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on Payment Systems and Financial Technology |
|
Issue of 2019‒07‒15
forty-six papers chosen by |
| By: | Emanuele Borgonovo; Stefano Caselli; Alessandra Cillo; Donato Masciandaro; Giovanno Rabitti |
| Abstract: | The aim of this paper is to analyze the demand of both traditional and new media of exchange – as cryptocurrencies and central bank digital currencies – proposing a novel specification of the demand for money. In this specification, the medium of payment (MOP) has three properties: the first two are the MOP’s standard functions as a medium of exchange and as a store of value, while the third is a novel function as a store of privacy (anonymity value). The proposed framework is tested using a laboratory experiment. Our results show that anonymity matters, but less of the other two properties; at the same time, the presence of anonymity increases the overall appeal of a MOP, particularly if the individuals are risk prone; given anonymity, the sacrifice ratio between liquidity risk and opportunity cost are relatively high. |
| Keywords: | Money, Cryptocurrencies, Central bank Digital Currency, Cash, Baumol, Friedman, Experimental economics |
| JEL: | B22 D72 E41 E42 E52 E58 G38 K42 |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:baf:cbafwp:cbafwp1895&r=all |
| By: | Akana, Tom (Federal Reserve Bank of Philadelphia) |
| Abstract: | The Consumer Finance Institute hosted a workshop in August 2018 featuring Michael Marx, senior director at Visa, Inc., to discuss recent data from the Visa Payment Panel, highlighting the evolution of consumer payment preferences since the Great Recession and the passage of the Credit Card Accountability Responsibility and Disclosure (CARD) Act of 2009. A number of intriguing trends were discussed. Debit card adoption and growth have shown signs of slowing, even as regulatory changes have increased its prevalence recently among younger consumers. Credit card usage continues to grow and has shifted largely to rewards-based products. Payment preferences for younger consumers appear to be influenced by the availability of financial products (driven by social and regulatory influences) as well as the advent of mobile wallets and person-to-person (P2P) technologies. This paper summarizes Marx’s presentation along with additional research. |
| Keywords: | Consumer payments; credit cards; debit cards; P2P; CARD Act |
| JEL: | D14 G28 |
| Date: | 2019–07–02 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedpdp:19-01&r=all |
| By: | Philip ME Garboden (Department of Urban and Regional Planning, University of Hawai‘i at Manoa) |
| Abstract: | This chapter considers the types of Big Data that have proven useful for macroeconomic forecasting. It first presents the various definitions of Big Data, proposing one we believe is most useful for forecasting. The literature on both the opportunities and challenges of Big Data are presented. It then proposes a taxonomy of the types of Big Data: 1) Financial Market Data; 2) E-Commerce and Credit Cards; 3) Mobile Phones; 4) Search; 5) Social Media Data; 6) Textual Data; 7) Sensors, and The Internet of Things; 8) Transportation Data; 9) Other Administrative Data. Noteworthy studies are described throughout. |
| Keywords: | big data, data sources |
| JEL: | C80 |
| Date: | 2019–07 |
| URL: | http://d.repec.org/n?u=RePEc:hae:wpaper:2019-3&r=all |
| By: | Maria Glenski; Tim Weninger; Svitlana Volkova |
| Abstract: | Social media signals have been successfully used to develop large-scale predictive and anticipatory analytics. For example, forecasting stock market prices and influenza outbreaks. Recently, social data has been explored to forecast price fluctuations of cryptocurrencies, which are a novel disruptive technology with significant political and economic implications. In this paper we leverage and contrast the predictive power of social signals, specifically user behavior and communication patterns, from multiple social platforms GitHub and Reddit to forecast prices for three cyptocurrencies with high developer and community interest - Bitcoin, Ethereum, and Monero. We evaluate the performance of neural network models that rely on long short-term memory units (LSTMs) trained on historical price data and social data against price only LSTMs and baseline autoregressive integrated moving average (ARIMA) models, commonly used to predict stock prices. Our results not only demonstrate that social signals reduce error when forecasting daily coin price, but also show that the language used in comments within the official communities on Reddit (r/Bitcoin, r/Ethereum, and r/Monero) are the best predictors overall. We observe that models are more accurate in forecasting price one day ahead for Bitcoin (4% root mean squared percent error) compared to Ethereum (7%) and Monero (8%). |
| Date: | 2019–07 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1907.00558&r=all |
| By: | Li Haoliang |
| Abstract: | With tremendous market of mobile phone keeps expanding, the application has changed the main platform from computer to mobile phone. As the mobile app has been a way of life, the impact of them should not be neglected. Some of them bring a lot convenience to us, undoubtedly. But the same way, the negative impact of mobile app could also be a hidden trouble in our life, especially social apps, which we use most frequently. This paper focuses on the development of applications, how social apps are impacting on our life, and what can we do to avoid the bad and use the good. Key Words:apps, social apps, life, applications Policy |
| Date: | 2018–03 |
| URL: | http://d.repec.org/n?u=RePEc:vor:issues:2018-25-06&r=all |
| By: | Ignasi Merediz-Sol\`a; Aurelio F. Bariviera |
| Abstract: | Blockchain technology, and more specifically Bitcoin (one of its foremost applications), have been receiving increasing attention in the scientific community. The first publications with Bitcoin as a topic, can be traced back to 2012. In spite of this short time span, the production magnitude (1162 papers) makes it necessary to make a bibliometric study in order to observe research clusters, emerging topics, and leading scholars. Our paper is aimed at studying the scientific production only around bitcoin, excluding other blockchain applications. Thus, we restricted our search to papers indexed in the Web of Science Core Collection, whose topic is "bitcoin". This database is suitable for such diverse disciplines such as economics, engineering, mathematics, and computer science. This bibliometric study draws the landscape of the current state and trends of Bitcoin-related research in different scientific disciplines. |
| Date: | 2019–06 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1906.08933&r=all |
| By: | Jia Barwick, Panle; Liu, Yanyan; Patacchini, Eleonora; Wu, Qi |
