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on Payment Systems and Financial Technology |
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Issue of 2019‒07‒29
39 papers chosen by |
| By: | Konstantinos Nikolopoulos (Bangor University); Konstantia Litsiou (Manchester Metropolitan University) |
| Abstract: | In this research paper we investigate changes in payment media used from consumers as a result of extreme financial restrictions. The motivation comes from the summer of 2015 in Greece where after failure for an agreement between Greece and the Troika (EU, IMF and ECB) for an extension of lending support from the latter, the Greek government decided to close the banks for three weeks; and apply capital controls still in place ten months after the event - however gradually relaxed. Methodologically we adopted grounded theory and through this a fully qualitative and longitudinal study comprised of three series (every six months) of in-depth interviews with individual citizens (on behalf of their households) over a period of one calendar year. We aim to investigate research changes in payment media used during and after the period when the banks were closed, as well as permanent changes in consumer and social behavior. Acknowledging that with this methodological approach reaching statistical significant results is very difficult to be achieved, we do however seek and to a great extend provide insight in what really happened during and after the events, and one thing came out again and again: people turned more into the use of debit cards, and secondary to online banking and to a lesser extent to credit cards; the later came with an inevitable raise of household debt. Cash use was only temporarily increased and more evidently during the three-week event, while all the previous aforementioned results had of a more permanent nature, as illustrated from the longitudinal analysis. |
| Keywords: | Financial Crisis; Banks; Capital Controls; Households; Payment media; |
| JEL: | G0 G21 G28 H12 H31 |
| Date: | 2019–07 |
| URL: | http://d.repec.org/n?u=RePEc:bng:wpaper:19008&r=all |
| By: | Konstantinos Nikolopoulos (Bangor University); Konstantia Litsiou (Manchester Metropolitan University) |
| Abstract: | In this research paper we investigate the relationship between economic crises and the changes in levels of social collateral, as well as the indirect changes in the use of payment media from consumers as a result of the latter. The scene is Europe in 2015 and the Eurozone crisis involving countries mostly hit form the crisis: Greece, Cyprus and to a lesser extent Spain, versus less affected economies like Sweden and UK. We use and analyse questions focusing on social collateral, taken from a much broader research instrument - a questionnaire with 54 questions that have been used in a series of studies focusing in the use of payment media during 2015. From a total of 1003 gathered questionnaires a comparative analysis is performed through time and space focusing on three periods: before the start of the crisis in 2008, after that, and during the last 12 months; in terms of geographical dispersion, the aforementioned five countries are researched. Our empirical results provide some preliminary evidence indicating an heterogeneous behaviour among the five countries under investigation, as well as a clear change over time - partially explained by the impact of the crisis. |
| Keywords: | Financial Crisis; Social Collateral; Households; Payment media; Europe; |
| JEL: | G01 A13 D10 H31 E4 |
| Date: | 2019–07 |
| URL: | http://d.repec.org/n?u=RePEc:bng:wpaper:19009&r=all |
| By: | Sonja Davidovic; Elena Loukoianova; Cormac Sullivan; Hervé Tourpe |
| Abstract: | The Bali Fintech Agenda highlights 12 principles for policymakers to consider when formulating their approaches to new financial technology (fintech). The agenda aims to harness the potential of fintech while managing associated risks. This paper looks at how some elements of the Bali Fintech Agenda could be used in Pacific island countries, which face significant financial-structural challenges. |
| Keywords: | Pacific Island Countries;Financial inclusion;Financial institutions;Technological innovation;Banks & banking;Banking regulations;Fintech, Bali Fintech Agenda; Pacific Islands; Small States; Financial Inclusion; Financial Development |
| URL: | http://d.repec.org/n?u=RePEc:imf:imfdep:19/14&r=all |
| By: | Guillaume Compain (Université Paris-Dauphine, PSL Research University); Philippe Eynaud (GREGOR - Groupe de Recherche en Gestion des Organisations - UP1 - Université Panthéon-Sorbonne - IAE Paris - Sorbonne Business School); Lionel Morel (CNRS - Centre National de la Recherche Scientifique); Corinne Vercher-Chaptal (CEPN - Centre d'Economie de l'Université Paris Nord - UP13 - Université Paris 13 - USPC - Université Sorbonne Paris Cité - CNRS - Centre National de la Recherche Scientifique) |
| Abstract: | The sharing economy harbours a diversity of stories and practices that make this notion somewhat ambiguous. On the one hand, some powerful platform-companies, designed to capture, process and control increasing volumes of data in the hope of generating high profits, claim to belong to the sharing economy. On the other hand, we find sharing platforms that aim to escape purely commercial principles and place sharing and solidarity at the heart of their development models. A qualitative study carried out in France with a sample of nine platforms belonging to this second type brought to light two findings. Firstly, the alternatives studied are characterised by a dynamic of "re-embedding" on at least one of the three fictitious commodities identified by Polanyi (labour, money and land). Secondly, they aim to go beyond the classical opposition between the open strategy of the digital commons and the more closed approach based on collective ownership found in platform cooperativism. They manage to overcome this opposition through mutualistic practices and alliances, and multi-stakeholder governance built around the general interest. In doing so, sharing platforms are inventing the outlines of a possible renewal of public action and laying the foundations for an organised response to the challenges of the social and ecological transition |
| Keywords: | Sharing Economy,Platform,Digital commons,platform cooperativism,substantive economy |
| Date: | 2019–06–27 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:halshs-02140104&r=all |
| By: | Svizzero, Serge; Tisdell, Clement |
