nep-pay New Economics Papers
on Payment Systems and Financial Technology
Issue of 2019‒12‒02
34 papers chosen by

  1. Tracking the circulation routes of fresh coins in Bitcoin: A way of identifying coin miners with transaction network structural properties By Zeng-Xian Lin; Xiao Fan Liu
  2. Technology Adoption and Access to Credit via Mobile Phones By Apoorv Gupta; Jacopo Ponticelli; Andrea Tesei
  3. Creation of a Blockchain and a New Ecosystem By YANO Makoto; Chris DAI; MASUDA Kenichi; KISHIMOTO Yoshio
  4. How do we choose to pay using evolving retail payment technologies? Some additional results from Japan By Hiroshi FUJIKI
  5. Innovations in emerging markets: the case of mobile money By Pelletier, Adeline; Khavul, Susanna; Estrin, Saul
  6. Low on Trust and High on Risks: Is Sidechain a Good Solution to Bitcoin Problems? By Jamal Bouoiyour; Refk Selmi; Olivier Hueber
  7. Cards on the table: efficiency and welfare effects of the no-surcharge rule By Henriques, David
  8. Back to the Future - Changing Job Profiles in the Digital Age By Stephany, Fabian; Lorenz, Hanno
  9. How Unique is "E-stonia"? A Cross-Country Comparison of E-Services Usage in Europe By Stephany, Fabian
  10. The platform governance triangle: conceptualising the informal regulation of online content By Gorwa, Robert
  11. News and consumer card payments By Guerino Ardizzi; Simone Emiliozzi; Juri Marcucci; Libero Monteforte
  12. Blockchain Business and its Regulation By YANO Makoto; Chris DAI; MASUDA Kenichi; KISHIMOTO Yoshio
  13. Measuring financial inclusion in the main euro area countries: the role of electronic cards By Giorgio Nuzzo; Stefano Piermattei
  14. Coding Together - Coding Alone: The Role of Trust in Collaborative Programming By Stephany, Fabian; Braesemann, Fabian; Graham, Mark
  15. An empirical study on Internet-based false news stories: experiences, problem awareness, and responsibilities By Gruener, Sven
  16. Big Data-Based Peer-to-Peer Lending Fintech: Surveillance System through Utilization of Google Play Review By Pranata, Nika; Farandy, Alan Ray
  17. Forecasting Bitcoin Returns: Is there a Role for the U.S. – China Trade War? By Vasilios Plakandaras; Elie Bouri; Rangan Gupta
  18. Development of a cyber threat intelligence apparatus in a central bank By Boris Giannetto; Pasquale Digregorio
  19. Call Your Leader: Does the Mobile Phone Affect Policymaking? By Rezki, Jahen Fachrul
  20. Job Prestige and Mobile Dating Success: A Field Experiment By Neyt, Brecht; Baert, Stijn; Vynckier, Jana
  21. Deep Reinforcement Learning in Cryptocurrency Market Making By Jonathan Sadighian
  22. Precautionary Savings and Shock-Coping Behaviors: The Effects of Promoting Mobile Bank Savings on Transactional Sex in Kenya* By Kelly Jones; Erick Gong
  23. Measuring the “gig” economy: Challenges and options By Lynn Riggs; Isabelle Sin; Dean Hyslop
  24. One Size Doesn’t Fit All: Plurality of Social Norms and Saving Behavior in Kenya By Hanna Fromell; Daniele Nosenzo; Trudy Owens; Fabio Tufano
  25. Portugal adoption of the gold standard: political reasons for a monetary choice (1846-1854) By Rita Martins de Sousa
  26. As long as the bank gains: expanding the retail distribution activity By Danilo Liberati; Francesco Vercelli
  27. Adverse Selection and Credit Certificates: Evidence from a P2P Platform By Hu, Maggie Rong; Li, Xiaoyang; Shi, Yang
  28. Servers and Waiters: What Matters in the Law of A.I. By Cofone, Ignacio
  29. Administration by Algorithm? Public Management meets Public Sector Machine Learning By Veale, Michael; Brass, Irina
  30. Data Markets in Making: The Role of Technology Giants By Koski, Heli; Pantzar, Mika
  31. The impact of Hurricane Maria on out-migration from Puerto Rico: Evidence from Facebook data By Alexander, Monica; Zagheni, Emilio; Polimis, Kivan
  32. Social Norms in Networks By Ushchev, Philip; Zenou, Yves
  33. Artificial intelligence approach to momentum risk-taking By Ivan Cherednik
  34. Imitation in the Imitation Game By Ravi Kashyap

  1. By: Zeng-Xian Lin; Xiao Fan Liu
    Abstract: Bitcoin draws the highest degree of attention among cryptocurrencies, while coin mining is one of the most important fashion of profiting in the Bitcoin ecosystem. This paper constructs fresh coin circulation networks by tracking the fresh coin transfer routes with transaction referencing in Bitcoin blockchain. This paper proposes a heuristic algorithm to identifying coin miners by comparing coin circulation networks from different mining pools and thereby inferring the common profit distribution schemes of Bitcoin mining pools. Furthermore, this paper characterizes the increasing trend of Bitcoin miner numbers during recent years.
