nep-pay New Economics Papers
on Payment Systems and Financial Technology
Issue of 2020‒11‒16
25 papers chosen by

  1. Reliability and security at the dawn of electronic bank transfers in the 1970s-1980s By Maixe-Altes, J. Carles
  2. Multiscale characteristics of the emerging global cryptocurrency market By Marcin W\k{a}torek; Stanis{\l}aw Dro\.zd\.z; Jaros{\l}aw Kwapie\'n; Ludovico Minati; Pawe{\l} O\'swi\k{e}cimka; Marek Stanuszek
  3. Does Financial Literacy Influence Use of Mobile Financial Services in Malawi? Evidence from Malawi Household Survey Data By Mirriam Muhome Matita; Takondwa Chauma
  4. Automated Chat Application Surveys Using WhatsApp By Fei, Jennifer; Wolff, Jessica Sadye; Hotard, Michael; Ingham, Hannah; Khanna, Saurabh; Lawrence, Duncan; Tesfaye, Beza; Weinstein, Jeremy; Yasenov, Vasil; Hainmueller, Jens
  5. The digital transformation of the music industry. The second decade: From download to streaming By Dolata, Ulrich
  6. The Digital Revolution and COVID-19 By Paolo E. Giordani; Francesco Rullani
  7. Conditional beta and uncertainty factor in the cryptocurrency pricing model By Khanh Q. Nguyen
  8. Inside the regulatory sandbox: effects on fintech funding By Giulio Cornelli; Sebastian Doerr; Leonardo Gambacorta; Ouarda Merrouche
  9. Examining the Potential for Uber and Lyft to be Included in Subsidized MobilityPrograms Targeted to Seniors, Low Income Adults, and People with Disabilities By Deakin, Elizabeth SM., J.D.; Halpern, Jeremy; Parker, Madeleine
  10. The Benefits and Challenges of Incorporating Uber and Lyft in Subsidized Ride Programs that Serve Vulnerable Populations By Halpern, Jeremy; Deakin, Elizabeth; Parker, Madeleine
  11. Gamblers Learn from Experience By Matthew Olckers; Joshua E. Blumenstock
  12. Digital labour platforms and labour protection in China By Zhou, Irene.
  13. Fear and Volatility in Digital Assets By Faizaan Pervaiz; Christopher Goh; Ashley Pennington; Samuel Holt; James West; Shaun Ng
  14. The uncertain promise of blockchain for government By Juho Lindman; Jamie Berryhill; Benjamin Welby; Mariane Piccinin Barbieri
  15. Valuing Goods Online and Offline: the Impact of Covid-19 By Diane Coyle; David Nguyen
  16. Social Media and Newsroom Production Decisions By Julia Cagé; Nicolas Hervé; Béatrice Mazoyer
  17. `You Will:' A Macroeconomic Analysis of Digital Advertising By Jeremy Greenwood; Yueyuan Ma; Mehmet Yorukoglu
  19. Surveying Vocational Rehabilitation Applicants Online: A Feasibility Study By Jesse J. Chandler
  20. Machine learning in credit risk: measuring the dilemma between prediction and supervisory cost By Andrés Alonso; José Manuel Carbó
  21. A Predictive and Prescriptive Analytics Framework for Efficient E-Commerce Order Delivery By Kandula, Shanthan; Krishnamoorthy, Srikumar; Roy, Debjit
  22. Development of an Information System on the Taxi Industry By David, Jean
  23. Drugs on the Web, Crime in the Streets - The Impact of Dark Web Marketplaces on Street Crime By Diego Zambiasi
  24. Hollywood Survival Strategies in the Post-COVID 19 Era By Johnson, Michael Jr
  25. The Geography of Travel Behavior in the Early Phase of the COVID-19 Pandemic By Jeffrey Brinkman; Kyle Mangum

  1. By: Maixe-Altes, J. Carles
    Abstract: From a historical perspective, the concept of reliability and computing security in the early 1970s, when electronic data transfer processes were in infancy, is especially interesting in terms of their implications in technological change and the business of banking. The cases of Japan, Spain and Germany, in terms of their national banking networks, provide an interesting field of analysis in terms of the implications that the online data transfer systems had for banking institutions. Concerns about the reliability of the computing processes and digital security were the key factors. These innovations laid the foundation for the advancement of networks and new banking services that would open up unprecedented horizons in what was to become known as service banking.
