Abstract:
This paper presents a Bayesian technique for the estimation of a logistic regression model
including variable selection. As in Ou & Penman (1989), the model is used to predict the
direction of company earnings, one year ahead, from a large set of accounting variables
from financial statements. To estimate the model, the paper presents a Markov chain Monte
Carlo sampling scheme that includes the variable selection technique of Smith & Kohn
(1996) and the non-Gaussian estimation method of Mira & Tierney (2001). The technique
is applied to data for companies in the United States and Australia. The results obtained
compare favourably to the technique used by Ou & Penman (1989) for both regions.