    Date: 2019–10
  2. By: Apoorv Gupta (Northwestern University); Jacopo Ponticelli (Northwestern University & CEPR); Andrea Tesei (Queen Mary University of London, CEPR, CEP (LSE) & CESifo)
    Abstract: Farmers in developing countries often lack access to timely and reliable information about modern technologies that are essential to improve agricultural productivity. The recent diffusion of mobile phones has the potential to overcome these barriers by making information available to those previously unconnected. In this paper we study the effect of mobile phone network expansion in rural India on adoption of high yielding variety seeds and chemical fertilizers. Our empirical strategy exploits geographical variation in the construction of mobile phone towers under a large government program targeting areas without existing coverage. To explore the role of mobile phones in mitigating information frictions we analyze the content of 1.4 million phone calls made by farmers to a major call center for agricultural advice. Farmers seek advice on which seed varieties and fertilizers better meet their needs and how to use them. We find that areas receiving mobile phone coverage experience higher adoption of these technologies. We also observe that farmers are often unaware of the eligibility criteria and loan terms offered by subsidized credit programs. Consistently, we find that areas receiving mobile phone coverage experience higher take-up of agricultural credit.
    Keywords: India, Agriculture, HYV Seeds, Credit Card
    JEL: G21 Q16 E51
    Date: 2019–09–12
  3. By: YANO Makoto; Chris DAI; MASUDA Kenichi; KISHIMOTO Yoshio
    Abstract: This study points out issues towards a better use of blockchain technology. It first identifies the role of data as the third major productive resources next to labor and capital in the digital economy and explains that block chain technology may facilitate an efficient and fair use of this important production factor. Blockchain technology may fundamentally change the current economy in three respects: (1) Data ownership, (2) money, and (3) data industry.
    Date: 2019–11
  4. By: Hiroshi FUJIKI
    Abstract: Using Japanese individual household datasets, we obtain the following results that are consistent with findings in most advanced economies. For our first set of findings, persons using electronic money (contactless prepaid cards available in Japan after 2001) for day-to-day transaction values of less than 5,000 yen have lower cash holdings than cash users. Second, the average cash holdings of credit card users for both day-to-day and regular payments are less than that of cash users for day-to-day payments not using credit cards for regular payments. Our second set of findings contributes to the related literature in at least two respects. First, we combine the choice of payment methods for both day-to-day and regular payments. Second, we pay due attention to institutional details about the use of credit cards in Japan and propose unique identifying assumptions excluding those persons using credit cards for day-to-day transactions but not regular payments, and those using cash for day-to-day transactions but credit cards for regular payments.
    Date: 2019–05
  5. By: Pelletier, Adeline; Khavul, Susanna; Estrin, Saul
    Abstract: Mobile money is a financial innovation that provides transfers, payments, and other financial services at a low or zero cost to individuals in developing countries where banking and capital markets are deficient and financial inclusion is low. We use transaction costs and institutional theories to explain the growth and impact of mobile money. Having developed a new archival dataset that tracks mobile money deployment across 90 emerging economies during 16 years between 2000 and 2015, we address the question of relative economic impact of the banking and telecoms sectors in the provision of mobile money. We show that telecom groups and not banks are more likely to launch mobile money in countries where legal rights are weaker and credit information less prevalent. However, it is when mobile money is offered via a banking channel that the spillover effects on the economy are greater. Findings have significant implications for policy and strategy.
