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on Network Economics |
| By: | Comola, Margherita (Paris School of Economics); Inguaggiato, Carla (University of Bern); Mendola, Mariapia (University of Milan Bicocca) |
| Abstract: | We study the role of social learning in the diffusion of cash crops in a resettled village economy in northeastern Brazil. We combine detailed geo-coded data on farming plots with dyadic data on social ties among settlers, and we leverage natural exogenous variation in network formation induced by the land occupation movement and the agrarian reform. By using longitudinal data on farming decisions over 15 years we find consistent evidence of significant peer effects in the decision to farm new cash fruits (pineapple and passion fruit). Our results suggest that social diffusion is heterogeneous along observed plot and crop characteristics, i.e. farmers growing water-sensitive crop are more likely to respond to the actions of peers with similar water access conditions. |
| Keywords: | technology adoption, agrarian reform, social networks, peer effects, Brazil |
| JEL: | C45 D85 J15 O33 Q15 |
| Date: | 2021–02 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp14092&r=all |
| By: | Schauf, Andrew; Oh, Poong |
| Abstract: | When individuals extract benefits from multiple resources, the decision they face is twofold: besides choosing how much total effort to exert for extraction, they must also decide how to allocate this effort. We focus on the allocation aspect of this choice in an iterated game played on bipartite networks of agents and common-pool resources (CPRs) that degrade linearly in quality as extraction increases. When CPR users attempt to reallocate their extraction efforts among resources to maximize their own payoffs in the very next round (that is, myopically), collective wealth is increased. Using a heterogeneous mean-field approach, we estimate how these reallocations affect the payoffs of CPR users of different degrees within networks having different levels of degree heterogeneity. Focusing specifically on Nash equilibrium initial conditions, which represent the patterns of over-exploitation that result from rational extraction, we find that networks with greater heterogeneity among CPR degrees show greater improvements over equilibrium due to reallocation. When the marginal utility of extraction diminishes, these reallocations also reduce wealth inequality. These findings emphasize that CPR users’ adaptive reallocations of effort—a behavior that previously-studied network evolutionary game models typically disallow by construction—can serve to direct individuals’ self interest toward the collective good. |
| Date: | 2021–01–12 |
| URL: | http://d.repec.org/n?u=RePEc:osf:socarx:w2cxp&r=all |
| By: | Mohammad Akbarpour (Stanford University - Stanford Graduate School of Business); Cody Cook (Stanford University - Stanford Graduate School of Business); Aude Marzuoli (Replica); Simon Mongey (University of Chicago - Department of Economics; NBER); Abhishek Nagaraj (University of California, Berkeley - Haas School of Business); Matteo Saccarola (University of Chicago - Department of Economics); Pietro Tebaldi (University of Chicago - Department of Economics; NBER); Shoshana Vasserman (Stanford University - Stanford Graduate School of Business); Hanbin Yang (Harvard University - Harvard Business School) |
| Abstract: | We develop a heterogeneous-agents network-based model to analyze alternative policies during a pandemic outbreak, accounting for health and economic trade-offs within the same empirical framework. We leverage a variety of data sources, including data on individuals’ mobility and encounters across metropolitan areas, health records, and measures of the possibility to be productively working from home. This combination of data sources allows us to build a framework in which the severity of a disease outbreak varies across locations and industries, and across individuals who differ by age, occupation, and preexisting health conditions. We use this framework to analyze the impact of different social distancing policies in the context of the COVID-19 outbreaks across US metropolitan areas. Our results highlight how outcomes vary across areas in relation to the underlying heterogeneity in population density, social network structures, population health, and employment characteristics. We find that policies by which individuals who can work from home continue to do so, or in which schools and firms alternate schedules across different groups of students and employees, can be effective in limiting the health and healthcare costs of the pandemic outbreak while also reducing employment losses. |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:bfi:wpaper:2020-75&r=all |
| By: | Becker, Sascha O. (Monash University); Lindenthal, Volker (University of Munich); Mukand, Sharun (University of Warwick); Waldinger, Fabian (University of Munich) |
| Abstract: | We study the role of professional networks in facilitating the escape of persecuted academics from Nazi Germany. From 1933, the Nazi regime started to dismiss academics of Jewish origin from their positions. The timing of dismissals created individual-level exogenous variation in the timing of emigration from Nazi Germany, allowing us to estimate the causal effect of networks for emigration decisions. Academics with ties to more colleagues who had emigrated in 1933 or 1934 (early émigrés) were more likely to emigrate. The early émigrés functioned as "bridging nodes" that helped other academics cross over to their destination. Furthermore, we provide some of the first empirical evidence of decay in social ties over time. The strength of ties also decays across space, even within cities. Finally, for high-skilled migrants, professional networks are more important than community networks. |
| Keywords: | Nazi Germany, professional networks, Antisemitism |
| JEL: | I20 I23 I28 J15 J24 N34 |
| Date: | 2021–02 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp14120&r=all |
| By: | Farid Naufal Aslam; Andry Alamsyah |
| Abstract: | The internet's rapid growth stimulates the emergence of start-up companies based on information technology and telecommunication (ICT) in Indonesia and Singapore. As the number of start-ups and its investor growth, the network of its relationship become larger and complex, but on the other side feel small. Everyone in the ICT start-up investment network can be reached in short steps, led to a phenomenon called small-world phenomenon, a principle that we are all connected by a short chain of relationships. We investigate the pattern of the relationship between a start-up with its investor and the small world characteristics using network analysis methodology. The research is conducted by creating the ICT start-up investment network model of each country and calculate its small-world network properties to see the characteristic of the networks. Then we compare and analyze the result of each network model. The result of this research is to give knowledge about the current condition of ICT start-up investment in Indonesia and Singapore. The research is beneficial for business intelligence purposes to support decision-making related to ICT start-up investment. |
| Date: | 2021–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2102.09102&r=all |
| By: | Marcello Esposito |
| Abstract: | Among the statistical techniques used to describe the behaviour of the financial markets, one of the most promising is based on the network analysis of the stock market. In this framework, the stock market is represented as a graph with nodes (the single stocks), edges (connections between stocks), and attributes (industry classification, volumes ...). The application of network analysis to the stock market is not new, but in previous contributions the market graph has been mainly derived from the correlationmatrix of the stock prices. This is a limitation, and the risks are to express in different words what traditional financial econometrics has already said about the returns’ distribution. Moreover, if we want to use network analysis not only as a descriptive tool but also as an inference instrument, we need other data than the correlation matrix itself. For this reason, we integrated the analysis and built the market graph with new type of data taken from the observation of the information gathering activity performed by retail investors through the Google’s search engine. We focussed the attention on financial crises, when a shock hits the economy in such a profound way that almost all the parameters entering the pricing equation of stocks must be reassessed. Those periods are relatively rare and short. They are characterised by extremely high levels of volatility and correlation. In these moments, searching for new information becomes of paramount importance. And then it is in these moments that we expect to observe more neatly the working of the underlying network. |
| Date: | 2021–02 |
| URL: | http://d.repec.org/n?u=RePEc:liu:liucec:2021-10&r=all |