nep-pay New Economics Papers
on Payment Systems and Financial Technology
Issue of 2020‒05‒04
twenty-one papers chosen by
Bernardo Bátiz-Lazo
Bangor University

  1. Important Factors Determining Fintech Loan Default: Evidence from the LendingClub Consumer Platform By Christophe Croux; Julapa Jagtiani; Tarunsai Korivi; Milos Vulanovic
  2. Covid-19, cash, and the future of payments By Raphael Auer; Giulio Cornelli; Jon Frost
  3. Deep reinforcement learning for the optimal placement of cryptocurrency limit orders By Schnaubelt, Matthias
  4. From signalling to endorsement: The valorisation of fledgling digital ventures By Klus, Milan Frederik
  5. Mean Field Game Approach to Bitcoin Mining By Charles Bertucci; Louis Bertucci; Jean-Michel Lasry; Pierre-Louis Lions
  6. Platform Cooperativism in Italy and in Europe By Francesca MARTINELLI, , & Giuseppe GUERINI; Samuele BOZZONI; Simone CAROLI; Francesca TAMASCELLI; Giuseppe GUERINI
  7. Using Big Data to Expand Financial Services : Benefits and Risks By Abraham,Facundo; Schmukler,Sergio L.; Tessada,Jose
  8. Shallow or deep? Detecting anomalous flows in the Canadian Automated Clearing and Settlement System using an autoencoder By Leonard Sabetti; Ronald Heijmans
  9. Hacia un mercado regional de servicios digitales en Centroamérica By -
  10. How Much Did People Refrain from Service Consumption due to the Outbreak of COVID-19? By Tsutomu Watanabe; Yuki Omori
  11. Robo-Advising By Francesco D'Acunto; Alberto G. Rossi
  12. The roles of the state in the governance of socio-technical systems' transformation By Borrás, Susana; Edler, Jakob
  13. Consumers’ Mobility, Expenditure and Online-Offline Substitution Response to COVID-19: Evidence from French Transaction Data By David Bounie; Youssouf Camara; John W. Galbraith
  14. Modeling the bias of digital data: an approach to combining digital and survey data to estimate and predict migration trends By Yuan Hsiao; Lee Fiorio; Jonathan Wakefield; Emilio Zagheni
  15. Migration between Platforms By Gary Biglaiser; Jacques Crémer; André Veiga
  16. Technologie Blockchain et intermédiation dans l'industrie musicale. By Laurent Bach; Remy Guichardaz; Eric Schenk
  17. Karl Helfferich and Rudolf Hilferding on Georg Friedrich Knapp’s State Theory of Money: Monetary Theories during the Hyperinflation of 1923 By Greitens, Jan
  18. The Geographic Spread of COVID-19 Correlates with Structure of Social Networks as Measured by Facebook By Theresa Kuchler; Dominic Russel; Johannes Stroebel
  19. Visual Elicitation of Brand Perception By Daria Dzyabura; Renana Peres
  20. Bitcoin: An Impossibility Theorem for Proof-of-Work based Protocols By Thomas Kruse; Philipp Strack
  21. Technological Revolutions, Structural Change & Catching-Up By Jan Fagerberg; Bart Verspagen

  1. By: Christophe Croux; Julapa Jagtiani; Tarunsai Korivi; Milos Vulanovic
    Abstract: This study examines key default determinants of fintech loans, using loan-level data from the LendingClub consumer platform during 2007–2018. We identify a robust set of contractual loan characteristics, borrower characteristics, and macroeconomic variables that are important in determining default. We find an important role of alternative data in determining loan default, even after controlling for the obvious risk characteristics and the local economic factors. The results are robust to different empirical approaches. We also find that homeownership and occupation are important factors in determining default. Lenders, however, are required to demonstrate that these factors do not result in any unfair credit decisions. In addition, we find that personal loans used for medical financing or small business financing are more risky than other personal loans, holding the same characteristics of the borrowers. Government support through various public-private programs could potentially make funding more accessible to those in need of medical services and small businesses without imposing excessive risk to small peer-to-peer (P2P) investors.