    Keywords: computer security and reliability, banks and savings banks, teleprocessing networks, EFT, ICT in banking
    JEL: G21 O33
    Date: 2020–06
  2. By: Marcin W\k{a}torek; Stanis{\l}aw Dro\.zd\.z; Jaros{\l}aw Kwapie\'n; Ludovico Minati; Pawe{\l} O\'swi\k{e}cimka; Marek Stanuszek
    Abstract: The review introduces the history of cryptocurrencies, offering a description of the blockchain technology behind them. Differences between cryptocurrencies and the exchanges on which they are traded have been shown. The central part surveys the analysis of cryptocurrency price changes on various platforms. The statistical properties of the fluctuations in the cryptocurrency market have been compared to the traditional markets. With the help of the latest statistical physics methods the non-linear correlations and multiscale characteristics of the cryptocurrency market are analyzed. In the last part the co-evolution of the correlation structure among the 100 cryptocurrencies having the largest capitalization is retraced. The detailed topology of cryptocurrency network on the Binance platform from bitcoin perspective is also considered. Finally, an interesting observation on the Covid-19 pandemic impact on the cryptocurrency market is presented and discussed: recently we have witnessed a "phase transition" of the cryptocurrencies from being a hedge opportunity for the investors fleeing the traditional markets to become a part of the global market that is substantially coupled to the traditional financial instruments like the currencies, stocks, and commodities. The main contribution is an extensive demonstration that structural self-organization in the cryptocurrency markets has caused the same to attain complexity characteristics that are nearly indistinguishable from the Forex market at the level of individual time-series. However, the cross-correlations between the exchange rates on cryptocurrency platforms differ from it. The cryptocurrency market is less synchronized and the information flows more slowly, which results in more frequent arbitrage opportunities. The methodology used in the review allows the latter to be detected, and lead-lag relationships to be discovered.
    Date: 2020–10
  3. By: Mirriam Muhome Matita; Takondwa Chauma (Lilongwe University of Agriculture and Natural Resources, Malawi)
    Abstract: Mobile financial services are gaining prominence and could be a possible avenue for fast-tracking financial inclusion in developing countries, including Malawi. However, adoption and usage of such services remains low among the Malawi population. This study investigates the influence of financial literacy on financial behaviour of individuals in Malawi, specifically use of mobile phone-based financial transactions. Descriptive and econometric analyses were conducted using cross-sectional data obtained from the Reserve Bank of Malawi. Findings reveal that the likelihood of using mobile financial services increases with increasing levels of financial literacy, type of employment and peri-urban residence. Furthermore, men are more likely to transact on mobile phones than females and that although income levels matter in the use of mobile financial transactions, the magnitude of effect is negligible. Results suggest opportunities for expanding access to financial services and products such as differentiation in financial literacy education by characteristics of population including gender of users. Informal settings do not preclude expansion of digital payments, and therefore financial product innovation and addressing rural resident’s constraints to access mobile financial services is crucial.