| Abstract: | Information is a crucial ingredient in economic decision making. Yet measuring the extent of information exchange among individuals and its effect on economic outcomes is a difficult task. We use the universe of de-identified cellphone usage records from more than one million users in a Chinese city over twelve months to quantify information exchange among individuals and examine the role of referrals -- human carriers of information -- in urban labor markets. We present the first evidence that information flow (measured by call volume) correlates strongly with worker flows, a pattern that persists at different levels of geographic aggregation. Condition on information flow, socioeconomic diversity in information sources (social contacts), especially that associated with the working population, is crucial and helps to predict worker flows. We supplement our phone records with auxiliary data sets on residential housing prices, job postings, and firm attributes from administrative data. Information passed on through referrals is valuable: referred jobs are associated with higher monetary gains, a higher likelihood to transition from part-time to full-time, reduced commuting time, and a higher probability of entering desirable jobs. Referral information is more valuable for young workers, people switching jobs from suburbs to the inner city, and those changing their industrial sector. Firms receiving referrals are more likely to have successful recruits and experience faster growth. |
| Keywords: | Entrop; Information; Mobile Communication; Social Networks; Urban Labor Market |
| JEL: | J60 L15 R23 |
| Date: | 2019–06 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:13786&r=all |
| By: | Brunnermeier, Markus K; Niepelt, Dirk |
| Abstract: | We develop a generic model of money and liquidity that identites sources of liquidity bubbles and seignorage rents. We provide sufficient conditions under which a swap of monies leaves the equilibrium allocation and price system unchanged. We apply the equivalence result to the "Chicago Plan," cryptocurrencies, the Indian de-monetization experiment, and Central Bank Digital Currency (CBDC). In particular, we show why CBDC need not undermine financial stability. |
| Keywords: | CBDC; Chicago Plan; equivalence; Inside money; monetary system; money creation; outside money; sovereign money |
| Date: | 2019–06 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:13778&r=all |
| By: | Sneha Master |
| Abstract: | Internet has brought technological innovations at a rapid pace. As an aid to the accounting firms and professional service organizations Cloud Accounting has brought about unquestionable benefits to various industries across the globe . Cloud Accounting enhances the velocity with which applications are deployed, brings out innovation, lowers cost and also makes the business agile. Many companies like Facebook, Google & Amazon have implemented this technology in their business module which enables the organizations to manage their perfect portfolio. The main aim of this paper is to examine and analyze the pros and cons of this technology, its operational module and its benefits for the purpose of accounting and financial reports. Key Words:Cloud, Cloud Computing , Cloud Accounting Policy |
| Date: | 2018–12 |
| URL: | http://d.repec.org/n?u=RePEc:vor:issues:2018-28-15&r=all |
| By: | Mahesh Thakker |
| Abstract: | Blockchain is a foundational change in how financial records are created, kept, and updated. Rather than having one single owner, blockchain records are distributed among all their users. The genius of the blockchain approach is in using a complex system of consensus and verification to ensure that, even with no central owner and with time lags between all the users, nevertheless a single, agreed-upon version of the truth propagates to all users as part of a permanent record. This creates a kind of ‘universal entry bookkeeping’, where a single entry is shared identically and permanently with every participant. This paper describes the technology and its likely impact on business, and in particular on the accounting profession. Key Words:blockchain, finance, accounting, book keeping Policy |
| Date: | 2018–12 |
| URL: | http://d.repec.org/n?u=RePEc:vor:issues:2018-28-14&r=all |
| By: | Simplice A. Asongu (Yaoundé/Cameroon); Nicholas M. Odhiambo (Pretoria, South Africa) |
| Abstract: | This study examines the role of information and communication technology (ICT) on remittances for industrialisation in a panel of 49 African countries for the period 1980-2014. The empirical evidence is based on three simultaneity-robust estimation techniques, namely: (i) Instrumental Fixed Effects (FE) in order to control for the unobserved heterogeneity; (ii) Generalised Method of Moments (GMM) to account for persistence in industrialisation; and (iii) Instrumental Quantile Regressions (QR) to control for initial levels of industrialisation. Our best estimators are from FE and QR estimations because the GMM regression outputs largely fail post-estimation diagnostic tests. The following findings are established: (i) There are positive marginal effects from the interaction between remittances and ICT in the FE regressions whereas there are negative marginal impacts from the interaction between remittances and ICT; (ii) Interactions between remittances and mobile phone penetration are positive in the bottom and 90th quantiles whereas the interaction between internet penetration and remittances is positive in the bottom and top quantiles of the industrialisation distribution. Overall, the role of ICT in remittances for industrialisation is much more apparent when existing levels of industrialisation are accounted for. The findings contribute to the debates on the importance of external flows and information infrastructure in economic growth as well as the relevance of remittances in driving economic development in environments where institutions are weak. The value of the study to scholars and policy makers also builds on the fact that the potential for ICT and remittances in Africa can be leveraged to address development challenges on the continent such as the low level of industrialisation. |
| Keywords: | Remittances; Industrialisation; ICT; Africa |
| JEL: | F24 F43 O30 O55 |
| Date: | 2019–01 |
| URL: | http://d.repec.org/n?u=RePEc:exs:wpaper:19/024&r=all |
| By: | David Byrne; Carol Corrado |
| Abstract: | This paper develops a framework for measuring digital services in the face of ongoing innovations in the delivery of content to consumers. We capture what Brynjolfsson and Saunders (2009) call "free goods" as the capital services generated by connected consumers' stocks of IT digital goods, a service flow that augments the existing measure of personal consumption in GDP. Its value is determined by the intensity with which households use their IT capital to consume content delivered over networks, and its volume depends on the quality of the IT capital. Consumers pay for delivery services, however, and the complementarity between device use and network use enables us to develop a quality-adjusted price measure for the access services already included in GDP. Our new estimates imply that accounting for innovations in consumer content delivery matters: The innovations boost consumer surplus by nearly $1,800 (2017 dollars) per connected user per year for the full period of this study (1987 to 2017) and contribute more than 1/2 percentage point to US real GDP growth during the last ten. All told, our more complete accounting of innovations is (conservatively) estimated to have moderated the post-2007 GDP growth slowdown by nearly .3 percentage points per year. |
| JEL: | E01 E21 E22 O31 |
| Date: | 2019–06 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:26010&r=all |
| By: | Küfeoğlu, S.; Liu, G.; Anaya, K.; Pollitt, M. |
