nep-pay New Economics Papers
on Payment Systems and Financial Technology
Issue of 2023‒10‒16
25 papers chosen by
Bernardo Bátiz-Lazo, Northumbria University

  1. Can Digital G2P Transfers Drive Financial Inclusion and Digital Payments? Evidence from India By Alan Gelb; Anit Mukherjee; Brian Webster
  2. Tokenization: Overview and Financial Stability Implications By Francesca Carapella; Grace Chuan; Jacob Gerszten; Nathan Swem
  3. FinTech-Issued Personal Loans in the U.S. By Jessica N. Flagg; Simona Hannon
  4. The digital divide in rural Ethiopia: Determinants and implications of sex-disaggregated mobile phone ownership and use By Warner, James; Mekonnen, Yalew; Habte, Yetimwork
  5. Trends in Consumers Towards Online Shopping After Coronavirus Pandemic By Mezghiche Djamel; Abdallah M'Hamed
  6. Can you spot a scam? Measuring and improving scam identification ability By Elif Kubilay; Eva Raiber; Lisa Spantig; Jana Cahlíková; Lucy Kaaria
  7. Pathways toward digitalization in Social Protection and Labor (SPL) service delivery By Lowe, Christina Louise; Rigolini, Iamele P.; Solbes Castro, Lucia; Bastagli, Francesca Adele
  8. 「書」中自有千里馬?企業經營臉書人才招募粉絲專頁 之動機、手法、困境與省思 By Huang, Tun-Chun
  9. Real-time VaR Calculations for Crypto Derivatives in kdb+/q By Yutong Chen; Paul Bilokon; Conan Hales; Laura Kerr
  10. The Returns to Viral Media : The Case of US Campaign Contributions By Boken, Johannes; Draca. Mirko; Mastrorocco, Nicola; Ornaghi, Arianna
  11. A Bayesian DSGE Approach to Modelling Cryptocurrency By Stylianos Asimakopoulos; Marco Lorusso; Francesco Ravazzolo
  12. Searching for Smurfs: Testing if Money Launderers Know Alert Thresholds By Rasmus Ingemann Tuffveson Jensen; Joras Ferwerda; Christian Remi Wewer
  13. Do you have two minutes to talk about your data? Willingness to participate and nonparticipation bias in Facebook data donation By Keusch, Florian; Pankowska, Paulina; Cernat, Alexandru; Bach, Ruben L.
  14. The Costs of Swapping on the Uniswap Protocol By Austin Adams; Benjamin Y Chan; Sarit Markovich; Xin Wan
  15. Artificial Intelligence and Its Impact on Information Technology (IT) Service Sector in Bangladesh By Fahmida Khatun; Nadia Nawrin
  16. Dynamic relationship between XRP price and correlation tensor spectra of the transaction network By Abhijit Chakraborty; Tetsuo Hatsuda; Yuichi Ikeda
  17. Immorality Judgments and Framing Effects in Voluntary Payment Settings By Elisa Hofmann; Deliah Bolesta; Aya Adra
  18. Algorithmic Collusion or Competition: the Role of Platforms' Recommender Systems By Xingchen Xu; Stephanie Lee; Yong Tan
  19. Stylized Facts From Prices at Multi-Channel Retailers in Mexico By Solórzano Diego
  20. Detecting Pump-and-Dumps with Crypto-Assets: Dealing with Imbalanced Datasets and Insiders’ Anticipated Purchases By Fantazzini, Dean; Xiao, Yufeng
  21. Can Patience Account for Subnational Differences in Student Achievement? Regional Analysis with Facebook Interests By Eric A. Hanushek; Lavinia Kinne; Sancassani Pietro; Ludger Woessmann
  22. GPT has become financially literate: Insights from financial literacy tests of GPT and a preliminary test of how people use it as a source of advice By Pawe{\l} Niszczota; Sami Abbas
  23. Digitalization: Definition and Measurement By Guyllaume Faucher; Stephanie Houle
  24. How is the literature on Digital Entrepreneurial Ecosystems structured? A socio-semantic network approach By Arnauld Bessagnet; Joan Crespo; Jerome Vicente
  25. How Automated Market Makers Approach the Thin Market Problem in Cryptoeocnomic Systems By Daniel Kirste; Niclas Kannengie{\ss}er; Ricky Lamberty; Ali Sunyaev

  1. By: Alan Gelb (Center for Global Development); Anit Mukherjee (Center for Global Development); Brian Webster (Center for Global Development)
