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on Network Economics |
| By: | Livia Shkoza (University of Konstanz, GSDS); Derya Uysal (University of Munich, CESifo); Winfried Pohlmeier (University of Konstanz, CASCB, ICEA) |
| Abstract: | This study focuses on the role of heterogeneity in network peer effects by accounting for network-specific factors and different driving mechanisms of peer behavior. We propose a novel Multivariate Instrumental Variable (MVIV) estimator which is consistent for a large number of networks keeping the individual network size bounded. We apply this approach to estimate peer effects on school achievement exploiting the network structure of friendships within classrooms. The empirical evidence presented is based on a unique network dataset from German upper secondary schools. We show that accounting for heterogeneity is not only crucial from a statistical perspective, but also yields new structural insights into how class size and gender composition affect school achievement through peer behavior. |
| Keywords: | network heterogeneity; peer effects; multivariate instrumental variables; minimum distance estimation; school achievement; |
| JEL: | D85 L14 I21 C30 C36 |
| Date: | 2023–09–06 |
| URL: | http://d.repec.org/n?u=RePEc:rco:dpaper:423&r=net |
| By: | Mathieu Lambotte (GAEL - Laboratoire d'Economie Appliquée de Grenoble - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - UGA - Université Grenoble Alpes - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - UGA - Université Grenoble Alpes); Sandrine Mathy (GAEL - Laboratoire d'Economie Appliquée de Grenoble - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - UGA - Université Grenoble Alpes - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - UGA - Université Grenoble Alpes); Anna Risch (GAEL - Laboratoire d'Economie Appliquée de Grenoble - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - UGA - Université Grenoble Alpes - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - UGA - Université Grenoble Alpes); Carole Treibich (GAEL - Laboratoire d'Economie Appliquée de Grenoble - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - UGA - Université Grenoble Alpes - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - UGA - Université Grenoble Alpes) |
| Abstract: | We investigate the role of peer effects at the work place on the individual choice of transportation mode. We collect original data through an online survey on networks and sustainable behaviors among 334 individuals working in ten laboratories of the University of Grenoble Alps in February 2020. Using a linear-in-means model for binary outcomes and distinguishing endogenous and exogenous peer effects, correlated effects and network endogeneity, we find that peers have a significant and positive effect on individual active transportation mode's choice. We show that in our setting, a simulated policy or intervention would be almost twice more effective in spreading active transportation mode through social spillover effects if it targets key players rather than random individuals. |
| Keywords: | Peer effects, Social network, Workplace, Transportation choice, Key players |
| Date: | 2022–06–14 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:hal-03702660&r=net |
| By: | L. S. Sanna Stephan |
| Abstract: | According to standard econometric theory, Maximum Likelihood estimation (MLE) is the efficient estimation choice, however, it is not always a feasible one. In network diffusion models with unobserved signal propagation, MLE requires integrating out a large number of latent variables, which quickly becomes computationally infeasible even for moderate network sizes and time horizons. Limiting the model time horizon on the other hand entails loss of important information while approximation techniques entail a (small) error that. Searching for a viable alternative is thus potentially highly beneficial. This paper proposes two estimators specifically tailored to the network diffusion model of partially observed adoption and unobserved network diffusion. |
| Date: | 2023–09 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2309.01489&r=net |
| By: | René van den Brink (VU University Amsterdam and Tinbergen Institute); Agnieszka Rusinowska (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, CNRS - Centre National de la Recherche Scientifique, UP1 - Université Paris 1 Panthéon-Sorbonne, PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris sciences et lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement) |
| Abstract: | This paper aims to connect the social network literature on centrality measures with the economic literature on von Neumann-Morgenstern expected utility functions using cooperative game theory. The social network literature studies various concepts of network centrality, such as degree, betweenness, connectedness, and so on. This resulted in a great number of network centrality measures, each measuring centrality in a different way. In this paper, we aim to explore which centrality measures can be supported as von Neumann-Morgenstern expected utility functions, reflecting preferences over different network positions in different networks. Besides standard axioms on lotteries and preference relations, we consider neutrality to ordinary risk. We show that this leads to a class of centrality measures that is fully determined by the degrees (i.e. the numbers of neighbours) of the positions in a network. Although this allows for externalities, in the sense that the preferences of a position might depend on the way how other positions are connected, these externalities can be taken into account only by considering the degrees of the network positions. Besides bilateral networks, we extend our result to general cooperative TU-games to give a utility foundation of a class of TU-game solutions containing the Shapley value. |
