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on Payment Systems and Financial Technology |
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Issue of 2023‒09‒25
25 papers chosen by |
| By: | Martinez Cuellar, Cristina; Tesliuc, Cornelia M.; Jaupart, Pascal Jean Edouard; Manigat, Ailo Klara |
| Abstract: | The Adaptive Social Protection for Increased Resilience project (ASPIRE or PSARA for itsacronym in French), financed by The World Bank and implemented by the government of Haiti, aims to design andimplement a cash transfer program for vulnerable households in Haiti, with a focus on increasing financial inclusion anddigitizing payments. This report analyzes the financial inclusion landscape of beneficiaries; identifies demand-sidebarriers to the uptake of Digital Financial Services (DFS); and provides recommendations for promoting the use of DFSamong beneficiaries and their communities. The findings of this report show that while access to formal financialservices is limited, there is more access and usage of mobile money and informal services through the VillageSavings and Loan Associations (VSLAs). The report recommends actions to remove barriers to DFS usage, such as creatingand promoting DFS use cases among beneficiaries, increasing trust and confidence in using e-wallets, working withpolicymakers to provide IDs for beneficiaries and with regulators to reduce Know Your Customer (KYC) on low-tieraccounts, and increasing mobile phone ownership. Additionally, the report suggests strategies to support arobust DFS ecosystem, including designing attractive products for low-income customers and building a sustainableCash-in and Cash-out agent network. |
| Date: | 2023–07–01 |
| URL: | http://d.repec.org/n?u=RePEc:wbk:hdnspu:184762&r=pay |
| By: | Hanfeng Chen; Maria Elena Filippin |
| Abstract: | We extend the Real Business Cycle model in Niepelt (2022) to analyze the risk to financial stability following the introduction of a central bank digital currency (CBDC). CBDC competes with commercial bank deposits as households' source of liquidity. We consider different degrees of substitutability between payment instruments and review the equivalence result in Niepelt (2022) by introducing a collateral constraint banks must respect when borrowing from the central bank. When CBDC and deposits are perfect substitutes, the central bank can offer loans to banks that render the introduction of CBDC neutral to the real economy. We show that the optimal level of the central bank's lending rate depends on the restrictiveness of the collateral constraint: the tighter it is, the lower the loan rate the central bank needs to post. However, when CBDC and deposits are imperfect substitutes, the central bank cannot make banks indifferent to the competition from CBDC. It follows that the introduction of CBDC has real effects on the economy. |
| Date: | 2023–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2308.10359&r=pay |
| By: | Phuong Duy Huynh; Son Hoang Dau; Xiaodong Li; Phuc Luong; Emanuele Viterbo |
| Abstract: | The rapid development of blockchain has led to more and more funding pouring into the cryptocurrency market, which also attracted cybercriminals' interest in recent years. The Ponzi scheme, an old-fashioned fraud, is now popular on the blockchain, causing considerable financial losses to many crypto-investors. A few Ponzi detection methods have been proposed in the literature, most of which detect a Ponzi scheme based on its smart contract source code or opcode. The contract-code-based approach, while achieving very high accuracy, is not robust: first, the source codes of a majority of contracts on Ethereum are not available, and second, a Ponzi developer can fool a contract-code-based detection model by obfuscating the opcode or inventing a new profit distribution logic that cannot be detected (since these models were trained on existing Ponzi logics only). A transaction-based approach could improve the robustness of detection because transactions, unlike smart contracts, are harder to be manipulated. However, the current transaction-based detection models achieve fairly low accuracy. We address this gap in the literature by developing new detection models that rely only on the transactions, hence guaranteeing the robustness, and moreover, achieve considerably higher Accuracy, Precision, Recall, and F1-score than existing transaction-based models. This is made possible thanks to the introduction of novel time-dependent features that capture Ponzi behaviours characteristics derived from our comprehensive data analyses on Ponzi and non-Ponzi data from the XBlock-ETH repository |
| Date: | 2023–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2308.16391&r=pay |
| By: | Andres Alonso-Robisco (Banco de España); Jose Manuel Carbo (Banco de España) |
