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on Network Economics |
| By: | Biavaschi, Costanza; Giulietti, Corrado; Zenou, Yves |
| Abstract: | This paper investigates the causal pathways through which ethnic social networks influence individual naturalization. Using the complete-count Census of 1930, we digitize information on the exact residence of newly arrived immigrants in New York City. This allows us to define networks with a granularity detail that was not used before for historical data - the Census block - and therefore to overcome issues of spatial sorting. By matching individual observations with the complete-count Census of 1940, we estimate the impact that the exogenous fraction of naturalized co-ethnics in the network observed in 1930 has on the probability of immigrants to acquire citizenship a decade later. Our results indicate that the concentration of naturalized co-ethnics in the network positively affects individual naturalization and that this relationship operates through one main channel: information dissemination. Indeed, immigrants who live among naturalized co-ethnics are more likely to naturalize because they have greater access to critical information about the benefits and procedures of naturalization. |
| Keywords: | Social networks,assimilation,naturalization,migration |
| JEL: | J61 J62 N32 Z1 |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:glodps:1049&r= |
| By: | Michael Bailey (Facebook); Drew Johnston (Harvard University); Theresa Kuchler (New York University); Johannes Stroebel (New York University); Arlene Wong (Princeton University) |
| Abstract: | We use de-identified data from Facebook to study the nature of peer effects in the market for cell phones. To identify peer effects, we exploit variation in friends’ new phone acquisitions resulting from random phone losses. A new phone purchase by a friend has a large and persistent effect on an individual’s own demand for phones of the same brand. While peer effects increase the overall demand for phones, a friend’s purchase of a particular phone brand can reduce an individual’s own demand for phones from competing brands, in particular if they are running on a different operating system. |
| Keywords: | Peer Effects, Demand Spillovers, Social Learning |
| JEL: | L1 L2 M3 D4 |
| Date: | 2021–01 |
| URL: | http://d.repec.org/n?u=RePEc:pri:econom:2021-66&r= |
| By: | Ready, Elspeth; Power, Eleanor |
| Abstract: | Reciprocity - the mutual provisioning of support/goods - is a pervasive feature of social life. Directed networks provide a way to examine the structure of reciprocity in a community. However, measuring social networks involves assumptions about what relationships matter and how to elicit them, which may impact observed reciprocity. In particular, the practice of aggregating multiple sources of data on the same relationship (e.g., double-sampled data, where both the giver and receiver are asked to report on their relationship) may have pronounced impacts on network structure. To investigate these issues, we examine concordance (ties reported by both parties) and reciprocity in a set of directed, double-sampled social support networks. We find low concordance in people's responses. Taking either the union (including any reported ties) or the intersection (including only concordant ties) of double-sampled relationships results in dramatically higher levels of reciprocity. Using multilevel exponential random graph models of social support networks from 75 villages in India, we show that these changes cannot be fully explained by the increase in the number of ties produced by layer aggregation. Respondents' tendency to name the same people as both givers and receivers of support plays an important role, but this tendency varies across contexts and relationships type. We argue that no single method should necessarily be seen as the correct choice for aggregation of multiple sources of data on a single relationship type. Methods of aggregation should depend on the research question, the context, and the relationship in question. |
| Keywords: | social networks; reciprocity; concordance; double sampling; informant accuracy; PLR-1303874; IBSS-143019; 752-2010-1089 |
| JEL: | C1 |
| Date: | 2021–12–12 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:112513&r= |
| By: | Beck, Ben; Pettit, Christopher; Winters, Meghan; Nelson, Trisalyn; Vu, Hai; Nice, Kerry A; Seneviratne, Sachith; Saberi, Meead |
