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on Network Economics |
| By: | Holtz, David; Zhao, Michael; Benzell, Seth G.; Cao, Cathy Y.; Rahimian, M. Amin; Yang, Jeremy; Allen, Jennifer Nancy Lee; Collis, Avinash; Moehring, Alex Vernon; Sowrirajan, Tara |
| Abstract: | Social distancing is the core policy response to COVID-19. But as federal, state and local governments begin opening businesses and relaxing shelter-in-place orders worldwide, we lack quantitative evidence on how policies in one region affect mobility and social distancing in other regions and the consequences of uncoordinated regional policies adopted in the presence of such spillovers. We therefore combined daily, county-level data on shelter-in-place and business closure policies with movement data from over 27 million mobile devices, social network connections among over 220 million of Facebook users, daily temperature and precipitation data from 62,000 weather stations and county-level census data on population demographics to estimate the geographic and social network spillovers created by regional policies across the United States. Our analysis showed the contact patterns of people in a given region are significantly influenced by the policies and behaviors of people in other, sometimes distant, regions. When just one third of a state’s social and geographic peer states adopt shelter in place policies, it creates a reduction in mobility equal to the state’s own policy decisions. These spillovers are mediated by peer travel and distancing behaviors in those states. A simple analytical model calibrated with our empirical estimates demonstrated that the “loss from anarchy” in uncoordinated state policies is increasing in the number of non cooperating states and the size of social and geographic spillovers. These results suggest a substantial cost of uncoordinated government responses to COVID-19 when people, ideas, and media move across borders. |
| Date: | 2020–05–20 |
| URL: | http://d.repec.org/n?u=RePEc:osf:osfxxx:b9psy&r=all |
| By: | Maria Cecilia Bustamante (University of Maryland - Department of Finance); Laurent Frésard (University of Lugano; Swiss Finance Institute) |
| Abstract: | We study whether, how, and why the investment of a firm depends on the investment of other firms in the same product market. Using an instrumental variable based on the presence of local knowledge externalities, we find a sizeable complementarity of investment among product market peers, holding across a large majority of sectors. Peer effects are stronger in concentrated markets, featuring more heterogeneous firms, and for smaller firms with less precise information. Our findings are consistent with a model in which managers are imperfectly informed about fundamentals and use peers' investments as a source of information. Product market peer effects in investment could amplify shocks in production networks. |
| Keywords: | investment, peer effect, competition, agglomeration economies |
| JEL: | G31 |
| Date: | 2020–05 |
| URL: | http://d.repec.org/n?u=RePEc:chf:rpseri:rp2043&r=all |
| By: | Jacopo Bonan; Pietro Battiston; Jaimie Bleck; Philippe LeMay-Boucher; Stefano Pareglio; Bassirou Sarr; Massimo Tavoni |
| Abstract: | Easy-to-use and risk-free technologies, which require little investment and potentially provide health and environmental benefits, often have low adoption rates. Using a randomized experiment in urban Mali, we assess the impact of a training session in which information on an improved cookstove (ICS) is provided along with the opportunity to purchase the product at the market price. We find direct and spillover effects from our invitation to the session on ICS ownership and usage. We then randomly assign half of the training participants to receive information on a peer's actual purchase. Our results indicate that conditional on receiving information, an individual is more likely to adopt the product if informed about a peer they know and who purchased the product. Our sessions have no discernible impact on product knowledge or household welfare. We argue that social interaction, through imitation, can represent an important channel for increasing take-up and diffusion. |
| Keywords: | Technology Adoption, Social Interaction, Imitation Effects, Cookstoves, Mali |
| JEL: | D91 O33 O13 M31 |
| Date: | 2020–05 |
| URL: | http://d.repec.org/n?u=RePEc:mib:wpaper:442&r=all |
| By: | Junyi Li; Xitong Wang; Yaoyang Lin; Arunesh Sinha; Micheal P. Wellman |
| Abstract: | We propose an approach to generate realistic and high-fidelity stock market data based on generative adversarial networks (GANs). Our Stock-GAN model employs a conditional Wasserstein GAN to capture history dependence of orders. The generator design includes specially crafted aspects including components that approximate the market's auction mechanism, augmenting the order history with order-book constructions to improve the generation task. We perform an ablation study to verify the usefulness of aspects of our network structure. We provide a mathematical characterization of distribution learned by the generator. We also propose statistics to measure the quality of generated orders. We test our approach with synthetic and actual market data, compare to many baseline generative models, and find the generated data to be close to real data. |
