|
on Payment Systems and Financial Technology |
|
Issue of 2019‒03‒04
thirty-one papers chosen by |
| By: | Abadi, Joseph; Brunnermeier, Markus K |
| Abstract: | When is record-keeping better arranged through a blockchain than through a traditional centralized intermediary? The ideal qualities of any record-keeping system are (i) correctness, (ii) decentralization, and (iii) cost efficiency. We point out a \textit{blockchain trilemma}: no ledger can satisfy all three properties simultaneously. A centralized record-keeper extracts rents due to its monopoly on the ledger. Its franchise value dynamically incentivizes correct reporting. Blockchains drive down rents by allowing for free entry of record-keepers and portability of information to competing "forks.'' Blockchains must therefore provide static incentives for correctness through computationally expensive proof-of-work algorithms and permit record-keepers to roll back history in order to undo fraudulent reports. While blockchains can keep track of ownership transfers, enforcement of possession rights is often better complemented by centralized record-keeping. |
| Keywords: | Blockchain Economics; cryptocurrencies; Digital Currencies; distributed ledger technology; Fintech |
| Date: | 2018–12 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:13420&r=all |
| By: | Maria Tokareva (National Research University Higher School of Economics); Konstantin Vishnevskiy (National Research University Higher School of Economics); Anton Zarubin (National Research University Higher School of Economics) |
| Abstract: | Internet of Things (IoT) technologies are of particular interest for telecommunication companies that can significantly affect the interaction of economic agents. As a result of the growth in the number of connected devices, the introduction of cloud services and business applications it became possible to combine equipment, information systems and management systems into a single communication network which in turn gave impetus to the development of the Internet of Things. The basis for the development of the Internet of Things is modern data transmission technologies including IoT Wireless Networks. There are, currently, a number of wireless IoT technologies which have different characteristics. In this regard, it is of interest to identify the most promising technologies that will form the basis of the infrastructure for the development of the IoT ecosystem. This paper develops an assessment model for the application potential of IoT wireless network technologies for the telecommunication sector. LPWAN, 4G and Wi-Fi were identified as the most promising technologies. The majority of the assessment criteria are applicable to other telecommunication technologies. |
| Keywords: | technology assessment, technology management, Internet of Things, wireless networks, telecommunication companies, decision model, digital platforms. |
| JEL: | C43 L15 L96 O14 |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:hig:wpaper:94sti2019&r=all |
| By: | Pele, Daniel Traian; Mazurencu-Marinescu-Pele, Miruna |
| Abstract: | In this paper, the authors investigate the statistical properties of some cryptocurrencies by using three layers of analysis: alpha-stable distributions, Metcalfe's law and the bubble behaviour through the LPPL modelling. The results show, in the medium to long-run, the validity of Metcalfe's law (the value of a network is proportional to the square of the number of connected users of the system) for the evaluation of cryptocurrencies; however, in the short-run, the validity of Metcalfe's law for Bitcoin is questionable. As the results showed a potential for herding behaviour, the authors then used LPPL models to capture the behaviour of cryptocurrencies exchange rates during an endogenous bubble and to predict the most probable time of the regime switching. The main conclusion is that Metcalfe's law may be valid in the long-run, however in the short-run, on various data regimes, its validity is highly debatable. |
| Keywords: | Cryptocurrency,Bitcoin,CRIX,Log-Periodic Power Law,Metcalfe's Law,Stable Distribution,Herding |
| JEL: | C22 C32 C51 C53 C58 E41 E42 E47 E51 G1 G17 |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:ifwedp:201916&r=all |
| By: | Volodymyr Babich; Gilles Hilary (GU - Georgetown University [Washington]) |
| Abstract: | Blockchain is a form of distributed ledger technology (DLT) that has grown in prominence, although its full potential and possible downsides are not yet fully understood, especially with respect to Operations Management (OM). This manuscript contributes to filling in this gap. We identify three research themes in applying Blockchain technology to OM, illustrated through several applications to OM problems. Elsewhere, in a companion article, (Babich and Hilary (2018)), we provide a conceptual framework for the role of Blockchain and other DLT in OM, along with specific examples of research questions, and we demonstrate how research in economics can inform research in OM on Blockchain applications. Finally, we discuss possible future uses for the technology. |