    JEL: G21 M13 O33
    Date: 2019–09–09
  6. By: Jamal Bouoiyour (IRMAPE - Institut de Recherche en Management et Pays Emergents - ESC Pau, CATT - Centre d'Analyse Théorique et de Traitement des données économiques - UPPA - Université de Pau et des Pays de l'Adour); Refk Selmi (IRMAPE - Institut de Recherche en Management et Pays Emergents - ESC Pau, CATT - Centre d'Analyse Théorique et de Traitement des données économiques - UPPA - Université de Pau et des Pays de l'Adour); Olivier Hueber (GREDEG - Groupe de Recherche en Droit, Economie et Gestion - UNS - Université Nice Sophia Antipolis - UCA - Université Côte d'Azur - CNRS - Centre National de la Recherche Scientifique)
    Abstract: Over the past few years, cryptocurrencies (especially Bitcoin) have attracted a particular attention. As the number of transactions increase, these systems tend to become slower, expensive, and unsustainable for a use-case such as payment. In this way, the Bitcoin sidechain seeks to provide prompt and confidential transactions between major trading platforms. Although poor performance and high volatility can push potential users away from Bitcoin, this study reveals that the introduction of sidechain solves some of the problems Bitcoin is facing. Using relatively new techniques, we find that the implementation of sidechain reduces Bitcoin price volatility, rises its efficiency, and enhances its usefulness as a transaction tool and a diversifier. We explain these changes in Bitcoin characteristics by the sidechain"s capacity to speed up the circulation of money by shortening block validation times and to an improvement in the scalability of Proof of Work and Bitcoin payment services. Our results also indicate that the sidechain liquid network lead to a less energy-consuming and in turn to less polluting Bitcoin system. But a weakly vanishing causality between Bitcoin mining and Bitcoin energy consumption implies that the concentration of miners is still follow available electrical supply.
    Keywords: Bitcoin,Volatility,Efficiency,Risk management,Energy use,Sidechain
    Date: 2019–11–05
  7. By: Henriques, David
    Abstract: In Electronic Payment Networks (EPNs), the No-Surcharge Rule (NSR) requires that merchants charge at most the same amount for a payment card transaction as for cash. In this paper, I use a three-party model (consumers, local monopolistic merchants, and a proprietary EPN) with endogenous transaction volumes, heterogeneous card use benefits for merchants and network externalities of card-accepting merchants on cardholders to assess the efficiency and welfare effects of the NSR. I show that the NSR: (i) promotes retail price efficiency for cardholders, and (ii) inefficiently reduces card acceptance among merchants. The NSR can enhance social welfare and improve payment efficiency by shifting output from cash payers to cardholders. However, if network externalities are sufficiently strong, the reduction of card payment acceptance affects cardholders negatively and, with the exception of the EPN, all agents will be worse off under the NSR. This paper also suggests that the NSR may be an instrument to decrease cash usage, but the social optimal policy on the NSR may depend on the competitive conditions in each market.
    Keywords: competition; electronic payment networks; market power; net-work externalities; no-surcharge rule; regulation; two-sided markets
    JEL: G21 L14 L42
    Date: 2018–11–01
  8. By: Stephany, Fabian; Lorenz, Hanno
    Abstract: The uniqueness of human labour is at question in times of smart technologies. The 250 years-old discussion on technological unemployment reawakens. Frey and Osborne (2012) estimate that half of US employment will be automated by algorithms within the next 20 years. Other follow-up studies conclude that only a small fraction of workers will be replaced by digital technologies. The main contribution of our work is to show that the diversity of previous findings regarding the degree of job automation is, to a large extent, driven by model selection and not by controlling for personal characteristics or tasks. For our case study, we consult Austrian experts in machine learning and industry professionals on the susceptibility to digital technologies in the Austrian labour market. Our results indicate that, while clerical computer-based routine jobs are likely to change in the next decade, professional activities, such as the processing of complex information, are less prone to digital change.
    Date: 2019–08–16
  9. By: Stephany, Fabian
    Abstract: User data fuel the digital economy, while individual privacy is at stake. Governments react differently to this challenge. Estonia, a small Baltic state, has become a role model for the renewal of the social contract in times of big data (hence, often ironically referred to as "E-stonia"). While e-governance usage has been growing in many parts of Europe during the last ten years, some regions are lagging behind. The Estonian example suggests that online governance is most accepted in a small state, with a young population, trustworthy institutions and the need of technological renewal. This work examines the development of e-governance usage (citizens interacting digitally with the government) during the last decade in Europe from a comprehensive cross-country perspective: Size, age and trust are relevant for the usage of digital government services in Europe. However, the quality of past communication infrastructure is not related to e-governance popularity.
    Date: 2019–08–25
  10. By: Gorwa, Robert
    Abstract: From the new Facebook ‘Oversight Body’ for content moderation to the ‘Christchurch Call to eliminate terrorism and violent extremism online,’ a growing number of voluntary and non-binding informal governance initiatives have recently been proposed as attractive ways to rein in Facebook, Google, and other platform companies hosting user-generated content. Drawing on the literature on transnational corporate governance, this article reviews a number of informal arrangements governing online content on platforms in Europe, mapping them onto Abbott and Snidal’s (2009) ‘governance triangle’ model. I discuss three key dynamics shaping the success of informal governance arrangements: actor competencies, ‘legitimation politics,’ and inter-actor relationships of power and coercion.
