nep-pay New Economics Papers
on Payment Systems and Financial Technology
Issue of 2021‒08‒23
nineteen papers chosen by
Bernardo Bátiz-Lazo
Northumbria University

  1. Soft and hard information in equity crowdfunding: network effects in the digitalization of entrepreneurial finance By Khavul, Susanna; Estrin, Saul; Wright, Mike
  2. New and evolving financial technologies implications for monetary policy and financial stability in Latin America By Eswar Prasad
  3. Tilted Platforms: Rental Housing Technology and the Rise of Urban Big Data Oligopolies By Geoff Boeing; Max Besbris; David Wachsmuth; Jake Wegmann
  4. Canadian job postings in digital sectors during COVID-19 By Alejandra Bellatin; Gabriela Galassi
  5. Bitcoin option pricing: A market attention approach By Alvaro Guinea; Alet Roux
  6. Remittances and the Future of African Economies By Ibrahim A. Adekunle; Sheriffdeen A. Tella
  7. Estimating Demand with Multi-Homing in Two-Sided Markets By Pauline Affeldt; Elena Argentesi; Lapo Filistrucchi
  8. Third-Degree Price Discrimination in the Age of Big Data By Charlson, G.
  9. Study on the Usability of Online Test Websites By Chen, Yen Tzu; Liu, Che Hung; Chen, Ho Ming
  10. Bank Seigniorage in a Monetary Production Economy By Biagio Bossone
  11. Comparison of the fin-tech evergreen fund in China and U.S.A By Tong, Antonia
  12. A Few Things You Wanted to Know about the Economics of CBDCs, but were Afraid to Model: a survey of what we can learn from who has done By Marcelo A. T. Aragão
  13. Machine Learning and Mobile Phone Data Can Improve the Targeting of Humanitarian Assistance By Emily Aiken; Suzanne Bellue; Dean Karlan; Christopher R. Udry; Joshua Blumenstock
  14. Household Financial Transaction Data By Scott R. Baker; Lorenz Kueng
  15. The making of data commodities: data analytics as an embedded process By Aaltonen, Aleksi Ville; Alaimo, Cristina; Kallinikos, Jannis
  16. Heterogeneidad en el uso de las fuentes de liquidez intradía en el sistema de pagos de alto valor By Fabio Ortega-Castro; Freddy Cepeda-López; Constanza Martínez-Ventura
  17. Financial dollarization and de-dollarization in the new millennium By Eduardo Levy Yeyati
  18. The concentration of digital markets: How to preserve the conditions for effective and undistorted competition? By Frédéric Marty
  19. Uber and Alcohol-Related Traffic Fatalities By Michael L. Anderson; Lucas W. Davis

  1. By: Khavul, Susanna; Estrin, Saul; Wright, Mike
    Abstract: As a digital financial innovation, equity crowdfunding (ECF) allows investors to exploit the complementarity of information provision and network effects in a reduced transaction cost environment. We build on the underlying distinction between soft and hard information and show that ECF platforms create an environment of greater information pooling that benefits from network externalities. We test our hypotheses using a unique proprietary dataset and find that soft information has a greater impact than hard on the likelihood that a financing pitch will be successful. Moreover, the effects of soft information are amplified by the size of the investor network on the platform and network size also positively moderates the effect of information on the amount invested during each pitch. We conclude that ECF platforms can successfully exploit low transaction costs of the digital environment and bring network externalities to bear on investor decisions. Taken together that these increase the supply of funds to entrepreneurs.
    Keywords: equity crowdfunding; entrepreneurial finance; soft information; network externalities; platforms; e Research Infrastructure and Investment Fund; Centre for Economic Performance; Springer deal
    JEL: G23 J26 M13
    Date: 2021–08–03
  2. By: Eswar Prasad
    Abstract: This paper provides a broad analytical overview of how technological changes are likely to affect the practice of central banking. While the advent of decentralized cryptocurrencies such as Bitcoin has dominated the headlines, a broader set of changes wrought by advances in technology are likely to eventually have a more profound and lasting impact on central banks.
