Testing for Bias in Forecasts for Independent Multinomial Outcomes

This paper deals with a test on forecast bias in predicting independent multinomial outcomes where the predictions are probabilities. The new Likelihood Ratio (and Wald) test extends the familiar Mincer Zarnowitz regression to a multinomial logit model instead of a linear regression. The test is eva...

Full description

Saved in:
Bibliographic Details
Main Authors: Philip Hans Franses, Richard Paap
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Forecasting
Subjects:
Online Access:https://www.mdpi.com/2571-9394/7/1/4
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper deals with a test on forecast bias in predicting independent multinomial outcomes where the predictions are probabilities. The new Likelihood Ratio (and Wald) test extends the familiar Mincer Zarnowitz regression to a multinomial logit model instead of a linear regression. The test is evaluated using various simulation experiments, which indicate that the size and power properties are good, even for small sample sizes, in the sense that the size is close to the used 5% level, and the power quickly reaches 1. We implement the test in an empirical setting on brand choice by individual households.
ISSN:2571-9394