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Related papers: Demand Modeling, Forecasting, and Counterfactuals,…

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Proceeding from the concept of rational expectations, a new dynamic model of supply and demand in a single market with one supplier, one buyer, and one kind of commodity is developed. Unlike the cob-web dynamic theories with adaptive…

General Physics · Physics 2007-05-23 V. Granik , A. Granik

In many situations people make sequences of similar, but unrelated decisions. Such decision sequences are prevalent in many important contexts including judicial judgments, loan approvals, college admissions, and athletic competitions. A…

General Economics · Economics 2024-08-13 Katja Bergonzoli , Laurent Bieri , Dominic Rohner , Christian Zehnder

Counterfactual explanations study what should have changed in order to get an alternative result, enabling end-users to understand machine learning mechanisms with counterexamples. Actionability is defined as the ability to transform the…

Artificial Intelligence · Computer Science 2025-08-05 Enrique Valero-Leal , Pedro Larrañaga , Concha Bielza

We build simple computational models of belief dynamics within the framework of discrete-spin statistical physics models, and explore how suitable they are for understanding and predicting real-world belief change on both the individual and…

Physics and Society · Physics 2018-07-10 Mirta Galesic , Daniel L. Stein

In school choice, students make decisions based on their expectations of particular schools' suitability, and the decision to gather information about schools is influenced by the acceptance odds determined by the mechanism in place. We…

Theoretical Economics · Economics 2023-03-15 SangMok Lee

Demand forecasting is a central component of the replenishment process for retailers, as it provides crucial input for subsequent decision making like ordering processes. In contrast to point estimates, such as the conditional mean of the…

Machine Learning · Computer Science 2021-07-23 F. Wick , U. Kerzel , M. Hahn , M. Wolf , T. Singhal , D. Stemmer , J. Ernst , M. Feindt

Demand-Response (DR) programs, whereby users of an electricity network are encouraged by economic incentives to rearrange their consumption in order to reduce production costs, are envisioned to be a key feature of the smart grid paradigm.…

Optimization and Control · Mathematics 2016-12-15 Alberto Benegiamo , Patrick Loiseau , Giovanni Neglia

Demand functions for goods are generally cyclical in nature with characteristics such as trend or stochasticity. Most existing demand forecasting techniques in literature are designed to manage and forecast this type of demand functions.…

Applications · Statistics 2011-10-04 Murphy Choy , Michelle L. F. Cheong

Many of the observations we make are biased by our decisions. For instance, the demand of items is impacted by the prices set, and online checkout choices are influenced by the assortments presented. The challenge in decision-making under…

Machine Learning · Computer Science 2025-07-02 Rares Cristian , Pavithra Harsha , Georgia Perakis , Brian Quanz

Evaluation of counterfactual queries (e.g., "If A were true, would C have been true?") is important to fault diagnosis, planning, determination of liability, and policy analysis. We present a method of revaluating counterfactuals when the…

Artificial Intelligence · Computer Science 2013-02-21 Alexander Balke , Judea Pearl

The behavior of users in relatively predictable, both in terms of the data they request and the wireless channels they observe. In this paper, we consider the statistics of such predictable patterns of the demand and channel jointly across…

Information Theory · Computer Science 2018-06-14 L. Srikar Muppirisetty , John Tadrous , Atilla Eryilmaz , Henk Wymeersch

Intertemporal choices involve making decisions that require weighing the costs in the present against the benefits in the future. One specific type of intertemporal choice is the decision between purchasing an individual item or opting for…

Information Retrieval · Computer Science 2023-09-20 Qingming Li , H. Vicky Zhao

Counterfactual explanations are usually obtained by identifying the smallest change made to an input to change a prediction made by a fixed model (hereafter called sparse methods). Recent work, however, has revitalized an old insight: there…

Machine Learning · Computer Science 2020-06-24 Martin Pawelczyk , Klaus Broelemann , Gjergji Kasneci

In this study, I investigate the dynamic decision problem with a finite parameter space when the functional form of conditional expected rewards is misspecified. Traditional algorithms, such as Thompson Sampling, guarantee neither an…

Econometrics · Economics 2025-05-22 Xinyu Dai

We derive a formal, decision-based method for comparing the performance of counterfactual treatment regime predictions using the results of experiments that give relevant information on the distribution of treated outcomes. Our approach…

Methodology · Statistics 2019-07-24 Michael Gechter , Cyrus Samii , Rajeev Dehejia , Cristian Pop-Eleches

We address a practical problem ubiquitous in modern marketing campaigns, in which a central agent tries to learn a policy for allocating strategic financial incentives to customers and observes only bandit feedback. In contrast to…

Machine Learning · Statistics 2019-11-12 Romain Lopez , Chenchen Li , Xiang Yan , Junwu Xiong , Michael I. Jordan , Yuan Qi , Le Song

Tabular foundation models achieve strong accuracy on choice prediction tasks, but their predictions often violate the economic logic those tasks require: raising a price sometimes increases predicted demand, and implied willingness-to-pay…

Machine Learning · Computer Science 2026-05-27 Yingshuo Wang , Xian Sun , Yanhang Li , Zhichao Fan , Zexin Zhuang

One of the exciting developments in the stated preference literature is the use of probabilistic stated preference experiments to estimate semi-parametric population distributions of ex ante returns and willingness-to-pay (WTP) for a choice…

Econometrics · Economics 2025-05-09 Romuald Meango , Esther Mirjam Girsberger

Structural models that admit multiple reduced forms, such as game-theoretic models with multiple equilibria, pose challenges in practice, especially when parameters are set-identified and the identified set is large. In such cases,…

Econometrics · Economics 2021-01-29 Nathan Canen , Kyungchul Song

We develop a Difference-in-Differences framework for discrete, ordered outcomes subject to underreporting. Such outcomes commonly arise in self-reported surveys on socially undesirable or stigmatized behaviors, where respondents may conceal…

Econometrics · Economics 2026-04-21 Daniel Gutknecht , Cenchen Liu
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