| Abstract: | Central banks are increasingly using verbal communication for policymaking, focusing not only on traditional monetary policy, but also on a broad set of topics. One such topic is central bank digital currency (CBDC), which is attracting attention from the international community. The complex nature of this project means that it must be carefully designed to avoid unintended consequences, such as financial instability. We propose the use of different Natural Language Processing (NLP) techniques to better understand central banks’ stance towards CBDC, analyzing a set of central bank discourses from 2016 to 2022. We do this using traditional techniques, such as dictionary-based methods, and two large language models (LLMs), namely Bert and ChatGPT, concluding that LLMs better reflect the stance identified by human experts. In particular, we observe that ChatGPT exhibits a higher degree of alignment because it can capture subtler information than BERT. Our study suggests that LLMs are an effective tool to improve sentiment measurements for policy-specific texts, though they are not infallible and may be subject to new risks, like higher sensitivity to the length of texts, and prompt engineering. |
| Keywords: | ChatGPT, BERT, CBDC, digital money |
| JEL: | G15 G41 E58 |
| Date: | 2023–08 |
| URL: | http://d.repec.org/n?u=RePEc:bde:wpaper:2321&r=pay |
| By: | Lennart Ante; Friedrich-Philipp Wazinski; Aman Saggu |
| Abstract: | This paper investigates retail investor motivations for digital real estate ownership in the crypto-metaverse. Utilizing a detailed financial behavior survey of metaverse landowners' intrinsic and extrinsic motivations, we apply principal components analysis to uncover four distinct motivational groups: (1) Aesthetics and Identity, (2) Social and Community, (3) Speculation and Investment, and (4) Innovation and Technology. Our findings reveal that age, education, investment knowledge, risk-taking, and impulsivity significantly influence investor group membership. This research provides valuable insights to investors and developers, underscoring the potential of a platform to attract retail investors with speculative intentions, engagement longevity, and passive or active trading characteristics, contingent on unique crypto-metaverse attributes. |
| Date: | 2023–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2308.10309&r=pay |
| By: | Caterina Calsamiglia; Laura Doval; Alejandro Robinson-Cort\'es; Matthew Shum |
| Abstract: | Thick two-sided matching platforms, such as the room-rental market, face the challenge of showing relevant objects to users to reduce search costs. Many platforms use ranking algorithms to determine the order in which alternatives are shown to users. Ranking algorithms may depend on simple criteria, such as how long a listing has been on the platform, or incorporate more sophisticated aspects, such as personalized inferences about users' preferences. Using rich data on a room rental platform, we show how ranking algorithms can be a source of unnecessary congestion, especially when the ranking is invariant across users. Invariant rankings induce users to view, click, and request the same rooms in the platform we study, greatly limiting the number of matches it creates. We estimate preferences and simulate counterfactuals under different ranking algorithms varying the degree of user personalization and variation across users. In our case, increased personalization raises both user match utility and congestion, which leads to a trade-off. We find that the current outcome is inefficient as it lies below the possibility frontier, and propose alternatives that improve upon it. |
| Date: | 2023–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2308.14703&r=pay |
| By: | Turner, Katherine; Chin, Staly; Nguyen, Andrea; Pike, Susan |
| Abstract: | This study explores interest in, and the challenges faced by transit agencies and operators in the adoption of open-loop payment systems. The research team focuses on the ways that agencies view passenger needs in the context of adopting open payments. Challenges with cash payments, an increasingly cashless society, and the expanding offerings of digital payment options have spurred increased interest in open-loop payments among transit operators. Paying for transit with cash can require additional time at boarding, add extra steps for passengers who must pay with exact fare, and result in service inefficiencies. It presents security concerns for drivers, and administrative burdens for agencies. While the full costs of cash handling vary per agency, the cost of handling and moving cash may be considerable. Pioneering transit agencies are adopting open payment systems that accept credit cards, debit cards, and smartphone/watch-based transactions. However, there is a huge diversity among transit agencies and as such, agencies face different challenges and to different degrees when considering the adoption of open payment systems. Challenges can include financial barriers, capacity limitations, technological challenges, the duration of existing contracts, competing needs, and a number of passenger challenges such as lack of credit cards or smartphones, or lack of familiarity with the technology. This study uses data collected from California transit agencies in the fall of 2022 that gathered information about agency perceptions of open-loop payments and the challenges with adopting open fare collection systems, and whether assistance programs would benefit transit agencies interested in adopting open-loop payments. Results of the present study indicate that the majority of agencies are considering or have considered implementing open payment systems, but agencies are not fully aware of the assistance available from the California Integrated Travel Program to help in the transition to digital and open payment systems. This study sheds light on the challenges facing small to medium transit agencies in the transition of California’s transit systems to open-loop payment systems. View the NCST Project Webpage |