| Abstract: | This paper reviews digitalisation in energy sector by looking at the business models of 40 interesting new start-up energy companies from around the world. These start-ups have been facilitated by the rise of distributed generation, much of it intermittent in nature. We review Artificial Intelligence (AI), Machine Learning, Deep Learning and Blockchain applications in energy sector. We discuss the rise of prosumers and small-scale renewable generation, highlighting the role of Feed-in-Tariffs (FITs), the Distribution System Platform concept and the potential for Peer-to-Peer (P2P) trading. Our aim is to help energy regulators calibrate their support new business models. |
| Keywords: | Feed-in tariff, Distribution System Platform, Peer-to-Peer, Blockchain |
| JEL: | L94 |
| Date: | 2019–06–25 |
| URL: | http://d.repec.org/n?u=RePEc:cam:camdae:1956&r=all |
| By: | Sanal Kumar Velayudhan (Indian Institute of Management, Kozhikode) |
| Abstract: | Online shopping is growing rapidly but rural markets have low acceptance of this retail channel. Literature on rural online shopping is scarce and so the literature examining the influences on online shopping is used to draw inferences for rural markets. The review examines the influence of consumer characteristics on online shopping, product characteristics influence on online shopping, relative competitive ability of online and off-line retail business and their influence on online shopping and the influence of infrastructure on online shopping. The review of online shopping literature is used to draw implications for decision making and also to understand the research issues for online shopping in rural markets. |
| Keywords: | Online Shopping, Rural India, Consumer Characteristics |
| Date: | 2019–03 |
| URL: | http://d.repec.org/n?u=RePEc:iik:wpaper:314&r=all |
| By: | Yang Hu (University of Waikato); Les Oxley (University of Waikato); Chunlin Lang (Zhengzhou University) |
| Abstract: | We examine the predictive power of economic policy uncertainty, volume, transaction activity, and Twitter on Bitcoin between 27 December 2013 and 11 February 2019 using the recently proposed time-varying Granger causality tests of Shi et al. (2018). First, of particular interest, we show that volume can only predict Bitcoin returns during two episodes (August 2016-January 2017 and May 2017-June 2017) based on a Wald test with a recursive evolving procedure under a homoskedasticity error assumption. However, volume cannot predict volatility under any speciï¬ cations. Secondly, both US economic policy uncertainty and equity market uncertainty indices, which are used as proxies for policy uncertainty, have no effect on predicting Bitcoin returns. Thirdly, transaction activity also cannot predict Bitcoin returns. Lastly, the number of tweets about Bitcoin can Granger cause the volume of Bitcoin (for example, March 2015-August 2015 and January 2016-February 2019) but not returns or volatility. |
| Keywords: | Bitcoin; economic policy uncertainty; volume; transaction activity; Twitter; time-varying Granger causality |
| JEL: | C12 C32 G12 G15 |
| Date: | 2019–07–10 |
| URL: | http://d.repec.org/n?u=RePEc:wai:econwp:19/12&r=all |
| By: | Svetlana Shomova (National Research University Higher School of Economics) |
| Abstract: | Political Internet meme is an underresearched contemporary phenomenon situated at the interface of digital media and political communication. Regarded as a unit of online transmission of cultural information, such a meme can be considered, on the on hand, as a manifestation of post-folklore, and on the other hand, as a mechanism of political participation and construction of social media users’ collective identity. The article presents the results of investigation into Internet memes generated by protest discourse in Runet (Russian Internet). Examination of a vast amount of Internet content allows drawing conclusions as to the thematic emphases of protest actions represented in Runet’s memosphere and to the specifics of the image of Russian protest as reflected in memes |
| Keywords: | political communication, political participation, new media, meme, internet meme, protest, Russia |
| JEL: | Z19 |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:hig:wpaper:68/ps/2019&r=all |
| By: | Yin-Wong Cheung (City University of Hong Kong); Robert N McCauley (Bank for International Settlements); Chang Shu (Bloomberg) |
| Abstract: | We study the ongoing diffusion of renminbi trading across the globe, the first such research for an international currency. We analyse the distribution in offshore renminbi trading in 2013 and 2016, using comprehensive data from the central bank triennial survey of foreign exchange markets. In 2013, Asian centres favoured by the policy of renminbi internationalisation had big shares in global renminbi trading. In the following three years, renminbi trading seemed to converge to the spatial pattern of all currencies, with a half-life of 7-8 years. The previously most traded emerging market currency, the Mexican peso, shows a similar pattern, although it is converging to the global norm more slowly. Three other emerging market currencies show a qualitatively similar evolution in the geography of their offshore trading. Overall the renminbi’s internationalisation is tracing an arc from the influence of administrative measures to the working of market forces. |
| Keywords: | international currency, FX turnover, renminbi internationalisation, international financial centre |
| JEL: | C24 F31 F33 G15 G18 |
| URL: | http://d.repec.org/n?u=RePEc:cth:wpaper:gru_2019_011&r=all |
| By: | Santucci, Larry (Federal Reserve Bank of Philadelphia) |
| Abstract: | Secured credit cards--credit cards whose limit is fully or partially collateralized by a bank deposit--are considered a gateway product to mainstream credit access. As consumers demonstrate good usage and repayment behavior, they may be offered the opportunity to graduate to an unsecured credit card. This paper uses anonymized account-level data to examine the prevalence of account graduation in the secured credit card market since 2012. Using a fixed effects regression model, we identify a set of usage and repayment behaviors that are correlated with account graduation. |
| Keywords: | credit cards; secured credit cards; account graduation |
| JEL: | D14 G21 |
| Date: | 2019–07–02 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedpdp:19-02&r=all |
| By: | OECD |
| Abstract: | The fifth generation of wireless networks, 5G, represents an evolutionary process of previous generations of wireless networks (i.e. 2G, 3G, and 4G). This next generation of wireless technology is intended to provide 20 Gbps download speeds and latency of one millisecond (i.e. download speeds 200 faster and one-tenth the latency of current 4G networks). This report examines what the future of 5G could mean for communication markets in terms of investment, good practices in spectrum management, competition, coverage and meeting the increasing requirements of the digital transformation. Case studies from OECD countries are the focus of the report, approaching the issue from a two-fold perspective: 5G national strategies, and technological trials. The report also explores how 5G may represent a paradigm shift, as it is the first standard conceived with the Internet of Things (IoT) world in mind, where different connected devices have diverse network requirements. |
| Date: | 2019–07–11 |
| URL: | http://d.repec.org/n?u=RePEc:oec:stiaab:284-en&r=all |
| By: | Croitor, Evgheni; Benlian, Alexander |
