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on Payment Systems and Financial Technology |
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Issue of 2023‒11‒20
24 papers chosen by |
| By: | \.Ibrahim Halil Efend\.io\u{g}lu; G\"okhan Akel; Bekir De\u{g}\.irmenc\.i; Dilek Aydo\u{g}du; Kamile Elmaso\u{g}lu; Hande Beg\"um Bum\.in Doyduk; Arzu \c{S}eker; Hatice Bah\c{c}e |
| Abstract: | Cryptocurrencies, enabling secure digital asset transfers without a central authority, are experiencing increasing interest. With the increasing number of global and Turkish investors, it is evident that interest in digital assets will continue to rise sustainably, even in the face of financial fluctuations. However, it remains uncertain whether consumers perceive blockchain technology's ease of use and usefulness when purchasing cryptocurrencies. This study aims to explain blockchain technology's perceived ease of use and usefulness in cryptocurrency purchases by considering factors such as quality customer service, reduced costs, efficiency, and reliability. To achieve this goal, data were obtained from 463 participants interested in cryptocurrencies in different regions of Turkey. The data were analyzed using SPSS Process Macro programs. The analysis results indicate that perceived ease of use and usefulness mediate the effects of customer service and reduced costs, efficiency, and security on purchase intention. |
| Date: | 2023–09 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2310.05970&r=pay |
| By: | Priyanka Bose; Dipanjan Das; Fabio Gritti; Nicola Ruaro; Christopher Kruegel; Giovanni Vigna |
| Abstract: | As cryptocurrency evolved, new financial instruments, such as lending and borrowing protocols, currency exchanges, fungible and non-fungible tokens (NFT), staking and mining protocols have emerged. A financial ecosystem built on top of a blockchain is supposed to be fair and transparent for each participating actor. Yet, there are sophisticated actors who turn their domain knowledge and market inefficiencies to their strategic advantage; thus extracting value from trades not accessible to others. This situation is further exacerbated by the fact that blockchain-based markets and decentralized finance (DeFi) instruments are mostly unregulated. Though a large body of work has already studied the unfairness of different aspects of DeFi and cryptocurrency trading, the economic intricacies of non-fungible token (NFT) trades necessitate further analysis and academic scrutiny. The trading volume of NFTs has skyrocketed in recent years. A single NFT trade worth over a million US dollars, or marketplaces making billions in revenue is not uncommon nowadays. While previous research indicated the presence of wrongdoings in the NFT market, to our knowledge, we are the first to study predatory trading practices, what we call opportunistic trading, in depth. Opportunistic traders are sophisticated actors who employ automated, high-frequency NFT trading strategies, which, oftentimes, are malicious, deceptive, or, at the very least, unfair. Such attackers weaponize their advanced technical knowledge and superior understanding of DeFi protocols to disrupt trades of unsuspecting users, and collect profits from economic situations that are inaccessible to ordinary users, in a "supposedly" fair market. In this paper, we explore three such broad classes of opportunistic strategies aiming to realize three distinct trading objectives, viz., acquire, instant profit generation, and loss minimization. |
| Date: | 2023–09 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2310.06844&r=pay |
| By: | Kazi Abdul, Mannan; Farhana, Khandaker Mursheda |
| Abstract: | Globally, large numbers of adults remain unbanked, and most of them live in rural areas of the Third World. The recent outbreak of the COVID-19 pandemic has shown us how inequalities in accessing financial services continue to affect us. However, digital financial inclusion has emerged as an effective tool used to tackle socioeconomic ills and drive economic development. In fact, due to these modern technological developments, the number of studies in this area is very limited, especially in the context of developing economies. This study examines the impacts of migrant remittances on digital financial inclusion within households in Bangladesh by using the Migration and Remittance Household Survey. To meet the research objectives of this study, a household survey was conducted and 2165 households interviewed in 2022–2023 in Bangladesh. The survey data collected was tested using univariate and multivariate estimations. This study finds that the coefficient of remittance has positive relationships with the probability of e-bank accounts and the use of mobile banking for a household’s financial transactions. However, the use of ATM cards by households for financial transactions has not been significantly affected. The article concludes that remittance flows may enhance access to and use of means of digital financial inclusion by reducing some of the barriers and costs in Bangladesh, which could greatly contribute to the country’s economic growth by creating and increasing a strong fund for investment. The findings of this study can help in taking various steps to facilitate the most powerful financial sector of Bangladesh, namely, remittance management. |
