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on Network Economics |
| By: | Johanna Einsiedler; Nikolaj Arpe Harmon; David Dreyer Lassen; Andreas Bjerre-Nielsen |
| Abstract: | A large literature uses exogenous variation to estimate how assignment to classrooms or other groups shapes social networks. Yet most of these analyses remain dyadic, treating each link in isolation, even though ties often form through triadic closure, as a friend of a friend also becomes a friend. Using fine-grained data on phone calls, text messages, physical co-location, and social-media ties, we estimate the network formation effects of randomly assigning first-year university students to classrooms and to smaller social groups. To analyze explicitly whether group assignment interact with triadic closure, we use our random assignment to estimate a subgraph generated model of network formation. Accounting for triadic closure turns out to be crucial. For social groups in particular, group assignment affects network formation almost entirely by inducing additional triadic closure. Estimates ignoring triadic closure can thus yield misleading predictions about the network effects and benefits of group assignment policies. |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2607.17926 |
| By: | Campbell, Arthur; Thornton, D.J.; Zenou, Yves |
| Abstract: | We study the role of influence in a model of the diffusion of social behaviors in a network. Individual behavior creates either positive spillovers (public goods) or negative spillovers (public bads). Our notion of influence captures the causal effect of an agent's adoption decision on the adoption decision of others in the network. We study a phase transition in equilibrium behavior around which viral equilibria—where diffusion occurs among a nontrivial fraction of the population—emerge. Public goods exhibit a continuous phase transition in equilibrium adoption, while public bads exhibit a discontinuous transition-- they emerge suddenly. Our findings reconcile disparate evidence that attending a public protest is a strategic complement in some settings and a substitute in others. |
| Keywords: | Diffusion; Public goods; Public bads; Narratives; Social Networks |
| JEL: | D43 D85 |
| Date: | 2024–09 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:19443 |
| By: | Scherpf, Erik; Zachary, Chandler |
| Abstract: | Recent disruptions to food supply chains have renewed interest in how shocks propagate through the U.S. food economy and which sectors occupy structurally important positions within it. This paper uses the USDA Economic Research Service Agri-Food Economic Data System (Ag-FEDS) to characterize the production network of the U.S. food economy and to connect that network structure to the USDA Food Dollar. We analyze the network along three dimensions: direction of propagation, depth of linkage, and conditioning on final food demand. Using measures based on input-output multiplier analysis, Domar weights, and related network centrality concepts, we examine both the overall food economy and the distinct production networks supporting food at home and food away from home. We also use the annual AgFEDS series from 2007 to 2024 to study the stability of these structural relationships over time. Conceptually, the paper shows how Food Dollar industry-group results can be decomposed into value-added intensity, food-conditional network centrality, and final-demand orientation, providing a bridge between Food Dollar accounting and the production-network literature. |
| Keywords: | Production Economics |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:ags:aaea26:404692 |
| By: | Ren Manfredi; Eugenio Vicario; Ennio Bilancini; Rossana Mastrandrea |
| Abstract: | Human cooperation is a phenomenon that has been extensively studied, and to date several explanations have been proposed, from network reciprocity to behavioral mechanisms that incorporate social and cognitive aspects. In this work, we studied the combined effect of conformity and network structure on the evolution of cooperation in the spatial Public Goods Game. By assigning agents different individual sensitivities to payoffs and neighborhood behavior, we explored the cooperative dynamics of this heterogeneous population on both regular and complex topologies. Our results show how the interaction between conformity and the distinctive features of each network can lead to very different outcomes, from the promotion of cooperation in regular topologies to null or negative effects in heterogeneous networks. |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2607.23131 |
| By: | Yingxing Li; Aureo 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: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2607.19625 |
| By: | Della Lena, Sebastiano; Safi, Shahir; Zenou, Yves |
| Abstract: | This paper examines the interplay between social networks, firm hiring policies, and the transmission of work ethics across generations. Specifically, we analyze how firms' preferences for weak-tie referrals versus traditional screening methods influence long-term labor market outcomes, including wages and employment. We also explore the role of parents in shaping their children's work ethics and how these cultural traits affect labor market integration. The findings reveal that while weak-tie referrals may provide short-term employment benefits, they also contribute to long-run inequalities in wages and work ethics between different social groups. Furthermore, differentiated hiring policies, while effective in the short term, can perpetuate social disparities if not properly addressed through integrative policies. |
| Date: | 2024–10 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:19570 |
| By: | Kasy, Maximilian (University of Oxford); Linos, Elizabeth (Harvard Kennedy School); Mobasseri, Sanaz (UCL) |
