|
on Payment Systems and Financial Technology |
|
Issue of 2019‒11‒25
29 papers chosen by |
| By: | Rudolf Kerschbamer; Daniel Neururer; Matthias Sutter |
| Abstract: | Credence goods markets are characterized by pronounced informational asymmetries between consumers and expert sellers. As a consequence, consumers are often exploited and market efficiency is threatened. However, in the digital age, it has become easy and cheap for consumers to self-diagnose their needs using specialized webpages or to access other consumers’ reviews on social media platforms in search for trustworthy sellers. We present a natural field experiment that examines the causal effect of information acquisition from new media on the level of sellers’ price charges for computer repairs. We find that even a correct self-diagnosis of a consumer about the appropriate repair does not reduce prices, and that an incorrect diagnosis more than doubles them. Internet ratings of repair shops are a good predictor of prices. However, the predictive valued of reviews depends on whether they are judged as reliable or not. For reviews recommended by the platform Yelp we find that good ratings are associated with lower prices and bad ratings with higher prices, while non-recommended reviews have a clearly misleading effect, because non-recommended positive ratings increase the price. |
| Keywords: | credence goods, fraud, information acquisition, internet, field experiment |
| JEL: | C93 D82 |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_7932&r=all |
| By: | Yannick LUNG; Léo MALHERBE; Matthieu MONTALBAN; ; ; |
| Abstract: | In less than 10 years, \"complementary local currencies\" have multiplied in France and have created a dynamic ecosystem. While almost all of them have developed with the introduction of paper money (notes), there is now a rapid shift towards digital tools, which for many analysts appears to be an essential factor in moving to a new stage in the development of these currencies. \r\nIn part one, the paper will discuss the challenges of this transition and the competitive/complementary relationships between local currencies and cryptocurrencies in the French context. The second part will study the strategies of actors to position themselves in the ongoing reconfiguration of the ecosystem. It will study the competition between digital solutions being adopted by complementary local currencies and consider the possibility of a new generation of local currencies in France through the emergence of FinTech players. |
| Keywords: | blockchain - complementary local currency – cryptocurrency – digitization – france |
| JEL: | E42 L31 O33 |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:grt:wpegrt:2019-14&r=all |
| By: | Brainard, Lael (Board of Governors of the Federal Reserve System (U.S.)) |
| Date: | 2019–10–16 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedgsq:1095&r=all |
| By: | Saman Adhami (VGSF - Vienna Graduate School of Finance); Dominique Guegan (UP1 - Université Panthéon-Sorbonne, CES - Centre d'économie de la Sorbonne - CNRS - Centre National de la Recherche Scientifique - UP1 - Université Panthéon-Sorbonne, University of Ca’ Foscari [Venice, Italy], UEH - University of Economics Ho Chi Minh City) |
| Abstract: | This paper reexamines the discussion on blockchain technology, crypto assets and ICOs, providing also evidence that in crypto markets there are currently two classes of assets, namely standalone cryptocurrencies (or 'coins') and tokens, which result from an ICO and are intrinsically linked to the performance of the issuing company or venture. While the former have been arguments of various empirical studies regarding their price dynamics and their effect on the variance of a well-diversified portfolio, no such study has been done to analyze listed tokens, which in our sample are over 700 and with a backing of about $17.3Bn from their respective ICOs. Therefore, investors interested in optimizing their portfolios should first assess the diversifier, hedge or safe haven role of tokens vis-à-vis traditional assets, on top of 'coins', in order to sensibly use this new asset class. After constructing various indices to represent both the token asset class as a whole and its sub-classes, we model dynamic conditional correlations among all the assets in our sample to obtain time-varying correlations for each token-asset pair. We find that tokens are effective diversifiers but not a hedge or a safe haven asset. We evidence that tokens retain important systematic differences with the two other asset classes to which they are most generally compared to, namely 'coins' and equities. |
| Keywords: | Cryptocurrency,Initial Coin Offering,DCC-MGARCH,Safe Haven,Hedge |
| Date: | 2019–09 |
| URL: | http://d.repec.org/n?u=RePEc:hal:cesptp:halshs-02353656&r=all |
| By: | Stanis{\l}aw Dro\.zd\.z; Ludovico Minati; Pawe{\l} O\'swi\k{e}cimka; Marek Stanuszek; Marcin W\k{a}torek |