| Keywords: | digital financial inclusion; migration; remittance; household; rural–urban; Bangladesh |
| JEL: | O3 R00 R23 R29 |
| Date: | 2023–08–01 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:118936&r=pay |
| By: | Xuan Teng (LMU Munich) |
| Abstract: | Platforms often display their products ahead of third-party products in search. Is this due to consumers preferring platform-owned products or platforms engaging in self-preferencing by biasing search towards their own products? What are the welfare implications? I develop a structural model of mobile application markets to identify self-preferencing and quantify its welfare effects, taking into account third-party developers' quality adjustment. A new dataset on app downloads, prices, characteristics, and search rankings is used to estimate the model. Estimates indicate self-preferencing. Simulations show higher consumer welfare and third-party profits without self-preferencing. |
| Keywords: | competition policy; platform design; consumer search; endogenous product choice; |
| JEL: | D12 D83 L13 L86 |
| Date: | 2023–10–23 |
| URL: | http://d.repec.org/n?u=RePEc:rco:dpaper:434&r=pay |
| By: | Edson Pindza; Jules Clement Mba; Sutene Mwambi; Nneka Umeorah |
| Abstract: | Cryptocurrencies and Bitcoin, in particular, are prone to wild swings resulting in frequent jumps in prices, making them historically popular for traders to speculate. A better understanding of these fluctuations can greatly benefit crypto investors by allowing them to make informed decisions. It is claimed in recent literature that Bitcoin price is influenced by sentiment about the Bitcoin system. Transaction, as well as the popularity, have shown positive evidence as potential drivers of Bitcoin price. This study considers a bivariate jump-diffusion model to describe Bitcoin price dynamics and the number of Google searches affecting the price, representing a sentiment indicator. We obtain a closed formula for the Bitcoin price and derive the Black-Scholes equation for Bitcoin options. We first solve the corresponding Bitcoin option partial differential equation for the pricing process by introducing artificial neural networks and incorporating multi-layer perceptron techniques. The prediction performance and the model validation using various high-volatile stocks were assessed. |
| Date: | 2023–10 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2310.09622&r=pay |
| By: | De Marco, Stefano; Dumont, Guillaume; Helsper, Ellen; Díaz-Guerra, Alejandro; Antino, Mirko; Rodríguez-Muñoz, Alfredo; Martínez-Cantos, José-Luis |
| Abstract: | This article examines how inequalities in digital skills shape the outcomes of online job‐seeking processes. Building on a representative survey of Spanish job seekers, we show that people with high digital skill levels have a greater probability of securing a job online, because of their ability to create a coherent profile and make their application visible. Additionally, it is less probable that they will experience burnout during this process than job seekers with low digital skill levels. Given the concentration of digital skills amongst people with high levels of material and digital resources, we conclude that the internet enforces existing material and health inequalities. |
| Keywords: | burnout; digital exclusion; digital inequality; digital skills; online job-seeking; Spain; RTI2018‐ 098967‐A‐I00; Research support (LSE library); Internal fund |
| JEL: | R14 J01 |
| Date: | 2023–10–18 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:120497&r=pay |
| By: | Sebastian Doerr; Jon Frost; Leonardo Gambacorta; Vatsala Shreeti |
| Abstract: | The entry of big tech companies into the financial services sector can bring significant benefits in terms of efficiency and financial inclusion. Yet big techs can also quickly dominate markets, engage in discriminatory behaviour, and harm data privacy. This leads to the emergence of new trade-offs between policy goals such as financial stability, competition and privacy. Regulators, both domestically and internationally, are actively working to address these trade-offs. This paper provides an overview over the state of the literature and the policy debate. |
| Keywords: | big techs, financial inclusion, competition, financial stability, data privacy |
| JEL: | E51 G23 O31 |
