nep-pay New Economics Papers
on Payment Systems and Financial Technology
Issue of 2020‒04‒06
forty-five papers chosen by

  1. FinTech credit: a critical review of empirical research By Nicola Branzoli; Ilaria Supino
  2. Shadow Digital Money By McAndrews, James; Menand, lev
  3. Digital data and management accounting: why we need to rethink research methods By Bhimani, Alnoor
  4. Digital Trade in MENA : Regulatory Readiness Assessment By Daza Jaller,Lillyana Sophia; Molinuevo,Martin
  5. The Impact of Plastic Money Use on VAT Compliance: Evidence from EU Countries By Amakoe D. Alognon; Antonios M. Koumpias; Jorge Martinez-Vazquez
  6. Adoption and use of mobile banking by low-income individuals in Senegal By François-Seck Fall; Luis Orozco; Al‐mouksit Akim
  7. Finanzwirtschaftliche Anwendungen der Blockchain-Technologie By Schuster, Philipp; Theissen, Erik; Uhrig-Homburg, Marliese
  8. Mechanism Design with Blockchain Enforcement By Hitoshi Matsushima; Shunya Noda
  9. Female Small Business Owners in China: discouraged, not discriminated By Mustafa Caglayan; Oleksandr Talavera; Lin Xiong
  10. The Value of Platform Strategy. It's the Ecosystem. Stupid! By Julien Gosse; Charles Hoffreumon; Nicolas van Zeebroeck; Jacques Bughin
  11. Global Software Piracy, Technology and Property Rights Institutions By Simplice A. Asongu
  12. Financial literacy and self-control in FinTech: Evidence from a field experiment on online consumer borrowing By Bu, Di; Hanspal, Tobin; Liao, Yin; Liu, Yong
  14. Microfinance and intermediation scale: is still a childhood industry ? By Célestin Mayoukou
  15. Taxation and Global Spillovers in the Digital Advertising Market. Theory and Evidence from Facebook By Andrea Lassmann; Federica Liberini; Antonio Russo; Ángel Cuevas; Rubén Cuevas
  16. Cryptocurrency Trading: A Comprehensive Survey By Fan Fang; Carmine Ventre; Michail Basios; Hoiliong Kong; Leslie Kanthan; Lingbo Li; David Martinez-Regoband; Fan Wu
  17. An Industry-Based Estimation Approach for Measuring the Cloud Economy By Christopher Hooton
  18. Using Mobile Phone Data to Reduce Spread of Disease By Milusheva,Sveta
  19. Social Media and Inclusive Human Development in Africa By Simplice A. Asongu; Nicholas M. Odhiambo
  20. Stablecoins as a crypto safe haven? Not all of them! By Baumöhl, Eduard; Vyrost, Tomas
  21. The Double Fence: Overlapping Institutions and Deforestation in the Colombian Amazon By Camilo De Los Rios Rueda
  22. Tail Risk Measurement In Crypto-Asset Markets By Daniel Felix Ahelegbey; Paolo Giudici; Fatemeh Mojtahedi
  23. Simple Rules for a Complex World with Arti?cial Intelligence By Jesus Fernandez-Villaverde
  24. NetDP: An Industrial-Scale Distributed Network Representation Framework for Default Prediction in Ant Credit Pay By Jianbin Lin; Zhiqiang Zhang; Jun Zhou; Xiaolong Li; Jingli Fang; Yanming Fang; Quan Yu; Yuan Qi
  25. "Mechanism Design with Blockchain Enforcement" By Kohei Maehashi; Mototsugu Shintani
  26. Investigating the Influence of Dockless Electric Bike-share on Travel Behavior, Attitudes, Health, and Equity By Fitch, Dillon PhD; Mohiuddin, Hossain; Handy, Susan PhD
  27. Quality checks on granular banking data: an experimental approach based on machine learning? By Fabio Zambuto; Maria Rosaria Buzzi; Giuseppe Costanzo; Marco Di Lucido; Barbara La Ganga; Pasquale Maddaloni; Fabio Papale; Emiliano Svezia
  28. THE EVOLUTION OF AIRBNB REGULATION - An International Longitudinal Investigation 2008-2020 By von Briel, Dorine; Dolnicar, Sara
  29. Payment and policy consequentiality in dichotomous choice contingent valuation: Experimental design effects on self-reported perceptions By Tobias Börger; Tenaw G. Abate; Margrethe Aanesen; Ewa Zawojska
  30. How special rewards in loyalty programs enrich consumer–brand relationships: The role of self‐expansion By Tiphaine Gorlier; Géraldine Michel
  31. Perceived Precautionary Savings Motives: Evidence from FinTech By Francesco D’Acunto; Thomas Rauter; Christoph K. Scheuch; Michael Weber
  32. Risk Spillover between Bitcoin and Conventional Financial Markets: An Expectile-Based Approach By Yue-Jun Zhang; Elie Bouri; Rangan Gupta
  33. Enacting Environments: An Ethnography of the Digitalisation and Naturalisation of Emissions By Lippert, Ingmar
  34. Determinants of Interest Rates in the P2P Consumer Lending Market: How Rational are Investors? By Andreas Dietrich; Reto Wernli
  35. Deconstructing Voice-over-IP By Safaningrum, Anggi Cecilia; Ling, Cathryn Li Yuan; Min, Venice
  36. Internet Job Search, Employment, and Wage Growth : Evidence from the Arab Republic of Egypt By El-Mallakh,Nelly
  37. Research Notes: Data Structures for Social Media Machine Learning — The Tweet Term Matrix (TTM) and Tweet Bio-Term Matrix (TBTM) By Flor, Nick V.