    Date: 2019–06–29
  11. By: Guerino Ardizzi (Bank of Italy); Simone Emiliozzi (Bank of Italy); Juri Marcucci (Bank of Italy); Libero Monteforte (Bank of Italy and Parliamentary Budget Office)
    Abstract: We exploit a unique daily data set on debit card expenditures to study the reaction of consumers to daily news relating to Economic Policy Uncertainty (EPU). Payments with debit cards are a proxy for consumption in the quarterly national accounts. Using big data techniques we construct daily EPU indexes, using either articles from Bloomberg news-wire or tweets from Twitter. Our empirical analysis at high frequency required estimates of daily seasonal components, finding strong patterns both within the week and within the month. Using local projections we find that daily shocks to EPU temporarily reduce debit card purchases, especially during the recent crisis; the main results are confirmed using monthly data and controlling for financial uncertainty and macroeconomic surprises. Furthermore, economic policy uncertainty affects the ratio between ATM withdrawals and debit card purchases, signaling an increase in households' preference for cash.
    Keywords: consumption, payment system, policy uncertainty, big data, daily seasonality, local projections
    JEL: C11 C32 C43 C52 C55 E52 E58
    Date: 2019–10
  12. By: YANO Makoto; Chris DAI; MASUDA Kenichi; KISHIMOTO Yoshio
    Abstract: As the blockchain industry is becoming larger, a new decentralized financial ecosystem is now developing. New financial devices, represented by terms like tokens, coins and ICOs are introduced to finance projects on blockchain. Many countries are now studying how to deal with this new financial ecosystem. The U.S. is now regulating it by the Securities Act whereas Japan is applying the Money Settlement Act and the Financial Instruments and Exchange Act. In this paper, without going into country-specific regulatory issues, we will investigate how the society may deal with the new decentralized financial ecosystem from the regulatory viewpoint.
    Date: 2019–11
  13. By: Giorgio Nuzzo (Bank of Italy); Stefano Piermattei (Bank of Italy)
    Abstract: Since financial inclusion has become a policy target in many countries, it is crucial to measure it properly. The usual indexes of financial inclusion include inappropriate variables and do not take into account other relevant aspects, thus misrepresenting the phenomenon. In this paper, we focus on the distribution of electronic cards, generally not included in the usual indexes of financial inclusion even if they provide alternatives to usual saving practices and make transactions across larger markets and wider geographic areas less costly. We show that if we also take account of these instruments, the comparative valuation of the degree of financial inclusion across the main euro-area countries changes substantially. We also employ survey data to analyse cross-country differences in the degree of financial inclusion and the distribution of multidimensional deprivations of specific sub-groups of populations.
    Keywords: financial inclusion, payment instruments, electronic cards
    JEL: G20 I22
    Date: 2019–07
  14. By: Stephany, Fabian; Braesemann, Fabian; Graham, Mark
    Abstract: In the digital economy, innovation processes increasingly rely on highly specialised know-how and open-source software shared on digital platforms on collaborative programming. The information that feeds into the content on these platforms is provided voluntarily by a vast crowd of knowledgeable users from all over the world. In contributing to the platforms, users invest their time and share knowledge with strangers to add to the rising body of digital knowledge.This requires an open mindset and trust. In this study, we argue that such a mindset is not just an individual asset, but determined by the local communities the users are embedded in. We, therefore, hypothesise that places with higher levels of trust should contribute more to StackOverflow, the world’s largest question-and-answer platform for programming questions. In relating the city-level contributions of 266 OECD metropolitan areas to infrastructure, economic, and trust measures, we find this hypothesis confirmed. In contrast, click rates to the platform are solely driven by infrastructure and economic variables, but not by trust. These findings highlight the importance of societal values in the 21st century knowledge economy: if policy-makers want to develop a lively local digital economy, it is not enough to provide fast Internet access and business opportunities. Instead, it is equally important to establish a trust-building environment that fosters sharing of innovative ideas, collaborations, and knowledge spillovers.
    Date: 2019–05–03
  15. By: Gruener, Sven
    Abstract: The Internet significantly reduced the marginal costs of generating and disseminating information. With false news stories in mind, scholars are increasingly interested in redesigning our information ecosystem because well-informed individuals are essential for a functioning democracy. This paper addresses the problem awareness of university students about false news stories. With the help of a questionnaire we seek for interesting correlations to generate hypotheses that can be analyzed in further studies with new data (i.e. exploratory study). They read as follows: (i) Facebook users are more likely to be suspicious of false news stories if they are interested in political topics. People are less likely to detect false news stories the stronger they trust in others and the more emphasis they put on the opinions of others, (ii) False news stories are perceived as a problem at the societal level, but not at the individual level, (iii) Men more often than women believe to be in touch with false news stories; men overestimate their ability to spot false news stories. People who fear false news stories are likely to believe that they could detect such infor-mation better than the average, and (iv) People see operators of platforms to be in charge against false news stories; people seem to trust less in government.