| Date: | 2019–05–15 |
| URL: | http://d.repec.org/n?u=RePEc:dar:wpaper:113160&r=all |
| By: | Jose Aurazo (Central Reserve Bank of Peru); Jose Vasquez (Central Reserve Bank of Peru) |
| Abstract: | This paper extends the tourist test model proposed by Rochet and Tirole (2011) by incorporating the government in order to take into account informality (understood as tax evasion in cash payments) and the net social cost of cash usage. These two elements are relevant in developing countries, where the shadow economy tends to be large and merchants usually evade taxes in cash transactions. The tourist test aims to determine an interchange fee that does not increase merchants' operating cost of accepting card payments. In the presence of informality, the tax gap between card and cash payments reduces merchants' net operating bene t of accepting card sales, which in turn lowers the interchange fee that passes the tourist test. In addition, the interchange fee resulting from the social welfare maximization exceeds this tourist test threshold while the interchange fee that maximizes the total user surplus is still compatible with the tourist test. |
| Keywords: | Tourist test, card payments, tax evasion, developing countries |
| JEL: | G21 L11 H26 |
| Date: | 2019–06 |
| URL: | http://d.repec.org/n?u=RePEc:gii:giihei:heidwp11-2019&r=all |
| By: | Aleksina, Anna; Akulenka, Stanislau; Lublóy, Ágnes |
| Abstract: | Crowdfunding in medical research is becoming more popular due to the shrinking and increasingly competitive government funding. In order to inform researchers applying for this complementary source of research funding, we investigate the determinants of successful crowdfunding campaigns in medical research. We find that establishing and maintaining professional contacts through social media is of major importance for successful crowdfunding campaigns; an additional tweet or retweet significantly increases the success of crowdfunding campaigns. In contrast to the stated preferences of prospective donors, we document that crowdfunding campaigns might achieve their fundraising goal regardless of the disease characteristics. Scientists thus may ask funding for any kind of project, including therapies for rare diseases and diseases with lower mortality rate. |
| Keywords: | crowdfunding, medical research, stated preferences, revealed preferences, disease characteristics |
| JEL: | L65 H51 I19 O31 |
| Date: | 2019–07–03 |
| URL: | http://d.repec.org/n?u=RePEc:cvh:coecwp:2019/07&r=all |
| By: | Silvia Bartolucci; Andrei Kirilenko |
| Abstract: | We propose a modelling framework for the optimal selection of crypto assets. Crypto assets differ by two essential features: security (technological) and stability (governance). Investors make choices over crypto assets similarly to how they make choices by using a recommender app: the app presents each investor with a pair of crypto assets with certain security-stability characteristics to be compared. Each investor submits its preference for adopting one of the two assets to the app. The app, in turn, provides a recommendation on whether the proposed adoption is sensible given the assets' essential features, information about the adoption choices of all other investors, and expected future economic benefits of adoption. Investors continue making their adoption choices over all pairs of crypto assets until their expected future economic benefits can no longer be improved upon. This constitutes an optimal selection decision. We simulate optimal selection decisions considering the behaviour of different types of investors, driven by their attitudes towards assets' features. We find a variety of possible emergent outcomes for the investments in the crypto-ecosystem and the future adoption of the crypto assets. |
| Date: | 2019–06 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1906.09632&r=all |
| By: | Sungwon Lee (The Korea Transport Institute); Gyung Chuk Kim (The Korea Transport Institute); Seung Kook Wu (The Korea Transport Institute); Jieun Oh (The Korea Transport Institute) |
| Abstract: | This paper explores the impact that advances in Information and Communication Technology (ICT) have on the behaviour of transport users and their mode choice habits in Seoul. It discusses the stated preference survey conducted in Seoul and the analysis carried out using the discrete choice modelling approach to understand the sensitivity of the demand for private and public transport uses on time, cost and availability of ICT. |
| Date: | 2019–02–22 |
| URL: | http://d.repec.org/n?u=RePEc:oec:itfaab:2019/02-en&r=all |
| By: | Yuan Yuan; Tracy Liu; Chenhao Tan; Qian Chen; Alex Pentland; Jie Tang |
| Abstract: | Pay-it-forward reciprocity encourages the spread of prosocial behavior. However, existing empirical evidence of pay-it-forward behavior has been largely based on laboratory experiments, which are limited in sample size and external validity. Extending this research, our study uses a natural experiment to examine pay-it-forward reciprocity in a real-life context with a large-scale dataset of 3.4 million users of an online platform. Our natural experiment is enabled by the randomness in the mechanism that WeChat, a Chinese online social networking platform, uses to split an online monetary gift (also known as a "red packet") to its recipients. Our results show that recipients on average pay forward 10.34% of the amount they receive. We further find that "Luckiest draw" recipients, or those who obtain the largest shares of their corresponding red packets, are 1.5 times more likely to pay it forward than other recipients. Our analyses indicate that in a multiple recipient setting, users' pay-it-forward behavior is enforced by a group norm that luckiest draw recipients should send the first subsequent gift and promoted by their distributional social preferences of the random amounts split by the platform. Finally, our study shows that those recipients without any in-group friends do pay it forward, even though their pay-it-forward behavior is less likely to be driven by their reputational concerns among acquaintances. Overall, our work provides insights into mechanisms and conditions that encourage pay-it-forward reciprocity, which have implications for fostering prosocial behavior. |
| Date: | 2019–06 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1906.09698&r=all |
| By: | Sabiha Ghazali (Anjuman-I-Islam's IHMCT, Mumbai); Omkumar Krishnan (Indian Institute of Management, Kozhikode) |
| Abstract: | Over the last few years working from Home on a Digital Cloud is a trend that is being pursued and adopted in many industries. With considerable advancement in technology, the scope of this pattern of work has increased manifold. This paper reviews the concept of mobility in today’s time which is not merely restricted to wider office spaces where employees can move freely, but also about the technological ability of the employees to work from anywhere or any space feasible. The cloud system is an enabler for such mobility as it brings in scalability and flexibility. Virtual Desktop Infrastructure (VDI) helps the employees to see their work desktop from practically anywhere enabling them to work from anywhere at any time. With the evolution of Industry 4.0 which is an amalgamation of cyber and physical world, it is impossible to keep digitization away from our everyday life and the borders of working time and non-working time is narrow. In this scenario work life balance is beings lowly replaced by work life integration concept in various industries. The scope of the current study is limited to the Hotel Industry which is being transformed rapidly by the elements of Industry 4.0. The primary reasons for friction in transformation to this model of employment sited are(i) Employees are aware of this pattern of work but aren’t educated enough towards it, thus creating a mental block(ii) Companies are apprehensive to use this style of work primarily because of loss of control and the lack of being able to measure productivity. The objective of the paper aims to explore the concept of work from home in hotel industry through a literature review and understand the adoption feasibility in Indian Metropolitan cities. |