| Date: | 2020–06 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2006.04212&r=all |
| By: | Daron Acemoglu; Asuman Ozdaglar; James Siderius; Alireza Tahbaz-Salehi |
| Abstract: | This paper develops a network model of interbank lending, in which banks decide to extend credit to their potential borrowers. Borrowers are subject to shocks that may force them to default on their loans. In contrast to much of the previous literature on financial networks, we focus on how anticipation of future defaults may result in ex ante “credit freezes,” whereby banks refuse to extend credit to one another. We first characterize the terms of the interbank contracts and the patterns of interbank lending that emerge in equilibrium. We then study how shifts in the distribution of shocks can result in complex credit freezes that travel throughout the network. We use this framework to analyze the effects of various policy interventions on systemic credit freezes. |
| JEL: | D85 G01 |
| Date: | 2020–05 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:27149&r=all |
| By: | Baumöhl, Eduard; Bouri, Elie; Hoang, Thi-Hong-Van; Shahzad, Syed Jawad Hussain; Výrost,Tomáš |
| Abstract: | Over the last few decades, large banks worldwide have become more interconnected, and as a result, the failure of one can trigger the failure of many. In finance, this phenomenon is often known as financial contagion, which can occur as a domino effect. In this paper, we show an unprecedented increase in bank interconnectedness during the outburst of the COVID-19 pandemic. We measure how extreme negative stock market returns for one bank spill over to all other banks within the network, and on this basis, we propose a new measure of systemic risk among banks. Our results indicate that the systemic risk and the density of the spillover network have never been as high as they have been during the pandemic, not even during the 2008 global financial crisis. Policy makers and regulatory authorities should be particularly cautious regarding this interconnected financial environment, as second waves of the pandemic could pose a significant danger to the worldwide economy, and the “it’s-just-a-flu” narrative will no longer be an option. |
| Keywords: | systemic risk,banks,COVID-19,pandemic,cross-quantilogram,financial networks,interconnectedness |
| JEL: | G01 G15 G21 G28 C21 |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:esprep:218944&r=all |
| By: | Fernando DePaolis; Phil Murphy; M. Clara DePaolis Kaluza |
| Abstract: | By applying network analysis techniques to large input-output system, we identify key sectors in the local/regional economy. We overcome the limitations of traditional measures of centrality by using random-walk based measures, as an extension of Blochl et al. (2011). These are more appropriate to analyze very dense networks, i.e. those in which most nodes are connected to all other nodes. These measures also allow for the presence of recursive ties (loops), since these are common in economic systems (depending to the level of aggregation, most firms buy from and sell to other firms in the same industrial sector). The centrality measures we present are well suited for capturing sectoral effects missing from the usual output and employment multipliers. We also develop an R package (xtranat) for the processing of data from IMPLAN(R) models and for computing the newly developed measures. |
| Date: | 2020–05 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2005.11285&r=all |
| By: | Bobby Chung (University of Illinois at Urbana-Champaign); Jian Zou (University of Illinois at Urbana-Champaign) |
| Abstract: | We utilize random assignment of students into classrooms in China middle schools to study the mechanisms behind the spillover of peer parental education on student achievement. Analyzing the China Education Panel Survey, we find a causal relationship between classmates' maternal education and student test score. In addition to the conventional peer effect and teacher response channel, we identify mother adjustment of parenting style as another important mediating factor. We provide suggestive evidence about the existence of mother's network, which facilitates the change in parenting style. We also find that the spillover of peer maternal education on non-repeaters and non-migrant students is stronger, primarily driven by higher parental investment on time. |
| Keywords: | peer effects, peers' parents, parental investments, parenting style |
| JEL: | D91 I24 J13 Z13 |
| Date: | 2020–06 |
| URL: | http://d.repec.org/n?u=RePEc:hka:wpaper:2020-045&r=all |
| By: | Giorgio Fabbri (Univ.Grenoble Alpes, CNRS, INRIA, Grenoble INP, GAEL, Grenoble, France); Silvia Faggian (Department of Economics, University Of Venice Ca’ Foscari, Italy); Giuseppe Freni (Department of Business and Economics, University of Naples “Parthenope”, Naples, Italy.) |
| Abstract: | We study the dynamics of the exploitation of a natural resource, distributed in space and mobile, where spatial diversification is introduced by a network structure. Players are assigned to different nodes by a regulator, after he/she decides at which nodes natural reserves are established. The game solution shows how the dynamics of spatial distribution depends on the productivity of the various sites, on the structure of the connections between the various locations, and on the preferences of the agents. At the same time, the best locations to host a nature reserve are identified in terms of the parameters of the model, and it turns out they correspond to the most central (in the sense of eigenvector centrality) nodes of a suitably redefined network which takes into account the nodes productivities. |
