nep-pay New Economics Papers
on Payment Systems and Financial Technology
Issue of 2020‒07‒27
twenty-one papers chosen by

  1. The Promise of Fintech; Financial Inclusion in the Post COVID-19 Era By Ratna Sahay; Ulric Eriksson von Allmen; Amina Lahreche; Purva Khera; Sumiko Ogawa; Majid Bazarbash; Kimberly Beaton
  2. Cash and COVID-19: The impact of the pandemic on demand for and use of cash By Heng Chen; Walter Engert; Kim Huynh; Gradon Nicholls; Mitchell Nicholson; Julia Zhu
  3. Bitcoin Is Not a New Type of Money By Michael Junho Lee; Antoine Martin
  4. The Price of BitCoin: GARCH Evidence from High Frequency Data By d’Artis Kancs; Pavel Ciaian; Miroslava Rajcaniova
  5. Cyber Attacks, Spillovers and Contagion in the Cryptocurrency Markets By Guglielmo Maria Caporale; Woo-Young Kang; Fabio Spagnolo; Nicola Spagnolo
  6. Measuring Digital Development with Online Data: Digital Economies in Eastern Europe and Central Asia By Braesemann, Fabian; Stephany, Fabian
  7. On the diffusion of mobile phone innovations for financial inclusion By Simplice A. Asongu; Nicholas Biekpe; Danny Cassimon
  8. Deviations from Triangular Arbitrage Parity in Foreign Exchange and Bitcoin Markets By Reynolds, Julia; Soegner, Leopold; Wagner, Martin
  9. Big-Data and Service Supply chain management: Challenges and opportunities By Badr Bentalha
  10. Economising on network provision while preserving competition: the challenges of 5G mobile network sharing By Pápai, Zoltán; McLean, Aliz; Csorba, Gergely; Nagy, Péter
  11. The Value of Platform Strategy It's the Ecosystem, Stupid! By Julien Gosse; Charles Hoffreumon; Nicolas van Zeebroeck; Jacques Bughin
  12. Merger Policy in Digital Markets: An Ex-Post Assessment By Argentesi, Elena; Buccirossi, Paolo; Calvano, Emilio; Duso, Tomaso; Marrazzo, Alessia; Nava, Salvatore
  13. COVID-19 and Digital Resilience: Evidence from Uber Eats By Manav Raj; Arun Sundararajan; Calum You
  14. How do machine learning and non-traditional data affect credit scoring? New evidence from a Chinese fintech firm By Gambacorta, Leonardo; Huang, Yiping; Qiu, Han; Wang, Jingyi
  15. Co-construction of innovation processes: What types of innovation networks do exist in digital agriculture ? By Boris Biao; Leila Temri; Nina Lachia
  16. Automation and the Future of Work By Stuart Andreason
  17. The Role of Satisfaction in Mediating the Effect of e-Service Convenience, Security, and Trust on Repurchase Intention in the Marketplace Case study: Shopee Marketplace By Juniwati
  18. Jumpstarting an international currency By Bahaj, Saleem; Reis, Ricardo
  19. Market Power, Competition and Innovation in digital markets: a survey By Calvano, Emilio; Polo, Michele
  20. Successful retailer strategies in price comparison platforms By Hackl, Franz; Hoelzl-Leitner, Michael; Winter-Ebmer, Rudolf; Zulehner, Christine
  21. Stablecoins 2.0: Economic Foundations and Risk-based Models By Ariah Klages-Mundt; Dominik Harz; Lewis Gudgeon; Jun-You Liu; Andreea Minca

  1. By: Ratna Sahay; Ulric Eriksson von Allmen; Amina Lahreche; Purva Khera; Sumiko Ogawa; Majid Bazarbash; Kimberly Beaton
    Abstract: Technology is changing the landscape of the financial sector, increasing access to financial services in profound ways. These changes have been in motion for several years, affecting nearly all countries in the world. During the COVID-19 pandemic, technology has created new opportunities for digital financial services to accelerate and enhance financial inclusion, amid social distancing and containment measures. At the same time, the risks emerging prior to COVID-19, as digital financial services developed, are becoming even more relevant.