| Abstract: | The "Metallist" origin of money, used as a medium of exchange, is based on the presumed low efficiency of barter. However, barter is usually ill-defined and archaeological evidence about it is inconclusive. Moreover, the transaction costs associated with barter seem to have been exaggerated by metallists. Indeed, the introduction of a unit of account reduces the complexity of the relative prices system usually associated with barter. Similarly, in-kind transactions have timing constraints which are often labeled as "the double coincidence of wants"; with a system of debt and credit, delayed exchange, that is lending, is possible. Such adaptability of barter is confirmed by the study of Mesopotamian and ancient Egyptian palatial economies. They provide evidence that non-monetary transactions have persisted during millennia, challenging the metallist vision about the origin of money. |
| Keywords: | Financial Economics, International Relations/Trade |
| Date: | 2019–07–22 |
| URL: | http://d.repec.org/n?u=RePEc:ags:uqseet:291788&r=all |
| By: | David R. Agrawal; David E. Wildasin |
| Abstract: | Technological innovations facilitating e-commerce have well-documented effects on consumer behavior and firm organization in the retail sector, but the effects of these new transaction technologies on fiscal systems remain unknown. By extending models of commodity tax competition to include urban spatial structure (agglomeration) and online commerce, one can analyze strategic tax-policy interactions among neighboring localities. Consumers buy different types of commodities, sold either by traditional or by online vendors. When the cost of online shopping falls, we show that equilibrium tax rates and revenues increase in small jurisdictions and decrease in large jurisdictions with retail shopping centers. Policy commentators warn that e-commerce erodes tax revenue - true enough for some localities - but, more accurately, changing transaction costs can generate entirely new commercial and fiscal equilibria that ultimately “redistribute” tax revenues from localities with concentrations of traditional vendors toward other, typically smaller, localities. |
| Keywords: | sales tax, retail shopping, agglomeration, e-commerce, fiscal competition |
| JEL: | H25 H71 H73 L81 R50 |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_7742&r=all |
| By: | Julien Chevallier (UP8 - Université Paris 8 Vincennes-Saint-Denis); Stéphane Goutte (UP8 - Université Paris 8 Vincennes-Saint-Denis); Khaled Guesmi (IPAG Paris - IPAG Paris); Samir Saadi (École de gestion Telfer / Université d'Ottawa - Université d'Ottawa) |
| Abstract: | This study contributes to the existing literature on the empirical characteristics of virtual currency allowing for dynamic transition between different economic regimes and considering various crashes and rallies over the business cycle, that are captured by jumps. We combine Markov-switching models with Levy jump-diffusion offer a new model that captures the different sub-period of crises over the business cycle, that are captured by jumps. This method also enables to test the relevance of dynamic measures of regime switching with respect to independent pure-jump process, which are not frequently used in the literature. Bitcoin offer something different than a traditional currency; there is potential value of having a network that helps as a secure repository for the common knowledge of all transactions. In addition, value of bitcoin fluctuates so wildly that it may be too risky to serve as a credible store of value. |
| Keywords: | Bitcoin,Jump process,Markov-switching model |
| Date: | 2019–07–05 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:halshs-02175669&r=all |
| By: | Leduc, Sylvain (Federal Reserve Bank of San Francisco); Liu, Zheng (Federal Reserve Bank of San Francisco) |
| Abstract: | We study the implications of automation for labor market fluctuations in a Diamond-Mortensen-Pissarides (DMP) framework that is generalized to incorporate automation decisions. If a job opening is not filled with a worker, a firm can choose to automate that position and use a robot instead of a worker to produce output. The threat of automation strengthens the firm's bargaining power against job seekers in wage negotiations, depressing equilibrium real wages in a business cycle boom. The option of automation also increases the value of a vacancy, raising the incentive for job creation, and thereby amplifying fluctuations in vacancies and unemployment relative to the standard DMP framework. Since automation improves labor productivity while muting wage increases, it implies a countercyclical labor income share, as observed in the data. |
| JEL: | E32 J63 J64 |
| Date: | 2019–07–18 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedfwp:2019-17&r=all |
| By: | Yuqing Zhang; Neil Walton |
| Abstract: | We study the application of dynamic pricing to insurance. We view this as an online revenue management problem where the insurance company looks to set prices to optimize the long-run revenue from selling a new insurance product. We develop two pricing models: an adaptive Generalized Linear Model (GLM) and an adaptive Gaussian Process (GP) regression model. Both balance between exploration, where we choose prices in order to learn the distribution of demands & claims for the insurance product, and exploitation, where we myopically choose the best price from the information gathered so far. The performance of the pricing policies is measured in terms of regret: the expected revenue loss caused by not using the optimal price. As is commonplace in insurance, we model demand and claims by GLMs. In our adaptive GLM design, we use the maximum quasi-likelihood estimation (MQLE) to estimate the unknown parameters. We show that, if prices are chosen with suitably decreasing variability, the MQLE parameters eventually exist and converge to the correct values, which in turn implies that the sequence of chosen prices will also converge to the optimal price. In the adaptive GP regression model, we sample demand and claims from Gaussian Processes and then choose selling prices by the upper confidence bound rule. We also analyze these GLM and GP pricing algorithms with delayed claims. Although similar results exist in other domains, this is among the first works to consider dynamic pricing problems in the field of insurance. We also believe this is the first work to consider Gaussian Process regression in the context of insurance pricing. These initial findings suggest that online machine learning algorithms could be a fruitful area of future investigation and application in insurance. |
| Date: | 2019–07 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1907.05381&r=all |
| By: | Apostolos Serletis (University of Calgary); Jinan Liu (University of Calgary) |
