nep-pay New Economics Papers
on Payment Systems and Financial Technology
Issue of 2019‒12‒09
twenty papers chosen by

  1. Using Facebook Ad Data to Track the Global Digital Gender Gap By Fatehkia, Masoomali; Kashyap, Ridhi; Weber, Ingmar
  2. Master Thesis: Evaluasi Aplikasi E-Commerce Menggunakan Extended Web Assessment Method (EWAM) dari Perspektif Konsumen: Studi Kasus Toko Buku Online di Indonesia By Susilo, Andi
  3. Redeemable Platform Currencies By Yang You; Kenneth S. Rogoff
  4. Quantifying Endogeneity of Cryptocurrency Markets By Michael Mark; Jan Sila; Thomas A. Weber
  5. The Global Platform Economy: A New Offshoring Institution Enabling Emerging-Economy Microproviders By Lehdonvirta, Vili; Kässi, Otto; Hjorth, Isis; Barnard, Helena; Graham, Mark
  6. Online Shoppers Acceptance An Exploratory Study By Siahaan, Andysah Putera Utama; Nasution, Muhammad Dharma Tuah Putra
  7. Digitisation in forest industry in Bulgaria - state and perspectives By Georgieva, Daniela; Popova, Radostina
  8. An Integrated Approach to the Evaluation of E-Service Quality in Airline Companies [Havayolu İşletmeleri̇nde E-Hi̇zmet Kali̇tesi̇ni̇n Değerlendi̇ri̇lmesi̇ne Yöneli̇k Bütünleşik Bir Yaklaşım] By Bakır, Mahmut
  9. The complexity of the intangible digital economy: an agent-based model By Bertani, Filippo; Ponta, Linda; Raberto, Marco; Teglio, Andrea; Cincotti, Silvano
  10. Analysing the social network of technology and information transfer for maize sheller service providers in Zimbabwe By Chikutuma, Mutsvandiani
  11. Detecting anomalous payments networks: A dimensionality reduction approach By Carlos León
  12. The Phenomenon of Cyber-Crime and Fraud Victimization in Online Shop By Siahaan, Andysah Putera Utama; Nasution, Muhammad Dharma Tuah Putra
  13. On the Disclosure of Promotion Value in Platforms with Learning Sellers By Yonatan Gur; Gregory Macnamara; Daniela Saban
  14. JChain: A new way to look inside the firm By Cervellera, Gian Piero; Amabile, Francesco; Napolitano, Alessio; Parenti, Daniele; Mauro, Kenneth; Lazzi, Francesca
  15. Is there within-outlet demand for media slant? Evidence from US presidential campaign news By Stone, Daniel; sood, Gaurav; Garz, Marcel; Wallace, Justin
  16. Do Digital Skill Certificates Help New Workers Enter the Market? Evidence from an Online Labour Platform By Kässi, Otto; Lehdonvirta, Vili
  17. Intangible Capital and Labour Productivity Growth: A Review of the Literature By Roth, Felix
  18. Towards Quantification of Explainability in Explainable Artificial Intelligence Methods By Sheikh Rabiul Islam; William Eberle; Sheikh K. Ghafoor
  19. Exports and imports in Zimbabwe: recent insights from artificial neural networks By NYONI, THABANI
  20. AI and Robotics Implications for the Poor By von Braun, Joachim

  1. By: Fatehkia, Masoomali; Kashyap, Ridhi; Weber, Ingmar
    Abstract: Gender equality in access to the internet and mobile phones has become increasingly recognised as a development goal. Monitoring progress towards this goal however is challenging due to the limited availability of gender-disaggregated data, particularly in low-income countries. In this data sparse context, we examine the potential of a source of digital trace `big data' -- Facebook's advertisement audience estimates -- that provides aggregate data on Facebook users by demographic characteristics covering the platform's over 2 billion users to measure and `nowcast' digital gender gaps. We generate a unique country-level dataset combining `online' indicators of Facebook users by gender, age and device type, `offline' indicators related to a country's overall development and gender gaps, and official data on gender gaps in internet and mobile access where available. Using this dataset, we predict internet and mobile phone gender gaps from official data using online indicators, as well as online and offline indicators. We find that the online Facebook gender gap indicators are highly correlated with official statistics on internet and mobile phone gender gaps. For internet gender gaps, models using Facebook data do better than those using offline indicators alone. Models combining online and offline variables however have the highest predictive power. Our approach demonstrates the feasibility of using Facebook data for real-time tracking of digital gender gaps. It enables us to improve geographical coverage for an important development indicator, with the biggest gains made for low-income countries for which existing data are most limited.