    Keywords: Financial inclusion;Technological innovation;Financial services;Financial services industry;Contagious diseases;Financial crises;Financial institutions;Macroprudential policies and financial stability;COVID-19,Pandemic,Fintech,,DPPP,DP,digital infrastructure,traditional financial institution,financial literacy,gender gap,digital literacy
    Date: 2020–07–01
  2. By: Heng Chen; Walter Engert; Kim Huynh; Gradon Nicholls; Mitchell Nicholson; Julia Zhu
    Abstract: Consumer spending declined significantly during the recent COVID-19 pandemic. This negative shock likely reduced spending across all methods of payment (cash, debit, credit, etc.). The mix of payment methods consumers use could also be affected. We study how the pandemic has influenced the demand for and use of cash. We also offer insights into the use of other payment methods, such as debit and credit cards.
    Keywords: Bank notes, Central bank research, Digital currencies and fintech, Econometric and statistical methods
    JEL: C1 C12 C9 E4 O5 O54
    Date: 2020–07
  3. By: Michael Junho Lee; Antoine Martin
    Abstract: Bitcoin, and more generally, cryptocurrencies, are often described as a new type of money. In this post, we argue that this is a misconception. Bitcoin may be money, but it is not a new type of money. To see what is truly new about Bitcoin, it is useful to make a distinction between “money,” the asset that is being exchanged, and the “exchange mechanism,” that is, the method or process through which the asset is transferred. Doing so reveals that monies with properties similar to Bitcoin have existed for centuries. However, the ability to make electronic exchanges without a trusted party—a defining characteristic of Bitcoin—is radically new. Bitcoin is not a new class of money, it is a new type of exchange mechanism, and this type of exchange mechanism can support a variety of forms of money as well as other types of assets.
    Keywords: exchange mechanism; cryptocurrencies; crypto assets; payments; bitcoin; classification; money
    JEL: E42 E5 G21
    Date: 2020–06–18
  4. By: d’Artis Kancs (European Commission - JRC); Pavel Ciaian (European Commission - JRC); Miroslava Rajcaniova (SAU, Department of Economic Policy)
    Abstract: This is the first paper that estimates the price determinants of BitCoin in a Generalised Autoregressive Conditional Heteroscedasticity framework using high frequency data. Derived from a theoretical model, we estimate BitCoin transaction demand and speculative demand equations in a GARCH framework using hourly data for the period 2013-2018. In line with the theoretical model, our empirical results confirm that both the BitCoin transaction demand and speculative demand have a statistically significant impact on the BitCoin price formation. The BitCoin price responds negatively to the BitCoin velocity, whereas positive shocks to the BitCoin stock, interest rate and the size of the BitCoin economy exercise an upward pressure on the BitCoin price.
    Keywords: Virtual currencies; BitCoin returns; volatility; price formation; GARCH; Digital Economy
    JEL: E31 E42 G12
    Date: 2019–02
  5. By: Guglielmo Maria Caporale; Woo-Young Kang; Fabio Spagnolo; Nicola Spagnolo
    Abstract: This paper examines mean and volatility spillovers between three major cryptocurrencies (Bitcoin, Litecoin and Ethereum) and the role played by cyber attacks. Specifically, trivariate GARCH-BEKK models are estimated which include suitably defined dummies corresponding to different types, targets and number per day of cyber attacks. Significant dynamic linkages (interdependence) among the three cryptocurrencies under investigation are found in most cases when cyber attacks are taken into account, Bitcoin appearing to be the dominant one. Further, Wald tests for parameter shifts during episodes of turbulence resulting from cyber attacks provide evidence that the latter affect the transmission mechanism between cryptocurrency returns and volatilities (contagion). More precisely, cyber attacks appear to strengthen cross-market linkages, thereby reducing portfolio diversification opportunities for cryptocurrency investors. Finally, the conditional correlation analysis confirms the previous findings.
    Keywords: mean and volatility spillovers, contagion, cryptocurrencies, cyber attacks
    JEL: C32 F30 G15
    Date: 2020
  6. By: Braesemann, Fabian; Stephany, Fabian
    Abstract: The Internet, like railways and roads in the past, is paving innovation and alters the way in which citizens, consumers, businesses, and governments function and interact with each other. This digital revolution is empowering societies. It opens new, effective, and scalable services for governments and the private sector. It provides us with a more adaptive, data-driven approach to decision making in many aspects of our life. The digitalisation is particularly relevant for developing countries, as they can seize the opportunity for leapfrogging in order to become part of the global digitalised economy. With the example of Eastern Europe and Central Asia, this work illustrates how openly available online data can be used to identify, monitor, and visualise trends in digital economic development. Our interactive online dashboard allows researchers, policy-makers, and the public to explore four aspects of digital development: E-services, online labour markets, online knowledge creation and access to online knowledge.
