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on Network Economics |
| By: | Della Lena, Sebastiano (Monash University); Merlino, Luca (ECARES, Universite libre de Bruxelles); Zenou, Yves (Monash University) |
| Abstract: | We study opinion dynamics in a social network consisting of two groups. Agents update their opinions by conforming to members of their own group while rejecting the views of the opposing group (affective polarization), and by listening to a media outlet that may provide biased information. We characterize the long-run opinions and identify when affective polarization and media bias lead to ideological polarization, persistent disagreement, or failures of learning. We also derive when information interventions or censorship improve { the accuracy of average opinions} and reduce disagreement, and when they backfire: better information helps only under specific media bias configurations and when directed to the agents we identify as most effective at propagating it through the network. |
| Keywords: | signed networks, opinion dynamics, affective polarization, group antagonism, information campaigns, targeting |
| JEL: | C7 D7 D85 |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18823 |
| By: | Charness, Gary (University of California, Santa Barbara); Feri, Francesco (Royal Holloway University of London); Jackson, Matthew (Stanford University); Melendez-Jimenez, Miguel (University of Malaga); Sutter, Matthias (Max Planck Institute for Behavioral Economics) |
| Abstract: | We provide a first causal analysis of the behavioral consequences of the friendship paradox—the fact that people’s friends in a network have more connections than average. We find that people’s behavior is biased by their network position: they do not best respond to what they should infer the average behavior of the population to be, but instead simply to the average behavior of their friends. Moreover, we find that they fail to learn to overcome such a bias when relocated within the network, varying their observational environment. In these games of complements, the friendship paradox generates a systematic upward distortion in actions, increases behavioral dispersion, and persists despite learning opportunities. |
| Keywords: | friendship paradox, networks, learning, experiment |
| JEL: | C91 D01 D85 D90 |
| Date: | 2026–08 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18861 |
| By: | Goulas, Sofoklis; Griselda, Silvia; Megalokonomou, Rigissa; Zenou, Yves |
| Abstract: | How do disruptive peers shape academic and career paths? We examine this question by leveraging the random assignment of students to classrooms in Greece and identifying the effects of peer disruptiveness on academic performance and career paths. Using suspension hours as a measure of disruptiveness, we find that students assigned to more disruptive classrooms have lower academic achievement, a higher risk of grade retention, and reduced likelihood of graduating from high school on time. They are also less likely to pursue competitive STEM fields or enroll in selective postsecondary programs. The adverse effects are more pronounced for students from low-income areas, in larger classrooms, or with fewer female peers. Using a lab-in-the-field experiment, we find that exposure to multiple disruptors, compared to just one, reduces students’ study motivation, college aspirations, and readiness for science studies and careers, especially for those seated closer to disruptive peers. |
| Keywords: | Lab-in-the-field experiment |
| JEL: | I24 I26 J16 J24 |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:19793 |
| By: | Fetzer, Thiemo; Lambert, Peter John; Feld, Bennet; Garg, Prashant |
| Abstract: | This paper leverages generative AI to build a network structure over 5, 000 product nodes, where directed edges represent input-output relationships in production. We layout a two-step 'build-prune' approach using an ensemble of prompt-tuned generative AI classifications. The 'build' step provides an initial distribution of edge-predictions, the 'prune' step then re-evaluates all edges. With our AI-generated Production Network (AIPNET) in toe, we document a host of shifts in the network position of products and countries during the 21st century. Finally, we study production network spillovers using the natural experiment presented by the 2017 blockade of Qatar. We find strong evidence of such spill-overs, suggestive of on-shoring of critical production. This descriptive and causal evidence demonstrates some of the many research possibilities opened up by our granular measurement of product linkages, including studies of on-shoring, industrial policy, and other recent shifts in global trade. |
| Keywords: | Large Language Models; Trade wars |
| JEL: | F14 F52 O25 N74 C81 |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:19708 |
| By: | Yingxing Li; Ã ureo de Paula; Weining Wang |
| Abstract: | This paper analyzes spillover effects in spatial (network) models when the neighborhood (adjacency) matrix is contaminated by measurement error from reporting, aggregation, or disclosure imperfections, leading to inconsistent estimation of network effects. We introduce a regularization framework for the latent network that allows for sparse and/or low-rank structure and accommodates potential correlation between measurement errors and outcomes. We propose two estimators: (i) a two-stage procedure that first denoises the adjacency matrix and then incorporates the purified network into a regression analysis, and (ii) a Generalized Method of Moments (GMM) estimator that jointly estimates regression parameters and refines the network structure. We then establish strictly improved consistency rates for the spillover effect estimator relative to naive estimation ignoring measurement error. Simulations demonstrate that, in the presence of noisy networks, our approach reduces the root mean squared error of spillover estimates relative to conventional methods by approximately 50−80%. We apply our framework to examine the international spillover of economic growth, and the tax competition across U.S. states, illustrating that denoising might restore Leontief stability and yields improved estimates of spillovers. |
| Date: | 2026–01–30 |
| URL: | https://d.repec.org/n?u=RePEc:bri:uobdis:26/841 |
| By: | Candogan, Ozan; Koenig, Michael; Marray, Kieran; Takes, Frank |