| Keywords: | Digital cloud, Cloud Computing, Hotel Industry |
| Date: | 2019–03 |
| URL: | http://d.repec.org/n?u=RePEc:iik:wpaper:313&r=all |
| By: | Maarten Goos (Utrecht School of Economics); Melanie Arntz (ZEW and University of Heidelberg); Ulrich Zierahn (ZEW); Terry Gregory (ZEW); Stephanie Carretero Gomez (European Commission - JRC); Ignacio Gonzalez Vazquez (European Commission - JRC); Koen Jonkers (European Commission - JRC) |
| Abstract: | New digital technologies more and more diffuse into the economy. Due to this digitisation, machines become increasingly able to perform tasks that previously only humans could to. Production processes and organizations are changing, new products, services and business models emerge. These trends have important implications for European labour markets. This working paper presents up-to date evidence on the consequences of technological innovations on labour markets based on the academic literature and discusses the resulting policy challenges along with examples of policy responses. One key finding is that so far recent technological change has had little effect on the aggregate number of jobs but leads to significant restructuring of jobs. This implies three key challenges for European labour markets: first, digitisation induces shifts in skill requirements, and workers’ fate in changing labour markets crucially depends on their ability to keep up with the change. Secondly, digitisation is not a purely technological process, but requires an accompanying process of organisational change. Thirdly, digitisation comes along with rising shares of alternative work arrangements, due to more outsourcing, standardisation, fragmentation, and online platforms. These alternative work arrangements imply both new opportunities and challenges. These challenges require adequate policy responses at the European, national and regional level, which the working paper outlines for education and training policies, active labour market policies, income policies, tax systems and technology policies. |
| Keywords: | Technical Change, Structural Change, Labour Markets, Europe |
| Date: | 2019–06 |
| URL: | http://d.repec.org/n?u=RePEc:ipt:laedte:201903&r=all |
| By: | Abhiman Das (Indian Institute of Management Ahmedabad); Ejaz Ghani (World Bank); Arti Grover (World Bank); William Kerr (Harvard Business School, Entrepreneurial Management Unit); Ramana Nanda (Harvard Business School, Entrepreneurial Managament Unit) |
| Abstract: | We use the construction of India's Golden Quadrangle (GQ) central highway network, together with comprehensive loan data drawn from the Reserve Bank of India, to investigate the interaction between infrastructure development and financial sector depth. We identify a disproportionate increase in loan count and average loan size in districts along the GQ highway network using stringent specifications with industry and district fixed effects. Our results hold in straight-line IV frameworks and are not present in 'placebo tests' with another highway that was planned to be upgraded at the same time as GQ but subsequently delayed. Importantly, however, results are concentrated in districts with stronger initial financial development, suggesting that while financing does respond to large infrastructure investments and help spur real economic outcomes, initial financial sector development might play an important role in determining where real activity will grow. |
| Date: | 2019–06 |
| URL: | http://d.repec.org/n?u=RePEc:hbs:wpaper:19-121&r=all |
| By: | Phil Goodwin (University of the West of England) |
| Abstract: | This paper looks at the roles of technologies and other factors in lifestyle choices, travel patterns and behaviours. Building on earlier Roundtable reports on value of time, it discusses how recent behavioural changes might affect the disutility of time spent travelling relative to time spent on other activities. The paper concludes with a discussion on the implications for policy practitioners around modelling and assessing value of travel time savings. |
| Date: | 2019–02–26 |
| URL: | http://d.repec.org/n?u=RePEc:oec:itfaab:2019/03-en&r=all |
| By: | Sebastian MP (Indian Institute of Management, Kozhikode) |
| Abstract: | Smart healthcare technologies are widely in use for the prevention and early diagnosis of diseases and are instrumental in transforming conventional medical care to patient-centric care. However, the traditional hospitals cannot entirely be replaced by home health systems, rather forcing them to become smart. The future smart hospitals are expected to have artificial intelligence (AI) tools for performing the patient diagnosis and robots for performing surgeries. The physicians will have the managing role, which could be performed through a touchscreen. This paper explores the challenges and opportunities associated with smart hospitals, and how they contribute to the objective of quality healthcare for everyone. The methodology used for the research is literature review. Machines do not have the common sense and blindly do what human beings instruct them to do. Thus, in spite of the digitalization and technology transformation of the healthcare processes, we cannot have hospitals without the human element. |
| Keywords: | AI,EHR, IoT, machine learning, smart heathcare, smart hospital, wearables |
| Date: | 2019–03 |
| URL: | http://d.repec.org/n?u=RePEc:iik:wpaper:315&r=all |
| By: | Simplice A. Asongu (Yaoundé/Cameroon); Nicholas M. Odhiambo (Pretoria, South Africa) |
| Abstract: | Inequality and gender economic exclusion are major policy concerns facing sub-Saharan Africa in the post-2015 development agenda. The study provides critical masses of inequality that should not be exceeded if governance is to promote gender economic participation. The research focuses on 42 countries in sub-Saharan Africa using annual data spanning from 2004 to 2014. The empirical evidence is based on the Generalized Method of Moments. The following findings are established. First, inequality (i.e. the Gini coefficient) levels that completely nullify the positive effect of governance on female labour force participation are 0.708 for political stability, 0.601 for voice & accountability, 0.588 for government effectiveness, 0.631 for regulatory quality, 0.612 for the rule of law, and 0.550 for corruption-control. Second, inequality thresholds at which female unemployment can no longer be mitigated by governance channels include: 0.561 (for political stability) and 0.465 (for the rule of law). Third, inequality levels that completely dampen the positive impact of governance on female employment are 0.608 for political stability, 0.580 for voice & accountability, 0.581 for government effectiveness, and 0.557 for the rule of law. As the main policy implication, for good governance to promote gender economic inclusion, inequality levels should not exceed established thresholds. |