  38. Centralized vs decentralized markets in the laboratory: The role of connectivity By Alfarano, Simone; Banal-Estanol, Albert; Camacho-Cuena, Eva; Iori, Giulia; Kapar, Burcu
  39. Automation, stagnation, and the implications of a robot tax By Gasteiger, Emanuel; Prettner, Klaus
  40. Time-varying volatility in Bitcoin market and information flow at minute-level frequency By Irena Barja\v{s}i\'c; Nino Antulov-Fantulin
  41. Does a Local Bias Exist in Equity Crowdfunding? By Lars Hornuf; Matthias Schmitt; Eliza Stenzhorn
  42. Does online fundraising increase charitable giving? A nation-wide field experiment on Facebook By Adena, Maja; Hager, Anselm
  43. Editorial to the special issue: The monetary economics of Basil J. Moore By Mark Setterfield
  44. The Global Financial Cycle and US Monetary Policy in an Interconnected World By Stéphane Dées; Alessandro Galesi
  45. On-Site Inspecting Zombie Lending By Diana Bonfim; Geraldo Cerqueiro; Hans Degryse; Steven Ongena

  1. By: Nicola Branzoli (Bank of Italy); Ilaria Supino (Bank of Italy)
    Abstract: FinTech credit has attracted significant attention from academics and policymakers in recent years. Given its growing importance, in this paper we provide an overview of the empirical research on FinTech credit to households and non-financial corporations (NFCs). We focus on three broad topics: i) the factors supporting the development of innovative business models for credit intermediation, such as marketplace lending; ii) the benefits of new credit risk assessment data and methods; iii) the implications of these innovations for access to credit. Three main messages emerge from the literature. First, the growth of lenders with innovative business models is mainly driven by the degree of local economic development and of competition in the banking sector. Second, new data and methods can improve traditional credit risk models because they are particularly helpful in screening opaque borrowers, such as those with scant credit history. Third, FinTech borrowers generally lack (or have limited) access to finance and tend to be riskier than traditional bank borrowers.
    Keywords: artificial intelligence, credit, digital technologies, FinTech, marketplace lending
    JEL: G21 G22 G23 G24
    Date: 2020–03
  2. By: McAndrews, James; Menand, lev
    Abstract: Promises by media platforms to provide digital transaction services will likely lead to a flood of new money. While these developments are potentially valuable, under current law the money created is unsound. It is not insured by the government, nor is it backed by safe assets. We should not yoke good technology to unsound money. Federal regulation is needed to guarantee safety and soundness, to restore monetary control to the Federal Reserve, and to prevent a race to the bottom between competing state regulatory regimes. With modest changes to the U.S. Code, innovation in payments will be just that—innovation in payments—and not also unsupervised and unsound money issuance.
    Keywords: payments, digital money, regulation, fintech
    JEL: G1 L0
    Date: 2020–03
  3. By: Bhimani, Alnoor
    Abstract: Digitalisation is having profound effects on how enterprises function. Its impact on accounting research is growing as the rise of the internet, mobile technologies and digital economy tools generate depth, breadth and variety of data that far exceed what researchers have had access to in the past. But whilst social scientists interested in organisational issues are starting to question conventional methodological approaches to the study of contexts where digital data forms are drawn upon, little such concern has been voiced in the management accounting literature. This paper seeks to explore the continued applicability of conventional methodological thinking when carrying out investigations within digital data environments to inform management accounting studies. It considers why digitalisation impacts methodological precepts, identifies how descriptive and explanatory modes of questioning which management accountants have conventionally opted for need rethinking, discusses ways in which digital data characteristics alter what can be drawn from empirical studies, and points to the potential offered within digitalised settings for methodological advance. It concludes by highlighting the necessity, where digitalisation exists, to question modes of posing questions and to reconsider the applicability of methodological precepts deployed by management accounting researchers to date.
    Keywords: Digitalisation; methodology; empiricism; datafication
    JEL: M40
    Date: 2020–02–14
  4. By: Daza Jaller,Lillyana Sophia; Molinuevo,Martin
    Abstract: A strong regulatory framework can provide essential tools for remote transactions and improve trust in digital trade. Yet, regulations can also introduce restrictions that hamper the conditions for digital markets. Based on a database of 20 Middle East and North Africa countries and 20 comparator countries around the world, this paper shows that the Middle East and North Africa region is falling behind in establishing a modern governance framework for the digital economy. The analysis focuses on a set of regulatory areas, including electronic documentation and signature, online consumer protection, data governance, cybersecurity, and intermediary liability regulations. It assesses each country's domestic regulatory framework in light of recent international trends and regulatory models. The study shows that regulation of digital markets in countries in the region is still in its infancy, being mostly governed by general laws that were not originally intended for the digital era. Some countries have tried to support an export-oriented information technology sector by keeping an updated regulatory framework. However, regulation in most countries in the region, regardless of their level of development, still features some major loopholes that can limit consumer trust in digital markets or reduce certainty -- and increase costs -- for digital businesses.
    Date: 2020–03–30
  5. By: Amakoe D. Alognon (International Center for Public Policy, Department of Economics, Andrew Young School of Policy Studies, Georgia State University); Antonios M. Koumpias (Department of Social Sciences, University of Michigan-Dearborn & Population Studies Center, Institute for Social Research, University of Michigan); Jorge Martinez-Vazquez (International Center for Public Policy, Department of Economics, Andrew Young School of Policy Studies, Georgia State University)
    Abstract: In the recent decades, several countries around the world have implemented cash restriction policies to incentivize the use of electronic means of payments with the aim to combat money laundering, terrorism financing, and tax evasion. This paper examines the impact of the proliferation in credit and debit card usage on consumption tax compliance using annual national level data for 26 European Union (EU) member states from 2000 to 2016. We measure consumption tax compliance using estimated Value-Added Tax (VAT) gaps, defined as the difference between the theoretical VAT liability according to the law and actual VAT collections. We exploit variation in time and space of credit and debit card usage across 26 EU member states from 2000-16 using panel data and instrumental variable techniques. We find that plastic money use significantly reduces tax evasion while cash withdrawals appear to noticeably widen the compliance gap. This paper contributes to the literature on the effect of modern means of payment on tax compliance by using a more adequate measure of the VAT compliance gap compared to earlier works and by accounting for potential confounders such as tax policy choices and ex ante enforcement capacity of tax administrations to curb the gap.
    Date: 2020–03
  6. By: François-Seck Fall (LEREPS - Laboratoire d'Etude et de Recherche sur l'Economie, les Politiques et les Systèmes Sociaux - UT1 - Université Toulouse 1 Capitole - UT2J - Université Toulouse - Jean Jaurès - Institut d'Études Politiques [IEP] - Toulouse - ENSFEA - École Nationale Supérieure de Formation de l'Enseignement Agricole de Toulouse-Auzeville); Luis Orozco (LEREPS - Laboratoire d'Etude et de Recherche sur l'Economie, les Politiques et les Systèmes Sociaux - UT1 - Université Toulouse 1 Capitole - UT2J - Université Toulouse - Jean Jaurès - Institut d'Études Politiques [IEP] - Toulouse - ENSFEA - École Nationale Supérieure de Formation de l'Enseignement Agricole de Toulouse-Auzeville); Al‐mouksit Akim (World Bank Group, LEDA-DIAL - Développement, Institutions et Modialisation - LEDa - Laboratoire d'Economie de Dauphine - IRD - Institut de Recherche pour le Développement - Université Paris Dauphine-PSL - CNRS - Centre National de la Recherche Scientifique)
    Abstract: The wide use of mobile phones is increasing low-income individuals' access to a large range of services. One of these services is mobile banking (m-banking). Today, m-banking represents a key vector of financial inclusion in many countries in Sub-Saharan Africa, especially in Senegal. Based on technology adoption theories applied to households in developing countries, this paper studies the determinants of the adoption and use of m-banking. We distinguish between possession or adoption from actual use of m-banking and examine the interdependence between these two decisions by using a Heckman sample selection model, through a sample of 1052 individuals in the suburbs of Dakar. Our main results are that the two decisions (adoption and use) are not independent from each other. Individual characteristics, such as education, possession of a bank account, and family network effects, are determinants of the adoption, and age, gender, and being a member of a tontine are determinants of the use. A major result of this study concerns women's low propensity to adopt m-banking because of their low levels of education. However, compared with men, when women adopt m-banking, they have a stronger propensity to use it.
