A Multiple Regression Model For Cost Control-Assumptions and Limitations.

Abstract

Abstract This article focuses on multiple regression analysis to cost control of decentralized operations in the consumer finance industry. There are potential accounting applications of multiple regression analysis in control of decentralized operations. Moreover, multiple regression can be a useful empirical research tool in other areas of accounting and finance. It is essential, however, to know the hidden limitations and assumptions in the approach and to perform the necessary tests to see that these assumptions are met be- fore plunging head-first into a sea of regression formulae. In cost analysis, one feature of multiple regression is the ability to use dichotomous variables. The advantage herein arises when a given characteristic may or may not exist in decentralized units. Multiple regression may be applied without assuming the disturbance terms are normally distributed. Multiple regression may be used in testing structural relationships between operating costs and various factors which are thought to affect these costs. Analysis of variance procedures may be extended to statistical tests of single coefficients and to statistical tests of the contribution to explained variation of sub-groups of factors included in the model.