| Date: | 2023–10 |
| URL: | http://d.repec.org/n?u=RePEc:bis:biswps:1129&r=pay |
| By: | Ms. Burcu Hacibedel; Hector Perez-Saiz |
| Abstract: | Failures in the crypto space—including the fall of Terra USD and the FTX debacle—have sparked calls for strengthening countries’ policy frameworks for crypto assets, including by enhanced regulation and supervision. How have these heightened concerns about crypto assets been picked up in systemic risk assessment, and what can be done going forward? In this paper, we introduce a conceptual macrofinancial framework to understand and track systemic risks stemming from crypto assets. Specifically, we propose a country-level Crypto-Risk Assessment Matrix (C-RAM) to summarize the main vulnerabilities, useful indicators, potential triggers and potential policy responses related to the crypto sector. We also discuss how experts and officials can weave in specific vulnerabilities stemming from crypto asset activity into their assessment of systemic risk, and how they can provide policy advice and take action to help contain systemic risks when needed. |
| Keywords: | Crypto assets; vulnerabilities; systemic risk; macrofinancial; analyzing Macrofinancial risk; macro-prudential risk; country-level Crypto-Risk Assessment Matrix; micro-prudential risk; price fluctuation; Virtual currencies; Financial sector; Currencies; Credit risk; Blockchain and DLT; Global |
| Date: | 2023–09–29 |
| URL: | http://d.repec.org/n?u=RePEc:imf:imfwpa:2023/214&r=pay |
| By: | Tom Akana; Valeria Zeballos Doubinko |
| Abstract: | In this paper, we explore the relationship between consumers’ use of buy now, pay later (BNPL) and their credit reports. BNPL is a deferred payment tool that allows consumers to split transactions into four payments over six weeks. Unlike many other financial products, it is offered primarily by fintech companies and advertised to consumers as free from fees and credit checks. These providers typically do not report a consumer’s use of BNPL and subsequent repayment behavior to credit bureaus, which makes studies of BNPL users’ credit more challenging. In this analysis, however, we leverage a unique data set combining anonymized survey data and appended credit bureau data collected by the market research firm Competiscan, on behalf of the Consumer Finance Institute (CFI) of the Federal Reserve Bank of Philadelphia. |
| Keywords: | buy now; pay later; BNPL; point-of-sale payments; consumer survey; credit reporting |
| JEL: | D10 D18 |
| Date: | 2023–09–28 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedpcd:96954&r=pay |
| By: | Nino Paulus; Lukas Lautenschlaeger; Wolfgang Schäfers |
| Abstract: | Problems and objective Social media platforms have become vibrant online platforms where people share their opinions and views on any topic (Yadav and Vishwakarma, 2020). With the increasing volume and speed of social media, the exchange of stock market-related information has become more important, which is why the effects of social media information on stock markets are becoming increasingly salient (Li et al., 2018). Business organizations need to understand these dynamics, as it reflects the interest of all kind of market participants – retail investors, institutional investors, but also clients, journalists and many others. Therefore, it is not surprising that there is evidence for public sentiment, obtained from social media, correlating with or even predicting economic indicators (e.g. Bollen et al., 2011; Sprenger et al., 2014; Xu and Cohen, 2018). Regarding real estate, Zamani and Schwartz (2017) successfully used Twitter language to forecast house price changes for a small sample at the county level. Except this limited research on real estate markets and the research for the general stock market, there is no more general study that examines the relationship between social media and real estate markets. Nevertheless, real estate markets are of particular interest, not only because of its popularity as an asset class among retail investors, but also because real estate is ubiquitous in daily life and the intransparency of the market. Sentiment indicators extracted from social media therefore promises to cover perspectives from all kinds of people and could therefore be more informative than traditional sentiment measures. However, as described by Li et al. (2018), social media-based sentiment indicators are not intended to replace traditional sentiment indicators, but rather complement them, as these are usually based on the knowledge of only a few industry insiders instead of that of the general public. Besides, the study focuses on indirect real estate (i.e. REITs) as it allows retail investors who represent the majority of social media users sharing equity-related information, to participate in real estate markets. Methodology & Data Using a dictionary-based