    Keywords: Mobile banking,mobile technologies,technology adoption,financial inclusion,individual characteristics,Senegal
    Date: 2020
  7. By: Schuster, Philipp; Theissen, Erik; Uhrig-Homburg, Marliese
    Abstract: Die Blockchain-Technologie wurde 2009 als technologische Basis der Kryptowährung Bitcoin erstmals implementiert. Ihr wird das Potential nachgesagt, eine disruptive Technologie zu sein, die zu nachhaltigen Veränderungen in vielen Bereichen des Wirtschaftslebens führen kann. In diesem Beitrag geben wir einen Überblick über die Technologie selbst sowie ihre finanzwirtschaftlichen Anwendungen. Dabei gehen wir insbesondere auf Kryptowährungen, auf das Potential sogenannter Smart Contracts, auf Initial Coin Offerings, die Abwicklung vonWertpapiergeschäften und mögliche Auswirkungen auf die Corporate Governance börsennotierter Unternehmen ein.
    Keywords: Blockchain,Kryptowährungen,Smart Contracts,Wertpapierabwicklung,Initial Coin Offerings,Corporate Governance
    JEL: G19 G29
    Date: 2020
  8. By: Hitoshi Matsushima; Shunya Noda
    Abstract: We study the design of self-enforcing mechanisms that rely on neither a trusted third party (e.g., court, trusted mechanism designer) nor a long-term relationship. Instead, we use a smart contract written on blockchains as a commitment device. We design the digital court, a smart contract that identifies and punishes agents who reneged on the agreement. The digital court substitutes the role of legal enforcement in the traditional mechanism design paradigm. We show that, any agreement that is implementable with legal enforcement can also be implemented with enforcement by the digital court. To pursue a desirable design of the digital court, we study a way to leverage truthful reports made by a small fraction of behavioral agents. Our digital court has a unique equilibrium as long as there is a positive fraction of behavioral agents, and it gives correct judgment in the equilibrium if honest agents are more likely to exist than dishonest agents. The platform for smart contracts is already ready in 2020; thus, self-enforcing mechanisms proposed in this paper can be used practically, even now. As our digital court can be used for implementing general agreements, it does not leak the detailed information about the agreement even if it is deployed on a public blockchain (e.g., Ethereum) as a smart contract.
    Date: 2020–03
  9. By: Mustafa Caglayan (Heriot-Watt University); Oleksandr Talavera (University of Birmingham); Lin Xiong (Robert Gordon University)
    Abstract: Using a unique small business loan application dataset from a peer-to-peer (P2P) digital loan platform in China, we show that lenders do not discriminate against female business owners. However, female entrepreneurs are more likely to be discouraged from applying for funds after a failed attempt compared to their male counterparts. We also find that borrower discouragement is prominent among those from less developed regions or those who need finance for working capital. Although, digitization of financial markets has made external funding more accessible to small business owners, provision of better information on application process would help those who may be discouraged from posting a new funding application.
    Keywords: Peer-to-peer (P2P) lending; Small business owners, Gender discrimination, Discouraged borrowers, Repeat rejections, Fintech, Digitization, China
    JEL: G14 G32 M10
    Date: 2020–03
  10. 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
  11. By: Simplice A. Asongu (Yaounde, Cameroon)
    Abstract: This study extends the literature on fighting software piracy by investigating how Intellectual Property Rights (IPRs) regimes interact with technology to mitigate software piracy when existing levels of piracy are considered. Two technology metrics (internet penetration rate and number of PC users) and six IPRs mechanisms (constitution, IPR law, main IP laws, WIPO Treaties, bilateral treaties and multilateral treaties) are used in the empirical analysis. The statistical evidence is based on: (i) a panel of 99 countries for the period 1994-2010 and (ii) interactive contemporary and non-contemporary Quantile regressions.The findings show that the relevance of IPR channels in the fight against software piracy is noticeably contingent on the existing levels of technology embodied in the pirated software. There is a twofold policy interest for involving modern estimation techniques such as interactive Quantile regressions. First, it uncovers that the impact of IPR systems on software piracy may differ depending on the nature of technologies used. Second, the success of initiatives to combat software piracy is contingent on existing levels of the piracy problem. Therefore, policies should be designed differently across nations with high-, intermediate- and low-levels of software piracy.
    Keywords: Piracy; Business Software; Software piracy; Intellectual Property Rights
    JEL: F42 K42 O34 O38 O57
    Date: 2020–01
  12. By: Bu, Di; Hanspal, Tobin; Liao, Yin; Liu, Yong
    Abstract: We report the results of a longitudinal intervention with students across five universities in China designed to reduce online consumer debt. Our research design allocates individuals to either a financial literacy treatment, a self-control training program, or a zero-touch control group. Financial education interventions improve test scores on general financial literacy but only marginally affect future online borrowing. Our self-control treatment features detailed tracking of spending and borrowing activity with a third-party app and introspection about individuals' consumption with a counselor. These sessions reduce future online borrowing, delinquency charges, and borrowing for entertainment reasons - and are driven by the male subjects in the sample. Our results suggest that self-regulation can affect financial behavior in e-commerce platforms.
