nep-pay New Economics Papers
on Payment Systems and Financial Technology
Issue of 2021‒02‒22
thirty papers chosen by



  1. When Does the Introduction of a New Currency Improve Welfare? By Max Fuchs; Jochen Michaelis
  2. Global Bitcoin Markets and Local Regulations By Park , Cyn-Young; Tian , Shu; Zhao , Bo
  3. An Effort to Measure Customer Relationship Performance in Indonesia's Fintech Industry By Alisya Putri Rabbani; Andry Alamsyah; Sri Widiyanesti
  4. Interdependencies between Mining Costs, Mining Rewards and Blockchain Security By Pavel Ciaian; d'Artis Kancs; Miroslava Rajcaniova
  5. Digital divides across consumers of internet services in Spain using panel data 2007-2019. Narrowing or not? By Teodosio Pérez Amaral; Angel Valarezo Unda; Rafael López Zorzano; Teresa Garín Muñoz
  6. The economic dependency of the Bitcoin security By Pavel Ciaian; d'Artis Kancs; Miroslava Rajcaniova
  7. Exploring the dependencies among main cryptocurrency log-returns: A hidden Markov model By Pennoni, Fulvia; Bartolucci, Francesco; Forte, Gianfranco; Ametrano, Ferdinando
  8. A Core of E-Commerce Customer Experience based on Conversational Data using Network Text Methodology By Andry Alamsyah; Nurlisa Laksmiani; Lies Anisa Rahimi
  9. Benefits of Cellular Telecommunication and Smart Card Data for Travel Behaviour Analysis By Patrick Bonnel
  10. Inferring Modal Split from Mobile Phones: Principles, Issues and Policy Recommendations By Norbert Brändle
  11. DEVELOPMENT OF BRAND HATE THROUGH ELECTRONIC MARKETING By Muhammad Taqi
  12. Detecting and Quantifying Wash Trading on Decentralized Cryptocurrency Exchanges By Friedhelm Victor; Andrea Marie Weintraud
  13. Blockchain and Institutions (II): Is The Platform Economy The New Rentier Capitalism? Actualising Achille Loria’s Analysis Of Rent And Its Elision By Plinio Limata; Paolo Santori
  14. Permissioned Distributed Ledgers and the Governance of Money By Raphael Auer; Cyril Monnet; Hyun Song Shin
  15. The Future of Healthcare around the World: Four indices integrating Technology, Productivity, Anti-Corruption, Healthcare and Market Financialization By Julia M. Puaschunder; Dirk Beerbaum
  16. Use of Big Data in Transport Modelling By Luis Willumsen
  17. Time-varying properties of asymmetric volatility and multifractality in Bitcoin By Tetsuya Takaishi
  18. The COVID-19 Shock and Consumer Credit: Evidence from Credit Card Data By ; ; Benjamin S. Kay
  19. Does Online Search Improve the Match Quality of New Hires? By Gürtzgen, Nicole; Lochner, Benjamin; Pohlan, Laura; Berg, Gerard J. van den
  20. Power-Law Return-Volatility Cross Correlations of Bitcoin By T. Takaishi
  21. INVESTIGATING DE FACTO AND DE JURE EXCHANGE RATE REGIMES By Emmanuel Erem
  22. Job search during the covid-19 crisis. By Hensvik, Lena; Le Barbanchon, Thomas; Rathelot, Roland
  23. The Small World Phenomenon and Network Analysis of ICT Startup Investment in Indonesia and Singapore By Farid Naufal Aslam; Andry Alamsyah
  24. Le choix du modèle de régulation des Fintech : entre sandbox et soundbox By Gurvan Branellec; Ji-Yong Lee
  25. A Retrospective Study of State Aid Control in the German Broadband Market By Tomaso Duso; Mattia Nardotto; Jo Seldeslachts
  26. The Banker's Oath And Financial Advice By Utz Weitzel; Michael Kirchler
  27. Matching Strategic Agents on a Two-Sided Platform By Masaki Aoyagi; Seung Han Yoo
  28. On Technical Trading and Social Media Indicators in Cryptocurrencies' Price Classification Through Deep Learning By Marco Ortu; Nicola Uras; Claudio Conversano; Giuseppe Destefanis; Silvia Bartolucci
  29. Portrayal of Women in Advertising on Facebook and Instagram By Fab-Ukozor Nkem; Onyebuchi Alexander Chima; Obayi Paul Martins; Anorue Luke Ifeanyi; Onwude Nnenna Fiona
  30. The Expression of Right-Wing Populism in the Netherlands across Facebook Posts By Fischer, Agneta; Brands, Charlotte; Abadi, David

  1. By: Max Fuchs (University of Kassel); Jochen Michaelis (University of Kassel)
    Abstract: In recent years, cryptocurrencies such as Bitcoin have emerged, in upcoming years, corporate currencies such as Libra (Diem) and central bank digital currencies will emerge even in low-inflation developed economies. Using the dual currency search model of Kiyotaki and Wright (1993), we show how the introduction of a supplement to traditional money affects average utility. The room for a welfare improvement depends on differences in returns and costs, but, in particular, on the fraction of cash traders who will be replaced by digital money traders.
