Causal Modelling of Heavy-Tailed Variables and Confounders with Application to River Flow

10/13/2021
by   Olivier C. Pasche, et al.
0

Confounding variables are a recurrent challenge for causal discovery and inference. In many situations, complex causal mechanisms only manifest themselves in extreme events, or take simpler forms in the extremes. Stimulated by data on extreme river flows and precipitation, we introduce a new causal discovery methodology for heavy-tailed variables that allows the use of a known potential confounder as a covariate and allows its effect to be almost entirely removed when the variables have comparable tails, and also decreases it sufficiently to enable correct causal inference when the confounder has a heavier tail. We introduce a new parametric estimator for the existing causal tail coefficient and a permutation test. Simulations show that the methods work well and the ideas are applied to the motivating dataset.

READ FULL TEXT

page 3

page 11

page 14

page 20

page 22

page 23

research
08/14/2019

Causal discovery in heavy-tailed models

Causal questions are omnipresent in many scientific problems. While much...
research
08/23/2021

Causal Analysis at Extreme Quantiles with Application to London Traffic Flow Data

Treatment effects on asymmetric and heavy tailed distributions are bette...
research
10/13/2021

Estimation and Inference of Extremal Quantile Treatment Effects for Heavy-Tailed Distributions

Causal inference for extreme events has many potential applications in f...
research
07/08/2019

Causal mechanism of extreme river discharges in the upper Danube basin network

Extreme hydrological events in the Danube river basin may severely impac...
research
07/18/2020

Autoregressive flow-based causal discovery and inference

We posit that autoregressive flow models are well-suited to performing a...
research
08/28/2023

Temporal clustering of extreme events in sequences of dependent observations separated by heavy-tailed waiting times

The occurrence of extreme events like heavy precipitation or storms at a...
research
09/11/2021

Uncovering Main Causalities for Long-tailed Information Extraction

Information Extraction (IE) aims to extract structural information from ...

Please sign up or login with your details

Forgot password? Click here to reset