| Abstract: | How do cryptocurrency prices evolve? Is there any interdependence among cryptocur- rency returns and/or volatilities? Are there any return spillovers and volatility spillovers between the cryptocurrency market and other financial markets? To answer these questions,we use GARCH-in-mean models to examine the relationship between volatility and returns of leading cryptocurrencies, to investigate spillovers within the cryptocurrency market, and also from the cryptocurrency market to other financial markets. Overall, we find statistically significant transmission of shocks and volatilities among the leading cryptocurrencies. We also find statistically significant spillover effects from the cryptocurrency market to other financial markets in the United States, as well as in other leading economies (Germany, theUnited Kingdom, and Japan). |
| Date: | 2019–07–19 |
| URL: | http://d.repec.org/n?u=RePEc:clg:wpaper:2019-09&r=all |
| By: | Hitoshi Matsushima (University of Tokyo) |
| Abstract: | This study clarifies that blockchain cannot replace the strategic value of trusted intermediaries, despite sufficient technological advancement for its implementation. Given the progress expected in the future, this study assumes that blockchain can implement various commitment devices for communication explored in the information design literature, without disclosing their details to anonymous record keepers. By considering revelation incentives explicitly, we show that substituting the verification task of players’ pre-owned private signals with a trusted intermediary can reduce transaction costs in liability, which cannot be achieved non-judicially by blockchain. Hence, trusted intermediaries play a significant role in executing information design through blockchain. |
| Date: | 2019–07 |
| URL: | http://d.repec.org/n?u=RePEc:cfi:fseres:cf462&r=all |
| By: | Geoff Boeing |
| Abstract: | As the rental housing market moves online, the Internet offers divergent possible futures: either the promise of more-equal access to information for previously marginalized homeseekers, or a reproduction of longstanding information inequalities. Biases in online listings' representativeness could impact different communities' access to housing search information, reinforcing traditional information segregation patterns through a digital divide. They could also circumscribe housing practitioners' and researchers' ability to draw broad market insights from listings to understand rental supply and affordability. This study examines millions of Craigslist rental listings across the US and finds that they spatially concentrate and over-represent whiter, wealthier, and better-educated communities. Other significant demographic differences exist in age, language, college enrollment, rent, poverty rate, and household size. Most cities' online housing markets are digitally segregated by race and class, and we discuss various implications for residential mobility, community legibility, gentrification, displacement, housing voucher utilization, and automated monitoring and analytics in the smart cities paradigm. While Craigslist contains valuable crowdsourced data to better understand affordability and available rental supply in real-time, it does not evenly represent all market segments. The Internet promises information democratization, and online listings can reduce housing search costs and increase choice sets. However, technology access/preferences and information channel segregation can concentrate such information-broadcasting benefits in already-advantaged communities, reproducing traditional inequalities and reinforcing residential sorting and segregation dynamics. Technology platforms construct new institutions with the power to shape spatial economies and human interactions. |
| Date: | 2019–07 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1907.06118&r=all |
| By: | Dilger, Alexander; Klus, Milan F. |
| Abstract: | Digitalisation has opened up new opportunities for the dissemination of information. That is why many academic journals have started introducing online services since the early 1990s. Previous studies suggest that online availability and free access to articles are positively connected to the number of citations. However, little is known about the relative impact of the introduction of online services at the journal level and what provides a long-term competitive advantage in times of digital change. Based on panel data from SSCI-listed management journals from 1989 to 2016, we examine which journals have pioneered the digital field, to what extent first-mover advantages can be identified, and which journal characteristics are associated with citation-based performance indicators. Our results show that lower-ranked journals were the first to introduce digital services and were beneficiaries of the digital age. Furthermore, we find a significant connection between the international composition of author teams and performance indicators. Our analysis of the relationship between online availability as well as open access and performance contradicts previous studies as we find that significant correlations diminish when adequately controlling for journal-level effects. |
| JEL: | I23 L82 L86 M21 O33 |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:umiodp:62019&r=all |
| By: | Songül Tolan (European Commission – JRC) |
| Abstract: | Machine learning algorithms are now frequently used in sensitive contexts that substantially affect the course of human lives, such as credit lending or criminal justice. This is driven by the idea that‘objective’ machines base their decisions solely on facts and remain unaffected by human cognitive biases, discriminatory tendencies or emotions. Yet, there is overwhelming evidence showing that algorithms can inherit or even perpetuate human biases in their decision making when they are based on data that contains biased human decisions. This has led to a call for fairness-aware machine learning. However, fairness is a complex concept which is also reflected in the attempts to formalize fairness for algorithmic decision making. Statistical formalizations of fairness lead to a long list of criteria that are each flawed (or harmful even) in different contexts. Moreover,inherent tradeoffs in these criteria make it impossible to unify them in one general framework. Thus,fairness constraintsin algorithms have to be specific to the domains to which the algorithms are applied. In the future, research in algorithmic decision making systems should be aware of data and developer biases and add a focus on transparency to facilitate regular fairness audits. |
| Keywords: | fairness, machine learning, algorithmic bias, algorithmic transparency |
| Date: | 2018–12 |
| URL: | http://d.repec.org/n?u=RePEc:ipt:decwpa:2018-10&r=all |
| By: | Wei Cui; Nigar Hashimzade |
