The problem of expectations formation has been either ignored or treated with very restrictive assumptions in traditional dividend adjustment models. Since these models are typically used to explain the dividend decisions of individual firms, a more satisfactory treatment of the process of expectations formation is needed. In order to analyze the dynamic dividend adjustment process, this article proposes a model, more general than previous ones, that is consistent with the rational expectations hypothesis. A nonlinear regression method is used to estimate the parameters of the model and to test the validity of the rational expectations hypothesis in dividend decisions making. The partial adjustment model with rational expectations explains dividend adjustments reasonably well. The overall results suggest that firms make use of available earnings information to form optimal future earnings forecasts; specifically, a firm's dividend adjustment process is completed in about two and a half quarters. This article also finds that the fourth-order serial correlation problem disappears after a generalized Tobit model is used for the parameter estimation.
- generalized Tobit
- likelihood ratio test
- two-step estimator
ASJC Scopus subject areas
- Business, Management and Accounting(all)