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Dynamic heterogeneity is now recognised as a central aspect of structural relaxation in disordered materials with slow dynamics, and was the focus of intense research in the last decade. Here we describe how initial, indirect observations…

Statistical Mechanics · Physics 2010-09-28 Ludovic Berthier , Giulio Biroli , Jean-Philippe Bouchaud , Robert L Jack

This study considers various semiparametric difference-in-differences models under different assumptions on the relation between the treatment group identifier, time and covariates for cross-sectional and panel data. The variance lower…

Econometrics · Economics 2020-08-17 Michael Zimmert

Long-term causal inference has drawn increasing attention in many scientific domains. Existing methods mainly focus on estimating average long-term causal effects by combining long-term observational data and short-term experimental data.…

Machine Learning · Computer Science 2025-03-04 Weilin Chen , Ruichu Cai , Junjie Wan , Zeqin Yang , José Miguel Hernández-Lobato

A new approach to defining the effective fracture toughness for heterogeneous materials is proposed. This temporal averaging approach is process-dependent, incorporating the crack velocity and material toughness. The effectiveness of the…

Geophysics · Physics 2022-07-14 Gaspare Da Fies , Daniel Peck , Martin Dutko , Gennady Mishuris

In this paper, we focus on exploiting the group structure for large-dimensional factor models, which captures the homogeneous effects of common factors on individuals within the same group. In view of the fact that datasets in…

Methodology · Statistics 2024-05-14 Yong He , Xiaoyang Ma , Xingheng Wang , Yalin Wang

Learning heterogeneous treatment effects (HTEs) is an important problem across many fields. Most existing methods consider the setting with a single treatment arm and a single outcome metric. However, in many real world domains, experiments…

Machine Learning · Computer Science 2022-06-13 Leon Yao , Caroline Lo , Israel Nir , Sarah Tan , Ariel Evnine , Adam Lerer , Alex Peysakhovich

We explore fairness from a statistical perspective by selectively utilizing either conditional distance covariance or distance covariance statistics as measures to assess the independence between predictions and sensitive attributes. We…

Machine Learning · Computer Science 2025-12-22 Ruifan Huang , Haixia Liu

This paper introduces a causal machine learning approach to investigate the impact of the EU-Canada Comprehensive Economic Trade Agreement (CETA). We propose a matrix completion algorithm on French customs data to obtain multidimensional…

General Economics · Economics 2025-05-01 Lionel Fontagné , Francesca Micocci , Armando Rungi

We formulate a continuous-time competitive equilibrium model of irreversible capacity investment in which a continuum of heterogeneous producers supplies a single non-durable good subject to exogenous stochastic demand. Each producer…

Probability · Mathematics 2025-12-04 Constantinos Kardaras , Alexandros Pavlis , Mihail Zervos

This paper constructs individual-specific density forecasts for a panel of firms or households using a dynamic linear model with common and heterogeneous coefficients as well as cross-sectional heteroskedasticity. The panel considered in…

Econometrics · Economics 2021-10-06 Laura Liu

The modelling of heterogeneous and architected materials poses a significant challenge, demanding advanced homogenisation techniques. However, the complexity of this task can be considerably simplified through the application of micropolar…

Soft Condensed Matter · Physics 2024-02-27 Adrianos E. F. Athanasiadis , Michal K. Budzik , Dilum Fernando , Marcelo A. Dias

A meta-model of the input-output data of a computationally expensive simulation is often employed for prediction, optimization, or sensitivity analysis purposes. Fitting is enabled by a designed experiment, and for computationally expensive…

Methodology · Statistics 2023-12-01 Andrew Gill , David J. Warne , Antony M. Overstall , Clare McGrory , James M. McGree

The estimation of heterogeneous treatment effects in the potential outcome setting is biased when there exists model misspecification or unobserved confounding. As these biases are unobservable, what model to use when remains a critical…

Methodology · Statistics 2024-05-09 Shonosuke Sugasawa , Kosaku Takanashi , Kenichiro McAlinn , Edoardo M. Airoldi

We present an approach to estimate distance-dependent heterogeneous associations between point-referenced exposures to built environment characteristics and health outcomes. By estimating associations that depend non-linearly on distance…

Methodology · Statistics 2021-07-14 Adam Peterson , Emma Sanchez-Vaznaugh , Brisa Sanchez

Optimal pricing, i.e., determining the price level that maximizes profit or revenue of a given product, is a vital task for the retail industry. To select such a quantity, one needs first to estimate the price elasticity from the product…

Econometrics · Economics 2022-01-12 Jianqing Fan , Ricardo P. Masini , Marcelo C. Medeiros

This paper presents a new nested production function that is specifically designed for analyzing capital and labor intensity of manufacturing industries in developing and developed regions. The paper provides a rigorous theoretical…

Theoretical Economics · Economics 2023-03-28 Samidh Pal

We introduce a two-parameter ensemble of random discrete-time Markov models that simultaneously captures critical slowing down and broken detailed balance. Extending a previously studied heterogeneous Markov ensemble, we incorporate…

Disordered Systems and Neural Networks · Physics 2026-02-06 Faheem Mosam , Eric De Giuli

In the analysis of binary longitudinal data, it is of interest to model a dynamic relationship between a response and covariates as a function of time, while also investigating similar patterns of time-dependent interactions. We present a…

Methodology · Statistics 2023-04-11 Jinwon Sohn , Seonghyun Jeong , Young Min Cho , Taeyoung Park

Recent improvements in additive manufacturing and high-throughput material synthesis have enabled the discovery of novel metallic materials for extreme environments. However, high-fidelity testing of advanced mechanical properties such as…

Materials Science · Physics 2025-02-20 C. Bean , M. Calvat , Y. Nie , R. L Black , N. Velisavljevic , D. Anjaria , M. A. Charpagne , J. C. Stinville

We incorporate a version of a spike and slab prior, comprising a pointmass at zero ("spike") and a Normal distribution around zero ("slab") into a dynamic panel data framework to model coefficient heterogeneity. In addition to homogeneity…

Econometrics · Economics 2024-02-07 Hyungsik Roger Moon , Frank Schorfheide , Boyuan Zhang