| Abstract: | In 2018, the European Council and the UK and Spanish governments each proposed to introduce a Digital Services Tax (DST), to be levied on the revenue of large digital platforms from advertising, online intermediation, and/or the transmission of data. We offer a rationalization of the DST as a tax on location-specific rent (LSR). That is, just as many countries already levy royalties on rent from extracting natural resources, one can think of the DST as levied on rent earned by digital platforms from particular locations. We provide stylized illustrations of how platform rent can be assigned to specific locations, even when users from multiple jurisdictions participate. We then elaborate the analogy between the DST and resource royalties, and analyze the DST’s incidence and effect on consumer welfare using a simple model. Finally, we argue that the DST suggests useful directions for redesigning international taxation in the age of labor-replacing AI technology. |
| Keywords: | digital services tax, international taxation, location-specific rent, digital platforms |
| JEL: | H25 K34 M37 M48 |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_7737&r=all |
| By: | Nelson, Jonathan K. (Syracuse University Florence and Harvard Kennedy School); Zeckhauser, Richard (Harvard Kennedy School) |
| Abstract: | Portraits served as a form of social media in the Renaissance. Prominent individuals commissioned portraits to convey their accomplishments and relationships, not merely their images. Political and church leaders, in particular, used the images to bolster their role, but these commissioned works entailed risks, importantly including risks to reputation. A portrait could be unflattering or unrecognizable. It could also be judged to be indecorous, especially if the portrait was perceived as an attempt to elevate an individual above his or her station. |
| Date: | 2019–07 |
| URL: | http://d.repec.org/n?u=RePEc:ecl:harjfk:rwp19-024&r=all |
| By: | Pogorelskiy, Kirill (University of Warwick); Shum, Matthew (Caltech) |
| Abstract: | More voters than ever get political news from their friends on social media platforms. Is this bad for democracy? Using context-neutral laboratory experiments, we find that biased (mis)information shared on social networks affects the quality of collective decisions relatively more than does segregation by political preferences on social media. Two features of subject behavior underlie this finding: 1) they share news signals selectively, revealing signals favorable to their candidates more often than unfavorable signals; 2) they na¨ively take signals at face value and account for neither the selection in the selection in the shared signals nor the differential informativeness of news signals across different sources. |
| Keywords: | news sharing, social networks, voting, media bias, fake news, polarization, filter bubble, lab experiments JEL Classification: C72, C91, C92, D72, D83, D85 |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:cge:wacage:427&r=all |
| By: | Marc Gronwald |
| Abstract: | This paper deals with cryptocurrency bubbles. First, it points out that a number of recent papers on cryptocurrency bubbles are awed due to an insufficient consideration of the fundamental value of cryptocurrencies. As even fiat money is said to exhibit features of bubbles, the same applies to cryptocurrencies. Thus, any empirical investigation into either the presence of cryptocurrency bubbles or the fundamental value of cryptocurrencies is needless. Second, the paper conducts a short empirical analysis into the relationship of the prices of Etherum and Bitcoin. Evidence of explosive periods is found in the price of Etherum even if this price is expressed in terms of Bitcoin rather than US Dollars. These periods, however, are found to be in the first half of 2016 and 2017, respectively, but not during the price peak period of Bitcoin witnessed end of 2017 and beginning of 2018. |
| Keywords: | cryptocurrencies, bubbles, bitcoin, Etherum, fundamental value, intrinsic value, fiat money |
| JEL: | C12 C22 E42 E52 G12 |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_7743&r=all |
| By: | Ryan Hawthorne; Lukasz Grzybowski |
| Abstract: | We test for the distributional effects of regulation and entry in the mobile telecommunications sector in a highly unequal country, South Africa. Using six waves of a consumer survey of over 134,000 individuals between 2009-2014, we estimate a discrete-choice model allowing for individual-specific price-responsiveness and preferences for network operators. Next, we use a demand and supply equilibrium framework to simulate prices and the distribution of welfare without entry and mobile termination rate regulation. We find that regulation benefits consumers significantly more than entry does, and that high-income consumers and city-dwellers benefit more in terms of increased consumer surplus. |
| Keywords: | mobile telecommunications, competition, entry, discrete choice, inequality |
| JEL: | L13 L40 L50 L96 |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_7703&r=all |
| By: | Schwab, Jakob; Ohnesorge, Jan |
| Abstract: | Blockchain technology (BT), famous due to its use in digital currencies, also offers new opportunities in other fields, one of which is trade integration. Developing countries especially could benefit from greater trade integration with BT, as the technology can, for example, remedy deficiencies with regard to financial system access, intellectual property protection and tax administration. BT allows virtually tamper-proof storage of transactions and other data on decentralised computer networks. In fact, it is possible to store not only data, but also entire programmes this securely: Smart contracts enable the automation of private transactions and administrative processes. This article summarises the latest research on the use of BT in trade integration by examining in more detail five key and, in some cases, linked fields of application. The first is trade finance, where BT could deliver direct cost savings for exporters and importers by removing the need for credit-lending intermediaries. Second, tamper-proof storage of information on the origin and composition of goods could enhance supply chain documentation. This makes it possible to more reliably verify compliance with sustainability standards, particularly for globally produced goods. However, for the information in blockchains to be truthful, it must be entered correctly (it is then tamperproof), a process that therefore requires monitoring. Third, BT could deliver improvements in the field of trade facilitation by making it easier for border authorities to access information on goods and thus easing reporting