    Abstract: Does channeling government-to-person (G2P) payments through bank accounts encourage financial inclusion and use? This paper explores the factors that have driven the adoption of digital payments in India by beneficiaries of PMGKY, the large-scale COVID-19 relief program launched in May 2020. India’s 2013 move to pay social benefits through direct transfers into bank accounts significantly increased account ownership, but uptake of digital payments has been slower, although it has accelerated more recently through smartphone-based apps. Recipient survey data shows that personal and household attributes influence the likelihood of adopting digital payments. Smartphone ownership and digital literacy improve the odds while being a woman reduces them. The strength of the local digital payments ecosystem also exerts significant influence on household adoption; favorable personal and ecosystem factors are needed for widespread use. The historical progression shows that G2P transfers create an entry point but that widespread access to low-cost mobile telecommunications, interoperability, and the entry of new players offering convenient payments interfaces have been vital to the growth of digital payments.
    Keywords: digital, payments, India
    JEL: G20 G53 O10 O16 O33 O35
    Date: 2022–06–09
  2. By: Francesca Carapella; Grace Chuan; Jacob Gerszten; Nathan Swem
    Abstract: In this paper we outline tokenization, which is a new and rapidly growing financial innovation in crypto asset markets, and we discuss potential benefits and financial stability implications. Tokenization refers to the process of constructing digital representations (crypto tokens) for non-crypto assets (reference assets). As we discuss below, tokenizations create interconnections between the digital asset ecosystem and the traditional financial system. At sufficient scale, tokenized assets could transmit volatility from crypto asset markets to the markets for the crypto token's reference assets.
    Keywords: Tokenization; Crypto-assets; Blockchain; Decentralized finance; DeFi; Financial stability and risk; Financial innovations; Interconnections
    JEL: D49 D53 G00 G10 G20 G23
    Date: 2023–09–08
  3. By: Jessica N. Flagg; Simona Hannon
    Abstract: The financial technology advances of the past decade brought to prominence a new group of lenders active within the personal loan space—financial technology (FinTech) lenders. Although traditional lenders such as banks, thrifts, credit unions, and finance companies continue to play an important role in providing personal loans to consumers, FinTech lenders gained a notable market share.
    Keywords: fintech; financial technology; personal loans
    Date: 2023–08–30
  4. By: Warner, James; Mekonnen, Yalew; Habte, Yetimwork
    Abstract: Mobile phones are rapidly being adopted in less developed countries, with widely acknowledged commensurate socio-economic benefits, including United Nations SDGs advocating for increased ownership of mobile phones to promote women’s empowerment. While overall mobile phone ownership is rising quickly in Ethiopia, it is lagging for rural women, particularly married rural women. Overall, we find that married men are approximately five times more likely to own a phone than their wives even though married women with phones are more active in agricultural decision making. This lack of female mobile phone ownership should be considered within the broader context of several recent Ethiopian digital initiatives, including mobile banking and mobile payments. These initiatives are likely to provide greater benefits to those individuals that own a mobile phone. By applying gender analysis to phone ownership, we believe that we can anticipate some potentially unexpected negative consequences for women created by these mobile phone initiatives. This paper outlines current rural sex-disaggregated phone ownership trends, determinants of phone ownership, and related impacts on intrahousehold decision making. We believe that by identifying these gender differences in mobile phone ownership, policymakers can better target their digital economy initiatives.