    Date: 2019
  4. By: Fei, Jennifer; Wolff, Jessica Sadye; Hotard, Michael; Ingham, Hannah; Khanna, Saurabh; Lawrence, Duncan; Tesfaye, Beza; Weinstein, Jeremy; Yasenov, Vasil; Hainmueller, Jens
    Abstract: We present a method to conduct automated surveys over WhatsApp, a popular cross-platform messaging service. The method relies on a combination of the WhatsApp Business, Twilio, and Google APIs to design the survey flow, send and receive survey messages automatically, and facilitate data processing. Respondents complete the survey entirely within the WhatsApp application in the form of a chat conversation. WhatsApp surveys incur relatively low costs to both respondents and researchers and facilitate continued engagement with mobile populations as users can retain their WhatsApp number even if they change SIM cards and phone numbers. We describe the use of this method with two case studies where we surveyed refugees and migrants in Colombia, as well as resettled refugees in the U.S. The case studies offer preliminary evidence that automated surveys over WhatsApp provide a viable alternative for surveying and panel data collection. While the method is not without limitations, it offers a promising research tool with opportunities for diverse implementation and empirical study given the widespread global use of WhatsApp. We o?er documentation and a public code repository as supplementary materials to support researchers in applying this method in other contexts.
    Date: 2020–10–30
  5. By: Dolata, Ulrich
    Abstract: The music industry was the first media sector to be massively affected by digitization and the internet. In this paper, the strongly technology-driven transformation of the sector is first reconstructed, divided into distinguishable development phases and condensed into characteristic peculiarities of an extended socio-technical upheaval. Subsequently, the most recent change in the music market and consumption from buying to accessing music will be examined and the thesis will be pursued that the implementation of streaming gives rise to qualitatively new possibilities and patterns of a technically mediated observation of consumers, curation of music and commodification of the product.
    Date: 2020
  6. By: Paolo E. Giordani (Dept. of Economics and Finance, LUISS University); Francesco Rullani (Dept. of Management, Università Ca' Foscari Venice)
    Abstract: We develop a simple model of digital markets to analyze the impact of Covid-19 on the digital transformation of sectors. The lockdown due to Covid-19 is modeled as a shock that wipes out the physical market, temporarily leaving digital consumption as the only option. Under plausible assumptions on digital demand and supply, the model predicts that such temporary shock produces an irreversible rise of the digital markets. This happens for three distinct reasons. First, by temporarily eliminating the physical market, Covid-19 provides a strong incentive for firms to carry out the fixed investments necessary to venture into the digital market (supply channel). Secondly, by forcing even the most reluctant consumers into the digital market, Covid-19 pushes them to familiarize with digital platforms, and this confidence endures in the post-Covid era (demand channel). Finally, if consumers' taste for digitalization is affected by the size of the digital market, a market may be entrapped into a low-digital equilibrium indefinitely. In such context, the lockdown due to the pandemic is the shock that may unleash the forces of digitalization and tilt the entire sector towards a high-digital equilibrium (network externalities channel).
    Keywords: digital transformation, digitalization, Covid-19, pandemic, disruptive technologies
    JEL: O3 L8 D8
    Date: 2020–11
  7. By: Khanh Q. Nguyen
    Abstract: This research is to assess cryptocurrencies with the conditional beta, compared with prior studies based on unconditional beta or fixed beta. It is a new approach to building a pricing model for cryptocurrencies. Therefore, we expect that the use of conditional beta will increase the explanatory ability of factors in previous pricing models. Besides, this research is also a pioneer in placing the uncertainty factor in the cryptocurrency pricing model. Earlier studies on cryptocurrency pricing have ignored this factor. However, it is a significant factor in the valuation of cryptocurrencies because uncertainty leads to investor sentiment and affects prices.
    Date: 2020–10
  8. By: Giulio Cornelli; Sebastian Doerr; Leonardo Gambacorta; Ouarda Merrouche
    Abstract: Policymakers around the world are adopting regulatory sandboxes as a tool for spurring innovation in the financial sector while keeping alert to emerging risks. Using unique data for the UK, this paper provides initial evidence on the effectiveness of the world's first sandbox in improving fintechs' access to finance. Firms entering the sandbox see a significant increase of 15% in capital raised post-entry, relative to firms that did not enter; and their probability of raising capital increases by 50%. Our results furthermore suggest that the sandbox facilitates access to capital through two channels: reduced asymmetric information and reduced regulatory costs or uncertainty. Our results are confirmed when we exploit the staggered introduction of the sandbox and compare firms in earlier to those in later sandbox cohorts, and when we compare participating firms to a matched set of firms that never enters the sandbox.