| Keywords: | Digital Assets,Visibility,Information aggregation,Validation,Resiliency,Smart contracts |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:hal-02005156&r=all |
| By: | Feder, Amir; Gandal, Neil; Hamrick, JT; Moore, Tyler; Mukherjee, Arghya; Rouhi, Farhang; Vasek, Marie |
| Abstract: | The surge of interest in cryptocurrencies has been accompanied by a proliferation of fraud. This paper examines a pervasive tactic long known to financial markets: pump and dump schemes. While the fundamentals of the ruse have not changed in the last century, the recent explosion of nearly 2,000 cryptocurrencies in a largely unregulated environment has greatly expanded the scope for abuse. The paper first quantifies the scope of cryptocurrency pump and dump on Discord and Telegram, two widely popular group messaging platforms with 130 million users and 200 million users respectively. Both platforms can handle large groups with thousands of users, and they are the most popular outlets for pump and dump schemes involving cryptocurrencies. We identified 3,767 different pump signals advertised on Telegram and another 1,051 different pump signals advertised on Discord during a six-month period in 2018. The schemes promoted more than 300 cryptocurrencies. These comprehensive data provide the first measure of the scope of pump and dump schemes across cryptocurrencies and suggest that this phenomenon is widespread and often quite profitable. This should raise concerns among regulators. We then examine which factors that affect the "success" of the pump, as measured by the percentage increase in price near the pump signal. We find that the coin's rank (market capitalization/volume) is the most important factor in determining the profitability of the pump: pumping obscure coins (with low volume) is much more profitable than pumping the dominant coins in the ecosystem. |
| Date: | 2018–12 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:13404&r=all |
| By: | Prüfer, Jens (Tilburg University, Center For Economic Research); Prüfer, Patricia (Tilburg University, Center For Economic Research) |
| Abstract: | The recent rise of big data and artificial intelligence (AI) is changing markets, politics, organizations, and societies. It also affects the domain of research. Supported by new statistical methods that rely on computational power and computer science --- data science methods --- we are now able to analyze data sets that can be huge, multidimensional, unstructured, and are diversely sourced. In this paper, we describe the most prominent data science methods suitable for entrepreneurship research and provide links to literature and Internet resources for self-starters. We survey how data science methods have been applied in the entrepreneurship research literature. As a showcase of data science techniques, based on a dataset of 95% of all job vacancies in the Netherlands over a 6-year period with 7.7 million data points, we provide an original analysis of the demand dynamics for entrepreneurial skills in the Netherlands. We show which entrepreneurial skills are particularly important for which type of profession. Moreover, we find that demand for both entrepreneurial and digital skills has increased for managerial positions, but not for others. We also find that entrepreneurial skills were significantly more demanded than digital skills over the entire period 2012-2017 and that the absolute importance of entrepreneurial skills has even increased more than digital skills for managers, despite the impact of datafication on the labor market. We conclude that further studies of entrepreneurial skills in the general population --- outside the domain of entrepreneurs --- is a rewarding subject for future research. |
| Keywords: | data science; machine learning; entrepreneurship; entrepreneurial skills; big data; artificial intelligence |
| JEL: | L26 C50 C87 O32 |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:tiu:tiucen:83a4ca9e-c0cd-4786-ac8c-923b9317f0aa&r=all |
| By: | Jacques Bughin; Tobias Kretschmer; Nicolas van Zeebroeck |
| Abstract: | With the increasing availability of digital technologies, many firms are planning to develop digitally-enabled business models. Digital technologies can give an impulse to realign strategies through two channels: Initial use of digital technologies may help firms spot their potential and encourage firms to develop digitally-supported business models, or emerging digital technologies may present a threat to firms, who then initiate a process of strategic renewal to relieve the pressure. We study how the adoption of new digital technologies is associated with changes to the strategy of the firm, and how both are shaped by a firm’s perception of the competitive stress created by new technological developments. Using two detailed survey-based datasets on firms’ expectations, adoption and strategy renewal for a wide range of AI and digital technologies, we find a strong positive association between the degree of strategy change and the adoption of advanced digital technologies. This relationship does not seem mediated by the level of competitive stress from digital technology, which is itself strongly associated with strategy change. Our results suggest a tight coupling between (technological) structure and strategy. |