    Date: 2020–05–29
  3. By: Geoff Boeing; Max Besbris; David Wachsmuth; Jake Wegmann
    Abstract: This article interprets emerging scholarship on rental housing platforms -- particularly the most well-known and used short- and long-term rental housing platforms - and considers how the technological processes connecting both short-term and long-term rentals to the platform economy are transforming cities. It discusses potential policy approaches to more equitably distribute benefits and mitigate harms. We argue that information technology is not value-neutral. While rental housing platforms may empower data analysts and certain market participants, the same cannot be said for all users or society at large. First, user-generated online data frequently reproduce the systematic biases found in traditional sources of housing information. Evidence is growing that the information broadcasting potential of rental housing platforms may increase rather than mitigate sociospatial inequality. Second, technology platforms curate and shape information according to their creators' own financial and political interests. The question of which data -- and people -- are hidden or marginalized on these platforms is just as important as the question of which data are available. Finally, important differences in benefits and drawbacks exist between short-term and long-term rental housing platforms, but are underexplored in the literature: this article unpacks these differences and proposes policy recommendations.
    Date: 2021–08
  4. By: Alejandra Bellatin; Gabriela Galassi
    Keywords: Digital technologies have helped maintain economic activity while allowing people to remain physically distant throughout the COVID-19 crisis. This note shows that the number of online postings for jobs related to the production of digital technologies in Canada decreased less than the number for other jobs and recovered more quickly after lockdowns were lifted.
    JEL: E24 J2 J23 J63 J64
    Date: 2021–08
  5. By: Alvaro Guinea; Alet Roux
    Abstract: A model is proposed that models Bitcoin prices by taking into account market attention. Assuming that market attention follows a mean-reverting Cox-Ingersoll-Ross process and allowing it to influence Bitcoin returns (after some delay) leads to a tractable affine model with semi-closed formulae for European put and call prices. A maximum likelihood estimation procedure is proposed for this model. The accuracy of its call and put prices outperforms a number of standard models when tested on real data.
    Date: 2021–07
  6. By: Ibrahim A. Adekunle (Babcock University, Nigeria); Sheriffdeen A. Tella (Olabisi Onabanjo University, Ago-Iwoye, Nigeria)
    Abstract: African nations have in time, passed over-relied on remittances inflow to augment domestic finances needed for growth. Despite the volume and magnitude of remittances that have to serve as an alternative source of investment financing, African remains mostly underdeveloped. The altruistic motives of sending remittances to Africa are likely to fade with time. In this study, we argued that the altruistic connection that has been the bedrock of sending money to African countries would eventually fade when the older generation passes away. To lean empirical credence to this assertion, we examine the structural linkages and the channels through which remittances predicts variations in financial developmentas a threshold for gauging the future of African economies. We gathered panel data on indices of remittances and financial development for thirty (30) African countries from 2003 through 2017. We employed the dynamic panel system generalised method of moment (dynamic system GMM) estimation procedure to establish a baseline level relationship between the variables of interest. We adjusted for heterogeneity assumptions inherent in ordinary panel estimation and found a basis for the strict orthogonal relationship among the variables. Findings revealed that a percentage increase in remittances inflow has a short-run, positive relationship with financial development in Africa. The result further revealed that the exchange rate negatively influences financial development in Africa. Based on the findings, it is suggested that, while attracting migrants' transfers which can have significant short-run poverty-alleviating advantages, in the long run, it might be more beneficial for African governments to foster financial sector development using alternative financial development strategies in anticipation of a flow of remittance that will eventually dry up.
    Keywords: Remittance; Financial Development; African Economies; System GMM; Africa
    JEL: F37 G21
    Date: 2021–01
  7. By: Pauline Affeldt; Elena Argentesi; Lapo Filistrucchi
    Abstract: We empirically investigate the relevance of multi-homing in two-sided markets. First, we build a micro-founded structural econometric model that encompasses demand for differentiated products and allows for multi-homing on both sides of the market. We then use an original dataset on the Italian daily newspaper market that includes information on double-homing by readers to estimate readers’ and advertisers’ demand. The results show that an econometric model that does not allow for multi-homing is likely to produce biased estimates of demand on both sides of the market. In particular, on the reader side, accounting for multi-homing helps to recognize complementarity between products; on the advertising side, it allows to measure to what extent advertising demand depends on the shares of exclusive and overlapping readers.
    Keywords: two-sided markets, platforms, multi-homing, media, advertising
    JEL: C51 D43 L13 L82 M37
    Date: 2021
  8. By: Charlson, G.
    Abstract: A platform holds information on the demographics of its users and wants maximise total surplus. The data generates a probability over which of two products a buyer prefers, with different data segmentations being more or less informative. The platform reveals segmentations of the data to two firms, one popular and one niche, preferring to reveal no information than completely revealing the consumer's type for certain. The platform can improve profits by revealing to both firms a segmentation where the niche firm is relatively popular, but still less popular than the other firm, potentially doing even better by revealing information asymmetrically. The platform has an incentive to provide more granular data in markets in which the niche firm is particularly unpopular or in which broad demographic categories are not particularly revelatory of type, suggesting that the profit associated with big data techniques differs depending on market characteristics.