| Keywords: | Africa; Gender; Inequality; Inclusive development |
| JEL: | G20 I10 I32 O40 O55 |
| Date: | 2019–01 |
| URL: | http://d.repec.org/n?u=RePEc:exs:wpaper:19/033&r=all |
| By: | Artur Kovalchuk (Kyiv School of Economics); Charles Kenny (Center for Global Development); Mallika Snyder (Center for Global Development) |
| Abstract: | This paper examines the impact of Ukraine’s ambitious procurement reform on outcomes amongst a set of procurements that used competitive tendering. The ProZorro system placed all of the country’s government procurement online, introduced an auction approach as the default procurement method, and extended transparency. The reform was introduced with a dramatic increase in the proportion of government procurement that was conducted competitively. This paper examines the impact of ProZorro and reform on contracts that were procured competitively both prior to and after the introduction of the new system. It finds some evidence of impact of the new system on increasing the number of bidders, cost savings, and reduced contracting times. |
| Keywords: | E-procurement, Transparency, Competition |
| JEL: | H57 D73 |
| Date: | 2019–06–11 |
| URL: | http://d.repec.org/n?u=RePEc:cgd:wpaper:511&r=all |
| By: | Kotas, Carsten |
| Abstract: | [Vorwort] Real Estate Crowdfunding (RECF) hat in den letzten Jahren international stark an Bedeutung gewonnen. In den USA wurde das erste gewinnorientierte Immobilienprojekt über eine Crowdfunding-Plattform im Jahr 2012 durch die Fundrise LLC (fundrise.com) realisiert. Die Kapitalfreunde GmbH startete im November 2012 die erste Plattform für Immobilien in Deutschland. Mittlerweile entwickelt sich RECF schnell und mit enormen Wachstumsraten, führt aber in Deutschland immer noch ein 'Schattendasein' bei der Immobilienfinanzierung. Aus der Sicht von Investoren verbindet RECF die Vorteile von direkten und indirekten Immobilieninvestments. Als Hauptvorteile von RECF werden insbesondere der leichte Zugang zur Assetklasse 'Immobilien', niedrige Minimuminvestments und geringe Transaktionskosten genannt. Ziel der Untersuchung ist die Klärung der Frage, ob es sich bei RECF um eine disruptive Finanzierungsform handelt, die die Dominanz des in Deutschland bei der Immobilienfinanzierung dominierenden Bankkredits infrage stellen könnte. Innovative Finanzierungsformen können ihr Potenzial nur dann voll entfalten, wenn die angebotenen Investitionsmöglichkeiten aus Sicht der Crowd (-Investoren) dem Fremdvergleich standhalten. Deswegen werden zunächst die rechtlichen Rahmenbedingungen für RECF in Deutschland aufgezeigt und im Anschluss alle zwischen 01.01.2012 und 31.12.2017 finanzierten Projekte nach einheitlichen Kriterien analysiert und aus Investorensicht miteinander verglichen. Die Datensätze umfassen insgesamt 188 Immobilienprojekte, die über 16 verschiedene Crowdfunding-Plattformen mit Hauptsitz in Deutschland finanziert wurden. Der vorliegende Beitrag aus der Reihe Arbeitspapiere der FOM liefert einen aktuellen und kompakten Beitrag zum wissenschaftlichen sowie praktischen Diskurs des Themenbereichs RECF. Dabei legt der Verfasser besonderen Wert darauf, RECF aus Sicht der Investoren zu beleuchten. Entscheidungen von Investoren erfolgen aufgrund individueller Rendite-Risikoabwägungen. In Deutschland überwogen in der Praxis bisher Nachrangdarlehen als gängige Finanzierungsinstrumente. Im Ergebnis lassen die steigenden Investitionsvolumina momentan lediglich den Schluss zu, dass diese Nachrangdarlehen eine sinnvolle Ergänzung für fehlendes Eigenkapital der Immobilienunternehmen darstellen. Umstritten bleibt, ob die Investoren eine adäquate Rendite als Kompensation für das eingegangene Risiko erzielen, da sie bei diesen Instrumenten letztendlich das Risiko eines Totalverlusts tragen. |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:fomarb:69&r=all |
| By: | Peng Wang (ECUST); Jun-Chao Ma (ECUST); Zhi-Qiang Jiang (ECUST); Wei-Xing Zhou (ECUST); Didier Sornette (ETH Zurich) |
| Abstract: | Empirical investor networks (EIN) proposed by \cite{Ozsoylev-Walden-Yavuz-Bildik-2014-RFS} are assumed to capture the information spreading path among investors. Here, we perform a comparative analysis between the EIN and the cellphone communication networks (CN) to test whether EIN is an information exchanging network from the perspective of the layer structures of ego networks. We employ two clustering algorithms ($k$-means algorithm and $H/T$ break algorithm) to detect the layer structures for each node in both networks. We find that the nodes in both networks can be clustered into two groups, one that has a layer structure similar to the theoretical Dunbar Circle corresponding to that the alters in ego networks exhibit a four-layer hierarchical structure with the cumulative number of 5, 15, 50 and 150 from the inner layer to the outer layer, and the other one having an additional inner layer with about 2 alters compared with the Dunbar Circle. We also find that the scale ratios, which are estimated based on the unique parameters in the theoretical model of layer structures \citep{Tamarit-Cuesta-Dunbar-Sanchez-2018-PNAS}, conform to a log-normal distribution for both networks. Our results not only deepen our understanding on the topological structures of EIN, but also provide empirical evidence of the channels of information diffusion among investors. |
| Date: | 2019–07 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1907.01119&r=all |
| By: | Onésimo Flores Dewey (Jetty) |
| Abstract: | This paper details the history of Jetty, an app-based collective transport platform operating in Mexico City since August 2017. It sets out the origins of the idea, recounts the strong competitive and regulatory pushback Jetty has faced, and evaluates Jetty’s current growth and impact. In this context, the paper explores the potential contribution of new app-based mobility services in environments such as Mexico City - where transit alternatives are ubiquitous, fares are low and unsubsidised, but service is unsafe, insecure, uncomfortable, unreliable and unaccountable. It asks to what extent a technology company can complement government regulations, by establishing and enforcing stricter service standards on private suppliers of service whilst remaining responsive and accountable to passengers. |
| Date: | 2019–01–15 |
| URL: | http://d.repec.org/n?u=RePEc:oec:itfaab:2019/01-en&r=all |
| By: | Konstantin Büchel, Maximilian v. Ehrlich, Diego Puga, Elisabet Viladecans-Marsal |
| Abstract: | Using anonymised cellphone data, we study the role of social networks in residential mobility decisions. Individuals with few local contacts are more likely to change residence. Movers strongly prefer places with more of their contacts close-by. Contacts matter because proximity to them is itself valuable and increases the enjoyment of attractive locations. They also provide hard-to-find local information and reduce frictions, especially in home-search. Local contacts who left recently or are more central are particularly influential. As people age, proximity to family gains importance relative to friends. |