| Keywords: | Digital transformation, Strategic Organization Design, Technology adoption, Strategic renewal, Digital strategy, Big data, Artificial Intelligence |
| Date: | 2019–01 |
| URL: | http://d.repec.org/n?u=RePEc:ict:wpaper:2013/284015&r=all |
| By: | George Selgin |
| Abstract: | Depending on how one interprets the question that forms the topic of my talk, one can argue that the answer is obvious, or one can argue just the opposite. In one sense of course, it’s obvious that non-state money is possible. That’s the sense in which we ask only whether some kinds of non-state money are possible. And of course, the answer is yes. The vast majority of payments today, in Poland as elsewhere, are made with privately produced forms of money – that is, with bank deposits of various kinds – transferable by cheque or using debit cards. And there is nothing surprising about that. But of course, my assigned question can also be understood in a different and more interesting way. The interesting question is not whether some kinds of non-state- supplied money are possible. It is a different question, or rather two different questions. One of these is whether non-state circulating monies, or currencies, are possible. Can we rely on the private sector to supply hand-to-hand circulating means of payment? The other even more fundamental question is whether we can have a complete monetary system in which all forms of money supplied privately, and the state plays no substantial regulatory role. |
| Keywords: | commodity money, coinage, banknotes, free banking, fiat money, non-state money, cryptocurriences, monetary history, monetary systems |
| JEL: | E52 B16 G23 |
| Date: | 2019–02–12 |
| URL: | http://d.repec.org/n?u=RePEc:sec:mbanks:0158&r=all |
| By: | Ferrarini, Benno (Asian Development Bank); Maupin, Julie (Max-Planck Institute for Comparative Public Law and International Law); Hinojales , Marthe (Asian Development Bank) |
| Abstract: | This paper takes a first pass at assessing areas of implementation for distributed ledger (or blockchain) technology in the context of development finance. It identifies five use cases, including digital identity, trade finance, project aid monitoring, smart energy, and supply chain management. A discussion of the main benefits, risks and implementation challenges suggests that experimentation with distributed ledger technology can produce immediate significant benefits in some areas, while others require further research and investment, as well as additional technical, infrastructural, or regulatory development. Development lenders can play a role in helping unleash these technologies’ positive developmental impact throughout the Asian region. |
| Keywords: | blockchain; developing Asia; distributed ledger technology; financial technology |
| JEL: | G21 M13 O33 |
| Date: | 2017–12–20 |
| URL: | http://d.repec.org/n?u=RePEc:ris:adbewp:0533&r=all |
| By: | Lin William Cong; Zhiguo He; Jiasun Li |
| Abstract: | The rise of centralized mining pools for risk sharing does not necessarily undermine the decentralization required for public blockchains. However, mining pools as a financial innovation significantly escalates the arms race among competing miners and thus increases the energy consumption of proof-of-work-based blockchains. Each individual miner's cross-pool diversification and endogenous fees charged by pools generally sustain decentralization --- larger pools better internalize their externality on global hash rates, charge higher fees, attract disproportionately fewer miners, and thus grow slower. Empirical evidence from Bitcoin mining supports our model predictions, and the economic insights apply to many other blockchain protocols, as well as mainstream industries with similar characteristics. |
| JEL: | D43 G2 G22 L13 L44 |
| Date: | 2019–02 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:25592&r=all |
| By: | Klus, Milan F.; Müller, Julia |
| Abstract: | Is leadership changing in an increasingly digitalised work environment? This question arises in corporate practice, societal debates, and in business management research. The evolution of digital technologies changes working environments considerably and creates new challenges for executives. So far, however, only little research has been conducted on how these challenges and technology-driven changes are associated with altered requirements for the skill set needed by executives. In this paper we bridge that gap by applying a three-stage research design. First, we develop a novel conceptual framework in which we categorise leadership skills and associate them with tasks, management level, and leadership experience. Building on this, we conduct semi-structured interviews with executives and systematically investigate job advertisements at the management level. Our interview results show that communication skills, subject-specific knowledge, self-organisation skills, and self-reflection skills are considered particularly relevant in times of rapid technology-driven change. Furthermore, many interview participants identify empathy and an open-mindedness towards the new as crucial personal traits. Our job advertisement analysis further reveals that executives need to be able to speak English, have IT skills, and be flexible, motivated, and stress tolerant. |
