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on Network Economics |
| By: | Gallo, E.; Langtry, A. |
| Abstract: | In recent years online social networks have become increasingly prominent in political campaigns and, concurrently, several countries have experienced shock election outcomes. This paper proposes a model that links these two phenomena. In our set-up, the process of learning from others on a network is influenced by confirmation bias, i.e. the tendency to ignore contrary evidence and interpret it as consistent with one's own belief. When agents pay enough attention to themselves, confirmation bias leads to slower learning in any symmetric network, and it increases polarization in society. We identify a subset of agents that become more/less influential with confirmation bias. The socially optimal network structure depends critically on the information available to the social planner. When she cannot observe agents' beliefs, the optimal network is symmetric, vertex-transitive and has no self-loops. We explore the implications of these results for electoral outcomes and media markets. Confirmation bias increases the likelihood of shock elections, and it pushes fringe media to take a more extreme ideology. |
| Keywords: | social learning, confirmation bias, network, elections, media |
| JEL: | C63 D72 D83 D85 D91 L15 |
| Date: | 2020–11–02 |
| URL: | http://d.repec.org/n?u=RePEc:cam:camdae:2099&r=all |
| By: | Campigotto, Nicola; Rapallini, Chiara; Rustichini, Aldo |
| Abstract: | This paper investigates the determinants of school friendship networks among adolescents, proposing a model of network formation and estimating it using a sample (CILS4EU) of about 10,000 secondary school students in four countries: England, Germany, the Netherlands and Sweden. We test the idea that networks arise according to homophily along many characteristics (gender, school achievement and ethnic and cultural backgrounds), and assess the relative importance of each factor. In addition to gender, we find that country of origin, generational status and religion predict friendship for foreign-born students. For country-born individuals, ties depend on a broader set of factors, including socioeconomic status and school achievement. In sum, homophilic preferences go considerably beyond ethnicity. Multiculturalism, which gives prominence to ethnic backgrounds, risks emphasising the differences in that dimension at the expense of affinity in others. |
| Keywords: | Friendship,Homophily,Immigration,Networks,Social cohesion |
| JEL: | D85 J15 Z13 |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:glodps:695&r=all |
| By: | Julia Cagé (Sciences Po Paris, Department of Economics, 28 rue des Saints Pères, 75007 Paris, France, and CEPR (London)); Nicolas Hervé (Institut National de l'Audiovisuel, 28 avenue des Frères Lumière, 94366 Bry-sur-Marne, France); Béatrice Mazoyer (CentraleSupélec, Université Paris-Saclay, 91190 Gif-sur-Yvette, France, and Institut National de l'Audiovisuel, 28 avenue des Frères Lumière, 94366 Bry-sur-Marne, France) |
| Abstract: | Social media affects not only the way we consume news, but also the way news is produced, including by traditional media outlets. In this paper, we study the propagation of information from social media to mainstream media, and investigate whether news editors are influenced in their editorial decisions by stories popularity on social media. To do so, we build a novel dataset including a representative sample of all tweets produced in French between July 2018 and July 2019 (1.8 billion tweets, around 70% of all tweets in French during the period) and the content published online by about 200 mainstream media during the same time period, and develop novel algorithms to identify and link events on social and mainstream media. To isolate the causal impact of popularity, we rely on the structure of the Twitter network and propose a new instrument based on the interaction between measures of user centrality and news pressure at the time of the event. We show that story popularity has a positive effect on media coverage, and that this effect varies depending on media outlets’ characteristics. These findings shed a new light on our understanding of how editors decide on the coverage for stories, and question the welfare effects of social media. |
| Keywords: | Internet, Information spreading, Network analysis, Social media, Twitter, Text analysis |
| JEL: | C31 D85 L14 L15 L82 L86 |
| Date: | 2020–10 |
| URL: | http://d.repec.org/n?u=RePEc:net:wpaper:2014&r=all |
| By: | Alison Andrew (Institute for Fiscal Studies, University College London); Orazio P. Attanasio (Cowles Foundation, Yale University); Britta Augsburg (Institute for Fiscal Studies); Jere Behrman (University of Pennsylvania); Monimalika Day (Ambedkar University); Pamela Jervis (University of Chile); Costas Meghir (Cowles Foundation, Yale University); Angus Phimister (Institute for Fiscal Studies, University College London) |
| Abstract: | Social connections are fundamental to human wellbeing. This paper examines the social networks of young married women in rural Odisha, India. This is a group, for whom highly-gendered norms around marriage, mobility, and work are likely to shape opportunities to form and maintain meaningful ties with other women. We track the social networks of 2,170 mothers over four years, and ï¬ nd a high degree of isolation. Wealthier women and women more-advantaged castes have smaller social networks than their less-advantaged peers. These gradients are primarily driven by the fact that more-advantaged women are less likely to know other women within their same socioeconomic group than are less-advantaged women are. There exists strong homophily by socioeconomic status that is symmetric across socioeconomic groups. Mediation analysis shows that SES differences in social isolation are strongly associated to caste, ownership of toilets and distance. Further research should investigate the formation and role of female networks. |