    Date: 2019–01–26
  16. By: Pranata, Nika (Asian Development Bank Institute); Farandy, Alan Ray (Asian Development Bank Institute)
    Abstract: Peer-to-peer lending (P2PL) FinTech is growing rapidly in Indonesia. With its flexibility and simplicity, P2PL reduces the financing gap that cannot be fulfilled by banks. However, the rapid development of P2PL also raises a number of problems that burden users such as unethical debt collection methods and the imposition of excessive interest rate and other costs that potentially threaten national financial system stability. Therefore, by utilizing big data, which in this case is 40,650 reviews from 110 P2PLs obtained from Google Play from March 2016 to August 2018, we build a big data-based P2PL surveillance system based on four aspects: legality, review rating, debt collection methods, and level of interest rates and other costs. By using relational database, structured query language (SQL), and text analysis, we found that (i) the majority of P2PL in Google Play are unauthorized; (ii) on average, authorized P2PL receives a better review rating; (iii) there are a lot of negative reviews related to unethical debt collection methods and excessive imposition of interest rate; and (iv) four P2PLs required special supervision from the Indonesia Financial Service Authority (OJK). Furthermore, the OJK should not passively wait for official reports to be filed by the public regarding violations of P2PL businesses. Through this big data-based system, the OJK can find these violations proactively because the system can act as an early warning system for the OJK in terms of P2PL surveillance.
    Keywords: fintech; peer to peer lending; big data; review; Google Play
    JEL: G23 G24 G28
    Date: 2019–04–12
  17. By: Vasilios Plakandaras (Department of Economics, Democritus University of Thrace, University Campus, Komotini, Greece); Elie Bouri (USEK Business School, Holy Spirit University of Kaslik, Jounieh, Lebanon); Rangan Gupta (Department of Economics, University of Pretoria, Pretoria, 0002, South Africa)
    Abstract: Previous studies provide evidence that trade related uncertainty tends to predict an increase in Bitcoin returns. In this paper, we extend the related literature by examining whether the information on the U.S. – China trade war can be used to forecast the future path of Bitcoin returns controlling for various explanatory variables. We apply ordinary least square (OLS) regression, support vector regression (SVR), and the least absolute shrinkage and selection operator (LASSO) techniques that stem from the field of machine learning, and find weak evidence of the role of the trade war in forecasting Bitcoin returns. Given that out-of-sample tests are more reliable than in-sample tests, our results tend to suggest that future Bitcoin returns are unaffected by trade related uncertainties, and investors can use Bitcoin as a safe haven in this context.
    Keywords: Bitcoin, forecasting, machine learning, U.S. – China trade war
    JEL: C53 G11 G17
    Date: 2019–11
  18. By: Boris Giannetto (Bank of Italy); Pasquale Digregorio (Bank of Italy)
    Abstract: The present work defines the development of a cyber threat intelligence (CTI) apparatus in a central bank. Such a system aims at promoting a preventive posture against constantly evolving threats such as cybercrime, cyber espionage, hacktivism, cyberterrorism and state-sponsored APTs. Central banks are targeted by a gamut of threat actors. Cyber-attacks against financial institutions are on the rise: Those directed against strategic data, infrastructures and platforms of a central bank, could have momentous repercussions on the vital ganglia of the financial system as a whole. CTI operates on a three-level scale: Tactical/technical, operational and strategic. As to the latter, geopolitical and context analysis is key. The proposed CTI apparatus - designed to cope with multifarious cyber threats - aims at spurring systemic prevention and resilient reaction.
    Keywords: cyber threat intelligence, cyber intelligence, geopolitical analysis, complex adaptive systems, cybersecurity, cyber resilience
    JEL: F50 G38 L50 O33
    Date: 2019–10
  19. By: Rezki, Jahen Fachrul
    Abstract: This paper analyses the impact of Information and Communication Technology (ICT) on policymaking on an Indonesian Village level. In this study, I use data from different waves of the Indonesian Village Potential Statistics (Potensi Desa) to determine whether mobile phone signal strength affects village policies and civic engagement activities. The results indicate that villages with a strong signal are statistically more likely to possess the proper infrastructure and economic programs. Furthermore, mobile phones increase civic engagement, which is consistent with previous studies related to collective action or mass mobilisation. Using the plausibly exogenous variation of lightning strike intensity as the instrumental variable, this study suggests that higher mobile phone signal strength is positively associated with the policies implemented by the village head. This study also demonstrates that ICT has a stronger effect in rural areas. One possible explanation is that mobile phones improve the relative ability for rural people to interact with their leaders. Another potential answer is the fact that there are significant differences between rural village and urban village governments, which could also affect policymaking.