| Keywords: | social networks, residential mobility |
| JEL: | R23 L14 |
| Date: | 2019–03 |
| URL: | http://d.repec.org/n?u=RePEc:rdv:wpaper:credresearchpaper23&r=all |
| By: | Simplice A. Asongu (Yaoundé/Cameroon); Jacinta C. Nwachukwu (Preston,United Kingdom); Stella-Maris I. Orim (Coventry University, UK); Chris Pyke (Preston, United Kingdom) |
| Abstract: | Purpose-The study complements the scant macroeconomic literature on the development outcomes of social media by examining the relationship between Facebook penetration and violent crime levels in a cross-section of 148 countries for the year 2012. Design/methodology/approach-The empirical evidence is based on Ordinary Least Squares (OLS), Tobit and Quantile regressions. In order to respond to policy concerns on the limited evidence on the consequences of social media in developing countries, the dataset is disaggregated into regions and income levels. The decomposition by income levels included: low income, lower middle income, upper middle income and high income. The corresponding regions include: Europe and Central Asia, East Asia and the Pacific, Middle East and North Africa, Sub-Saharan Africa and Latin America. Findings-From OLS and Tobit regressions, there is a negative relationship between Facebook penetration and crime. However, Quantile regressions reveal that the established negative relationship is noticeable exclusively in the 90th crime quantile. Further, when the dataset is decomposed into regions and income levels, the negative relationship is evident in the Middle East and North Africa (MENA) while a positive relationship is confirmed for sub-Saharan Africa. Policy implications are discussed. Originality/value- Studies on the development outcomes of social media are sparse because of a lack of reliable macroeconomic data on social media. This study primarily complemented five existing studies that have leveraged on a newly available dataset on Facebook. |
| Keywords: | Crime; Social media; ICT; Global evidence; Social networks |
| JEL: | K42 D83 O30 D74 D83 |
| Date: | 2019–01 |
| URL: | http://d.repec.org/n?u=RePEc:exs:wpaper:19/003&r=all |
| By: | Tisdell, Clement A.; Svizzero, Serge |
| Abstract: | Patterns are explored of the evolutionary stages in the management of economic exchange as economic activity grows and becomes more diverse and complex. These patterns are related to the economic development and external trade of Phoenician city-states. In addition, attention is given to how well economic theories explain the evolution of Phoenician external trading, with particular attention being given to the Heckscher-Ohlin theory of international trade. Also explored is the role of ‘new’ (evolving) media of exchange in facilitating interactive trade, especially that of Phoenicia. The possible methods that Phoenician rulers (and some other ancient rulers) adopted to extract a portion of the economic surplus from trade are outlined, and the policy issues they faced are discussed. It is concluded that media of exchange such as gold, silver and other treasures which initially fostered the growth of international trade, subsequently resulted in stifling this growth. This is because these items came to be regarded as a measure of real material wealth and led to policies being adopted by states which were intended to increase each state’s stock of these treasures. The seeds of mercantilism were sown. This system had several negative economic consequences and it actually tended to reduce international trade and decrease the economic prosperity of nations. |
| Keywords: | Financial Economics, International Relations/Trade |
| Date: | 2019–07–11 |
| URL: | http://d.repec.org/n?u=RePEc:ags:uqseet:291441&r=all |
| By: | Bi, Huixin (Federal Reserve Bank of Kansas City); Traum, Nora |
| Abstract: | This paper examines how newspaper reporting affects government bond prices during the U.S. state default of the 1840s. Using unsupervised machine learning algorithms, the paper first constructs novel ``fiscal information indices'' for state governments based on U.S. newspapers at the time. The impact of the indices on government bond prices varied over time. Before the crisis, the entry of new western states into the bond market spurred competition: more state-specific fiscal news imposed downward pressure on bond prices for established states in the market. During the crisis, more state-specific fiscal information increased (lowered) bond prices for states with sound (unsound) fiscal policy. |
| Keywords: | Sovereign Default; Information; Fiscal Policy |
| JEL: | E62 H30 N41 |
| Date: | 2019–06–01 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedkrw:rwp19-04&r=all |
| By: | Sam Ganzfried; Max Chiswick |
| Abstract: | Poker is a large complex game of imperfect information, which has been singled out as a major AI challenge problem. Recently there has been a series of breakthroughs culminating in agents that have successfully defeated the strongest human players in two-player no-limit Texas hold 'em. The strongest agents are based on algorithms for approximating Nash equilibrium strategies, which are stored in massive binary files and unintelligible to humans. A recent line of research has explored approaches for extrapolating knowledge from strong game-theoretic strategies that can be understood by humans. This would be useful when humans are the ultimate decision maker and allow humans to make better decisions from massive algorithmically-generated strategies. Using techniques from machine learning we have uncovered a new simple, fundamental rule of poker strategy that leads to a significant improvement in performance over the best prior rule and can also easily be applied by human players. |
| Date: | 2019–06 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1906.09895&r=all |
| By: | Algan, Yann (Sciences Po and CEPR); Dalvit, Nicolò (Sciences Po); Do, Quoc-Anh (Sciences Po and CEPR); Le Chapelain, Alexis (Department of Economics); Zenou, Yves (Monach University) |
| Abstract: | We study how friendship shapes students' political opinions in a natural experiment. We use the indicator whether two students were exogenously assigned to a short-term \integration group", unrelated to scholar activities and dissolved before the school year, as instrumental variable for their friendship, to estimate the effect of friendship on pairwise political opinion outcomes in dyadic regressions. After six months, friendship causes a reduction of differences in opinions by one quarter of the mean difference. It likely works through a homophily-enforced mechanism, by which friendship causes politically-similar students to join political associations together, which reinforces their political similarity. The effect is strong among initially similar pairs, but absent in dissimilar pairs. Friendship affects opinion gaps by reducing divergence, therefore polarization and extremism, without forcing individuals' views to converge. Network characteristics also matter to the friendship effect. |
| Keywords: | Political opinion; Polarization; Friendship effect; Social networks; Homophily; Extremism; Learning; Natural experiment |
| JEL: | C93 D72 Z13 |
| Date: | 2019–07–04 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:iuiwop:1294&r=all |
| By: | Algan, Yann; Dalvit, Nicolo; Do, Quoc-Anh; Le Chapelain, Alexis; Zenou, Yves |