    Date: 2018–03–06
  2. By: Susilo, Andi (Universitas Respati Indonesia)
    Abstract: In Internet world, many sites featured fancy graphics, well organized content, but they did not really mean that a site induced the visitor to come back on a regular basis. Thus many companies and institutions discovered with surprise that even comparatively large budgets allocated to the development of their Web sites did not always guarantee success. An often quoted possible reason, why potential customers turn their screens rather off than meddle their way through a purchase order, is a Web sites’ low level of consumer focus. There must be a vital interest for online sellers to design their Web sites according to their (potential) customer's needs. The Extended Web Assessment Method (EWAM) represents an instrument for making general statements on the quality of a commercial Web site from a consumer perspective. EWAM is an evaluation tool specifically created for the assessment of electronic commerce applications. EWAM builds on the Web Assessment Method developed at University of St. Gallen, Switzerland by Petra Schubert and Dorian Selz. It mainly integrates findings from Davis’s TAM and Fishbein & Ajzein’ TRA. EWAM the method is based on an evaluation grid that includes a set of criteria with which to appraise the quality and success of ecommerce applications. The focus is on consumer perspectives and the specific features of the Internet as a medium. In this study, researcher used the EWAM tool that built with Google Apps Web Based Application for evaluation of e-shops whose main business is selling books. Four Web sites have been selected in Indonesia and one Web site as De Facto Standard. The findings show that most of the Web sites in Indonesia assessed do not fully meet the expectations of consumers. Four Web sites have overall scores below +1 (<+1, score +1 means “good”) from range (-2/+2). The following overall score for each Web site result: (0.31) as The Worst Practice Profile, (0.35), (0.67), and (0.73) as The Best Practice Profile
    Date: 2018–05–19
  3. By: Yang You; Kenneth S. Rogoff
    Abstract: Can massive online retailers such as Amazon and Alibaba issue digital tokens that potentially compete with bank debit accounts? We explore whether a large platform’s ability to guarantee value and liquidity by issuing prototype digital tokens for in-platform purchases constitutes a significant advantage that could potentially be leveraged into wider use. Our central finding is that unless introducing tradability creates a significant convenience yield, platforms can potentially earn higher revenues by making tokens non-tradable. The analysis suggests that if platforms have any comparative advantage in issuing tradable tokens, it comes from other factors.
    JEL: E42 G23 L51
    Date: 2019–11
  4. By: Michael Mark (Chair of Operations, Economics and Strategy, Ecole Polytechnique Federale de Lausanne, Station 5, CH-1015 Lausanne, Switzerland); Jan Sila (Institute of Economic Studies, Faculty of Social Sciences, Charles University, Opletalova 26, 110 00, Prague, Czech Republic); Thomas A. Weber (Chair of Operations, Economics and Strategy, Ecole Polytechnique Federale de Lausanne, Station 5, CH-1015 Lausanne, Switzerland)
    Abstract: In this paper we construct a "reflexivity" index for Bitcoin crypto currency that measures the amount of activity generated endogenously within the market. For this purpose we fit a univariate self-exciting Hawkes process with two-classes of parametric kernels to high-frequency trade data that allows for a parsimonious representation of endogenous-exogenous dynamics.
    Keywords: Hawkes process, endogeneity, branching ratio, maximum-likelihood estimation, cryptocurrencies, bitcoin
    JEL: G14 G15 C58
    Date: 2019–10
  5. By: Lehdonvirta, Vili; Kässi, Otto; Hjorth, Isis; Barnard, Helena; Graham, Mark
    Abstract: Global online platforms match firms with service providers around the world, in services ranging from software development to copywriting and graphic design. Unlike in traditional offshore outsourcing, service providers are predominantly one-person microproviders located in emerging-economy countries not necessarily associated with offshoring and often disadvantaged by negative country images. How do these microproviders survive and thrive? We theorize global platforms through transaction cost economics (TCE), arguing that they are a new technology-enabled offshoring institution that emerges in response to cross-border information asymmetries that hitherto prevented microproviders from participating in offshoring markets. To explain how platforms achieve this, we adapt signaling theory to a TCE-based model and test our hypotheses by analyzing 6 months of transaction records from a leading platform. To help interpret the results and generalize them beyond a single platform, we introduce supplementary data from 107 face-to-face interviews with microproviders in Southeast Asia and Sub-Saharan Africa. Individuals choose microprovidership when it provides a better return on their skills and labor than employment at a local (offshoring) firm. The platform acts as a signaling environment that allows microproviders to inform foreign clients of their quality, with platform-generated signals being the most informative signaling type. Platform signaling disproportionately benefits emerging-economy providers, allowing them to partly overcome the effects of negative country images and thus diminishing the importance of home country institutions. Global platforms in other factor and product markets likely promote cross-border microbusiness through similar mechanisms.