| Abstract: | This paper develops a framework for identification, estimation, and inference on the causal mechanisms driving endogenous social network formation. Identification is challenging because of unobserved confounders and reverse causality; inference is complicated by questions of equilibrium and sampling. We leverage repeated observations of a network over time and random variation in initial ties to address challenges to causal identification. Our design-based approach sidesteps questions of sampling and asymptotics by treating both the set of nodes (individuals) and potential outcomes as non-random. We apply our approach to data from a large professional services firm, where new hires are randomly assigned to project teams within offices. We estimate the causal effect on tie formation of indirect ties, network degree, and local network density. Indirect ties have a strong and significant positive effect on tie formation, while the effects of degree and density are smaller and less robust. |
| Keywords: | network formation, design-based inference |
| JEL: | D85 C31 |
| Date: | 2026–06 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18759 |
| By: | Wayne Yuan Gao; Ming Li |
| Abstract: | We develop a finite-sample valid inference procedure for strategic network formation models in which linking decisions depend on endogenous network statistics (say, the number of common friends). Only a single network is required to be observed, and we restrict neither its density, nor the dependence structure induced by strategic interaction, nor the equilibrium selection mechanism. We exploit a bounding-by-c technique to construct a set of sandwich inequalities that are valid realization by realization, with the middle term involving only the i.i.d. pairwise error. We then average the sandwich inequalities over cells of exogenous covariates, and obtain identifying restrictions under a nonstandard pathwise limit formulation. For inference, we construct test statistics whose finite-sample uncertainty can be controlled by statistics of the exogenous covariates and errors alone, whose conditional distributions are exactly simulable in both semiparametric and parametric settings. Our proposed inference procedure is also computationally tractable, with no need to solve, simulate, or enumerate equilibrium network structures. In simulations, our procedure easily scales to networks of size 10, 000, and yields confidence sets that certifies the sign of the strategic coefficient. In two empirical applications (with network size about 300~9500), we find statistical evidence for positive link interdependence at 95% confidence level. |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2607.27505 |
| By: | Juan Estrada; Kim Huynh; David Jacho-Chavez; Leonardo Sanchez-Aragon |
| Abstract: | A novel method to estimate social effect coefficients in the popular so-called linear-in-means regression model in the Social Sciences is presented here that utilizes non-experimental multidimensional network data. The procedure can accommodate social interactions that correlate with the error in the model by making use of a different set of network links among the same observations that are exogenous in the traditional sense. In particular, the full observability of a two-layered multiplex network data structure is assumed here to propose a new Generalized 3-Stage Least Squares (G3SLS) estimator that is consistent, asymptotically normally distributed, and also easy to implement using widely-used existing statistical software because of its closed-form definition. The underlying assumptions are general enough to accommodate common problems with observational data such as measurement error, simultaneity, and unobserved heterogeneity. Monte Carlo exercises confirm the good small sample performance of the proposed G3SLS estimator in these scenarios. An empirical application finds positive and significant peer effects in citations among research articles published in top general-interest journals in economics. |
| Date: | 2026–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2608.01421 |
| By: | TszKin Julian Chan; Juan Estrada; Kim Huynh; David Jacho-Chavez; Chungsang Tom Lam; Leonardo Sanchez-Aragon |
| Abstract: | This paper introduces an innovative approach to identifying and estimating the parameters of interest in the widely recognized linear-in-means regression model under conditions where the initial randomization of peers determines the observed network. We assert that peers who are initially randomized do not produce social effects. However, after randomization, agents can endogenously develop significant connections that potentially generate peer influences. We present a moment condition that compiles local heterogeneous identifying information for all agents within the population. Under the assumption of $\psi$-dependence in the endogenous network space, we propose a Generalized Method of Moments (GMM) estimator, which is proven to be consistent, asymptotically normally distributed, and straightforward to implement using commonly available statistical software due to its closed-form expression. Monte Carlo simulations demonstrate the GMM estimator's strong small-sample performance. An empirical analysis utilizing data from Hong Kong high school students reveals substantial positive spillover effects on math test scores among study partners in our sample, provided that their seatmates were exogenously assigned by their teachers. |
| Date: | 2026–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2608.01405 |
| By: | Alberto Acedo |