    Date: 2018–11–23
  20. By: Neyt, Brecht (Ghent University); Baert, Stijn (Ghent University); Vynckier, Jana (Ghent University)
    Abstract: Research exploiting data on classic (offline) couple formation has confirmed predictions from evolutionary psychology in a sense that males attach more value to attractiveness and women attach more value to earnings potential. We examine whether these human partner preferences survive in a context of fewer search and social frictions. We do this by means of a field experiment on the mobile dating app Tinder, which takes a central place in contemporary couple formation. Thirty-two fictitious Tinder profiles that randomly differ in job status and job prestige are evaluated by 4,800 other, real users. We find that both males and females do not use job status or job prestige as a determinant of whom to show initial interest in on Tinder. However, we do see evidence that, after this initial phase, males less frequently begin a conversation with females when those females are unemployed but also then do not care about the particular job prestige of employed females.
    Keywords: job prestige, partner preferences, dating apps, online dating, Tinder
    JEL: J12 J16 J13 C93
    Date: 2019–11
  21. By: Jonathan Sadighian
    Abstract: This paper sets forth a framework for deep reinforcement learning as applied to market making (DRLMM) for cryptocurrencies. Two advanced policy gradient-based algorithms were selected as agents to interact with an environment that represents the observation space through limit order book data, and order flow arrival statistics. Within the experiment, a forward-feed neural network is used as the function approximator and two reward functions are compared. The performance of each combination of agent and reward function is evaluated by daily and average trade returns. Using this DRLMM framework, this paper demonstrates the effectiveness of deep reinforcement learning in solving stochastic inventory control challenges market makers face.
    Date: 2019–11
  22. By: Kelly Jones; Erick Gong
    Abstract: For the vulnerable, even small shocks can have significant short-and long-term impacts. Beneficial shock-coping mechanisms are not widely available in sub-Saharan Africa. We test whether individual precautionary savings can reduce a shock-coping behavior common in SSA that has negative spillovers: transactional sex. Among a set of vulnerable women, we randomly assigned an intervention that promoted savings in a mobile banking account labeled for goals and emergency expenses. We find that the intervention led to an increase in total mobile savings, reductions in transactional sex as a risk-coping response, and a decrease in symptoms of sexually transmitted infections. Changes are sustained in the medium-term.
    Keywords: Shock-coping; Savings; Sexual behavior; Kenya; Africa
    JEL: O12 D14 I15 J16
    Date: 2019
  23. By: Lynn Riggs (Motu Economic and Public Policy Research); Isabelle Sin (Motu Economic and Public Policy Research); Dean Hyslop (Motu Economic and Public Policy Research)
    Abstract: The increase in internet-based services has raised policy interest in gig work, which is work done outside formal employer-employee relationships. Given the dearth of information about the nature and magnitude of gig work and the extent of its growth in New Zealand, it is unclear whether current regulatory institutions adequately regulate it. There is also concern among policymakers about the effect of gig work on the financial stability of gig workers. In this paper we provide a New Zealand-specific typology for identifying gig work, and discuss conceptual and practical issues related to measuring it. We describe how existing New Zealand data can be used to learn more about gig work and make suggestions for improving its measurement in the future.
    Keywords: Gig work, Gig economy
    JEL: J21 J40 J46 J81 J83 J88
    Date: 2019–11
  24. By: Hanna Fromell (University of Groningen); Daniele Nosenzo (University of Nottingham, School of Economics & Luxembourg Institute of Socio-Economic Research (LISER)); Trudy Owens (University of Nottingham, School of Economics); Fabio Tufano (University of Nottingham, School of Economics)
    Abstract: We measure the social norms of sharing income with kin and neighbors in villages in Kenya. We find a plurality of norms: from a strict norm prohibiting wealth accumulation to a norm facilitating saving. Several individual and social network characteristics predict the norms upheld; the pro-saving norm becomes majoritarian when an individual can conceal their income from kin and neighbors. Whether income secrecy facilitates savings depends on the type of norm individuals uphold: stricter norm supporters are helped by secrecy, pro-saving norm supporters are harmed. This highlights the importance of measuring social norms when devising pro-saving policy interventions.
