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Motivated by the application of real-time pricing in e-commerce platforms, we consider the problem of revenue-maximization in a setting where the seller can leverage contextual information describing the customer's history and the product's…

Machine Learning · Computer Science 2019-08-13 Virag Shah , Jose Blanchet , Ramesh Johari

An important goal of empirical demand analysis is choice and welfare prediction on counterfactual budget sets arising from potential policy-interventions. Such predictions are more credible when made without arbitrary…

Econometrics · Economics 2020-10-02 Debopam Bhattacharya

Applied macroeconomists frequently use impulse response estimators motivated by linear models. We study whether the estimands of such procedures have a causal interpretation when the true data generating process is in fact nonlinear. We…

Econometrics · Economics 2025-11-18 Michal Kolesár , Mikkel Plagborg-Møller

Motivated by the prevalence of prediction problems in the economy, we study markets in which firms sell models to a consumer to help improve their prediction. Firms decide whether to enter, choose models to train on their data, and set…

Theoretical Economics · Economics 2025-10-10 Krishna Dasaratha , Juan Ortner , Chengyang Zhu

The adoption of automated, data-driven decision making in an ever expanding range of applications has raised concerns about its potential unfairness towards certain social groups. In this context, a number of recent studies have focused on…

The paper aims at reconsidering the famous Le Cam LAN theory. The main features of the approach which make it different from the classical one are as follows: (1) the study is nonasymptotic, that is, the sample size is fixed and does not…

Statistics Theory · Mathematics 2013-03-06 Vladimir Spokoiny

In machine learning, metric elicitation refers to the selection of performance metrics that best reflect an individual's implicit preferences for a given application. Currently, metric elicitation methods only consider metrics that depend…

Machine Learning · Computer Science 2025-01-03 Chethan Bhateja , Joseph O'Brien , Afnaan Hashmi , Eva Prakash

This paper is concerned with the selection and estimation of fixed and random effects in linear mixed effects models. We propose a class of nonconcave penalized profile likelihood methods for selecting and estimating important fixed…

Statistics Theory · Mathematics 2012-11-05 Yingying Fan , Runze Li

Automation raises productivity and reduces paid human labor, but it also reallocates income and ownership claims. This paper studies that tradeoff in a static benchmark and in a stationary heterogeneous-agent general equilibrium. Firms…

General Economics · Economics 2026-05-07 Erhan Bayraktar

We derive a backward and forward nonlinear PDEs that govern the implied volatility of a contingent claim whenever the latter is well-defined. This would include at least any contingent claim written on a positive stock price whose payoff at…

Computational Finance · Quantitative Finance 2019-07-18 Peter Carr , Andrey Itkin , Sasha Stoikov

I provide a model of rational inattention with heterogeneity and prove it is observationally equivalent to a state-dependent stochastic choice model subject to attention costs. I demonstrate that additive separability of unobservable…

Econometrics · Economics 2024-02-16 Martin Bustos

We review the "production approach" to estimating markups, the ratio of price to marginal cost. The approach is uniquely scalable: it requires no model of consumer demand or market structure and applies broadly across firms, industries, and…

General Economics · Economics 2026-04-16 John Fernald , Amit Gandhi , Dimitrije Ruzic , James Traina

This paper develops a class of potential outcomes models characterized by three main features: (i) Unobserved heterogeneity can be represented by a vector of potential outcomes and a type describing the manner in which an instrument…

Econometrics · Economics 2023-10-10 Manu Navjeevan , Rodrigo Pinto , Andres Santos

If pricing kernels are assumed non-negative then the inverse problem of finding the pricing kernel is well-posed. The constrained least squares method provides a consistent estimate of the pricing kernel. When the data are limited, a new…

Statistics Theory · Mathematics 2008-12-10 Vladislav Kargin

Motivated by the dynamic assortment offerings and item pricings occurring in e-commerce, we study a general problem of allocating finite inventories to heterogeneous customers arriving sequentially. We analyze this problem under the…

Data Structures and Algorithms · Computer Science 2019-05-14 Will Ma , David Simchi-Levi

Every prediction is ultimately used in a downstream task. Consequently, evaluating prediction quality is more meaningful when considered in the context of its downstream use. Metrics based solely on predictive performance often diverge from…

Machine Learning · Computer Science 2025-08-26 Novin Shahroudi , Viacheslav Komisarenko , Meelis Kull

We study offline dynamic pricing when historical data provide incomplete coverage of the price space such that some candidate prices, including the optimal one, may be entirely unobserved. This setting is common in practice and is…

Machine Learning · Statistics 2026-05-25 Zeyu Bian , Lan Wang , Zhengling Qi

We study the situation of an agent who can trade on a financial market and can also transform some assets into others by means of a production system, in order to price and hedge derivatives on produced goods. This framework is motivated by…

Pricing of Securities · Quantitative Finance 2012-03-02 Adrien Nguyen Huu

We develop a market model in which products generate state-dependent potential hidden charges. Firms differ in their ability to realize this potential. Unlike firms, consumers do not observe the state. They try to infer hidden charges from…

Theoretical Economics · Economics 2024-09-24 Yair Antler ad Ran Spiegler

Empirical evidence suggests that even the most competitive markets are not strictly efficient. Price histories can be used to predict near future returns with a probability better than random chance. Many markets can be considered as {\it…

Statistical Mechanics · Physics 2009-10-31 Yi-Cheng Zhang