    Keywords: Strategic interaction, network games, interventions, industrial organisation, platforms, hypergraphs
    JEL: D40 L10 L40
    Date: 2021–08–19
  9. By: Chen, Yen Tzu; Liu, Che Hung; Chen, Ho Ming
    Abstract: Online test websites can provide a more convenient and efficient dynamic learning approach and personalized learning services, which is one of the important approaches to digital learning. However, the usability of online test websites affects users’ learning efficacy. This study explored the impact of the usability of online test websites on users, and the results can help website operators seeking to improve the websites’ usability. Based on the relevant literature, this study synthesized three major metrics of the usability of online test websites and summarized typical work priorities of such websites to design usability test items. The study considered one online test website: A Remedial Education Institution for Learners to Take Civil Service Examination. The results show that, with respect to usability, the website still has quite a few deficiencies that affect users’ effectiveness and efficiency when using the website and cause users to be less satisfied with the website. Based on these results, this study offered four specific recommendations for improving effectiveness, efficiency, and satisfaction in terms of the usability of the online test website: enhancing interaction and instructions, following the inertia of interface use, simplifying information organization, and diversifying information content.
    Date: 2021–08–05
  10. By: Biagio Bossone
    Abstract: This article speaks to post-Keynesian economists and their fundamental vision of monetary production economies. It focuses on the role of commercial banks as creators of money in monetary production economies and studies the rent-extraction power of banks in the form of "seigniorage." The article examines how the relative size of banks in the payment system combines with their capacity to determine quantities and prices in the market for demand deposits and gives them the power to extract seigniorage from the economy; it clarifies the distinction between seigniorage originating from commercial bank money creation and profits derived from pure financial intermediation; and analyzes how seigniorage affects the economy’s price level and resource distribution. The article draws political-economy and economic-policy implications.
    Keywords: Commercial banks; Interest rate; Money creation; Prices; Resource distribution; Seigniorage
    JEL: E19 E20 E31 E40 E52 E58 E62 G21
    Date: 2021–08
  11. By: Tong, Antonia
    Abstract: Compared to a Chinese investor, the U.S. investors invest in Fin-Tech evergreen fund is not a strange financial activity. In the fast-developing of different technology nowadays, the US. Fin-Tech evergreen investors are always attempting to catch the wave of the opportunity to invest in new financial technology companies that will almost like investing in Apple, Microsoft, SpaceX, or Teslar twenty years ago. This article intends to introduce, compare, and analyst the fin-tech evergreen development in both the USA and China. Fin-Tech Evergreen financing is a concept used to describe the gradual infusion of funds into a fin-tech company. It is feasible to organize for the receipt of venture capital money in advance. Nevertheless, with FinTech's evergreen investment, investors provide cash in incremental payments throughout the company's or product's development phase. It is a perpetual fund architecture with no set end date. It frequently provides investors with the ability to exit their commitment and allows the fund manager to acquire additional cash. Investors are allowed to reinvest cash generated by realized returns, thus the term "evergreen." With a thorough explanation of the two most powerful economic powers' investment direction of the evergreen fund, the general public will learn more about the evergreen fund's future and destiny.
    Date: 2021–08–13
  12. By: Marcelo A. T. Aragão
    Abstract: To mistarget and to mistime the issuance of a Central Bank Digital Currency (CBDC) can be detrimental to welfare. This holds even for tentative experiments under controlled conditions since this may prompt unintended expectations by economic agents. To counteract the uncertainty that is inherent in any innovation, academics and central bank researchers have been active in developing models of a prospective economy, or at least of prospective markets, where a fiat currency in digital form coexists. Irrespective of whether such a proposal entails a positive or negative stance, we contend that it is possible to infer from this body of work: opportunities, risks, and policy guidelines they imply (or fail to address). This paper, therefore, is a survey of this model development activity that, we aim to show, results in a better understanding of the economic implications of a CBDC. For this purpose, we have selected and reviewed twenty-nine proposals. I have classified them with respect to motivations, preoccupations, and foundations, observing what they conclude regarding the potential for coexistence with private alternatives and for harm to policy mandates. I have identified knowns, i.e., what models imply, and unknowns, i.e., what models omit or oversimplify. I have found that our analysis can give focus to further research that can steer the ongoing legal and technical design efforts.