| Keywords: | weighted network, degree, centrality measure, externalities, neutrality to ordinary risk, expected utility function |
| Date: | 2023–08 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:halshs-04188289&r=net |
| By: | Ben Ost; Weixiang Pan; Douglas A. Webber |
| Abstract: | We provide the first evidence on the role of college networks in the re-employment of displaced workers. An extensive literature examines the consequences of layoffs, but the factors which facilitate re-employment are relatively under-studied. Using administrative data and a cross-cohort design, we find that network connections with actively-hiring employers increase the re-employment rate. This result is driven by re-employment at contact’s firms suggesting that a stronger network does not improve worker quality more broadly. These results suggest that college has the potential to improve employment outcomes beyond improved human capital and signaling. |
| Date: | 2023–06 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedgfe:96645&r=net |
| By: | Carrell, Scott; Figlio, David; Lusher, Lester |
| Abstract: | We study how author-editor and author-reviewer network connectivity and "match" influence editor decisions and reviewer recommendations of economic research at the Journal of Human Resources. Our empirical strategy employs several dimensions of fixed effects to overcome concerns of endogenous assignment of papers to editors and reviewers. Authors who attended the same PhD program, were ever colleagues with, are affiliates of the same National Bureau of Economic Research program(s), or are more closely linked via coauthorship networks as the handling editor are significantly more likely to avoid a desk rejection. Likewise, authors from the same PhD program or who previously worked with the reviewer are significantly more likely to receive a positive evaluation. We also find that sharing "signals" of ability, such as publishing in the "top five", attending a high ranked PhD program, or being employed by a similarly ranked economics department, significantly influences editor decisions and/or reviewer recommendations. We find some evidence that published papers with greater author-editor connectivity subsequently receive fewer citations. |
| Date: | 2023 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:i4rdps:60&r=net |
| By: | Jeon, Doh-Shin; Lefouili, Yassine; Li, Yaxin; Simcoe, Timothy |
| Abstract: | Motivated by several examples, including Internet of Things patent licensing, we develop a tractable model of multi-product ecosystems, where one or more plat- forms provide inputs to a set of devices linked through demand-side externalities. Prices depend on each device's Katz-Bonacich centrality in a network dened by the externalities, and we show how the relevant network diers for an ecosystem monop- olist, a social planner, or a group of complementary platforms. We use the model to revisit Cournot's analysis of complementary monopolies in a platform setting, and to analyze a partial (one-sided) merger of complementary platforms. |
| Keywords: | Multi-sided Market, Complementary Platforms, Network, Centrality, ; IoT, Licensing |
| Date: | 2023–09–13 |
| URL: | http://d.repec.org/n?u=RePEc:tse:wpaper:128468&r=net |
| By: | L. S. Sanna Stephan |
| Abstract: | Network diffusion models are applicable to many socioeconomic interactions, yet network interaction is hard to observe or measure. Whenever the diffusion process is unobserved, the number of possible realizations of the latent matrix that captures agents' diffusion statuses grows exponentially with the size of network. Due to interdependencies, the log likelihood function can not be factorized in individual components. As a consequence, exact estimation of latent diffusion models with more than one round of interaction is computationally infeasible. In the present paper, I propose a trimming estimator that enables me to establish and maximize an approximate log likelihood function that almost exactly identifies the peak of the true log likelihood function whenever no more than one third of eligible agents are subject to trimming. |
| Date: | 2023–09 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2309.01471&r=net |
| By: | Rosa van den Ende (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, Universität Bielefeld = Bielefeld University); Antoine Mandel (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 - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris sciences et lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement); Agnieszka Rusinowska (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 - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris sciences et lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement) |
| Abstract: | We provide an axiomatic approach to the allocation of responsibility for GHG emissions in supply chains. Considering a set of axioms standardly used in networks and decision theory, and consistent with legal principles underlying responsibility, we show that responsibility measures shall be based on exponential discounting of upstream and downstream emissions. From a network theory perspective, the proposed responsibility measure corresponds to a convex combination of the Bonacich centralities for the upstream and downstream weighted adjacency matrices. Scope 1 emissions, consumption-based accounting and income-based accounting are obtained as particular cases of our approach, which also gives a precise meaning to scope 3 emissions while avoiding double-counting. We apply our approach to the assessment of country-level responsibility for global GHG emissions and to sector-level responsibility in the USA. We examine how the responsibility of sectors/countries varies with the discounting of indirect emissions. We identify three groups of countries/sectors: producers of emissions whose responsibility decreases with the discounting factor, consumers of emissions whose responsibility increases with the discounting factor, and an intermediary group whose responsibility mostly depends on the network position and varies non-monotonically with the discounting factor. Overall, our axiomatic approach provides strong normative foundations for the definition of reporting requirements for indirect emissions and for the allocation of responsibility in claims for climate-related loss and damage. |