    Keywords: digital money, dual currency regime, welfare comparison
    JEL: E41 E42 E51
    Date: 2021
    URL: http://d.repec.org/n?u=RePEc:mar:magkse:202106&r=all
  2. By: Park , Cyn-Young (Asian Development Bank); Tian , Shu (Asian Development Bank); Zhao , Bo (Asian Development Bank)
    Abstract: Since the launch of Bitcoin in 2009, the spectacular rise and fall of cryptocurrencies and the underlying blockchain technology have attracted global attention. While the application of distributed ledger technology presents great economic and business potential, significant volatility and speculative trading of cryptocurrencies have raised concerns over investor and consumer protection and prompted government interventions within their respective jurisdictions. This study focuses on the six Bitcoin trading markets comprising 99% of global trading volume as of February 2018. Adopting the event study methodology to newly compiled information about local regulation events, we find that the effect of government regulations on the Bitcoin price is only short-lived, but regulations discourage trading activities for a longer term in local markets. Interestingly, however, the repressive effect of domestic regulations on trading activities can be mitigated by the domestic financial market openness. Together, these findings are consistent with the view that Bitcoin markets are globally integrated and that, to uphold market integrity, international cooperation would be essential.
    Keywords: Bitcoin; cryptocurrency; financial market openness; international cooperation; regulation
    JEL: E61 G10 G14 G18
    Date: 2020–01–23
    URL: http://d.repec.org/n?u=RePEc:ris:adbewp:0605&r=all
  3. By: Alisya Putri Rabbani; Andry Alamsyah; Sri Widiyanesti
    Abstract: The availability of social media simplifies the companies-customers relationship. An effort to engage customers in conversation networks using social media is called Social Customer Relationship Management (SCRM). Social Network Analysis helps to understand network characteristics and how active the conversation network on social media. Calculating its network properties is beneficial for measuring customer relationship performance. Financial Technology, a new emerging industry that provides digital-based financial services utilize social media to interact with its customers. Measuring SCRM performance is needed in order to stay competitive among others. Therefore, we aim to explore the SCRM performance of the Indonesia Fintech company. In terms of discovering the market majority thought in conversation networks, we perform sentiment analysis by classifying into positive and negative opinion. As case studies, we investigate Twitter conversations about GoPay, OVO, Dana, and LinkAja during the observation period from 1st October until 1st November 2019. The result of this research is beneficial for business intelligence purposes especially in managing relationships with customers.
    Date: 2021–02
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2102.08262&r=all
  4. By: Pavel Ciaian; d'Artis Kancs; Miroslava Rajcaniova
    Abstract: This paper studies to what extent the cost of operating a proof-of-work blockchain is intrinsically linked to the cost of preventing attacks, and to what extent the underlying digital ledger security budgets are correlated with the cryptocurrency market outcomes. We theoretically derive an equilibrium relationship between the cryptocurrency price, mining rewards and mining costs, and blockchain security outcomes. Using daily crypto market data for 2014-2021 and employing the autoregressive distributed lag approach - that allows treating all the relevant moments of the blockchain series as potentially endogenous - we provide empirical evidence of cryptocurrency price and mining rewards indeed being intrinsically linked to blockchain security outcomes.
    Date: 2021–02
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2102.08107&r=all
  5. By: Teodosio Pérez Amaral (Instituto Complutense de Análisis Económico. Universidad Complutense de Madrid); Angel Valarezo Unda (Instituto Complutense de Análisis Económico. Universidad Complutense de Madrid); Rafael López Zorzano (Instituto Complutense de Análisis Económico. Universidad Complutense de Madrid); Teresa Garín Muñoz (UNED)
    Abstract: Digital gaps have the potential to exacerbate the inequalities that exist in society. The main objective of this paper is to study the gaps that occur in the use of internet services by households in Spain during the period 2007-2019 and to become useful in the design of policies addressed to narrow specific digital divides. The data is a panel obtained from the ICT-H Survey on Households of the National Statistics Institute. This paper defines the gaps as the differences in the use of internet services across individual consumers. A selected group of twelve digital services are considered: e-commerce, e-selling, e-tourism, e-learning, e-health, e-banking, e-government, VoIP, chat, email, cloud services, and social networks. The second level digital gaps are analyzed in each service according to six relevant socio-demographic characteristics: gender, age, education, digital skills, population size, and income. A set of graphs show the evolution of the gaps. Gaps are narrowing in most dimensions and specific characteristics, but not in others such as age, education, and digital skills. The gaps reveal the evolution of digitization and in some cases of digital exclusion for specific groups. Specific knowledge about digital gaps is useful for policymakers, since closing the digital divide is an explicit policy goal in this country, as well as in other parts of Europe. Then, a dynamic panel data model was proposed and estimated using Arellano and Bond techniques. A dynamic/network effect was found, as well as other socio-demographic determinants. Finally, the paper contains conclusions, policy recommendations and an agenda for future research. The policy recommendations consist of digital education programs targeted at the most exposed groups such as the elderly, the less well-educated and people with lower digital skills.