    Keywords: Financial literacy,online borrowing,Consumer credit,Self-control,FinTech,China
    JEL: D14 D18 G23 G21
    Date: 2020
  13. By: W. Gregory Voss (TBS - Toulouse Business School, IRDEIC - Institut de Recherche en Droit Européen, International et Comparé (Toulouse) - UT1 - Université Toulouse 1 Capitole)
    Abstract: Globalization seems to call for the harmonization of laws, especially in sectors affecting global business, and this is all the truer with respect to laws affecting the technology industry, with the facility of its cross-border communications networks. Data privacy law on both sides of the Atlantic benefits from common origins but eventually divergence occurred, causing compliance challenges for companies and the potential halting of cross-border data flows from the European Union to the United States. Harmonization could possibly obviate such difficulties, and there is a window of opportunity to achieve this with discussion in the United States of a potential federal data privacy law. After setting out the historical context, this study posits and details three major obstacles to full-scale transatlantic harmonization of data privacy law, from the perspective of what has become the predominant data privacy model-that of the European Union. These are: laissez-faire policy and neoliberalism in the United States (and resulting focus on self-regulation there), the lobbying power of the U.S. technology industry giants in a conducive U.S. legislative system, and differing constitutional provisions on both sides of the Atlantic.
    Abstract: La mondialisation semble demander l'harmonisation des lois, en particulier dans les secteurs qui touchent les entreprises mondiales, et c'est d'autant plus vrai en ce qui concerne les lois affectant l'industrie de la technologie, avec la facilité de ses réseaux de communication transfrontaliers. La législation sur la protection des données des deux côtés de l'Atlantique bénéficie d'origines communes, mais la divergence s'est finalement produite, ce qui a posé des problèmes de conformité pour les entreprises et l'arrêt potentiel des flux transfrontaliers de données de l'Union européenne vers les États-Unis. L'harmonisation pourrait éventuellement éviter de telles difficultés, et il y a une fenêtre d'opportunité pour y parvenir en discutant aux États-Unis d'une éventuelle loi fédérale sur la protection des données. Après avoir établi le contexte historique, cette étude pose et détaille trois obstacles majeurs à l'harmonisation transatlantique à grande échelle du droit de la protection des données, du point de vue de ce qui est devenu le modèle prédominant de la protection des données, celui de l'Union européenne. Il s'agit de la politique de laissez-faire et du néolibéralisme aux États-Unis (et l'accent mis sur l'autoréglementation qui en résulte), du pouvoir de lobbying des géants de l'industrie technologique des États-Unis dans un système législatif américain favorable et de dispositions constitutionnelles différentes sur des deux côtés de l'Atlantique.
    Keywords: neoliberalism,laissez-faire policy,lobbying,FTC,harmonization of laws,data privacy,GDPR,Data protection,fundamental rights,Droits fondamentaux,Freedom of speech,First amendment,Premier amendement,Néolibéralisme,Laisser-faire,harmonisation des lois,Protection des données personnelles,Liberté d'expression,RGPD
    Date: 2019
  14. By: Célestin Mayoukou (CREAM - Centre de Recherche en Economie Appliquée à la Mondialisation - UNIROUEN - Université de Rouen Normandie - NU - Normandie Université - IRIHS - Institut de Recherche Interdisciplinaire Homme et Société - UNIROUEN - Université de Rouen Normandie - NU - Normandie Université)
    Abstract: L'industrie de la microfinance connait depuis 30 ans une mutation perpétuelle. L'échelle de son intermédiation s'est progressivement élargie. Centrée à ses débuts sur des acteurs du secteur informel ; cette activité touche désormais une large clientèle englobant même des PME exportatrices. Son mode de refinancement s'étend désormais au marché international des capitaux, puisque des Fonds d'investissement et des Banques multinationales alimentent les IMF en capitaux. La digitalisation et les plateformes de crédits en ligne ont aussi fait leur entrée dans la microfinance. Cette industrie n'est plus désormais une industrie dans l'enfance Mots clés : Microfinance, intermédiation, industrie microfinancière. Code JL. G21, G23, F34 Abstract
    Abstract: Microfinance industry is changing progressively during this last thirty years. The depth of is intermediation is growing. Serving at the beginning of the informal customers ; he serves since several years yet, small and medium enterprise (SME). Multinational banks and international funds had also entering the microfinance industry by granting loans to microfinance institutions. The digital innovation had disrupted the sector who become adult. Key Words: Microfinance, intermediation, microfinance industry JL Code. G21, G23, F34.
    Keywords: Microfinance,intermediation,microfinance industry,industrie microfinancière
    Date: 2019–05–09
  15. By: Andrea Lassmann; Federica Liberini; Antonio Russo; Ángel Cuevas; Rubén Cuevas
    Abstract: We study the effects of taxation on the international online advertising market, using data on Facebook ad prices, Facebook users product preferences and international trade. Our data encompass a de facto increase in the platform’s corporate tax rate in several countries. We show that, due to international trade linkages, tax changes produce global spillovers. Yet, advertisers experience higher prices in countries that directly face the tax increases compared to advertisers in countries that do not. This result is consistent with a theoretical model, which shows that the platform reduces the supply of ads to advertisers from countries where taxation increases.
    Keywords: tax incidence, online advertising, Facebook
    JEL: H22 H25 F23
    Date: 2020
  16. By: Fan Fang; Carmine Ventre; Michail Basios; Hoiliong Kong; Leslie Kanthan; Lingbo Li; David Martinez-Regoband; Fan Wu
    Abstract: Since the inception of cryptocurrencies, an increasing number of financial institutions are gettinginvolved in cryptocurrency trading. It is therefore important to summarise existing research papersand results on cryptocurrency trading. This paper provides a comprehensive survey of cryptocurrencytrading research, by covering 118 research papers on various aspects of cryptocurrency trading (e.g.,cryptocurrency trading systems, bubble and extreme condition, prediction of volatility and return,crypto-assets portfolio construction and crypto-assets, technical trading and others). This paper alsoanalyses datasets, research trends and distribution among research objects (contents/properties) andtechnologies, concluding with promising opportunities in cryptocurrency trading
    Date: 2020–03
  17. By: Christopher Hooton
    Abstract: The usage of cloud computing technology in business and daily life has grown rapidly in recent years. However, measurement and research on the impacts of that usage remain relatively scarce and new. The current paper examines the economic contributions of cloud technology by estimating the size of the 'cloud economy' in the United States. The author uses input from cloud industry experts and product line receipt details to identify specific commercial receipts related to the cloud industry. The author then uses an adapted input-output methodology previously employed by other groups examining the size of the technology sector to estimate the economic size of the cloud in terms of Output, Earnings, Employment, Value-Added, Direct-Effect Earnings, and Direct-Effect Employment. The estimates are simply a starting point for measuring the economic size of the cloud, but they compare favorably with other estimates from industry groups and private parties. The key advantage of the current paper is the detailing of a replicable approach to use in future research including a discussion of the identification criteria used by the consulting experts.