approach, a classical machine learning approach as well as a deep learning based approach to extract the sentiment of approximately 4 million tweets, this paper compared methods of different complexity in terms of their ability to classify social media sentiment and predict indirect real estate returns on a monthly basis. The baseline for this comparison is a conventional dictionary-based approach including valence shifting properties. The dictionary used is the real estate specific dictionary developed Ruscheinsky et al. (2018). For the classical machine learning method, a support vector machine (SVM), which already has stated to be potent in a real estate context (Hausler et al., 2018), is utilized. The more complex deep learning approach is based on a Long Short-Term Memory (LSTM) model. The usefulness of deep learning-based approaches for sentiment analysis in a real estate context has been proven before by Braun et al. (2019). As high-tradevolume-stocks tend to be discussed most on Twitter, posts are collected from this platform (Xu and Cohen, 2018), including a ten-year timespan from 2013 to 2022. Hereby selection is made on the basis of cashtags representing all US REITs. The monthly total return of the FTSE Nareit allEquity Total Return states the dependent variable, whereby the created sentiment variable is the variable of interest. Contribution to science and practice The aim of this study is to create a standardized framework that enables investors of all kinds to better classify current market events and thus better navigate the opaque real estate market. This framework could be applied not only by investors, but vice versa by REITs to understand and optimize their position in society and in the investor landscape. To the authors knowledge, this is the first study to analyze the impact of social media sentiment on (indirect) real estate returns, based on a comprehensive national dataset. |
| JEL: | R3 |
| Date: | 2023–01–01 |
| URL: | http://d.repec.org/n?u=RePEc:arz:wpaper:eres2023_200&r=pay |
| By: | Athiphat Muthitacharoen; Athiphat Muthitacharoen |
| Abstract: | This study leverages the unique opportunities presented by the digitization of economic activity to investigate the impact of Thailand's 'Half and Half' program—a targeted, digital co-pay fiscal stimulus—on SMEs and consumer spending. Utilizing weekly province-level data from LINE MAN Wongnai, a leading digital delivery platform in Thailand, the study offers insights that were previously challenging to glean from traditional cash stimulus methods. My analysis employs a difference-in-difference framework, using program participation as the basis for the identification strategy. The study primarily focuses on the period from August to December 2021, which includes the program’s integration with delivery platforms in October 2021. I find that the 'Half and Half' program significantly elevates sales among participating vendors relative to nonparticipants. Regarding the underlying mechanism, the findings indicate that the increase in sales is primarily driven by an expansion in the unique customer base, rather than an increase in individual order sizes. Crucially, these positive effects persist even after the program’s conclusion, with smaller vendors experiencing more pronounced sustained benefits. On the consumer side, I find that the program leads to a considerable increase in total subsidy-inclusive spending, albeit with some substitution from non-program spending. The estimated marginal propensity to consumer (MPC) stands at 0.4, with a higher value in lower-income provinces. This investigation enriches the emerging literature on digital fiscal stimulus, underlining their potential for both immediate and sustained economic impact. The findings bear crucial implications for policymakers navigating fiscal strategies in an increasingly digital economic landscape. |
| Keywords: | fiscal stimulus, digital platform, SME, consumption |
| JEL: | D22 H32 O31 |
| Date: | 2023 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_10711&r=pay |
| By: | Fumiko Hayashi; Aditi Routh; Ying Lei Toh |
| Abstract: | Using multi-year survey data, we conduct a regression model analysis to examine which types of unbanked households are more likely to open a bank account and which types are less likely. We proxy for households’ likelihood of opening a bank account using their prior banking status and interest in having a bank account. Unbanked households who previously had a bank account and are interested in having a bank account are more likely to open an account. These households tend to be more educated, to be native-born, to use alternative financial services, and to have access to digital technology. In contrast, households who never had a bank account and are uninterested in a bank account are less likely to open an account. These households tend to be less educated, to be of a racial minority, to be foreign born, to lack access to digital technology, and to rely heavily on cash. Moreover, they tend to distrust banks. Advancing financial inclusion for this group will require strategies to increase their trust in the financial services industry. |