    Keywords: Digital divide; Digital gaps; Internet services; Individual panel data; Dynamic panel data model.
    JEL: C30 L86 L96
    Date: 2021–01
    URL: http://d.repec.org/n?u=RePEc:ucm:doicae:2101&r=all
  6. By: Pavel Ciaian; d'Artis Kancs; Miroslava Rajcaniova
    Abstract: We study to what extent the Bitcoin blockchain security permanently depends on the underlying distribution of cryptocurrency market outcomes. We use daily blockchain and Bitcoin data for 2014-2019 and employ the ARDL approach. We test three equilibrium hypotheses: (i) sensitivity of the Bitcoin blockchain to mining reward; (ii) security outcomes of the Bitcoin blockchain and the proof-of-work cost; and (iii) the speed of adjustment of the Bitcoin blockchain security to deviations from the equilibrium path. Our results suggest that the Bitcoin price and mining rewards are intrinsically linked to Bitcoin security outcomes. The Bitcoin blockchain security's dependency on mining costs is geographically differenced - it is more significant for the global mining leader China than for other world regions. After input or output price shocks, the Bitcoin blockchain security reverts to its equilibrium security level.
    Date: 2021–02
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2102.08378&r=all
  7. By: Pennoni, Fulvia; Bartolucci, Francesco; Forte, Gianfranco; Ametrano, Ferdinando
    Abstract: A multivariate hidden Markov model is proposed to explain the price evolution of Bitcoin, Ethereum, Ripple, Litecoin, and Bitcoin Cash. The observed daily log-returns of these five major cryptocurrencies are modeled jointly. They are assumed to be correlated according to a variance-covariance matrix conditionally on a latent Markov process having a finite number of states. For the purpose of comparing states according to their volatility, we estimate specific variance-covariance matrix varying across states. Maximum likelihood estimation of the model parameters is carried out by the Expectation-Maximization algorithm. The hidden states represent different phases of the market identified through the estimated expected values and volatility of the log-returns. We reach interesting results in detecting these phases of the market and the implied transition dynamics. We also find evidence of structural medium term trend in the correlations of Bitcoin with the other cryptocurrencies.
    Keywords: Bitcoin, Bitcoin cash, decoding, Ethereum, expectation-maximization algorithm, Litecoin, Ripple, time-series
    JEL: C32 C51 C53
    Date: 2020
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:106150&r=all
  8. By: Andry Alamsyah; Nurlisa Laksmiani; Lies Anisa Rahimi
    Abstract: E-commerce provides an efficient and effective way to exchange goods between sellers and customers. E-commerce has been a popular method for doing business, because of its simplicity of having commerce activity transparently available, including customer voice and opinion about their own experience. Those experiences can be a great benefit to understand customer experience comprehensively, both for sellers and future customers. This paper applies to e-commerces and customers in Indonesia. Many Indonesian customers expressed their voice to open social network services such as Twitter and Facebook, where a large proportion of data is in the form of conversational data. By understanding customer behavior through open social network service, we can have descriptions about the e-commerce services level in Indonesia. Thus, it is related to the government's effort to improve the Indonesian digital economy ecosystem. A method for finding core topics in large-scale internet unstructured text data is needed, where the method should be fast but sufficiently accurate. Processing large-scale data is not a straightforward job, it often needs special skills of people and complex software and hardware computer system. We propose a fast methodology of text mining methods based on frequently appeared words and their word association to form network text methodology. This method is adapted from Social Network Analysis by the model relationships between words instead of actors.
    Date: 2021–02
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2102.09107&r=all
  9. By: Patrick Bonnel (ENTPE)
    Abstract: This paper proposes the estimation of trip origin-destination matrices using big data through two case studies. In the first, trip matrices are estimated from mobile network data and compared with household travel survey results. In the second, public transport trip matrices are derived from smart card data and compared with passenger survey data. The paper concludes that sample size and longitudinal data collection are big data’s main strengths, yet are limited by privacy protection constraints and by the need to control for biases in the sample.