| JEL: | M12 M15 M51 M54 O32 O33 |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:umiodp:112018&r=all |
| By: | Asongu, Simplice; Odhiambo, Nicholas |
| Abstract: | The study examines the relationship between tourism and social media from a cross section of 138 countries with data for the year 2012.The empirical evidence is based on Ordinary Least Squares, Negative Binomial and Quantile regressions. Two main findings are established. First, there is a positive relationship between Facebook penetration and the number of tourist arrivals. Second, Facebook penetration is more relevant in promoting tourist arrivals in countries where initial levels in tourist arrivals are the highest and low. The established positive relationship can be elucidated from four principal angles: the transformation of travel research, the rise in social sharing, improvements in customer service and the reshaping of travel agencies. This study explores a new dataset on social media. There are very few empirical studies on the relevance of social media in development outcomes. |
| Keywords: | Social Media; Tourism |
| JEL: | D83 O30 Z00 |
| Date: | 2018–03 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:92344&r=all |
| By: | Sudipto Karmakar; Abhinav Narayanan |
| Abstract: | The recent demonetization exercise in India is a unique monetary experiment that made 86 percent of the total currency in circulation invalid. In a country where currency in circulation constitutes 12 percent of GDP, the policy turned out to be a purely exogenous macroeconomic shock that affected all agents of the economy. This paper documents the impact of this macroeconomic shock on one such systematically important agent of the economy: the household. By construction, the policy helped households with bank accounts in disposing of the demonetized cash. We use a new household-level data set to tease out the effects of this policy on households with no bank accounts. Our results show that the impact of demonetization on household income and expenditure has been transient with the major impact being seen in December-2016. There is significant heterogeneity in the impact across households in different asset classes. We also show evidence of recovery of household finances whereby households were able to smooth out consumption during the post-demonetization period. However, this recovery phase is associated with an increase in household borrowing from different sources, primarily for the purpose of consumption. In particular, informal borrowing (money lenders, shops) increased substantially during this period. Thus, the policy although transient in nature, contributed to the unintended consequence of increased leverge for households. |
| Keywords: | Demonetization, Household finance, Leverage |
| JEL: | E21 E51 G28 |
| Date: | 2019–02 |
| URL: | http://d.repec.org/n?u=RePEc:ise:remwps:wp0732019&r=all |
| By: | Volodymyr Babich; Gilles Hilary (GU - Georgetown University [Washington]) |
| Abstract: | Blockchain is a form of distributed ledger technology. While it has grown in prominence, its full potential and possible downsides are not fully understood yet, especially with respect to Operations Management (OM). This article fills this gap. After briefly reviewing the technical foundations, we explore multiple business and policy aspects. We identify five key strengths, the corresponding five main weaknesses, and three research themes of applying Blockchain technology to OM. The key strengths are (1) visibility, (2) aggregation, (3) validation, (4) automation, and (5) resiliency. The corresponding weaknesses are (1) lack of privacy, (2) lack of standardization, (3) garbage in, garbage out, (4) black box effect, and (5) inefficiency. The three research themes are (1) information, (2) automation, and (3) tokenization. We illustrate these research themes with multiple promising research problems, ranging from classical inventory management, to new areas of ethical OM, and to questions of Industrial Organization. |
| Keywords: | Smart contracts,Digital Assets,Resiliency,Validation,Visibility,Information aggregation |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:hal-02005158&r=all |
| By: | Levashenko, Antonina (Левашенко, Антонина) (The Russian Presidential Academy of National Economy and Public Administration); Ermokhin, Ivan (Ермохин, Иван) (The Russian Presidential Academy of National Economy and Public Administration); Zubarev, Andrey (Зубарев, Андрей) (The Russian Presidential Academy of National Economy and Public Administration); Sinelnikova-Muryleva, Elena (Синельникова-Мурылева Елена) (The Russian Presidential Academy of National Economy and Public Administration); Trunin, Pavel (Трунин, Павел) (The Russian Presidential Academy of National Economy and Public Administration, Gaidar Institute for Economic Policy) |