    Date: 2020–06–27
  7. By: Simplice A. Asongu (Yaounde, Cameroon); Nicholas Biekpe (Cape Town, South Africa); Danny Cassimon (University of Antwerp, Belgium)
    Abstract: “Replications are an important part of the research process because they allow for greater confidence in the findings” (McEwan, Carpenter & Westerman, 2018, p. 235). This study extends Lashitew, van Tulder and Liasse (2019, RP) by addressing the concern of multicollinearity that affects the signs and significance of estimated coefficients. This article investigates nexuses between innovations in mobile money and financial inclusion in developing countries. Demand and supply factors that affect the diffusion of mobile services as well as macro-level institutional and economic factors are taken on board. The empirical evidence is based on Tobit regressions. The study finds that when the empirical analysis is robust to multicollinearity, two main tendencies are apparent: the significant findings of Lashitew et al. (2019) are confirmed and many new significant estimated coefficients emerge. While this study confirms the findings of the underlying research, it also goes further to improve the harmony in narratives between the predictors and the outcome variables. Accordingly, by accounting for multicollinearity, the earlier findings are now more consistent across the set of predictors (i.e. demand and supply factors) and the attendant financial inclusion outcomes (i.e. mobile money accounts, mobile used to send money and mobile used to receive money).
    Keywords: Mobile money; technology diffusion; financial inclusion; inclusive innovation
    JEL: D10 D14 D31 D60 O30
    Date: 2020–03
  8. By: Reynolds, Julia (Institute of Finance, Universita della Svizzera Italiana, Lugano); Soegner, Leopold (Department of Economics and Finance, Institute for Advanced Studies, Vienna, Austria, Vienna Graduate School of Finance and NYU Abu Dhabi); Wagner, Martin (Department of Economics, University of Klagenfurt, Bank of Slovenia, Ljubljana and Institute for Advanced Studies, Vienna, Austria)
    Abstract: This paper applies recently developed procedures to monitor and date so-called “financial market dislocations”, defined as periods in which substantial deviations from arbitrage parities take place. In particular, we focus on deviations from the triangular arbitrage parity for exchange rate triplets from a cointegration perspective. Due to increasing attention on and importance of mispricing in the market for cryptocurrencies, we include the cryptocurrency Bitcoin in addition to fiat currencies. We do not find evidence for substantial deviations from the triangular arbitrage parity when only traditional fiat currencies are concerned, but document significant deviations from triangular arbitrage parities in the newer markets for Bitcoin. We confirm the importance of our results for portfolio strategies by showing that a currency portfolio that trades based on our detected break-points outperforms a simple buy-and-hold strategy.
    Keywords: Triangular Arbitrage Parity, Foreign Exchange Markets, Cryptocurrencies, Cointegration, Monitoring
    JEL: G12 G15 C22 C32
    Date: 2020–07
  9. By: Badr Bentalha (USMBA - Université Sidi Mohamed Ben Abdellah)
    Abstract: The Big-Data describes the large volume of data used by economic actors. The data is analysed quickly to formulate instant analysis and data storage. This system is useful for several economic fields such as logistics and supply chain management (SCM). The latter is a management of physical and information flows, from customer to customer and from supplier to supplier, in order to offer a satisfactory response to customer needs. SCM was born and flourished in an industrial context. Nevertheless, several cur of Big-Data help improve the performance of supply chain management in service companies? To answer this question, we will define the concepts of SCM in services, focusing on the concept of Big-Data while analyzing the impact of Big-Data on the efficiency of SCM in service companies.
