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In several recent studies scale economies in the operations of commercial banking have been detected, assuming that expansion takes place with a fixed number of plants [1, 2, and 3]. The data for these studies were available for the periods 1959-1961 and 1963-1965 in one region of the United States. The purpose of this paper is to reestimate similar functions for an expanded sample covering virtually the entire United States for the year 1968. in this way, the results of earlier studies may be checked for generality, and the effect of time on the results may be investigated. In Section II, the model is described. The data and empirical results are presented in Section III. Section IV is a summary and conclusion. [ABSTRACT FROM AUTHOR]

In this paper, a risk-analysis simulation procedure was utilized to incorporate both a cash-flow liquidity concept and uncertainty in a liquidity-planning simulation model. The components of cash flow were specified. The model was implemented with the assistance of a large savings bank. The results indicate that a substantial dispersion in probable outcomes exists, from a $1 million outflow to $10 million inflow. The expected net flow, $5 million, greatly exceeds the point estimate derived by simply summing the individual point estimates. In fact, there is a 50 percent chance that the net flow will exceed the point estimate by more than $1.5 million. Such results from the liquidity planning model clearly give the banker a basis for determining the adequacy of his present liquidity position and therefore his cash management policy, as well as the optimum strategy in tens of various adjustment policies. Notwithstanding the benefits from implementation, the limitations noted previously should be repeated [1]. First, it is not dynamic in the sense of projecting through time. That is, the probability distribution is obtained for a flow that is to take place over a period of time. It is not possible to make any statement about cash needs for any particular day during that time. Second, the model does not seek an optimum solution. Third, the flows are considered independent and exogenous to the bank. Fourth, the underlying economic relationships are not derived rigorously. Hopefully, future refinements will deal with these and other problems. [ABSTRACT FROM AUTHOR]

The article presents a banking firm model which extends previous research on local bank market structure and impacts on its performance, incorporating market structure, competition, and bank demand deposit pricing policies. Questions are also raised regarding the significance of regulatory restrictions on the model. Empirical support is also provided, highlighting the problem of zero explicit yield restrictions on demand deposits.

The results of our tests indicate that branching does tend to reduce variability within a metropolitan area. Given the data with which we worked, no conclusive statement can be made concerning the relationship of geographical dispersion to diversification of deposits. In this paper we have measured the impact of branching on deposit variability for one financial institution and for one type of deposit. Thus, our results should be viewed as a first step in studying this question. If data become available, further replication for different areas and different types of deposits, especially demand deposits, should be undertaken. [ABSTRACT FROM AUTHOR]

Current conditions in the money and credit markets, along with the memory of the “crunch” of late 1966, have caused both the managers of financial institutions and their regulators to reconsider their concepts of “liquidity.” Both Minsky and Ritter have argued forcefully that traditional attention paid to balance sheet proportions should be abandoned in favor of an intertemporal analysis of cash flows [6], [7], and [8]. Ritter states that: “With a multidimensional cash flow forecast extending several years into the future, probability estimates can be made regarding potential liquidity needs over time” [8]. The purpose of this paper is to suggest a forecasting method which explicitly deals with the problem of uncertainty. The method is specifically designed for a mutual savings bank, but it could easily be adapted for a savings and loan association and, with perhaps greater effort, a commercial bank.2 In Section I, components of cash inflows and outflows are examined with the general objective of classification according to: (1) degree of uncertainty and (2) degree of management control. A risk analysis simulation model which permits explicit consideration of uncertainty is presented in Section II. Problems of implementing the model are discussed in Section III, while the implications of the analysis for future research are considered in Section IV. [ABSTRACT FROM PUBLISHER]

Commercial bank portfolio models developed by Hester [6], Porter [11], and Kane and Malkiel [7], among others, relate the structure of an asset portfolio to variation in the level of deposits. Similarly, in a recent application of linear programming to asset management, Cohen and Hammer [3] specify a liquidity constraint based upon deposit fluctuations. However, there have been few empirical studies of the determinants of demand deposit fluctuations. The purpose of this paper is to extend the work of Gramley [4], Rangarajan [12], and Wilkerson [14] on the determinants of deposit variability. In this paper, the analysis will be confined to demand deposit variability. [ABSTRACT FROM AUTHOR]

This article reports on commercial bank lending behavior in relation to the customers' depositing and borrowing decisions. The study uses date from various commercial banks in Massachusetts which provide a convenient set of commercial bank customers for a test of the deposit rate hypothesis. Testing of this hypothesis is difficult because commercial banks do not provide information concerning their individual customers and the relationship between bank and customer in many cases is multi-dimensional. Also, multiple regression analysis was applied to the survey data.

The abstract is for "Returns to Scale for Commercial Banking Products," by Frederick W. Bell and Neil B. Murphy of Clark University and Federal Deposit Insurance Corporation.