| Abstract: | Cryptoeconomics is a large new market. Today, the global turnover of cryptocurrency is at around $ 200 billion. In 2017–2018 in the framework of the ICO campaigns, people from Russia attracted a total of $ 2.3 billion, having conducted 311 ICO campaigns. There are new participants in this market: cryptobirds and cryptoexchangers, crypto funds, decentralized organizations conducting ICO-campaigns from different sectors of the economy. The Russian Federation should create favorable conditions for the development of a new sector of the economy. The report examines the main approaches to the definition and essence of cryptocurrencies, analyzes the functions performed by them, as well as the challenges that the emergence of cryptocurrencies forms for the traditional financial system and monetary policy. In addition, a comparative analysis of the regulation of this new sector of the economy in the OECD countries and the Russian Federation is presented, and recommendations are given to bring Russian legislation in line with international best practice. |
| Date: | 2019–01 |
| URL: | http://d.repec.org/n?u=RePEc:rnp:ppaper:021913&r=all |
| By: | Abroskin, Alexander (Аброскин, Александр) (The Russian Presidential Academy of National Economy and Public Administration); Zaitsev, Yury (Зайцев, Юрий) (The Russian Presidential Academy of National Economy and Public Administration); Idrisov, Georgiy (Идрисов, Георгий) (The Russian Presidential Academy of National Economy and Public Administration); Knobel, Alexander (Кнобель, Александр) (The Russian Presidential Academy of National Economy and Public Administration, Russian Foreign Trade Academy); Ponomareva, Ekaterina (Пономарева, Екатерина) (The Russian Presidential Academy of National Economy and Public Administration) |
| Abstract: | The key element of technological progress at the end of the 20th century was the computerization of industrial production and other sectors of the economy, which was replaced by digitalization at the beginning of the 21st century. The basis of digitalization is based on more complex technologies, not always related to the telecommunications sector, capable of significantly changing the processes of interaction between economic agents and the methods of organizing production. According to the authors, due to the lack of a single internationally recognized definition and methodology for assessing the digital economy, inter-country and intertemporal comparisons of the contribution of the digital sector to GDP are difficult. The paper presents estimates according to which the size of the digital economy in Russia ranges from 1 to 3.7% of GDP, and analyzes the complexity of correctly estimating the growth rate of well-being as a result of digitalization. The report also analyzes the impact of digitalization on various macroparameters of the economy, taking into account the interests of all economic agents. |
| Date: | 2019–01 |
| URL: | http://d.repec.org/n?u=RePEc:rnp:ppaper:021922&r=all |
| By: | Tetsuya Takaishi; Takanori Adachi |
| Abstract: | This letter investigates the dynamic relationship between market efficiency, liquidity, and multifractality of Bitcoin. We find that before 2013 liquidity is low and the Hurst exponent is less than 0.5, indicating that the Bitcoin time series is anti-persistent. After 2013, as liquidity increased, the Hurst exponent rose to approximately 0.5, improving market efficiency. For several periods, however, the Hurst exponent was found to be significantly less than 0.5, making the time series anti-persistent during those periods. We also investigate the multifractal degree of the Bitcoin time series using the generalized Hurst exponent and find that the multifractal degree is related to market efficiency in a non-linear manner. |
| Date: | 2019–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1902.09253&r=all |
| By: | Long, Vicky (The Ratio Institute); Domeij, Bengt (The Ratio Institute) |
| Abstract: | What role can trademark play in appropriability regime, especially in a digitalized era where many innovations are easy to copy and difficult to protect, and where rapid diffusion is the norm? This study, using the Swedish video games industry as a case, aims to provide some insights and tentative answers to those questions. Combining firm-level interviews, statistical data concerning EUIPO trademarks filed by the Swedish video games industry, we present the quantitative trends of trademarking across this industry sector (i.e. timeline; distribution across technological platforms and firm sizes; correlation with turnover), as well as qualitative explanations for that. This study contributes to a meso-level explanation of the role of trademarks (registrations) in appropriability on the one hand, and to the understanding of the complexity of the general appropriability conditions (and logic) in the Digital Era, on the other. |
| Keywords: | Intellectual Property Rights (IPRs); Appropriability; Video Games; Digitalization; Innovation; Vicky Long; Bengt Domeij |