| Abstract: | We study disease spread on a social network where individuals adjust contacts to avoid infection. Susceptible individuals rewire links from infectious individuals to other susceptibles, reducing infections and causing the disease to only become endemic at higher infection rates. We formulate the planner’s problem of implementing targeted lockdowns to control endemic disease as a semidefinite program that is computationally tractable even with many groups. Rewiring complements policy by allowing more intergroup contact as the rewiring rate increases. We apply our model to compute optimal spatially targeted lockdowns for the Netherlands during Covid-19 using a population-level contact network for 17.26 million individuals. Our findings indicate that, with rewiring, a targeted lockdown policy permits 12% more contacts compared to one without rewiring, underscoring the significance of accounting for network endogeneity in effective policy design. |
| JEL: | C63 E23 I12 I15 I18 I19 |
| Date: | 2025–01 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:19892 |
| By: | Arnaud Natal (IFP - Institut Français de Pondichéry - MEAE - Ministère de l'Europe et des Affaires étrangères - CNRS - Centre National de la Recherche Scientifique, UB - Université de Bordeaux, BSE - Bordeaux sciences économiques - UB - Université de Bordeaux - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement); Damien Girollet (BSE - Bordeaux sciences économiques - UB - Université de Bordeaux - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, UB - Université de Bordeaux) |
| Abstract: | Using original data from rural South India, we examine how personality traits intersect with caste and gender to shape interpersonal network characteristics in a Global South context. We analyse the relationship between four personality traits (emotional stability, plasticity, conscientiousness, and locus of control) and three network outcomes (strength of ties, caste, and gender heterophily) using econometric tools. We document four main findings. Firstly, personality traits significantly shape tie strength, reflecting differences in how individuals balance relational dependence and social autonomy. Secondly, personality is associated with selective social boundary crossing, which may facilitate interaction across caste lines, while remaining constrained by gender norms. Thirdly, personality traits shape network characteristics to a similar extent across networks, suggesting that ties remain governed by stable patterns of social interaction. Fourthly, personality operates as a context-dependent resource, shaping networks primarily among individuals who are structurally able to act, particularly men and middle castes. |
| Keywords: | Social network, Caste, Gender, Locus of control, Big Five |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05547405 |
| By: | Ferrari, Alessandro |
| Abstract: | I study the role of industries’ position in supply chains in shaping the transmission of final demand shocks. First, I use a novel shift-share design leveraging destination-specific final demand shocks and a new measure of destination exposure accounting for direct and indirect linkages. I find that demand shocks amplify significantly as they propagate upstream, with upstream industries experiencing output elasticities up to three times larger than final good producers, consistent with the bullwhip effect. To rationalize these empirical results, I develop a tractable production network model with inventories and study how the properties of the network and the cyclicality of inventories interact to determine whether final demand shocks amplify or dissipate upstream. I test the mechanism by directly estimating the model-implied relationship between output growth and demand shocks, mediated by network position and inventories. I find that the presence of inventories increases output elasticities by 18% on average, highlighting the macroeconomic significance of this channel. Finally, I use the model to quantitatively study the effects of long-run trends of lengthening supply chains and rising inventories on the volatility of the economy. |
| Keywords: | Production networks; Supply chains; Inventories; Bullwhip Effect; Shock amplification |
| JEL: | C67 E23 E32 F14 F44 L14 L16 |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:19716 |
| By: | Bilgin, Nuriye Melisa; Faia, Ester; Ottaviano, Gianmarco |
| Abstract: | We examine how upstream firms’ technology adoption affects the performance and adoption decisions of downstream partners. Using business-to-business data with administrative records on advanced technology adoption, we find gains in productivity, performance, adoption probabilities of firms connected to the adopter, relatively to those that are not. Identification combines staggered event studies, balanced panels of pre-existing relationships, and recentering methods to address expected exposure within the network. Gains vary along firm size, centrality, technology quality, but do not systematically increase with input exposure, suggesting that knowledge spillovers may induce organizational adjustments. Adoption by competitors is associated with short-run negative effects. |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:19804 |
| By: | QIU, Zhesheng; Wang, Yicheng Wan; Xu, Le; Zanetti, Francesco |
| Abstract: | This paper studies the design of monetary policy in small open economies with domestic and cross-border production networks and nominal rigidities. The monetary policy that closes the domestic output gap is nearly optimal and is implemented by stabilizing the aggregate inflation index that weights sectoral inflation according to the sector’s roles as a supplier of inputs and a net exporter of products within the international production networks. To close the output gap, monetary policy should assign large weights to inflation in sectors with small direct or indirect (i.e., via the downstream sectors) import shares and failing to account for the cross-border production networks overemphasizes inflation in sectors that export intensively directly and indirectly (i.e., via the downstream sectors). We validate our theoretical results using the World Input-Output Database and show that the monetary policy that closes the output gap outperforms alternative policies that abstract from the openness of the economy or the input-output linkages. |
| Keywords: | Production networks |
| JEL: | E6 E52 F41 |
| Date: | 2025–01 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:19828 |
