Predicting firm financial distress: a mixed logit model.

ABSTRACT: above the past three decades the literature upon financial distress prediction has largely been confined to simple multiple discriminant analysis, binary logistic or probit analysis, or rudimentary multinomial logit moulds (MNL). There has been a conspicuous absence of modeling innovation in this literature as well as a failure to retain abreast of important methodological exhibitions emerging in other fields of the social sciences. In particular, there has been no recognition of major advances in discrete choice modeling above the last 15 years, which has increasingly relaxed behaviorally questionable assumptions associated with the independently and identically distributed errors (IID) condition