    Abstract: Le Big-Data décrit le grand volume de données utilisées par les acteurs de la vie économiques. Les données sont analysées rapidement de façon à formuler des analyses instantanées et un stockage de données. Ce système est utile po plusieurs domaines économiques comme la logistique et le supply chain management (SCM). Ce dernier est une gestion des flux physiques et d'informations, du client au client et du fournisseur au fournisseur, afin d'offrir une réponse satisfaisan aux besoins des clients. Le SCM a vu le jour et s'est épanoui dans un contexte industriel. Néanmoins, plusieurs recherches actuelles traitent le SCM dans le domaine de services. Ainsi, comment le recours au Big la performance du supply chain management des entreprises de services allons cerner les concepts de SCM dans les services, en nous focalisant sur les spécificités du management du Service Supply Chain Management (SSCM), et le concept de Big entreprises de services.
    Keywords: Service Supply Chain,SCM,Service Logistics,Big-Data,Supply chain,Digital Supply Chain,Entreprises de Services,Logistique de services
    Date: 2020
  10. By: Pápai, Zoltán; McLean, Aliz; Csorba, Gergely; Nagy, Péter
    Abstract: The aim of the paper is to discuss the challenges in the competition assessment of 5G mobile network sharing which emerge in addition to those which were relevant under 4G networks (or below). Chapter 2 of the paper briefly discusses the main types of mobile network sharing. Chapter 3 presents our analytical framework for the competition assessment of mobile network sharing agreements, built on the approach laid out in guidelines by the European Commission and European regulators, as well as competition cases in European jurisdictions. Throughout, we focus on radio access network (RAN) sharing. Chapter 4 brings 5G into the picture. Here we discuss five special 5G technology and service characteristics which pose new challenges to the competition assessment of 5G RAN sharing agreements and should be in the focus of future research.
    Keywords: mobile markets,network sharing,competition,competitive assessment,5G
    Date: 2019
  11. By: Julien Gosse; Charles Hoffreumon; Nicolas van Zeebroeck; Jacques Bughin
    Abstract: Despite an abundant literature on platforms, there have been surprisingly few quantitative studies on their adoption by established firms and their impact on performance. The unspoken assumption is that platforms increase companies’ performance. This paper uses a global, cross-industry, sample of over 1300 firms to show that, while it seems adopting platform strategies is positively associated with firm performance, the effect is confounded by (1) the digital maturity of firms and (2) their ecosystem strategy. Our results refine our understanding of platform strategy’s value by uncovering the importance of shifting to ecosystem approaches involving value co-creation. They suggest that success is not about the adoption of any platform technology, but rather about seizing integration opportunities brought by its underlying ecosystem
    Keywords: Ecosystem, platform, strategy, partnership, value co-creation
    Date: 2020–03
  12. By: Argentesi, Elena; Buccirossi, Paolo; Calvano, Emilio; Duso, Tomaso; Marrazzo, Alessia; Nava, Salvatore
    Abstract: This paper presents a broad retrospective evaluation of mergers and merger decisions in the digital sector. We first discuss the most crucial features of digital markets such as network effects, multi-sidedness, big data, and rapid innovation that create important challenges for competition policy. We show that these features have been key determinants of the theories of harm in major merger cases in the past few years. We then analyse the characteristics of almost 300 acquisitions carried out by three major digital companies Amazon, Facebook, and Google between 2008 and 2018. We cluster target companies on their area of economic activity and show that they span a wide range of economic sectors. In most cases, their products and services appear to be complementary to those supplied by the acquirers. Moreover, target companies seem to be particularly young, being four-years-old or younger in nearly 60% of cases at the time of the acquisition. Finally, we examine two important merger cases, Facebook/Instagram and Google/Waze, providing a systematic assessment of the theories of harm considered by the UK competition authorities as well as evidence on the evolution of the market after the transactions were approved. We discuss whether the CAs performed complete and careful analyses to foresee the competitive consequences of the investigated mergers and whether a more effective merger control regime can be achieved within the current legal framework.
    Keywords: Antitrust; Big Data; Digital Markets; Ex-post; mergers; network effects; platforms
    JEL: K21 L4
    Date: 2019–12
  13. By: Manav Raj; Arun Sundararajan; Calum You
    Abstract: We analyze how digital platforms can increase the survival rate of firms during a crisis by providing continuity in access to customers. Using order-level data from Uber Technologies, we study how the COVID-19 pandemic and the ensuing shutdown of businesses in the United States affected independent, small business restaurant supply and demand on the Uber Eats platform. We find evidence that small restaurants experience significant increases in total activity, orders per day, and orders per hour following the closure of the dine-in channel, and that these increases may be due to both demand-side and supply-side shocks. We document an increase in the intensity of competitive effects following the shock, showing that growth in the number of providers on a platform induces both market expansion and heightened inter-provider competition. Our findings underscore the critical role that digital will play in creating business resilience in the post-COVID economy, and provide new managerial insight into how supply-side and demand-side factors shape business performance on a platform.