    Date: 2021–01–27
    URL: http://d.repec.org/n?u=RePEc:oec:itfaab:2021/06-en&r=all
  10. By: Norbert Brändle (Austrian Institute Of Technology)
    Abstract: This paper describes methods to identify trip details, including the mode of transport for each trip, from smartphone app data and from mobile network data. Use cases include travel demand surveys, travel behaviour gamification, mobility-as-a-service and automated ticketing. In the context of transport planning, the paper examines solutions to protect privacy and to enhance the representativeness of mobile phone data samples. It makes recommendations to overcome the many obstacles involved, in particular the scarcity of annotated training data.
    Date: 2021–01–27
    URL: http://d.repec.org/n?u=RePEc:oec:itfaab:2021/07-en&r=all
  11. By: Muhammad Taqi (European University of Lefke, Faculty of Business, Izmir, Turkey)
    Abstract: The internet has become one of the most important and influential aspects of human lives, which cannot simply be parted away. The virtual world, which is accessed through the internet, has changed the lives of people throughout the world. It has shaped people's opinions related to everything around them and most importantly, of consumer goods and services. These opinions can take form both in positive or negative emotional messages which show the type of consumer-brand relationship that exists. The consumer-brand relationship which has its two extremes, on the positive side of the spectrum is the emotion of Love and on the other end of the spectrum lies the emotion of Hate which is one of the most extreme negative forms of emotion. It is a similar emotion like other emotions that are built over time, but at times, can be a result of spontaneous reaction towards an event. The current conceptual study aims to explore how e-marketing and social media platforms participate in the development of brand hate in consumers. The study goes over various forms of online marketing tools to show how they aid in developing brand hate in consumers. The study concludes that online marketing and social media do aid in developing brand hate and other negative emotions towards a brand.
    Keywords: Brand Hate, Negative Emotions, Online Marketing, Brand Relationship, ConsumerBrand Relationship
    JEL: D1 M30
    Date: 2020–12
    URL: http://d.repec.org/n?u=RePEc:aly:journl:202070&r=all
  12. By: Friedhelm Victor; Andrea Marie Weintraud
    Abstract: Cryptoassets such as cryptocurrencies and tokens are increasingly traded on decentralized exchanges. The advantage for users is that the funds are not in custody of a centralized external entity. However, these exchanges are prone to manipulative behavior. In this paper, we illustrate how wash trading activity can be identified on two of the first popular limit order book-based decentralized exchanges on the Ethereum blockchain, IDEX and EtherDelta. We identify a lower bound of accounts and trading structures that meet the legal definitions of wash trading, discovering that they are responsible for a wash trading volume in equivalent of 159 million U.S. Dollars. While self-trades and two-account structures are predominant, complex forms also occur. We quantify these activities, finding that on both exchanges, more than 30\% of all traded tokens have been subject to wash trading activity. On EtherDelta, 10% of the tokens have almost exclusively been wash traded. All data is made available for future research. Our findings underpin the need for countermeasures that are applicable in decentralized systems.
    Date: 2021–02
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2102.07001&r=all
  13. By: Plinio Limata (LUMSA University); Paolo Santori (LUMSA University)
    Abstract: Today there is a growing consensus on the benefits of the platform economy. All the stakeholders are fairly remunerated, and the market sphere is grounded on the parties’ mutual advantage; points of equilibria are reached more efficiently, and costs of production and transaction are lowered thanks to the channels created by the platforms. We question this idyllic picture highlighting their role as value extractors in current market societies, which parallels the role of rent in the modern era’s economic system. Therefore, we employ Achille Loria’s (1857–1943, dubbed ‘the Italian Marx’) philosophical and economic categories to understand whether the platform economy is a form of contemporary rent-seeking and, if so, to suggest steps to avoid its continued, yet hidden, value extraction.
    Keywords: platform economy; rent; Achille Loria; value extraction
    Date: 2021–01
    URL: http://d.repec.org/n?u=RePEc:lsa:wpaper:wpc37&r=all
  14. By: Raphael Auer; Cyril Monnet; Hyun Song Shin
    Abstract: We explore the economics and optimal design of “permissioned” distributed ledger technology (DLT) in a credit economy. Designated validators verify transactions and update the ledger at a cost that is derived from a supermajority voting rule, thus giving rise to a public good provision game. Without giving proper incentives to validators, however, their records cannot be trusted because they cannot commit to verifying trades and they can accept bribes to incorrectly validate histories. Both frictions challenge the integrity of the ledger on which credit transactions rely. In this context, we examine the conditions under which the process of permissioned validation supports decentralized exchange as an equilibrium, and analyze the optimal design of the trade and validation mechanisms. We solve for the optimal fees, number of validators, supermajority threshold and transaction size. A stronger consensus mechanism requires higher rents be paid to validators. Our results suggest that a centralized ledger is likely to be superior, unless weaknesses in the rule of law and contract enforcement necessitate a decentralized ledger.