| Abstract: | The Triadic Stress Index (TSI) takes a network index whose four factors were first observed in soil microbiome co-occurrence networks and applies it, without alteration, to the correlation network of financial assets. We test it on five markets spanning 2006-2026 (equities including banking crises and the AI sector, cryptocurrencies, commodities, foreign exchange and sovereign debt), against three independent definitions of a crisis episode, at a fixed alarm budget, out of sample, with block-bootstrap intervals and a Holm correction across the family of tests. The benchmarks are the Absorption Ratio, the industry standard used by MSCI and central banks; the effective rank and the Vendi score, the sharpest spectral measures available; Ollivier-Ricci curvature; and the global and local balance indices of signed correlation networks. Three comparisons favour the index. It carries a per-node decomposition, diag(A^3), naming which asset is carrying the concentration with no parameter to select, and scores 0.97-0.99 against 0.33-0.84 for the only published per-node alternative, whereas spectral attribution must first choose how many components to read and collapses under a standard but wrong choice. Its alarms are the cleanest of anything tested, 4.0% of them with no matching episode against 14.7% for the effective rank and roughly 59% for the Absorption Ratio. And it beats the Absorption Ratio on detection by 0.273 in F1 out of sample, p |
| Date: | 2026–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2608.10788 |
| By: | Fuchs, Simon; Wong, Woan Foong |
| Abstract: | Over half of distance-weighted U.S. freight is shipped using more than one transport mode. We examine how multimodal transport networks shape the economic and environmental impacts of infrastructure investments and disruptions. We develop a tractable spatial equilibrium model of multimodal routing with mode-specific congestion at intermodal terminals. We estimate a modal substitution elasticity using road and rail data, and a terminal congestion elasticity using vessel-positioning data. Calibrated to the U.S. freight network, the model identifies key bottlenecks and quantifies $.46-$1.85 billion in real GDP gains from intermodal terminal improvements, with additional environmental benefits from shifting away from carbon-intensive road transport. Ignoring mode-specific congestion overstates welfare gains from highway improvements by 85%, while ignoring multimodal flexibility understates them by 22%. Losing rail network access is estimated to reduce real GDP by $230 billion. |
| Keywords: | Spatial equilibrium; Infrastructure investments; Disruption |
| JEL: | F11 R12 R42 |
| Date: | 2024–09 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:19531 |
| By: | Alan, Sule; Carlana, Michela; Leone, Marinella |
| Abstract: | We evaluate an intervention designed to increase teachers’ awareness of social isolation by providing them with their own students' social network and information on developmental risks associated with social exclusion. Using friendship data and incentive-compatible measures of antisocial and prosocial behavior, we find that the intervention reduces social isolation and antisocial behavior without improving prosocial behavior. The reduction in antisocial behavior leads to better economic outcomes in treated classrooms, measured by average payoffs and the Gini coefficient. Our findings highlight the personal and communal benefits of alleviating social exclusion and antisocial peer relationships in schools. |
| JEL: | I24 I28 C93 |
| Date: | 2024–09 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:19454 |
| By: | Han-Yu Zhu; Maria Cristina Rulli; Wei-Xing Zhou |
| Abstract: | Food supply shocks in major producing economies can propagate through trade networks and generate uneven impacts across the global food system. This study examines the robustness of economies' food supply under production shocks to major producers in the global staple food system. Using 2023 production, reserve, and bilateral trade data for wheat, rice, maize, and soybean, we construct a calorie-based global food supply network across economies. We extend a dynamic shock propagation framework and then simulate production shocks to major producing economies, tracing how supply losses propagate. The results show substantial heterogeneity in robustness across crops and economies. Wheat exhibits the highest overall robustness, whereas soybean shows the lowest. Economies with high robustness tend to be either relatively isolated from the trade network or actively engaged in trade while maintaining strong and stable domestic production, whereas low-robustness economies are predominantly those with high import dependence. Import dependence and per capita production emerge as the most important determinants of robustness. Based on these findings, we design two counterfactual policies targeting highly import-dependent economies: increasing reserve availability and adjusting trade linkages. Counterfactual experiments show that the two policies yield only modest overall improvements, with effects varying substantially across crops. Both policies improve robustness in the aggregated system and wheat, trade adjustment is more effective for rice, and it brings limited or even negative effects for maize and soybean. |
| Date: | 2026–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2608.01010 |
| By: | Casal, Lucia; Caunedo, Julieta |
| Abstract: | Capital accumulation and the systematic reallocation of economic activity across sectors are two of the most salient features of economic development. These two features are interconnected through the production of various types of capital and heterogeneous usage intensity across sectors, which is summarized by the investment network. Our paper introduces the first harmonized measures of the investment network across the development spectrum and documents novel empirical regularities. We propose a simple theory linking disparities in this network to disparities in income per capita across countries. We show that Domar weights and the elasticity of output to sectorial productivity are nontrivial functions of the investment network and equilibrium sectorial investment rates. For our sample of 58 countries, we show that 33% of cross-country differences in income per capita can be accounted for by disparities in the investment network. These differences are twice as large as the role of capital in income disparities estimated through standard development accounting. |