| Abstract: | Background: Numerous studies have explored associations between bicycle network characteristics and bicycle ridership. However, the majority of these studies have been conducted in inner metropolitan regions and as such, there is limited knowledge on how various characteristics of bicycle networks relate to bicycle trips within and across entire metropolitan regions, and how the size and composition of study regions impact on the association between bicycle network characteristics and bicycle ridership. Methods: We conducted a retrospective analysis of household travel survey data and bicycle infrastructure in the Greater Melbourne region, Australia. Seven network metrics were calculated and Bayesian spatial models were used to explore the association between these network characteristics and bicycle ridership (measured as counts of the number of trips, and the proportion of all trips that were made by bike). Results: We demonstrated that bicycle ridership was associated with several network characteristics, and that these characteristics varied according to the outcome (count of the number of trips made by bike or the proportion of trips made by bike) and the size and characteristics of the study region. Conclusions: These findings challenge the utility of approaches based on spatially modelling network characteristics and bicycle ridership when informing the monitoring and evaluation of bicycle networks. There is a need to progress the science of measuring safe and connected bicycle networks for people of all ages and abilities. |
| Date: | 2021–11–19 |
| URL: | http://d.repec.org/n?u=RePEc:osf:osfxxx:39ke6&r= |
| By: | Poledna, Sebastian; Martínez-Jaramillo, Serafín; Caccioli, Fabio; Thurner, Stefan |
| Abstract: | Financial markets create endogenous systemic risk, the risk that a substantial fraction of the system ceases to function and collapses. Systemic risk can propagate through different mechanisms and channels of contagion. One important form of financial contagion arises from indirect interconnections between financial institutions mediated by financial markets. This indirect interconnection occurs when financial institutions invest in common assets and is referred to as overlapping portfolios. In this work we quantify systemic risk from indirect interconnections between financial institutions. Complete information of security holdings of major Mexican financial intermediaries and the ability to uniquely identify securities in their portfolios, allows us to represent the Mexican financial system as a bipartite network of securities and financial institutions. This makes it possible to quantify systemic risk arising from overlapping portfolios. We show that focusing only on direct interbank exposures underestimates total systemic risk levels by up to 50% under the assumptions of the model. By representing the financial system as a multi-layer network of direct interbank exposures (default contagion) and indirect external exposures (overlapping portfolios) we estimate the mutual influence of different channels of contagion. The method presented here is the first quantification of systemic risk on national scales that includes overlapping portfolios. |
| Keywords: | financial networks; financial regulation; multi-layer networks; overlapping portfolios; systemic risk |
| JEL: | D85 G18 G21 |
| Date: | 2021–02 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:113734&r= |
| By: | Pablo D. Fajgelbaum (Princeton University); Amit Khandelwal (Columbia University); Wookun Kim (Southern Methodist University); Cristiano Mantovani (Universitat Pompeu Fabra); Edouard Schaal (CREI, ICREA, UPF, BGSE and CEPR) |
| Abstract: | We study optimal dynamic lockdowns against Covid-19 within a commuting network. Our framework integrates canonical spatial epidemiology and trade models, and is applied to cities with varying initial viral spread: Seoul, Daegu and NYC-Metro. Spatial lockdowns achieve substantially smaller income losses than uniform lockdowns. In NYM and Daegu—with large initial shocks—the optimal lockdown restricts inflows to central districts before gradual relaxation, while in Seoul it imposes low temporal but large spatial variation. Actual commuting reductions were too weak in central locations in Daegu and NYM, and too strong across Seoul. |
| Keywords: | COVID-19, pandemics, South Korea, United States, commuting, lockdown |
| JEL: | R38 R4 C6 |
| Date: | 2020–11 |
| URL: | http://d.repec.org/n?u=RePEc:pri:econom:2020-36&r= |
| By: | Aigner, Ernest |
| Abstract: | The structure of academic economics has received a fair amount of attention within and beyond the discipline. Less focus has been given the interdependencies of country and global dynamics. Building and advancing this tradition, this explorative study examines geographic variation and country specific developments in research practices in academic economics. More specifically I investigate the interdependencies of global dynamics with country-level developments in the US, Germany, UK, France, Switzerland and Austria. To that purpose the study investigates a large-scale data set using inequality measures and social network analysis. The dataset analysed in this study comprises 453,863 articles published in 477 journals citing each other a total of 3,807,289 times. This exploratory study confirms the high level of concentration and finds similar trends on the country level. Further, an international convergence in the discipline can be observed, possibly limiting the place-specific relevance of knowledge created in academic economics. |
| Keywords: | economic sociology, academic economics, citation analysis, heterodox economics, concentration, geography of economics |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:wiw:wus009:8161&r= |