nep-pay New Economics Papers
on Payment Systems and Financial Technology
Issue of 2020‒07‒13
23 papers chosen by

  1. Real-Time Prediction of BITCOIN Price using Machine Learning Techniques and Public Sentiment Analysis By S M Raju; Ali Mohammad Tarif
  2. Tokenomics: Dynamic Adoption and Valuation By Lin William Cong; Ye Li; Neng Wang
  3. Trading Privacy for the Greater Social Good: How Did America React During COVID-19? By Anindya Ghose; Beibei Li; Meghanath Macha; Chenshuo Sun; Natasha Ying Zhang Foutz
  4. Online Consumption During the COVID-19 Crisis: Evidence from Japan By Tsutomu Watanabe; Yuki Omori
  5. The Impact of Peer-to-Peer Lending on Small Business Loans By Jin-Hyuk Kim; Frank Stähler
  6. Dualism in Bitcoin Dynamics: existence of an Upper Bound in Poincaré Recurrence Theorem for Deterministic vs Stochastic Behavior By Grilli, Luca; Santoro, Domenico
  7. Re-evaluating cryptocurrencies' contribution to portfolio diversification -- A portfolio analysis with special focus on German investors By Tim Schmitz; Ingo Hoffmann
  8. How design features affect evaluations of participatory platforms By Christensen, Henrik Serup
  9. The Evolution of Technological Space and Firms’ Workforce Composition in a Manufacturing Region By Giancarlo Corò; Monica Plechero; Francesco Rullani; Mario Volpe
  10. Panorama de las fintech: principales desafíos y oportunidades para el Uruguay By Lavalleja, Martín
  11. How Important is the Yellow Pages? Experimental Evidence from Tanzania By Aker, Jenny; Blumenstock, Joshua; Dillon, Brian
  12. Internet and politics: evidence from U.K. local elections and local government policies By Gavazza, Alessandro; Nardotto, Mattia; Valletti, Tommaso
  13. The Value of Time: Evidence From Auctioned Cab Rides By Buchholz, Nicholas; Doval, Laura; Kastl, Jakub; Matejka, Filip; Salz, Tobias
  14. On the profitability of selfish blockchain mining under consideration of ruin By Hansjörg Albrecher; Pierre-Olivier Goffard
  15. Measuring excess mortality during the COVID-19 pandemic in low- and lower-middle income countries: the need for mobile phone surveys By Adjiwanou, Vissého; Alam, Nurul; Alkema, Leontine; Asiki, Gershim; Bawah, Ayaga; Béguy, Donatien; Cetorelli, Valeria; Dube, Albert; Feehan, Dennis; Fisker, Ane Baerent
  16. The Evolution of CEO Compensation in Venture Capital Backed Startups By Ewens, Michael; Nanda, Ramana; Stanton, Christopher
  17. Migration between platforms By Biglaiser, Gary; Crémer, Jacques; Veiga, André
  18. Volatility Connectedness of Major Cryptocurrencies: The Role of Investor Happiness By Elie Bouri; David Gabauer; Rangan Gupta; Aviral Kumar Tiwari
  19. Öffentliche vs. Private Blockchains in der Finanzwirtschaft By Friedrich Thießen
  20. The chicken or the egg: Technology adoption and network infrastructure in the market for electric vehicles By Nathan Delacrétaz; Bruno Lanz; Jeremy van Dijk
  21. Meios de pagamento emitidos pelo Estado português By Ana Tomás; Nuno Valério
  22. Tweeting on Monetary Policy and Market Sentiments: The Central Bank Surprise Index By Donato Masciandaro; Davide Romelli; Gaia Rubera
  23. The Economics of Social Data By Bergemann, Dirk; Bonatti, Alessandro; Gan, Tan

  1. By: S M Raju; Ali Mohammad Tarif
    Abstract: Bitcoin is the first digital decentralized cryptocurrency that has shown a significant increase in market capitalization in recent years. The objective of this paper is to determine the predictable price direction of Bitcoin in USD by machine learning techniques and sentiment analysis. Twitter and Reddit have attracted a great deal of attention from researchers to study public sentiment. We have applied sentiment analysis and supervised machine learning principles to the extracted tweets from Twitter and Reddit posts, and we analyze the correlation between bitcoin