platform's incentive to distort reputations for its own profit. Such distortion is self-limited by the platform's need to maintain enough accuracy that trustworthy sellers remain in the market, without which rational buyers would refrain from purchases altogether. Nonetheless, the optimal strategy for the platform can be to invest in order to reduce signal accuracy. When the platform can freely set commission fees, however, maximum profit may be achieved by costly investment in an accurate reputation system. These findings highlight the intricate tensions between platform incentives and resulting social utility for marketplace participants. |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2511.21875 |
| By: | Gupta, Sagnik Kumar; Ojha, Manini; Dhamija, Gaurav |
| Abstract: | We examine whether women's exposure to the internet enhances their economic agency in India. Using nationally representative data and an instrumental variables strategy that exploits plausibly exogenous variation in district-level mobile tower density, we identify the causal effect of internet access on women's financial control and use of formal banks. We find that internet exposure increases women's overall financial autonomy by 10 percentage points. We document improvements in independent mobility, employment, and financial awareness which we consider potential mechanisms of our estimated effects. Disaggregated outcomes show higher likelihood that women have money of their own over which they full control, as well as increased ownership and active use of a bank account. Our results are robust to additional controls and a battery of sensitivity analyses. Heterogeneity analyses indicate that effects are concentrated among women with at least secondary education, and among those from historically disadvantaged social groups. Overall, our findings highlight the importance of digital connectivity in enhancing the usage of financial resources, with important implications for women's autonomy and participation in the formal economy. |
| Keywords: | Internet Exposure, Mobile Tower Density, Financial Autonomy, Instrumental Variable, India |
| JEL: | D13 G20 I31 J16 O12 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:glodps:1697 |
| By: | Weikang Zhang; Alison Watts |
| Abstract: | Crypto enthusiasts claim that buying and holding crypto assets yields high returns, often citing Bitcoin's past performance to promote other tokens and fuel fear of missing out. However, understanding the real risk-return trade-off and what factors affect future crypto returns is crucial as crypto becomes increasingly accessible to retail investors through major brokerages. We examine the HODL strategy through two independent analyses. First, we implement 480 million Monte Carlo simulations across 378 non-stablecoin crypto assets, net of trading fees and the opportunity cost of 1-month Treasury bills, and find strong evidence of survivorship bias and extreme downside concentration. At the 2-3 year horizon, the median excess return is -28.4 percent, the 1 percent conditional value at risk indicates that tail scenarios wipe out principal after all costs, and only the top quartile achieves very large gains, with a mean excess return of 1, 326.7 percent. These results challenge the HODL narrative: across a broad set of assets, simple buy-and-hold loads extreme downside risk onto most investors, and the miracles mostly belong to the luckiest quarter. Second, using a Bayesian multi-horizon local projection framework, we find that endogenous predictors based on realized risk-return metrics have economically negligible and unstable effects, while macro-finance factors, especially the 24-week exponential moving average of the Fear and Greed Index, display persistent long-horizon impacts and high cross-basket stability. Where significant, a one-standard-deviation sentiment shock reduces forward top-quartile mean excess returns by 15-22 percentage points and median returns by 6-10 percentage points over 1-3 year horizons, suggesting that macro-sentiment conditions, rather than realized return histories, are the dominant indicators for future outcomes. |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2512.02029 |
| By: | Burga, Carlos; Cespedes, Jacelly; Parra, Carlos R; Ricca, Bernardo |
| Abstract: | A long-standing debate concerns whether technological change widens wage gaps by benefiting skilled labor. We show that financial technologiesspecifically, instant payment systemscan instead reduce wage inequality. Using an administrative dataset covering all registered employees in Brazil, we study the nationwide rollout of Pix, an instant payment platform introduced in late 2020. Our empirical strategy is a triple difference-in-differences design that exploits variation in preexisting mobile penetration across municipalities, the differential benefits of Pix for cash-intensive versus non-cash-intensive sectors, and the timing of Pixs rollout. A one standard deviation increase in mobile penetration leads to a 1.2 percent wage increase in cash-intensive sectors relative to non-cash-intensive sectors following Pixs introduction. These wage gains are concentrated among workers with less education, reducing the college wage premium by 1 percentage point. Further evidence suggests that increased small-business labor demand, amplified by local labor market frictions, drives these effects. Overall, instant payment systems disproportionately benefit small, cash-intensive businesses, enhancing labor demand in sectors reliant on low-skill workers and highlighting how financial technologies can shape distributional outcomes differently from skill-biased technologies. |
| JEL: | J31 O33 G23 |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:idb:brikps:14416 |
| By: | Emilio Ocampo; Nicolás Cachanosky |
| Abstract: | This paper investigates a puzzle in the behavior of the money supply in Ecuador after it formally adopted the US dollar as its currency in January 2000. Modern open economy macroeconom-ics (MOEM) predicts that in a small open economy under an official dollarization regime, the money supply is endogenous to movements in the balance of payments. However, Ecuador’s monetary and balance of payment statistics suggest otherwise. This incongruity has led some authors to claim that MOEM does not hold in Ecuador. We challenge this claim and argue that three factors can explain the apparent puzzle: a) monetary data misspecification, b) measure-ment errors in foreign trade flows, and c) an exogenous expansion of its balance sheet of the Central Bank of Ecuador’s (CBE) during the period 2009-2014 to finance government deficits. We conclude that Ecuador’s experience under dollarization is consistent with a key prediction of MOEM: inflation convergence. However, it also shows that the constraints that in theory an official dollarization places on fiscal profligacy and monetary activism can be overcome by creative spendthrift politicians. Finally, we highlight the challenge of measuring cash in econo-mies that are dollarized or are part of a currency union and the need to consider the institutional and regulatory framework adopted for the central bank after dollarization to understand the monetary dynamics of an officially dollarized economy. |
