nep-pay New Economics Papers
on Payment Systems and Financial Technology
Issue of 2019‒09‒09
forty-nine papers chosen by

  1. Explaining the Interplay Between Merchant Acceptance and Consumer Adoption in Two-Sided Markets for Payment Methods By Kim Huynh; Gradon Nicholls; Oleksandr Shcherbakov
  2. Central bank digital currencies: The case of universal central bank reserves By Paolo Fegatelli
  3. In search for stability in crypto-assets: are stablecoins the solution? By Bullmann, Dirk; Klemm, Jonas; Pinna, Andrea
  4. ChainNet: Learning on Blockchain Graphs with Topological Features By Nazmiye Ceren Abay; Cuneyt Gurcan Akcora; Yulia R. Gel; Umar D. Islambekov; Murat Kantarcioglu; Yahui Tian; Bhavani Thuraisingham
  5. Crowdfunding Dynamics By Paul Belleflamme; Thomas Lambert; Armin Schwienbacher
  6. Global Value Chains and the Innovation of the Chinese Mobile Phone Industry By Yuqing Xing
  7. Robonomics: The Study of Robot-Human Peer-to-Peer Financial Transactions and Agreements By Irvin Steve Cardenas; Jong-Hoon Kim
  9. Towards a Utility Theory of Privacy and Information Sharing and the Introduction of Hyper-Hyperbolic Discounting in the Digital Big Data Age By Julia M. Puaschunder
  10. The operators and their future: The state of play and emerging business models By OECD
  12. Are Bitcoins price predictable? Evidence from machine learning techniques using technical indicators By Samuel Asante Gyamerah
  13. Blockchain technologies as a digital enabler for sustainable infrastructure By OECD
  14. Surveying the Technical and Visual Facilities of Digital Technology in Mural Painting By Yasaman Farhangpour
  15. Exploring the Use of Data-driven Journalism in Thai Mass Media By Monwipa Wongrujira
  16. There's an app feature for that: Establishing user preferred mobile app features through asynchronous online interviews By Andrea Potgieter; Chris Rensleigh
  17. Consumer Uptake of Internet Banking, Endogenous Market Structure and Regional Integration in Europe By Bruce Lyons; Minyan Zhu
  18. Mobile Money adoption and information gaps: Evaluating the impact of video advertisement By Barriga-Cabanillas, Oscar
  19. The Impact of Mobile Money on Smallholder Producer Resilience: Evidence from Kenya By Yao, Becatien H.; Shanoyan, Aleksan
  20. Crime and Networks: 10 Policy Lessons By Lindquist, Matthew J.; Zenou, Yves
  21. Who Gained from India’s Demonetization? Insights from Satellites and Surveys By Chanda, Areendam; Cook, Justin
  22. Data-sharing in IoT Ecosystems from a Competition Law Perspective: The Example of Connected Cars By Wolfgang Kerber
  23. Subsidies and the African Green Revolution: Direct Effects and Social Network Spillovers of Randomized Input Subsidies in Mozambique By Michael Carter; Rachid Laajaj; Dean Yang
  24. Homicide and Social Media: Global Empirical Evidence By Simplice A. Asongu; Joseph I. Uduji; Elda N. Okolo-Obasi
  25. Good practice guide on online consumer ratings and reviews By OECD
  26. Cryptocurrencies, Currency Competition, and the Impossible Trinity By Pierpaolo Benigno; Linda M. Schilling; Harald Uhlig
  27. Understanding online consumer ratings and reviews By OECD
  28. Platforms as service ecosystems: lessons from social media By Alaimo, Cristina; Kallinikos, Jannis; Vallderama-Venegas, E
  29. Skills-Displacing Technological Change and Its Impact on Jobs: Challenging Technological Alarmism? By McGuinness, Seamus; Pouliakas, Konstantinos; Redmond, Paul
  30. Reinforcement Learning: Prediction, Control and Value Function Approximation By Haoqian Li; Thomas Lau
  31. Las viviendas turísticas ofertadas por plataformas on-line: Estado de la cuestión By Armando Ortuño; Juan Luis Jiménez
  32. Racial Disparities in Voting Wait Times: Evidence from Smartphone Data By M. Keith Chen; Kareem Haggag; Devin G. Pope; Ryne Rohla
  33. Predicting Consumer Default: A Deep Learning Approach By Stefania Albanesi; Domonkos F. Vamossy
  34. What Does Peer-To-Peer Lending Evidence Say about the Risk-Taking Channel of Monetary Policy? By Yiping Huang; Xiang Li; Chu Wang
  35. Barter and the Origin of Money and Some Insights from the Ancient Palatial Economies of Mesopotamia and Egypt By Serge Svizzero; Clement Tisdell
  36. Predicting Returns With Text Data By Zheng Tracy Ke; Bryan T. Kelly; Dacheng Xiu
  37. WhatsApp utilisation at an initial teacher preparation programme at a university of technology in South Africa By Nkosinomusa Mabaso; Lawrence Meda
  38. The probability of automation of occupations in Italy By Emilia Filippi; Sandro Trento
  39. Adoption of herd management smartphone apps in German dairy farming By Michels, Marius; Bonke, Vanessa; Mußhoff, Oliver
  40. Buy-Online-and-Pick-up-in-Store in Omnichannel Retailing By Yasuyuki Kusuda
  41. How social media usage affects consumer trust? Evidence from Chinese community supported agriculture By Tan, Si; Chen, Weiping
  42. Teacher perception using the mobile phone in the teacher working group; age matters By Mohamad adning; Diana Sari Dj; Kulsum Nur Hayati
  43. Now-casting Spain By Manu García; Juan F. Rubio-Ramírez
  44. Spot and Futures Prices of Bitcoin: Causality, Cointegration and Price Discovery from a Time-Varying Perspective By Yang Hu; Yang (Greg) Hou; Les Oxley
  45. Optimal Search Segmentation Mechanisms for Online Platform Markets By Zhenzhe Zheng; R. Srikant
  46. Economic Black Holes and Labor Singularities in the Presence of Self-replicating Artificial Intelligence By YANO Makoto; FURUKAWA Yuichi
  47. The finer points of model comparison in machine learning: forecasting based on russian banks’ data By Denis Shibitov; Mariam Mamedli
  48. Does the Estimation of the Propensity Score by Machine Learning Improve Matching Estimation? The Case of Germany's Programmes for Long Term Unemployed By Goller, Daniel; Lechner, Michael; Moczall, Andreas; Wolff, Joachim
  49. An introduction to flexible methods for policy evaluation By Huber, Martin

  1. By: Kim Huynh; Gradon Nicholls; Oleksandr Shcherbakov
    Abstract: Recent consumer and merchant surveys show a decrease in the use of cash at point-of-sale (POS). Increasingly, consumers and merchants have access to a growing array of payment innovations as substitutes for cash. The market for payments is two-sided, meaning that a method of payment can be used only if both consumers and merchants adopt/accept it. This paper develops a model to assess how innovations affect consumers’ adoption and merchants’ acceptance of various payment instruments, and their usage patterns at the POS. We model this interdependence in two stages. First, consumers and merchants decide on which methods of payment to adopt and accept, respectively. Second, consumers and merchants meet at the POS, and the consumer chooses their preferred method of payment given what the merchant accepts. Estimates from our model suggest that both sides of the market can benefit from accepting all means of payment. Further, our model predicts that merchants are much more sensitive to an increase in their payment costs than consumers. We use our model to predict what would happen under three scenarios. First, increasing merchants’ cost of using credit cards would significantly reduce merchant acceptance of this payment instrument in favour of debit. Second, the cost of using cash would have to increase substantially on both sides of the market for cash usage to fall below 1 percent of transaction volume. Finally, even if all consumers/merchants adopted/accepted all methods of payment, cash would fall but would remain at 20 percent of transaction volume. These findings suggest a completely cashless society is unlikely in the foreseeable future.