    Keywords: digital currencies, money, distributed ledger, blockchain, coordination game, global game, consensus, market design.
    JEL: C72 C73 D4 E42 G2 L86
    Date: 2021–02
    URL: http://d.repec.org/n?u=RePEc:ube:dpvwib:dp2101&r=all
  15. By: Julia M. Puaschunder (The New School, USA); Dirk Beerbaum (Frankfurt School of Finance and Management, Frankfurt am Main)
    Abstract: The currently ongoing COVID-19 crisis has challenged healthcare around the world. The global solution against global pandemic spreads but also to provide essential healthcare is likely to feature components of technological advancement and economic productivity as a starting ground for vital solution finding. Anti-corruption is a necessary prerequisite for access to and quality of healthcare provision in the public sphere. Market innovation financialization of a society raises private sector funds for research and development but also funds the market-oriented implementation of healthcare, which appears beneficial and efficient in combating future healthcare crises. Technology-driven growth, corruption free-healthcare and well-funded markets fostering innovation account for the most prospective public and private sector remedies of the global COVID-19 crisis. These ingredients differ vastly around the world. This paper innovatively combines the mentioned facets in four indices. Highlighting international differences in economic starting positions as well as public and private sector healthcare provision potential around the world serves as indicator where in the world global pandemic medical solutions may thrive in the future. Reflecting the different pandemic crisis alleviation ingredients concurrently allows to capture unknown interaction effects. Pegging remedy credentials to certain regions of the world also holds invaluable insights on what territories of the world should take the lead in different sectors when bundling our common world efforts to overcome the COVID-19 pandemic together. Index 1 highlights the connectedness of Artificial Intelligence (AI) – as operationalized by internet connectivity – with economic productivity – measured in Gross Domestic Products (GDP) – around the world. Index 2 captures the degree of anti-corruption in its relation with a strong public healthcare sector over an entire world sample. Index 3 integrates internet connectivity with anti-corruption and promising healthcare internationally. Index 4 shows the impact of internet connectivity, GDP, anti-corruption, healthcare in light of market capitalization prospects with special attention to technological innovations in the digital age. In its entirety, the four indices highlight different facets of the future of medical care in order to bundle our common efforts strategically in overcoming COVID-19 and thriving in a healthier and more digitalized world to come.
    Keywords: Access to healthcare, Advancements, AI-GDP Index, Apps, Artificial Intelligence (AI), Coronavirus, Corruption-free maximization of excellence and precision, Corruption Perception
    Date: 2020–08
    URL: http://d.repec.org/n?u=RePEc:smo:apaper:021jpmd&r=all
  16. By: Luis Willumsen (Nommon Solutions and Technologies)
    Abstract: This paper guides transport planners in making the best use of mobile phone traces, derived either from mobile network data or from smartphone app data. It suggests combining such new data sources with conventional travel surveys whose sample size and cost could ultimately be reduced. In the context of a rapidly evolving mobility landscape, with new modes and new services available, big data can help monitor behaviour change, learn from quasi-experiments and develop next-generation travel demand modelling tools.
    Date: 2021–01–27
    URL: http://d.repec.org/n?u=RePEc:oec:itfaab:2021/05-en&r=all
  17. By: Tetsuya Takaishi
    Abstract: This study investigates the volatility of daily Bitcoin returns and multifractal properties of the Bitcoin market by employing the rolling window method and examines relationships between the volatility asymmetry and market efficiency. Whilst we find an inverted asymmetry in the volatility of Bitcoin, its magnitude changes over time, and recently, it has become small. This asymmetric pattern of volatility also exists in higher frequency returns. Other measurements, such as kurtosis, skewness, average, serial correlation, and multifractal degree, also change over time. Thus, we argue that properties of the Bitcoin market are mostly time dependent. We examine efficiency-related measures: the Hurst exponent, multifractal degree, and kurtosis. We find that when these measures represent that the market is more efficient, the volatility asymmetry weakens. For the recent Bitcoin market, both efficiency-related measures and the volatility asymmetry prove that the market becomes more efficient.
    Date: 2021–02
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2102.07425&r=all
  18. By: ; ; Benjamin S. Kay
    Abstract: We use credit card data from the Federal Reserve Board's FR Y-14M reports to study the impact of the COVID-19 shock on the use and availability of consumer credit across borrower types from March through August 2020. We document an initial sharp decrease in credit card transactions and outstanding balances in March and April. While spending starts to recover by May, especially for risky borrowers, balances remain depressed overall. We find a strong negative impact of local pandemic severity on credit use, which becomes smaller over time, consistent with pandemic fatigue. Restrictive public health interventions also negatively affect credit use, but the pandemic itself is the main driver. We further document a large reduction in credit card originations, especially to risky borrowers. Consistent with a tightening of credit supply and a flight-to-safety response of banks, we find an increase in interest rates of newly issued credit cards to less creditworthy borrowers.