    Keywords: fintech, regulatory sandbox, startups, venture capital.
    JEL: G32 G38 M13 O3
    Date: 2020–11
  9. By: Deakin, Elizabeth SM., J.D.; Halpern, Jeremy; Parker, Madeleine
    Abstract: Public agencies have subsidized taxi rides for people who have difficulty driving a car or using the regular transit system – targeting older residents and people with disabilities. There is interest among public agencies to add transportation network companies (TNCs), such as Uber and Lyft, to subsidized ride programs as a travel option due to the widespread availability of TNCs and high-quality service. Key issues include the need for wheelchair accessible vehicles, subsidy needs, and clients who lack or are uncomfortable using a smartphone and credit card. This research included a review of programs nationwide and interviews with program managers and clients to identify best practices. Best practices from agencies included contracting for wheelchair accessible TNC services, offering classes to help clients learn how to use the needed technologies, arranging for prepaid debit cards, creating a centralized billing system, providing a concierge service for those who need extra assistance, and setting subsidies based on need. Other recommended practices include providing high travel needs coverage, developing straightforward pricing structures, and not imposing restrictions on trip distance or trip purposes eligible for subsidy.
    Keywords: Social and Behavioral Sciences, Ridesourcing, paratransit services, taxi services, subsidies, persons with disabilities, aged, public transit, mobility applications, equity
    Date: 2020–10–01
  10. By: Halpern, Jeremy; Deakin, Elizabeth; Parker, Madeleine
    Abstract: Cities, transit agencies, and social service providers across the U.S. have implemented programs that provide taxi subsidies for people who have difficulty driving a car or using the regular transit system. These programs usually serve older residents and people with disabilities, though a few also serve low income users. Taxi subsidy programs provide curb-to-curb or door-to-door transportation at a fraction of the cost of paratransit.1 However, as Transportation Network Companies (TNCs), such as Uber and Lyft, have entered markets around the country, taxi availability has declined, resulting in lower levels of service. In response, many public agencies are considering the addition of TNCs to subsidized ride programs; however, the inclusion of TNCs in these programs is not straightforward. For example, agencies must evaluate the extent to which their clients need wheelchair accessible vehicles or other personal assistance. In addition, TNC platforms require users to request rides through a smartphone and use debit or credit cards for payment, which is problematic for unbanked customers and those who do not own or have access to a smartphone.
    Keywords: Social and Behavioral Sciences
    Date: 2020–10–01
  11. By: Matthew Olckers (SoDa Laboratories, Monash University); Joshua E. Blumenstock (SoDa Laboratories, Monash University)
    Abstract: Mobile phone-based gambling has grown wildly popular in Africa. Commentators worry that low ability gamblers will not learn from experience, and may rely on debt to gamble. Using data on financial transactions for over 50 000 Kenyan smartphone users, we find that gamblers do learn from experience. Gamblers are less likely to bet following poor results and more likely to bet following good results. The reaction to positive and negative feedback is of equal magnitude, and is consistent with a model of Bayesian updating. Using an instrumental variables strategy, we find no evidence that increased gambling leads to increased debt.
    Keywords: gambling, sports betting, mobile money, Bayesian updating
    JEL: D83 L83 O16
    Date: 2020–11
  12. By: Zhou, Irene.
    Abstract: The growth of digital labour platforms worldwide creates both opportunities and challenges to the world of work as well as the traditional approaches of regulating work and setting minimum stand- ards. This paper explores the implications of the digital labour platforms for labour regulation in China and the potential applicability of existing laws and regulations to platform work. It begins by defining platform work and reviewing its scope, composition and characteristics, with a focus on working con- ditions in China, followed by analysis on how labour regulation is complicated by the platform business models. In analysing the existing regulatory frameworks, the regulatory gaps become apparent. The paper concludes with policy options based on relevant international standards and the approaches to regulating platforms in other countries and the Chinese context, including its economic and policy environment as well as its industrial relations system.