    Keywords: Cloud computing, digital economy, national accounts, economic estimates
    JEL: L86 E01 O30
    Date: 2020–02
  18. By: Milusheva,Sveta
    Abstract: While human mobility has important benefits for economic growth, it can generate negative externalities. This paper studies the effect of mobility on the spread of disease in a low-incidence setting when people do not internalize their risks to others. Using malaria as a case study and 15 billion mobile phone records across nine million SIM cards, this paper causally quantifies the relationship between travel and the spread of disease. The estimates indicate that an infected traveler contributes to 1.7 additional cases reported in the health facility at the traveler's destination. This paper develops a simulation-based policy tool that uses mobile phone data to inform strategic targeting of travelers based on their origins and destinations. The simulations suggest that targeting informed by mobile phone data could reduce the caseload by 50 percent more than current strategies that rely only on previous incidence.
    Date: 2020–03–30
  19. By: Simplice A. Asongu (Yaounde, Cameroon); Nicholas M. Odhiambo (Pretoria, South Africa)
    Abstract: This study investigates the relationship between social media and inclusive human development in 49 African countries for the year 2012. Social media is measured with Facebook penetration whereas inclusive human development is proxied by the inequality- adjusted human development index. The empirical evidence is based on Ordinary Least Squares, Tobit and Quantile regressions. Ordinary Least Squares provided baseline results, Tobit regressions account for the limited range in the outcome variable while Quantile regressions are engaged to control for initial levels of inequality-adjusted human development. From Ordinary Least Squares and Tobit results, Facebook penetration is positively associated with inclusive human development. Quantile regressions confirm this positive nexus and further establish that the positive association is slightly higher in magnitude in the above-median sub-sample. From a comparative assessment, it is apparent that with the exception of the resource-wealth sub-samples, higher levels of Facebook penetration are associated with comparatively higher levels of inclusive human development. Accordingly, the positive association between Facebook penetration and inclusive human development is: (i) a positive function of income levels and (ii) more apparent in Middle East and North African countries (compared to Sub-Saharan African countries), English common law countries (compared to their French civil law counterparts), and coastal countries (in relation to landlocked countries).
    Keywords: Social Media; Inclusive development; Income levels; Regions
    JEL: D83 O30 D74 D83
    Date: 2020–01
  20. By: Baumöhl, Eduard; Vyrost, Tomas
    Abstract: We test the safe haven properties of the largest stablecoins (USDT, USDC, TUSD, PAX, DAI, GUSD) against the standard “nonstable” coins (BTC, ETH, XRP, BCH, LTC). Our dataset comprises high-frequency 1-minute data calculated as volume-weighted averages across 18 exchanges where these cryptocurrencies are traded, thus capturing the entire price movement around the world. Using a quantile coherency cross-spectral measure, we find that only TUSD, PAX, and GUSD can serve as safe havens.
    Keywords: cryptocurrencies,stablecoins,quantile dependence,cross-spectral analysis,diversification,safe haven
    JEL: G11 G15 F31
    Date: 2020
  21. By: Camilo De Los Rios Rueda
    Abstract: There is evidence that suggests that both the creation of Protected Areas (PAs) and indigenous Reserves (IRs) has helped to reduce deforestation. Nevertheless, there are some overlapping zones between these institutions in the Colombian Amazon that have not been studied. Are these overlaps affecting the deforestation in the IRs? How are the indigenous communities responding to these overlaps? In this paper I estimate the impacts of these overlaps on the deforestation inside the IRs using a Propensity Score Matching (PSM) methodology. I use important determinants of the location of PAs and deforestation to create a valid counterfactual within the IRs. My results suggest that the overlap significantly reduces the deforestation, but that there is a differential effect depending on the IR’s size. These results suggest that the extra legal restriction imposed by the central government, favor the territorial control inside the IRs. This paper provides a starting point to analyze the current relationship between the central government, the indigenous communities and how it affects deforestation
    Keywords: deforestation, Indigenous Reserves, Protected Areas, Amazon
    JEL: Q2 Q5 R5
    Date: 2020–02–14
  22. By: Daniel Felix Ahelegbey (Università di Pavia); Paolo Giudici (Università di Pavia); Fatemeh Mojtahedi (Sari Agricultural Sciences and Natural Resources University)
    Abstract: The paper examines the relationships among market assets during stressful times, using two recently proposed econometric modeling techniques for tail risk measurement: the extreme downside hedge (EDH) and the extreme downside correlation (EDC). We extend both measures taking into account the sensitivity of asset’s return to innovations not only from the overall market index, but also from its components, by means of network modelling. Applying our proposal to the cryptocurrencies market, we find that crypto-assets can be clustered in two groups: speculative assets, such as Bitcoin, which are mainly “givers” of tail contagion; and technical assets, such as Ethereum, which are mainly “receivers” of contagion.
    Keywords: Crypto-assets, Extreme downside hedge, Extreme downside correlation, Network Models, Systematic risk, Systemic risk.
    JEL: C31 C58 G01 G12
    Date: 2020–03
  23. By: Jesus Fernandez-Villaverde (University of Pennsylvania)
    Abstract: Can arti?cial intelligence, in particular, machine learning algorithms, replace the idea of simple rules, such as ?rst possession and voluntary exchange in free markets, as a foundation for public policy? This paper argues that the preponderance of the evidence sides with the interpretation that while arti?cial intelligence will help public policy along important aspects, simple rules will remain the fundamental guideline for the design of institutions and legal environments where markets operate. “Digital socialism” might be a hipster thing to talk about in Williamsburg or Shoreditch, but it is as much of a chimera as “analog socialism.”
    Keywords: Arti?cial intelligence, machine learning, economics, law, rule of law
    JEL: D85 H10 H30
    Date: 2020–03–20
  24. By: Jianbin Lin; Zhiqiang Zhang; Jun Zhou; Xiaolong Li; Jingli Fang; Yanming Fang; Quan Yu; Yuan Qi
    Abstract: Ant Credit Pay is a consumer credit service in Ant Financial Service Group. Similar to credit card, loan default is one of the major risks of this credit product. Hence, effective algorithm for default prediction is the key to losses reduction and profits increment for the company. However, the challenges facing in our scenario are different from those in conventional credit card service. The first one is scalability. The huge volume of users and their behaviors in Ant Financial requires the ability to process industrial-scale data and perform model training efficiently. The second challenges is the cold-start problem. Different from the manual review for credit card application in conventional banks, the credit limit of Ant Credit Pay is automatically offered to users based on the knowledge learned from big data. However, default prediction for new users is suffered from lack of enough credit behaviors. It requires that the proposal should leverage other new data source to alleviate the cold-start problem. Considering the above challenges and the special scenario in Ant Financial, we try to incorporate default prediction with network information to alleviate the cold-start problem. In this paper, we propose an industrial-scale distributed network representation framework, termed NetDP, for default prediction in Ant Credit Pay. The proposal explores network information generated by various interaction between users, and blends unsupervised and supervised network representation in a unified framework for default prediction problem. Moreover, we present a parameter-server-based distributed implement of our proposal to handle the scalability challenge. Experimental results demonstrate the effectiveness of our proposal, especially in cold-start problem, as well as the efficiency for industrial-scale dataset.