| JEL: | O32 O34 |
| Date: | 2019–02–18 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:ratioi:0318&r=all |
| By: | Auerbach, Paul (Kingston University London) |
| Abstract: | Widespread uneasiness has emerged concerning a perceived slowdown in productivity growth. The question posed here is whether our destiny is indeed tied to inexorable movements in productivity and innovation, whatever these things may be, or can we build a future contingent upon collective choices and guided by human needs and desires? |
| Keywords: | Artificial Intelligence; innovation; productivity; Schumpeter; technological change; total factor productivity. |
| JEL: | O10 O30 O33 O40 O47 |
| Date: | 2019–02–25 |
| URL: | http://d.repec.org/n?u=RePEc:ris:kngedp:2019_003&r=all |
| By: | Farboodi, Maryam; Mihet, Roxana; Philippon, Thomas; Veldkamp, Laura |
| Abstract: | We study a model where firms accumulate data as a valuable intangible asset. Data accumulation affects firms' dynamics. It increases the skewness of the firm size distribution as large firms generate more data and invest more in active experimentation. On the other hand, small data-savvy firms can overtake more traditional incumbents, provided they can finance their initial money-losing growth. Our model can be used to estimate the market and social value of data. |
| Keywords: | Big Data; firm size |
| Date: | 2019–01 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:13489&r=all |
| By: | Dobrolyubova, Elena (Добролюбова, Елена) (The Russian Presidential Academy of National Economy and Public Administration); Yuzhakov, Vladimir (Южаков, Владимир) (The Russian Presidential Academy of National Economy and Public Administration); Efremov, Aleksey (Ефремов, Алексей) (The Russian Presidential Academy of National Economy and Public Administration); Klochkova, Elena (Клочкова, Елена) (The Russian Presidential Academy of National Economy and Public Administration); Talapina, Elvira (Талапина, Эльвира) (The Russian Presidential Academy of National Economy and Public Administration); Startsev, Yaroslav (Старцев, Ярослав) (The Russian Presidential Academy of National Economy and Public Administration) |
| Abstract: | The report discusses theoretical and practical approaches to the digital transformation of public administration in the interests of ensuring and increasing its effectiveness. The authors assess the impact of digitalization on the quality of public administration and show a strong relationship between the indicators of e-government development, on the one hand, and the effectiveness of public administration, on the other. Based on the analysis of foreign experience in the use of digital technologies in planning, monitoring and evaluating results in public administration, an assessment was made of the potential for using such technologies in Russian practice. The report shows that digital technologies can overcome the problems in the development of public authorities by results that have arisen and identified earlier, and digital transformation can be a driver for the introduction of a new model of public administration - public management by results. Whether this happens or not depends on the extent to which in practice it will be possible to lift the restrictions on the introduction of digital technologies in general and in public administration in particular. |
| Date: | 2019–01 |
| URL: | http://d.repec.org/n?u=RePEc:rnp:ppaper:021909&r=all |
| By: | Duccio Gamannossi degl’Innocenti (University of Exeter, UK); Matthew D. Rablen (University of Sheffield, UK) |
| Abstract: | We relate tax evasion behavior to a substantial literature on social comparison in judgements. Taxpayers engage in tax evasion as a means to boost their expected consumption relative to others in their social network. The unique Nash equilibrium of the model relates optimal evasion to a (Bonacich) measure of network centrality: more central taxpayers evade more. Given that tax authorities are now investing heavily in big-data tools that aim to construct social networks, we investigate the value of acquiring network information. We do this using networks that allow for celebrity taxpayers, whose consumption is widely seen, and who are systematically of higher wealth. We show that there are pronounced returns to the initial acquisition of network information, albeit targeting audits with highly incomplete knowledge of social networks may be counterproductive. |
| Keywords: | Tax Evasion; Social Networks; Network centrality; Optimal Auditing; Social Comparison; Relative Consumption |
| JEL: | H26 D85 K42 |
| Date: | 2019–02 |
| URL: | http://d.repec.org/n?u=RePEc:shf:wpaper:2019005&r=all |
| By: | Jinho Lee; Raehyun Kim; Yookyung Koh; Jaewoo Kang |
