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on Network Economics |
| By: | Michael Greinecker; Karolina Vocke |
| Abstract: | We study stability notions for networked many-to-many matching markets with individually insignificant agents in distributional form. Outcomes are formulated as joint distributions over characteristics of agents and contract choices. Characteristics can lie in an arbitrary Polish space. We provide a mechanical method for transferring existence results for finite matching models to large matching models for many stability notions. In particular, we show that tree-stable and pairwise-stable outcomes exist. |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2604.26902 |
| By: | Zizhong Yan; Jingrong Li; Yi Zhang |
| Abstract: | Estimating network formation models with degree heterogeneity raises two problems in empirical networks. First, agents that send no links, receive no links, or link to all remaining agents can make the fixed-effects MLE fail to exist. Trimming these agents changes the estimation sample and induces selection bias. Second, the incidental-parameter problem biases common parameters and average partial effects. We resolve both issues through a penalized likelihood approach. Our leading specification is a directed network model with reciprocity, nesting the standard undirected and non-reciprocal directed models. The penalty guarantees finite-sample existence and yields bias corrections for coefficients and partial effects. We establish asymptotic results without imposing compactness on the fixed-effects. Allowing the fixed effects to diverge at a logarithmic rate, our asymptotic framework accommodates the degree sparsity ubiquitous in large empirical networks. A global trade application demonstrates that our estimator avoids selection bias and recovers robust parameters where conventional methods fail. |
| Date: | 2026–05 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2605.00771 |
| By: | Yeqing Duan (Department of Political Science, Lund University); Nils Droste (Department of Food and Resource Economics, University of Copenhagen); Brian Danley (Department of Earth Sciences, Natural Resources and Sustainable Development, Uppsala University) |
| Abstract: | Land use transition toward multifunctional practices is greatly affected by social learning, yet the temporal interaction between learning mechanisms and network structure remains underexplored. This study examines two social learning channels, information exchange and normative pressure, and how network architecture shapes their effects on transition outcomes. We developed SALT (Social learning in Agent-based Land use Transitions), a spatially explicit model that integrates the Consumat framework and reinforcement learning. The model is parameterized using a Swedish forestry context, simulating landowner adaptive decisions under integrated and modular social networks. Results show that the two channels play distinct roles across transition phases. Lack of knowledge limits adoption in early adoption. Individual experience is the main source of knowledge accumulation, and social learning alone cannot close the knowledge gap. As adoption spreads, normative pressure constrains implementation intensity to the prevailing local average, explaining the gap between behavioral and actual landscape changes. Network architecture shapes both channels. Integrated networks widen information exchange and allow alternative-use norms to strengthen over time, while modular networks restrict information circulation and lock in low-implementation local norms. Landscape change organizes along social ties rather than geographic proximity, with architecture determining whether adoption clusters into cohesive blocks or disperses as a diffuse mosaic in the social network. Landowner types contribute differently to behavior change and landscape change across both architectures. These findings suggest that effective transition governance must be tailored to both phase and social context. Early interventions should prioritize technical assistance, while raising the visible norm of implementation intensity matters more as adoption spreads. In modular communities, consolidating norms within communities before extending outreach is more effective than diffuse seeding. Instruments targeting behavior change need to be paired with those that directly support implementation intensity of alternative practice among less conformity-constrained landowners. |
| Keywords: | Land use transition; Social learning; Social network structure; Agent-based modelling; Multifunctional landscape |
| JEL: | C63 D83 Q24 Q57 |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:foi:wpaper:2026_01 |
| By: | Giacomo Como; Fabio Fagnani; Elisa Luciano; Alessandro Milazzo; Marco Scarsini |
| Abstract: | This paper studies the transmission of productivity shocks in general equilibrium production networks, when firms in different sectors operate under informational rigidity and rely on external debt. Rigidity breaks the Modigliani-Miller irrelevance of leverage and may generate default following shocks, even in equilibrium. The economy consists of firms, banks, and consumers. Under proportional shock transmission, we prove that a unique Walrasian rigid equilibrium exists and provide explicit expressions for equilibrium quantities, prices, and interest rates. We show that, on the one hand, Hulten's theorem fails under rigidity, even without leverage. On the other hand, we prove that welfare is smaller than in the first best if and only if both leverage and rigidity exist. The latter increase the total cost of debt and have inflationary effects on the levered sectors, which propagate downstream, and shift consumption and labor upstream. The occurrence of default depends solely on real shocks and the network structure, while the magnitude of the losses depends also on the connectedness of the economy and the cost of debt of the connected sectors. We provide conditions for default cascades to occur and study two examples of default propagation. |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2604.23566 |
