arXiv preprints from January 1, 2026 through September 23, 2026 — 07:09:14 EST
This paper proposes a metric approach to measuring the complexity of lotteries. Starting by observing that degenerate lotteries are the simplest choice alternatives, the complexity of a lottery is evaluated by its distance from the closest degenerate lottery. Equivalently, a lottery is complex when it is difficult to approximate it by...
AI is increasingly being used to help with AI R&D. Under certain conditions this feedback loop might be able to produce an intelligence explosion, with rapidly escalating AI capabilities. I explore the mathematics of the most explosive possibilities, with an eye to understanding what drives the dynamics. I show that singular growth...
This paper studies how information censoring enables a myopic cutoff rule in Bayesian sequential search. Under full information, Bayesian learning generally destroys the monotonicity of continuation values, preventing simple cutoff rules. We show that one-sided censoring restores monotonicity by limiting posterior fluctuations,...
This paper employs a Threshold Bayesian Vector Autoregression (TBVAR) to estimate the regime-dependent macroeconomic effects of capital regulation in Hungary. Using the Factor-based Index of Systemic Stress (FISS) as the threshold variable, the model identifies normal and stress regimes consistent with the occasionally binding...
We formulate the voter's strategic information acquisition to control the future self's action as a Bayesian persuasion problem. Our main result shows that acquiring information that is irrelevant to the voter's objective can be a \textit{worst-case optimal} solution: it can reduce the possibility that the future self is swayed by...
Academic freedom has come under growing strain worldwide. To study whether and how academics respond to political pressure, we exploit a natural experiment: the publication in early 2025 of a "blacklist" of words flagged by the U.S. government. We find that the release of this list led to a sharp reduction in the use of these flagged...
Ownership matters for the media's watchdog role. We map the ownership networks behind thousands of online news outlets in the U.S., Canada, and Europe. The networks reveal who is ultimately responsible for the news: for over half of the outlets, a single entity. The rest sit behind multi-layered structures, making responsibility hard...
We develop an axiomatic model of robust Bayesian persuasion where the sender cannot fully control the information available to the receiver. After selecting an information structure, the sender expects that more informative structures might be implemented. We model this by allowing the sender to assess each information structure under...
We develop a model of interbank networks with random liquidity shocks. Networks of dilutable debt---e.g., long-term, unsecured---facilitate efficient liquidity transfers: Shocked banks pledge interbank claims as collateral for new senior debt, diluting existing debt. Unlike with non-dilutable debt, indebtedness and connectedness are...
We develop a method for estimating and testing a single block of a macroeconomic model with heterogeneous agents, without placing assumptions on the structure of the rest of the economy. In a large class of models, individual agents' decisions depend on the macroeconomy only through their expectations of the evolution of a...
While technological innovations typically increase wage inequality by favoring skilled workers, we show that instant payment systems instead reduce it. We study the labor market effects of instant payment systems in the context of Brazil's Pix rollout. Using matched employer-employee data, we implement a triple-difference design that...
Limited dependent variable models are central to empirical economics, but likelihood-based inference is infeasible when likelihoods involve high-dimensional integration over latent variables. This paper proposes Stochastically Estimated Gradient Ascent (SEGA), a scalable estimation approach for limited dependent variable models. Using...
We study minimax-optimal designs and estimators for estimating the sample average treatment effect in finite population randomized experiments, where both design and estimator are unrestricted. For binary potential outcomes, we show this minimax risk is equivalent to the minimax risk $ρ_n^*$ of an estimation problem with $2$ unknown...
Pawn loans offer borrowers a substantial degree of repayment flexibility in exchange for a harsh penalty in case of default: forfeit of collateral worth more than the loan amount along with any payments made toward recovery. Using a large RCT conducted in Mexico City, we document key stylized facts about pawn lending and explore the...
A single clinical algorithm can deliver unequal accuracy across patient groups, and concern about such disparity has grown as artificial intelligence (AI) spreads through clinical decision-making. In response, a liability rule introduced in the United States holds healthcare providers responsible when their reliance on disparate...
We study the sensitivity of IceCube to blazar-boosted dark matter in a fermionic dark matter model with a massive vector mediator coupling to quarks. To this aim, we compute the diffuse flux arising from a sample of 324 blazars with proton spectra inferred from multiwavelength observations, adopting conservative dark matter spike...
We introduce the problem of designing mechanisms that incentivize strategic agents to form self-funded marketplaces. In our model, if agent $i$ exerts effort $x_i\in [0,1]$, they incur a cost of $x_i\cdot c_i$ (where $c_i$ is unknown to the mechanism designer) and they generate revenue $x_i\cdot r_i$; crucially, $c_i$ can be greater...
The search for Galactic sources capable of accelerating cosmic rays (CRs) to PeV energies has advanced significantly in recent years. High-energy observatories such as LHAASO have detected extended gamma-ray halos around several sources, suggesting that CRs escape their acceleration sites through anomalously slow diffusion....
With the rapid advancement of image editing models and their widespread application across various domains, there is an increasingly urgent need to deploy these model capabilities directly into real-world scenarios. However, existing benchmarks remain confined to simple single-image tasks, suffering from limited coverage dimensions...
We introduce the notion of a "compressive domain" for the action of a rational function on the Berkovich projective line over a complete nontrivially-valued algebraically closed nonarchimedean field. We prove that such a domain always contains a classical fixed point, and we leverage this fact to give a sharp upper bound for the...
We implemented on GPU a mixed quantum-classical Liouville molecular dynamics simulation based on a momentum-jump-free theory. The trajectory spawning that was previously implemented on CPU for sampling enhancement was eliminated to avoid the overhead of thread divergence and dynamic memory allocation on the GPU. This achieved a...
High-resolution image restoration from degraded inputs is challenging because it must preserve global structural consistency while recovering fine-grained local details, especially at 4K resolution where direct diffusion-based restoration is computationally expensive and prone to repeated or inconsistent textures. In this work, we...
Modern generative models increasingly produce distribution-valued outputs, such as predicted cellular responses to genetic perturbations in single-cell genomics. While these models provide valuable auxiliary information, they are inherently imperfect, creating a need for statistical methods that leverage their predictions without...
Consider level-$k$ $SL(2,R) \times SL(2,R)$ Chern-Simons theory on a semi-infinite solid cylinder, with a Wilson line in the unitary principal continuous series inserted along the time direction at the center of the spatial disc. We argue that at the $τ=0$ cut, this Euclidean path integral prepares the bulk dual of a heavy Virasoro...
We show that a mass-Hom bound for a numerical pre-stability condition on a projective scheme over a field implies the support property with respect to the full numerical Grothendieck group. Combined with the recent construction of stability conditions on projective schemes, this yields stability conditions with full support property...