    Keywords: Sharing norms; forced solidarity; social pressure; savings; social norms; KrupkaWeber method; lab-in-the-field experiment
    Date: 2019–12
  25. By: Rita Martins de Sousa
    Abstract: This article analyses the transition from bimetallism to the gold standard in Portugal. The research has emphasised that the high percentage of gold coins in circulation and the network externalities were the main reasons for the de jure adoption of the gold standard in 1854. However, it has not provided a justification for either the appreciation of gold in the Portuguese market in 1847 which was contrary to the international trend or the reasons behind the decision to continue to circulate British gold sovereigns in 1851 when all other foreign coins were withdrawn. We argue that the political pressure applied by groups with ownership of British gold coins explains the transition from bimetallism to the gold standard.
    Keywords: PMonetary history, Gold standard, Portugal, nineteenth century JEL classification: N13; N20; E42
    Date: 2019
  26. By: Danilo Liberati (Bank of Italy); Francesco Vercelli (Bank of Italy)
    Abstract: We investigate the retail distribution of financial products by the Italian banking system between 2010 and 2017. We focus on mutual fund shares, insurance contracts and individually managed portfolios, analysing the characteristics of the banks that distribute these instruments the most and the contribution of each product to bank profitability. We find that banks with larger amounts of bad loans relative to equity distribute more asset management instruments, an activity that does not absorb equity. When liquidity constraints are less binding, banks that are financed more through deposits increase their distribution activity. Moreover, banks with stronger lending specialization are less involved in distributing financial products. Finally, fees from the distribution of individually managed portfolios contribute to bank profitability more than those from the distribution of mutual fund shares.
    Keywords: Banks, Distribution fees, Non-interest income
    JEL: D14 G21
    Date: 2019–10
  27. By: Hu, Maggie Rong (Asian Development Bank Institute); Li, Xiaoyang (Asian Development Bank Institute); Shi, Yang (Asian Development Bank Institute)
    Abstract: Certificates are widely used as a signaling mechanism to mitigate adverse selection when information is asymmetric. To reduce information asymmetry between lenders and borrowers, Chinese peer-to-peer (P2P) lending platforms encourage borrowers to obtain various kinds of credit certificates. As P2P markets continue to develop, it is plausible that certification may play a pivotal role in ensuring investment efficiency. We perform the first empirical investigation of this issue, using unique data from Renrendai, one of the People’s Republic of China’s largest P2P lending platforms. We find that surprisingly, loans with more credit certificates experience a higher rate of delinquency and default. However, lenders remain attracted by higher certificates despite lower loan performance ex post, which results in distorted capital allocation and reduced investment inefficiency. Overall, we document a setting where credit certificates fail to serve as an accurate signal due to their costless nature, where poor-quality borrowers use more certificates to boost their credit profiles and improve their funding success. Possible explanations for this phenomenon include differences in marginal benefit of certificates for different borrower types, bounded rationality, cognitive simplification, and borrower myopia.
    Keywords: P2P lending; credit allocation; adverse selection; certificate; bounded rationality; cognitive simplification
    JEL: G10 G20 G21 G23
    Date: 2019–04–11
  28. By: Cofone, Ignacio (McGill University)
    Abstract: The European Parliament’s recent declaration that robots are “electronic persons” illustrates the widespread uncertainty about how to regulate robots and artificial intelligence (A.I.) agents. This article aims to confront that uncertainty. To date, most regulations have treated robots and A.I. agents either as tools or people, making questionable assignments of rights and responsibilities. Instead, regulations should reckon that robots and A.I. agents escape this dichotomy. The law must assign rights and responsibilities for entities with characteristics that exist on a continuum between tools and people. This article describes this continuum through three characteristics that help us consistently place robots and A.I. agents along it: emergence, embodiment, and social valence. It proposes a framework for analogizing A.I. entities to existing entities that the law already understands, thereby creating a baseline for assigning rights and responsibilities for their actions.
    Date: 2019–02–10
  29. By: Veale, Michael; Brass, Irina
    Abstract: Public bodies and agencies increasingly seek to use new forms of data analysis in order to provide 'better public services'. These reforms have consisted of digital service transformations generally aimed at 'improving the experience of the citizen', 'making government more efficient' and 'boosting business and the wider economy'. More recently however, there has been a push to use administrative data to build algorithmic models, often using machine learning, to help make day-to-day operational decisions in the management and delivery of public services rather than providing general policy evidence. This chapter asks several questions relating to this. What are the drivers of these new approaches? Is public sector machine learning a smooth continuation of e-Government, or does it pose fundamentally different challenge to practices of public administration? And how are public management decisions and practices at different levels enacted when machine learning solutions are implemented in the public sector? Focussing on different levels of government: the macro, the meso, and the 'street-level', we map out and analyse the current efforts to frame and standardise machine learning in the public sector, noting that they raise several concerns around the skills, capacities, processes and practices governments currently employ. The forms of these are likely to have value-laden, political consequences worthy of significant scholarly attention.
