Based upon the ubiquitous nature of cash flow projections in the decision-making process, it would be desirable to be able to find answers to questions of the following form:(1) How does the level of variability in demand affect the cash outflows for payment of accounts payable liabilities?(2) Does the method used in planning production influence the firm's cash flow patterns?Analysis of existing attempts to model the cause and effect relationships within the cash flow process reveals that the ability to answer questions similar to the ones posed above does not exist. The research accomplished to date can be characterized as being definitional and hypothetical; cash flows have been defined, lists of factors that may influence cash flow patterns have been postulated, and simple examples of what may happen to cash flow patterns have been constructed. Although these preliminary steps are necessary, they are not sufficient for a thorough understanding of the cash flow process. Analysis must be undertaken to establish the cash flow consequences of various combinations of environmental and organizational factors.

Beta coefficients were initially defined by Sharpe [11] as the slope term in the simple linear regression function where the rate of return on a market index was the independent variable and a security's rate of return was the dependent variable. As indicated by Brenner and Smidt [4], accurate estimation of beta coefficients is important for at least two reasons. First, they are important for understanding risk-return relationships in capital market theory. Second, they are important for use in making investment decisions. Some confusion has appeared, however, in recent research regarding both the optimal estimation interval and the intertemporal stability of beta coefficients. The purpose of this paper is to examine this confusion and present new evidence on the estimation and stability of beta.