price movements and sentiments in tweets. We explored several algorithms of machine learning using supervised learning to develop a prediction model and provide informative analysis of future market prices. Due to the difficulty of evaluating the exact nature of a Time Series(ARIMA) model, it is often very difficult to produce appropriate forecasts. Then we continue to implement Recurrent Neural Networks (RNN) with long short-term memory cells (LSTM). Thus, we analyzed the time series model prediction of bitcoin prices with greater efficiency using long short-term memory (LSTM) techniques and compared the predictability of bitcoin price and sentiment analysis of bitcoin tweets to the standard method (ARIMA). The RMSE (Root-mean-square error) of LSTM are 198.448 (single feature) and 197.515 (multi-feature) whereas the ARIMA model RMSE is 209.263 which shows that LSTM with multi feature shows the more accurate result.
    Date: 2020–06
  2. By: Lin William Cong; Ye Li; Neng Wang
    Abstract: We develop a dynamic asset-pricing model of cryptocurrencies/tokens that allow users to conduct peer-to-peer transactions on digital platforms. The equilibrium value of tokens is determined by aggregating heterogeneous users' transactional demand rather than discounting cashflows as in standard valuation models. Endogenous platform adoption builds upon user network externality and exhibits an S-curve — it starts slow, becomes volatile, and eventually tapers off. Introducing tokens lowers users' transaction costs on the platform by allowing users to capitalize on platform growth. The resulting intertemporal feedback between user adoption and token price accelerates adoption and dampens user-base volatility.
    JEL: E42 G12 L86
    Date: 2020–05
  3. By: Anindya Ghose; Beibei Li; Meghanath Macha; Chenshuo Sun; Natasha Ying Zhang Foutz
    Abstract: Digital contact tracing and analysis of social distancing from smartphone location data are two prime examples of non-therapeutic interventions used in many countries to mitigate the impact of the COVID-19 pandemic. While many understand the importance of trading personal privacy for the public good, others have been alarmed at the potential for surveillance via measures enabled through location tracking on smartphones. In our research, we analyzed massive yet atomic individual-level location data containing over 22 billion records from ten Blue (Democratic) and ten Red (Republican) cities in the U.S., based on which we present, herein, some of the first evidence of how Americans responded to the increasing concerns that government authorities, the private sector, and public health experts might use individual-level location data to track the COVID-19 spread. First, we found a significant decreasing trend of mobile-app location-sharing opt-out. Whereas areas with more Democrats were more privacy-concerned than areas with more Republicans before the advent of the COVID-19 pandemic, there was a significant decrease in the overall opt-out rates after COVID-19, and this effect was more salient among Democratic than Republican cities. Second, people who practiced social distancing (i.e., those who traveled less and interacted with fewer close contacts during the pandemic) were also less likely to opt-out, whereas the converse was true for people who practiced less social-distancing. This relationship also was more salient among Democratic than Republican cities. Third, high-income populations and males, compared with low-income populations and females, were more privacy-conscientious and more likely to opt-out of location tracking.
    Date: 2020–06
  4. By: Tsutomu Watanabe (Graduate School of Economics, University of Tokyo); Yuki Omori (Nowcast Inc.; M.A. candidate, Graduate School of Information Science and Technology, University of Tokyo.)