    Keywords: Bank notes; Digital Currencies and Fintech; Econometric and statistical methods; Financial services
    JEL: C51 L13 L15 L81 L96
    Date: 2019–08
  2. By: Paolo Fegatelli
    Abstract: We analyse several motivations for the introduction of a widely accessible central bank digital currency (CBDC). If a central bank decided to offer a CBDC, its design would have to consider different areas of central bank activity, taking into account multiple policy principles, objectives and constraints. In addition, the introduction of a CBDC on a large scale may have a non-trivial impact on the architecture of the financial system. From this perspective, some common arguments in favour of CBDC may seem simplistic and the field of feasible options may be narrower than often believed. We reconsider Tobin’s idea to establish a system of universal access to central bank reserves, and clarify its feasibility and advantages as an account-based CBDC.
    Keywords: Central bank digital currency, universal central bank reserves, deposited currency accounts, cash, central bank, central bank policies, monetary policy, financial stability, payment systems, deposit insurance, bank deposits, inside money, collateral, virtual currencies
    JEL: E41 E42 E43 E51 E52 E58
    Date: 2019–07
  3. By: Bullmann, Dirk; Klemm, Jonas; Pinna, Andrea
    Abstract: Stablecoins claim to stabilise the value of major currencies in the volatile crypto-asset market. This paper describes the often complex functioning of different types of stablecoins and proposes a taxonomy of stablecoin initiatives. To this end it relies on a novel framework for their classification, based on the key dimensions that matter for crypto-assets, namely: (i) accountability of issuer, (ii) decentralisation of responsibilities, and (iii) what underpins the value of the asset. The analysis of different types of stablecoins shows a trade-off between the novelty of the stabilisation mechanism used in an initiative (from mirroring the traditional electronic money approach to the alleged introduction of an “algorithmic central bank”) and its capacity to maintain a stable market value. While relatively less innovative stablecoins could provide a solution to users seeking a stable store of value, especially if legitimised by the adherence to standards that are typical of payment services, the jury is still out on the potential future role of more innovative stablecoins outside their core user base. JEL Classification: E42, L17, O33
    Keywords: crypto-assets, distributed ledger technology, electronic money, stablecoins
    Date: 2019–08
  4. By: Nazmiye Ceren Abay; Cuneyt Gurcan Akcora; Yulia R. Gel; Umar D. Islambekov; Murat Kantarcioglu; Yahui Tian; Bhavani Thuraisingham
    Abstract: With emergence of blockchain technologies and the associated cryptocurrencies, such as Bitcoin, understanding network dynamics behind Blockchain graphs has become a rapidly evolving research direction. Unlike other financial networks, such as stock and currency trading, blockchain based cryptocurrencies have the entire transaction graph accessible to the public (i.e., all transactions can be downloaded and analyzed). A natural question is then to ask whether the dynamics of the transaction graph impacts the price of the underlying cryptocurrency. We show that standard graph features such as degree distribution of the transaction graph may not be sufficient to capture network dynamics and its potential impact on fluctuations of Bitcoin price. In contrast, the new graph associated topological features computed using the tools of persistent homology, are found to exhibit a high utility for predicting Bitcoin price dynamics. %explain higher order interactions among the nodes in Blockchain graphs and can be used to build much more accurate price prediction models. Using the proposed persistent homology-based techniques, we offer a new elegant, easily extendable and computationally light approach for graph representation learning on Blockchain.
    Date: 2019–08
  5. By: Paul Belleflamme; Thomas Lambert; Armin Schwienbacher
    Abstract: Various forms of social learning and network effects are at work on crowdfunding platforms, giving rise to informational and payoff externalities. We use novel entrepreneur-backer data to study how these externalities shape funding dynamics, within and across projects. We find that backers decide to back a particular project based on past contributions not only to that project—as documented by prior work—but also to other contemporaneous projects—a novel result. Our difference-in-differences estimates indicate that such ‘cross-project funding dynamics’ account for 4-5% in the increase of contributions that projects generate on a daily basis. We show that recurrent backers are the main transmission channel of cross-project funding dynamics: by initiating social learning about project existence and quality, recurrent backers encourage future funding by other backers. Our results demonstrate that even though contemporaneous projects compete for funding, they jointly benefit from their common presence on the platform. We finally show that these crowdfunding dynamics stir platform growth, with important consequences for competition among platforms.
    Keywords: crowdfunding, digital platforms, FinTech, network effects, social learning
    JEL: D43 G23 L14 L26 L86
    Date: 2019
  6. By: Yuqing Xing (National Graduate Institute for Policy Studies, Tokyo, Japan)
    Abstract: Global Value chains (GVC) provide a new channel of innovation for firms participating in value chains or utilizing the value chain strategy to grow. Upgrading to high value added segments of GVCs step by step is a linear model of innovation. Our analysis on the Chinese firms involved in the value chain of the iPhone shows that the Chinese mobile industry has climbed up ladders of the iPhone value chain and performed relatively sophisticated tasks beyond simple assembly. In addition, by examining foreign value added and technology embedded in the smartphones of OPPO, Xiaomi and Huawei, we argue the Chinese smartphone vendors primarily follow a non-linear model of innovation, jumping directly to brand development before acquiring sufficient technology capacity. They have been focusing on incremental innovations and product differentiation by taking advantage of available technology platforms. The value chain strategy enabled them to overcome technology deficiency effectively and opened a short-cut to catch-up foreign rivals and evolve into leading smartphone makers in both domestic and foreign markets.