    Date: 2019–04–19
  30. By: Koski, Heli; Pantzar, Mika
    Abstract: Abstract This paper focuses on the role of large technology companies’ entry and expansion to the data-intensive market areas via their technological development and strategic acquisitions of companies. We analyze the evolvement of personal data related innovation in various data-intensive domains. We find that the ideas related to personal data are increasingly protected by patents. The growth in the numbers of personal data related patents was relatively modest from 2005 to the early 2010s, but it has intensified since 2011. Large technology companies’ entry to various new market areas is reflected in an exponential increase in patent applications particularly in the artificial intelligence domain. Furthermore, we find that the number of artificial intelligence/data analytics companies acquired by the data giants has escalated during the 2010s. Patent and acquisition data further echo technology giants’ intentions to expand their activities into the financial and personal health services. Overall, the data show the data giants’ buyouts are frequently targeted to companies active in the markets outside their core business. Our analysis illustrates how the divergencies in the data giants’ innovation activities and strategic acquisitions have led them to each conquer their specific areas of dominance in the global markets for data.
    Keywords: Data economy, Innovation, Patents, Acquisitions, Technology giants
    JEL: G34 L12 L25 O33
    Date: 2019–11–19
  31. By: Alexander, Monica; Zagheni, Emilio; Polimis, Kivan
    Abstract: Natural disasters such as hurricanes can cause substantial population out-migration. However, the magnitude of population movements is difficult to estimate using only traditional sources of migration data. We utilize data obtained from Facebook's advertising platform to estimate out-migration from Puerto Rico in the months after Hurricane Maria. We find evidence to indicate a 17.0% increase in the number of Puerto Rican migrants present in the US over the period October 2017 to January 2018. States with the biggest increases were Florida, New York and Pennsylvania, and there were disproportionately larger increases in the 15-30 age groups and for men compared to women. Additionally, we find evidence of subsequent return migration to Puerto Rico over the period January 2018 to March 2018. These results illustrate the power of complementing social media and traditional data to monitor demographic indicators over time, particularly after a shock, such as a natural disaster, to understand large changes in population characteristics.
    Date: 2019–01–28
  32. By: Ushchev, Philip (National Research University); Zenou, Yves (Monash Universitiy)
    Abstract: Although the linear-in-means model is the workhorse model in empirical work on peer effects, its theoretical properties are understudied. In this study, we develop a social-norm model that provides a micro foundation of the linear-in-means model and investigate its properties. We show that individual outcomes may increase, decrease, or vary non-monotonically with the taste for conformity. Equilibria are usually inefficient and, to restore the first best, the planner needs to subsidize (tax) agents whose neighbors make efforts above (below) the social norms. Thus, giving more subsidies to more central agents is not necessarily efficient. We also discuss the policy implications of our model in terms of education and crime.
    Keywords: Social norms; Conformism; Local-average model; Welfare; Anti-conformism; Network formation
    JEL: D85 J15 Z13
    Date: 2019–11–18
  33. By: Ivan Cherednik
    Abstract: We propose a mathematical model of momentum risk-taking, which is real-time risk management, and discuss its implementation: an automated momentum equity trading system. Risk-taking is one of the key components of general decision-making, a challenge for artificial intelligence and machine learning. We begin with a simple continuous model of news impact and then perform its discretization, adjusting it to dealing with discontinuous functions. Stock charts are the main examples for us; stock markets are quite a test for any risk management theories. An entirely automated trading system based on our approach proved to be successful in extensive historical and real-time experiments. Its preimage is a new contract card game presented at the end of the paper.
    Date: 2019–11
  34. By: Ravi Kashyap
    Abstract: We discuss the objectives of automation equipped with non-trivial decision making, or creating artificial intelligence, in the financial markets and provide a possible alternative. Intelligence might be an unintended consequence of curiosity left to roam free, best exemplified by a frolicking infant. For this unintentional yet welcome aftereffect to set in a foundational list of guiding principles needs to be present. A consideration of these requirements allows us to propose a test of intelligence for trading programs, on the lines of the Turing Test, long the benchmark for intelligent machines. We discuss the application of this methodology to the dilemma in finance, which is whether, when and how much to Buy, Sell or Hold.
    Date: 2019–11

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.