Researchers in financial accounting often use qualitative response models in choice‐based empirical research. Most of this research relies on the familiar techniques of dichotomous probit or logistic regression. Only a limited amount of this research uses n‐chotomous qualitative response models such as ordered probit or multinomial logistic regression. A potential explanation for this limited use is that the interpretation of model coefficients in qualitative response models with limited dependent variables (dichotomous or n‐chotomous) differs substantially from OLS regression, and econometric texts do not provide a systematic approach to coefficient interpretation. This paper discusses several approaches to interpreting coefficients in n‐chotomous qualitative response models. These methods focus on partial derivatives, elasticities of probability, sensitivity analysis, and odds ratios. The methods are applied to the models presented in Thomas (1989) and Mittelstaedt (1989). Additional analyses of the models demonstrate that the methods of interpretation can provide different conclusions or strengthen existing conclusions. The methods provide a better understanding of the directional effects of model coefficients, the relative responsiveness of the probability of choice to changes in the independent variables, and the effects of changes in the independent variables on the probability of choice. These methods should make these models more attractive to researchers interested in choice‐based financial accounting research, and allow for a broader range of decision outcomes than that provided by dichotomous qualitative response models.

Provides additional evidence on factors influencing inventory accounting choice in the United States. Comparison of firms using first in, first out (FIFO) and last in, first out (LIFO) inventory accounting methods; Study design and specification of variables; Effect of potential tax savings on inventory accounting policy choice.

Reviews the book "Valuation: Measuring and Managing the Value of Companies," by Tom Copeland, Tim Koller and Jack Murrin.

[This study provides additional evidence on factors influencing inventory accounting policy choice. Following Lee and Hsieh (1985), Dopuch and Pincus (1988), and Lindahl (1989), we compare long-time FIFO users with long-time LIFO users to test variables that might be expected to influence inventory method choice. This study incorporates a tax savings variable in evaluating the LIFO/FIFO choice. We also survey financial executives to corroborate the results of secondary data analyses and to seek new insights about inventory method choice. The findings suggest that: (1) anticipated tax savings is the primary reason firms use LIFO and (2) other firms do not use LIFO because of numerous factors without a single dominant reason. Most of these factors diminish the potential tax savings from LIFO. They include LIFO layer liquidations, LIFO bookkeeping costs, declining production costs, and contradictory tax and financial reporting rules on accounting for inventory obsolescence. However, other factors include effects on debt covenants, concern about the complexity of LIFO, and the requirements of FIFO for government contracts. Two unexpected findings emerged. First, the multivariate model is quite accurate in predicting FIFO firms, but predicts less then half of those using LIFO. Second, the correspondence between the responses to the FIFO survey and the cross-sectional data is not as strong as might be expected, which suggests that determinants of inventory choice continue to be elusive.]