| Keywords: | Harvesting, spatial models, differential games, nature reserve |
| JEL: | Q20 Q28 R11 C73 |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:ven:wpaper:2020:07&r=all |
| By: | Konstantinos Angelopoulos; Spyridon Lazarakis; James Malley |
| Abstract: | We develop a theoretical framework where the cross-sectional distributions of hours, earnings, wealth and consumption are determined jointly with a set of expenditure targets defining peer and aspirational pressure for members of different social classes. We show existence of a stationary socio-economic equilibrium, under idiosyncratic stochastic productivity and socio-economic class participation. We calibrate a model belonging to this framework using British data and find that it captures the main patterns of inequality, between and within the social groupings. We find that the effects of peer pressure on within group inequality differ between groups. We also find that wealth and consumption inequality increase within groups who aspire to match social targets from a higher class, despite a reduction in within-group inequality in hours and earnings. |
| Keywords: | inequality, incomplete markets, peer pressure, aspirations |
| JEL: | E21 E25 D01 D31 |
| Date: | 2019–09 |
| URL: | http://d.repec.org/n?u=RePEc:gla:glaewp:2019_06&r=all |
| By: | Jozef Barunik; Michael Ellington |
| Abstract: | This paper examines the pricing of dynamic horizon specific network risk in the cross-section of stock returns. We suggest how to track such dynamic network connections on a daily basis using time-varying parameter vector auto-regressions. Empirically, we characterize the short-term and long-term risks from a large-scale dynamic network on all S&P500 constituents' return volatilities. Consistent with theory, we show that stocks with high sensitivities to dynamic network risk earn lower returns. A two-standard deviation increase in long-term (short-term) network risk loadings associate with a 14.73% (12.96%) drop in annualized expected returns. |
| Date: | 2020–06 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2006.04639&r=all |
| By: | de Soyres, Francois; Gaillard, Alexandre |
| Abstract: | We revisit the association between trade and GDP comovement for 135 countries from 1970 to 2009. Guided by a simple theory, we introduce two notions of trade linkages: (i) the usual direct bilateral trade index and (ii) new indexes of common exposure to third countries capturing the role of similarity in trade networks. Both measures are economically and statistically associated with GDP correlation, suggesting an additional channel through which GDP fluctuations propagate through trade linkages. Moreover, high income countries become more synchronized when the content of their trade is tilted toward inputs while trade in final goods is key for low income countries. Finally, we present evidence that the density of the international trade network is associated with an amplification of the association between global trade flows and bilateral GDP comovement, leading to a significant evolution of the trade comovement slope over the last two decades. |
| Keywords: | International Trade, International Business Cycle Comovement, Networks, Input-Output Linkages. |
| JEL: | F15 F4 F44 F62 |
| Date: | 2020–01–30 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:100518&r=all |
| By: | Antoine Devulder; Noëmie Lisack |
| Abstract: | We analyse the propagation of carbon taxation through input-output production networks. To do so, we use a static multi-sector general equilibrium model including France, the rest of the European Union and the rest of the world to simulate the impact of carbon tax scenarios on economic activity. We find that a tax increase on sectors' and households' greenhouse gas emissions corresponding to a carbon price of 100 euros per ton of carbon dioxide equivalent entails a decrease in French aggregate real value added by 1.2% at a 5-to10-year horizon when implemented in France only, vs. 1.5% when implemented in the whole EU. Impacts on sectoral real value added range from -20% to negligible. The most affected sectors are generally the most polluting ones, but the tax also propagates across sectors via intermediate inputs. Specifically, the network structure tends to affect comparatively more upstream sectors than downstream ones, given their taxation levels. International financial markets also play an important role by neutralizing the positive response of final demand that would result from the redistribution of the tax proceeds to domestic households. |
| Keywords: | Carbon tax, multi-sector model, international production networks. |
| JEL: | D57 F11 H23 |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:bfr:banfra:760&r=all |
| By: | Maximilian Gobel; Tanya Araújo |