    Date: 2020–03
  25. By: Kohei Maehashi (School of Engineering, The University of Tokyo); Mototsugu Shintani (Faculty of Economics, The University of Tokyo)
    Abstract: We perform a thorough comparative analysis of factor models and machine learningto forecast Japanese macroeconomic time series. Our main results can be summarizedas follows. First, factor models and machine learning perform better than the con-ventional AR model in many cases. Second, predictions made by machine learningmethods perform particularly well for medium to long forecast horizons. Third, thesuccess of machine learning mainly comes from the nonlinearity and interaction ofvariables, suggesting the importance of nonlinear structure in predicting the Japanesemacroeconomic series. Fourth, while neural networks are helpful in forecasting, simplyadding many hidden layers does not necessarily enhance its forecast accuracy. Fifth,the composite forecast of factor models and machine learning performs better thanfactor models or machine learning alone, and machine learning methods applied toprincipal components are found to be useful in the composite forecast.
    Date: 2020–03
  26. By: Fitch, Dillon PhD; Mohiuddin, Hossain; Handy, Susan PhD
    Abstract: Cities throughout the world have implemented bike-share systems as a strategy for expanding mobility options. While these have attracted substantial ridership, little is known about their influence on travel behavior more broadly. The aim of this study was to examine how shared electric bikes (e-bikes) and e-scooters influence individual travel attitudes and behavior, and related outcomes of physical activity and transportation equity. The study involved a survey in the greater Sacramento area of 1959 households before (Spring 2016) and 988 after (Spring 2019) the Summer 2018 implementation of the e-bike and e-scooterservice operated by Jump, Inc., as well as a direct survey of 703 e-bike users (in Fall 2018 & Spring 2019). Among householdrespondents, 3–13% reported having used the service. Of e-bike share trips, 35% substituted for car travel, 30% substituted for walking, and 5% were used to connect to transit. Before- and after-household surveys indicated a slight decrease in self-reported (not objectively measured) median vehicle miles traveled and slight positive shifts in attitudes towards bicycling. Service implementation was associated with minimal changes in health in terms of physical activity and numbers of collisions. The percentages of users by self-reported student status, race, and income suggest a fairly equitable service distribution by these parameters, but each survey under-represents racial minorities and people with low incomes. Therefore, the study is inconclusive about how this service impacts those most in need. Furthermore, aggregated socio-demographics of areas where trips started or ended did not correlate with, and therefore are not reliable indicators of, the socio-demographics of e-bike-share users. Thus, targeted surveying of racial minorities and people with low-incomes is needed to understand bike-share equity.
    Keywords: Social and Behavioral Sciences, Bicycles, vehicle sharing, electric vehicles, shared mobility, travel behavior, travel surveys, demographics, e-scooters, electric bicycles
    Date: 2020–03–01
  27. By: Fabio Zambuto (Bank of Italy); Maria Rosaria Buzzi (Bank of Italy); Giuseppe Costanzo (Bank of Italy); Marco Di Lucido (Bank of Italy); Barbara La Ganga (Bank of Italy); Pasquale Maddaloni (Bank of Italy); Fabio Papale (Bank of Italy); Emiliano Svezia (Bank of Italy)
    Abstract: We propose a new methodology, based on machine learning algorithms, for the automatic detection of outliers in the data that banks report to the Bank of Italy. Our analysis focuses on granular data gathered within the statistical data collection on payment services, in which the lack of strong ex ante deterministic relationships among the collected variables makes standard diagnostic approaches less powerful. Quantile regression forests are used to derive a region of acceptance for the targeted information. For a given level of probability, plausibility thresholds are obtained on the basis of individual bank characteristics and are automatically updated as new data are reported. The approach was applied to validate semi-annual data on debit card issuance received from reporting agents between December 2016 and June 2018. The algorithm was trained with data reported in previous periods and tested by cross-checking the identified outliers with the reporting agents. The method made it possible to detect, with a high level of precision in term of false positives, new outliers that had not been detected using the standard procedures.
    Keywords: banking data, data quality management, outlier detection, machine learning, quantile regression, random forests
    JEL: C18 C81 G21
    Date: 2020–03
  28. By: von Briel, Dorine; Dolnicar, Sara (The University of Queensland)
    Abstract: Peer-to-peer accommodation has been extensively studied over the past decade. The area that has most fascinated academic researchers – and most challenged policy-makers – is how to regulate peer-to-peer accommodation to avoid negative side effects, without restricting economic benefits (Dolnicar, 2019). Regulations are typically reported as individual case studies at one point in time (Hajibaba & Dolnicar, 2017). Yet they are continuously evolving. Policy makers put them in place, only to later change them, sometimes radically, as in the case of Tasmania (Grimmer, Vorobjovas-Pinta & Massey, 2019). This is the first study investigating Airbnb regulations at key international tourist destinations longitudinally. We (1) develop a typology of destinations based on their regulatory reaction to Airbnb, and (2) identify key regulatory aims, and specific measures for policy makers to achieve those aims.
    Date: 2020–03–10
  29. By: Tobias Börger (Economics Division, University of Stirling); Tenaw G. Abate (NORCE Norwegian Research Centre AS, Siva Innovasjonssenter); Margrethe Aanesen (Norwegian College of Fishery Science, UiT – Arctic University of Norway); Ewa Zawojska (Faculty of Economics Sciences, University of Warsaw)
    Abstract: Although the contingent valuation literature emphasises the importance of controlling for respondents’ consequentiality perceptions, this literature has rarely accounted for the difference between payment and policy consequentiality. We examine the influence of the randomly assigned tax amount on consequentiality self-reports and their potential endogeneity using data from a single dichotomous choice survey about reducing marine plastic pollution in Norway. Results show that consequentiality perceptions are a function of the tax amount, with payment consequentiality decreasing and policy consequentiality increasing with higher tax amounts. We discuss the challenge of finding valid instruments to address potential endogeneity of consequentiality perceptions.