    Date: 2018–08–22
  6. By: Siahaan, Andysah Putera Utama (Universitas Pembangunan Panca Budi); Nasution, Muhammad Dharma Tuah Putra
    Abstract: Consumers are increasingly easy to access to information resources. Consumers quickly interact with whatever they will spend. Ease of use of technology an impact on consumer an attitude are increasingly intelligent and has encouraged the rise of digital transactions. Technology makes it easy for them to transact on an e-commerce shopping channel. Future e-commerce trends will lead to User Generated Content related to user behavior in Indonesia that tends to compare between shopping channels. The purpose of this study was to examine the direct and indirect effects of Perceived Ease of Use on Behavioral Intention to transact in which Perceived Usefulness is used as an intervening variable. The present study used the descriptive exploratory method with causal-predictive analysis. Determination method of research sample used purposive sampling. The enumerator team assists in the distribution of questionnaires. The results of the study found that the direct effect of perceived ease of use on behavioral intention to transact is smaller than that indirectly mediated by perceived usefulness variables.
    Date: 2018–06–29
  7. By: Georgieva, Daniela; Popova, Radostina
    Abstract: A main objective of the paper is to present the state, current trends and challenges in front of the enterprises in Bulgarian Forest sector, based on the introduction of digital tools and solutions in business and economy as a whole. A subject of analyses is the degree of digitisation of forest sector enterprises based on the implementation and use of online-based applications and electronic catalogs; specialized information and communication management systems and networks; office and warehouse management software. The indicators under analysis are divided into the following groups - "connectivity and digital skills"; "internal processes" and "relationship with customers, suppliers and third parties". In order to achieve comparability of the results, the selected indicators are the same as those officially used by Eurostat. For the purposes of the analysis, secondary and primary data are used as well as publications in the specialized literature, legislation framework and analyzes of statistical data from national and international databases. The paper presents primary results from in-depth interviews with management representatives from large forest industry enterprises, according to the requirements of the Bulgarian Accountancy Act (AA). Good digital practices in the furniture manufacturers are also presented, and some opportunities for development of the Forest industry entities are suggested.
    Keywords: digitisation; Forest sector; Forest industry; in-depth interviews; large enterprises
    JEL: Q00 Q16
    Date: 2019–02
  8. By: Bakır, Mahmut
    Abstract: Nowadays, as a result of technological developments, information technology has deeply affected the activities of many sectors and has begun to support these sectors as a marketing tool. The air transport sector is undoubtedly one of these sectors. It is known that ticket sales are largely carried out over the internet in the air transport industry where passengers are basically transported from one place to another. In this point as well as in other services, the concept of quality (e-service) also stands out as an important competition tool in the services offered over the internet. As a matter of fact, e-service quality affects customer satisfaction and loyalty positively, which is decisive on the success of airline companies. In this context, it is aimed to determine the importance levels of the factors affecting the quality of e-services offered in the air transport sector by using integrated methods in the study and to rank the national airline companies according to their e-service quality performances. For this purpose, firstly, the factors affecting the quality of e-service were obtained as a result of the literature survey. A hierarchical model was established with the elements obtained and the importance of the factors affecting the quality of e-service as a result of expert opinions were determined using the Analytical Hierarchy Process (AHP). In the next phase of the study, the data obtained as a result of the questionnaire applied to 395 passengers at International Antalya Airport were analyzed using the ARAS method and ranked according to the performances of airlines. According to the results obtained; it has been determined that the most important factor that has an effect on e-service quality is reliability and Atlasglobal has the highest e-service quality performance.