    Keywords: ETHIOPIA; EAST AFRICA; AFRICA SOUTH OF SAHARA; AFRICA; mobile phones; developing countries; socioeconomic development; women's empowerment; rural areas; women; gender; marriage; agriculture; technological innovation; Sustainable Development Goals; intrahousehold decision making; rural households
    Date: 2023
  5. By: Mezghiche Djamel (UMBB - Université M'Hamed Bougara Boumerdes); Abdallah M'Hamed (IMT - Institut Mines-Télécom [Paris])
    Abstract: Online marketing has become popular in world in general and the Arab world in particular is witnessing the desirability and satisfaction of the world. However, he did not meet his right in Algeria, which knows of the delay in adopting commercial transactions in the electronic environment despite growing consumer demand for Internet use, their trends towards online shopping. In our view, this may be due to the lack of adequate mechanisms affecting the Algerian user in the adoption of shopping.
    Keywords: Online marketing Coronavirus Pandemic online shopping Online Apps consumer. JEL Classification Codes: D43, F16, G14, L11, Online marketing, Coronavirus Pandemic, online shopping, Online Apps, consumer. JEL Classification Codes: D43
    Date: 2023–06–04
  6. By: Elif Kubilay (University of Essex, IZA - Forschungsinstitut zur Zukunft der Arbeit - Institute of Labor Economics); Eva Raiber (AMSE - Aix-Marseille Sciences Economiques - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique, CEPR - Center for Economic Policy Research - CEPR); Lisa Spantig (UKA - Universitätsklinikum RWTH Aachen - University Hospital Aachen [Aachen, Germany] - RWTH - Rheinisch-Westfälische Technische Hochschule Aachen University, University of Essex); Jana Cahlíková (Universität Bonn = University of Bonn); Lucy Kaaria (UoN - University of Nairobi)
    Abstract: The expansion of digital financial services leads to severe consumer protection issues such as fraud and scams. As these potentially decrease trust in digital services, especially in developing countries, avoiding victimization has become an important policy objective. In an online experiment, we first investigate how well individuals in Kenya identify phone scams using a novel measure of scam identification ability. We then test the effectiveness of scam education, a commonly used approach by organizations for fraud prevention. We find that common tips on how to spot scams do not significantly improve individuals' scam identification ability, i.e., the distinction between scams and genuine messages. This null effect is driven by an increase in correctly identified scams and a decrease in correctly identified genuine messages, indicating overcaution. Additionally, we find suggestive evidence that genuine messages with scam-like features are misclassified more often, highlighting the importance of a careful design of official communication.
    Keywords: Consumer protection, consumer fraud, digital financial services, scam susceptibility, scam education, Kenya
    Date: 2023
  7. By: Lowe, Christina Louise; Rigolini, Iamele P.; Solbes Castro, Lucia; Bastagli, Francesca Adele
    Abstract: This paper offers three key contributors to the excising literature. Firstly, it reviewsthe use of technology across each phase of delivering social protection and labor (SPL) benefits and services. Secondly, it reviews evidence on potential outcomes arising from digitalization initiatives, and identifies factors and conditions that facilitate successful design and implementation. Lastly, the paper outlines a conceptual framework for different digitalizing pathways. This framework distinguishes between: (1) the progressive digitalization of analog core SPL architecture; (2) ‘leapfrogging’ innovations, which use novel digital approaches from the outset in contexts where SPL provision is nascent and traditional core architecture does not exist; and (3) the use of supporting technologies that may be helpful in their own right but neither contribute to, nor rely on, to digitalization of core SPL architecture
    Date: 2023–10–05
  8. By: Huang, Tun-Chun
    Abstract: More and more corporate recruiters are (or are interested in) using Facebook fan pages to achieve their recruitment goals. Despite research interest in social media recruitment has grown rapidly in recent years, many questions remain unanswered in the literature. Why and how do companies use Facebook fan pages as a recruitment channel? What are the challenges and opportunities faced by these companies? To answer these questions, qualitative evidence collected from 29 firms operating Facebook fan pages for recruitment purposes. Results of the present study are interpreted through the lens of an extended Technology Acceptance Model. First, we identified five key determinants of the organizational adoption of Facebook fan pages (i.e., low/zero cost, popularity, contagion, usability, and interactivity). In addition, instrumental and symbolic motives have driven firms to operate fan pages in different ways. Finally, challenges and possible solutions for running Facebook fan pages were discussed. Taken together, the present study depicts the status quo of social media recruitment in Taiwan and provides future research and practical suggestions for both academics and practitioners.