    Date: 2021–08
  13. By: Emily Aiken; Suzanne Bellue; Dean Karlan; Christopher R. Udry; Joshua Blumenstock
    Abstract: The COVID-19 pandemic has devastated many low- and middle-income countries (LMICs), causing widespread food insecurity and a sharp decline in living standards. In response to this crisis, governments and humanitarian organizations worldwide have mobilized targeted social assistance programs. Targeting is a central challenge in the administration of these programs: given available data, how does one rapidly identify the individuals and families with the greatest need? This challenge is particularly acute in the large number of LMICs that lack recent and comprehensive data on household income and wealth. Here we show that non-traditional “big” data from satellites and mobile phone networks can improve the targeting of anti-poverty programs. Our approach uses traditional survey-based measures of consumption and wealth to train machine learning algorithms that recognize patterns of poverty in non-traditional data; the trained algorithms are then used to prioritize aid to the poorest regions and mobile subscribers. We evaluate this approach by studying Novissi, Togo’s flagship emergency cash transfer program, which used these algorithms to determine eligibility for a rural assistance program that disbursed millions of dollars in COVID-19 relief aid. Our analysis compares outcomes – including exclusion errors, total social welfare, and measures of fairness – under different targeting regimes. Relative to the geographic targeting options considered by the Government of Togo at the time, the machine learning approach reduces errors of exclusion by 4-21%. Relative to methods that require a comprehensive social registry (a hypothetical exercise; no such registry exists in Togo), the machine learning approach increases exclusion errors by 9-35%. These results highlight the potential for new data sources to contribute to humanitarian response efforts, particularly in crisis settings when traditional data are missing or out of date.
    JEL: C55 I32 I38 O12 O38
    Date: 2021–07
  14. By: Scott R. Baker; Lorenz Kueng
    Abstract: The growth of the availability and use of detailed household financial transaction microdata has dramatically expanded the ability of researchers to understand both household decision-making as well as aggregate fluctuations across a wide range of fields. This class of transaction data is derived from a myriad of sources including financial institutions, FinTech apps, and payment intermediaries. We review how these detailed data have been utilized in finance and economics research and the benefits they enable beyond more traditional measures of income, spending, and wealth. We discuss the future potential for this flexible class of data in firm-focused research, real-time policy analysis, and macro statistics.
    JEL: C81 D14 G5 H31
    Date: 2021–07
  15. By: Aaltonen, Aleksi Ville; Alaimo, Cristina; Kallinikos, Jannis
    Abstract: This paper studies the process by which data are generated, managed, and assembled into tradable objects we call data commodities. We link the making of such objects to the open and editable nature of digital data and to the emerging big data industry in which they are diffused items of exchange, repurposing, and aggregation. We empirically investigate the making of data commodities in the context of an innovative telecommunications operator, analyzing its efforts to produce advertising audiences by repurposing data from the network infrastructure. The analysis unpacks the processes by which data are repurposed and aggregated into novel data-based objects that acquire organizational and industry relevance through carefully maintained metrics and practices of data management and interpretation. Building from our findings, we develop a process theory that explains the transformations data undergo on their way to becoming commodities and shows how these transformations are related to organizational practices and to the editable, portable, and recontextualizable attributes of data. The theory complements the standard picture of data encountered in data science and analytics and renews and extends the promise of a constructivist IS research into the age of datafication. The results provide practitioners, regulators included, vital insights concerning data management practices that produce commodities from data.
    Keywords: advertising audience; analytics; big data; case study; data commodities; data-based objects; social practices; Taylor & Francis deal
    JEL: J50
    Date: 2021–08–06
  16. By: Fabio Ortega-Castro; Freddy Cepeda-López; Constanza Martínez-Ventura
    Abstract: En este documento se estudian las fuentes de liquidez que usan las entidades financieras que participan en el sistema de pagos de alto valor para cumplir con sus obligaciones diarias. Para este propósito, diseñamos e implementamos un algoritmo que descompone la unidad de caja de estas entidades en diferentes conceptos de fuente de liquidez, mediante reglas asociadas a los conceptos de pagos recibidos (fuentes) y enviados (usos). Los valores asignados por el algoritmo evidencian que a nivel agregado las fuentes preferidas son el ahorro de liquidez, la dinámica y los saldos overnight. A nivel de entidad, se observan diferencias en las preferencias que se pueden atribuir al tipo de negocio que realizan, a la disponibilidad (regulación y condiciones macroeconómicas) y a los costos de las fuentes. **** ABSTRACT: This document studies the sources of liquidity used by financial entities that participate in the large-value payment system to meet their daily obligations. For this purpose, we design and implement an algorithm that breaks down the cash unit of these entities into different concepts of liquidity source, through rules associated with the concepts of payments received (sources) and sent (uses). The values assigned by the algorithm show that at the aggregate level the preferred sources are liquidity savings, dynamics, and overnight balances. At the entity level, there are differences in preferences that can be attributed to the type of business they carry out, the availability (regulation and macroeconomic conditions) and the costs of the sources.
