arXiv subjects

Gergely Horvath

Publications and source records attributed to Gergely Horvath.

4 recordsLinked to original sources

arXiv2026

Is Decentralized Finance Actually Decentralized? An Interdisciplinary Framework Integrating Network Theory, Agent-Based Simulation, and Longitudinal Evidence from Aave, GHO Issuance, and Cross-Chain Expansion

Decentralized finance (DeFi) can broaden access while leaving activity, network position, and infrastructure concentrated. We develop a four-dimensional framework for participation, activity distribution, structural position, and infrastructure dependence, integrating network theory, theorem-consistent agent-based simulation, and longitudinal analysis of 1,956,216 Aave V3 Pool events. We study GHO issuance on Ethereum (15 July 2023) and its first cross-chain expansion to Aave's existing Arbitrum market (2 July 2024). Excluding each activation week, mean weekly active position-holder addresses increased by 91.0% around Ethereum issuance and 1.7% around Arbitrum expansion, while activity concentration fell by 31.5% on Ethereum but rose by 58.1% on Arbitrum. On a common 2024 calendar, the Arbitrum--Gnosis DiD-style change is +1.9833 for log participation and -0.01842 for position-holder-event HHI. Rule-based simulations recover the analytical equilibrium and show why aggregate growth can coexist with lower, unchanged, or higher concentration, while chain dispersion alone cannot establish route or shared-component resilience. Role-aware analysis further shows that network-structure conclusions vary by protocol action and scale. Intellectually, the framework explains why four dimensions of decentralization can diverge. Practically, it helps researchers, protocol designers, governance communities, and policymakers assess stablecoin growth without equating adoption with decentralization.

econ.GN↗

arXiv2024

The impact of social status on the formation of collaborative ties and effort provision: An experimental study

We study whether competition for social status induces higher effort provision and efficiency when individuals collaborate with their network neighbors. We consider a laboratory experiment in which individuals choose a costly collaborative effort and their network neighbors. They benefit from their neighbors' effort and effort choices of direct neighbors are strategic complements. We introduce two types of social status in a 2x2 factorial design: 1) individuals receive monetary benefits for incoming links representing popularity; 2) they receive feedback on their relative payoff ranking within the group. We find that link benefits induce higher effort provision and strengthen the collaborative ties relative to the Baseline treatment without social status. In contrast, the ranking information induces lower effort as individuals start competing for higher ranking. Overall, we find that social status has no significant impact on the number of links in the network and the efficiency of collaboration in the group.

econ.GN↗

arXiv2024

Network formation and efficiency in linear-quadratic games: An experimental study

We experimentally study effort provision and network formation in the linear-quadratic game characterized by positive externality and complementarity of effort choices among network neighbors. We compare experimental outcomes to the equilibrium and efficient allocations and study the impact of group size and linking costs. We find that individuals overprovide effort relative to the equilibrium level on the network they form. However, their payoffs are lower than the equilibrium payoffs because they create fewer links than it is optimal which limits the beneficial spillovers of effort provision. Reducing the linking costs does not significantly increase the connectedness of the network and the welfare loss is higher in larger groups. Individuals connect to the highest effort providers in the group and ignore links to relative low effort providers, even if those links would be beneficial to form. This effect explains the lack of links in the network.

econ.GN↗

arXiv2022

Skill requirements in job advertisements: A comparison of skill-categorization methods based on explanatory power in wage regressions

In this paper, we compare different methods to extract skill requirements from job advertisements. We consider three top-down methods that are based on expert-created dictionaries of keywords, and a bottom-up method of unsupervised topic modeling, the Latent Dirichlet Allocation (LDA) model. We measure the skill requirements based on these methods using a U.K. dataset of job advertisements that contains over 1 million entries. We estimate the returns of the identified skills using wage regressions. Finally, we compare the different methods by the wage variation they can explain, assuming that better-identified skills will explain a higher fraction of the wage variation in the labor market. We find that the top-down methods perform worse than the LDA model, as they can explain only about 20% of the wage variation, while the LDA model explains about 45% of it.

econ.GN↗