    Date: 2023–06–29
  9. By: Yutong Chen; Paul Bilokon; Conan Hales; Laura Kerr
    Abstract: Cryptocurrency market is known for exhibiting significantly higher volatility than traditional asset classes. Efficient and adequate risk calculation is vital for managing risk exposures in such market environments where extreme price fluctuations occur in short timeframes. The objective of this thesis is to build a real-time computation workflow that provides VaR estimates for non-linear portfolios of cryptocurrency derivatives. Many researchers have examined the predictive capabilities of time-series models within the context of cryptocurrencies. In this work, we applied three commonly used models - EMWA, GARCH and HAR - to capture and forecast volatility dynamics, in conjunction with delta-gamma-theta approach and Cornish-Fisher expansion to crypto derivatives, examining their performance from the perspectives of calculation efficiency and accuracy. We present a calculation workflow which harnesses the information embedded in high-frequency market data and the computation simplicity inherent in analytical estimation procedures. This workflow yields reasonably robust VaR estimates with calculation latencies on the order of milliseconds.
    Date: 2023–09
  10. By: Boken, Johannes (University of Warwick); Draca. Mirko (University of Warwick); Mastrorocco, Nicola (University of Warwick); Ornaghi, Arianna (Hertie School)
    Abstract: Social media has changed the structure of mass communication. In this paper we explore its role in influencing political donations. Using a daily dataset of campaign contributions and Twitter activity for US Members of Congress 2019-2020, we find that attention on Twitter (as measured by likes) is positively correlated with the amount of daily small donations received. However, this is not true for everybody : the impact on campaign donations is highly skewed, indicating very concentrated returns to attention that are in line with a ‘winner-takes-all’ market. Our results are confirmed in a geography-based causal design linking member’s donations across states.
    Keywords: Social Media ; Twitter ; Campaign Contributions JEL Codes: D72 ; P00
    Date: 2023
  11. By: Stylianos Asimakopoulos; Marco Lorusso; Francesco Ravazzolo
    Abstract: We develop and estimate a DSGE model to evaluate the economic repercussions of cryptocurrency. In our model, cryptocurrency offers an alternative currency option to government currency, with endogenous supply and demand. We uncover a substitution effect between the real balances of government currency and cryptocurrency in response to technology, preferences and monetary policy shocks. We find that an increase in cryptocurrency productivity induces a rise in the relative price of government currency with respect to cryptocurrency. Since cryptocurrency and government currency are highly substitutable, the demand for the former increases whereas it drops for the latter. Our historical decomposition analysis shows that fluctuations in the cryptocurrency price are mainly driven by shocks in cryptocurrency demand, whereas changes in the real balances for government currency are mainly attributed to government currency and cryptocurrency demand shocks.
    Date: 2023–09
  12. By: Rasmus Ingemann Tuffveson Jensen; Joras Ferwerda; Christian Remi Wewer
    Abstract: To combat money laundering, banks raise and review alerts on transactions that exceed confidential thresholds. This paper presents a data-driven approach to detect smurfing, i.e., money launderers seeking to evade detection by breaking up large transactions into amounts under the secret thresholds. The approach utilizes the notion of a counterfactual distribution and relies on two assumptions: (i) smurfing is unfeasible for the very largest financial transactions and (ii) money launderers have incentives to make smurfed transactions close to the thresholds. Simulations suggest that the approach can detect smurfing when as little as 0.1-0.5\% of all bank transactions are subject to smurfing. An application to real data from a systemically important Danish bank finds no evidence of smurfing and, thus, no evidence of leaked confidential thresholds. An implementation of our approach will be available online, providing a free and easy-to-use tool for banks.