| Abstract: | Cross-correlations in fluctuations of the daily exchange rates within the basket of the 100 highest-capitalization cryptocurrencies over the period October 1, 2015, through March 31, 2019, are studied. The corresponding dynamics predominantly involve one leading eigenvalue of the correlation matrix, while the others largely coincide with those of Wishart random matrices. However, the magnitude of the principal eigenvalue, and thus the degree of collectivity, strongly depends on which cryptocurrency is used as a base. It is largest when the base is the most peripheral cryptocurrency; when more significant ones are taken into consideration, its magnitude systematically decreases, nevertheless preserving a sizable gap with respect to the random bulk, which in turn indicates that the organization of correlations becomes more heterogeneous. This finding provides a criterion for recognizing which currencies or cryptocurrencies play a dominant role in the global crypto-market. The present study shows that over the period under consideration, the Bitcoin (BTC) predominates, hallmarking exchange rate dynamics at least as influential as the US dollar. The BTC started dominating around the year 2017, while further cryptocurrencies, like the Ethereum (ETH) and even Ripple (XRP), assumed similar trends. At the same time, the USD, an original value determinant for the cryptocurrency market, became increasingly disconnected, its related characteristics eventually approaching those of a fictitious currency. These results are strong indicators of incipient independence of the global cryptocurrency market, delineating a self-contained trade resembling the Forex. |
| Date: | 2019–11 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1911.08944&r=all |
| By: | Steven Engels; Monika Sherwood |
| Abstract: | This paper explores the increasing diffusion of digital labour platforms, i.e. online software which facilitates the interaction between buyers and sellers of paid labour services through matching algorithms and structured information exchange. Although the phenomenon itself has only recently started to develop, its prevalence is rapidly increasing. We illustrate the various forms digital labour platforms can take, frame the issues they raise in the broader debate on digitalisation and succinctly describe the various angles from which the Commission services have so far approached digital labour platforms in analytical and policy work. The paper also explores the impact the rapid growth of the considered platforms could potentially have on the wider economy and raises three sets of relevant economic policy questions, focusing on: • the contribution of digital labour platforms to overall labour market functioning (including wages) and productivity; • the possible impact of digital labour platforms on macro-economic aggregates such as GDP and total employment at EU and Member State level; • the impact of the growing participation in the labour markets intermediated by online platforms on public finances. |
| JEL: | J01 E24 |
| Date: | 2019–06 |
| URL: | http://d.repec.org/n?u=RePEc:euf:dispap:099&r=all |
| By: | Jagtiani, Julapa (Federal Reserve Bank of Philadelphia); Lambie-Hanson, Lauren (Federal Reserve Bank of Philadelphia); Lambie-Hanson, Timothy (Federal Reserve Bank of Philadelphia) |
| Abstract: | Following the 2008 financial crisis, mortgage credit tightened and banks lost significant mortgage market share to nonbank lenders, including to fintech firms recently. Have fintech firms expanded credit access, or are their customers similar to those of traditional lenders? Unlike in small business and unsecured consumers lending, fintech mortgage lenders do not have the same incentives or flexibility to use alternative data for credit decisions because of stringent mortgage origination requirements. Fintech loans are broadly similar to those made by traditional lenders, despite innovations in the marketing and the application process. However, nonbanks market to consumers with weaker credit scores than do banks, and fintech lenders have greater market shares in areas with lower credit scores and higher mortgage denial rates. |
| Keywords: | fintech; mortgage lending; homeownership; online mortgages; credit access |
| JEL: | G20 G21 G28 R20 R30 |
| Date: | 2019–11–18 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedpwp:19-47&r=all |
| By: | Darius, Philipp; Stephany, Fabian |
| Abstract: | With a network approach, we examine the case of the German far-right party Alternative für Deutschland (AfD) and their potential use of a "hashjacking" strategy - the use of someone else’s hashtag in order to promote one's own social media agenda. Our findings suggest that right-wing politicians (and their supporters/retweeters) actively and effectively polarise the discourse not just by using their own party hashtags, but also by "hashjacking" the political party hashtags of other established parties. The results underline the necessity to understand the success of right-wing parties, online and in elections, not entirely as a result of external effects (e.g. migration), but as a direct consequence of their digital political communication strategy. |
| Date: | 2019–10–10 |
| URL: | http://d.repec.org/n?u=RePEc:osf:socarx:6gbc9&r=all |