    Keywords: Contingent valuation, single dichotomous choice, payment consequentiality, policy consequentiality, endogeneity, marine plastic pollution
    JEL: Q51
    Date: 2020
  30. By: Tiphaine Gorlier; Géraldine Michel (IAE Paris - Sorbonne Business School)
    Abstract: Although brands offer different kinds of rewards through their loyalty programs, little is known about how they can impact consumer–brand relationships and brand attitude. How do loyalty program rewards influence the consumer–brand relationship? And which kinds of rewards establish or maintain closer relationships between consumers and brands than others? To answer these questions, the present research makes use of self‐expansion theory (Aron & Aron, 1986) and two experiments that manipulate the extraordinary character of rewards offered to consumers. Our findings show that special rewards produce higher self‐expansion than mundane rewards. Moreover, the positive effect of the rewards' extraordinary character on brand evaluation, recommendation, and identification is sequentially and fully mediated by self‐brand inclusion and self‐expansion. Finally, we show that consumer satisfaction moderates the impact of special and mundane rewards on self‐brand inclusion.
    Keywords: brand inclusion,brand relationships,loyalty program,satisfaction,self‐expansion,special reward
    Date: 2020–01–08
  31. By: Francesco D’Acunto; Thomas Rauter; Christoph K. Scheuch; Michael Weber
    Abstract: We study the spending response of first-time borrowers to an overdraft facility and elicit their preferences, beliefs, and motives through a FinTech application. Users increase their spending permanently, lower their savings rate, and reallocate spending from non-discretionary to discretionary goods. Interestingly, liquid users react more than others but do not tap into negative deposits. The credit line acts as a form of insurance. These results are not fully consistent with models of financial constraints, buffer stock models, or present-bias preferences. We label this channel perceived precautionary savings motives: Liquid users behave as if they faced strong precautionary savings motives even though no observables, including elicited preferences and beliefs, suggest they should.
    JEL: D14 E21 E51 G21
    Date: 2020–03
  32. By: Yue-Jun Zhang (Business School, Hunan University, Changsha 410082, China; Center for Resource and Environmental Management, Hunan University, Changsha 410082, China); Elie Bouri (USEK Business School, Holy Spirit University of Kaslik, Jounieh, Lebanon); Rangan Gupta (Department of Economics, University of Pretoria, Pretoria, South Africa)
    Abstract: We challenge the existing literature that points to the detachment of Bitcoin from the global financial system. We use daily data from August 17, 2011 - February 14, 2020 and apply a risk spillover approach based on expectiles. Results show reasonable evidence to imply the existence of downside risk spillover between Bitcoin and four assets (equities, bonds, currencies, and commodities), which seems to be time dependent. Our main findings have implications for participants in both the Bitcoin and the traditional financial markets for the sake of asset allocation, and risk management. For policy makers, our findings suggest that Bitcoin should be monitored carefully for the sake of financial stability.
    Keywords: Bitcoin, financial markets, asset classes, downside risk spillover, expectile VaR, CAR-ARCHE
    Date: 2020–03
  33. By: Lippert, Ingmar (Museum für Naturkunde Berlin)
    Abstract: The PhD thesis and its related publications address how a carbon footprint of a multinational company was enacted. Related publications draw out a range of implications of this analysis for, inter alia, the sociology of the environment, Science and Technology Studies (STS), social studies of Big Data, the sociology of numbers and quantification.
    Date: 2020–04–01
  34. By: Andreas Dietrich; Reto Wernli
    Abstract: In an ideal world, individuals are well informed and make rational choices. Regulators can fill in to protect consumers, such as retail investors. Online P2P lending is a rather new form of market-based finance where regulation is still in its infancy. We analyze how retail investors price the credit risk of P2P consumer loans in a reverse auction framework where personal interaction is absent. The explained interest rate variance is considerably larger than in comparable studies using bank loan data. Our results indicate that retail investors act rational in this weakly regulated environment. This seems surprising when considering the limited set of information provided to the investor. Factors representing economic status significantly influence lender evaluations of the borrower's credit risk. The explanatory power of loan-specific factors increase as the market for P2P consumer loans matures. Furthermore, we find statistical evidence of some discrimination by the lenders with respect to nationality and gender.
    Date: 2020–03
  35. By: Safaningrum, Anggi Cecilia; Ling, Cathryn Li Yuan; Min, Venice
    Abstract: The implications of ambimorphic archetypes have been far-reaching and pervasive. After years of natural research into consistent hashing, we argue the simulation of public-private key pairs, which embodies the confirmed principles of theory. Such a hypothesis might seem perverse but is derived from known results. Our focus in this paper is not on whether the well-known knowledge-based algorithm for the emulation of checksums by Herbert Simon runs in Θ( n ) time, but rather on exploring a semantic tool for harnessing telephony (Swale).
    Date: 2020–04–02
  36. By: El-Mallakh,Nelly
    Abstract: This paper assesses the impact of Internet job search on employment in the Arab Republic of Egypt, the most populous country in the Middle East and North Africa region. Using panel data from the 2012 and 2018 rounds of the Egypt Labor Market Panel Survey, the paper examines the impact of Internet job search by the unemployed on their employment prospects. It also examines the impact of Internet job search by employed job seekers on their wage growth, as well as the impact of digitalization at the workplace on earnings. Accounting for individual and geographical unobserved heterogeneity using panel data, the results suggest that Internet job search is an effective job search method, as it increases the probability that the unemployed -- and in particular unemployed men -- will find employment. Auxiliary placebo regressions confirm that preexisting trends in labor market outcomes are not driving the results. However, Internet job search by employed job seekers does not appear to have an impact on their wage growth, nor does digitalization at the workplace affect the wage growth of employed individuals.
    Date: 2020–03–26
  37. By: Flor, Nick V. (University of New Mexico)
    Abstract: The document term matrix (“DTM”) is a representation of a collection of documents, and is a key input to many machine learning algorithms. It can be applied to a collection of tweets as well. I give the set-predicate formalism for the tweet term matrix (“TTM”), and the tweet bio-term matrix (“TBTM”).
    Date: 2020–03–09
  38. By: Alfarano, Simone; Banal-Estanol, Albert; Camacho-Cuena, Eva; Iori, Giulia; Kapar, Burcu
    Abstract: This paper compares the performance of centralized and decentralized markets experimentally. We constrain trading exchanges to happen on an exogenously predetermined network, representing the trading relationships in markets with differing levels of connectivity. Our experimental results show that, despite having lower trading volumes, decentralized markets are not necessarily less efficient. Although information can propagate quicker through highly connected markets, we show that higher connectivity also induces informed traders to trade faster and exploit further their information advantages before the information becomes fully incorporated into prices. This not only reduces market efficiency, but it also increases wealth inequality. We show that, in more connected markets, informed traders trade not only relatively quicker, but also more, in the right direction, despite not doing it at better prices.