| Keywords: | Growth |
| JEL: | E21 E23 O41 |
| Date: | 2024–09 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:19481 |
| By: | Joan Vilá (Universidad de la República (Uruguay). Facultad de Ciencias Económicas y de Administración. Instituto de Economía); Marcelo Bérgolo (Universidad de la República (Uruguay). Facultad de Ciencias Económicas y de Administración. Instituto de Economía; Universidad de la República (Uruguay). Facultad de Ciencias Económicas y de Administración. Instituto de Economía); Guillermo Cruces (Universidad de San Andres) |
| Abstract: | Standard welfare evaluations of means-tested transfers typically treat eligibility enforcement as affecting only households directly exposed to the rule. We show that this direct-only approach is incomplete when enforcement events transmit information through workplace networks, inducing other beneficiaries to adjust formal employment and reported earnings. We study Uruguay's AFAM-PE conditional cash transfer, in which household income eligibility is verified monthly using administrative records of formal earnings and households exceeding the threshold may lose benefits, while most beneficiaries are largely unaware of the income rule. Linking program records, social security employment histories, and firm identifiers, we build workplace networks defined six months before each peer's exposure to enforcement and identify spillovers using a fuzzy regression discontinuity design that exploits quasi-random variation in whether a peer crosses the income threshold. Coworkers of peers just above the cutoff reduce registered labor earnings by 20\%, and the corresponding fuzzy-RD estimate implies a decline of about one-third of baseline earnings in response to a peer's suspension. These effects emerge within two months and persist for at least 12 months. The response operates almost entirely on the extensive margin of formal employment, and most of the decline reflects transitions to informal work rather than exit from the labor force. Spillovers are concentrated in small firms and among similar coworkers, are nearly three times larger when the suspended peer actively contacted the program's support service, and are absent among non-beneficiary coworkers. This pattern is consistent with information transmission as the main channel. Incorporating these indirect responses lowers the estimated MVPF of the program as implemented with enforcement from 0.53 to 0.36. Because the same information channel operates wherever means-tested programs are enforced through records of formal earnings, evaluations that count only directly exposed households systematically understate the cost of enforcement. |
| Keywords: | Social assistance, Income-testing, Enforcement spillovers, Peer effects, Workplace networks, Informality, MVPF |
| JEL: | H53 H75 I38 J13 J22 J46 O17 |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:ulr:wpaper:dt-09-26 |
| By: | Francetic; I.; |
| Abstract: | Objectives: In healthcare systems with high provider fragmentation, integrated care could curb spending and reduce inefficiency. This paper evaluates whether primary care network topology and the connectedness of providers affect patient-level healthcare expenditures and utilization across six spending categories. Methods: Using Swiss mandatory health insurance claims from 2015 to 2024 structured into three triennia (2015—2017, 2017—2019, 2022—2024), I construct patient-sharing networks among primary healthcare providers over baseline two-year windows. Communities are detected using a spatially weighted Leiden algorithm under the Constant Potts Model objective function. Patients are assigned to communities via their main primary care provider. Imposing community stability in the first two years of the triennium, patients switching communities in year three are identified as network movers. To identify supply-side network effects. I implement a within-movers ANCOVA design evaluating the change in comm unity degree centralisation, the change in (log) degree centrality of the main primary care provider, and the change in local clustering, across both extensive (propensity to incur spending) and intensive (log expenditure) margins.Results: Within-mover estimates point in the same direction at both scales: greater connectedness is associated with lower utilisation and spending. For communities comprised of 3 or more providers, a one-standard-deviation increase in comm unity degree centralisation lowers the probability of incurring expenditure in every category examined, by between 0.5 percentage points (outpatient care) and 3.6 percentage points (emergency care), and reduces conditional spending on laboratory tests by 14.3% and on prescription drugs by 9.7%. Switching to a m ain primary care provider with higher degree centrality (i.e. one who collaborates more with other providers) likewise reduces spending across all expenditure classes, with the largest drops observed for laboratory tests ( — 1.1 p.p. extensive, —5.0% intensive per doubling of the provider’s degree). Higher local clustering around the main primary care provider reduces the propensity to incur expenses on prescription drugs and emergency care and reduces conditional drug spending, but leaves the remaining categories unaffected.Discussion : Connectedness in primary care, whether measured by the structural position of a patient’s own provider or by the coordination architecture of the community that provider belongs to, is associated with lower spending, concentrated in the diagnostic and pharmaceutical categories where duplication is easiest to avoid. Whether network centralisation is a valid cost-containment instrument should be confirmed by further accompanying evidence on quality, for example using health outcomes to distinguish lower spending from under-provision. |