    Keywords: Fuentes de liquidez, usos de liquidez, liquidez intradía, sistema de pagos de alto valor, sources of liquidity, uses of liquidity, intraday liquidity, large-value payment system
    JEL: E42 E58 E70
    Date: 2021–08
  17. By: Eduardo Levy Yeyati
    Abstract: Dollarization, in its many variants, is crucial to understanding Latin American macroeconomics, as well as that of many developing countries. This paper builds a new updated dataset on dollarization, reviews its evolution in Latin America since 2000, and summarizes the lessons learned from several de-dollarizing attempts in the region, based on a three-way taxonomy: 1) attempts that focus on the macroeconomic drivers, 2) microeconomic measures that deter investors from dollarizing their financial assets and liabilities based on market incentives or regulatory limits, and 3) regulations that affect the choice of foreign currency as a means of payment or a unit of account. The study provides examples using seven cases that may be considered paradigmatic of the different dollarization varieties: Bolivia, Peru, Uruguay, Costa Rica, El Salvador, Ecuador and Venezuela.
    Date: 2021–01–29
  18. By: Frédéric Marty
    Abstract: The policy initiatives announced on both sides of the Atlantic to complement competition rules focus on two key dimensions: the contestability of markets on the one hand and fairness in their functioning on the other. The underlying idea is that the market positions of Big Tech would be inexpugnable - insofar as high barriers to entry protect them from self-regulating competition and insofar as they would have regulatory power over their respective ecosystems. Competition for the market would no longer be free, and competition in the market would be distorted. Our purpose in this working paper is to discuss these two dimensions. Are digital markets still contestable, and is the competition in them still competition on the merits? Finally, we discuss the remedies proposed to address these two alleged phenomena. La concentration des marchés numériques : Comment préserver les conditions d'une concurrence effective pour le marché et d'une concurrence non faussée dans le marché ? Les initiatives politiques annoncées de part et d’autre de l’Atlantique pour compléter les règles de concurrence mettent l’accent sur deux dimensions essentielles : la contestabilité des marchés d’une part et la loyauté dans le fonctionnement dans leur fonctionnement d’autre part. L’idée sous-jacente est la suivante : les positions de marché des grandes entreprises du numérique seraient inexpugnables – dans la mesure où de fortes barrières à l’entrée les protègent d’un caractère auto-régulateur de la concurrence et dans la mesure où elles jouiraient d’un pouvoir de régulation sur leurs écosystèmes respectifs. La concurrence pour le marché ne serait plus libre et la concurrence dans le marché serait faussée. Notre propos dans ce document de travail est de discuter ces deux dimensions. Les marchés numériques sont-ils toujours contestables et la concurrence qui s’y exerce est-elle encore une concurrence par les mérites ? Nous discutons enfin les remèdes proposés pour répondre à ces deux phénomènes allégués.
    Keywords: contestability,fairness,loyalty,Big Tech,concentration,exclusionary abuses, contestabilité,loyauté de la concurrence,équité,Big Tech,concentration,abus d’éviction
    JEL: K21 L41
    Date: 2021–08–17
  19. By: Michael L. Anderson; Lucas W. Davis
    Abstract: Previous studies of the effect of ridesharing on traffic fatalities have yielded inconsistent, often contradictory conclusions. In this paper we revisit this question using proprietary data from Uber measuring monthly rideshare activity at the Census tract level. Most previous studies are based on publicly-available information about Uber entry dates into US cities, but we show that an indicator variable for whether Uber is available is a poor measure of rideshare activity — for example, it explains less than 3% of the tract-level variation in ridesharing, reflecting the enormous amount of variation both within and across cities. Using entry we find inconsistent and statistically insignificant estimates. However, when we use the more detailed proprietary data, we find a robust negative impact of ridesharing on traffic fatalities. Impacts concentrate during nights and weekends and are robust across a range of alternative specifications. Overall, our results imply that ridesharing has decreased US alcohol-related traffic fatalities by 6.1% and reduced total US traffic fatalities by 4.0%. Based on conventional estimates of the value of statistical life the annual life-saving benefits range from $2.3 to $5.4 billion. Back-of-the-envelope calculations suggest that these benefits may be of similar magnitude to producer surplus captured by Uber shareholders or consumer surplus captured by Uber riders.
    JEL: I12 I18 R41 R49
    Date: 2021–07

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