| Keywords: | Business, Social and Behavioral Sciences, Transit payments, open-loop payment, cashless transit, California Integrated Travel Project |
| Date: | 2023–09–01 |
| URL: | http://d.repec.org/n?u=RePEc:cdl:itsdav:qt63613602&r=pay |
| By: | Haochen Li; Maria Polukarova; Carmine Ventre |
| Abstract: | We take inspiration from statistical physics to develop a novel conceptual framework for the analysis of financial markets. We model the order book dynamics as a motion of particles and define the momentum measure of the system as a way to summarise and assess the state of the market. Our approach proves useful in capturing salient financial market phenomena: in particular, it helps detect the market manipulation activities called spoofing and layering. We apply our method to identify pathological order book behaviours during the flash crash of the LUNA cryptocurrency, uncovering widespread instances of spoofing and layering in the market. Furthermore, we establish that our technique outperforms the conventional Z-score-based anomaly detection method in identifying market manipulations across both LUNA and Bitcoin cryptocurrency markets. |
| Date: | 2023–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2308.08683&r=pay |
| By: | Gambato, Jacopo; Sandrini, Luca |
| Abstract: | We study the incentives of a streaming platform to bias consumption when products are vertically differentiated. The platform offers mixed bundles of content to monetize consumers' interest in variety and pays royalties to sellers based on the effective consumption of the content they produce. When products are not vertically differentiated, the platform has no incentive to bias consumption in equilibrium: the platform being active represents a Pareto-improvement compared to the case in which she is not. With vertical differentiation, royalties can differ; the platform always biases recommendations in favor of the cheapest content, which hurts consumers and the high-quality seller. Biased recommendation always diminishes the incentives of a seller to increase the quality of her content for a given demand. If a significant share of the users is ex-ante unaware of the existence of the sellers the platform can bias recommendations more freely, but joining the platform encourages investment in quality. The bias, however, can lead to inefficient allocation of R&D efforts. From a policy perspective, we propose this as a novel rationale for regulating algorithmic recommendations in streaming platforms. |
| Keywords: | platform economics, media economics, recommendation bias, innovation |
| JEL: | D4 L1 L5 |
| Date: | 2023 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:zewdip:23032&r=pay |
| By: | Dean Corbae; Pablo D'Erasmo; Kuan Liu |
| Abstract: | This paper discusses concentration in consumer credit markets with a focus on fintech lenders and residential mortgages. We present evidence that shows that concentration among fintech lenders is significantly higher than that for bank lenders and other nonbank lenders. The data also show that the overall concentration in mortgage lending has declined between 2011 and 2019, driven mostly by a reduction in concentration among bank lenders. We present a simple model to show that changes in lender financial technology (interpreted as improvements in quality of loan services) explain more than 50 percent of the increase in fintech market shares and 43 percent of the increase in fintech concentration. This change in concentration in the fintech industry may have important implications for regulatory policy and financial stability. |
| Keywords: | fintech; concentration; mortgage lending |
| JEL: | G2 L1 L5 |
| Date: | 2023–06–08 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedpwp:96316&r=pay |
| By: | Joshua S. Gans; Hanna Halaburda |
| Abstract: | The core premise of permissionless blockchains is their reliable and secure operation without the need to trust any individual agent. At the heart of blockchain consensus mechanisms is an explicit cost (whether work or stake) for participation in the network and the opportunity to add blocks to the blockchain. A key rationale for that cost is to make attacks on the network, which could be theoretically carried out if a majority of nodes were controlled by a single entity, too expensive to be worthwhile. We demonstrate that a majority attacker can successfully attack with a {\em negative cost}, which shows that the protocol mechanisms are insufficient to create a secure network, and emphasizes the importance of socially driven mechanisms external to the protocol. At the same time, negative cost enables a new type of majority attack that is more likely to elude external scrutiny. |