    Date: 2023–09
  13. By: Keusch, Florian; Pankowska, Paulina; Cernat, Alexandru; Bach, Ruben L.
    Abstract: Data donation is a novel approach to collecting digital trace data, where users are asked to download their retrospective data from a platform and share them with the researchers. Little is known about the willingness to donate data and the potential bias that may arise from nonparticipation. We conducted a study among over 900 German Facebook users asking them to donate two data packages. While around 80 percent of participants were willing to donate their data, only around one third of them successfully did so. Trust in researchers positively correlates with willingness and donation success, and trust in Facebook is negatively associated with donation success. The framing of the data donation request did not affect the outcomes. We find no difference in frequency of Facebook use between donors and non-donors.
    Date: 2023–09–10
  14. By: Austin Adams; Benjamin Y Chan; Sarit Markovich; Xin Wan
    Abstract: We present the first in-depth empirical characterization of the costs of trading on a decentralized exchange (DEX). Using quoted prices from the Uniswap Labs interface for two pools -- USDC-ETH (5bps) and PEPE-ETH (30bps) -- we evaluate the efficiency of trading on DEXs. Our main tool is slippage -- the difference between the realized execution price of a trade, and its quoted price -- which we breakdown into its benign and adversarial components. We also present an alternative way to quantify and identify slippage due to adversarial reordering of transactions, which we call reordering slippage, that does not require quoted prices or mempool data to calculate. We find that the composition of transaction costs varies tremendously with the trade's characteristics. Specifically, while for small swaps, gas costs dominate costs, for large swaps price-impact and slippage account for the majority of it. Moreover, when trading PEPE, a popular 'memecoin', the probability of adversarial slippage is about 80% higher than when trading a mature asset like USDC. Overall, our results provide preliminary evidence that DEXs offer a compelling trust-less alternative to centralized exchanges for trading digital assets.
    Date: 2023–09
  15. By: Fahmida Khatun; Nadia Nawrin
    Abstract: This paper has attempted to examine the 4IR’s penetration and impacts on the workforce in the IT services sector in Bangladesh. This study also discusses some of the challenges that Bangladesh IT sector faces at present. Finally, contemplating Bangladesh’s preparedness for the digital age of 4IR in terms of access to technology and policy framework, the paper makes a number of recommendations which can enable the country to reap the full benefits of 4IR.
    Keywords: Artificial Intelligence, Fourth industrial revolution, 4IR, CPD-FES Publication
    Date: 2021–11
  16. By: Abhijit Chakraborty; Tetsuo Hatsuda; Yuichi Ikeda
    Abstract: The emergence of cryptoassets has sparked a paradigm shift in the world of finance and investment, ushering in a new era of digital assets with profound implications for the future of currency and asset management. A recent study showed that during the bubble period around the year, 2018, the price of cryptoasset, XRP has a strong anti correlation with the largest singular values of the correlation tensors obtained from the weekly XRP transaction networks. In this study, we provide a detailed analysis of the method of correlation tensor spectra for XRP transaction networks. We calculate and compare the distribution of the largest singular values of the correlation tensor using the random matrix theory with the largest singular values of the empirical correlation tensor. We investigate the correlation between the XRP price and the largest singular values for a period spanning two years. We also uncover the distinct dependence between XRP price and the singular values for bubble and non-bubble periods. The significance of time evolution of singular values is shown by comparison with the evolution of singular values of the reshuffled correlation tensor. Furthermore, we identify a set of driver nodes in the transaction networks that drives the market during the bubble period using the singular vectors.