    Keywords: COVID-19; Bank lending; Consumer credit; Credit cards; Credit supply; Household spending
    JEL: E21 G21 G51 I18
    Date: 2021–02–02
    URL: http://d.repec.org/n?u=RePEc:fip:fedgfe:2021-08&r=all
  19. By: Gürtzgen, Nicole (Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany]); Lochner, Benjamin (Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany]); Pohlan, Laura (Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany]); Berg, Gerard J. van den
    Abstract: "This paper studies the effects of the high-speed internet expansion on the match quality of new hires. We combine data on internet availability at the local level with German individual register and vacancy data. Results show that internet availability has no major impact on the stability of new matches and their wages. We confirm these findings using vacancy data, by explicitly comparing match outcomes of online and non-online recruits. Further results show that online recruiting not only raises the number of applicants and the share of unsuitable candidates per vacancy, but also induces employers to post more vacancies." (Author's abstract, IAB-Doku) ((en)) Additional Information auch erschienen als: IZA discussion paper, 14031
    JEL: J64 H40 L96 C26
    Date: 2021–02–17
    URL: http://d.repec.org/n?u=RePEc:iab:iabdpa:202102&r=all
  20. By: T. Takaishi
    Abstract: This paper investigates the return-volatility asymmetry of Bitcoin. We find that the cross correlations between return and volatility (squared return) are mostly insignificant on a daily level. In the high-frequency region, we find thata power-law appears in negative cross correlation between returns and future volatilities, which suggests that the cross correlation is \revision{long ranged}. We also calculate a cross correlation between returns and the power of absolute returns, and we find that the strength of \revision{the cross correlations} depends on the value of the power.
    Date: 2021–02
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2102.08187&r=all
  21. By: Emmanuel Erem (Department of Economics, Maynooth University, Ireland.)
    Abstract: Exchange rate regimes have evolved a lot of the years, specifically the past century, right from the Gold standard to the Bretton Woods era that led to the creation of the International Monetary Fund (IMF) and Post Bretton Woods periods that have seen the emergence of currency unions and a whole range of hybrid and more sophisticated exchange rate regimes. This evolution has led to the emergence of de jure and de facto exchange rate regimes. This discrepancy can be very misleading and pervasive for monetary policy and stability. In this paper, we combine an empirical econometric approach to develop an algorithm that will classify the de facto regimes that countries are practising by modelling exchange rate bands and the behaviour of a particular currency towards an anchor. The sample is representative of the globe. We believe the algorithm performs well and may be adopted by monetary authorities and international bodies like the International Monetary Fund.
    Keywords: Exchange rate regime, algorithm
    JEL: F33
    Date: 2020–04
    URL: http://d.repec.org/n?u=RePEc:aly:journl:202049&r=all
  22. By: Hensvik, Lena (Uppsala University); Le Barbanchon, Thomas (Bocconi University); Rathelot, Roland (University of Warwick)
    Abstract: This paper measures the job-search responses to the COVID-19 pandemic using realtime data on vacancy postings and job ad views on Sweden’s largest online job board. First, new vacancy postings drop by 40%, similar to the US. Second, job seekers respond by searching less intensively, to the extent that effective labour market tightness increases during the first three months after the COVID outbreak. Third, they redirect their search towards less severely hit occupations, beyond what changes in vacancies would predict. Overall, these job search responses have the potential to amplify the labour demand shock.
    Keywords: coronavirus; search intensity; search direction; labour demand shock; job vacancies; online job board
    JEL: E24 J21 J22 J23 J62 J63 J64
    Date: 2021–01–22
    URL: http://d.repec.org/n?u=RePEc:hhs:ifauwp:2021_001&r=all
  23. By: Farid Naufal Aslam; Andry Alamsyah
    Abstract: The internet's rapid growth stimulates the emergence of start-up companies based on information technology and telecommunication (ICT) in Indonesia and Singapore. As the number of start-ups and its investor growth, the network of its relationship become larger and complex, but on the other side feel small. Everyone in the ICT start-up investment network can be reached in short steps, led to a phenomenon called small-world phenomenon, a principle that we are all connected by a short chain of relationships. We investigate the pattern of the relationship between a start-up with its investor and the small world characteristics using network analysis methodology. The research is conducted by creating the ICT start-up investment network model of each country and calculate its small-world network properties to see the characteristic of the networks. Then we compare and analyze the result of each network model. The result of this research is to give knowledge about the current condition of ICT start-up investment in Indonesia and Singapore. The research is beneficial for business intelligence purposes to support decision-making related to ICT start-up investment.