| Date: | 2023–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2308.06568&r=pay |
| By: | Tim Matthies; Thomas L\"ohden; Stephan Leible; Jun-Patrick Raabe |
| Abstract: | This research investigates the growing trend of retail investors participating in certain stocks by organizing themselves on social media platforms, particularly Reddit. Previous studies have highlighted a notable association between Reddit activity and the volatility of affected stocks. This study seeks to expand the analysis to Twitter, which is among the most impactful social media platforms. To achieve this, we collected relevant tweets and analyzed their sentiment to explore the correlation between Twitter activity, sentiment, and stock volatility. The results reveal a significant relationship between Twitter activity and stock volatility but a weak link between tweet sentiment and stock performance. In general, Twitter activity and sentiment appear to play a less critical role in these events than Reddit activity. These findings offer new theoretical insights into the impact of social media platforms on stock market dynamics, and they may practically assist investors and regulators in comprehending these phenomena better. |
| Date: | 2023–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2308.09968&r=pay |
| By: | BELLIA Mario (European Commission - JRC); DI GIROLAMO Francesca (European Commission - JRC); NAI FOVINO Igor (European Commission - JRC); PETRACCO GIUDICI Marco (European Commission - JRC); SPORTIELLO Luigi (European Commission - JRC); VESPE Michele (European Commission - JRC) |
| Abstract: | A digital euro contributes to strengthening the international role of the euro and Europe’s open strategic autonomy against other currencies, such as third country central bank digital currencies and private non-bank digital moneys. The proposal protects stability of the payment system by ensuring that the euro remains its reference point as the European economy keeps digitalizing. At the same time, introducing a digital euro could present some drawbacks that would need to be minimized by careful design options. |
| Date: | 2023–07 |
| URL: | http://d.repec.org/n?u=RePEc:ipt:iptwpa:jrc134382&r=pay |
| By: | de Cornière, Alexandre; Mantovani, Andrea; Shekhar, Shiva |
| Abstract: | We investigate the welfare effects of third-degree price discrimination by a two-sided platform that enables interaction between buyers and sellers. Sellers are heterogenous with respect to their per-interaction benefit, and, under price discrimination, the platform can condition its fee on sellers’ type. In a model with linear demand on each side, we show that price discrimination: (i) increases participation on both sides; (ii) enhances total welfare; (iii) may result in a strict Pareto improvement, with both seller types being better-off than under uniform pricing. These results, which are in stark contrast to the traditional analysis of price discrimination, are driven by the existence of cross-group network effects. By improving the firm’s ability to monetize seller participation, price discrimination induces the platform to attract more buyers, which then increases seller participation. The Pareto improvement result means that even those sellers who pay a higher price under discrimination can be better-off, due to the increased buyer participation. |
| JEL: | D42 D62 L11 L12 |
| Date: | 2023–08 |
| URL: | http://d.repec.org/n?u=RePEc:tse:wpaper:128428&r=pay |
| By: | Cameron Cornell; Lewis Mitchell; Matthew Roughan |
| Abstract: | Methodologies to infer financial networks from the price series of speculative assets vary, however, they generally involve bivariate or multivariate predictive modelling to reveal causal and correlational structures within the time series data. The required model complexity intimately relates to the underlying market efficiency, where one expects a highly developed and efficient market to display very few simple relationships in price data. This has spurred research into the applications of complex nonlinear models for developed markets. However, it remains unclear if simple models can provide meaningful and insightful descriptions of the dependency and interconnectedness of the rapidly developed cryptocurrency market. Here we show that multivariate linear models can create informative cryptocurrency networks that reflect economic intuition, and demonstrate the importance of high-influence nodes. The resulting network confirms that node degree, a measure of influence, is significantly correlated to the market capitalisation of each coin ($\rho=0.193$). However, there remains a proportion of nodes whose influence extends beyond what their market capitalisation would imply. We demonstrate that simple linear model structure reveals an inherent complexity associated with the interconnected nature of the data, supporting the use of multivariate modelling to prevent surrogate effects and achieve accurate causal representation. In a reductive experiment we show that most of the network structure is contained within a small portion of the network, consistent with the Pareto principle, whereby a fraction of the inputs generates a large proportion of the effects. Our results demonstrate that simple multivariate models provide nontrivial information about cryptocurrency market dynamics, and that these dynamics largely depend upon a few key high-influence coins. |
