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on Network Economics |
| By: | Luca Colombo (Deakin University, Burwood, Australia - Deakin University [Burwood]); Paola Labrecciosa (Monash Business School); Agnieszka Rusinowska (CNRS - Centre National de la Recherche Scientifique, CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics - ENPC - École des Ponts ParisTech - ENS Paris - École normale supérieure - Paris - PSL - Université Paris sciences et lettres - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique - EHESS - École des hautes études en sciences sociales - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement) |
| Abstract: | The paper presents a novel approach based on di¤erential games to the study of criminal networks. We extend the static crime network game (Ballester et al., 2004, 2006) to a dynamic setting. First, we determine the relationship between the Markov Perfect Equilibrium (MPE) and the vector of Bonacich centralities. The established proportionality between the Nash equilibrium and the Bonacich centrality in the static game does not hold in general in the dynamic setting. Next, focusing on regular networks, we provide an explicit characterization of equilibrium strategies, and conduct comparative dynamic analysis with respect to the network size, network density, and implicit growth rate of total wealth in the economy. Contrary to the static game, where aggregate equilibrium increases with network size and density, in the dynamic setting, more criminals or more connected criminals can lead to a decrease in total crime, both in the short run and at the steady state. We also examine another novel issue in the network theory literature, i.e., the existence of a voracity e¤ect, occurring when an increase in the implicit growth rate of total wealth in the economy lowers economic growth. We do identify the presence of such a voracity e¤ect in our setting. |
| Keywords: | differential games,Markov Perfect Equilibrium,social networks,criminal networks,Bonacich centrality |
| Date: | 2022–02–28 |
| URL: | http://d.repec.org/n?u=RePEc:hal:cesptp:halshs-03601580&r= |
| By: | David de la Croix; Pauline Morault (Université de Cergy-Pontoise, THEMA) |
| Abstract: | Using a new database of European academics,we provide a global view of the eect of the Protestant Reformation on the network of universities and on their individual importance within the network (centrality). A connection (edge) between two universities (nodes) is dened by the presence of the same scholar in both universities. Protestantism strongly impacted the structure of the network. Dyadic regressions conrm that geography was important as well, but does not substitute for the eect of religion. We isolate the eect of religion on each university centrality comparing simulated networks with and without religious identity. The reorganization of the network induced by the Reformation harmed Protestant universities less than Catholics. As the number of publications per university is strongly correlated with centrality, our simulations lend credence to the view that the loss of connectedness of the Southern European universities after the (Counter-)Reformation was important in triggering their scientic demise. |
| Keywords: | Upper-Tail Human Capital, Universities, Network, Centrality, Publications, Fragmentation. |
| JEL: | N33 O15 I25 |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:ema:worpap:2022-11&r= |
| By: | Tanya Araújo; R. Vilela Mendes |
| Abstract: | Long range connections play an essential role in dynamical processes on networks, on the processing of information in biological networks, on the structure of social and economical networks and in the propagation of opinions and epidemics. Here we review the evidence for long range connections in real world networks and discuss the nature of the nonlo- cal diffusion arising from different distance-dependent laws. Particular attention is devoted to exponential and power laws. |
| Date: | 2022–03 |
| URL: | http://d.repec.org/n?u=RePEc:ise:remwps:wp02212022&r= |
| By: | Matej Belin; Tomas Jelinek; Stepan Jurajda |
| Abstract: | Survivor testimonies link survival in deadly POW camps, Gulags, and Nazi concentration camps to the formation of close friendships with other prisoners. We provide statistical evidence consistent with these fundamentally selective testimonies. We study the survival of the 140 thousand Jews who entered the Theresienstadt ghetto, where 33 thousand died and from where over 80 thousand were sent to extermination camps. We ask whether an individual’s social status prior to deportation, and the availability of potential friends among fellow prisoners influenced the risk of death in Theresienstadt, the ability to avoid transports to the camps, and the chances of surviving Auschwitz. Pre-deportation social status protected prisoners in the self-administered society of the Theresienstadt ghetto, but it was no longer helpful in the extreme conditions of the Auschwitz-Birkenau concentration camp. Relying on multiple proxies of pre-existing social networks, we uncover a significant survival advantage to entering Auschwitz with a group of potential friends. |
| Keywords: | social status; social networks; Holocaust survival; Nazi concentration camp; ghetto; Theresienstadt/Terezín; Auschwitz-Birkenau; |
| Date: | 2022–03 |
| URL: | http://d.repec.org/n?u=RePEc:cer:papers:wp720&r= |
| By: | Martin Mugnier |
| Abstract: | Novel estimators are proposed for linear grouped fixed effects models. Rather than predicting a single grouping of units, they deliver a collection of groupings with the same flavor as the so-called LASSO regularization path. Mild conditions are found that ensure their asymptotic guarantees are the same as the so-called grouped fixed effects and post-spectral estimators (Bonhomme and Manresa, 2015; Chetverikov and Manresa, 2021). In contrast, the new estimators are computationally straightforward and do not require prior knowledge of the number of groups. Monte Carlo simulations suggest good finite sample performance. Applying the approach to real data provides new insights on the potential network structure of the unobserved heterogeneity. |
| Date: | 2022–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2203.08879&r= |
| By: | Péter Csóka (Department of Finance, Corvinus University of Budapest and Centre for Economic and Regional Studies); P. Jean-Jacques Herings (Department of Econometrics and Operations Research, Tilburg University) |
| Abstract: | We consider financial networks where agents are linked to each other with financial contracts. A centralized clearing mechanism collects the initial endowments, the liabilities and the division rules of the agents and determines the payments to be made. A division rule specifies how the assets of the agents should be rationed, the four most common ones being the proportional, the priority, the constrained equal awards, and the constrained equal losses division rules. Since payments made depend on payments received, we are looking for solutions to a system of equations. The set of solutions is known to have a lattice structure, leading to the existence of a least and a greatest clearing payment matrix. Previous research has shown how decentralized clearing selects the least clearing payment matrix. We present a centralized approach towards clearing in order to select the greatest clearing payment matrix. To do so, we formulate the determination of the greatest clearing payment matrix as a programming problem. When agents use proportional division rules, this programming problem corresponds to a linear programming problem. We show that for the other common division rules, it can be written as an integer linear programming problem. |
| Keywords: | Financial networks, systemic risk, bankruptcy rules, clearing, integer linear programming |
| JEL: | C71 G10 |
| Date: | 2022–03 |
| URL: | http://d.repec.org/n?u=RePEc:has:discpr:2208&r= |
| By: | Pircalabelu, Eugen (Université catholique de Louvain, LIDAM/ISBA, Belgium) |
| Abstract: | A method for balancing the within/between group similarity is proposed in the frameworkof estimating graphs when data from multiple groups or classes are available. The method leverages connections between the Karush-Kuhn-Tucker (KKT) conditions for estimating ℓ1 penalized graphs in order to define an optimization problem that can be solved with already existing, known algorithms from the literature. The method is illustrated on an fMRI dataset and with a simulated, controlled experiment. Statistical guarantees are as well provided. |
| Keywords: | Within/between group similarity ; Penalized graphical models ; Differential networks |
| Date: | 2022–02–01 |
| URL: | http://d.repec.org/n?u=RePEc:aiz:louvad:2022007&r= |