| Date: | 2020–11 |
| URL: | http://d.repec.org/n?u=RePEc:cwl:cwldpp:2261&r=all |
| By: | Max H. Farrell; Tengyuan Liang; Sanjog Misra |
| Abstract: | We propose a methodology for effectively modeling individual heterogeneity using deep learning while still retaining the interpretability and economic discipline of classical models. We pair a transparent, interpretable modeling structure with rich data environments and machine learning methods to estimate heterogeneous parameters based on potentially high dimensional or complex observable characteristics. Our framework is widely-applicable, covering numerous settings of economic interest. We recover, as special cases, well-known examples such as average treatment effects and parametric components of partially linear models. However, we also seamlessly deliver new results for diverse examples such as price elasticities, willingness-to-pay, and surplus measures in choice models, average marginal and partial effects of continuous treatment variables, fractional outcome models, count data, heterogeneous production function components, and more. Deep neural networks are well-suited to structured modeling of heterogeneity: we show how the network architecture can be designed to match the global structure of the economic model, giving novel methodology for deep learning as well as, more formally, improved rates of convergence. Our results on deep learning have consequences for other structured modeling environments and applications, such as for additive models. Our inference results are based on an influence function we derive, which we show to be flexible enough to to encompass all settings with a single, unified calculation, removing any requirement for case-by-case derivations. The usefulness of the methodology in economics is shown in two empirical applications: the response of 410(k) participation rates to firm matching and the impact of prices on subscription choices for an online service. Extensions to instrumental variables and multinomial choices are shown. |
| Date: | 2020–10 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2010.14694&r=all |
| By: | Aref Ardekani (UP1 - Université Panthéon-Sorbonne, CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, UNILIM - Université de Limoges) |
| Abstract: | By applying the interbank network simulation, this paper examines whether the causal relationship between capital and liquidity is influenced by bank positions in the interbank network. While existing literature highlights the causal relationship that moves from liquidity to capital, the question of how interbank network characteristics affect this relationship remains unclear. Using a sample of commercial banks from 28 European countries, this paper suggests that banks' interconnectedness within interbank loan and deposit networks affects their decisions to set higher or lower regulatory capital rations when facing higher illiquidity. This study provides support for the need to implement minimum liquidity ratios to complement capital ratios, as stressed by the Basel Committee on Banking Regulation and Supervision. This paper also highlights the need for regulatory authorities to consider the network characteristics of banks. |
| Keywords: | Interbank network topology,Bank regulatory capital,Liquidity risk,Basel III |
| Date: | 2020–10 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:halshs-02967226&r=all |
| By: | Julian di Giovanni; Galina Hale |
| Abstract: | We quantify the role of global production linkages in explaining spillovers of U.S. monetary policy shocks to stock returns of 54 sectors in 26 countries. We first present a conceptual framework based on a standard open-economy production network model that delivers a spillover pattern consistent with a spatial autoregression (SAR) process. We then use the SAR model to decompose the overall impact of U.S. monetary policy on stock returns into a direct and a network effect. We find that up to 80% of the total impact of U.S. monetary policy shocks on average country-sector stock returns are due to the network effect of global production linkages. We further show that U.S. monetary policy shocks have a direct impact predominantly on U.S. sectors and then propagate to the rest of the world through the global production network. Our results are robust to controlling for correlates of the global financial cycle, foreign monetary policy shocks, and to changes in variable definitions and empirical specifications. |
| Keywords: | Global production network, asset prices, monetary policy shocks |
| JEL: | G15 F10 F36 |
| Date: | 2020–10 |
| URL: | http://d.repec.org/n?u=RePEc:upf:upfgen:1747&r=all |
| By: | A. D. Correia; L. L. Leestmaker; H. T. C. Stoof |