| By: | Jamie Berryhill; Kévin Kok Heang; Rob Clogher; Keegan McBride |
| Abstract: | Artificial Intelligence (AI) is an area of research and technology application that can have a significant impact on public policies and services in many ways. In just a few years, it is expected that the potential will exist to free up nearly one-third of public servants’ time, allowing them to shift from mundane tasks to high-value work. Governments can also use AI to design better policies and make better decisions, improve communication and engagement with citizens and residents, and improve the speed and quality of public services. While the potential benefits of AI are significant, attaining them is not an easy task. Government use of AI trails that of the private sector; the field is complex and has a steep learning curve; and the purpose of, and context within, government are unique and present a number of challenges. |
| Date: | 2019–11–21 |
| URL: | http://d.repec.org/n?u=RePEc:oec:govaaa:36-en&r=all |
| By: | Funjika Patricia; Nsabimana Aimable |
| Abstract: | Access to mobile phone has increased substantially over the last decade in sub-Saharan Africa. The evidence suggests that increased use of mobile phones in the region has upgraded the market prices received by producers for their cash crops, but so far there is limited knowledge on labour market transitions effects of mobile phone access.In this study, we use farm household and individual labour force information, from LSMS-ISA Tanzania National Panel Survey, to examine the impact of mobile phone ownership on labour markets and farm productivity in the country. The study shows that successive increases in mobile phone use lead to movement of labour share from agriculture into non-farming sectors. The results also show that mobile phone access significantly reduces the intensity of work by household members on the farm and is instead associated with an increase in hired farm workers. Our results also show that mobile phone access has heterogeneous labour market effects, depending on the age of individuals.Given the important surge of information communication technology in sub-Saharan Africa, including Tanzania, the results suggest that using mobile phones to stimulate agricultural developments would improve marginal productivity of labour in the farming sector and induce a surge in off-farm employment opportunities. |
| Keywords: | Market prices,Mobile phones,Agricultural productivity,Tanzania |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:unu:wpaper:wp-2019-71&r=all |
| By: | Gaurav, Kumar; Ghosh, Sayantari; Bhattacharya, Saumik; Singh, Yatindra Nath |
| Abstract: | In marketing world, social media is playing a crucial role nowadays. One of the most recent strategies that exploit social contacts for the purpose of marketing, is referral marketing, where a person shares information related to a particular product among his/her social contacts. When this spreading of marketing information goes viral, the diffusion process looks like an epidemic spread. In this work, we perform a systematic study with a goal to device a methodology for using the huge amount of survey data available to understand customer behaviour from a more mathematical and quantitative perspective. We perform an unsupervised natural language processing based analysis of the responses of a recent survey focusing on referral marketing to correlate the customers’ psychology with transitional dynamics, and investigate some major determinants that regulate the diffusion of a campaign. In addition to natural language processing for topic modeling, detailed differential equation based analysis and graph theoretical treatment, experiments have been performed for generation of a recommendation network to understand the diffusion dynamics in homogeneous as well as heterogeneous population. A complete mathematical treatment with analysis over real social networks can help us to determine key customer motivations and their impacts on a marketing strategy, which are important to ensure an effective spread of a designed marketing campaign. Pointing out possibilities of extending these studies to game theoretic modeling, we prescribe a new quantitative framework that can find its application to all areas of social dynamics, beyond the field of marketing. |
| Date: | 2019–09–12 |
| URL: | http://d.repec.org/n?u=RePEc:osf:socarx:6spnr&r=all |
| By: | Moustafa, Khaled |
| Abstract: | The Internet has revolutionized the way knowledge is currently produced, stored and disseminated. A few finger clicks on a keyboard can save time and many hours of search in libraries or shopping in stores. Online trademarks with an (e-) prefix such as e-library, e-business, e-health etc., are increasingly part of our daily professional vocabularies. However, the Internet has also produced multiple negative side effects, ranging from an unhealthy dependency to a dehumanization of human relationships. Fraudulent, unethical and scam practices are also flourishing through for example misleading online advertising methods. Some social and professional networks gather users' profiles for selling and advertising purposes, sometimes by making it technically difficult to unsubscribe. Here, I discuss some of these unethical aspects and propose some potential solutions to reduce them. |