    Date: 2018–03–31
  9. By: Bertani, Filippo; Ponta, Linda; Raberto, Marco; Teglio, Andrea; Cincotti, Silvano
    Abstract: During the last decades, we have witnessed a strong development of intangible digital technologies. Software, artificial intelligence and algorithms are increasingly affecting both production systems and our lives; economists have started to figure out the long-run complex economic implications of this new technological wave. In this paper, we address this question through the agent-based modelling approach. In particular, we enrich the macroeconomic model Eurace with the concept of intangible digital technology and investigate its effects both at the micro and macro level. Results show the emergence of the relevant stylized facts observed in the business domain, such as increasing returns, winner-take-most phenomena and market lock-in. At the macro level, our main finding is an increasing unemployment level, since the sizeable decrease of the employment rate in the mass-production system, provided by the higher productivity of digital assets, is usually not counterbalanced by the new jobs created in the digital sector.
    Keywords: Intangible assets, Digital transformation, Technological unemployment, Agent-based economics
    JEL: C63 D24 O33
    Date: 2019–11–21
  10. By: Chikutuma, Mutsvandiani
    Abstract: Smallholder farmers and their households in Zimbabwe depend on maize as a staple food and source of income. despite the high demand for maize production, there is little service provision particularly shelling on post-harvest technologies. Therefore, service providers for maize shelling are suggested to have a strong social network with customers and other service providers for demand creation. The aim of the project was to understand the business approaches of the service providers and their performances, using SNA to track the use of shellers for service provision and the associated information network in Domboshava and Makonde districts, Zimbabwe. SNA through interviews were used to assess the demand for shelling through customer and non-customer characteristics, to identify demand creation approaches and to analyze how the communication network differs between service providers. There was a variation in total earnings on average Makonde service providers with more earnings than in Domboshava. Service providers obtained the customers based on trust from the community. Total earnings increased with increasing number of customers (p<0.001), higher degree centrality and shelling capacity for both districts. Network density was higher in Domboshava than in Makonde district indicating more frequent contacts in Domboshava. Despite the earnings, most of the service providers operated below full capacity due to the low maize production caused by drought and the late availability of shelling services to the farmers. The service providers that achieved higher turnovers, tended to have shelling machines with higher capacities compared to those operating with small shelling capacities. Service providers started their business in 2016 season and little promotion had been made amongst farmers for shellers’ awareness campaign. There is more urgent need for promotion and business development and upgrading of shelling capacities to boost business performance. Identification of central actors such as the agricultural extension officers is vital in the social network for dissemination of information for high uptake of services.
    Date: 2019–11–16
  11. By: Carlos León (Banco de la República de Colombia)
    Abstract: Anomaly detection methods aim at identifying observations that deviate manifestly from what is expected. Such methods are usually run on low dimensional data, such as time series. However, the increasing importance of high dimensional payments and exposures data for financial oversight requires methods able to detect anomalous networks. To detect an anomalous network, dimensionality reduction allows measuring to what extent its main connective features (i.e. the structure) deviate from those regarded as typical or expected. The key to such measure resides in the ability of dimensionality reduction methods to reconstruct data with an error; this reconstruction error serves as a yardstick for deviation from what is expected. Principal component analysis (PCA) is used as dimensionality reduction method, and a clustering algorithm is used to classify reconstruction errors into normal and anomalous. Based on data from Colombia’s large-value payments system and a set of synthetic anomalous networks created by means of intraday payments simulations, results suggest that detecting anomalous payments networks is feasible and promising for financial oversight purposes. **** RESUMEN: Los métodos para detección de anomalías buscan identificar observaciones que se desvían ostensiblemente de lo esperado. Esos métodos suelen utilizarse con datos de baja dimensionalidad, tales como las series de tiempo. Sin embargo, la creciente importancia de las series de redes de pagos y exposiciones –series de alta dimensionalidad- en el seguimiento de los mercados financieros exige métodos aptos para detectar redes anómalas. Para detectar una red anómala, la reducción de dimensiones permite cuantificar qué tan diferentes son las características conectivas de una red (i.e. su estructura) con respecto a aquellas que pueden ser consideradas como normales. Esto se consigue gracias a que la reducción de dimensiones permite reconstruir los datos con un error; ese error sirve de parámetro para determinar qué tan diferentes son las características conectivas de las redes. La descomposición por componentes principales es utilizada como método para reducir dimensionalidad, y un algoritmo de agrupamiento clasifica los errores de reconstrucción en normales o anómalos. Con base en datos del sistema de pagos de alto valor colombiano y un conjunto de redes de pagos anómalas creadas artificialmente a partir de métodos de simulación de pagos intradía, los resultados sugieren que la detección de redes de pagos anómalas es posible y prometedor para propósitos de seguimiento de los mercados financieros.