| By: | Ying-Hui Shao; Yan-Hong Yang; Yun Zhang |
| Abstract: | Connectedness measures quantify aggregate risk spillovers but obscure the local interaction patterns that generate systemic risk. We develop a motif-based framework that first extracts multiscale backbones from quantile connectedness networks and then identifies directed triadic motifs whose frequencies exceed randomization baselines. To distinguish how assets' sectoral identities shape local spillover structures, we introduce colored motifs under sector partitions of increasing granularity. Using orbit positions that capture each node's structural role within directed triadic motifs, we construct portfolio strategies that exploit an asset's place in the spillover architecture. Applying the framework to 39 commodity and equity futures across lower, median, and upper conditional quantiles, we find that motif-based portfolios outperform minimum correlation and minimum connectedness benchmarks on risk-adjusted returns. We further show that in tail networks, assets with greater orbit-position diversity tend to act as net spillover transmitters rather than receivers, establishing positional diversity as a tail-specific marker of systemic influence. These findings demonstrate that local triadic topology carries portfolio-relevant information that aggregate connectedness measures miss. |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2604.25406 |
| By: | Pietro Dall'Ara |
| Abstract: | Coordination is an important aspect of innovative contexts, where: the more innovative a course of action, the more uncertain its outcome. To study the interplay of coordination and informational ``complexity'', I embed a beauty-contest game into a complex environment. I identify a new conformity phenomenon. This effect may push towards the exploration of unknown alternatives or constitute a status-quo bias, depending on the network structure of players' interactions. In an application, I show that an organization with decentralized authority can implement profit maximization in a sufficiently complex environment. |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2604.24757 |
| By: | Boeing, Geoff (Northeastern University) |
| Abstract: | Urban planners need up-to-date, global, and consistent street network models and indicators to measure resilience and performance, model accessibility, and target local quality-of-life interventions. This article presents up-to-date street network models and indicators for every urban area in the world. It uses 2025 urban area boundaries from the Global Human Settlement Layer, allowing users to join these data to hundreds of other urban attributes. Its workflow ingests 180 million OpenStreetMap nodes and 360 million OpenStreetMap edges across 10, 351 urban areas in 189 countries. The code, models, and indicators are publicly available for reuse. These resources unlock worldwide urban street network science beyond samples as well as local analyses in under-resourced regions where models and indicators are otherwise less-accessible. |
| Date: | 2026–05–01 |
| URL: | https://d.repec.org/n?u=RePEc:osf:socarx:z9cqh_v1 |
| By: | Avishek Bhandari; Ipsita Parida; Hitesh Kumar Sahu |
| Abstract: | We address the joint detection-and-attribution problem in cross-border financial contagion through a two-stage framework. The first stage applies wavelet-quantile transfer entropy across time-scales and lower, median, and upper-tail quantiles. The second stage attributes each significant link to one of five channels comprising of i) Trade, ii) Financial, iii) Geopolitical, iv) Behavioural, and v) Monetary Policy, via instrumental-variables two-stage least squares with channel-specific external instruments, LASSO-based instrument selection (Belloni, Chernozhukov and Hansen, 2014), local projections at one-, five-, and twenty-two-day horizons (Jorda, 2005), heteroskedasticity-based identification (Rigobon, 2003) for episodes in which over-identification is rejected, and Cinelli-Hazlett (2020) sensitivity bounds. The framework is applied to 18 G20 equity markets across eight crisis sub-periods spanning January 2006 to March 2026. Network density varies meaningfully across sub-periods (range 14% to 32%). Dominant-channel identification is robust across methods in the Pre-Crisis baseline and the European Sovereign Debt Crisis, both dominated by financial frictions; for the remaining six episodes identification is method-sensitive, and we report the share posterior alongside an explicit identification-status classification. Trade is empirically prominent across all post-2007 episodes, ranging from 9% during Pre-Crisis to 28% during the Global Financial Crisis. The behavioural channel is bounded above by 22% across all eight episodes under the de-confounded composite. The framework provides a methodologically disciplined account of cross-border contagion mechanisms and offers identification-status disclosure not systematically present in the existing literature. |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2604.26546 |