requirements for exporting firms. By reducing dependence on central database operators, BT could help bring about a breakthrough with existing digital technology in the area of trade. Fourth, facilitating access to information on goods could also simplify customs and taxation procedures and make them less vulnerable to corruption and fraud. This goes hand in hand with cost reductions for exporters and better mobilisation of domestic resources for public budgets. Fifth, in the field of digital trade, BT also facilitates management of digital file rights in environments where, for institutional reasons, there is little intellectual property protection. This could help to promote digital industries in developing countries. However, when it comes to using BT in border and customs systems in particular, it is essential to involve the relevant authorities at an early stage. At the same time, it is necessary to promote uniform technical standards for supply chain documentation in order to safeguard interoperability between the different systems across actors and national borders and thus fully leverage the cost advantages. If these guidelines are taken into account, then BT could effectively support sustainable trade integration of developing countries. |
| Keywords: | Digitalisierung,Handel und Investitionen |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:diebps:42019&r=all |
| By: | Etumnu, Chinonso E.; Foster, Kenneth A.; Widmar, Nicole Olynk; Lusk, Jayson L.; Ortega, David L. |
| Keywords: | Marketing |
| Date: | 2019–06–25 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea19:290858&r=all |
| By: | Filippo Belloc |
| Abstract: | Thanks to algorithmic management, the digital platform sector does not require sophisticated governance structures and labour intensity tends to be higher than in traditional sectors. So, why aren’t usually digital labour platforms worker cooperatives? We develop a simple model to study the comparative viability of a worker-managed (WM) via-app labour platform firm vis-à-vis a capital-managed (CM) counterpart. Firms compete over workers by choosing the optimal size and (CM firms only) the pay policy. Given the size of the market, we show that WM platforms maximize per-capita incomes over a middle range interval of firm size. At the equilibrium size, viability of WM firms may be impeded by the costs of the external capital, no matter how low, which enable CM firms to pay a wage premium. The worker payoff in CM firms is higher in the presence of higher unit revenues and network effects (which improve the ability to pay of WM firms, thereby stimulating pay competition between platforms) and lower when WM platforms need to charge new members a fee to overcome free-riding problems faced by those who fund the initial investment. The model also shows that the conditions for worker buyouts are weaker than those required for WM platform creation from scratch, and that group incentive mechanisms allow WM platforms to better pursue quality improvements than CM firms, when digital techniques make the cost of effort relatively low. |
| Keywords: | labour platforms, via-app work, worker-managed firms |
| JEL: | J54 L22 P13 |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_7708&r=all |
| By: | David Easley (Cornell University; Cornell University and EIEF); Christopher Rojas (Cornell University) |
| Abstract: | We develop a dynamic matched sample estimation algorithm to distinguish peer influence and homophily effects on item adoption decisions in dynamic networks, with numerous items diffusing simultaneously. We infer preferences using a machine learning algorithm applied to previous adoption decisions, and we match agents using those inferred preferences. We show that ignoring previous adoption decisions leads to significantly overestimating the role of peer influence in the diffusion of information, mistakenly confounding influence-based contagion with diffusion driven by common preferences. Our matching-on-preferences algorithm with machine learning reduces the relative effect of peer influence on item adoption decisions in this network significantly more than matching on earlier adoption decisions, as well other observable characteristics. We also show significant and intuitive heterogeneity in the relative effect of peer influence. |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:eie:wpaper:1912&r=all |
| By: | Cheng, Wallace; Brandi, Clara |
| Abstract: | Digitalisation is transforming the economy and redefining trade. Recently, members of the World Trade Organization (WTO) have started to discuss how trade policies and rules should be adapted to address this transformation. For example, in January 2019, 76 WTO members announced the launch of “negotiations on trade-related aspects of electronic commerce”. The scope of these e-commerce negotiations is yet to be defined, but to ban tariffs on electronic transmissions will certainly be on the priority list of WTO members such as the United States (US) and the European Union (EU). The idea of banning tariffs on electronic transmission originated at the WTO’s Ministerial Conference (MC) in 1998, when Members declared that they would “continue their current practice of not imposing customs duties on electronic transmissions”. This temporary moratorium on e-commerce tariffs needs to be regularly extended, requiring a decision made “by consensus”. Members have repeatedly extended the moratorium on tariffs on “electronic transmissions”, most recently at the latest WTO MC in 2017. But the WTO e-commerce moratorium is increasingly disputed: First, while net exporters of digital products and services, typically industrialised countries, understand the tariff ban to apply to digital content, net importers interpret it as referring only to electronic carriers (e.g. CDs, electronic bits), which means that they regard themselves as permitted to impose customs duties on the content of online trade. Second, while net exporters like the US and the EU propose a permanent ban on e-commerce tariffs in order to provide greater certainty to consumers and business, arguing that the resulting revenue losses are small, net importers like India and South Africa underline that they suffer much greater revenue losses than industrialised countries and have to bear the brunt of the moratorium. Third, while industrialised countries argue that the ban on tariffs on electronic transmissions would reduce market distortions, developing countries are concerned that a permanent moratorium would limit their options to protect domestic products and services traded online. Fourth, the moratorium has stirred a debate about how to create a level playing field between domestic and foreign suppliers of digital products