| Date: | 2023–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2308.15769&r=pay |
| By: | OECD |
| Abstract: | The digital security of communication networks is crucial to the functioning of our societies. Four trends are shaping networks, raising digital security implications: i) the increasing criticality of communication networks, ii) increased virtualisation of networks and use of cloud services, iii) a shift towards more openness in networks and iv) the role of artificial intelligence in networks. These trends bring benefits and challenges to digital security. While digital security ultimately depends on the decisions made by private actors (e.g. network operators and their suppliers), the report underlines the role governments can play to enhance the digital security of communication networks. It outlines key policy objectives and actions governments can take to incentivise the adoption of best practices and support stakeholders to reach an optimal level of digital security, ranging from light-touch to more interventionist approaches. |
| Date: | 2023–09–13 |
| URL: | http://d.repec.org/n?u=RePEc:oec:stiaab:358-en&r=pay |
| By: | ISHIKAWA Yoshifumi; NAKAMURA Ryohei |
| Abstract: | The advancement of electronic commerce, including online purchases through the internet, is astounding. Especially during the COVID-19 pandemic, there has been a significant increase in both the per-household expenditure on internet-related activities and the proportion of households making purchases through the internet, leading to a substantial expansion of the market size. Historically, local governments have aimed to boost intra-regional consumption by promoting commercial development within their areas, as the presence of large-scale retail stores in neighboring regions would result in consumption leakage. However, in the case of e-commerce, consumers may exhibit behavior driven by factors that are distinct from those influencing traditional store selection. In the case of e-commerce, where distance resistance is virtually absent, the potential for significant spatial disparity between consumption destinations and supply sources emerges. Consequently, this study delves into the determinants of purchase rates within e-commerce. The analysis indicates that factors such as the scale of retail store locations within the region, the age-specific population distribution, proximity to adjacent municipalities, and the degree of urbanization have an impact on purchase rates driven by e-commerce activities within the region. As consumer participation in e-commerce grows, it leads to a decrease in local purchase rates. This reduction in local purchase rates further affects regional circulation through the interconnected structures of industrial relationships and income consumption. In this study, the authors incorporate variations in intra-regional consumption rates into a small-region-level income-consumption endogenous interregional input-output model developed by the authors, enabling an analysis of the impact of the advancement of e-commerce on the regional economy. |
| Date: | 2023–08 |
| URL: | http://d.repec.org/n?u=RePEc:eti:rdpsjp:23029&r=pay |
| By: | Mas’ud, Abdulsalam; Mohammed, Sani Damamisau; Gimba, Yusuf Abdu |
| Abstract: | Recently, there has been an expansion in the deployment of digital systems and digital IDs among taxing authorities. However, little is known about the extent to which such technologies are being adopted, or about whether the data from them is being used strategically to improve tax administration. Even less is known about this in the context of subnational tax administration, although this could be very relevant in some contexts, such as Nigeria. This study investigates the extent of the adoption and strategic usage of data from e-tax systems and digital IDs among state internal revenue services (SIRSs) in Nigeria. Data was collected through qualitative interviews conducted within the SIRSs – one from each of the country’s six geopolitical zones, and within the Federal Inland Revenue Service (FIRS). The qualitative data from the interviews was evaluated using thematic analysis. The findings revealed that there is scope for improvement in the adoption and usage of data from e-tax systems and digital IDs among the SIRSs. It was also found that the extent of adoption and strategic data usage from e-tax systems by SIRSs likely improves states’ per capita internally generated revenue (IGR), but similar insights on the impact of digital IDs have not been obtained. Lastly, it was found that there are some lessons SIRSs could learn from FIRS in terms of strategic use of data from e-tax systems and digital IDs. Specifically, SIRSs need to integrate an audit risk engine and machine learning for performing analytics into their e-tax systems, and also automate the estimation of annual credits for withholding tax suffered, tax refunds and penalties, as well as tax audit management including case selection, allocation of auditors and generating audit reports. Some policy recommendations are offered that are consistent with these findings. |