| Date: | 2018–05–27 |
| URL: | http://d.repec.org/n?u=RePEc:osf:arabix:3gv5e&r=all |
| By: | BELLEFLAMME Paul, (CORE, UCLouvain); PEITZ Martin, (Universität Mannheim) |
| Abstract: | We consider two-sided platforms with the feature that some users on one or both sides of the market lack information about the price charged to participants on the other side of the market. With positive cross-group external effects, such lack of pricie information makes demand less elastic. A monopoly platform does not benefit from opaqueness and optimality reveals price information. By contrast, in a two-sided singlehoming duopoly, platforms benefit from opaqueness and, thus, do not have an incentive to disclose price information. In competitive bottleneck markets, results are more nuanced: if one side is fully informed (for exogenous reasons), plaltforms may decide to inform users on the other side either fully, partially or not at all, depending on the strength of cross-group external effects and hte degree of horizontal differentiation. |
| Keywords: | price transparency, two-sided markets, competitive bottleneck, platform competition, price information, strategic disclosure |
| Date: | 2019–06–18 |
| URL: | http://d.repec.org/n?u=RePEc:cor:louvco:2019011&r=all |
| By: | Jelena Reljic; Rinaldo Evangelista; Mario Pianta |
| Abstract: | The diffusion of digital technologies and their impact on employment and skills is investigated in this article considering six major European countries (Germany, France, Spain, Italy, the Netherlands and the United Kingdom) and 42 manufacturing and service industries over the 2009-2014 period. We analyse two key dimensions of digitalisation - industries' consumption of intermediate inputs from digital-intensive sectors and investment in ICT tangible and intangible assets per employee. We first investigate their effect on total employment finding that job creation in industries is supported by high digital consumption and reduced by high digital investment. We then explore how these variables have shaped the evolution of four professional groups - Managers, Clerks, Craft and Manual workers, defined on the basis of ISCO classes - and the increasingly polarised skill structure of European economies. |
| Keywords: | Digital technology; Innovation; Employment; Skills; European industries. |
| Date: | 2019–11–13 |
| URL: | http://d.repec.org/n?u=RePEc:ssa:lemwps:2019/36&r=all |
| By: | Theodoros Pantelidis; Saeid Rasulkhani; Joseph Y. J. Chow |
| Abstract: | As Mobility as a Service (MaaS) systems become increasingly popular, travel is changing from unimodal trips to personalized services offered by a market of mobility operators. Traditional traffic assignment models ignore the interaction of different operators. However, a key characteristic of MaaS markets is that urban trip decisions depend on both user route decisions as well as operator service and pricing decisions. We adopt a new paradigm for traffic assignment in a MaaS network of multiple operators using the concept of stable matching to allocate costs and determine prices offered by operators corresponding to user route choices and operator service choices without resorting to nonconvex bilevel programming formulations. Unlike our prior work, the proposed model allows travelers to make multimodal, multi-operator trips, resulting in stable cost allocations between competing network operators to provide MaaS for users. Algorithms are proposed to generate stability conditions for the stable outcome pricing model. Extensive computational experiments demonstrate the use of the model, and effectiveness of the proposed algorithm, to handling pricing responses of MaaS operators in technological and capacity changes, government acquisition, consolidation, and firm entry, using the classic Sioux Falls network. |
| Date: | 2019–11 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1911.04435&r=all |
| By: | Edwards, Lilian; Veale, Michael |
| Abstract: | Cite as Lilian Edwards and Michael Veale, 'Slave to the Algorithm? Why a 'right to an explanation' is probably not the remedy you are looking for' (2017) 16 Duke Law and Technology Review 18–84. (First posted on SSRN 24 May 2017) Algorithms, particularly machine learning (ML) algorithms, are increasingly important to individuals’ lives, but have caused a range of concerns revolving mainly around unfairness, discrimination and opacity. Transparency in the form of a “right to an explanation” has emerged as a compellingly attractive remedy since it intuitively promises to “open the black box” to promote challenge, redress, and hopefully heightened accountability. Amidst the general furore over algorithmic bias we describe, any remedy in a storm has looked attractive. However, we argue that a right to an explanation in the EU General Data Protection Regulation (GDPR) is unlikely to present a complete remedy to algorithmic harms, particularly