    Abstract: The spread of novel coronavirus (COVID-19) infections has led to substantial changes in consumption patterns. While demand for services that involve face-to-face contact has decreased sharply, online consumption of goods and services, such as through e-commerce, is increasing. The aim of this study is to investigate whether online consumption will continue to increase even after COVID-19 subsides, using credit card transaction data. Online consumption requires upfront costs, which have been regarded as one of the factors inhibiting the diffusion of online consumption. However, if many consumers made such upfront investments due to the coronavirus pandemic, they would have no reason to return to offline consumption after the pandemic has ended, and high levels of online consumption should continue. Our main findings are as follows. First, the main group responsible for the increase in online consumption are consumers who were already familiar with online consumption before the pandemic and purchased goods and service both online and offline. These consumers increased the share of online spending in their spending overall and/or stopped offline consumption completely and switched to online consumption only. Second, some consumers that had never used the internet for purchases before started to use the internet for their consumption activities due to COVID-19. However, the share of consumers making this switch was not very different from the trend before the crisis. Third, by age group, the switch to online consumption was more pronounced among youngsters than seniors. These findings suggest that it is not the case that during the pandemic a large number of consumers made the upfront investment necessary to switch to online consumption, so a certain portion of the increase in online consumption is likely to fall away again as COVID-19 subsides.
    Date: 2020–06
  5. By: Jin-Hyuk Kim; Frank Stähler
    Abstract: We investigate the impact of peer-to-peer lending on the small business loans originated by US depository institutions that are subject to the Community Reinvestment Act. We present a model where a borrower can choose between a traditional bank and a crowdlending platform and show that the entry of crowdlending can induce a switching effect as well as a credit expansion effect. Using the staggered entry of LendingClub across states between 2009 and 2017, we find that the platform entry reduced the small business loans originated by banks, in particular, in the low- or moderate-income tracts as well as in the distressed middle-income tracts with a high poverty rate. A conservative estimate suggests that the crowdlending entry may have reduced the aggregate lending volume to small businesses.
    Keywords: crowdfunding, marketplace lending, fintech, Community Reinvestment Act
    JEL: G21 G28
    Date: 2020
  6. By: Grilli, Luca; Santoro, Domenico
    Abstract: In this paper we want to describe a model of the dynamics of the Bitcoin cryptocurrency system. We can define a duality in these dynamics: Bitcoin mostly behaves as a deterministic system and in some time intervals, much shorter, it enters a stochastic regime. In particular, using Poincaré’s recurrence theorem, it was possible to study when the transition from one regime to another occurs. Furthermore, by applying our hypothesis to real data it was possible to explain a reason why the Bitcoin system is affected by such a "high volatility".
    Keywords: Ergodic Theory, Bitcoin, Finance, Deterministic, Stochastic
    JEL: C44 E37 F17 G17
    Date: 2020–06–11
  7. By: Tim Schmitz; Ingo Hoffmann
    Abstract: In this paper, we investigate whether mixing cryptocurrencies to a German investor portfolio improves portfolio diversification. We analyse this research question by applying a (mean variance) portfolio analysis using a toolbox consisting of (i) the comparison of descriptive statistics, (ii) graphical methods and (iii) econometric spanning tests. In contrast to most of the former studies we use a (broad) customized, Equally-Weighted Cryptocurrency Index (EWCI) to capture the average development of a whole ex ante defined cryptocurrency universe and to mitigate possible survivorship biases in the data. According to Glas/Poddig (2018), this bias could have led to misleading results in some already existing studies. We find that cryptocurrencies can improve portfolio diversification in a few of the analyzed windows from our dataset (consisting of weekly observations from 2014-01-01 to 2019-05-31). However, we cannot confirm this pattern as the normal case. By including cryptocurrencies in their portfolios, investors predominantly cannot reach a significantly higher efficient frontier. These results also hold, if the non-normality of cryptocurrency returns is considered. Moreover, we control for changes of the results, if transaction costs/illiquidities on the cryptocurrency market are additionally considered.