| Keywords: | upstream and downstream emission responsibilities, supply chains and networks, responsibility measure, axiomatization, Bonacich centrality |
| Date: | 2023–08 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:halshs-04188365&r=net |
| By: | Mengsi Gao; Peng Ding |
| Abstract: | Network experiments have been widely used in investigating interference among units. Under the ``approximate neighborhood interference" framework introduced by \cite{Leung2022}, treatments assigned to individuals farther from the focal individual result in a diminished effect on the focal individual's response, while the effect remains potentially nonzero. \cite{Leung2022} establishes the consistency and asymptotic normality of the inverse-probability weighting estimator for estimating causal effects in the presence of interference. We extend these asymptotic results to the Hajek estimator which is numerically identical to the coefficient from the weighted-least-squares fit based on the inverse probability of the exposure mapping. The numerically equivalent regression-based approach offers two notable advantages: it can provide standard error estimators through the same weighted-least-squares fit, and it allows for the integration of covariates into the analysis. Furthermore, we introduce the regerssion-based network-robust variance estimator, adopting the form of the Heteroskedasticity and Autocorrelation Consistent estimator, and analyze its asymptotic bias. Recognizing that the variance estimator can be anti-conservative, we propose an adjusted variance estimator to improve empirical coverage. Although we focus on regression-based point and variance estimators, our theory holds under the design-based framework, which assumes that the randomness comes solely from the design of network experiments and allows for arbitrary misspecification of the regression models. |
| Date: | 2023–09 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2309.07476&r=net |
| By: | Moritz Goldbeck (ifo Institute & LMU Munich) |
| Abstract: | Digital work settings potentially facilitate remote collaboration and thereby decrease geographic frictions in knowledge work. Here, I analyze spatial collaboration patterns of some 191 thousand software developers in the United States on the largest code repository platform GitHub. Despite advanced digitization in this occupation, developers are geographically highly concentrated, with 79.8% of users clustering in only ten economic areas, and colocated developers collaborate about nine times as much as non-colocated developers. However, the colocation effect is much smaller than in less digital social or inventor networks, and apart from colocation geographic distance is of little relevance to collaboration. This suggests distance is indeed less important for collaboration in a digital work setting while other strong drivers of geographic concentration remain. Heterogeneity analyses provide insights on which types of collaboration tend to colocate: the colocation effect is smaller within larger organizations, for high-quality projects, among experienced developers, and for sporadic interactions. Overall, this results in a smaller colocation effect in larger economic areas. |
| Keywords: | geography; digitalization; networks; knowledge economy; colocation; |
| JEL: | L84 O18 O30 R32 |
| Date: | 2023–09–05 |
| URL: | http://d.repec.org/n?u=RePEc:rco:dpaper:422&r=net |
| By: | Marc König (Karlsruher Institute for Technology, EnTechnon,); Manon Enjolras (ERPI - Equipe de Recherche sur les Processus Innovatifs - UL - Université de Lorraine); Christina Ungerer (Konstanz University of Applied Sciences, IST Institute for Strategic Innovation and Technology Management); Mauricio Camargo (ERPI - Equipe de Recherche sur les Processus Innovatifs - UL - Université de Lorraine); Guido Baltes (Konstanz University of Applied Sciences, IST Institute for Strategic Innovation and Technology Management) |
| Abstract: | At the early stage of a successful tech venture's life cycle, it is assumed that the business model will evolve to higher quality over time. However, there are few empirical insights into business model evolution patterns for the performance-related classification of early-stage tech ventures. We created relevant variables evaluating the evolution of the venture-centric network and the technological proposition of both digital and non-digital ventures' business models using the text of submissions to the official business plan award in the German State of Baden-Württemberg between 2006 and 2012. Applying a principal component analysis/rough set theory mixed methodology, we explore performance-related business model classification rules in the heterogeneous sample of business plans. We find that ventures need to demonstrate real interactions with their customers' needs to survive. The distinguishing success rules are related to patent applications, risk capital, and scaling of the organisation. The rules help practitioners to classify business models in a way that allows them to prioritise action for performance. |
| Keywords: | network theory, business model, life cycle, RST, rough set theory, PCA, principal component analysis, tech ventures |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:hal-03685241&r=net |