    Keywords: crowdfunding; lasso selection methods; peer-to-peer lending; household finance; machine learning; financial innovation; big data; P2P/marketplace lending
    JEL: G21 D14 D10 G29 G20
    Date: 2020–04–16
  2. By: Raphael Auer; Giulio Cornelli; Jon Frost
    Abstract: The Covid-19 pandemic has fanned public concerns that the coronavirus could be transmitted by cash. Scientific evidence suggests that the probability of transmission via banknotes is low when compared with other frequently-touched objects, such as credit card terminals or PIN pads. To bolster trust in cash, central banks are actively communicating, urging continued acceptance of cash and, in some instances, sterilising or quarantining banknotes. Some encourage contactless payments. Looking ahead, developments could speed up the shift toward digital payments. This could open a divide in access to payments instruments, which could negatively impact unbanked and older consumers. The pandemic may amplify calls to defend the role of cash - but also calls for central bank digital currencies.
    Date: 2020–04–03
  3. By: Schnaubelt, Matthias
    Abstract: This paper presents the first large-scale application of deep reinforcement learning to optimize the placement of limit orders at cryptocurrency exchanges. For training and out-of-sample evaluation, we use a virtual limit order exchange to reward agents according to the realized shortfall over a series of time steps. Based on the literature, we generate features that inform the agent about the current market state. Leveraging 18 months of high-frequency data with 300 million historic trades and more than 3.5 million order book states from major exchanges and currency pairs, we empirically compare state-of-the-art deep reinforcement learning algorithms to several benchmarks. We find proximal policy optimization to reliably learn superior order placement strategies when compared to deep double Q-networks and other benchmarks. Further analyses shed light into the black box of the learned execution strategy. Important features are current liquidity costs and queue imbalances, where the latter can be interpreted as predictors of short-term mid-price returns. To preferably execute volume in limit orders to avoid additional market order exchange fees, order placement tends to be more aggressive in expectation of unfavorable price movements.
    Keywords: Finance,Optimal Execution,Limit Order Markets,Machine learning,Deep Reinforcement Learning
    Date: 2020
  4. By: Klus, Milan Frederik
    Abstract: Despite extensive research on the liability of newness of young firms and what they can do to reduce information asymmetries, relatively little is known about how young digital ventures' growth and scaling is affected by different forms of endorsement. With a focus on third-party endorsements from industry analysts, I approach this question using a two-stage research design. First, I empirically examine the connection between awards given by industry analysts and the funding of digital ventures. I use the example of the Cool Vendor award given by the analyst firm Gartner and focus on the fintech domain. Using semi-structured interviews, I then identify and explain different forms of endorsement from a digital venture perspective, thereby differentiating between pure market signals and more sophisticated mechanisms. This differentiation is presented in a conceptual framework, which I propose as a supplement to the signalling literature. This paper promotes a better understanding of what helps fledgling digital firms to develop and prosper.
    JEL: D83 G24 M13 O33
    Date: 2020
  5. By: Charles Bertucci (CMAP, Ecole Polytechnique, Palaiseau, France); Louis Bertucci (Institut Louis Bachelier, Paris, France; Haas School of Business, UC Berkeley, Berkeley, California); Jean-Michel Lasry (Universit\'e Paris-Dauphine, PSL Research University, CEREMADE, Paris, France); Pierre-Louis Lions (Universit\'e Paris-Dauphine, PSL Research University, CEREMADE, Paris, France; Coll\`ege de France, Paris, France)
    Abstract: We present an analysis of the Proof-of-Work consensus algorithm, used on the Bitcoin blockchain, using a Mean Field Game framework. Using a master equation, we provide an equilibrium characterization of the total computational power devoted to mining the blockchain (hashrate). From a simple setting we show how the master equation approach allows us to enrich the model by relaxing most of the simplifying assumptions. The essential structure of the game is preserved across all the enrichments. In deterministic settings, the hashrate ultimately reaches a steady state in which it increases at the rate of technological progress. In stochastic settings, there exists a target for the hashrate for every possible random state. As a consequence, we show that in equilibrium the security of the underlying blockchain is either $i)$ constant, or $ii)$ increases with the demand for the underlying cryptocurrency.