    Date: 2020–06
  8. By: Christensen, Henrik Serup
    Abstract: Online participatory platforms are introduced to boost citizen involvement in political decision-making. However, the design features of these platforms vary considerably, and these are likely to affect how prospective users evaluate the usefulness of these platforms. Previous studies explored how prevalent different design features are and how they affect the success of platforms in terms of impact, but the attitudes of prospective users remain unclear. Since these evaluations affect the prospects for launching successful participatory platforms, it is imperative to assess what citizens want from such digital possibilities for participation. This study uses a conjoint experiment (n=1048) conducted in Finland that explore the impact of seven design features: Discussion possibilities; Interaction with politicians and experts; Information availability, Aim of participation; Identity verification; Anonymous participation and Accessibility. Furthermore, it is examined whether the effects differ across use of ICTs measured by generation, time online and prior use of participatory platforms. The results suggest that most design features have clear effects on evaluations, and that deliberative features have the strongest effects. Furthermore, the effects are relatively stable across prior use although the less experienced put a stronger emphasis on verification.
    Date: 2020–05–22
  9. By: Giancarlo Corò (Department of Economics, University Of Venice Cà Foscari); Monica Plechero (Department of Economics, University Of Venice Cà Foscari); Francesco Rullani (Department of Management, University Of Venice Cà Foscari); Mario Volpe (Department of Economics, University Of Venice Cà Foscari)
    Abstract: The development of the technological space of a manufacturing region relates to its human capital. However, the dynamic relation between local firms’ workforce composition and their adoption of Industry 4.0 enabling technologies over time is still under investigated. The paper contributes to filling this gap analysing the relation over 10 years between technology adoption and the occupational choices of 1800 firms from one of the most industrialized regions of Italy: the Veneto Region. The results from descriptive as well as inferential analysis show that such relational dynamics are a multifaceted phenomenon, presenting a series of counterintuitive features.
    Keywords: Digital technologies, Industry 4.0; manufacturing region, workforce, SME
    JEL: R11 O33 E24
    Date: 2020
  10. By: Lavalleja, Martín
    Abstract: Las empresas que proveen productos y servicios financieros innovadores, mediante la utilización de tecnología han tenido un crecimiento exponencial en el mercado financiero mundial en los últimos años. Estas empresas reducen los costos y simplifican los procedimientos, mejorando la eficiencia de los servicios financieros, lo que favorece la inclusión financiera y el acceso al crédito para las pequeñas y medianas empresas. América Latina no se ha quedado al margen de esta evolución, produciéndose un marcado crecimiento en los emprendimientos fintech, mientras que la regulación en la mayoría de los países es aún incipiente. En 2019 el sector fintech en Uruguay estaba compuesto por 63 empresas, operando en diversos segmentos. El segmento más destacado es el de empresas que desarrollan productos tecnológicos específicos para instituciones financieras, En segundo lugar, se ubican las empresas que otorgan préstamos a través de una plataforma electrónica, finalmente se encuentra el segmento de pagos y remesas. Teniendo en cuenta el impacto positivo que los emprendimientos de préstamos ente pares pueden tener en el sistema financiero, este trabajo recomienda explorar la posibilidad de implementación de un sandbox regulatorio, que a partir de la reducción de las exigencias para funcionar y el establecimiento de un plazo, permita valorar en la práctica los riesgos reales.
    Date: 2020–06–24
  11. By: Aker, Jenny; Blumenstock, Joshua; Dillon, Brian
    Abstract: Mobile phones reduce the cost of communicating with existing social contacts, but do not eliminate frictions in forming new relationships. We report the findings of a two-sided randomized control trial in central Tanzania, centered on the production and distribution of a "Yellow Pages" phone directory with contact information for local enterprises. Enterprises randomly assigned to be listed in the directory receive more business calls, make greater use of mobile money, and are more likely to employ workers. There is evidence of positive spillovers, as both listed and unlisted enterprises in treatment villages experience significant increases in sales relative to a pure control group. Households randomly assigned to receive copies of the directory make greater use their phones for farming, are more likely to rent land and hire labor, have lower rates of crop failure, and sell crops for weakly higher prices. Willingness-to-pay to be listed in future directories is significantly higher for treated enterprises.