| By: | Mr. Francesco Grigoli |
| Abstract: | I study how the production network shapes monetary policy transmission to prices. Using U.S. data, I show that industries farther upstream from final demand exhibit larger cumulative price responses to monetary shocks, while downstream industries absorb shocks through output. A calibrated multi-sector New Keynesian model rationalizes these patterns: upstream sectors, which sell predominantly to other firms, reprice more frequently and therefore exhibit less price rigidity. A counterfactual decomposition of the price response shows that this heterogeneity in price rigidity---rather than cost-cascade propagation through input-output linkages---is the primary driver of the cross-sectional responses. The upstreamness differential is strongly asymmetric, large following expansionary shocks but nearly absent following contractionary ones, consistent with asymmetric price rigidity compounding across production stages. Together, these findings suggest that monetary policy's potency depends on the production network's architecture. |
| Keywords: | production networks; price rigidity; monetary policy transmission; input-output linkages; asymmetric price adjustment |
| Date: | 2026–06–26 |
| URL: | https://d.repec.org/n?u=RePEc:imf:imfwpa:2026/127 |
| By: | Demir, Banu; Javorcik, Beata; Panigrahi, Piyush |
| Abstract: | This paper explores how improved internet infrastructure impacts supply chains and economic activity, focusing on Türkiye. Using the expansion of fiber-optic networks and firm-to-firm transaction data, we find that better connectivity shifts input sourcing to well-connected regions and diversifies supplier networks. We estimate a spatial equilibrium model with endogenous network formation and rational inattention and find that high-speed internet reduced information acquisition and communication costs. Enhanced connectivity increased real income by 2.2% in the median province. Our findings underscore the importance of digital infrastructure investments in fostering economic growth by improving supply chain efficiency and broadening firms’ access to suppliers. |
| Date: | 2025–01 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:19827 |
| By: | Yechan Park |
| Abstract: | Economic policies rarely affect only their direct targets. To study these spillovers, researchers summarize who else was treated with a simple exposure measure, such as the share of treated neighbors within a radius. But for many settings, economic theory provides little guidance on choosing the functional form (e.g., ring) of that measure or its parameters (e.g., radius). We show that the data can inform both choices. Correctly specified exposure measures imply orthogonality conditions that can be used for both estimation and testing. We establish consistency and asymptotic normality of the resulting estimator under spatial and network dependence in a design-based framework, with all randomness arising from treatment assignment. We then characterize the efficient moment conditions. Applied to two large-scale anti-poverty programs, the framework supports some prior radius estimates but rejects others. In the latter case, the revised radius yields substantively different policy-effect estimates. |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2607.08640 |
| By: | Li Gan |
| Abstract: | I measure whether the rise of services is ultimately supported by household consumption or by non-household demand through production networks, investment, exports, and government. Using harmonized input-output tables for 76 economies over 1995-2022, I attribute service value added to its ultimate domestic final-demand category and measure the household orientation of each service economy in both levels and growth. The conventional service share does not reveal the type: it is negatively correlated with household orientation, and only about four in ten tertiarization episodes are majority-household. Among the 65 economies whose service share rose over 1995-2018, 77 percent became less household-oriented; the share is 75 percent under a two-percentage-point material-change threshold. Yet household-supported production becomes more service-intensive with income because households' aggregate position falls faster. A one-type benchmark has no purchaser margin; a two-type extension gives the condition for this reversal. An exact Leontief accounting and Shapley decomposition allocate a median 73 percent of service-share growth to production-system channels, which are the largest contribution in 80 percent of economies with materially rising shares. The decline in household orientation is instead allocated mainly to aggregate final-demand structure. The service share records how much service activity exists, not which economic transformation produced it. |
| Date: | 2026–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2608.06584 |
| By: | Sara Chehab; Giorgos Iacovides; Parisa Yazdanparast; Danilo Mandic |
| Abstract: | Current portfolio construction methods are either agnostic to the effects of idiosyncratic shocks (standard factor models) or to the latent data structure driving systematic returns (recent graph-based approaches). This presents an opportunity to combine the complementary market aspects captured by the factor and graph domains, allowing asset allocations to operate directly on the underlying market structure, rather than on its observed co-movement or its finite-sample artefacts. In this work, we introduce the Mutually-INformed Graph-Locality and Exposures framework (MINGLE), which mutually regularises the factor and graph domains by redefining graph locality through systematic factor exposure profiles, rather than via observed co-movements. This is formalised through a unified Alternating Direction Method of Multipliers (ADMM) framework that jointly learns a latent factor representation and its induced graph topology directly from market returns. The resulting exposure-similarity graph aligns more closely with established economic sectors than conventional correlation-based graphs. Portfolios constructed from this representation are shown to consistently outperform their correlation-based counterparts across a range of volatility regimes and transaction cost levels. For rigour, paired statistical testing confirms that these gains stem from the reconciliation of the graph and factor domains. |
| Date: | 2026–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2608.06618 |