    Date: 2019–08
  7. By: Irvin Steve Cardenas; Jong-Hoon Kim
    Abstract: The concept of a blockchain has given way to the development of cryptocurrencies, enabled smart contracts, and unlocked a plethora of other disruptive technologies. But, beyond its use case in cryptocurrencies, and in network coordination and automation, blockchain technology may have serious sociotechnical implications in the future co-existence of robots and humans. Motivated by the recent explosion of interest around blockchains, and our extensive work on open-source blockchain technology and its integration into robotics - this paper provides insights in ways in which blockchains and other decentralized technologies can impact our interactions with robot agents and the social integration of robots into human society.
    Date: 2019–08
  8. By: KITALA CHRISTIAN MALAMSHA (Moshi Co operative University)
    Abstract: Adoption of mobile banking services by mobile phone owners in terms of level of adoption and usefulness of adoption remained inadequate in Tanzania. Such inadequacy of adoption is a result of utilizing traditional banking services by mobile phone owners which decreases advantage of using mobile banking technology. Mobile banking is a situation whereby the customer interacts with a bank via mobile device, an electronic banking system which allows bank customers to get access to their bank accounts via mobile phone. The establishment of adoption level, the factors influencing adoption and usefulness of mobile banking technology among mobile phone owners remains silent. That was a knowledge gap on which the research for this paper focused. The article is intended to assess adoption of mobile banking services by mobile phone owners in Moshi municipality, Tanzania. The specific objectives were to evaluate the level of adoption of mobile banking, analyse factors influencing adoption of mobile banking and evaluate usefulness of mobile banking services. Primary data were collected using questionnaires. They were administered to 182 mobile phone owners who are bank customers. Descriptive and inferential statistics were used. The adoption level of mobile baking was revealed to be inadequate. The main factors found to be behind non-adoption of mobile banking service was risk of loss and fear of system failure which was found to negatively affect adoption of mobile banking service. The risks found to have the greatest influence were fear of sending money to wrong account or phone number and loss of personal or account information. Perceived convenience was found to positively affect adoption of mobile banking. The usefulness established included; accessibility, saving of time and comfort mostly used to pay bills and funds transfer. It therefore concluded that adoption of mobile banking is inadequate and is affected negatively by risk of loss and fear while affected positively by perceived convenience and mobile banking is useful in various ways. It is argued that mobile banking should be adopted by banks and mobile phone owners in Tanzania.
    Keywords: Adoption, Mobile phone owners, Mobile banking services, Factors, Usefulness, Moshi Tanzania
    JEL: G21
    Date: 2019–07
  9. By: Julia M. Puaschunder (The New School, NY)
    Abstract: Economics is concerned about utility. Utility theory captures people’s preferences or values. As one of the foundations of economic theory, the wealth of information and theories on utility lacks information about decision-making conflicts between preferences and values. The preference for communication is inherent in human beings as a distinct feature of humanity. Leaving a written legacy that can inform many generations to come is a humane-unique advancement of society. At the same time, however, privacy is a core human value. People choose what information to share with whom and like to protect some parts of their selves by secrecy. Protecting people’s privacy is a codified virtue around the globe grounded in the wish to uphold individual’s dignity. Yet to this day, no utility theory exists to describe the internal conflict arising from the individual preference to communicate and the value of privacy. In the age of instant communication and social media big data storage and computational power; the need for understanding people’s trade off between communication and privacy has leveraged to unprecedented momentum. For one, enormous data storage capacities and computational power in the e-big data era have created unforeseen opportunities for big data hoarding corporations to reap hidden benefits from individual’s information sharing, which occurs bit by bit in small tranches over time.
    Keywords: Behavioral Economics, Behavioral Political Economy, Democratisation of information, Education, Exchange value, Governance, Preferences, Right to delete, Right to be forgotten, Social media, Utility, Value
    Date: 2018
  10. By: OECD
    Abstract: This report analyses different models for how operators may provide access to communication services over the next five to ten years. To that end, it analyses leading-edge demand and examines the type of companies that serve this demand. It then clusters and compares different categories of operators. These include traditional (vertically integrated) mobile and fixed broadband providers; (vertically integrated) cable operators; wholesale-only operators (utility); wireline wholesale-only providers; wireless wholesale-only providers; and (terminal) equipment and online service providers. The report outlines the most important developments in these categories before signalling emerging technologies that may influence operators in the future. It concludes by comparing different types of operators against policy objectives.
    Date: 2019–09–05
  11. By: Manveen Singh (Jindal Global Law School, O.P. Jindal Global University)
    Abstract: Standards and standards-setting organizations (SSOs) have played a crucial role in shaping the innovation landscape for over three decades, especially in the information and communication technologies (ICT) sector. The advancement in mobile telecommunication and the Internet has led to a fundamental change in the way individuals communicate with each other. Devices such as smartphones, tablets, laptops and smart watches bear complex mechanical and technological features and perform multiple functionalities by connecting seamlessly. However, in order for the interoperability of these devices and their functionalities to come through, there is a requirement of a common set of specifications and interfaces, in the form of standards. Standards are widely acknowledged to be the mainstay of modern economy and can lead to an increase in the value of consumer products, as well as increased rates of innovation. The setting of standards and commercializing of innovation at large is facilitated by voluntary associations called SSOs. Competing firms come together under the auspices of SSOs to collaboratively select and adopt uniform technical standards. It is worth noting that the benefits brought about by these standards have a greater visibility in the ICT sector, primarily on account of two reasons. First, in order to make complex technologies work, there is a requirement of hundreds of thousands of patents. Second, there is a strong need for devices and networks to interoperate in the ICT sector, which makes it absolutely necessary to develop common technical standards.SSOs are further tasked with the responsibility of fostering a regime of rapid technological innovation by balancing the interests of their members; their membership comprising of patent owners or standard essential patent (SEP) holders on one hand and implementers or licensees on the other. While the patent owners are involved in research and development (R&D) and look to maximize their earnings from licensing out their SEPs, the implementers look to seek licenses from SEP holders on terms that are fair, reasonable and non-discriminatory (FRAND), in order to use the patented technology in the manufacturing of standard-compliant end-use products. There is yet, a third category of member companies that are vertically integrated and besides owning SEPs, also operate actively in the downstream market. As members of SSOs, these firms compete in the market on both, horizontal and vertical levels, which gives rise to a possible likelihood of collusion albeit theoretically. It is because of this aspect of standard-setting, that the role of SSOs becomes extremely important.A pertinent question that arises then is, what are SSOs and how do they function? Furthermore, what is the legality of SSOs and how have they helped in the evolution of industry standards? In an attempt to answer the aforementioned questions, the focus of this paper shall center around standardization and standard-setting organizations, while tracing the evolution of standards and standard-setting activities in the ICT sector.