in some of the core “algorithmic war stories” that have shaped recent attitudes in this domain. Firstly, the law is restrictive, unclear, or even paradoxical concerning when any explanation-related right can be triggered. Secondly, even navigating this, the legal conception of explanations as “meaningful information about the logic of processing” may not be provided by the kind of ML “explanations” computer scientists have developed, partially in response. ML explanations are restricted both by the type of explanation sought, the dimensionality of the domain and the type of user seeking an explanation. However, “subject-centric" explanations (SCEs) focussing on particular regions of a model around a query show promise for interactive exploration, as do explanation systems based on learning a model from outside rather than taking it apart (pedagogical vs decompositional explanations ) in dodging developers' worries of IP or trade secrets disclosure. Based on our analysis, we fear that the search for a “right to an explanation” in the GDPR may be at best distracting, and at worst nurture a new kind of “transparency fallacy.” But all is not lost. We argue that other parts of the GDPR related (i) to the right to erasure ("right to be forgotten") and the right to data portability; and (ii) to privacy by design, Data Protection Impact Assessments and certification and privacy seals, may have the seeds we can use to make algorithms more responsible, explicable, and human-centred. |
| Date: | 2017–11–18 |
| URL: | http://d.repec.org/n?u=RePEc:osf:lawarx:97upg&r=all |
| By: | Newhart, Mary; Brooks, Joshua; Library, Cornell |
| Abstract: | Cornell e-Rulemaking Initiative Publications. 19. Rulemaking, the process through which United States (U.S.) federal government agencies develop major health, safety and economic regulations, was an early target of electronic government (e-government) efforts. Because it was an established decision-making process that had substantial formal requirements of transparency, public participation and responsiveness it seemed a perfect target for technology-supported participatory policymaking. It was believed that new technologies could transform rulemaking, increasing its democratic legitimacy and improving its policy outcomes by broadening the range of participating individuals and groups (Brandon and Carlitz, 2003; Coglianese, 2004; Noveck, 2004). Despite the promise of a more deliberative and democratic process, rulemaking efforts have failed to produce broader meaningful public engagement. In this paper we examine if lack of adoption of participatory eRulemaking platforms can be explained by the disruption to agencies’ established rulemaking practices. We will consider how agencies react to technological innovation as a risk due to their deep-rooted organizational cultures and the impact of judicial and political oversight. We will provide examples of agency risk and culture, including from our own experiences with RegulationRoom, a socio-technological participation platform that has facilitated public participation in six federal rulemakings. We will also draw on a comparison of for-profit businesses and rulemaking agencies in thinking about motivation to adopt (or avoid) new technologies. |
| Date: | 2018–01–09 |
| URL: | http://d.repec.org/n?u=RePEc:osf:lawarx:mzy2x&r=all |
| By: | Christoph March |
| Abstract: | Artificial intelligence (AI) is starting to pervade the economic and social life rendering strategic interactions with artificial agents more and more common. At the same time, experimental economic research has increasingly employed computer players to advance our understanding of strategic interaction in general. What can this strand of research teach us about an AI-shaped future? I review 90 experimental studies using computer players. I find that, in a nutshell, humans act more selfishly and more rational in the presence of computer players, and they are often able to exploit these players. Still, many open questions prevail. |
| Keywords: | experiment, robots, computer players, survey |
| JEL: | C90 C92 O33 |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_7926&r=all |
| By: | Stoehr, Niklas; Braesemann, Fabian; Zhou, Shi |
| Abstract: | The digital transformation is driving revolutionary innovations and new market entrants threaten established sectors of the economy such as the automotive industry. Following the need for monitoring shifting industries, we present a network-centred analysis of car manufacturer web pages. Solely exploiting publicly-available information, we con- struct large networks from web pages and hyperlinks. The network properties disclose the internal corporate positioning of the three largest automotive manufacturers, Toyota, Volkswagen and Hyundai with respect to innovative trends and their international outlook. We tag web pages concerned with topics like e-mobility & environment or autonomous driving, and investigate their relevance in the network. Toyota and Hyundai are concerned with e-mobility throughout large parts of their web page network; Volkswagen devotes more specialized sections to it, but reveals a strong focus on autonomous driving. Sentiment analysis on individual web pages uncovers a relationship between page linking and use of positive language, particularly with respect to innovative trends. Web pages of the same country domain form clusters of different size in the network that reveal strong correlations with sales market orientation. Our approach is highly transparent, reproducible and data driven, and could be used to gain complementary insights into innovative strategies of firms and competitive landscapes. |