    Date: 2020
  13. By: Faizaan Pervaiz; Christopher Goh; Ashley Pennington; Samuel Holt; James West; Shaun Ng
    Abstract: We show Bitcoin implied volatility on a 5 minute time horizon is modestly predictable from price, volatility momentum and alternative data including sentiment and engagement. Lagged Bitcoin index price and volatility movements contribute to the model alongside Google Trends with markets responding often several hours later. The code and datasets used in this paper can be found at r.
    Date: 2020–10
  14. By: Juho Lindman; Jamie Berryhill; Benjamin Welby; Mariane Piccinin Barbieri
    Abstract: Blockchain remains a hot topic for digital transformation and innovation. In the private sector, blockchain has demonstrated disruptive potential through proven use cases. However, despite strong interest and greater awareness, blockchain has had minimal impact on the public sector, where few projects have moved beyond small pilots. At the same time, there is a growing scepticism and cynicism about public sector blockchain. This paper seeks to understand why this is, by analysing the latest research in the area and identifying and analysing government experiences with successful and unsuccessful projects. It provides early findings on beliefs, characteristics, and practices related to government blockchain projects and the organisations that seek to implement them, with a focus on factors contributing to success or non-success. Although blockchain has yet to affect government in the ways that early hype predicted, government decision makers will nonetheless need to understand and monitor this emerging technology.
    Date: 2020–11–16
  15. By: Diane Coyle; David Nguyen
    Abstract: This paper uses a survey representative of the UK online population to assess the willingness to accept loss of certain goods. We had conducted an initial survey in February, focusing on ‘free’ online goods and some potential substitutes and comparators. Consistent with other contingent valuation studies, consumers on average assigned valuations to many of these goods, particularly when benchmarked against revenue figures for the services. Our pilot studies, discussed in a forthcoming paper, also suggested that the actual valuations are not well anchored, but the methodology can give consistent rankings among goods. It is also a useful way to assess changes in valuations. Repeating the survey in May, during the UK, lockdown, we observed significant changes in the valuations of different goods and services, with some large differences by age and gender. In this sense the lockdown has acted as a natural experiment testing for the extent to which digital goods and physical goods are substitutes. These valuation changes may indicate which services are most valuable in a post-pandemic world where more activity takes place online. They also provide important, policy-relevant insights into distributional questions.
    Keywords: digital services, valuations, lockdown
    JEL: D12 D60 I31 C43
    Date: 2020–07
  16. By: Julia Cagé (Sciences Po Paris, Department of Economics, 28 rue des Saints Pères, 75007 Paris, France, and CEPR (London)); Nicolas Hervé (Institut National de l'Audiovisuel, 28 avenue des Frères Lumière, 94366 Bry-sur-Marne, France); Béatrice Mazoyer (CentraleSupélec, Université Paris-Saclay, 91190 Gif-sur-Yvette, France, and Institut National de l'Audiovisuel, 28 avenue des Frères Lumière, 94366 Bry-sur-Marne, France)
    Abstract: Social media affects not only the way we consume news, but also the way news is produced, including by traditional media outlets. In this paper, we study the propagation of information from social media to mainstream media, and investigate whether news editors are influenced in their editorial decisions by stories popularity on social media. To do so, we build a novel dataset including a representative sample of all tweets produced in French between July 2018 and July 2019 (1.8 billion tweets, around 70% of all tweets in French during the period) and the content published online by about 200 mainstream media during the same time period, and develop novel algorithms to identify and link events on social and mainstream media. To isolate the causal impact of popularity, we rely on the structure of the Twitter network and propose a new instrument based on the interaction between measures of user centrality and news pressure at the time of the event. We show that story popularity has a positive effect on media coverage, and that this effect varies depending on media outlets’ characteristics. These findings shed a new light on our understanding of how editors decide on the coverage for stories, and question the welfare effects of social media.
