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Analysis of Multiple Long Run Relations in Panel Data Models with Applications to Financial Ratios
Alexander Chudik, M. Hashem Pesaran, Ron P. Smith
https://arxiv.org/abs/2506.02135

Analysis of Multiple Long Run Relations in Panel Data Models with Applications to Financial Ratios
This paper provides a new methodology for the analysis of multiple long run relations in panel data models where the cross section dimension, $n$, is large relative to the time series dimension, $T$. For panel data models with large $n$ researchers have focused on panels with a single long run relationship. The main difficulty has been to eliminate short run dynamics without generating significant uncertainty for identification of the long run. We overcome this problem by using non-overlapping …

Sen. Mike Lee faces criticism over posts on Minnesota shooting (Allison Pecorin/ABC News)
https://abcnews.go.com/Politics/sen-mike-lee-faces-criticism-posts-minnesota-shooting/story?id=122930819
http://www.memeorandum.com/250617/p125#a250617p125

Decision-making in light-trapped slime molds involves active mechanical processes
Lisa Schick, Emily Eichenlaub, Fabian Drexel, Alexander Mayer, Siyu Chen, Marcus Roper, Karen Alim
https://arxiv.org/abs/2506.12803

Decision-making in light-trapped slime molds involves active mechanical processes
Decision-making is the process of selecting an action among alternatives, allowing biological and artificial systems to navigate complex environments and optimize behavior. While neural systems rely on neuron-based sensory processing and evaluation, decision-making also occurs in organisms without a centralized organizing unit, such as the unicellular slime mold \textit{Physarum polycephalum}. Unlike neural systems, P. polycephalum relies on rhythmic peristaltic contractions to drive internal f…

Fast Geometric Embedding for Node Influence Maximization
Alexander Kolpakov, Igor Rivin
https://arxiv.org/abs/2506.07435 https://arxi…

Fast Geometric Embedding for Node Influence Maximization
Computing classical centrality measures such as betweenness and closeness is computationally expensive on large-scale graphs. In this work, we introduce an efficient force layout algorithm that embeds a graph into a low-dimensional space, where the radial distance from the origin serves as a proxy for various centrality measures. We evaluate our method on multiple graph families and demonstrate strong correlations with degree, PageRank, and paths-based centralities. As an application, it turns …