    Keywords: Anomaly, payments, network, dimensionality, clustering, anomalías, pagos, redes, dimensionalidad, agrupamiento
    JEL: E42 C38 C53
    Date: 2019–12
  12. By: Siahaan, Andysah Putera Utama (Universitas Pembangunan Panca Budi); Nasution, Muhammad Dharma Tuah Putra
    Abstract: Simple negligence can be a fatal impact. The threat of cyber in 2017 is feeble, and it starts from “wanna cry” until “nopetya” that the impact is relatively weak. The public also feels the threat of cybercrime even in many countries who have become the target of cyber-war, the society became the most disadvantaged. Cybercrimes have an impact on the National Security, financial loss and consumer confidence. Therefore, in the middle of the more high dependency, man will use information technology, cybersecurity must be the primary priority for a state. The Indonesian people still believe that only the information is available on the internet. Even though the information may unnecessarily is accurate. The results of a survey conducted by the CIGI Ipsos in 2016 released in 2017 shows that 65 percent of Indonesia receives the information is available on the internet without filtering the first.
    Date: 2018–06–29
  13. By: Yonatan Gur; Gregory Macnamara; Daniela Saban
    Abstract: We consider a platform facilitating trade between sellers and buyers with the objective of maximizing consumer surplus. In many such platforms prices are set by revenue-maximizing sellers, but the platform may influence prices through its promotion policy (e.g., increasing demand to a certain product by assigning to it a prominent position on the webpage), and the information it reveals about the additional demand associated with being promoted. Identifying effective joint information design and promotion policies for the platform is a challenging dynamic problem as sellers can sequentially learn the promotion "value" from sales observations and update prices accordingly. We introduce the notion of confounding promotion polices, which are designed to prevent a Bayesian seller from learning the promotion value (at the cost of diverting consumers away from the best product offering). Leveraging this notion, we characterize the maximum long-run average consumer surplus that is achievable by the platform when the seller is myopic. We then establish that long-run average optimality can be maintained by optimizing over a class of joint information design and promotion policies under which the platform provides the seller with a (random) information signal at the beginning of the horizon, and then uses the best confounding promotion policy, which prevents the seller from further learning. Additionally, we show that myopic pricing is a best response to such a platform strategy, thereby establishing an approximate Bayesian Nash equilibrium between the platform and the seller. Our analysis allows one to identify practical long-run average optimal platform policies in a broad range of demand models and evaluate the impact of the search environment and the design of promotions on consumer surplus.
    Date: 2019–11
  14. By: Cervellera, Gian Piero; Amabile, Francesco; Napolitano, Alessio; Parenti, Daniele; Mauro, Kenneth; Lazzi, Francesca
    Abstract: JChain takes advantage of the blockchain mechanism to measure all activities into the firm. The idea is that to create a large database where all activities are masured and recorded by means of a Eurocoin-based-payment system.
    Date: 2017–11–16
  15. By: Stone, Daniel; sood, Gaurav; Garz, Marcel; Wallace, Justin
    Abstract: Variation in political slant across media outlets, and demand for such slant, has been studied extensively. We conduct a novel within-outlet (and within-topic) analysis of the demand for ``congenially'' slanted news. We study so-called horse race news from six major online outlets for the 2012 and 2016 US presidential campaigns. We find very limited evidence of higher demand for more congenial stories, and somewhat stronger evidence of higher demand for more \emph{uncongenial} stories. However, we also find that, as expected, news is slanted congenially across outlets, counter-acting (and perhaps causing) any within-outlet preference for uncongenial slant. We discuss how our results are consistent with the three major mechanisms driving demand for slant studied in the theoretical literature, and enhance understanding of when each mechanism is more likely to come into play.
    Date: 2018–10–16
  16. By: Kässi, Otto; Lehdonvirta, Vili
    Abstract: We study the effects of a voluntary skill certification scheme in an online freelancing labour market. We show that obtaining skill certificates increases a worker’s earnings. This effect is not driven by increased worker productivity but by decreased employer uncertainty. The increase in worker earnings is mostly realised through an increase in the value of the projects obtained (up to 10%) rather than an increase in the number of projects obtained (up to 0.03 projects). In addition, we find evidence for negative selection to completing skill certificates, which suggests that the workers who complete more skill certificates are, on average, in a more disadvantaged position in the labour market. Finally, skill certificates are found to be an imperfect substitute to other types of standardised information. On the whole, the results suggest that certificates play a role in helping new workers break into the labour market, but are more valuable to workers with at least some work experience. More stringent skill certification tests could improve the benefits to new workers.