| Abstract: | We here study the Battle of the Sexes game on small networks, extending the response strategy analysis to asymmetric games and three players. We model the different steady states, that are obtained in numerical simulations from the various update strategies, as different response strategy equilibria. These are then mapped to a generalized Ising model, describing the correlations between the players' outcomes in a way that is agnostic to the existence of a link, but that coincides with the correlation device if there is one. Going to three players, we look at and compare the equilibrium solutions for three representative types of networks. We find that players that are not directly connected retain a degree of correlation that is proportional to their initial correlation. We also find that the local network structure is the most relevant for small values of the magnetic field and the interaction strength of the Ising model. This research paves the way to a statistical physics description of games on networks that is scale sensitive and has the potential to give an analytical description of both long- and short-range behavior observed in numerical simulations. |
| Date: | 2020–11 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2011.02739&r=all |
| By: | Jeffrey Brinkman; Kyle Mangum |
| Abstract: | We use a panel of county-level location data derived from cellular devices in the U.S. to track travel behavior and its relationship with COVID-19 cases in the early stages of the outbreak. We find that travel activity dropped significantly as case counts rose locally. People traveled less overall, and they specifically avoided areas with relatively larger outbreaks, independent of government restrictions on mobility. The drop in activity limited exposure to out-of-county virus cases, which we show was important because such case exposure generated new cases inside a county. This suggests the outbreak would have spread faster and to a greater degree had travel activity not dropped accordingly. Our findings imply that the scale and geographic network of travel activity and the travel response of individuals are important for understanding the spread of COVID-19 and for policies that seek to control it. |
| Keywords: | travel behavior; mobility; COVID-19 pandemic; spatial dynamics; spacial networks; cellular device location |
| JEL: | R11 I18 H11 |
| Date: | 2020–09–28 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedpwp:88960&r=all |
| By: | KAWATA Yuji; OWAN Hideo |
| Abstract: | The Elderly Employment Stabilization Law revised in 2006 helped the government to increase elderly employment. Although there has been a discussion of whether the re-employment of elderly workers substitutes or complements the employment of young workers, there are few studies that examine potential peer effects of the former group on the latter's productivity or motivation in the workplace. Note that there might be knowledge spillovers from elderly workers to peers, especially younger ones (positive peer effects) but the presence of unmotivated elderly workers might demoralize peers (negative peer effects). This paper investigates such peer effects from the exposure to elderly workers using the employee satisfaction survey of a Japanese firm. We show that elderly workers do not have significant peer effects on coworkers' satisfaction on average. However, the effects are heterogeneous depending on the ability of the elderly workers, reflected in their wages, and the age and job levels of their peers. Namely, regular workers are more satisfied when they work with elderly workers who receive higher wages. Coworkers in their 30s and 40s receive more training and those in their 50s are more satisfied when they work with elderly workers. In contrast, first line managers are less satisfied by the allocation of elderly workers, especially those with high levels of ability. This paper contributes to the discussion on the efficient assignment of elderly workers. |
| Date: | 2020–11 |
| URL: | http://d.repec.org/n?u=RePEc:eti:dpaper:20084&r=all |
| By: | Federico Crudu; Laura Neri; Silvia Tiezzi |
| Abstract: | This paper examines the impact of overweight family members on weight outcomes of Italian children aged 6 to 14 years. We use an original dataset matching the 2012 cross sections of the Italian Multipurpose Household Survey and the House hold Budget Survey. Since the identification of within-family peer effects is known to be challenging, we implement our analysis on a partially identified model using inferential procedures recently introduced in the literature and based on standard Bayesian computation methods. We find evidence of a strong, positive effect of both overweight peer children in the family and of overweight adults on children weight outcomes. The impact of overweight peer children in the household is larger than the impact of adults. In particular, the estimated confidence sets associated to the peer children variable is positive with upper bound around one or larger, while the confidence sets for the parameter associated to obese adults often include zero and have upper bound that rarely is larger than one. |
| Keywords: | child obesity; confidence sets; partial identification; peer effects within the family |
| JEL: | I12 C15 C21 C35 |
| Date: | 2020–10 |
| URL: | http://d.repec.org/n?u=RePEc:usi:wpaper:845&r=all |
| By: | Zachary Feinstein; Andreas Sojmark |
| Abstract: | In this work we provide a simple setting that connects the structural modelling approach of Gai-Kapadia interbank networks with the mean-field approach to default contagion. To accomplish this we make two key contributions. First, we propose a dynamic default contagion model with endogenous early defaults for a finite set of banks, generalising the Gai-Kapadia framework. Second, we reformulate this system as a stochastic particle system leading to a limiting mean-field problem. We study the existence of these clearing systems and, for the mean-field problem, the continuity of the system response. |