| Abstract: | The determination of reliable early-warning indicators of economic crises is a hot topic in economic sciences. Pinning down recurring patterns or combinations of macroeconomic indicators is indispensable for adequate policy adjustments to prevent a looming crisis. We investigate the ability of several macroeconomic variables telling crisis countries apart from non-crisis economies. We introduce a selfcalibrated clustering-algorithm, which accounts for both similarity and dissimilarity in macroeconomic fundamentals across countries. Furthermore, imposing a desired community structure, we allow the data to decide by itself, which combination of indicators would have most accurately foreseen the exogeneously de?ned network topology. We quantitatively evaluate the degree of matching between the data-generated clustering and the desired community-structure. |
| Keywords: | Early-Warning Models, Crisis Prediction, Macroeconomic Dynamics, Network Analysis, Community Structure, Great Recession, Clustering Algorithm |
| JEL: | C38 G01 C52 |
| Date: | 2020–05 |
| URL: | http://d.repec.org/n?u=RePEc:ise:remwps:wp01282020&r=all |
| By: | Elie Bouri (Holy Spirit University of Kaslik (USEK), USEK Business School, Jounieh, Lebanon); Oguzhan Cepni (Central Bank of the Republic of Turkey, Ankara, Turkey); David Gabauer (Software Competence Center Hagenberg, Data Analysis Systems, Softwarepark 21, 4232 Hagenberg, Austria); Rangan Gupta (Department of Economics, University of Pretoria, Pretoria, 0002, South Africa) |
| Abstract: | In this paper, we show evidence of a dramatic change in the structure and time-varying patterns of return connectedness across various assets (gold, crude oil, world equities, currencies, and bonds) around the COVID-19 outbreak. Using the TVP-VAR connectedness approach, the results show that the dynamic total connectedness across the five assets was moderate and quite stable until early 2020. After that, the total connectedness spikes and the structure of the network of connectedness alters, which concurs with the COVID-19 outbreak. The equity and USD indices are the primary transmitters of shocks before the outbreak, whereas the bond index becomes the main transmitters of shocks during the COVID-19 outbreak. However, the USD index is a net receiver of shocks to other assets during the outbreak period. Furthermore, using a recently developed newspaper-based index of uncertainty in financial markets due to infectious diseases to capture the recent impact of Covid-19, we find that connectedness is positively related to this index, and increases at higher levels (conditional quantiles) of connectedness. Overall, our results reflect the speedy disturbing effects of the COVID-19 outbreak, which matters to the formulations of policies seeking to achieve financial stability. The results also indicate a possibility to threaten investors’ portfolios and fade the benefits of diversification. |
| Keywords: | COVID-19 outbreak; financial markets contagion; return connectedness; TVP-VAR |
| JEL: | C32 C5 F3 G15 |
| Date: | 2020–05 |
| URL: | http://d.repec.org/n?u=RePEc:pre:wpaper:202047&r=all |
| By: | Riccardo Doyle |
| Abstract: | Interbank contagion can theoretically exacerbate losses in a financial system and lead to additional cascade defaults during downturn. In this paper we produce default analysis using both regression and neural network models to verify whether interbank contagion offers any predictive explanatory power on default events. We predict defaults of U.S. domiciled commercial banks in the first quarter of 2010 using data from the preceding four quarters. A number of established predictors (such as Tier 1 Capital Ratio and Return on Equity) are included alongside contagion to gauge if the latter adds significance. Based on this methodology, we conclude that interbank contagion is extremely explanatory in default prediction, often outperforming more established metrics, in both regression and neural network models. These findings have sizeable implications for the future use of interbank contagion as a variable of interest for stress testing, bank issued bond valuation and wider bank default prediction. |
| Date: | 2020–05 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2005.12619&r=all |
| By: | Bailey, Michael; Gupta, Abhinav; Hillenbrand, Sebastian; Kuchler, Theresa; Richmond, Robert; Ströbel, Johannes |
| Abstract: | We use anonymized data from Facebook to construct a new measure of the pairwise social connectedness between 180 countries and 332 European regions. We find that two countries trade more with each other when they are more socially connected and when they share social connections with a similar set of other countries. The social connections that determine trade in each product are those between the regions where the product is produced in the exporting country and those where it is used in the importing country. Once we control for social connectedness, the estimated effect of geographic distance on trade declines substantially, and the effect of country borders disappears. Our findings suggest that social connectedness increases trade by reducing information asymmetries and by providing a substitute for both trust and formal mechanisms of contract enforcement. We also present evidence against omitted variables and reverse causality as alternative explanations for the observed relationships between social connectedness and trade flows. |
| Keywords: | Contract enforcement; Information Frictions; international trade; Social Connectedness |
| JEL: | F1 F5 F6 |
| Date: | 2020–04 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:14624&r=all |