| Keywords: | Switzerland; healthcare; collaboration; connectedness; integrated care; |
| JEL: | I11 I18 D85 |
| Date: | 2026–08 |
| URL: | https://d.repec.org/n?u=RePEc:yor:hectdg:26/11 |
| By: | Jiahao Weng |
| Abstract: | This study develops an agent-based financial market model to explain stock-price momentum and reversal through the joint effects of local herding and delayed information diffusion. Investors form heterogeneous Gaussian beliefs about the next-period price, choose among buying, selling, and remaining inactive, and revise their action probabilities in response to neighboring investors. The local interaction structure is represented by von Neumann and Moore lattices and is later replaced by Erd\H{o}s--R\'enyi and Watts--Strogatz networks for robustness. A separate information process updates investor beliefs through a finite-speed diffusion mechanism, allowing informational adjustment to be distinguished from behavioral imitation. The simulations show that stronger herding produces spatially clustered trading, larger price fluctuations, and more pronounced excess kurtosis in returns. Faster information diffusion reduces the time required for prices to approach the signal-implied value, whereas the combination of information diffusion and social reinforcement generates overshooting and subsequent reversal. An empirical application to China's A-share market compares conventional CSAD and LSV measures with a rolling tail-based herding indicator obtained after Johnson $S_U$ transformation. The indicators display similar time variation and rise during major market disruptions. These findings identify information delay, local social reinforcement, and the eventual decay of herding as complementary mechanisms behind momentum and reversal. |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2607.27063 |
| By: | Antonova, Anastasiia; Müller, Gernot |
| Abstract: | The defining feature of the New Keynesian model is that goods prices are adjusted infrequently. In the one-sector version of the model, goods are intrinsically homogeneous and should trade at the same price. By targeting inflation, monetary policy can achieve the efficient allocation. In the network version of the model, sectoral shocks call for an adjustment of relative prices and give rise to a trade-off between adjusting relative prices across sectors and maintaining price stability within sectors. Monetary policy alone can no longer achieve the first best. Against this background, we study the optimal tax response to sectoral shocks. It features twice as many tax instruments as there are sectors, is budget-neutral, and is not confined to the sector where the shock originates. A simple rule that targets sectoral inflation approximates the optimal policy well. We illustrate the quantitative relevance of our results using a calibrated version of the model. |
| Keywords: | Network |
| JEL: | E62 |
| Date: | 2024–09 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:19444 |
| By: | Kirill Borusyak; Peter Hull; Evan Munro |
| Abstract: | We study the optimal design and analysis of experiments for estimating spillover effects. Assuming a known (e.g., linear) exposure mapping, we characterize the treatment-assignment distribution and regression-based estimator that minimize worst-case asymptotic variance against a broad class of distributions of unobservables. The design problem yields an intuitive solution in which the planner trades off spillover signal strength against diffusion of spillover variation. The analysis problem yields a simple recentered instrumental variable estimator to best leverage this variation. This framework produces natural solutions in several benchmark cases - such as clustered exposure - and suggests computationally tractable approximations for general networks, including bipartite settings. We illustrate these new tools in semi-synthetic experiments based on two applications from development economics. Our approach yields large standard error reductions in both experiments, increasing effective sample sizes by 50-100% or more. |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2607.18601 |
| By: | Qing, Chen; Dall'Erba, Sandy |
| Abstract: | Domestic grain trade connects geographically uneven production regions, processing centers, and demand markets through regional trade linkages. This paper examines whether U.S. county-level cereal grain trade is spatially interdependent and whether local trade intensity is associated with climate-related moisture conditions in nearby counties. Using a downscaled county-to-county trade network and spatial econometric models, the analysis shows that county-level imports and exports are geographically clustered rather than randomly distributed. Spatial dependence is more pronounced for exports than for imports, suggesting that export intensity is more closely tied to regional production clusters and neighboring trade activity. Growing-season SPEI, measured relative to historical norms, is also associated with trade intensity beyond local county boundaries. In particular, neighboring counties’ SPEI is negatively associated with local import and export intensity. Overall, the results suggest that domestic grain trade functions as a regional spatial system rather than a set of independent local markets, highlighting the importance of regional linkages in county-level grain trade. |
| Keywords: | Community/Rural/Urban Development |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:ags:aaea26:404760 |