and services. We argue that WTO members should take the ongoing debate as an opportunity for the WTO to play an important role in redefining trade in a digitalised economy. To take up this challenge, we recommend the following: (a) WTO Members should seek agreement on what the e-commerce tariff moratorium covers and what it does not. (b) Concerns about who wins and who loses in the wake of the moratorium require deep-dive reflections. WTO members should thus not rush to make the moratorium permanent. They should consider extending it for (at least) another two years at MC12 and use this time to prepare a fully fledged agreement to replace the temporary decision and which could be called the Agreement on Digital Products and Other Services (ADPOS). (c) The WTO secretariat should actively engage in the ongoing broader discussions about taxation in the digitalised economy. New evolutions of international and national tax reforms and data-driven digital trade offer unprecedented opportunities for the WTO to reshape the trade agenda. But the WTO may be left behind in addressing the future of trade in a digitalised economy if it does not respond strategically. |
| Keywords: | Digitalisierung,Handel und Investitionen |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:diebps:62019&r=all |
| By: | Nashihah, Faidatun |
| Abstract: | This article explains the problems in the development and management of cash waqf in Indonesia. Cash waqf by people, groups of people, and institutions or legal entities in the form of cash. Waqf cash is still debated among scholars whether it is legal or not, and managing cash waqf professionally is still a discourse and not many people or institutions can accept such waqf models. This article also discusses understanding, legal basis, problematics, management and solutions. Also discussed about cash waqf as the basis for community economic development by opening up Muslim rigidity to cash waqf, as well as the economic prospects of waqf property. The potential of waqf is one of the instruments of economic empowerment for Muslims even though management in Indonesia is still not good. But seen from the number, waqf property in Indonesia is quite large. Money waqf has played an important role as one of the new Islamic fiscal instruments in the economy. Money waqf has two functions as a means of worship and the achievement of social welfare. This article tries to explore how the problems in developing money waqf management such as the way it is distributed and its circulation and how the waqf is able to have a good impact on the surrounding community. |
| Keywords: | Problems, Development, Management, Cash Waqf, Indonesia. |
| JEL: | A10 G00 G23 G24 H00 P4 P43 |
| Date: | 2019–07–10 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:95176&r=all |
| By: | Bucci, Andrea |
| Abstract: | Accurately forecasting multivariate volatility plays a crucial role for the financial industry. The Cholesky-Artificial Neural Networks specification here presented provides a twofold advantage for this topic. On the one hand, the use of the Cholesky decomposition ensures positive definite forecasts. On the other hand, the implementation of artificial neural networks allows to specify nonlinear relations without any particular distributional assumption. Out-of-sample comparisons reveal that Artificial neural networks are not able to strongly outperform the competing models. However, long-memory detecting networks, like Nonlinear Autoregressive model process with eXogenous input and long shortterm memory, show improved forecast accuracy respect to existing econometric models. |
| Keywords: | Neural Networks; Machine Learning; Stock market volatility; Realized Volatility |
| JEL: | C22 C45 C53 G17 |
| Date: | 2019–07 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:95137&r=all |
| By: | Banga Karishma |
| Abstract: | This paper examines whether digitalization can be a driver of ‘upgrading’ in global value chains and help developing countries move into higher value-added activities. In particular, the paper provides empirical evidence on the impact of digital capabilities on product upgrading in Indian manufacturing firms participating in global value chains.Empirical analysis is undertaken on a panel of global value chain manufacturing firms in the period 2001–15, using the methodology of system generalized method-of-moments. Product upgrading is captured through a novel sales-weighted average product sophistication indicator at the firm level, while principal component analysis is used to construct a digital capability index that draws information on both ‘hard’ and ‘soft’ digital assets of the firm. Empirical results suggest that an increase in digital capability of the firm has a significant and positive impact on its product sophistication, other things being constant.Firms with both high levels of digital capability and share of skilled labour are observed to have roughly 4–5 per cent higher product sophistication than firms with low levels of digital capability and skills. In addition, lagged product sophistication, size, industry concentration, and to some extent R&D, are also found to have a positive and significant impact on product sophistication of Indian global value chain firms.The paper further attempts to tie these empirical results to the global value chain governance literature, and advances the nexus of governance and digitalization as a key area of global value chain research. |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:unu:wpaper:wp-2019-43&r=all |
| By: | Paech, Philipp |
| Abstract: | Since the emergence of the virtual currency Bitcoin in 2009, a new, Internet-based way of recording entitlements and enforcing rights has increasingly captured the interest of businesses and governments. The technology is commonly called ‘blockchain’ and is often associated with a closely related phenomenon, the ‘smart contract’. The market is now exploring ways of using these concepts for financial assets, such as securities, legal tender and derivative contracts. This article develops a conceptual framework for the governance of blockchain-based networks in financial markets. It constructs a vision of how financial regulation and private law should set the boundaries of this new technology in order to protect market participants and societies at large, while at the same time allowing for the necessary room for innovation. |
| Keywords: | blockchain technology; Fintech; financial assets; financial regulation; private law; private international law |
| JEL: | F3 G3 |
| Date: | 2017–11–20 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:80440&r=all |
| By: | Melia, Elvis |