    Date: 2023–09
  17. By: Elisa Hofmann (Friedrich Schiller University Jena); Deliah Bolesta (Center for Criminological Research Saxony, Chemnitz); Aya Adra (Ramón Llull University, Esade Business School, Barcelona)
    Abstract: The Theory of Dyadic Morality (TDM; Schein and Gray (2018)) posits that immorality judgments emerge from norm violations, harm perceptions, and negative affect. We test this core prediction in an applied setting: voluntary payment settings, such as the Pay-What-You-Want mechanism. In our study, we assess own payment intentions and how voluntary payments of an ostensible individual for an online-news website are judged by participants regarding their perceptions of immorality, harm, anger, and social norms. As political orientation is a key variable in theorizing and exploring immorality judgments in psychological research, we take its potential impact into account in our study. Because voluntary payments have been shown to be sensitive to framing, we vary the pricing mechanism’s name in a between-subjects one-factorial design with four factor levels (Pay-What-You-Want, You-Can, It-Is-Worth-To-You, You-Believe-Is-Fair). The results of our online experiment with 602 Americans indicate that voluntary payment settings are indeed perceived as moral domains. We find that perceptions of norm violation, harm, and negative affect predict immorality judgments, lending empirical support to the Theory of Dyadic Morality. We also show that these components, the immorality judgments, and the own payment intentions are sensitive to framing effects. Finally, we find substantial differences between liberals and conservatives, suggesting an ideological influence on immorality judgments.
    Keywords: Theory of Dyadic Morality, immorality judgments, experiment, voluntary payments, Pay-What-You-Want, framing, social norms
    JEL: C99 D01 D91 L11
    Date: 2023–10–20
  18. By: Xingchen Xu; Stephanie Lee; Yong Tan
    Abstract: Recent academic research has extensively examined algorithmic collusion resulting from the utilization of artificial intelligence (AI)-based dynamic pricing algorithms. Nevertheless, e-commerce platforms employ recommendation algorithms to allocate exposure to various products, and this important aspect has been largely overlooked in previous studies on algorithmic collusion. Our study bridges this important gap in the literature and examines how recommendation algorithms can determine the competitive or collusive dynamics of AI-based pricing algorithms. Specifically, two commonly deployed recommendation algorithms are examined: (i) a recommender system that aims to maximize the sellers' total profit (profit-based recommender system) and (ii) a recommender system that aims to maximize the demand for products sold on the platform (demand-based recommender system). We construct a repeated game framework that incorporates both pricing algorithms adopted by sellers and the platform's recommender system. Subsequently, we conduct experiments to observe price dynamics and ascertain the final equilibrium. Experimental results reveal that a profit-based recommender system intensifies algorithmic collusion among sellers due to its congruence with sellers' profit-maximizing objectives. Conversely, a demand-based recommender system fosters price competition among sellers and results in a lower price, owing to its misalignment with sellers' goals. Extended analyses suggest the robustness of our findings in various market scenarios. Overall, we highlight the importance of platforms' recommender systems in delineating the competitive structure of the digital marketplace, providing important insights for market participants and corresponding policymakers.
    Date: 2023–09
  19. By: Solórzano Diego
    Abstract: Using data gathered through web scraping techniques, this paper characterizes product categories' frequency, size and dispersion of price changes in eight retail chains in Mexico, and compare them with price statistics stemming from brick and mortar stores data of the same retailers. Notably, between 2016 and 2019, prices observed in brick and mortar stores (offline) change more frequently than those observed on websites (online). However, given a price change, online prices tend to exhibit larger price changes than their offline counterparts. In 2020, period affected by the pandemic, the above relationship across sales channel holds, while the frequency of price changes increased roughly by the same magnitude in both sales channels and the average size of price adjustments did not change relative to previous years. Results from this paper highlight the importance of recognizing the differences between survey and web scraped data.
    Keywords: Nominal rigidities;Consumer prices;Web scraped data;Survey microdata
    JEL: E31 L16
    Date: 2023–09
  20. By: Fantazzini, Dean; Xiao, Yufeng
    Abstract: Detecting pump-and-dump schemes involving cryptoassets with high-frequency data is challenging due to imbalanced datasets and the early occurrence of unusual trading volumes. To address these issues, we propose constructing synthetic balanced datasets using resampling methods and flagging a pump-and-dump from the moment of public announcement up to 60 min beforehand. We validated our proposals using data from Pumpolymp and the CryptoCurrency eXchange Trading Library to identify 351 pump signals relative to the Binance crypto exchange in 2021 and 2022. We found that the most effective approach was using the original imbalanced dataset with pump-and-dumps flagged 60 min in advance, together with a random forest model with data segmented into 30-s chunks and regressors computed with a moving window of 1 h. Our analysis revealed that a better balance between sensitivity and specificity could be achieved by simply selecting an appropriate probability threshold, such as setting the threshold close to the observed prevalence in the original dataset. Resampling methods were useful in some cases, but threshold-independent measures were not affected. Moreover, detecting pump-and-dumps in real-time involves high-dimensional data, and the use of resampling methods to build synthetic datasets can be time-consuming, making them less practical.