    Date: 2018–11–14
  17. By: Roth, Felix
    Abstract: This paper surveys a wide range of studies on the impact of capital investment in intangible assets on labour productivity growth and highlights their main findings on. Surveying the literature at the country, industry and firm level, this paper finds evidence of the increasing importance of business investment in intangible assets in explaining the dynamics of labour productivity growth. Moreover, the findings reported in the literature surveyed suggest that in order to fully reap the benefits of investment in information and communication technology (ICT) and artificial intelligence (AI), it is essential for businesses to make complementary investment in intangible assets. In addition, the literature on the drivers of business capital investment in intangibles highlights the importance of having in place a well-endowed infrastructure of public intangibles. Judging from the wide range of economic literature surveyed, this paper finds that the contemporary economic debate now broadly acknowledges the importance of intangibles for the transformation of developed economies towards becoming fully-fledged knowledge economies.
    Keywords: Intangible Capital,Labour Productivity Growth,Total Factor Productivity Growth,Information and Communication Technology,Artificial Intelligence,European Union
    Date: 2019
  18. By: Sheikh Rabiul Islam; William Eberle; Sheikh K. Ghafoor
    Abstract: Artificial Intelligence (AI) has become an integral part of domains such as security, finance, healthcare, medicine, and criminal justice. Explaining the decisions of AI systems in human terms is a key challenge--due to the high complexity of the model, as well as the potential implications on human interests, rights, and lives . While Explainable AI is an emerging field of research, there is no consensus on the definition, quantification, and formalization of explainability. In fact, the quantification of explainability is an open challenge. In our previous work, we incorporated domain knowledge for better explainability, however, we were unable to quantify the extent of explainability. In this work, we (1) briefly analyze the definitions of explainability from the perspective of different disciplines (e.g., psychology, social science), properties of explanation, explanation methods, and human-friendly explanations; and (2) propose and formulate an approach to quantify the extent of explainability. Our experimental result suggests a reasonable and model-agnostic way to quantify explainability
    Date: 2019–11
    Abstract: This study, which is the first of its kind in the case of Zimbabwe; attempts to model and forecast Zimbabwe’s exports and imports using annual time series data ranging over the period 1975 – 2017. In order to analyze Zimbabwe’s export and import dynamics, the study employed the Neural Network approach, a deep-learning technique which has not been applied in this area in the case of Zimbabwe. The Hyperbolic Tangent function was selected and applied as the activation function of the neural networks applied in this study. The neural networks applied in this research were evaluated using the most common forecast evaluation statistics, i.e. the Error, MSE and MAE; and it was clearly shown that the neural networks yielded reliable forecasts of Zimbabwe’s exports and imports over the period 2018 – 2027. The main results of the study indicate that imports will continue to outperform exports over the out-of-sample period. Amongst other policy recommendations, the study encourages Zimbabwean policy makers to intensify export growth promotion policies and strategies such as clearly identifying export drivers as well as export diversification if persistant current account deficits in Zimbabwe are to be dealt with effectively.
    Keywords: ANNs; exports; forecast; hyperbolic tangent function; imports; trade deficits; Zimbabwe
    JEL: F13 P33 Q17
    Date: 2019–11–04
  20. By: von Braun, Joachim
    Abstract: Artificial intelligence and robotics (AI/R) have the potential to result in great change of livelihoods. While individual impacts of AI/R on, for instance, employment, have been subject to a lot of research, how AI/R may affect the poor is scarce. This paper aims to draw attention to how AI/R may impact the poor and marginalized and highlights research needs. A thought experiment compares the future situation of the poor in an AI/R scenario to a scenario without AI/R. A framework is established that depicts poverty and marginality conditions of health, education, public services, work, small businesses including farming as well as voice and empowerment of the poor. This conceptual framework identifies points of entry of AI/R, and is complemented by a more detailed discussion of the way in which changes through AI/R in these areas may relate positively or adversely to the livelihood of the poor. This paper concludes that empirical scenarios and modelling analyses are needed to better understand the different components in the emerging technological and institutional AI/R innovations and identify how they will shape the livelihoods of poor households and communities.
    Keywords: Agribusiness, Financial Economics, Health Economics and Policy, Labor and Human Capital, Research and Development/Tech Change/Emerging Technologies, Teaching/Communication/Extension/Profession
    Date: 2019–12–03

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