    Date: 2020–04
  6. By: Francesca MARTINELLI, , & Giuseppe GUERINI (Fondazione Centro Studi Doc, Verona (Italy)); Samuele BOZZONI (Confcooperative Lombardia (Italy)); Simone CAROLI (Confcooperative Modena (Italy)); Francesca TAMASCELLI (Legacoop Estense – Culture and Media (Italy)); Giuseppe GUERINI (Cecop – Cicopa Europe)
    Abstract: This research investigates some cases of cooperative platforms in the field of workerowned cooperation and consumer cooperation and explores the effects of the merger of platform technology with cooperation. The research focuses on the main consequences of this merger on the organizational model and the engagement level of individuals and studies the change of attitudes of providers and consumers when they are engaged in a cooperative project. The argument is that a cooperative platform can offer solutions and answers to both platform workers’ needs and problems of modern consumption by allowing both providers and consumers to join the entrepreneurial project, share resources – and, in specific cases, earnings – in an equal way, and be part of a community. Against the outsourcing and dispersive models of a classical digital platform, such as Deliveroo, Uber or Airbnb, where providers and consumers are separated and isolated, a cooperative platform enables the propensity of providers and consumers to engage in collective actions and become the protagonist of the platform activity. In this way, the organizational form of a cooperative platform is both an alternative to classical digital platforms and an evolution of traditional cooperative models.
    Keywords: Platform cooperativism, Gig workers, Prosumers, Digital platform, Platform work
    JEL: O35
    Date: 2019
  7. By: Abraham,Facundo; Schmukler,Sergio L.; Tessada,Jose
    Abstract: Big data is transforming financial services around the world. Advances in data analytics and computational power are allowing firms to exploit data in an easier, faster, and more reliable manner, and at a larger scale. By using big data, financial firms and new entrants from other sectors are able to provide more and better financial services. Governments are also exploring ways to use big data collected by the financial sector more systematically to get a better picture of the financial system as a whole and the overall economy. Despite its benefits, the wider use of big data has raised concerns related to consumer privacy, data security, discrimination, data accuracy, and competition. Hence, policy makers have started to regulate and monitor the use of big data by financial institutions and to think about how to use big data for the benefit of all.
    Keywords: ICT Applications,Legal Institutions of the Market Economy,Financial Structures,Financial Sector Policy
    Date: 2019–11–01
  8. By: Leonard Sabetti; Ronald Heijmans
    Abstract: Financial market infrastructures and their participants play a crucial role in the economy. Financial or operational challenges faced by one participant can have contagion effects and pose risks to the broader financial system. Our paper applies (deep) neural networks (autoencoder) to detect anomalous flows from payments data in the Canadian Automated Clearing and Settlement System (ACSS) similar to Triepels et al. (2018). We evaluate several neural network architecture setups based on the size and number of hidden layers, as well as differing activation functions dependent on how the input data was normalized. As the Canadian financial system has not faced bank runs in recent memory, we train the models on "normal" data and evaluate out-of-sample using test data based on historical anomalies as well as simulated bank runs. Our out-of-sample simulations demonstrate the autoencoder's performance in different scenarios, and results suggest that the autoencoder detects anomalous payment flows reasonably well. Our work highlights the challenges and trade-offs in employing a workhorse deep-learning model in an operational context and raises policy questions around how such outlier signals can be used by the system operator in complying with the prominent payment systems guidelines and by financial stability experts in assessing the impact on the financial system of a financial institution that shows extreme behaviour.
    Keywords: Anomaly Detection; Autoencoder; Neural Network; Articial intelligence; ACSS; Financial Market Infrastructure; Retail Payments
    JEL: C45 E42 E58
    Date: 2020–04
  9. By: -
    Abstract: En este documento se presenta un análisis de los principales factores que pueden impulsar u obstaculizar la creación de un mercado de servicios digitales en Centroamérica. Se analiza la situación de la oferta exportable de Costa Rica y Panamá como una aproximación del nivel de preparación regional en tres dimensiones: la capacidad de conectividad digital; el marco legal y regulatorio, y los acuerdos internacionales que se relacionan con el comercio de servicios digitales. Para ello se recopiló información estadística disponible sobre la oferta exportable de servicios digitales de ambos países, se consultó la opinión de expertos locales y se revisaron indicadores de organizaciones internacionales. Asimismo, se examina la experiencia europea en la creación de un mercado único digital, y se hace una breve revisión de otros países de Centroamérica con el fin de hacer una comparación. Los principales resultados sugieren que la región se encuentra rezagada con respecto a las economías desarrolladas y a América Latina en cuanto a servicios digitales y a la economía digital. Al final del documento se proponen recomendaciones estratégicas para fomentar activamente la creación de un mercado de servicios digitales en Centroamérica.