    Keywords: agriculture; mobile phones; Search costs; Small and medium enterprises; Tanzania; telephone directories
    JEL: D83 M37 O13 Q13
    Date: 2020–03
  12. By: Gavazza, Alessandro; Nardotto, Mattia; Valletti, Tommaso
    Abstract: We empirically study the effects of broadband internet diffusion on local election outcomes and on local government policies using rich data from the U.K. Our analysis shows that the internet has displaced other media with greater news content (i.e. radio and newspapers), thereby decreasing voter turnout, most notably among less-educated and younger individuals. In turn, we find suggestive evidence that local government expenditures and taxes are lower in areas with greater broadband diffusion, particularly expenditures targeted at less-educated voters. Our findings are consistent with the idea that voters’ information plays a key role in determining electoral participation, government policies, and government size.
    Keywords: local elections; voter turnout; local government expenditure; media; internet
    JEL: D72 H72 H75 L82 L86 N44
    Date: 2019–10–01
  13. By: Buchholz, Nicholas; Doval, Laura; Kastl, Jakub; Matejka, Filip; Salz, Tobias
    Abstract: We estimate valuations of time using detailed consumer choice data from a large European ride hail platform, where drivers bid on trips and consumers choose between a set of potential rides with different prices and waiting times. We estimate consumer demand as a function of prices and waiting times. While demand is responsive to both, price elasticities are on average four times higher than waiting-time elasticities. We show how these estimates can be mapped into values of time that vary by place, person, and time of day. Regarding variation within a day, the value of time during non-work hours is 16% lower than during work hours. Regarding the spatial dimension, our value of time measures are highly correlated both with real estate prices and urban GPS travel flows. We apply our measures to quantify the opportunity cost of traffic congestion in Prague, which we estimate at $483,000 per day.
    Date: 2020–04
  14. By: Hansjörg Albrecher; Pierre-Olivier Goffard (SAF - Laboratoire de Sciences Actuarielle et Financière - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon)
    Abstract: Mining blocks on a blockchain equipped with a proof of work consensus protocol is well-known to be resource-consuming. A miner bears the operational cost, mainly electricity consumption and IT gear, of mining, and is compensated by a capital gain when a block is discovered. This paper aims at quantifying the profitability of mining when the possible event of ruin is also considered. This is done by formulating a tractable stochastic model and using tools from applied probability and analysis, including the explicit solution of a certain type of advanced functional differential equation. The expected profit at a future time point is determined for the situation when the miner follows the protocol as well as when he/she withholds blocks. The obtained explicit expressions allow to analyze the sensitivity with respect to the different model ingredients and to identify conditions under which selfish mining is a strategic advantage.
    Keywords: Blockchain,miner,cryptocurrency,ruin theory,dual risk model
    Date: 2020–05–29
  15. By: Adjiwanou, Vissého; Alam, Nurul; Alkema, Leontine; Asiki, Gershim; Bawah, Ayaga; Béguy, Donatien; Cetorelli, Valeria; Dube, Albert; Feehan, Dennis; Fisker, Ane Baerent
    Abstract: In low income and lower-middle income countries, data from civil registration systems do not allow monitoring excess mortality during the COVID-19 pandemic. Rapid mobile phone surveys aimed at measuring mortality trends on a monthly basis are a realistic and safe option for filling that data gap. The data generated by mobile phone surveys can play a key role in better targeting areas or population groups most affected by the pandemic. They can also help monitor the impact of interventions and programs, and rapidly identify what works in mitigating the impact of COVID-19.