| Keywords: | unbanked consumers; financial services; racial equity |
| JEL: | D12 G21 G23 G41 |
| Date: | 2023–06–20 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedkrw:96698&r=pay |
| By: | Lara Berger (University of Cologne); Anna Kerkhof (University of Munich, ifo Institute for Economic Research, and CESifo); Felix Mindl (University of Cologne and iwp Institute for Economic Policy); Johannes Münster (University of Cologne) |
| Abstract: | We conduct a randomized survey experiment to compare the short-term and longer-term effects of fact checking to a brief media literacy intervention. We show that the impact of fact checking is limited to the corrected fake news, whereas media literacy helps to distinguish between false and correct information more generally, both immediately and two weeks after the intervention. A plausible mechanism is that media literacy enables participants to critically evaluate social media postings, while fact checking fails to enhance their skills. Our results promote media literacy as an effective tool to fight fake news, that is cheap, scalable, and easy-to-implement. |
| Keywords: | Covid, Facebook, fact checking, fake news, media literacy, misinformation, nutrition, social media, supplements, survey experiment, vaccine |
| JEL: | L51 L82 Z18 |
| Date: | 2023–10 |
| URL: | http://d.repec.org/n?u=RePEc:ajk:ajkdps:262&r=pay |
| By: | Christian Peukert; Margaritha Windisch |
| Abstract: | Intellectual property rights are fundamental to how economies organize innovation and steer the diffusion of knowledge. Copyright law, in particular, has developed constantly to keep up with emerging technologies and the interests of creators, consumers, and intermediaries of the different creative industries. We provide a synthesis of the literature on the law and economics of copyright in the digital age, with a particular focus on the available empirical evidence. First, we discuss the legal foundations of the copyright system and developments of length and scope throughout the era of digitization. Second, we review the literature on technological change with its opportunities and challenges for the stakeholders involved. We give special attention to empirical evidence on online copyright enforcement, changes in the supply of works due to digital technology, and the importance of creative re-use and new licensing and business models. We then set out avenues for further research identifying critical gaps in the literature regarding the scope of empirical copyright research, the effects of technology that enables algorithmic licensing, and copyright issues related to software, data and artificial intelligence. |
| Keywords: | copyright, digitization, technology, enforcement, licensing, business models, evidence |
| JEL: | K11 L82 L86 |
| Date: | 2023 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_10687&r=pay |
| By: | Waterson, Michael (University of Warwick) |
| Abstract: | This paper analyses the consumer impacts of arbitrage focusing on the significant role of internet platforms as monopolistic arbitrageurs between essentially competitive sub-markets that have not been previously linked. As arbitrageurs, there is the potential for them to create consumer benefit, but for a series of reasons, we show that consumer welfare may not be enhanced and that particular sections of the community may be disadvantaged by their actions. |
| Keywords: | Arbitrage ; Consumer welfare ; Platforms ; Two-sided markets JEL Codes: D51 ; L81 ; L86 ; D47 ; F11 |
| Date: | 2023 |
| URL: | http://d.repec.org/n?u=RePEc:wrk:warwec:1481&r=pay |
| By: | Debashrita Mohapatra; Debi Prasad Mohapatra; Ram Sewak Dubey |
| Abstract: | This paper studies the widespread price dispersion of homogeneous products across different online platforms, even when consumers can easily access price information from comparison websites. We collect data for the 200 most popular hotels in London (UK) and document that prices vary widely across booking sites while making reservations for a hotel room. Additionally, we find that prices listed across different platforms tend to converge as the booking date gets closer to the date of stay. However, the price dispersion persists until the date of stay, implying that the "law of one price" does not hold. We present a simple theoretical model to explain this and show that in the presence of aggregate demand uncertainty and capacity constraints, price dispersion could exist even when products are homogeneous, consumers are homogeneous, all agents have perfect information about the market structure, and consumers face no search costs to acquire information about the products. Our theoretical intuition and robust empirical evidence provide additional insights into price dispersion across online platforms in different institutional settings. Our study complements the existing literature that relies on consumer search costs to explain the price dispersion phenomenon. |