    Date: 2020–04–21
  10. By: Tsutomu Watanabe (Graduate School of Economics, University of Tokyo. Nowcast Inc.); Yuki Omori (Nowcast Inc. M.A. candidate, Graduate School of Information Science and Technology, University of Tokyo.)
    Abstract: With the spread of coronavirus infections, there has been a growing tendency to refrain from consuming services such as eating out that involve contact with people. Self-restraint in service consumption is essential to stop the spread of infections, and the national government as well as local governments such as the Tokyo government are calling for consumers as well as firms providing such services to exercise self-restraint. One way to measure the degree of self-restraint has been to look at changes in the flow of people using smart phone location data. As a more direct approach, this note uses credit card transaction data on service spending to examine the degree to which people exercise self-restraint. The results indicate that of men aged 35-39 living in the Tokyo metropolitan area, the share that used their credit card to pay for eating out in March 2020 was 27 percent. Using transaction data for January, i.e., before the full outbreak of the virus in Japan, yields an estimated share of 32 percent for March. This means that the number of people eating out fell by 15 percent. Apart from eating out, similar self-restraint effects can be observed in various other sectors such as entertainment, travel, and accommodation. Looking at the degree of self-restraint by age shows that the self-restraint effect was relatively large among those in their late 30s to early 50s. However, below that age bracket, the younger the age group, the smaller was the self-restraint effect. Moreover, the self-restraint effect was also small among those aged 55 and above. Further, the degree of self-restraint varies depending on the type of service; it is highest with regard to entertainment, travel, and accommodation. The number of people who spent on these services in March 2020 was about half of the number during normal times. However, the 80 percent reduction demanded by the government has not been achieved.
    Date: 2020–04
  11. By: Francesco D'Acunto; Alberto G. Rossi
    Abstract: In this chapter, we first discuss the limitations of traditional financial advice, which led to the emergence of robo-advising. We then describe the main features of robo-advising and propose a taxonomy of robo-advisors based on four defining dimensions---personalization, discretion, involvement, and human interaction. Building on these premises, we delve into the theoretical and empirical evidence on the design and effects of robo-advisors on two major sets of financial decisions, that is, investment choices (for both short- or long-term horizons) and the allocation of financial resources between spending and saving. We conclude by elaborating on five broadly open issues in robo-advising, which beget theoretical and empirical research by scholars in economics, finance, psychology, law, philosophy, as well as regulators and industry practitioners.
    Keywords: FinTech, behavioral economics, algorithmic advice, A1, financial regulation, financial literacy
    JEL: D14 G21
    Date: 2020
  12. By: Borrás, Susana; Edler, Jakob
    Abstract: The transformative turn of innovation policy has resulted in calls for a more entrepreneurial and directional role of the state. However, the multiple roles that the state might play in such processes remain underexplored. This paper studies the embedded role of the state in four distinct modes of governance in socio-technical systems. Using a three-pillar analytical model, the paper examines four illustrative cases: cryptocurrencies, smart cities, automated vehicles, and nuclear power. The paper identifies 13 different roles of the state, indicating relevant variation across the four modes of governance. We discuss whether some roles of the state are more transformative than others, and provide clues for policy implications, and a future research agenda. The concept developed in the paper contributes to a more differentiated understanding of the transformative roles of the state.
    Date: 2020
  13. By: David Bounie; Youssouf Camara; John W. Galbraith
    Abstract: This paper investigates a number of general phenomena connected with consumer behaviour in response to a severe economic shock, using billions of French card transactions measured before and during the COVID-19 epidemic. We examine changes in consumer mobility, anticipatory behaviour in response to announced restrictions, and the contrasts between the responses of online and traditional point-of-sale (offline) consumption expenditures to the shock. We track hourly, daily and weekly responses as well as estimating an aggregate fixed-period impact effect via a difference in-difference estimator. The results, particularly at the sectoral level, suggest that recourse to the online shopping option diminished somewhat the overall impact of the shock on consumption expenditure, thereby increasing resiliency of the economy. Ce cahier de recherche étudie un certain nombre de phénomènes généraux liés au comportement des consommateurs en réponse à un choc économique sévère, en utilisant les milliards de transactions par carte mesurées avant et pendant l'épidémie de COVID-19. Nous examinons l'évolution de la mobilité des consommateurs, les comportements d'anticipation en réponse aux restrictions annoncées, et la différence entre les réponses au choc des dépenses de consommation en ligne et dans les points de vente traditionnels (hors ligne). Nous analysons également les réponses horaires, journalières et hebdomadaires, et estimons l’impact global à l’aide de la méthode des doubles différences. Les résultats, en particulier au niveau sectoriel, suggèrent que le recours à l’achat en ligne a en quelque sorte diminué l'impact global du choc sur les dépenses de consommation, augmentant ainsi la résilience de l'économie.