    Date: 2020–05–19
  16. By: Ewens, Michael (California Institute of Technology); Nanda, Ramana; Stanton, Christopher
    Abstract: We use individual-level data to shed light on the evolution of founder-CEO compensation in venture capital-backed startups. We document that having a tangible, marketable product is a fundamental milestone in CEOs' compensation contracts, marking the point at which liquid cash compensation begins to increase significantly – well before a liquidity event. "Product market fit" also coincides with key human capital in the startup becoming more replaceable, marking an apparent transition in the firm’s lifecycle from differentiation to standardization. Although substantial increases in cash compensation for founder-CEOs in response to milestones improves the certainty equivalent of attempting entrepreneurship relative to flat pay, low cash compensation in the very early years can still deter entrepreneurship for potential entrants. We characterize the types of individuals most likely to be impacted by this constraint and hence those whose ideas are unlikely to be commercialized through VC-backed entrepreneurship.
    Date: 2020–05–20
  17. By: Biglaiser, Gary; Crémer, Jacques; Veiga, André
    Abstract: We study incumbency advantage in markets with positive consumption externalities. Users of an incumbent platform receive stochastic opportunities to migrate to an entrant. They can accept a migration opportunity or wait for a future opportunity. In some circumstances, users have incentives to delay migration until others have migrated. If they all do so, no migration takes place, even when migration would have been Pareto-superior. This provides an endogenous micro-foundation for incumbency advantage. We use our framework to identify environments where incumbency advantage is larger.
    Keywords: industry dynamics; migration; Platform; Standardization and Compatibility
    JEL: D85 L14 L15 L16 R23
    Date: 2020–03
  18. By: Elie Bouri (Holy Spirit University of Kaslik (USEK), USEK Business School, Jounieh, Lebanon); David Gabauer (Software Competence Center Hagenberg, Data Analysis Systems, Softwarepark 21, 4232 Hagenberg, Austria); Rangan Gupta (Department of Economics, University of Pretoria, Pretoria, 0002, South Africa); Aviral Kumar Tiwari (Rajagiri Business School, Rajagiri Valley Campus, Kochi, India)
    Abstract: In this paper, we first obtain a time-varying measure of volatility connectedness involving fifteen major cryptocurrencies based on a dynamic conditional correlation-generalized autoregressive conditional heteroscedasticity (DCC-GARCH) model, and then analyze the role of investor sentiment in explaining the movement of the connectedness metric within a quantile-on-quantile framework. Our findings show that lower quantiles of investor happiness, built on Twitter feed data as a proxy for investor sentiment, is positively associated with the entire conditional distribution of connectedness, but the opposite is observed at higher values of investor happiness. In addition, when we look at the effect of sentiment on the common market volatility, we are able to deduce that as investors become exceedingly unhappy, overall market volatility increases and this is associated with high market connectedness. The heightened volatility possibly due to higher trading, seems to suggest that cryptocurrencies are used for hedging when investor sentiment is weak, with evidence in favor of this behavior being relatively stronger than the possible speculative motive associated with happy investors, as low total connectedness is coupled with high common volatility. Our results tend to suggest that, relatively more diversification opportunities are available when investors are happy rather than when sentiment is weak.