    Date: 2021–02
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2102.09102&r=all
  24. By: Gurvan Branellec (Brest Business School); Ji-Yong Lee (Audencia Business School)
    Abstract: La révolution technologique digitale touche l'ensemble des métiers de la finance. Elle conduit les régulateurs à encadrer les nouveaux acteurs qui ne cessent de gagner en popularité. Les pouvoirs publics sont confrontés à des impératifs complexes à concilier. D'un côté, ils souhaitent ouvrir le cadre juridique traditionnel afin d'intensifier la concurrence en permettant aux start-up Fintech de proposer des services financiers aux particuliers et aux entreprises. D'un autre côté, il est nécessaire de contrôler ces activités à risque et protéger ainsi le consommateur. La France est donc confrontée au défi de la construction d'un cadre juridique à même d'éviter de brider l'innovation des Fintech. Celles-ci étant en plein essor en Angleterre et aux États-Unis, il est pertinent de s'interroger sur la possibilité d'une prise en compte par la France des modèles réglementaires en vigueur dans ces pays, à défaut de mettre en place une réglementation différente. Notre travail tente d'apporter une contribution à cette problématique par le biais d'une conciliation entre la littérature juridique anglo-saxonne (anglaise et américaine) et celle en économie financière.
    Keywords: Business Law,Brest Business School. Contact : gurvan.branellecsbrest-bs.com. ** Professeur associé,Finance,Audencia Business School. Contact : jyleesaudencia.com
    Date: 2019–04–01
    URL: http://d.repec.org/n?u=RePEc:hal:journl:hal-02612617&r=all
  25. By: Tomaso Duso; Mattia Nardotto; Jo Seldeslachts
    Abstract: We provide an evaluation of the impact of public subsidy schemes that aimed to support the development of basic broadband infrastructure in rural areas of Germany. Such subsidies are subject to state aid control by the European Commission (EC). While the EC increasingly recognises the role of economic analysis in controlling public aid to companies, there are to date no full retrospective studies performed on state aid control, especially assessing the so-called balancing test. In this study, we do not only analyse whether the aid was effective in solving a market failure – low broadband coverage in rural areas – but also study its impact on competitive outcomes, on both rival firms and consumers. We adopt a difference-in-differences framework after using a matching procedure to account for selection on observables. We find that the aid significantly increased broadband coverage. More importantly, we find that the number of internet providers has significantly increased in the municipalities receiving aid. This additional entry decreased average prices. Therefore, the subsidies complied with EU state aid rules, both in terms of effectiveness and competition.
    Keywords: State aid, ex-post evaluation, broadband, coverage, entry, competition, prices
    JEL: C23 D22 L1 L4 L64
    Date: 2021
    URL: http://d.repec.org/n?u=RePEc:diw:diwwpp:dp1931&r=all
  26. By: Utz Weitzel; Michael Kirchler
    Abstract: Financial misbehavior is widespread and costly. The Dutch government legally requires every employee in the financial sector to take a Hippocratic oath, the so-called "banker's oath." We investigate whether moral nudges that directly and indirectly remind financial advisers of their oath affect their service. In a large-scale audit study, professional auditors confronted 201 Dutch financial advisers with a conflict of interest. We find that when auditors apply a moral nudge, referring to the banker's oath, advisers are less likely to prioritize bank's interests. In additional prediction tasks, we find that Dutch regulators expect stronger effects of the oath than observed.
    Keywords: experimental finance, audit study, banker?s oath, moral nudges, financial advice
    JEL: C92 D84 G02 G14
    Date: 2021–04
    URL: http://d.repec.org/n?u=RePEc:inn:wpaper:2021-04&r=all
  27. By: Masaki Aoyagi; Seung Han Yoo (Department of Economics, Korea University, Seoul, Republic of Korea)
    Abstract: A platform offers sellers and buyers trading opportunities by creating one-to-one matches between them. A matching mechanism consists of a menu of subscription plans for each side and specifies fees and the probabilities with which subscribers of each plan are matched with subscribers of different plans on the other side. We characterize optimal matching mechanisms which maximize the subscription revenue under the incentive compatibility conditions. When the agents are strategic in their interactions with their matched partners, we show that the optimal matching rule may not equal socially efficient positive assortative matching (PAM) but instead focus on the extraction of the agents’ informational rents. We then examine the efficiency of the optimal mechanism in two alternative scenarios in which the platform exercises stronger control over the interactions between the matched agents. When the subscription fee can be conditioned on the success of a transaction, we show that the optimal mechanism is efficient with PAM restored as the optimal matching rule. However, when the platform has full control over the allocation and price of the good, we show that the optimal mechanism employs PAM but may create efficiency distortions by blocking some efficient transactions.