    Keywords: Standards, standardization, SSO, patents, SEP, technology
    JEL: O30
    Date: 2019–07
  12. By: Samuel Asante Gyamerah
    Abstract: The uncertainties in future Bitcoin price make it difficult to accurately predict the price of Bitcoin. Accurately predicting the price for Bitcoin is therefore important for decision-making process of investors and market players in the cryptocurrency market. Using historical data from 01/01/2012 to 16/08/2019, machine learning techniques (Generalized linear model via penalized maximum likelihood, random forest, support vector regression with linear kernel, and stacking ensemble) were used to forecast the price of Bitcoin. The prediction models employed key and high dimensional technical indicators as the predictors. The performance of these techniques were evaluated using mean absolute percentage error (MAPE), root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R-squared). The performance metrics revealed that the stacking ensemble model with two base learner (random forest and generalized linear model via penalized maximum likelihood) and support vector regression with linear kernel as meta-learner was the optimal model for forecasting Bitcoin price. The MAPE, RMSE, MAE, and R-squared values for the stacking ensemble model were 0.0191%, 15.5331 USD, 124.5508 USD, and 0.9967 respectively. These values show a high degree of reliability in predicting the price of Bitcoin using the stacking ensemble model. Accurately predicting the future price of Bitcoin will yield significant returns for investors and market players in the cryptocurrency market.
    Date: 2019–09
  13. By: OECD
    Abstract: Embracing new technologies that could enable drastic reductions in GHG emissions will be key to delivering low-emissions pathways for growth, but it is not always obvious what the big breakthroughs will look like. This report looks at how blockchain technology can be applied to support sustainable infrastructure investment that is aligned with climate change objectives. It focuses on three key points: the financing of infrastructure initiatives, the creation of visibility and alignment of climate action, and the provisioning of awareness and access for institutions and consumers.
    Date: 2019–09–05
  14. By: Yasaman Farhangpour (University of Florence)
    Abstract: Digital technology and new inventions caused changes in methods, facilities, living style, and eventually in art. New perceptions of aesthetic and existence appeared. In this regard, mural art and its concept experienced many alterations. Now, we observe diverse frescos benefitting from capabilities of soft and hardware digital, in the process of their creation. Acquisition of vast capabilities of digital technology, devices and facilities indicates that modern devices are more advanced and their utilities are more diverse than the traditional ones. Nowadays, with the expansion of technology and artists? tendency in using modern devices, necessity for perception of new concepts in fresco as a multi dimensional art is quite noticeable. Restrictions are minimized and possibility for performing them with modern capabilities in interaction with architecture, environment, space, and audience senses is provided and special visual attractions for artist and urban management is created.
    Keywords: Digital, Mural, Fresco, Visual, Multi dimensions
    Date: 2019–07
  15. By: Monwipa Wongrujira (Sukhothai Thammathirat Open University)
    Abstract: Technology and mobile devices allow many news consumers become news senders?prosumer (i.e. being both consumers and producers of news and information at the same time). Anyone could be a reporter. Also, there are tons of news and information flow around us every day. The differences between media reporting stories and information running around social media are the quality of news and information. If the media do only report ?who what when where why how,? they did not accomplish their task as a journalist. Data-driven journalism becomes significant in news reporting process. It needs not merely Big Data, but also analysis process and presentation. This paper intends to explore the use of data journalism among the mass media in Thailand. Whereas social media become more and more popular and drawing attention among Thai news consumers, the professional media need to differentiate their news reporting to focus on in-depth or investigative reporting. How the professional media apply data-driven journalism; to what extend did they use data for reporting a story; and what are the obstacles affecting their application of data journalism. Factors affecting the use of data-driven journalism included: data sources (incomplete, unstructured, and difficult to access), data compiling, time consuming and limitation of technology for data analysis and presentation.
    Keywords: Data journalism, professionalism, news reporting, mass media, social media, Thailand
    Date: 2019–07
  16. By: Andrea Potgieter (University of Johannesburg); Chris Rensleigh (University of Johannesburg)
    Abstract: A mobile application's (app) popularity and influence is determined by its users.These users download, use, review and support an app based on a myriad of requirements and needs. The aim of this paper is to showcase the results from asynchronous online interviews, which was focused on exploring the needs of potential users of a mobile blood donation app in South Africa.This paper specifically reports on the results of the 89 interviews conducted with existing and potential blood donors in South Africa during late 2017 and early 2018. As part of a larger, exploratory sequential mixed method research project, the interview schedule described in this paper was guided by the Leximancer analyses of app store reviews of existing blood donation apps, and the results from the interview informed a quantitative questionnaire. The results of the interviews, garnered from a Leximancer analyses, showed that the potential convenience afforded to blood donors by a blood donation app was important ? aspects such as reminders to donateand GPS functionality for finding blood donation events, among others, were mentioned as preferred features by respondents.Furthermore, several respondents noted that a question and answer feature with the blood donation organisation would be a value adding feature in an app of this kind.
    Keywords: Mobile app features; blood donation; Leximancer
    JEL: L31 L86 D83
    Date: 2019–07
  17. By: Bruce Lyons (School of Economics, University of East Anglia); Minyan Zhu (Department of Economics, University of Reading)
    Abstract: This paper examines how market structure influences the early introduction and consumer uptake of a digital service that is a convenient alternative to traditional service delivery. Digital provision also has "extended geographic reach" and "lower sunk costs" as compared with bricks-and-mortar service provision. We further examine how these affect market structure. Internet banking provides an important example that also allows us to separate regional integration and national concentration dimensions of market structure. We develop an econometric model of the effects of market structure on the introduction and consumer uptake of internet banking. We estimate using panel data for all EU Member States and find that both concentration and regionalisation bring these forward. Next, we examine how consumer uptake of the digital product then begins to impact on banking market structure. We find a substantial de-concentrating effect in large non-regionalised markets and indirect evidence of integration in previously regionalised markets. This is consistent with internet banking having enhanced competition in both integrated markets and, despite little change in national concentration, also in previously regionalised markets.