| Abstract: | We applied Deep Q-Network with a Convolutional Neural Network function approximator, which takes stock chart images as input, for making global stock market predictions. Our model not only yields profit in the stock market of the country where it was trained but generally yields profit in global stock markets. We trained our model only in the US market and tested it in 31 different countries over 12 years. The portfolios constructed based on our model's output generally yield about 0.1 to 1.0 percent return per transaction prior to transaction costs in 31 countries. The results show that there are some patterns on stock chart image, that tend to predict the same future stock price movements across global stock markets. Moreover, the results show that future stock prices can be predicted even if the training and testing procedures are done in different countries. Training procedure could be done in relatively large and liquid markets (e.g., USA) and tested in small markets. This result demonstrates that artificial intelligence based stock price forecasting models can be used in relatively small markets (emerging countries) even though they do not have a sufficient amount of data for training. |
| Date: | 2019–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1902.10948&r=all |
| By: | Chun, Natalie (Asian Development Bank); Tang, Heiwai (Johns Hopkins School of Advanced International Studies) |
| Abstract: | This paper studies the effects of firms’ investments in information and communication technologies (ICT) on their demand for female and skilled workers. Using the gradual liberalization of the broadband Internet sector across provinces from 2006 to 2009 as a source of exogenous variation to identify the causal impacts of ICT, we find evidence from the country’s comprehensive enterprise survey data that firms’ adoption of broadband Internet and other related ICT increased their relative demand for female and college-educated workers. The effect of ICT on firms’ female employment is particularly strong among the college-educated workers, and is stronger in industries that are more dependent on highly manual and physical tasks. These results suggest that ICT can lower gender inequality in the labor market by shifting the labor demand from highly manual, routine tasks in which men have a comparative advantage toward more nonroutine, interactive tasks in which women hold a comparative advantage. However, the effect of ICT is weaker in industries relying more on complex and interactive tasks, suggesting that gender differences in education may have limited female labor supply for the most innovative industries that require highly technical skills to complement ICT. |
| Keywords: | gender inequality; ICT; information technology; infrastructure; wage inequality |
| JEL: | I24 J16 J21 J22 |
| Date: | 2018–05–22 |
| URL: | http://d.repec.org/n?u=RePEc:ris:adbewp:0545&r=all |
| By: | Shen, Ze; Bessler, David; Leatham, David |
| Keywords: | Agribusiness |
| Date: | 2019–02 |
| URL: | http://d.repec.org/n?u=RePEc:ags:saea19:284301&r=all |
| By: | Ehnts, Dirk H. |
| Abstract: | In 1905, Georg Friedrich Knapp published The State Theory of Money in his native German, claiming that money is a "creature of law" and not connected to metals via some intrinsic value. When the English translation appeared in 1924, apparently at the wishes of John Maynard Keynes, the German version had run through four editions, upon which the last the translation builds. There also had been considerable debate about "Chartalism" - the idea that money derived its acceptance by legal means - in the German academic literature. Among others, Knut Wicksell and Georg Simmel commented on it. Since so far there has not been any English-language publication on this issue, it is deemed worthwhile to provide such. After presenting the main arguments that Knapp makes in his book, the academic reviews that followed are presented and evaluated. |
| Keywords: | chartalism,Modern Monetary Theory,monetary theory,public finance,deficit spending,taxation,value of money,metallism |
| JEL: | E40 E42 E51 F31 H20 |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:ipewps:1152019&r=all |
| By: | Sangyeon Kim; Myungjoo Kang |
| Abstract: | Financial time series prediction, especially with machine learning techniques, is an extensive field of study. In recent times, deep learning methods (especially time series analysis) have performed outstandingly for various industrial problems, with better prediction than machine learning methods. Moreover, many researchers have used deep learning methods to predict financial time series with various models in recent years. In this paper, we will compare various deep learning models, such as multilayer perceptron (MLP), one-dimensional convolutional neural networks (1D CNN), stacked long short-term memory (stacked LSTM), attention networks, and weighted attention networks for financial time series prediction. In particular, attention LSTM is not only used for prediction, but also for visualizing intermediate outputs to analyze the reason of prediction; therefore, we will show an example for understanding the model prediction intuitively with attention vectors. In addition, we focus on time and factors, which lead to an easy understanding of why certain trends are predicted when accessing a given time series table. We also modify the loss functions of the attention models with weighted categorical cross entropy; our proposed model produces a 0.76 hit ratio, which is superior to those of other methods for predicting the trends of the KOSPI 200. |