    Keywords: assortative, screening, auction, subscription, revenue maximization
    JEL: D42 D47 D62 D82 L12
    Date: 2020
    URL: http://d.repec.org/n?u=RePEc:iek:wpaper:2010&r=all
  28. By: Marco Ortu; Nicola Uras; Claudio Conversano; Giuseppe Destefanis; Silvia Bartolucci
    Abstract: This work aims to analyse the predictability of price movements of cryptocurrencies on both hourly and daily data observed from January 2017 to January 2021, using deep learning algorithms. For our experiments, we used three sets of features: technical, trading and social media indicators, considering a restricted model of only technical indicators and an unrestricted model with technical, trading and social media indicators. We verified whether the consideration of trading and social media indicators, along with the classic technical variables (such as price's returns), leads to a significative improvement in the prediction of cryptocurrencies price's changes. We conducted the study on the two highest cryptocurrencies in volume and value (at the time of the study): Bitcoin and Ethereum. We implemented four different machine learning algorithms typically used in time-series classification problems: Multi Layers Perceptron (MLP), Convolutional Neural Network (CNN), Long Short Term Memory (LSTM) neural network and Attention Long Short Term Memory (ALSTM). We devised the experiments using the advanced bootstrap technique to consider the variance problem on test samples, which allowed us to evaluate a more reliable estimate of the model's performance. Furthermore, the Grid Search technique was used to find the best hyperparameters values for each implemented algorithm. The study shows that, based on the hourly frequency results, the unrestricted model outperforms the restricted one. The addition of the trading indicators to the classic technical indicators improves the accuracy of Bitcoin and Ethereum price's changes prediction, with an increase of accuracy from a range of 51-55% for the restricted model, to 67-84% for the unrestricted model.
    Date: 2021–02
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2102.08189&r=all
  29. By: Fab-Ukozor Nkem (Imo State University, Owerri); Onyebuchi Alexander Chima (Imo State University, Owerri); Obayi Paul Martins (Godfrey Okoye University, Enugu); Anorue Luke Ifeanyi (University of Nigeria Nsukka); Onwude Nnenna Fiona (Godfrey Okoye University, Enugu)
    Abstract: The growth in the use of social media in the developing world has encouraged most people and businesses to take the advert of their products or services to the social media. This study sought to find out how women are portrayed on social media adverts using the Goffman’s category, which indicates cases of stereotype and subjugation of women in the society. This study was anchored on the framing theory. The researchers used content analysis research design. Using Wimmer and Dominick online calculator on a population of 1,523, the researchers arrived at a sample size of 431 and increased it by 71% to obtain approximately 600. Code sheet and coding guide served as the instrument for data collection. The inter-coder reliability was established using Holsti and Pearson’s r formulas. Data analyses were done using the cluster approach. Using Goffman’s categories, this study revealed that women are subliminally portrayed as sex objects in some selected online ads. This is made evident in the results from body display, relative size, functional ranking, and family categories, which revealed that from the angle of Facebook, 33.8% of the pictures-based advert revealed body display, while on the part of Instagram, 28.9% of the videos showed significant body display. Further analysis revealed that picture (35.2%) and video (25.7%) adverts on Instagram have more propensity to show feminine touches than Facebook, and that over 35% of the video content on social media has one form of ritualization of subordination or the other.
    Keywords: Social Media, Advertising, Facebook, Instagram, Portrayal, Women
    Date: 2020–08
    URL: http://d.repec.org/n?u=RePEc:smo:apaper:019fun&r=all
  30. By: Fischer, Agneta; Brands, Charlotte; Abadi, David (University of Amsterdam)
    Abstract: When it comes to political communication on social media, Facebook has arisen as one of the most important platforms. Recent research on populist discourses provides evidence for populist ideology fragments emerging across Facebook posts. Moreover, the level of populist language styles and the adoption of typical populist rhetoric appears to be ‘endemic' across political actors across the whole political spectrum, even among non-populist ones. In total, 51 posts from Geert Wilders were analyzed before and 71 in the period after the 2019 Dutch elections (N = 122). This study tackles the use of the founding elements of populist communication strategies: references to the people, references to the elites, and references to the others. For a populist leader, Wilders’ Facebook posts do not contain many references to the people. Instead, he focuses on the elites (e.g., the EU) and on the others (e.g., Muslims or asylum seekers). The clearest difference between the pre- and post-election period seems to be that Wilders gradually changes his populist communication strategies from a focus on the elites, to a focus on the others. In doing so, he uses more references to religion and blaming the others. He also refers more to people within the country (asylum seekers and immigrants) in the post-election period (36,6%) than in the pre-election period (23,5%). His posts show clear examples of populist nativism, while he paints a picture of a battle between the Netherlands and the EU (the elites), Muslims or asylum seekers (the others).
    Date: 2019–11–20
    URL: http://d.repec.org/n?u=RePEc:osf:osfxxx:35puf&r=all

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