| Keywords: | Finance, |
| Date: | 2023 |
| URL: | http://d.repec.org/n?u=RePEc:idq:ictduk:18075&r=pay |
| By: | Gautam Kumar Biswas; Faruque Ahamed |
| Abstract: | The study analyzed the impact of financial inclusion on the effectiveness of monetary policy in developing countries. By using a panel data set of 10 developing countries during 2004-2020, the study revealed that the financial inclusion measured by the number of ATM per 100, 000 adults had a significant negative effect on monetary policy, whereas the other measure of financial inclusion i.e. the number of bank accounts per 100, 000 adults had a positive impact on monetary policy, which is not statistically significant. The study also revealed that foreign direct investment (FDI), lending rate and exchange rate had a positive impact on inflation, but only the effect of lending rate is statistically significant. Therefore, the governments of these countries should make necessary drives to increase the level of financial inclusion as it stabilizes the price level by reducing the inflation in the economy. |
| Date: | 2023–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2308.12542&r=pay |
| By: | Rodríguez-Lesmes, Paul (Facultad de Economía Universidad del Rosario); Gutierrez, Luis H. (Facultad de Economía Universidad del Rosario); Urueña-Mejia, Juan Carlos (Facultad de Economía Universidad del Rosario; Corporacion Universitaria Minuto de Dios); Ortiz, Andres (Corporacion Universitaria Minuto de Dios, and Universidad de La Salle); Medina Rojas, Ivan (Corporacion Universitaria Minuto de Dios); Romero, Mauricio (Fundacion Capital) |
| Abstract: | The challenge for policymakers is providing good quality business training services that can reach vast numbers of firms while not expensive. This paper examines the marginal impact of implementing a free smartphone-based business training called Expertienda for Colombian microentrepreneurs. Using teams of local university students and a randomised control trial design, we invited microentrepreneurs to install the application in 2021 and follow up with them at least three times. The sample consisted of 1, 013 microentrepreneurs in 10 Colombian cities, for whom we collected administrative records on the application usage and observational and survey data one year after the implementation. We show that for every 100 incentivized businesses, 4 installed and used the app. Moreover, there is no evidence of spillovers at the local level regarding take-up. Regarding business performance, results show no evidence that the course affected financial inclusion, formalisation, or business practices indexes. |
| Keywords: | Financial inclusion; business practices; Formality; Digital training; Microbusiness |
| JEL: | C93 D22 O10 O17 |
| Date: | 2023–09–11 |
| URL: | http://d.repec.org/n?u=RePEc:col:000092:020902&r=pay |
| By: | Benjamin Monnery; François-Charles Wolff |
| Abstract: | Participatory democracy and public consultations are increasingly being used to shape public policy or resolve political issues. In France, the Grand Débat was launched in early 2019 as a democratic response to the Yellow Vests movement, a massive grassroots social protest. With more than 500, 000 participants, the Grand Débat platform was interpreted as a popular success by the government and the media, but little is known about which citizens expressed their opinions online. Although participants on the platform were anonymous and only answered public policy questions, we are able to infer their support for the Yellow Vests movement by using a second platform (a Facebook app) that asks similar questions as well as support for the Yellow Vests. We find that a large majority of participants in the Grand Débat did not support the Yellow Vests movement, in contrast to the general population at the time. This is evidence of a strong self-selection of participants on political grounds, resulting in a biased representation of French public opinion. |
| Keywords: | participatory democracy; social protest; public opinion; selection on observables and unobservables |
| JEL: | D71 D72 C53 |
| Date: | 2023 |
| URL: | http://d.repec.org/n?u=RePEc:drm:wpaper:2023-23&r=pay |
| By: | Gisli Gylfason (PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris sciences et lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, PJSE - Paris Jourdan Sciences Economiques - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris sciences et lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement) |