| Date: | 2019–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1902.10877&r=all |
| By: | Calvano, Emilio; Calzolari, Giacomo; Denicolò, Vincenzo; Pastorello, Sergio |
| Abstract: | Increasingly, pricing algorithms are supplanting human decision making in real marketplaces. To inform the competition policy debate on the possible consequences of this development, we experiment with pricing algorithms powered by Artificial Intelligence (AI) in controlled environments (computer simulations), studying the interaction among a number of Q-learning algorithms in a workhorse oligopoly model of price competition with Logit demand and constant marginal costs. In this setting the algorithms consistently learn to charge supra-competitive prices, without communicating with one another. The high prices are sustained by classical collusive strategies with a finite phase of punishment followed by a gradual return to cooperation. This finding is robust to asymmetries in cost or demand and to changes in the number of players. |
| Keywords: | artificial intelligence; Collusion; Pricing-Algorithms; Q-Learning; Reinforcement Learning |
| JEL: | D43 D83 L13 L41 |
| Date: | 2018–12 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:13405&r=all |
| By: | Asongu, Simplice; Folarin, Oludele; Biekpe, Nicholas |
| Abstract: | This study examines the stability of money demand in the proposed West African Monetary Union (WAMU). The study uses annual data for the period 1981 to 2015 from thirteen of the fifteen countries making-up the Economic Community of West African States (ECOWAS). A standard money demand function is designed and estimated using a bounds testing approach to co-integration and error-correction modeling. The findings show divergence across ECOWAS member states in the stability of money demand. This divergence is informed by differences in cointegration, stability, short run and long term determinants, and error correction in event of a shock. |
| Keywords: | Stable; demand for money; bounds test |
| JEL: | C22 E41 |
| Date: | 2018–01 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:92343&r=all |
| By: | Daske, Thomas |
| Abstract: | This study explores mechanism design for networks of interpersonal relationships. Agents' social (i.e., altruistic or spiteful) preferences and private payoffs are all subject to asymmetric information; utility is (quasi-)linear, types are independent. I show that any network of at least three agents can resolve any allocation problem with a mechanism that is Bayesian incentive-compatible, ex-interim individually rational, and ex-post Pareto-efficient (also ex-post budget-balanced). By contrast, a generalized Myerson-Satterthwaite theorem is established for two agents. The central tool to exploit the asymmetry of information about agents' social preferences is "gamification": Resolve the agents' allocation problem with an efficient social-preference robust mechanism; ensure agents' participation with the help of a mediator, some network member, who complements that mechanism with an unrelated hawk-dove like game between the others, a game that effectively rewards (sanctions) strong (poor) cooperation at the expense (to the benefit) of the mediator. Ex interim, agents (and the mediator) desire this game to be played, for it provides them with a platform to live out their propensities to cooperate or compete. - A figurative example is a fund-raiser, hosted by the "mediator", complemented with awarding the best-dressed guest. |
| Keywords: | networks,social preferences,mechanisms,gamification,Coase theorem |
| JEL: | C70 D62 D64 D82 D85 |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:esprep:193148&r=all |
| By: | Knaus, Michael C.; Lechner, Michael; Strittmatter, Anthony |
| Abstract: | We investigate the finite sample performance of causal machine learning estimators for heterogeneous causal effects at different aggregation levels. We employ an Empirical Monte Carlo Study that relies on arguably realistic data Generation processes (DGPs) based on actual data. We consider 24 different DGPs, Eleven different causal machine learning estimators, and three aggregation levels of the estimated effects. In the main DGPs, we allow for selection into treatment based on a rich set of observable covariates. We provide evidence that the estimators can be categorized into three groups. The first group performs consistently well across all DGPs and aggregation levels. These estimators have multiple steps to account for the selection into the treatment and the outcome process. The second group shows competitive performance only for particular DGPs. The third group is clearly outperformed by the other estimators. |
| Keywords: | Causal Forest; Causal machine learning; conditional average treatment effects; Lasso; Random Forest; selection-on-observables |
| JEL: | C21 |
| Date: | 2018–12 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:13402&r=all |