| Keywords: | money supply; dollarization |
| JEL: | E42 E59 O54 |
| Date: | 2025–06 |
| URL: | https://d.repec.org/n?u=RePEc:cem:doctra:898 |
| By: | Elacqua, Gregory; Kutscher, Macarena; Nascimento, Danielle; Dias, Isabella; Margitic, Juan Francisco |
| Abstract: | Despite improvements in access to information, digital platforms, and centralized school admission systems, many parents continue to choose seemingly lower-quality schools, often prioritizing proximity over academic performance. We examine the role of information provision in this context through a randomized controlled trial (RCT) within the centralized admission platform of Recife, Brazil testing whether personalized school recommendations influence parental choice. Specifically, we implemented two treatment arms: one offering recommendations that ranked schools by quality within a defined distance (quality treatment), and another ranking schools solely by proximity (distance treatment). While the overall impact of the treatments was limited, we do find meaningful positive effects among users who actively engaged (”compliers”) with the recommendations (1424% of families). Compliers in the quality treatment were more likely to select higher-performing schools, particularly among first-grade applicants and families without strong prior preferences. These findings underscore both the promise of digital nudges in improving school choices and the challenges of deploying such tools in recently centralized systems, where many families enter with preset preferences and limited familiarity with the process. |
| Keywords: | school choice;Information Provision;Digital Nudges;Randomized Controlled Trials;Centralized Admission Systems;Parental School Choice Behavior;Digital Nudges and Engagement;Challenges in Centralized Admission;Decision.making;Education, childhood, equality |
| JEL: | I21 I24 I28 D83 C93 |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:idb:brikps:14420 |
| By: | John Beirne (Asian Development Bank); Pradeep Panthi (Policy Research Institute); Guna Raj Bhatta (Nepal Rastra Bank) |
| Abstract: | This paper examines the role of financial development as a buffer for the appreciating effects of remittances on exchange rates using annual data from 1996 to 2021 for 146 economies, with a focus on 43 high remittance-receiving economies. A panel regression framework is employed in the baseline analysis, which remains robust to an instrumental variables approach. The findings reveal that remittances have appreciating effects on real effective exchange rates (REER), especially in high remittance-receiving economies, consistent with the “Dutch disease” mechanism. Examining subcomponents of financial development, we find that stronger domestic financial markets and market-based financial deepening are critical channels for absorbing the REER appreciation effects of remittances |
| Keywords: | remittances;exchange rates;financial development |
| JEL: | F24 F31 G21 O16 |
| Date: | 2025–11–27 |
| URL: | https://d.repec.org/n?u=RePEc:ris:adbewp:021791 |
| By: | Nicola Cortinovis |
| Abstract: | Entrepreneurs in rural areas face much greater difficulties than those located in cities, also with respect to the access to entrepreneurial finance. Recent developments in the provision of capital, however, have opened new opportunities for small firms and start-ups to obtain funding. In this empirical work, I hypothesize that crowdfunding provides crucial resources and support for rural-based entrepreneurs and that rural areas characterized by greater (bridging) social capital are better positioned to benefit from the opportunities of crowdfunding. Using a newly developed database linking crowdfunding campaigns to industry and counties in the U.S. (KIUS), county-level information on social capital and official U.S. census data, I test these hypotheses. My findings indicate that crowdfunding is indeed positively related to the number of ventures operating in the industry-location in the following period. In addition, this relationship is stronger for counties with higher levels of bridging social capital and of civic engagement. The results are robust to a number of checks, including a placebo test and matching exercises. |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:egu:wpaper:2535 |
| By: | Douglas Cumming; My Nguyen; Anh Viet Pham; Ama Samarasinghe |
| Abstract: | We examine the role of cybercrime legislation around the world in shaping the stability of the banking system. We compile a novel dataset covering the enactment of cybercrime legislation in 132 developed and developing countries to empirically test this research question. We find that the enactment of cybercrime laws enhances the stability of the banking sector. This key finding holds across a comprehensive suite of robustness tests, including alternative measures of bank stability and model specifications. We document significant cross-sectional heterogeneity, with the effect being more pronounced in countries with heavier penalties for illegal cyber activities and legal frameworks that hold banks accountable for their cybersecurity practices. In addition, the positive impact is stronger in jurisdictions with greater international legal cooperation and effective enforcement mechanisms. We further investigate two channels (i.e., funding liquidity and operational risk) through which cybercrime laws may influence bank stability. Our results indicate that these laws can significantly bolster bank stability by enhancing funding liquidity and mitigating operational risk. Overall, our study highlights the crucial role of cybercrime legislation in fostering a secure and resilient banking environment. It offers new insights into how these laws contribute to bank stability on both individual and systemic levels. |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2512.01237 |
| By: | Marcus, J. Scott |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:itse25:331292 |