| Abstract: | In the past two decades, Africa has experienced a wave of mobile telephony and the early stages of internet connectivity. This paper summarises recent empirical research findings on the impact that information and communication technologies (ICTs) have had on jobs in Africa, be it in creating new jobs, destroying old jobs, or changing the quality of existing jobs in levels of productivity, incomes, or working conditions. The paper discusses various channels in which ICTs can impact jobs: In theory, they have the potential to allow for text-based services platforms that can help farmers and small and medium-sized enterprises (SMEs) become more productive or receive better access to market information; mobile money has the potential to allow the most vulnerable workers more independence and security; and the internet could allow women, in particular, to increase their incomes and independence. This literature review examines what rigorous empirical evidence actually exists to corroborate these claims. Most of the studies reviewed do indeed find positive effects of ICTs on jobs (or related variables) in Africa. On the basis of these findings, the paper reviews policy options for those interested in job creation in Sub-Saharan Africa. The paper concludes by highlighting that these positive findings may exist in parallel with negative structural dynamics that are more difficult to measure. Also, the review’s findings - while positive across the board - should be seen as distinct for ICTs in the period of the 2000s and 2010s, and cannot easily be transferred to expect similarly positive effects of the much newer, Fourth Industrial Revolution Technologies (such as machine learning, blockchain technologies, big data analytics, platform economies), which may produce entirely different dynamics. |
| Keywords: | Digitalisierung |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:diedps:32019&r=all |
| By: | Alexis Bogroff (University Paris 1 Panthéon-Sorbonne); Dominique Guégan (University Paris 1 Panthéon-Sorbonne; labEx ReFi France; University Ca’ Foscari Venice) |
| Abstract: | An extensive list of risks relative to big data frameworks and their use through models of artificial intelligence is provided along with measurements and implementable solutions. Bias, interpretability and ethics are studied in depth, with several interpretations from the point of view of developers, companies and regulators. Reflexions suggest that fragmented frameworks increase the risks of models misspecification, opacity and bias in the result. Domain experts and statisticians need to be involved in the whole process as the business objective must drive each decision from the data extraction step to the final activatable prediction. We propose an holistic and original approach to take into account the risks encountered all along the implementation of systems using artificial intelligence from the choice of the data and the selection of the algorithm, to the decision making. |
| Keywords: | Artificial Intelligence, Bias, Big Data, Ethics, Governance, Interpretability, Regulation, Risk |
| JEL: | C4 C5 C6 C8 D8 G28 G38 K2 |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:ven:wpaper:2019:19&r=all |
| By: | Asongu, Simplice A; Odhiambo, Nicholas M |
| Abstract: | The research assesses how information and communication technology (ICT) modulates the effect of foreign direct investment (FDI) on economic growth dynamics in 25 countries in Sub-Saharan Africa for the period 1980-2014. The employed economic growth dynamics areGross Domestic Product (GDP) growth, real GDP and GDP per capita while ICT is measured by mobile phone penetration and internet penetration. The empirical evidence is based on the Generalised Method of Moments. The study finds that both internet penetration and mobile phone penetration overwhelmingly modulate FDI to induce overall positive net effects on all three economic growth dynamics. Moreover, the positive net effects are consistently more apparent in internet-centric regressions compared to ???mobile phone???-oriented specifications. In the light of negative interactive effects, net effects are decomposed to provide thresholds at which ICT policy variables should be complemented with other policy initiatives in order to engender favorable outcomes on economic growth dynamics. Practical and theoretical implications are discussed. |
| Keywords: | Economic Output; Foreign Investment; Information Technology; Sub-Saharan |
| Date: | 2019–07 |
| URL: | http://d.repec.org/n?u=RePEc:uza:wpaper:25593&r=all |
| By: | 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 compare the ability of two measures of uncertainty, a newspaper-based measure and an internet search-based measure, to predict Bitcoin returns. Using monthly data from July 2010 to May 2019 and a predictive regression model characterized by a heteroskedastic error structure and, we show that Bitcoin is a hedge against both measures. However, the predictive content of the internet-derived uncertainty related queries measure is statistically stronger than the measure of uncertainty based on newspapers for predicting Bitcoin returns, which is possibly due to the fact that the measure of uncertainty is now directly obtained from individual investors via internet searches. |
| Keywords: | Bitcoin, Hedging, Predictability, Economic Uncertainty |
| JEL: | C32 G12 |
| Date: | 2019–07 |
| URL: | http://d.repec.org/n?u=RePEc:pre:wpaper:201955&r=all |
| By: | Zhenqian Huang (Macroeconomic Policy and Financing for Development Division, United Nations Economic and Social Commission for Asia and the Pacific); Lena Kaiser (Macroeconomic Policy and Financing for Development Division, United Nations Economic and Social Commission for Asia and the Pacific) |
| Abstract: | Technological advancements bring both opportunities and challenges for taxation policy. Although they improve revenue raising and efficiency of spending, to fully harness such benefits requires concerted national and international efforts. Asian and Pacific economies are at the forefront in reforming taxation policies in a digital era to counter under- or double-taxation. |
| Date: | 2019–07 |
| URL: | http://d.repec.org/n?u=RePEc:unt:pbmpdd:pb102&r=all |
| By: | Kang, Kee-Youn |
| Abstract: | We develop a general equilibrium model of cryptocurrency to study the optimal design of a cryptocurrency system. Agents trade cryptocurrency using digital wallets, and the cryptocurrency system provides verification of a digital wallet’s history of double spending attempts. Delaying the delivery of goods until payment information is confirmed in the blockchain prevents double spending. However, double spending can be prevented without a delivery lag under some conditions if a wallet has a good reputation in terms of its history of double spending attempts. In particular, as the difficulty of mining work rises, the incentive to engage in double spending with a good wallet decreases. We study the optimal design of the cryptocurrency system in terms of the difficulty of mining work and the supply of cryptocurrency and evaluate the welfare gain that would be captured if the current Bitcoin system adopted the optimal cryptocurrency system. |