    Keywords: Internet Banking, Digital Markets, Endogenous Market Structure, Market Integration, Consumer Diffusion
    JEL: L11 O33 F15 G21 L81
    Date: 2019–04–25
  18. By: Barriga-Cabanillas, Oscar
    Keywords: International Development
    Date: 2019–06–25
  19. By: Yao, Becatien H.; Shanoyan, Aleksan
    Keywords: Agribusiness
    Date: 2019–06–25
  20. By: Lindquist, Matthew J. (SOFI, Stockholm University); Zenou, Yves (Monash University)
    Abstract: Social network analysis can help us understand more about the root causes of delinquent behavior and crime and provide practical guidance for the design of crime prevention policies. To illustrate these points, we first present a selective review of several key studies and findings from the criminology and police studies literature. We then turn to a presentation of recent contributions made by network economists. We highlight 10 policy lessons and provide a discussion of recent developments in the use of big data and computer technology.
    Keywords: co-offending, crime, criminal networks, social networks, peer effects, key player
    JEL: A14 K42 Z13
    Date: 2019–08
  21. By: Chanda, Areendam; Cook, Justin
    Abstract: On November 8, 2016, the Indian government abruptly demonetized 86% of its currency in circulation in an attempt to reduce black money, corruption, and counterfeiting. Yet, 99% of the currency was eventually returned to banks. We exploit large regional variations in deposit growth as a result of demonetization to study the medium-term effects of this policy. Using night-light data, we show that districts which experienced higher deposit growth during the demonetization period recorded higher levels of economic activity in the year and a half that followed. We estimate a one standard deviation increase in deposits is associated with a 5% increase in district GDP per capita. Further, districts with larger rural population, agricultural and non-agricultural informal labor shares also recorded an increase in nighttime light activity. The results are also supported by household-level surveys on income and expenditures.
    Keywords: Demonetization, Regional Economic Growth, Monetary Policy, Indian Economy, Difference in Difference, Informal Economy, Agriculture, Credit
    JEL: E21 E26 E51 E65 O11 O13 O16 O17 O18 O5
    Date: 2019–08–23
  22. By: Wolfgang Kerber (Philipps University Marburg)
    Abstract: This paper analyses whether competition law can help to solve problems of access to data and interoperability in IoT ecosystems, where often one firm has exclusive control of the data produced by a smart device (and of the technical access to this device). Such a gatekeeper position can lead to the elimination of competition for after-market and other complementary services in such IoT ecosystems. This problem is analysed both from an economic and a legal perspective, and also generally for IoT ecosystems as well as for the much discussed problems of “access to in-vehicle data and resources†in connected cars, where the “extended vehicle†concept of the car manufacturers leads to such positions of exclusive control. The paper analyses, in particular, the competition rules about abusive behavior of dominant firms (Art. 102 TFEU) and of firms with “relative market power†(§ 20 (1) GWB) in German competition law. These provisions might offer (if appropriately applied and amended) at least some solutions for these data access problems. Competition law, however, might not be sufficient for dealing with all or most of these problems, i.e. that also additional solutions might be needed (data portability, direct data (access) rights, or sector-specific regulation).
    Keywords: data access, Internet of Things, data sharing, data access, competition, digital economy, connected cars
    JEL: K23 L62 L86 O33
    Date: 2019
  23. By: Michael Carter; Rachid Laajaj; Dean Yang
    Abstract: The Green Revolution bolstered agricultural yields and rural well-being in Asia and Latin America, but bypassed sub-Saharan Africa. We study the first randomized controlled trial of a government-implemented input subsidy program (ISP) in Africa. A temporary subsidy for Mozambican maize farmers stimulates Green Revolution technology adoption and leads to increased maize yields. Effects of the subsidy persist in later unsubsidized years. In addition, social networks of subsidized farmers benefit from spillovers, experiencing increases in technology adoption, yields, and beliefs about the returns to the technologies. Spillovers account for the vast majority of subsidy-induced gains. ISPs alleviate informational market failures, stimulating learning about new technologies by subsidy recipients and their social networks
    JEL: O12 O33 O55 Q12
    Date: 2019–08
  24. By: Simplice A. Asongu (Yaoundé/Cameroon); Joseph I. Uduji (University of Nigeria, Nsukka, Nigeria); Elda N. Okolo-Obasi (University of Nigeria, Nsukka, Nigeria)
    Abstract: This study investigates the relationship between social media and homicide in a cross section of 148 countries for the year 2012. The empirical evidence is based on Ordinary Least Squares, Tobit and Quantile regressions. The findings from Ordinary Least Squares and Tobit regressions show a negative relationship between Facebook penetration and the homicide rate. The negative relationship is driven by the 75th quantile of the conditional distribution of the homicide rate. The negative nexus is also driven by upper middle income countries and “Europe and Central Asia†. Three main implications are apparent when the findings are compared and contrasted. First, established findings from OLS and Tobit regressions are driven by countries with above-median levels of homicide. Second, such above-median countries are largely associated with upper middle income countries and nations in “Europe and Central Asia†. Third, modelling the relationship between Facebook penetration and homicide at the conditional mean of homicide may be misleading unless it is contingent on initial levels of homicide and tailored differently across income levels and regions of the world.
    Keywords: Homicide; Social media
    JEL: K42 D83 O30 D74 D83
    Date: 2019–01
  25. By: OECD
    Abstract: Building on the OECD Recommendation of the Council on Consumer Protection in E-Commerce, this paper aims to provide practical guidance to businesses on online consumer ratings and reviews. The document focuses on four issue areas: (i) fake ratings and reviews; (ii) incentivised ratings and reviews; (iii) negative ratings and reviews; and (iv) misleading moderation practices.
    Date: 2019–09–06
  26. By: Pierpaolo Benigno; Linda M. Schilling; Harald Uhlig
    Abstract: We analyze a two-country economy with complete markets, featuring two national currencies as well as a global (crypto)currency. If the global currency is used in both countries, the national nominal interest rates must be equal and the exchange rate between the national currencies is a risk- adjusted martingale. We call this result Crypto-Enforced Monetary Policy Synchronization (CEMPS). Deviating from interest equality risks approaching the zero lower bound or the abandonment of the national currency. If the global currency is backed by interest-bearing assets, additional and tight restrictions on monetary policy arise. Thus, the classic Impossible Trinity becomes even less reconcilable.