    Keywords: Internet, Information spreading, Network analysis, Social media, Twitter, Text analysis
    JEL: C31 D85 L14 L15 L82 L86
    Date: 2020–10
  17. By: Jeremy Greenwood (University of Pennsylvania); Yueyuan Ma (University of Pennsylvania); Mehmet Yorukoglu (Koc University)
    Abstract: A model is developed where traditional and digital advertising finance the provision of free media goods and affect price competition. The economy is not efficient. Media goods are under provided. Additionally, there is too much advertising when ads cannot be perfectly directed toward potential buyers. The tax-cum-subsidy policy that overcomes these inefficiencies is characterized. The model is calibrated to the U.S. economy. The movement toward digital advertising increases consumer welfare significantly and is disproportionately financed by better-off consumers. The welfare gain from the optimal tax-cum-subsidy policy is much smaller than the one realized by the introduction of digital advertising. This is a report on research in progress.
    Keywords: advertising, consumer welfare, free media goods, directed and undirected advertising, leisure, price competition, public policy
    Date: 2020–10
  18. By: nanda, Sinta Alisa qortrun
    Abstract: Tentang bagaimana crownfunding diterapkan di digital humanity
    Date: 2020–10–02
  19. By: Jesse J. Chandler
    Abstract: Web surveys enable efficient data collection, but their usefulness is potentially limited when studying people with disabilities, who often lack Internet access. In this study, we test the feasibility of collecting web survey data from a sample of state vocational rehabilitation applicants.
    Keywords: vocational rehabilitation, assessment/evaluation
  20. By: Andrés Alonso (Banco de España); José Manuel Carbó (Banco de España)
    Abstract: New reports show that the financial sector is increasingly adopting machine learning (ML) tools to manage credit risk. In this environment, supervisors face the challenge of allowing credit institutions to benefit from technological progress and financial innovation, while at the same ensuring compatibility with regulatory requirements and that technological neutrality is observed. We propose a new framework for supervisors to measure the costs and benefits of evaluating ML models, aiming to shed more light on this technology’s alignment with the regulation. We follow three steps. First, we identify the benefits by reviewing the literature. We observe that ML delivers predictive gains of up to 20?% in default classification compared with traditional statistical models. Second, we use the process for validating internal ratings-based (IRB) systems for regulatory capital to detect ML’s limitations in credit risk mangement. We identify up to 13 factors that might constitute a supervisory cost. Finally, we propose a methodology for evaluating these costs. For illustrative purposes, we compute the benefits by estimating the predictive gains of six ML models using a public database on credit default. We then calculate a supervisory cost function through a scorecard in which we assign weights to each factor for each ML model, based on how the model is used by the financial institution and the supervisor’s risk tolerance. From a supervisory standpoint, having a structured methodology for assessing ML models could increase transparency and remove an obstacle to innovation in the financial industry.
    Keywords: artificial intelligence, machine learning, credit risk, interpretability, bias, IRB models
    JEL: C53 D81 G17
    Date: 2020–10
  21. By: Kandula, Shanthan; Krishnamoorthy, Srikumar; Roy, Debjit
    Abstract: Achieving timely last-mile order delivery is often the most challenging part of an e-commerce order fulfillment. Effective management of last-mile operations can result in significant cost savings and lead to increased customer satisfaction. Currently, due to the lack of customer availability information, the schedules followed by delivery agents are optimized for the shortest tour distance. Therefore, orders are not delivered in customer-preferred time periods resulting in missed deliveries. Missed deliveries are undesirable since they incur additional costs. In this paper, we propose a decision support framework that is intended to improve delivery success rates while reducing delivery costs. Our framework generates delivery schedules by predicting the appropriate delivery time periods for order delivery. More specifically, the proposed framework works in two stages. In the first stage, order delivery success for every order throughout the delivery shift is predicted using machine learning models. The predictions are used as an input for the optimization scheme, which generates delivery schedules in the second stage. The proposed framework is evaluated on two real-world datasets collected from a large e-commerce platform. The results indicate the effectiveness of the decision support framework in enabling savings of up to 10.6% in delivery costs when compared to the current industry practice.