| Date: | 2023–10 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2310.12341&r=pay |
| By: | Merve Engür; Kerem Yavuz Arslanli |
| Abstract: | The commercial real estate sector is being transformed by technology and PropTech. Companies are increasingly looking for new alternatives and Blockchain has the potential to solve the issues about challenges, regarding liquidity and transparency by offering fresh alternatives for commercial real estate investors. The main problem examined is that the complexity of the leasing processes and the handling of the process with different actors make the whole process open to errors. Smart contracts using blockchain technology promise to solve this complexity in the contract process. Smart contracts are also claimed to form a structure where reliability and transparency are guaranteed. The purpose of smart contracts is to ensure that the lease agreement is signed, the rent is paid on time, and the contract termination is implemented in accordance with the terms. This research explores the application areas of smart contracts based on Blockchain technology and potential application innovations in the commercial property market and finds criteria for using smart contracts in property leasing. Smart contracts are an important example of the use of Blockchain technology in commercial real estate leasing. Therefore, it is essential to find criteria that allow the use of smart contracts in commercial property leasing. The criteria that smart contracts must meet in order to be preferable to the existing contract type are questioned and if these criteria are met, whether smart contracts can be used in the shopping center rental process has been researched. The criteria considered in the current lease agreement process, and the use of blockchain technology in the commercial real estate industry are explained. In commercial real estate contracts, the application areas of smart contracts are explored. The importance of the criteria in this process is determined through a survey of employees in commercial property leasing companies. The survey investigating the criteria for smart contracts to be used instead of existing lease contracts will be made to the target people and the survey results will be evaluated by a scoring method. The AHP method is used to integrate the criteria into the hierarchical structure and show which criteria are effective in the selection decision for the leasing contract process. The scoring system determines which criteria are more important than the others. Participants in the interview were asked which criterion they preferred over the others. The criteria that resulted from these surveys were scored using scoring matrices. The survey using the AHP method revealed the criteria and features that the leasing process must promise for the use of smart contracts. As a result, the opportunity for smart contracts to be integrated into the commercial property leasing process is being pursued. |
| Keywords: | blockchain; commercial property; Property Lease; Smart Contract |
| JEL: | R3 |
| Date: | 2023–01–01 |
| URL: | http://d.repec.org/n?u=RePEc:arz:wpaper:eres2023_213&r=pay |
| By: | Heinz Hollenstein (KOF Swiss Economic Institute, ETH Zurich, Switzerland) |
| Abstract: | The study provides evidence with respect to some topics of inter- and intra-firm diffusion of digital technology so far neglected in research. The analysis is based on a slightly extended version of the encompassing model of Battisti et al. (2009). We use a unique dataset that provides for the entire business sector information on the diffusion of 24 digital technologies ranging from old ones up to others developed only in recent years. We use the model, firstly, to analyse the determinants of the inter- and intra-firm diffusion of the entire set of digital technologies. Secondly, we do the same for six subfields of digital technology we identified by use of a factor analysis. Thirdly, we examine the effect of in-house learning on the intra-firm diffusion of digital technology. We distinguish between “cross-learning†(learning from previous experience with such technologies in subfields other than that considered) and “cumulative learning†(effect of previous application of relatively “old†digital technologies on the intensity of usage of advanced technology in the same or a closely related subfield). Finally, we analyse the determinants of a firm’s decision to digitalise a particular combination of two or more functional fields of its activity (fabrication, storage, marketing, etc.). The findings of this paper strongly support the underlying model in the case of the first and the second topic, whereas the evidence is somewhat weaker with regard to the third and the fourth element of the study. Finally, we find that complementing the “Battisti model†with variables representing firm-specific anticipated benefits is highly sensible, as these are powerful drivers of adoption and diffusion, which points to a strong forward-looking behaviour of firms in the diffusion process. |
