We develop an analytical framework to appropriately model and adequately analyze A/B tests in presence of nonparametric non-stationarities in the targeted business metrics. A/B tests, also known as online randomized controlled experiments, have been used at scale by data-driven enterprises to...

Why does misinformation persist, and how does it distort the long-run beliefs and actions of rational agents? We study a model where receivers see an infinite stream of messages from a sender of unknown type who observes private signals about an unknown state of the world. We characterize the...

Automatic differentiation (AD) is a popular method of computing exact derivatives in complex sensitivity analyses and optimisation routines that lack closed-form solutions, posing challenges for analytical and numerical alternatives. This paper introduces a vectorised version of AD that builds...

The capture ratio is a widely-used investment performance measure. We study the statistical problem of estimating the capture ratio based on a finite number of observations of a fund's returns. We derive the asymptotic distribution of the estimator and use it for testing whether one fund has a...

This paper examines the econometric causal model for policy analysis developed by the seminal ideas of Ragnar Frisch and Trygve Haavelmo. We compare the econometric causal model with two popular causal frameworks: Neyman-Holland causal model and the do-calculus. The Neyman-Holland causal model...

Many researchers investigate the sharing economy effect using panel regressions that assume a constant coefficient over space and time, but without testing whether this is the case. Using the Airbnb data in Barron et al. (2021), we find that the logarithms of both predictor and response...

In this work, we develop a multi-fidelity Bayesian experimental design framework to efficiently quantify the extreme-event statistics of an input-to-response (ItR) system with given input probability and expensive function evaluations. The key idea here is to leverage low-fidelity samples whose...