| Abstract: | We study how friendship shapes students' political opinions in a natural experiment. We use the indicator whether two students were exogenously assigned to a short-term "integration group", unrelated to scholar activities and dissolved before the school year, as instrumental variable for their friendship, to estimate the effect of friendship on pairwise political opinion outcomes in dyadic regressions. After six months, friendship causes a reduction of differences in opinions by one quarter of the mean difference. It likely works through a homophily-enforced mechanism, by which friendship causes politically-similar students to join political associations together, which reinforces their political similarity. The effect is strong among initially similar pairs, but absent in dissimilar pairs. Friendship affects opinion gaps by reducing divergence, therefore polarization and extremism, without forcing individuals' views to converge. Network characteristics also matter to the friendship effect. |
| Keywords: | extremism; friendship effect; homophily; learning; Natural Experiment; Polarization; Political opinion; Social Networks |
| JEL: | C93 D72 Z13 |
| Date: | 2019–06 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:13771&r=all |
| By: | Davide Viviano |
| Abstract: | The empirical analysis of experiments and quasi-experiments often seeks to determine the optimal allocation of treatments that maximizes social welfare. In the presence of interference, spillover effects lead to a new formulation of the statistical treatment choice problem. This paper develops a novel method to construct individual-specific optimal treatment allocation rules under network interference. Several features make the proposed methodology particularly appealing for applications: we construct targeting rules that depend on an arbitrary set of individual, neighbors' and network characteristics, and we allow for general constraints on the policy function; we consider heterogeneous direct and spillover effects, arbitrary, possibly non-linear, regression models, and we propose estimators that are robust to model misspecification; the method flexibly accommodates for cases where researchers only observe local information of the network. From a theoretical perspective, we establish the first set of guarantees on the utilitarian regret under interference, and we show that it achieves the min-max optimal rate in scenarios of practical and theoretical interest. We discuss the empirical performance in simulations and we illustrate our method by investigating the role of social networks in micro-finance decisions. |
| Date: | 2019–06 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1906.10258&r=all |
| By: | Lechner, Michael; Okasa, Gabriel |
| Abstract: | In econometrics so-called ordered choice models are popular when interest is in the estimation of the probabilities of particular values of categorical outcome variables with an inherent ordering, conditional on covariates. In this paper we develop a new machine learning estimator based on the random forest algorithm for such models without imposing any distributional assumptions. The proposed Ordered Forest estimator provides a flexible estimation method of the conditional choice probabilities that can naturally deal with nonlinearities in the data, while taking the ordering information explicitly into account. In addition to common machine learning estimators, it enables the estimation of marginal effects as well as conducting inference thereof and thus providing the same output as classical econometric estimators based on ordered logit or probit models. An extensive simulation study examines the finite sample properties of the Ordered Forest and reveals its good predictive performance, particularly in settings with multicollinearity among the predictors and nonlinear functional forms. An empirical application further illustrates the estimation of the marginal effects and their standard errors and demonstrates the advantages of the flexible estimation compared to a parametric benchmark model. |
| Keywords: | Ordered choice models, random forests, probabilities, marginal effects, machine learning |
| JEL: | C14 C25 C40 |
| Date: | 2019–07 |
| URL: | http://d.repec.org/n?u=RePEc:usg:econwp:2019:08&r=all |
| By: | Brendan Hoover; Richard S. Middleton; Sean Yaw |
| Abstract: | Cost Surfaces are a quantitative means of assigning social, environmental, and engineering costs that impact movement across landscapes. Cost surfaces are a crucial aspect of route optimization and least cost path (LCP) calculations and are used in a wide range of disciplines including computer science, landscape ecology, and energy infrastructure modeling. Linear features present a key weakness to traditional routing calculations along costs surfaces because they cannot identify whether moving from a cell to its adjacent neighbors constitutes crossing a linear barrier (increased cost) or following a corridor (reduced cost). Following and avoiding linear features can drastically change predicted routes. In this paper, we introduce an approach to address this "adjacency" issue using a search kernel that identifies these critical barriers and corridors. We have built this approach into a new Java-based open-source software package called CostMAP (cost surface multi-layer aggregation program), which calculates cost surfaces and cost networks using the search kernel. CostMAP not only includes the new adjacency capability, it is also a versatile multi-platform package that allows users to input multiple GIS data layers and to set weights and rules for developing a weighted-cost network. We compare CostMAP performance with traditional cost surface approaches and show significant performance gains, both following corridors and avoiding barriers, using examples in a movement ecology framework and pipeline routing for carbon capture, and storage (CCS). We also demonstrate that the new software can straightforwardly calculate cost surfaces on a national scale. |
| Date: | 2019–06 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1906.08872&r=all |
| By: | Joshua Zoen Git Hiew; Xin Huang; Hao Mou; Duan Li; Qi Wu; Yabo Xu |
| Abstract: | Traditional sentiment construction in finance relies heavily on the dictionary-based approach, with a few exceptions using simple machine learning techniques such as Naive Bayes classifier. While the current literature has not yet invoked the rapid advancement in the natural language processing, we construct in this research a textual-based sentiment index using a novel model BERT recently developed by Google, especially for three actively trading individual stocks in Hong Kong market with hot discussion on Weibo.com. On the one hand, we demonstrate a significant enhancement of applying BERT in sentiment analysis when compared with existing models. On the other hand, by combining with the other two existing methods commonly used on building the sentiment index in the financial literature, i.e., option-implied and market-implied approaches, we propose a more general and comprehensive framework for financial sentiment analysis, and further provide convincing outcomes for the predictability of individual stock return for the above three stocks using LSTM (with a feature of a nonlinear mapping), in contrast to the dominating econometric methods in sentiment influence analysis that are all of a nature of linear regression. |
| Date: | 2019–06 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1906.09024&r=all |