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on Network Economics |
| By: | Yann Bramoullé (AMSE - Aix-Marseille Sciences Economiques - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique, Académie d'Aix-Marseille, CNRS - Centre National de la Recherche Scientifique); Garance Genicot (Department of Economics, Georgetown University) |
| Abstract: | This paper studies the dynamics of information diffusion within networks, encompassing both general and targeted dissemination. We first characterize the theoretical foundations of diffusion centrality. Next, we introduce two extensions of diffusion centrality: targeting centrality and reachability, that we believe to better capture situations involving targeted requests. We derive general explicit formulas for the computation of these novel centrality measures. |
| Keywords: | Diffusion, Centrality, Political intermediation, Targeting |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-04718273 |
| By: | Raúl Duarte; Frederico Finan; Horacio Larreguy; Laura Schechter |
| Abstract: | Politicians rely on political brokers to buy votes throughout much of the developing world. We investigate how social networks facilitate these vote-buying exchanges. Our conceptual framework suggests brokers should be particularly well-placed within the network to learn about non-copartisans’ reciprocity in order to target transfers effectively. As a result, parties should recruit brokers who are central among non-copartisans. We combine village network data from brokers and citizens with broker reports of vote buying, allowing us to use broker and citizen fixed effects. We show that networks diffuse information about citizens to brokers who leverage it to target transfers. In particular, among those citizens who are not registered to their party, brokers target reciprocal citizens about whom they can learn more through their network, and these citizens are more likely to support the brokers’ party. Moreover, recruited brokers are significantly more central than other citizens among non-copartisans, but not among copartisans. These results highlight the importance of information diffusion through social networks for vote buying, broker recruitment, and ultimately for political outcomes. |
| Keywords: | vote buying, brokers, social networks |
| JEL: | D72 O12 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_11349 |
| By: | Giorgio Fabbri (Univ. Grenoble Alpes, CNRS, INRA, Grenoble INP, GAEL, 38000 Grenoble, France); Silvia Faggian (Department of Economics, Ca’ Foscari University of Venice, Italy); Giuseppe Freni (Department of Business and Economics, Parthenope University of Naples, Italy) |
| Abstract: | This study examines the dynamics of capital stocks distributed among several nodes, representing different sites of production and connected via a weighted, directed network. The network represents the externalities or spillovers that the production in each node generates on the capital stock of other nodes. A regulator decides to designate some of the nodes for the production of a consumption good to maximize a cumulative utility from consumption. It is demonstrated how the optimal strategies and stocks depend on the productivity of the resource sites and the structure of the connections between the sites. The best locations to host production of the consumption good are identified per the model’s parameters and correspond to the least central (in the sense of eigenvector centrality) nodes of a suitably redefined network that combines both flows between nodes and the nodes’ productivity. |
| Keywords: | Capital allocation, Production externalities, Network spillovers, Economic centrality measures |
| JEL: | C61 D62 O41 R12 |
| Date: | 2024–11–05 |
| URL: | https://d.repec.org/n?u=RePEc:ctl:louvir:2024011 |
| By: | Rhys Murrian (Department of Economics and SoDa Labs, Monash University); Paul A. Raschky (Department of Economics and SoDa Labs, Monash University); Klaus Ackermann (Department of Econometrics and Business Statistics and SoDa Labs, Monash University) |
| Abstract: | This paper empirically investigates how an individual’s network influences their purchase and subsequent use of experience goods. Utilising data on the network and game-ownership of over 108 million users from the world’s largest video game platform, we analyse whether a user’s friendship network influences their decision to purchase single-player video games. Our identification strategy uses an instrumental variable (IV) approach that employs the temporal lag of purchasing decisions from second degree friends. We find strong peer effects in the individual game adoption in the contemporary week. The effect is stronger if the friend who purchased the game is an old friend compared to a key player in the friendship network. Comparing the results to adoption decisions for a major label game, we find peer effects of a similar size and duration. However, the time subsequently spent playing the games is higher for players who were neither influenced by a peer who is a key player nor an old friend. Considering the increasing importance of online networks on consumption decisions, our findings offer some first insights on the heterogeneity of peer effects between old and key player friends and also provide evidence in consumers’ biases in social learning. |
| Keywords: | networks, experience goods, product adoption, taste projection |
| JEL: | D12 Z13 |
| Date: | 2024–10 |
| URL: | https://d.repec.org/n?u=RePEc:mos:moswps:2024-17 |
| By: | Elisa Grugni; Giorgio Ricchiuti |
| Abstract: | Modern economies exhibit deeply integrated and synchronized networks among heterogeneous agents. This paper focuses on the trade network and seeks to unravel the mechanisms that underpin its emergence and evolution. To this end, we develop a multi-country general equilibrium model of trade that incorporates firms and countries heterogeneity as well as asymmetric information and financial frictions. Within this framework, the export decisions of firms give rise to an international trade network that mirrors the structure of real-world trade flows. Thus, the model, by encompassing both within and between country heterogeneity, facilitates the investigation of a range of stylized facts pertaining to firm exporting behavior and globalization. Once the network is established, the paper aims at capturing the effects of financial shocks on trade flows and their network-based spillovers. The introduction of a credit market in a trade model provides novel insights on the influence of monetary and financial factors on trade patterns. |
| Keywords: | trade, productivity, net worth, financial frictions, network analysis |
| JEL: | F11 F12 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:frz:wpaper:wp2024_26.rdf |
| By: | Eyo I. Herstad; Myungkou Shin |
| Abstract: | This paper develops an econometric model to analyse heterogeneity in peer effects in network data with endogenous spillover across units. We introduce a rank-dependent peer effect model that captures how the relative ranking of a peer outcome shapes the influence units have on one another, by modeling the peer effect to be linear in ordered peer outcomes. In contrast to the traditional linear-in-means model, our approach allows for greater flexibility in peer effect by accounting for the distribution of peer outcomes as well as the size of peer groups. Under a minimal condition, the rank-dependent peer effect model admits a unique equilibrium and is therefore tractable. Our simulations show that that estimation performs well in finite samples given sufficient covariate strength. We then apply our model to educational data from Norway, where we see that higher-performing students disproportionately drive GPA spillovers. |
| Date: | 2024–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2410.14317 |
| By: | Breen, Casey; Rahman, Saeed; Kay, Christina; Smits, Joeri; Azar, Abraham; Ahuka-Mundeke, Steve; Feehan, Dennis |
| Abstract: | Reliable estimates of death rates in complex humanitarian emergencies are critical for assessing the severity of a crisis and for effectively allocating resources. However, in many humanitarian settings, logistical and security concerns make conventional methods for estimating death rates infeasible. We develop and test a new method for estimating death rates in humanitarian emergencies using reports of deaths in survey respondents’ social networks. To test our method, we collected original data in Tanganyika Province of the Democratic Republic of the Congo, a setting where reliable estimates of death rates are in high demand. Qualitative fieldwork suggested testing two different types of personal networks as the basis for death rate estimates: deaths among immediate neighbors and deaths among kin. We benchmarked our network estimates against a standard retrospective household mortality survey, which estimated a crude death rate nearly twice as high as our network-based methods. Given both methods are equally plausible, our findings underscore the need for further validation and development of both methods. |
| Date: | 2024–10–24 |
| URL: | https://d.repec.org/n?u=RePEc:osf:socarx:4efdt |