| Keywords: | Adoption and diffusion of digital technologies, extent of digitalisation of business, inter- and intra-firm diffusion, Rank, stock/order and epidemic effects, effects of learning on the diffusion of IT, digitalisation of functional fields of firm activity |
| JEL: | O30 O31 O32 O33 |
| Date: | 2022–06 |
| URL: | http://d.repec.org/n?u=RePEc:kof:wpskof:22-504&r=pay |
| By: | Gustavo Berganti\~nos; Juan D. Moreno-Ternero |
| Abstract: | We study the problem of sharing the revenues raised from subscriptions to music streaming platforms among content providers. We provide direct, axiomatic and game-theoretical foundations for two focal (and somewhat polar) methods widely used in practice: pro-rata and user-centric. The former rewards artists proportionally to their number of total streams. With the latter, each user's subscription fee is proportionally divided among the artists streamed by that user. We also provide foundations for a family of methods compromising among the previous two, which addresses the rising concern in the music industry to explore new streaming models that better align the interests of artists, fans and streaming services. |
| Date: | 2023–10 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2310.11861&r=pay |
| By: | Roshan Iyer |
| Abstract: | We analyze returns and volatility spillovers among a representative set of crypto and financial assets. The magnitude of spillovers increases during periods of heightened turbulence due to negative economic-financial news, crypto market events, or exogenous shocks. There is evidence of increasing spillovers over time, with a peak during the COVID-19 pandemic, implying growing interdependence. Crypto assets predominantly transmit spillovers to financial markets, though reversals occur during periods of financial stress. The increased correlation during risk-off episodes suggests that crypto assets could serve as important conduits for financial market shocks, generating financial stability risks. |
| Keywords: | Cryptocurrencies; Crypto assets; Bitcoin; Spillovers; Return and Volatility Connectedness |
| Date: | 2023–09–29 |
| URL: | http://d.repec.org/n?u=RePEc:imf:imfwpa:2023/213&r=pay |
| By: | Conor B. Hamill; Raad Khraishi; Simona Gherghel; Jerrard Lawrence; Salvatore Mercuri; Ramin Okhrati; Greig A. Cowan |
| Abstract: | Interest-free promotions are a prevalent strategy employed by credit card lenders to attract new customers, yet the research exploring their effects on both consumers and lenders remains relatively sparse. The process of selecting an optimal promotion strategy is intricate, involving the determination of an interest-free period duration and promotion-availability window, all within the context of competing offers, fluctuating market dynamics, and complex consumer behaviour. In this paper, we introduce an agent-based model that facilitates the exploration of various credit card promotions under diverse market scenarios. Our approach, distinct from previous agent-based models, concentrates on optimising promotion strategies and is calibrated using benchmarks from the UK credit card market from 2019 to 2020, with agent properties derived from historical distributions of the UK population from roughly the same period. We validate our model against stylised facts and time-series data, thereby demonstrating the value of this technique for investigating pricing strategies and understanding credit card customer behaviour. Our experiments reveal that, in the absence of competitor promotions, lender profit is maximised by an interest-free duration of approximately 12 months while market share is maximised by offering the longest duration possible. When competitors do not offer promotions, extended promotion availability windows yield maximum profit for lenders while also maximising market share. In the context of concurrent interest-free promotions, we identify that the optimal lender strategy entails offering a more competitive interest-free period and a rapid response to competing promotional offers. Notably, a delay of three months in responding to a rival promotion corresponds to a 2.4% relative decline in income. |
| Date: | 2023–11 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2311.01901&r=pay |