| Keywords: | Blockchain, Cryptocurrency, Delivery lag, Double spending, Trade history |
| JEL: | D86 E40 E50 G10 |
| Date: | 2019–05–06 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:93598&r=all |
| By: | J. M. Calabuig; H. Falciani; E. A. S\'anchez-P\'erez |
| Abstract: | We develop a new topological structure for the construction of a reinforcement learning model in the framework of financial markets. It is based on Lipschitz type extension of reward functions defined in metric spaces. Using some known states of a dynamical system that represents the evolution of a financial market, we use our technique to simulate new states, that we call ``dreams". These new states are used to feed a learning algorithm designed to improve the investment strategy. |
| Date: | 2019–07 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1907.05697&r=all |
| By: | Brummelhuis, Raymond; Luo, Zhongmin |
| Abstract: | The 2007-09 financial crisis revealed that the investors in the financial market were more concerned about the future as opposed to the current capital adequacy for banks. Stress testing promises to complement the regulatory capital adequacy regimes, which assess a bank's current capital adequacy, with the ability to assess its future capital adequacy based on the projected asset-losses and incomes from the forecasting models from regulators and banks. The effectiveness of stress-test rests on its ability to inform the financial market, which depends on whether or not the market has confidence in the model-projected asset-losses and incomes for banks. Post-crisis studies found that the stress-test results are uninformative and receive insignificant market reactions; others question its validity on the grounds of the poor forecast accuracy using linear regression models which forecast the banking-industry incomes measured by Aggregate Net Interest Margin. Instead, our study focuses on NIM forecasting at an individual bank's level and employs both linear regression and non-linear Machine Learning techniques. First, we present both the linear and non-linear Machine Learning regression techniques used in our study. Then, based on out-of-sample tests and literature-recommended forecasting techniques, we compare the NIM forecast accuracy by 162 models based on 11 different regression techniques, finding that some Machine Learning techniques as well as some linear ones can achieve significantly higher accuracy than the random-walk benchmark, which invalidates the grounds used by the literature to challenge the validity of stress-test. Last, our results from forecast accuracy comparisons are either consistent with or complement those from existing forecasting literature. We believe that the paper is the first systematic study on forecasting bank-specific NIM by Machine Learning Techniques; also, it is a first systematic study on forecast accuracy comparison including both linear and non-linear Machine Learning techniques using financial data for a critical real-world problem; it is a multi-step forecasting example involving iterative forecasting, rolling-origins, recalibration with forecast accuracy measure being scale-independent; robust regression proved to be beneficial for forecasting in presence of outliers. It concludes with policy suggestions and future research directions. |
| Keywords: | Regression, Machine Learning, Time Series Analysis, Bank Capital, Stress Test, Net Interest Margin, Forecasting, PPNR, CCAR |
| JEL: | C4 C45 C5 C58 C6 G01 |
| Date: | 2019–03–02 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:94779&r=all |
| By: | Bakari, Sayef |
| Abstract: | We analyze the relationship between economic growth and innovation taking into consideration the importance of the internet. To do so, we use a panel ARDL model, with data on a sample of 76 developed and developing countries in different geographic regions for the 1995–2016 period. Our findings provide empirical evidence of the positive role of innovation and internet in economic growth and the positive role of economic growth and internet in innovation. From these results, we derive several basic policy conclusions. |
| Keywords: | Innovation, Economic Growth, Internet |
| JEL: | O31 O32 O38 O47 O50 |
| Date: | 2019–06 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:94851&r=all |
| By: | Belloc, Filippo |
| Abstract: | We study hours worked by drivers in the peer-to-peer transportation sector with cross-side network effects. Medallion lease (regulated market), commission-based (Uber-like pay) and profit-sharing ("pure" taxi coop) compensation schemes are compared. Our static model shows that network externalities matter, depending on the number of active drivers. When the number of drivers is limited, in the presence of positive network effects, a regulated system always induces more hours worked, while the commission fee influences the comparative incentives towards effort of Uber-like pay versus profit-sharing. When the number of drivers is infinite (or close to it), the influence of network externalities on optimal effort vanishes. |
| Keywords: | Uber, network effects, ride-sharing, pay schemes, effort, taxi industry |
| JEL: | J22 J33 L91 |
| Date: | 2019–06–27 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:95179&r=all |
| By: | Felix Ritchie; Jim Smith |
| Abstract: | Data providers such as government statistical agencies perform a balancing act: maximising information published to inform decision-making and research, while simultaneously protecting privacy. The emergence of identified administrative datasets with the potential for sharing (and thus linking) offers huge potential benefits but significant additional risks. This article introduces the principles and methods of linking data across different sources and points in time, focusing on potential areas of risk. We then consider confidentiality risk, focusing in particular on the "intruder" problem central to the area, and looking at both risks from data producer outputs and from the release of micro-data for further analysis. Finally, we briefly consider potential solutions to micro-data release, both the statistical solutions considered in other contributed articles and non-statistical solutions. |
| Date: | 2019–07 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1907.06465&r=all |