    Date: 2020–11–05
  22. By: David, Jean
    Keywords: Public Economics
    Date: 2020–10–22
  23. By: Diego Zambiasi
    Abstract: The Dark Web has changed the way drugs are traded globally by shifting trade away from the streets and onto the web. In this paper, I study whether the Dark Web has an impact on street crime, a common side effect of traditional drug trade. To identify a causal effect, I use daily data from the US and exploit unexpected shutdowns of large online drug trading platforms. In a regression discontinuity design, I compare crime rates in days after the shutdowns to those immediately preceding them. I find that shutting down Dark Web markets leads to a significant increase in drug trade in the streets. However, the effect is short-lived. In the days immediately following shutdowns, drug-related crimes increase by five to almost ten percent but revert to pre-shutdown levels within ten days. I find no impact of shutdowns of Dark Web marketplaces on thefts, assaults, homicides and prostitution.
    Keywords: Dark web; Darknet markets; Drugs; Crime
    JEL: K42 L13
    Date: 2020–09
  24. By: Johnson, Michael Jr (California State University Northridge)
    Abstract: Since the arrival of the Coronavirus in the United States, Americans have been forced to quarantine themselves at home in dramatic fashion, unlike almost any other time in the nation’s history. Moreover, the American workforce has been equally impacted by virtue of state-imposed shutdowns that have affected innumerable businesses, including the Hollywood entertainment industry, which is the subject of this research. I examine how commercial entertainment conglomerates like AT&T, Comcast, Disney, ViacomCBS, and Fox have responded to mandatory closures for businesses that employ a human workforce upon whom they rely for their labor, and to human consumers they seek to distribute their film and television commodities to for profit . Using textual and discourse analyses in a political economic theoretical framework, I review contemporary reports about the economic conditions which have influenced the industry’s technological adaptation and innovation and argue that the Hollywood television and film industries will capitalize upon this current public health crisis as a motivator to adopt streaming platforms as the new preferred distribution mechanism of entertainment long after COVID 19 is a memory. This qualitative research examines the technological adaptations employed by these entertainment conglomerates to analyze (1) how the transition to streaming video on demand has occurred, and evaluates (2) what the adoption of these survival strategies mean for Hollywood’s long-term economic future and survival in a “digitally competitive” (Smith and Telang 2017) marketplace.
    Date: 2020–11–05
  25. By: Jeffrey Brinkman; Kyle Mangum
    Abstract: We use a panel of county-level location data derived from cellular devices in the U.S. to track travel behavior and its relationship with COVID-19 cases in the early stages of the outbreak. We find that travel activity dropped significantly as case counts rose locally. People traveled less overall, and they specifically avoided areas with relatively larger outbreaks, independent of government restrictions on mobility. The drop in activity limited exposure to out-of-county virus cases, which we show was important because such case exposure generated new cases inside a county. This suggests the outbreak would have spread faster and to a greater degree had travel activity not dropped accordingly. Our findings imply that the scale and geographic network of travel activity and the travel response of individuals are important for understanding the spread of COVID-19 and for policies that seek to control it.
    Keywords: travel behavior; mobility; COVID-19 pandemic; spatial dynamics; spacial networks; cellular device location
    JEL: R11 I18 H11
    Date: 2020–09–28

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