    Keywords: pump-and-dump; crypto-assets; minority class; class imbalance; machine learning; random forests
    JEL: C14 C25 C35 C38 C51 C53 C58 G17 G32 K42
    Date: 2023
  21. By: Eric A. Hanushek (Hoover Institution, Stanford University); Lavinia Kinne (ifo Institute); Sancassani Pietro (ifo Institute); Ludger Woessmann (LMU Munich)
    Abstract: Decisions to invest in human capital depend on people’s time preferences. We show that differences in patience are closely related to substantial subnational differences in educational achievement, leading to new perspectives on longstanding within-country disparities. We use social-media data – Facebook interests – to construct novel regional measures of patience within Italy and the United States. Patience is strongly positively associated with student achievement in both countries, accounting for two-thirds of the achievement variation across Italian regions and one-third across U.S. states. Results also hold for six other countries with more limited regional achievement data.
    Keywords: patience; student achievement; regions; social media;
    JEL: I21 Z10
    Date: 2023–09–18
  22. By: Pawe{\l} Niszczota; Sami Abbas
    Abstract: We assess the ability of GPT -- a large language model -- to serve as a financial robo-advisor for the masses, by using a financial literacy test. Davinci and ChatGPT based on GPT-3.5 score 66% and 65% on the financial literacy test, respectively, compared to a baseline of 33%. However, ChatGPT based on GPT-4 achieves a near-perfect 99% score, pointing to financial literacy becoming an emergent ability of state-of-the-art models. We use the Judge-Advisor System and a savings dilemma to illustrate how researchers might assess advice-utilization from large language models. We also present a number of directions for future research.
    Date: 2023–08
  23. By: Guyllaume Faucher; Stephanie Houle
    Abstract: This paper provides an overview of digitalization and its economic implications. We assess the scope of digitalization in Canada as well as the challenges related to its measurement.
    Keywords: Digitalization; Potential output
    JEL: E01 O33 O51
    Date: 2023–09
  24. By: Arnauld Bessagnet; Joan Crespo; Jerome Vicente
    Abstract: The paper provides a socio-semantic analysis of a scientific field which is of a growing importance to the academic community and policy makers: the field of digital entrepreneurial ecosystems. The purpose is to understand the way in which the ideas, theories and knowledge domains that nourish the field are structured. For this, we propose a methodology that combines the analysis of the structural properties of the co-authorship network with the semantic specificities that shape the sub-communities that interact within the field. The results show that despite the sign of a scientific integration, some key scientific issues on digital entrepreneurial ecosystems remain under-explored. We conclude on the importance of the method to identify knowledge gaps to be filled and better frame private and public incentives for future collaborations.
    Keywords: Digital Entrepreneurial Ecosystems; State-of-the-art review; Socio-semantic networks, scientometrics
    Date: 2023–10
  25. By: Daniel Kirste; Niclas Kannengie{\ss}er; Ricky Lamberty; Ali Sunyaev
    Abstract: The proper design of automated market makers (AMMs) is crucial to enable the continuous trading of assets represented as digital tokens on markets of cryptoeconomic systems. Improperly designed AMMs can make such markets suffer from the thin market problem (TMP), which can cause cryptoeconomic systems to fail their purposes. We developed an AMM taxonomy that showcases AMM design characteristics. Based on the AMM taxonomy, we devised AMM archetypes implementing principal solution approaches for the TMP. The main purpose of this article is to support practitioners and researchers in tackling the TMP through proper AMM designs.
    Date: 2023–09

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