    Date: 2020–06
  14. By: Gambacorta, Leonardo; Huang, Yiping; Qiu, Han; Wang, Jingyi
    Abstract: This paper compares the predictive power of credit scoring models based on machine learning techniques with that of traditional loss and default models. Using proprietary transaction-level data from a leading fintech company in China for the period between May and September 2017, we test the performance of different models to predict losses and defaults both in normal times and when the economy is subject to a shock. In particular, we analyse the case of an (exogenous) change in regulation policy on shadow banking in China that caused lending to decline and credit conditions to deteriorate. We find that the model based on machine learning and non-traditional data is better able to predict losses and defaults than traditional models in the presence of a negative shock to the aggregate credit supply. One possible reason for this is that machine learning can better mine the non-linear relationship between variables in a period of stress. Finally, the comparative advantage of the model that uses the fintech credit scoring technique based on machine learning and big data tends to decline for borrowers with a longer credit history.
    Keywords: credit risk; credit scoring; Fintech; Machine Learning; non-traditional information
    JEL: G17 G18 G23 G32
    Date: 2019–12
  15. By: Boris Biao (UMR MOISA - Marchés, Organisations, Institutions et Stratégies d'Acteurs - Cirad - Centre de Coopération Internationale en Recherche Agronomique pour le Développement - INRA - Institut National de la Recherche Agronomique - CIHEAM-IAMM - Centre International de Hautes Etudes Agronomiques Méditerranéennes - Institut Agronomique Méditerranéen de Montpellier - CIHEAM - Centre International de Hautes Études Agronomiques Méditerranéennes - Montpellier SupAgro - Institut national d’études supérieures agronomiques de Montpellier - Montpellier SupAgro - Centre international d'études supérieures en sciences agronomiques, Montpellier SupAgro - Institut national d’études supérieures agronomiques de Montpellier); Leila Temri (UMR MOISA - Marchés, Organisations, Institutions et Stratégies d'Acteurs - Cirad - Centre de Coopération Internationale en Recherche Agronomique pour le Développement - INRA - Institut National de la Recherche Agronomique - CIHEAM-IAMM - Centre International de Hautes Etudes Agronomiques Méditerranéennes - Institut Agronomique Méditerranéen de Montpellier - CIHEAM - Centre International de Hautes Études Agronomiques Méditerranéennes - Montpellier SupAgro - Institut national d’études supérieures agronomiques de Montpellier - Montpellier SupAgro - Centre international d'études supérieures en sciences agronomiques, Montpellier SupAgro - Institut national d’études supérieures agronomiques de Montpellier); Nina Lachia (Chaire AgroTIC - Montpellier SupAgro - Institut national d’études supérieures agronomiques de Montpellier)
    Keywords: digital innovation,innovation network,stakeholder network,agriculture
    Date: 2019–05–15
  16. By: Stuart Andreason
    Abstract: There are numerous reports that highlight potential effects that new technology will have on the U.S. labor market, and many of them are not exactly what you would expect. For example, with the advent of the internet and ubiquity of spreadsheets in the 1980s, analyst employment soared. The new technology unlocked latent demand for more analysis that had been simply too expensive before the new communication and productivity technologies became common. The need for more analysis led to more analysts…even though there were new technologies that made the work more efficient or productive.