| Date: | 2019–10–09 |
| URL: | http://d.repec.org/n?u=RePEc:osf:socarx:bu5zs&r=all |
| By: | Lips, Wouter |
| Abstract: | The EU Commission’s directive proposals on corporate taxation of digital multinationals, especially the digital services tax (DST), show the increased assertiveness of the Commission on taxation matters. Both inward and outwards in the parallel OECD negotiations on digital taxation. By drawing on Kingdon’s Multiple Streams Framework, elite interviews and policy documents, I assess the dynamics of the proposal at the EU and OECD. While the DST will fall short in the EU Council due to unanimity requirements, I argue that the Commission actually achieved its pre-prescribed goals. Within the EU, it provided coherency for unilateral DSTs by member states. At the OECD, the proposals increased the threat of uncoordinated unilateral measures. This created a period of uncertainty and pressured laggard states, which helped lead to a tentative window for reform. As such, the proposals are an example of cross-platform policy entrepreneurship by the EU Commission, projecting influence despite unanimity constraints. |
| Date: | 2019–10–09 |
| URL: | http://d.repec.org/n?u=RePEc:osf:socarx:k2t9j&r=all |
| By: | Matthieu Bellon; Jillie Chang; Era Dabla-Norris; Salma Khalid; Frederico Lima; Enrique Rojas; Pilar Villena |
| Abstract: | This paper examines the impact of e-invoicing on firm tax compliance and performance using administrative tax data and quasi-experimental variation in the rollout of VAT electronic invoicing in Peru. We find that e-invoicing increases reported firm sales, purchases and value-added by over 5 percent in the first year after adoption. The impact is concentrated among smaller firms and sectors with higher rates of non-compliance, suggesting that e-invoicing enhances compliance by lowering compliance costs and strengthening deterrence. The reform’s positive effects on tax collection are hindered by shortcomings in the VAT refund mechanism in Peru, suggesting that digital tools such as e-invoicing should be complemented by other reforms to improve revenue mobilization. |
| Date: | 2019–11–01 |
| URL: | http://d.repec.org/n?u=RePEc:imf:imfwpa:19/231&r=all |
| By: | Leonardo Madio; Carroni, Elias; Shekhar, Shiva |
| Abstract: | This article studies incentives for a premium provider (Superstar) to offer exclusive contracts to competing platforms mediating the interactions between consumers and firms. When platform competition is intense, more consumers affiliate with the platform favored by Superstar exclusivity. This mechanism is self-reinforcing as firms follow consumer decisions and some join the favored platform only. Exclusivity always benefits firms and might eventually benefit consumers. A vertical merger (platform-Superstar) makes non-exclusivity more likely than if the Superstar was independent. The analysis provides novel insights for managers and policymakers and it is robust to several variations and extensions. |
| JEL: | L13 L22 L86 K21 |
| Date: | 2019–10–10 |
| URL: | http://d.repec.org/n?u=RePEc:jmp:jm2019:pma2756&r=all |
| By: | Jeffrey Trossman (Blake, Cassels & Graydon LLP); Jeffrey Shafer (Blake, Cassels & Graydon LLP) |
| Keywords: | Fiscal and Tax Policy; Business and Capital Taxation |
| JEL: | H25 |
| Date: | 2019–11 |
| URL: | http://d.repec.org/n?u=RePEc:cdh:ebrief:297&r=all |
| By: | Caglayan, Mustafa; Talavera, Oleksandr; Zhang, Wei |
| Abstract: | We explore individual lender behaviour on Renrendai.com, a leading Chinese peer-to-peer (P2P) crowdlending platform. Using a sample of roughly 5 million investor-loan-hour observations and applying a high-dimension fixed effect estimator, we establish evidence of herding behaviour: the investors in our sample tend to prefer assets that had attracted strong interest in previous periods. The herding behaviour relates to both the experience of the investor and the length of time of each investment session. The results show that herding happens mostly in the first or final hour of long sessions. Herding behaviour is further confirmed by estimates at the listing-hour data. |
| JEL: | G21 |
| Date: | 2019–11–14 |
| URL: | http://d.repec.org/n?u=RePEc:bof:bofitp:2019_022&r=all |
| By: | Michael Dubrovsky; Marshall Ball; Bogdan Penkovsky |