| By: | Nicolas Wattiez; Hervé Goy (UJML - Université Jean Moulin - Lyon 3 - Université de Lyon, Laboratoire de Recherche Magellan - UJML - Université Jean Moulin - Lyon 3 - Université de Lyon - Institut d'Administration des Entreprises (IAE) - Lyon, Iaelyon - Iaelyon School of Management - UJML - Université Jean Moulin - Lyon 3 - Université de Lyon) |
| Abstract: | In France, public aid for financing research and innovation has multiplied since the beginning of the 2000s. With the advent of the "research tax credit", an innovation financing consulting industry has gradually developed. This niche of the business consulting sector has been little studied, so that the effects of digital transformation on the traditional business model of firms in the sector remain, to this day, largely unknown. This article aims to fill this gap based on a qualitative exploratory study of 16 players in the sector in France. Our results highlight three ways in which the business models of innovation financing consultancies have changed as a result of digitalisation. Finally, we discuss the similarities and differences with the results of similar studies conducted in the general consulting industry. |
| Abstract: | En France, les aides publiques au financement de la recherche et de l'innovation se sont multipliées depuis le début des années 2000. Avec l'avènement du crédit impôt recherche, une industrie du conseil en financement de l'innovation s'est progressivement développée. Cette niche du secteur du conseil aux entreprises a très peu été étudiée, si bien que les effets de la transformation numérique sur le modèle économique traditionnel des cabinets du secteur restent, jusqu'à ce jour, largement méconnus. Cet article vise à combler cette lacune à partir d'une étude qualitative à visée exploratoire menée auprès de 16 acteurs du secteur en France. Nos résultats mettent en évidence trois modalités d'évolution des modèles d'affaires des cabinets de conseil en financement de l'innovation sous l'effet de la numérisation. Les similitudes mais aussi les différences avec les résultats de travaux proches menés dans l'industrie du conseil généraliste sont finalement discutées. |
| Keywords: | Consulting – Digital transformation – Business model – Financing – Innovation, Conseil – Transformation numérique – Modèle économique – Financement – Innovation |
| Date: | 2023–06–28 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:halshs-04232253&r=pay |
| By: | Pongpitch Amatyakul; Panchanok Jumrustanasan; Pornchanok Tapkham |
| Abstract: | We investigate the impacts of fiscal transfers on households during the Covid-19 recovery period using a novel transaction-level money transfer dataset. The study focuses on direct fiscal transfers in 2021 that occurred as a result of the second major wave of Covid-19 in Thailand and analyses spending patterns for the recipients. We group the recipients by income levels and analyse patterns at the monthly and daily levels. The two main research questions are: (1) How much more spending did the groups make as a proportion of the fiscal stimulus? and (2) Did the stimulus makeup for lost spending during lock-down? We find that overall the recipients spent, on average, 40% of the money received over the first six days and 49% accumulatively over the first three months compared to a matched control group with similar characteristics. Unsurprisingly, the lower income group spent the highest proportion of the money received and the fiscal injection more than covered up for their lost spending during the lock-down period. |
| Keywords: | impacts of fiscal transfers, Covid-19, transaction-level data |
| JEL: | D12 H31 C55 |
| Date: | 2023–10 |
| URL: | http://d.repec.org/n?u=RePEc:bis:biswps:1130&r=pay |
| By: | Bram De Rock; Florine Le Henaff |
| Abstract: | We created a unique data set based on social media data by collecting and geo-localising all the tweets of 54 thousand Swedish citizens from January 2019 to June 2019. This allows us to construct an attractive individual-level measure of preferences for pro-environmental behavior. We demonstrate this by using our measure in two applications. We first document a subjective well-being gap between individuals with and without green preferences, using the average sentiment scores in tweets as a proxy of individuals’ subjective well-being. We then investigate the existence of a gender gap in green preferences and the propensity to act for the environment, relating our measure to publicly available data on electric and hybrid car registrations and political support for environmental policies in Sweden. |
| Keywords: | Individual preferences, social media, pro-environmental behavior, subjective well-being, gender identities |
| Date: | 2023–10 |
| URL: | http://d.repec.org/n?u=RePEc:eca:wpaper:2013/364363&r=pay |