    JEL: D53 E4 F31 G12
    Date: 2019–08
  27. By: OECD
    Abstract: This paper takes stock of recent developments related to online consumer ratings and reviews and their effects on consumer behaviour. It provides an overview of key consumer benefits and risks associated with user-generated feedback, and identifies consumer policy challenges, including misleading and deceptive practices, a lack of accuracy, and consumer biases. It also points to issues for further consideration by consumer policy makers and enforcement authorities, as well as businesses and consumer organisations.
    Date: 2019–09–06
  28. By: Alaimo, Cristina; Kallinikos, Jannis; Vallderama-Venegas, E
    JEL: J50
    Date: 2019–08–06
  29. By: McGuinness, Seamus (Economic and Social Research Institute, Dublin); Pouliakas, Konstantinos (European Centre for the Development of Vocational Training (Cedefop)); Redmond, Paul (ESRI, Dublin)
    Abstract: We use data from a new international dataset - the European Skills and Jobs Survey - to create a unique measure of skills-displacing technological change (SDT), defined as technological change that may render workers' skills obsolete. We find that 16 percent of adult workers in the EU are impacted by SDT, with significant variance across countries, ranging from a high of 28 percent in Estonia, to below seven percent in Bulgaria. Despite claims that technological change contributes to the deskilling of jobs, we present evidence that SDT is associated with dynamic upskilling of workers. The paper also presents the first direct micro-evidence of the reinstatement effect of automating technology, namely a positive contribution of automation to the task content and skills complexity of the jobs of incumbent workers. Despite the recent focus on the polarising impact of automation and associated reskilling needs of lower-skilled individuals, our evidence also draws attention to the fact that SDT predominantly affects higher-skilled workers, reinforcing inequalities in upskilling opportunities within workplaces. Workers affected by SDT also experience greater job insecurity.
    Keywords: technological change, automation, skills, tasks, skill mismatch, skills obsolescence
    JEL: J24 O33 O31
    Date: 2019–08
  30. By: Haoqian Li; Thomas Lau
    Abstract: With the increasing power of computers and the rapid development of self-learning methodologies such as machine learning and artificial intelligence, the problem of constructing an automatic Financial Trading Systems (FTFs) becomes an increasingly attractive research topic. An intuitive way of developing such a trading algorithm is to use Reinforcement Learning (RL) algorithms, which does not require model-building. In this paper, we dive into the RL algorithms and illustrate the definitions of the reward function, actions and policy functions in details, as well as introducing algorithms that could be applied to FTFs.
    Date: 2019–08
  31. By: Armando Ortuño; Juan Luis Jiménez
    Abstract: El presente trabajo analiza la oferta de alojamientos turísticos que se canaliza a través de plataformas on-line, con especial atención al caso de Airbnb. En él se repasa la todavía escasa literatura existente sobre los efectos de estas plataformas sobre el sector hotelero y el mercado inmobiliario, así como la regulación existente en distintos países, ciudades y comunidades autónomas y el tratamiento fiscal de esta actividad. También se realiza un análisis descriptivo del grado de penetración de Airbnb en España y se ofrecen algunas recomendaciones para dar respuesta a los retos que plantea el fenómeno.
    Date: 2019–03
  32. By: M. Keith Chen; Kareem Haggag; Devin G. Pope; Ryne Rohla
    Abstract: Equal access to voting is a core feature of democratic government. Using data from millions of smartphone users, we quantify a racial disparity in voting wait times across a nationwide sample of polling places during the 2016 US presidential election. Relative to entirely-white neighborhoods, residents of entirely-black neighborhoods waited 29% longer to vote and were 74% more likely to spend more than 30 minutes at their polling place. This disparity holds when comparing predominantly white and black polling places within the same states and counties, and survives numerous robustness and placebo tests. Our results document large racial differences in voting wait times and demonstrates that geospatial data can be an effective tool to both measure and monitor these disparities.
    Date: 2019–08
  33. By: Stefania Albanesi; Domonkos F. Vamossy
    Abstract: We develop a model to predict consumer default based on deep learning. We show that the model consistently outperforms standard credit scoring models, even though it uses the same data. Our model is interpretable and is able to provide a score to a larger class of borrowers relative to standard credit scoring models while accurately tracking variations in systemic risk. We argue that these properties can provide valuable insights for the design of policies targeted at reducing consumer default and alleviating its burden on borrowers and lenders, as well as macroprudential regulation.
    Date: 2019–08
  34. By: Yiping Huang; Xiang Li; Chu Wang
    Abstract: This paper uses loan application-level data from a peer-to-peer lending platform to study the risk-taking channel of monetary policy. By employing a direct ex-ante measure of risk-taking and estimating the simultaneous equations of loan approval and loan amount, we are the first to provide quantitative evidence of the impact of monetary policy on the risk-taking of nonbank financial institution. We find that the search-for-yield is the main workhorse of the risk-taking effect, while we do not observe consistent findings of risk-shifting from the liquidity change. Monetary policy easing is associated with a higher probability of granting loans to risky borrowers and a greater riskiness of credit allocation, but these changes do not necessarily relate to a larger loan amount on average.
    Keywords: monetary policy, risk-taking, nonbank financial institution, peer-to-peer lending, search-for-yield, risk-shifting
    JEL: E52 G23
    Date: 2019
  35. By: Serge Svizzero (CEMOI - Centre d'Économie et de Management de l'Océan Indien - UR - Université de La Réunion); Clement Tisdell
    Date: 2019–08–30
  36. By: Zheng Tracy Ke; Bryan T. Kelly; Dacheng Xiu
    Abstract: We introduce a new text-mining methodology that extracts sentiment information from news articles to predict asset returns. Unlike more common sentiment scores used for stock return prediction (e.g., those sold by commercial vendors or built with dictionary-based methods), our supervised learning framework constructs a sentiment score that is specifically adapted to the problem of return prediction. Our method proceeds in three steps: 1) isolating a list of sentiment terms via predictive screening, 2) assigning sentiment weights to these words via topic modeling, and 3) aggregating terms into an article-level sentiment score via penalized likelihood. We derive theoretical guarantees on the accuracy of estimates from our model with minimal assumptions. In our empirical analysis, we text-mine one of the most actively monitored streams of news articles in the financial system—the Dow Jones Newswires—and show that our supervised sentiment model excels at extracting return-predictive signals in this context.