    Keywords: Experiments, financial markets, diffusion of information, decentralized trading.
    JEL: C92 D82 G14
    Date: 2020–02
  39. By: Gasteiger, Emanuel; Prettner, Klaus
    Abstract: We assess the long-run growth effects of automation in the overlapping generations framework. Although automation implies constant returns to capital and, thus, an AK production side of the economy, positive long-run growth does not emerge. The reason is that automation suppresses wage income, which is the only source of investment in the overlapping generations model. Our result stands in sharp contrast to the representative agent setting with automation, where sustained long-run growth is possible even without technological progress. Our analysis therefore provides a cautionary tale that the underlying modeling structure of saving/investment decisions matters for the derived economic impact of automation. In addition, we show that a robot tax has the potential to raise per capita output and welfare at the steady state. However, it cannot induce a takeoff toward positive long-run growth.
    Keywords: Automation,robot taxes,stagnation,economic growth,fiscal policy
    JEL: O33 O41 E60
    Date: 2020
  40. By: Irena Barja\v{s}i\'c; Nino Antulov-Fantulin
    Abstract: In this paper, we analyze the time-series of minute price returns on the Bitcoin market through the statistical models of generalized autoregressive conditional heteroskedasticity (GARCH) family. Several mathematical models have been proposed in finance, to model the dynamics of price returns, each of them introducing a different perspective on the problem, but none without shortcomings. We combine an approach that uses historical values of returns and their volatilities - GARCH family of models, with a so-called "Mixture of Distribution Hypothesis", which states that the dynamics of price returns are governed by the information flow about the market. Using time-series of Bitcoin-related tweets and volume of transactions as external information, we test for improvement in volatility prediction of several GARCH model variants on a minute level Bitcoin price time series. Statistical tests show that the simplest GARCH(1,1) reacts the best to the addition of external signal to model volatility process on out-of-sample data.
    Date: 2020–04
  41. By: Lars Hornuf; Matthias Schmitt; Eliza Stenzhorn
    Abstract: We use hand-collected data of 20,460 investment decisions and two distinct portals to analyze whether investors in equity crowdfunding direct their investments to local firms. In line with agency theory, the results suggest that investors exhibit a local bias, even when we control for family and friends. In addition to the regular crowd, our sample includes angel-like investors, who invest considerable amounts and exhibit a larger local bias. Well-diversified investors are less likely to suffer from this behavioral anomaly. The data further show that portal design is important for attracting investors more prone to having a local bias. Overall, we find that investors who direct their investments to local firms more often pick start-ups that run into insolvency or are dissolved, which indicates that local investments in equity crowdfunding constitute a behavioral anomaly rather and a rational preference. Here again, however, portal design plays a crucial role.
    Keywords: equity crowdfunding, crowdinvesting, local bias, individual investor behavior, entrepreneurial finance
    JEL: G11 G24 K22 M13
    Date: 2020
  42. By: Adena, Maja; Hager, Anselm
    Abstract: Does online fundraising increase charitable giving? We implemented a natural field experiment across Germany, randomly assigning all of the country's 8,000 zip codes to Save the Children Facebook fundraising videos or a pure control and studied changes in the volume of donations to this and other similar charities by zip code. Our design circumvents many shortcomings inherent in studies based on click-through data, especially substitution and measurement issues. We found that (i) the video fundraising increased donation frequency and value to Save the Children during the campaign and in the subsequent five weeks; (ii) the campaign was profitable for the fundraiser; and (iii) the effects were similar independent of the video content and impression assignment strategy. However, we also found that the overall volume of donations does not increase, due to a massive crowding out of donations to other similar charities. Finally, we demonstrate that click data are an inappropriate proxy for donations.
    Keywords: Charitable giving,field experiments,fundraising,social media,competition
    JEL: C93 D64 D12
    Date: 2020
  43. By: Mark Setterfield (Department of Economics, New School for Social Research)
    Abstract: This paper outlines endogenous money theory (EMT) and the contributions of Basil J. Moore to EMT. It then describes the various papers that will appear in Volume 17, Issue 3 (2020) of the European Journal of Economics and Economic Policies: Intervention. Coolectively, these papers explore the monetary economics of Basil J. Moore – its origins, substance, and application – in light of its status as an ongoing and still-developing research project.
    Keywords: Basil J. Moore, monetary economics, horizontalism
    JEL: E43 E51 E52
    Date: 2020–03
  44. By: Stéphane Dées; Alessandro Galesi
    Abstract: We assess the international spillovers of US monetary policy with a large-scale global VAR which models the world economy as a network of interdependent countries. An expansionary US monetary policy shock contributes to the emergence of a Global Financial Cycle, which boosts macroeconomic activity worldwide. We also find that economies with floating exchange rate regimes are not fully insulated from US monetary policy shocks and, even though they appear to be relatively less affected by the shocks, the differences in responses across exchange rate regimes are not statistically significant. The role of US monetary policy in driving these macrofinancial spillovers gets even reinforced by the complex network of interactions across countries, to the extent that network effects roughly double the direct impacts of US monetary policy surprises on international equity prices, capital flows, and global growth.
    Keywords: : Trilemma, Global Financial Cycle, Monetary Policy Spillovers, Network Effects.
    JEL: C32 E52 F40
    Date: 2019
  45. By: Diana Bonfim (Banco de Portugal; Catholic University of Portugal (UCP) - Catolica Lisbon School of Business and Economics); Geraldo Cerqueiro (Catolica-Lisbon SBE); Hans Degryse (KU Leuven, Department Accounting, Finance and Insurance; Centre for Economic Policy Research (CEPR)); Steven Ongena (University of Zurich - Department of Banking and Finance; Swiss Finance Institute; KU Leuven; Centre for Economic Policy Research (CEPR))
    Abstract: Banks may have incentives to continue lending to “zombie” firms in order to avoid or delay the recognition of credit losses. In spite of growing regulatory pressure, there is evidence that “zombie lending” remains widespread, even in developed countries. We exploit information on a unique series of authoritative on-site inspections of bank credit portfolios in Portugal to investigate how such inspections affect banks’ future lending decisions. We find that following an inspection a bank becomes up to 9 percentage points less likely to refinance a firm with negative equity, implying a halving of the unconditional refinancing probability. Hence, banks structurally change their lending decisions following on-site inspections, suggesting that – even in the age of reg-tech – supervisory “reg-leg” can remain a potent tool to tackle zombie lending.
    Keywords: zombie lending, bank supervision
    JEL: G21 G32
    Date: 2020–02

General information on the NEP project can be found at For comments please write to the director of NEP, Marco Novarese at <>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.