    Keywords: Automation
    JEL: J21
    Date: 2019–03–27
  17. By: Juniwati (Faculty Economic and Business. Universitas Tanjungpura, Pontianak, Indonesia Author-2-Name: Sumiyati Author-2-Workplace-Name: Universitas Muhammadiah Pontianak, Indonesia Author-3-Name: Author-3-Workplace-Name: Author-4-Name: Author-4-Workplace-Name: Author-5-Name: Author-5-Workplace-Name: Author-6-Name: Author-6-Workplace-Name: Author-7-Name: Author-7-Workplace-Name: Author-8-Name: Author-8-Workplace-Name:)
    Abstract: Objective - The development of information technology that encourages the rise of online buying and selling has opened opportunities for market participants. This requires satisfying services for customers by every market participant. Shopee is one of the biggest marketplace actors in Indonesia. The purpose of the study is to estimate the factors that influence consumers' intention to buy back at Shopee's marketplace. Methodology/Technique - The mediation variable used is satisfaction. The research sample consists of 200 respondents, who are Shopee consumers in Pontianak, Indonesia. Findings - The findings of this study are there is a positive and significant effect between E-Service convenience and Satisfaction variables (ß = 0.390) and Repurchase Interest (ß = 0.355), E-Trust variables also have a positive and significant effect on Satisfaction (ß = 0.437) and Interest Repurchase (ß = 0.386). Satisfaction has a positive and significant effect on Repurchase Intention with (ß = 0.483). Type of Paper - Empirical
    Keywords: Satisfaction; e-Service Convenience; Security; Trust; Repurchase Intention.
    JEL: M31 M13 M39
    Date: 2020–06–30
  18. By: Bahaj, Saleem (Bank of England); Reis, Ricardo (London School of Economics)
    Abstract: Monetary and financial policies that lower the cost of credit for working capital in a currency outside of its country can provide the impetus for that currency to be used in international trade. This paper shows this in theory, by exploring the complementarity in the currency used for financing working capital and the currency used for invoicing sales. Financial policies by a central bank can jump-start the use of its currency outside a country’s borders. In the data, the creation of 38 swap lines by the People’s Bank of China between 2009 and 2018 provides a test of the theory. Signing a swap line with a country is significantly associated with increases in the use of the RMB in payments to and from that country in the following months.
    Keywords: Trade credit; RMB internationalisation; swap lines
    JEL: E42 F13 F33
    Date: 2020–06–12
  19. By: Calvano, Emilio; Polo, Michele
    Abstract: This article focuses on the economics of digital markets with particular emphasis on those features that are commonly deemed critical for Antitrust. Digital markets are often concentrated due to network effects and due to the need of large amounts of Data for production. We review papers characterizing the nature of social harms caused by market power and the role of competition FOR the market and IN the market to relief some of that harm. Special emphasis is given to the role of (i) human attention (which is monetized and is a key input in advertising markets), (ii) Data (which is the oil that powers these markets) and (iii) innovation (incentives, entry for buyout and killer acquisitions).
    Keywords: Digital Markets; Economics of attention; Innovation; killer acquisitions; network effects
    JEL: L1 L4
    Date: 2020–01
  20. By: Hackl, Franz; Hoelzl-Leitner, Michael; Winter-Ebmer, Rudolf; Zulehner, Christine
    Abstract: The choice of an appropriate e-commerce strategy for the listing in price comparison platforms (eBay, Amazon, price search engines) is crucial for the survival of online stores in B2C e-commerce business. We use a comprehensive data set from the Austrian price search engine to identify successful e-commerce strategies with regard to these listing decisions. An e-commerce strategy is a set of choices including listing, availability, and decisions on the price path and shipping cost. We apply cluster analysis to identify the different strategies that have been used by online retailers. Using various success measures such as revenue, clicks, market share, and the survival of firms we present causal evidence on the effectiveness of different e-commerce strategies.
    Keywords: business strategies; E-commerce; online trade; Retailing
    JEL: L10 L81
    Date: 2020–01
  21. By: Ariah Klages-Mundt; Dominik Harz; Lewis Gudgeon; Jun-You Liu; Andreea Minca
    Abstract: Stablecoins are one of the most widely capitalized type of cryptocurrency. However, their risks vary significantly according to their design and are often poorly understood. In this paper, we seek to provide a sound foundation for stablecoin theory, with a risk-based functional characterization of the economic structure of stablecoins. First, we match existing economic models to the disparate set of custodial systems. Next, we characterize the unique risks that emerge in non-custodial stablecoins and develop a model framework that unifies existing models from economics and computer science. We further discuss how this modeling framework is applicable to a wide array of cryptoeconomic systems, including cross-chain protocols, collateralized lending, and decentralized exchanges. These unique risks yield unanswered research questions that will form the crux of research in decentralized finance going forward.
    Date: 2020–06

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