Knowledge that Transforms

The purpose of this paper is to provide evidence on the following question: Are there more banking offices available per person to furnish consumer and business services in branch banking states than in unit banking states? This question is a central part of a broader issue of what limitations should be placed on the ability of individual banks to branch. Indeed, in a recent review of the literature dealing with the branching question, and prepared for the Senate Banking Committee (McIntyre Committee), Guttentag [8] stated: “One of the most pervasive arguments for branch banking is that branch banks provide more office facilities than unit banking.” Yet the available evidence on the question is sparse and existing research contains methodological difficulties which make the findings of questionable value.

Since the beta systematic risk coefficient and the standard deviation are both important statistics in the received capital market theory [22] and the received option theory [1], considerabe effort has been expended on obtaining empirical estimates of these statistics [30]. The ordinary least squares (OLS) technique is typically utilized to estimate beta as the regression coefficient of a simple linear regression. However, the OLS betas for common stocks were found to be disconcertingly unstable over time [5, 6, 13, 15, 25]. But, whether the OLS beta or an adjusted beta were used, the regression statistics could still only explain less than half of the variability of most New York Stock Exchange (NYSE) stocks' returns (more specifically, R2

James R. Follain, Jr., A Study of the Demand for Housing by Low Versus High Income Households, The Journal of Financial and Quantitative Analysis, Vol. 14, No. 4, Proceedings of 14th Annual Conference of the Western Finance Association, June 21-23, 1979 (Nov., 1979), pp. 769-782

Roy L. Crum, Darwin D. Klingman, Lee A. Tavis, Implementation of Large-Scale Financial Planning Models: Solution Efficient Transformations, The Journal of Financial and Quantitative Analysis, Vol. 14, No. 1 (Mar., 1979), pp. 137-152

There is a considerable body of empirical research in accounting devoted to the analysis of relationships between accounting numbers and security prices. Very roughly, this body of research may be classified into three different categories: (i) share price valuation models and the determination of market equity values; (ii) the measurement of “unexpected earnings” and their contemporaneous association with security returns; (iii) the forecasting of future security returns. The selection and definition of accounting numbers in most of these types of studies have, by and large, been quite heuristic. The accounting variables are usually selected with little consideration given to their empirical time-series behavior; more important appears to be their intrinsic economic connotations. The approaches can thus be thought of as stipulating the existence of “real” economic variables, e.g., real income for a period, and then using numbers of published accounting statements as estimates of the real variables. The errors in estimates of the true variables are then often minimized by the use of aggregation procedures and the diversification effects of such procedures. The postulating of real economic variables has another methodological advantage: it permits the use of comparative statics analysis of corporate behavior and its effect on equity risk and return. For example, Hamada [7], among others, has shown that leverage affects risk in the usually hypothesized manner but this analytical result depends on the assumption that leverage and earnings are real and unambiguous economic variables without “measurement” errors.

Recently, there has been an increased interest in the role that bankruptcy or ruin plays in the valuation process. Several authors have discussed this subject (Gordon [17], Quirk [27], and Smith [35]) and some have constructed theoretical models attempting to show how the probability or risk of ruin introduces an element of risk into valuation (for example, Bierman [5], Borch [8], Tinsely [37]). The question of corporate survival is, therefore, central to the financial considerations of the firm. None, however, has attempted empirical tests of the role of such a probability in valuation.

Robert H. Edelstein, An Appraisal of Residential Property Tax Regressivity, The Journal of Financial and Quantitative Analysis, Vol. 14, No. 4, Proceedings of 14th Annual Conference of the Western Finance Association, June 21-23, 1979 (Nov., 1979), pp. 753-768

Charles W. Noland, Assessing Hedonic Indexes for Housing, The Journal of Financial and Quantitative Analysis, Vol. 14, No. 4, Proceedings of 14th Annual Conference of the Western Finance Association, June 21-23, 1979 (Nov., 1979), pp. 783-800

In a recent issue of this journal Barnea [1] presented an empirical study of the impact of a specialist (market-maker) on the variability of the price of a stock. He concludes with others that “the chief cost of dealing with a market maker is the difference between the theoretical but unobservable equilibrium price and the transaction price, rather than the bid-ask spread.” This paper presents a rigorous dynamic model in which the specialist, who is uncertain about the future arrival of tenders, determines transaction prices periodically over the trading day. The structure of the model permits a direct comparison of the specialist's prices to the “equilibrium price, ” to be defined below, and also to what prices would be in the absence of a specialist.

The Journal of Financial and Quantitative Analysis © 1979 University of Washington School of Business Administration