| Abstract: | How does social media affect the composition of political protests in the United States? Using early adoption of Twitter at the 2007 South by Southwest (SXSW) festival as a plausibly exogenous source of variation in county-level Twitter penetration (Müller & Schwarz, 2023), and comprehensive data on protest events, this paper finds that Twitter penetration increases the frequency of protests overall, but also radicalizes them. Twitter disproportionately fuels protests with participation of "extreme" groups-groups that are particularly militant, radical, or hateful. These effects do not depend on the topic of the protest nor political leaning. I also present survey evidence suggesting that coordination is not the only mechanism driving these results: An increase in county-level Twitter penetration implies an increase in respondent's willingness to justify violence against other people, normalizing the participation in extreme groups and extreme protests. |
| Keywords: | Twitter, Collective action, Protests, Social media, Information Technology |
| Date: | 2023–08 |
| URL: | http://d.repec.org/n?u=RePEc:hal:psewpa:halshs-04188189&r=pay |
| By: | Alexey Zaytsev; Alex Natekin; Evgeni Vorsin; Valerii Smirnov; Oleg Sidorshin; Alexander Senin; Alexander Dudin; Dmitry Berestnev |
| Abstract: | Given the escalating risks of malicious attacks in the finance sector and the consequential severe damage, a thorough understanding of adversarial strategies and robust defense mechanisms for machine learning models is critical. The threat becomes even more severe with the increased adoption in banks more accurate, but potentially fragile neural networks. We aim to investigate the current state and dynamics of adversarial attacks and defenses for neural network models that use sequential financial data as the input. To achieve this goal, we have designed a competition that allows realistic and detailed investigation of problems in modern financial transaction data. The participants compete directly against each other, so possible attacks and defenses are examined in close-to-real-life conditions. Our main contributions are the analysis of the competition dynamics that answers the questions on how important it is to conceal a model from malicious users, how long does it take to break it, and what techniques one should use to make it more robust, and introduction additional way to attack models or increase their robustness. Our analysis continues with a meta-study on the used approaches with their power, numerical experiments, and accompanied ablations studies. We show that the developed attacks and defenses outperform existing alternatives from the literature while being practical in terms of execution, proving the validity of the competition as a tool for uncovering vulnerabilities of machine learning models and mitigating them in various domains. |
| Date: | 2023–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2308.11406&r=pay |
| By: | KONISHI Yoko; SAITO Takashi; IGEI Naoya; MIYASHITA Yutaka; YAMAMOTO Naoto |
| Abstract: | This paper documents the daily lives of Japanese residents during the three-year period (2020-2022) of the COVID-19 pandemic using Consumption Big Data. We use retail store sales (POS) covering 344 items, including food, beverage, infection prevention, and household goods data from about 6, 000 stores nationwide, including supermarkets, convenience stores, home centers/discount stores, drug stores, and specialty stores. By looking at changes in the ranking of sales value, we were able to identify increases and decreases in sales by item, as well as items that are related to the pandemic. We also confirmed that the sales by item follow Zipf's law. Furthermore, we clustered the weekly series of sales from before the pandemic by their characteristics and observed changes in purchasing patterns and seasonality based on their classification. |
| Date: | 2023–08 |
| URL: | http://d.repec.org/n?u=RePEc:eti:rdpsjp:23028&r=pay |
| By: | Yifeng Philip Chen; Edward J. Oughton; Jakub Zagdanski; Maggie Mo Jia; Peter Tyler |
| Abstract: | Broadband connectivity is regarded as generally having a positive macroeconomic effect, but we lack evidence as to how it affects key economic activity metrics, such as firm creation, at a very local level. This analysis models the impact of broadband Next Generation Access (NGA) on new business creation at the local level over the 2011-2015 period in England, United Kingdom, using high-resolution panel data. After controlling for a range of factors, we find that faster broadband speeds brought by NGA technologies have a positive effect on the rate of business growth. We find that in England between 2011-2015, on average a one percentage increase in download speeds is associated with a 0.0574 percentage point increase in the annual growth rate of business establishments. The primary hypothesised mechanism behind the estimated relationship is the enabling effect that faster broadband speeds have on innovative business models based on new digital technologies and services. Entrepreneurs either sought appropriate locations that offer high quality broadband infrastructure (contributing to new business establishment growth), or potentially enjoyed a competitive advantage (resulting in a higher survival rate). The findings of this study suggest that aspiring to reach universal high capacity broadband connectivity is economically desirable, especially as the costs of delivering such service decline. |
| Date: | 2023–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2308.14734&r=pay |