    Keywords: COVID-19,Consumption Expenditure,Consumer Mobility,Online Commerce,Resiliency,Transaction Data, COVID-19,Dépenses de consommation,Mobilité des consommateurs,Commerce en ligne,Résilience,Données de transaction
    JEL: E21 E62 E61
    Date: 2020–04–29
  14. By: Yuan Hsiao (Max Planck Institute for Demographic Research, Rostock, Germany); Lee Fiorio; Jonathan Wakefield; Emilio Zagheni (Max Planck Institute for Demographic Research, Rostock, Germany)
    Keywords: USA, computational demography, digital demography, migration, migration measurement
    JEL: J1 Z0
    Date: 2020
  15. By: Gary Biglaiser; Jacques Crémer; André Veiga
    Abstract: We study incumbency advantage in markets with positive consumption externalities. Users of an incumbent platform receive stochastic opportunities to migrate to an entrant. They can accept a migration opportunity or wait for a future opportunity. In some circumstances, users have incentives to delay migration until others have migrated. If they all do so, no migration takes place, even when migration would have been Pareto-superior. This provides an endogenous micro-foundation for incumbency advantage. We use our framework to identify environments where incumbency advantage is larger.
    Keywords: platform migration, standardization and compatibility, industry dynamics
    JEL: D85 L14 R23 L15 L16
    Date: 2020
  16. By: Laurent Bach; Remy Guichardaz; Eric Schenk
    Abstract: A travers la numérisation des contenus, des outils de production et des canaux de diffusion, les évolutions technologiques « récentes » ont entraîné une profonde remise en cause des activités d’intermédiation des acteurs dominants de l’industrie musicale. Après une réorganisation difficile de leurs ressources et de leurs compétences, ces dernières ont su redéployer leurs fonctions d’intermédiation notamment au service d’une stratégie dites « 360° ». Parmi les technologies récentes, la Blockchain est souvent présentée comme un outil de désintermédiation. En effet, la Blockchain permet à des membres d’un réseau décentralisé de stocker et partager de l’information ou d’effectuer des transactions sans qu’il ne soit nécessaire de faire intervenir le moindre organe central de contrôle. Bien qu’encore balbutiant, cette technologie a déjà été utilisée par certains acteurs de l’industrie musicale, par exemple, la chanteuse-compositrice Imogen Heap. Cet article vise à analyser l’impact de la technologie Blockchain sur les différents niveaux d’intermédiations de l’industrie musicale. Pour cela, nous mobilisons les approches théoriques de l’intermédiation telles que décrites dans Guichardaz et al. (2019) et Schenk et al. (2019). Dans le cadre d’une approche qualitative, nous avons mené une série d'entretiens semi-directifs auprès d'acteurs situés à différents niveaux d'intermédiations de l'industrie de la musique, mais aussi de spécialistes de la technologie Blockchain.
    Keywords: Blockchain, Intermédiation, Industrie musicale, Chaîne de valeur.