| Abstract: | Most cryptocurrencies rely on Proof-of-Work (PoW) "mining" for resistance to Sybil and double-spending attacks, as well as a mechanism for currency issuance. Hashcash PoW has successfully secured the Bitcoin network since its inception, however, as the network has expanded to take on additional value storage and transaction volume, Bitcoin PoW's heavy reliance on electricity has created scalability issues, environmental concerns, and systemic risks. Mining efforts have concentrated in areas with low electricity costs, creating single points of failure. Although PoW security properties rely on imposing a trivially verifiable economic cost on miners, there is no fundamental reason for it to consist primarily of electricity cost. The authors propose a novel PoW algorithm, Optical Proof of Work (oPoW), to eliminate energy as the primary cost of mining. Proposed algorithm imposes economic difficulty on the miners, however, the cost is concentrated in hardware (capital expense-CAPEX) rather than electricity (operating expenses-OPEX). The oPoW scheme involves minimal modifications to Hashcash-like PoW schemes, inheriting safety/security properties from such schemes. Rapid growth and improvement in silicon photonics over the last two decades has led to the commercialization of silicon photonic co-processors (integrated circuits that use photons instead of electrons to perform specialized computing tasks) for low-energy deep learning. oPoW is optimized for this technology such that miners are incentivized to use specialized, energy-efficient photonics for computation. Beyond providing energy savings, oPoW has the potential to improve network scalability, enable decentralized mining outside of low electricity cost areas, and democratize issuance. Due to the CAPEX dominance of mining costs, oPoW hashrate will be significantly less sensitive to underlying coin price declines. |
| Date: | 2019–11 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1911.05193&r=all |
| By: | Tyler Pike; Horacio Sapriza; Thomas Zimmermann |
| Abstract: | This paper constructs a leading macroeconomic indicator from microeconomic data using recent machine learning techniques. Using tree-based methods, we estimate probabilities of default for publicly traded non-financial firms in the United States. We then use the cross-section of out-of-sample predicted default probabilities to construct a leading indicator of non-financial corporate health. The index predicts real economic outcomes such as GDP growth and employment up to eight quarters ahead. Impulse responses validate the interpretation of the index as a measure of financial stress. |
| Keywords: | Corporate Default ; Early Warning Indicators ; Economic Activity ; Machine Learning |
| JEL: | C53 E32 G33 |
| Date: | 2019–09–20 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedgfe:2019-70&r=all |
| By: | Christophe HURLIN; Christophe PERIGNON |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:leo:wpaper:2712&r=all |
| By: | Krimmer, Robert; Duenas-Cid, David; Krivonosova, Iuliia; Serrano, Radu Antonio; Freire, Marlon; Wrede, Casper |
| Abstract: | The Åland Islands will use Internet Voting for the first time for expatriate voters at the next Parliamentary Elections, to be held in October 2019. This electoral modernization is a response to the need detected to introduce changes in order to better integrate expatriate voters and the younger generations into the electoral system, and represents a first step towards fully introducing i-Voting in future elections. This working paper provides a frame-work for the Ålandic electoral system for further analysis of the costs involved to introduce new voting channels following the CoDE Project methodology. |
| Date: | 2019–09–27 |
| URL: | http://d.repec.org/n?u=RePEc:osf:socarx:5zr2e&r=all |
| By: | Femg, Xunan (Shanghai University of Finance and Economics); Johansson, Anders C. (Stockholm China Economic Research Institute) |
| Abstract: | We examine the role top executives’ social media activity plays for the stock market. When analyzing a unique data set of board chairs’ posts on Chinese social media platform Sina Weibo, we find that they are positively associated with stock returns. When we take a closer look at content, we show it is work-related content that drives stock returns. Non-work-related content has an immediate but transitory effect, suggesting that such posts grab the attention of investors but only contain noise. We also find that information asymmetry plays a significant role in the relationship between board chairs’ Weibo posts and stock returns. Also, the more followers that board chairs have on their Weibo account, the larger the effect Weibo posts have on stock returns. Furthermore, relative to state-controlled firms, Weibo posts by board chairs in private firms exhibit a significantly larger effect on stock returns. Finally, we find that a laxer regulatory environment translates into board chairs’ work-related Weibo posts having a larger effect on stock returns. Top executive social media activity thus acts as a complementary channel for firm-specific information being disseminated to the stock market. |
| Keywords: | Social Media; Microblogging; Information dissemination; Stock market; Investors; China |
| JEL: | G12 G14 N20 |
| Date: | 2019–11–15 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:hascer:2019-052&r=all |