Tootfinder

This https://arxiv.org/abs/2303.11721 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_eco…

Using Forests in Multivariate Regression Discontinuity Designs
We discuss estimation and inference of conditional treatment effects in regression discontinuity (RD) designs with multiple scores. In addition to local linear regressions and the minimax-optimal estimator more recently proposed by Imbens and Wager (2019), we argue that two variants of random forests, honest regression forests and local linear forests, should be added to the toolkit of applied researchers working with multivariate RD designs; their validity follows from results in Wager and Ath…

The existence and uniqueness of Hashiguchi connection in KG-approach
S. G. Elgendi, A. Soleiman
https://arxiv.org/abs/2506.09739 https://

The existence and uniqueness of Hashiguchi connection in KG-approach
In this study, we treat intrinsic Finsler geometry using the Klein-Grifone approach (KG-approach). A uniqueness and existence theorem for the Hashiguchi connection on a Finsler manifold is investigated intrinsically (in coordinate-free fashion). Calculations are made for the Hashiguchi connection's torsion and curvature tensors. Some properties are examined, together with the Bianchi identities of the associated curvature and torsion tensors. An overview of the four fundamental linear connectio…

Inference on the value of linear programs
Leonard Goff, Eric Mbakop
https://arxiv.org/abs/2506.06776 https://arxiv.org/pdf/2506.06776…

Inference on the value of linear programs
This paper studies inference on the value of linear programs (LPs) when both the objective function and constraints are possibly unknown and must be estimated from data. We show that many inference problems in partially identified models can be reformulated in this way. Building on Shapiro (1991) and Fang and Santos (2019), we develop a pointwise valid inference procedure for the value of LPs. We modify this pointwise inference procedure to construct one-sided inference procedures that are unif…

Potential absence of observed $\pi^2$ linear-chain structures in $^{14}$O via $^{10}$C($\alpha,\alpha$) resonant scattering
J. Bishop, A. Hollands, Tz. Kokolova, G. V. Rogachev, C. Wheldon, E. Aboud, S. Ahn, M. Barbui, N. Curtis, J. Hooker, C. Hunt, H. Jayatissa, E. Koshchiy, S. Pirrie, B. T. Roeder, A. Saastamoinen, S. Upadhyayula
https://

Potential absence of observed $π^2$ linear-chain structures in $^{14}$O via $^{10}$C($α,α$) resonant scattering
Background: The preference for light nuclear systems to coagulate into $α$-particle clusters has been well-studied. The possibility of a linear chain configuration of $α$-particles would allow for a new way to study this phenomenon. Purpose: A rotational band of states in $^{14}$C has been claimed showing a $π^2$ linear chain structure. The mirror system, $^{14}$O, has been studied here to examine how this linear chain structure is affected by replacing the valence neutrons with protons. Met…

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients
Iosif Lytras, Sotirios Sabanis, Ying Zhang
https://arxiv.org/abs/2506.04878

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients
Motivated by applications in deep learning, where the global Lipschitz continuity condition is often not satisfied, we examine the problem of sampling from distributions with super-linearly growing log-gradients. We propose a novel tamed Langevin dynamics-based algorithm, called kTULA, to solve the aforementioned sampling problem, and provide a theoretical guarantee for its performance. More precisely, we establish a non-asymptotic convergence bound in Kullback-Leibler (KL) divergence with the …

The Spurious Factor Dilemma: Robust Inference in Heavy-Tailed Elliptical Factor Models
Jiang Hu, Jiahui Xie, Yangchun Zhang, Wang Zhou
https://arxiv.org/abs/2506.05116

The Spurious Factor Dilemma: Robust Inference in Heavy-Tailed Elliptical Factor Models
Factor models are essential tools for analyzing high-dimensional data, particularly in economics and finance. However, standard methods for determining the number of factors often overestimate the true number when data exhibit heavy-tailed randomness, misinterpreting noise-induced outliers as genuine factors. This paper addresses this challenge within the framework of Elliptical Factor Models (EFM), which accommodate both heavy tails and potential non-linear dependencies common in real-world da…

Exacerbation of viscoelastic instability due to viscous heating
Ankush Kamboj, Ramkarn Patne, P. A. L. Narayana, Kirti Chandra Sahu
https://arxiv.org/abs/2506.04617

Exacerbation of viscoelastic instability due to viscous heating
The linear stability analysis of the pressure-driven flow of an Oldroyd-B fluid through a plane channel is performed to examine the effects of viscous heating-induced buoyancy on the ``purely elastic instability" predicted by \citet{khalid2021continuous} (Phys. Rev. Lett., 2021, 127, 134502). We do not impose any external heating; rather, the temperature increase in the system is solely due to the viscous heating generated by the flow of a highly viscous fluid, which induces buoyancy. This buoy…

This https://arxiv.org/abs/2412.04115 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Special Divisors on Real Trigonal Curves
In this paper we examine the topology of Brill-Noether varieties associated to real trigonal curves. More precisely, we aim to count the connected components of the real locus of the varieties parametrizing linear systems of degree $d$ and dimension at least $r$. We do this count when the relations $m=g-d+r-1\leq d-2r-1$ are satisfied, where $m$ is the Maroni invariant and $g$ is the genus of the curve.

Teaching Mathematics for Economists
Eric Hillebrand
https://arxiv.org/abs/2505.22671 https://arxiv.org/pdf/2505.22671

Teaching Mathematics for Economists
In this chapter, I discuss teaching mathematical tools specifically tailored for economics students. A typical one-semester course in this area seeks to blend a range of topics: from foundational elements of subjects such as linear algebra and multivariate calculus to intermediate areas like real and convex analysis and further into advanced topics such as dynamic optimization in both continuous and discrete time. This breadth of coverage corresponds to material usually spread across multiple y…

This https://arxiv.org/abs/2502.16673 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

On the asymptotic validity of confidence sets for linear functionals of solutions to integral equations
This paper examines the construction of confidence sets for parameters defined as linear functionals of a function of W and X whose conditional mean given Z and X equals the conditional mean of another variable Y given Z and X. Many estimands of interest in causal inference can be expressed in this form, including the average treatment effect in proximal causal inference and treatment effect contrasts in instrumental variable models. We derive a necessary condition for a confidence set to be un…