    JEL: C53 C58 G10 G11 G12 G14 G17
    Date: 2019–08
  37. By: Nkosinomusa Mabaso (Cape Peninsula University of Technology); Lawrence Meda (Cape Peninsula University of Technology)
    Abstract: All universities in South Africa are encouraged to use a Learning Management System such as Blackboard to facilitate blended learning. Despite, the availability of Blackboard at one university of technology in the country, some lecturers and students prefer utilising WhatsApp for teaching and learning. The purpose of this study is to investigate students and lecturers? perspectives about learning and teaching using WhatsApp at a university in South Africa. The study was done using a qualitative case study within an intepretivist paradigm. It was guided by Garrison, Anderson and Archer?s Community of Inquiry as a theoretical framework. Sixteen students and two lecturers who heavily use WhatsApp were purposively selected to participate in semi-structured interviews and focus group discussions. The study found that lecturers use WhatsApp not only for communication purposes, but to foster collaborative learning among students. Although students noted some limitations which they experience when using WhatsApp, they preferred the social media to blackboard. The study concludes that although WhatsApp is response to students? needs, it does not adequately prepare students to graduate with digital literacy skills expected by the Department of Education in the country.
    Keywords: LMS; Utilisation; WhatsApp; Curriculum; Teacher
    JEL: I20
    Date: 2019–06
  38. By: Emilia Filippi; Sandro Trento
    Abstract: There is a rising concern for technological unemployment due to the current digital revolution. In order to estimate the probability of automation of occupations we applied two methods: occupation-based approach [Frey and Osborne (2017]) and task-based approach [Nedelkoska and Quintini (2018)]. We found that occupations with a high risk of automation require many routine activities, whereas occupations at low risk require abilities like perception, manipulation, creative intelligence and social intelligence. In Italy, based on the occupation-based approach, 33.2% of workers face a high risk of replacement; this percentage decrease at 18.1% if we apply the task-based approach. Male workers appear to face a higher risk of replacement than female ones. Actual automation may be lower than expected as it depends on many factors, such as technical feasibility, economic benefits that can be obtained and job creation thanks to technology itself. Finally, we stress the importance to adopt some policies; education and training of employees seems to be the most effective one.
    Keywords: technological change and unemployment; automation of occupations; skills and human capital
    JEL: E24 J24 J62 J64 O33 O39
    Date: 2019
  39. By: Michels, Marius; Bonke, Vanessa; Mußhoff, Oliver
    Abstract: Recent years have been marked by a steady increase in decision support tools available for farmers. Likewise, the number of dairy herd management smartphone apps to support on-farm decision making has increased. The existing literature does not yet cover topics concerning the adoption of herd management smartphone apps or which specific functions of such apps are perceived as useful by dairy farmers. Thus, this study tries to close this research gap by providing results about the adoption and use of dairy herd management smartphone apps derived from an online survey conducted in 2018 with 280 German dairy farmers. Dairy farmers rate functions related to the observation of animal health, reproduction management and data gathering as most useful. By rating functions and not specific smartphone apps, the results are also of interest for dairy sectors and developers outside Germany. Our results show that in our sample 91% of the dairy farmers use a smartphone and 61% already use a herd management smartphone app. Moreover, 38% of the adopters use such an app on a daily basis. Technology adoption cannot solely be explained by economic reasoning, but also the beliefs about a technology play a crucial role in decision making. Thus, this study also sought to determine whether an extended Technology Acceptance Model could explain adoption and use of herd management smartphone apps applying partial least squares structural equation modelling. All hypotheses of the Technology Acceptance Model could be verified by this study. The key attitudinal components of the model are perceived ease of use and perceived usefulness, which both positively influence the intention to use herd management smartphone apps; this ultimately has a positive effect on the actual usage behavior. All in all, our model explained 33% of the variance in the actual use of herd management apps by German dairy farmers.
    Keywords: Agribusiness, Farm Management, Livestock Production/Industries
    Date: 2019–08–26
  40. By: Yasuyuki Kusuda
    Abstract: In this paper, we extend the model of Gao and Su (2016) and consider an omnichannel strategy in which inventory can be replenished when a retailer sells only in physical stores. With "buy-online-and-pick-up-in-store" (BOPS) having been introduced, consumers can choose to buy directly online, buy from a retailer using BOPS, or go directly to a store to make purchases without using BOPS. The retailer is able to select the inventory level to maximize the probability of inventory availability at the store. Furthermore, the retailer can incur an additional cost to reduce the BOPS ordering lead time, which results in a lowered hassle cost for consumers who use BOPS. In conclusion, we found that there are two types of equilibrium: that in which all consumers go directly to the store without using BOPS and that in which all consumers use BOPS.
    Date: 2019–09
  41. By: Tan, Si; Chen, Weiping
    Keywords: Agribusiness
    Date: 2019–06–25
  42. By: Mohamad adning (Brunel University of London); Diana Sari Dj (Quality Insurance of Education Institute, Lampung Province, Indonesia); Kulsum Nur Hayati (Development Center for Radio Media Education and Culture, Yogyakarta, Indonesia)
    Abstract: This study examined senior teachers and junior teachers at primary school to show their mobile phone activity level among teacher working group in Lampung Province in 5 districts. The category of junior teachers are teachers whom are under 32 years (246 teachers) and senior teachers are categorised among teachers whom are over 50 years (304 teachers) and the total respondent is 550 teachers. There are two main elements of this research. Firstly, there is perception on the activity on junior teachers and senior teachers in primary school in teacher working group in Lampung Province. The research found that senior teachers are more active and care about being a part of teacher working group as compared to junior teachers, but both of them said that teacher working group helps them to improve their competencies. Secondly, there is a perception of the activity by junior teachers and senior teachers in the mobile phone group chat in the teacher working group. The result indicates that the junior teachers perceive themselves as experts (63% of the respondents) in using mobile phone, higher than senior teachers (23%). The result has also found that not all junior teachers were engaged in the group chat in teacher working group (72%), and the same pattern was seen among senior teachers as only 75% of them were engaged in group chat. There is a different perception of activity between junior teachers and senior teacher in collaborative learning through the mobile phone in teacher working group based on t-test with an independent sample test. The data indicates (2 tailed) 0.011 compare to the table
    Keywords: Teacher working group, mobile phone, teacher
    JEL: I20 I21 I29
    Date: 2019–06
  43. By: Manu García; Juan F. Rubio-Ramírez
    Abstract: En este documento se resume la metodología del Nowcasting de Fedea. Se utiliza un modelo dinámico de factores bayesiano para generar predicciones en tiempo real de la tasa de crecimiento interanual del PIB de la economía española durante el trimestre en curso y el siguiente. La predicción incorpora la información disponible en 18 variables macroeconómicas y se actualiza cada vez que se publican nuevos datos de alguna de ellas.