| Date: | 2020–10 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2010.15254&r=all |
| By: | Koopmans, Ruud |
| Abstract: | "Closing borders is naive, the virus will come regardless" - this was the policy assumption that was repeatedly stated until mid-March by the WHO, the EU, as well as responsible authorities in Germany and other countries. Meanwhile, other states had started closing their borders to travellers from high-risk countries or to introduce mandatory quarantines. On 17 March, the EU did what it had previously argued against, and closed its borders to travellers from outside the EU and the Schengen Area. Germany, too, changed its line, and closed its borders to France, Switzerland, and Austria and on 18 March also to travellers from Italy. Who was right? Those who initially rejected travel restrictions as useless or those countries that decided to introduce them early on? Results from a global analysis of travel restrictions and cross-national differences in mortality rates as a result of the COVID-19 pandemic suggest that the belief that the spread of the virus could not be significantly slowed down by entry restrictions was fatally mistaken. The paper also shows that exposure of a country to international travel, as indicated by centrality in air travel networks and tourist numbers is strongly associated with higher COVID-19 mortality rates. By contrast, island states, which have lower exposure to international travel because of their lack of land borders, have much lower mortality. The results are robust across a wide variety of model specifications and controls, including domestic COVID-19 containment measures. The findings have important policy implications and suggest that in containing upcoming waves of the COVID-19 pandemic as well as similar pandemics in the future, the risks of exposure to international travel and the advantages of early travel restrictions should be given much greater weight. Among various types of travel restrictions, the findings suggest prioritizing targeted restrictions over global ones, and mandatory quarantines for travellers over entry bans. |
| Keywords: | Covid-19 pandemic,diffusion,social networks,international travel,World Health Organization (WHO),Covid-19-Pandemie,Diffusion,soziale Netzwerke,internationale Reisen,Weltgesundheitsorganisation (WHO) |
| JEL: | I18 D85 L93 |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:wzbmit:spvi2020103&r=all |
| By: | Bjørn Bo Sørensen; Christian Estmann; Enilde Francisco Sarmento; John Rand |
| Abstract: | Mozambique is among the world's least complex economies. By systematically accounting for both supply- and demand-side factors, we identify new products and sectors that can help to diversify and upgrade its economy. In a supply-side analysis, we use network methods from the literature on economic complexity to identify a set of target products that are complex, require productive capabilities useful in the export of other products, and are close to Mozambique's existing productive structure. |
| Keywords: | economic complexity, Trade, Exports, Structural transformation, Mozambique |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:unu:wpaper:wp-2020-141&r=all |
| By: | Jan Motl; Pavel Kord\'ik |
| Abstract: | This article is concerned with the cost and time effective scheduling of financial auditors with Integer Linear Programming. The schedule optimization takes into account 13 different constraints, staff scarcity, frequent alterations of the input data with the need to minimize the changes in the generated schedule, and scaling issues. We compared two exact formulations of the problem and we found a multi-commodity network flow formulation to be 24 times faster than a three-dimensional formulation. The delivered implementation reduced time to the first schedule from 3 man-days to 1 hour and the schedule update time from 1 man-day to 4 minutes. |
| Date: | 2020–11 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2011.02776&r=all |
| By: | Zhipu Zhou; Alexander Shkolnik; Sang-Yun Oh |
| Abstract: | Factor modeling of asset returns has been a dominant practice in investment science since the introduction of the Capital Asset Pricing Model (CAPM) and the Arbitrage Pricing Theory (APT). The factors, which account for the systematic risk, are either specified or interpreted to be exogenous. They explain a significant portion of the risk in large portfolios. We propose a framework that asks how much of the risk, that we see in equity markets, may be explained by the asset returns themselves. To answer this question, we decompose the asset returns into an endogenous component and the remainder, and analyze the properties of the resulting risk decomposition. Statistical methods to estimate this decomposition from data are provided along with empirical tests. Our results point to the possibility that most of the risk in equity markets may be explained by a sparse network of interacting assets (or their issuing firms). This sparse network can give the appearance of a set exogenous factors where, in fact, there may be none. We illustrate our results with several case studies. |
| Date: | 2020–10 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2010.13245&r=all |