This paper investigates the forecasting accuracy of bankruptcy hazard rate models for U.S. companies over the time period 1962–1999 using both yearly and monthly observation intervals. The contribution of this paper is multiple-fold. One, using an expanded bankruptcy database we validate the superior forecasting performance of Shumway's (2001) model as opposed to Altman (1968) and Zmijewski (1984). Two, we demonstrate the importance of including industry effects in hazard rate estimation. Industry groupings are shown to significantly affect both the intercept and slope coefficients in the forecasting equations. Three, we extend the hazard rate model to apply to financial firms and monthly observation intervals. Due to data limitations, most of the existing literature employs only yearly observations. We show that bankruptcy prediction is markedly improved using monthly observation intervals. Fourth, consistent with the notion of market efficiency with respect to publicly available information, we demonstrate that accounting variables add little predictive power when market variables are already included in the bankruptcy model.

This paper investigates the forecasting accuracy of bankruptcy hazard rate models for U.S. companies over the time period 1962–1999 using both yearly and monthly observation intervals. The contribution of this paper is multiple-fold. One, using an expanded bankruptcy database we validate the superior forecasting performance of Shumway's (2001) model as opposed to Altman (1968) and Zmijewski (1984). Two, we demonstrate the importance of including industry effects in hazard rate estimation. Industry groupings are shown to significantly affect both the intercept and slope coefficients in the forecasting equations. Three, we extend the hazard rate model to apply to financial firms and monthly observation intervals. Due to data limitations, most of the existing literature employs only yearly observations. We show that bankruptcy prediction is markedly improved using monthly observation intervals. Fourth, consistent with the notion of market efficiency with respect to publicly available information, we demonstrate that accounting variables add little predictive power when market variables are already included in the bankruptcy model.

Mergers and acquisitions improve market efficiency by capturing synergies between firms. But takeovers also impose externalities (both positive and negative) on the remaining firms in the industry. This paper describes a new equilibrium concept designed to explain and predict takeovers in this setting. We experimentally compare the new equilibrium concept to that of competing con-cepts in situations without and with externalities. Moreover, we examine the predicted dynamics of takeovers and outcome implications of those dynamics. Our experimental results support the predictions of the new equilibrium concept and provide implications for further empirical tests. 1.

Mergers and acquisitions improve market efficiency by capturing synergies between firms. But takeovers also impose externalities (both positive and negative) on the remaining firms in the industry. This paper describes a new equilibrium concept designed to explain and predict takeovers in this setting. We experimentally compare the new equilibrium concept to that of competing concepts in situations without and with externalities. Moreover, we examine the predicted dynamics of takeovers and outcome implications of those dynamics. Our experimental results support the predictions of the new equilibrium concept and provide implications for further empirical tests.