    Date: 2019–02
  44. By: Yang Hu (University of Waikato); Yang (Greg) Hou (University of Waikato); Les Oxley (University of Waikato)
    Abstract: This paper investigates the causal relationships, cointegration and price discovery between spot and futures markets of Bitcoin using the daily data from a time-varying perspective for the first time in the literature. We apply the time-varying Granger causality test of Shi et al. (2018) to explore the causal relationship between spot and futures markets and find that futures prices Granger cause spot prices. We identify the existence of a cointegration relationship under the consideration of a time-varying cointegrating coefficient between spot and futures prices based on the Park and Hahn (1999) test. We also explore the time-varying price discovery process and find that futures prices dominate in the process, implying a leading informational role.
    Keywords: Bitcoin; futures; time-varying; causality; cointegration; price discovery
    JEL: C5 G12 G13 G14
    Date: 2019–08–31
  45. By: Zhenzhe Zheng; R. Srikant
    Abstract: Online platforms, such as Airbnb,, Amazon, Uber and Lyft, can control and optimize many aspects of product search to improve the efficiency of marketplaces. Here we focus on a common model, called the discriminatory control model, where the platform chooses to display a subset of sellers who sell products at prices determined by the market and a buyer is interested in buying a single product from one of the sellers. Under the commonly-used model for single product selection by a buyer, called the multinomial logit model, and the Bertrand game model for competition among sellers, we show the following result: to maximize social welfare, the optimal strategy for the platform is to display all products; however, to maximize revenue, the optimal strategy is to only display a subset of the products whose qualities are above a certain threshold. We extend our results to Cournot competition model, and show that the optimal search segmentation mechanisms for both social welfare maximization and revenue maximization also have simple threshold structures. The threshold in each case depends on the quality of all products, the platform's objective and seller's competition model, and can be computed in linear time in the number of products.
    Date: 2019–08
  46. By: YANO Makoto; FURUKAWA Yuichi
    Abstract: This study is motivated by the widely-held view that self-replicating artificial intelligence may approach "some essential singularity . . . beyond which human affairs, as we know them, could not continue" (von Neumann). It investigates what state this process would lead to in an economy with frictionless markets. We demonstrate that if the production technologies, too, are frictionless, all workers will eventually be pulled into the most labor friendly sector (economic black hole). If, instead, they are subject to a friction created by congestion, it will eventually give rise to a state in which all workers will be unemployed (labor singularity).
    Date: 2019–08
  47. By: Denis Shibitov (Bank of Russia, Russian Federation); Mariam Mamedli (Bank of Russia, Russian Federation)
    Abstract: We evaluate the forecasting ability of machine learning models to predict bank license withdrawal and the violation of statutory capital and liquidity requirements (capital adequacy ratio N1.0, common equity Tier 1 adequacy ratio N1.1, Tier 1 capital adequacy ratio N1.2, N2 instant and N3 current liquidity). On the basis of 35 series from the accounting reports of Russian banks, we form two data sets of 69 and 721 variables and use them to build random forest and gradient boosting models along with neural networks and a stacking model for different forecasting horizons (1, 2, 3, 6, 9 months). Based on the data from February 2014 to October 2018 we show that these models with fine-tuned architectures can successfully compete with logistic regression usually applied for this task. Stacking and random forest generally have the best forecasting performance comparing to the other models. We evaluate models with commonly used performance metrics (ROC-AUC and F1) and show that, depending on the task, F1-score could be better at defining the model’s performance. Comparison of the results depending on the metrics applied and types of cross-validation used illustrate the importance of choosing the appropriate metric for performance evaluation and the cross-validation procedure, which accounts for the characteristics of the data set and the task under consideration. The developed approach shows the advantages of non-linear methods for bank regulation tasks and provides the guidelines for the application of machine learning algorithms to these tasks.
    Keywords: machine learning, random forest, neural networks, gradient boosting, forecasting, bank supervision
    JEL: C53 C52 C5
    Date: 2019–08
  48. By: Goller, Daniel (University of St. Gallen); Lechner, Michael (University of St. Gallen); Moczall, Andreas (Institute for Employment Research (IAB), Nuremberg); Wolff, Joachim (Institute for Employment Research (IAB), Nuremberg)
    Abstract: Matching-type estimators using the propensity score are the major workhorse in active labour market policy evaluation. This work investigates if machine learning algorithms for estimating the propensity score lead to more credible estimation of average treatment effects on the treated using a radius matching framework. Considering two popular methods, the results are ambiguous: We find that using LASSO based logit models to estimate the propensity score delivers more credible results than conventional methods in small and medium sized high dimensional datasets. However, the usage of Random Forests to estimate the propensity score may lead to a deterioration of the performance in situations with a low treatment share. The application reveals a positive effect of the training programme on days in employment for long-term unemployed. While the choice of the "first stage" is highly relevant for settings with low number of observations and few treated, machine learning and conventional estimation becomes more similar in larger samples and higher treatment shares.
    Keywords: programme evaluation, active labour market policy, causal machine learning, treatment effects, radius matching, propensity score
    JEL: J68 C21
    Date: 2019–08
  49. By: Huber, Martin
    Abstract: This chapter covers different approaches to policy evaluation for assessing the causal effect of a treatment or intervention on an outcome of interest. As an introduction to causal inference, the discussion starts with the experimental evaluation of a randomized treatment. It then reviews evaluation methods based on selection on observables (assuming a quasi-random treatment given observed covariates), instrumental variables (inducing a quasi-random shift in the treatment), difference-in-differences and changes-in-changes (exploiting changes in outcomes over time), as well as regression discontinuities and kinks (using changes in the treatment assignment at some threshold of a running variable). The chapter discusses methods particularly suited for data with many observations for a flexible (i.e. semi- or nonparametric) modeling of treatment effects, and/or many (i.e. high dimensional) observed covariates by applying machine learning to select and control for covariates in a data-driven way. This is not only useful for tackling confounding by controlling for instance for factors jointly affecting the treatment and the outcome, but also for learning effect heterogeneities across subgroups defined upon observable covariates and optimally targeting those groups for which the treatment is most effective.
    Keywords: Policy evaluation; treatment effects; machine learning; experiment; selection on observables; instrument; difference-indifferences; changes-in-changes; regression discontinuity design; regression kink design
    JEL: C21 C26 C29
    Date: 2019–08–12

General information on the NEP project can be found at For comments please write to the director of NEP, Marco Novarese at <>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.