    Keywords: Cryptocurrency Market, DCC-GARCH, Volatility Connectedness, Investor Happiness, Quantile-on-Quantile Regression
    JEL: C22 C32 G10
    Date: 2020–06
  19. By: Friedrich Thießen (Chemnitz University of Technology, Department of Economics, Chair for Finance and Banking Management)
    Abstract: Blockchains gelten als zukunftsträchtige Datenbanktechnologien. In dieser Studie werden Public und Private Blockchain-Konzepte hinsichtlich ihrer Stärken und Schwächen miteinander verglichen. Dazu werden die Konzepte in einen strategischen und einen operativen Teil getrennt. Es zeigt sich, dass auf der strategischen Ebene die Führungsstrukturen bei Public Blockchain-Projekten suboptimal sind. Dies gilt für die grundlegenden Corporate Governance Strukturen, die Verantwortlichkeiten für die zentrale Software (Core Client), den dezentralen Betrieb der Blockchain im Rahmen von DLT-Systemen und die Nichtsteuerbarkeit von Anwendungen Dritter, die auf die Public Blockchain ohne Restriktionen zugreifen können. Auf der operativen Ebene erscheinen Public Blockchain-Strukturen auf den ersten Blick durchaus möglich. Aber hier stehen Effizienzkriterien im Weg. Public Blockchains sind im Betrieb nicht günstig. Geschwindigkeit und Skalierbarkeit sind beschränkt. Nach Angriffen kann die Datenbank nur schwer wieder richtiggestellt werden. Für den Fall nachlassenden Interesses von Nodes muss der Initiator eines Blockchain-Projektes Vorkehrungen treffen, selbst einzuspringen. Das sind Nachteile im operativen Betrieb, die sehr schwer wiegen. Insgesamt ergibt sich Skepsis hinsichtlich der Public Blockchain. Die Zukunft scheint eher in Private Blockchain- und ganz klassischen Datenbankprojekten zu liegen.
    Keywords: Public Blockchain, Private Blockchain, Corporate Governance, Finance
    Date: 2020–06
  20. By: Nathan Delacrétaz; Bruno Lanz; Jeremy van Dijk
    Abstract: We document non-linear stock effects in the relationship linking emerging technology adoption and network infrastructure increments. We exploit 2010-2017 data covering nascent to mature electric vehicle (EV) markets across 422 Norwegian municipalities together with two complementary identification strategies: control function regressions of EV sales on flexible polynomials in the stock of charging stations and charging points, and synthetic control methods to quantify the impact of initial infrastructure provision in municipalities that previously had none. Our results are consistent with indirect network effects and the behavioral bias called "range anxiety", and support policies targeting early infrastructure provision to incentivize EV adoption.
    Keywords: Technology adoption; network externality; electric vehicles; charging infrastructure; two-sided markets; behavioral bias; range anxiety; environmental policy.
    JEL: L14 D62 L91 O33 Q48 Q55 Q58
    Date: 2020–08
  21. By: Ana Tomás; Nuno Valério
    Abstract: This working paper aims to present an exhaustive list of the current means of payment issued by the Portuguese state or under its control since it exists as an effectively independent state in the 13th century and their main numismatic and monetary characteristics.
    Keywords: Portugal, coins, banknotes, scriptnotes JEL classification: E42 – o governo e o sistema monetário / government and the monetary system
    Date: 2020
  22. By: Donato Masciandaro; Davide Romelli; Gaia Rubera
    Abstract: This paper explores the relationship between central bank communication and market sentiment, and proposes a new measure. Market sentiment is proxied using a Twitter-based metric: the Central Bank Surprise Index. The empirical study covers three cases: the Federal Reserve, the European Central Bank and the Bank of England.
    Keywords: monetary policy, central bank communication, financial market, social media, Twitter, Federal Reserve System, European Central Bank, Bank of England, Bank of Japan
    JEL: E44 E52 E58 G14 G15
    Date: 2020
  23. By: Bergemann, Dirk; Bonatti, Alessandro; Gan, Tan
    Abstract: A data intermediary pays consumers for information about their preferences and sells the information so acquired to firms that use it to tailor their products and prices. The social dimension of the individual data---whereby an individual's data are predictive of the behavior of others---generates a data externality that reduces the intermediary's cost of acquiring information. We derive the intermediary's optimal data policy and show that it preserves the privacy of the consumers' identities while providing precise information about market demand to the firms. This enables the intermediary to capture the entire value of information as the number of consumers grows large.
    Keywords: consumer privacy; data externality; data flow; data intermediaries; data policy; data rights; personal information; privacy paradox; social data
    JEL: D44 D82 D83
    Date: 2020–03

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