We use cookies to ensure that we give you the best experience on our website. You can change your cookie settings at any time. Otherwise, we'll assume you're OK to continue.


Virtual seminar: Dr. Timothy Christensen - New York University

Thursday, 14 October 2021
15:00 to 17:00
Dr Timothy Christensen
Virtual event

Topic: Robust Forecasting

This webinar is brought to you by QRFE.

Abstract: We use a decision-theoretic framework to study the problem of forecasting discrete outcomes when the forecaster is unable to discriminate among a set of plausible forecast distributions because of partial identification or concerns about model misspecification or structural breaks. We derive “robust” forecasts which minimize maximum risk or regret over the set of forecast distributions. We show that for a large class of models including semiparametric panel data models for dynamic discrete choice, the robust forecasts depend in a natural way on a small number of convex optimization problems which can be simplified using duality methods. Finally, we derive “efficient robust” forecasts to deal with the problem of first having to estimate the set of forecast distributions and develop a suitable asymptotic efficiency theory. Forecasts obtained by replacing nuisance parameters that characterize the set of forecast distributions with efficient first-stage estimators can be strictly dominated by our efficient robust forecasts.

Click here to read the paper.

Visit Dr Timothy Christensen's website here.

To join the seminar, click here.