    JEL: L14 L82 M21
    Date: 2020
  17. By: Greitens, Jan
    Abstract: The monetary ideas of Georg Friedrich Knapp have recently resurfaced in the context of the Modern Monetary Theory whose representatives see themselves in his tradition. The historical debate on Knapp's "State Theory of Money," which divided opinion when it was first published in 1905 as well as during the period of German inflation that peaked in 1923, is therefore of particular interest. Knapp describes money largely from a legal perspective, labelling it a "creature of the legal order". The principle "Mark = Mark" reflects his nominalistic approach. However, he opposed monetary state financing, and favoured balanced governmental budgets. One of his students, Karl Helfferich, was the most influential monetary theorist in the German Reich during the first decades of the 20th century. In defining Knapp's view as an ultimate ideal that might be realised at some point, and his own metallist approach as a practical necessity, he tries to reconcile his teacher's nominalistic theory on the one hand with his own gold currency-principles on the other.The monetary theory of the Marxist Rudolf Hilferding was eclectic, but he moved closer to a nominalistic approach after studying Knapp's theory. During inflation, Helfferich, a representative of the Balance of Payments Theory, and Hilferding, more of the Quantity Theory of Money, also held opposing views in the public debate on the monetary reforms required. The relationship between the three authors was highly complex. While Helfferich and Knapp were personally close, they were far apart in their theories although Helfferich tried to conceal this fact. Hilferding and Helfferich, meanwhile, held similar views on some practical points, such as the necessity of a gold-based currency, but clashed vehemently on a personal level. (English version of: Karl Helfferich und Rudolf Hilferding über Georg Friedrich Knapps "Staatliche Theorie des Geldes": Geldtheorien zur Zeit der Hyperinflation von 1923“, IBF Paper Series 04-19, 928/)
    Keywords: Helfferich,Hilferding,Knapp,State Theory of Money,Hyperinflation,Modern Monetary Theory
    JEL: B31 E31 N14
    Date: 2020
  18. By: Theresa Kuchler; Dominic Russel; Johannes Stroebel
    Abstract: We use anonymized and aggregated data from Facebook to show that areas with stronger social ties to two early COVID-19 "hotspots" (Westchester County, NY, in the U.S. and Lodi province in Italy) generally have more confirmed COVID-19 cases as of March 30, 2020. These relationships hold after controlling for geographic distance to the hotspots as well as for the income and population density of the regions. These results suggest that data from online social networks may prove useful to epidemiologists and others hoping to forecast the spread of communicable diseases such as COVID-19.
    JEL: I0 R0
    Date: 2020–04
  19. By: Daria Dzyabura (New Economic School, Moscow, Russia); Renana Peres (Hebrew University of Jerusalem, Israel)
    Abstract: Understanding how consumers perceive brands is at the core of effective brand management. In this paper, we present the Brand Visual Elicitation Platform (B-VEP), an electronic tool we developed that allows consumers to create online collages of images that represent how they view a brand. Respondents select images for the collage from a searchable repository of tens of thousands of images. We implement an unsupervised machine-learning approach to analyze the collages and elicit the associations they describe. We demonstrate the platform’s operation by collecting large, unaided, directly elicited data for 303 large US brands from 1,851 respondents. Using machine learning and image-processing approaches to extract from these images systematic content associations, we obtain a rich set of associations for each brand. We combine the collage-making task with well-established brand-perception measures such as brand personality and brand equity, and suggest various applications for brand management.
    Keywords: Image processing, machine learning, branding, brand associations, brand collages, Latent Dirichlet Allocation
    Date: 2019–12
  20. By: Thomas Kruse (Giessen University); Philipp Strack (Cowles Foundation, Yale University)
    Abstract: We analyze how to optimally engage in social distancing (SD) in order to minimize the spread of an infectious disease. We identify conditions under which the optimal policy is single-peaked, i.e., ï¬ rst engages in increasingly more social distancing and subsequently decreases its intensity. We show that the optimal policy might delay measures that decrease the transmission rate substantially to create “herd-immunity†and that engaging in social distancing sub-optimally early can increase the number of fatalities. Finally, we ï¬ nd that optimal social distancing can be an effective measure in substantially reducing the death rate of a disease.
    Keywords: Social Distancing, SIR model, Time-Optimal Control of an Epidemic
    Date: 2020–04
  21. By: Jan Fagerberg (TIK, University of Oslo & UNU-MERIT); Bart Verspagen (UNU-MERIT)
    Abstract: Technological revolutions, i.e., clusters of technologies that collectively have a transformational impact on the global economy, are rare events that dramatically influence the opportunities facing countries at different levels of development. A central suggestion in the relevant literature is that countries that manage to adopt the new technologies associated with a specific technological revolution benefit economically from it. This is also assumed to go together with a changing specialization pattern in international trade. The paper considers the empirical merits of these suggestions, drawing on GDP and trade data for a large number of countries on different levels of development from the post-second-world-war period. The empirical analysis reveals a major divide in the global economy between a group of modern, industrialized countries, specialized in technology-based production, and another group of countries, specialized in commodities and resource-based products, and lagging behind both in terms of technology and income. More to the future, the paper also discusses the extent to which a new green technological revolution, with renewable energy as a central element, is currently emerging, and what impact this possibly might have for catching-up, structural change and economic growth for countries at different levels of development, e.g., China.
    Date: 2020–04

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