John D. Stowe

Product Risk, Asymmetric Information, and Trade Credit

The purpose of this paper is to explain cross-sectional variations in trade credit terms across firms and industries. This study shows that there is a separating equilibrium in which the size of the cash discount conveys information about product quality. The driving forces of this equilibrium outcome are the risk-sharing motives of the producer and buyer as well as asymmetric information about product quality. The empirical implications of the model are derived and discussed in relation to industry practices.

A Canonical Correlation Analysis of Commercial Bank Asset/Liability Structures

Commercial banks have been the subjects of a large body of empirical re? search employing regression and econometric models and discriminant analysis. The purpose of this paper is to empirically identify and describe relationships, including hedging behavior, between the asset side and the liability/capital side of the balance sheets of a cross-section of large U.S. banks. Canonical correla? tion analysis is the statistical technique that is employed. Unlike regression anal? ysis which explains the behavior of a single dependent variable as a function of a set of independent variables, canonical correlation analysis relates two sets of variables. In the present case, one set of variables is the composition of the lefthand side of the balance sheet and the other set is the right-hand side. The vari? ables used in this study are asset and liability/capital categories expressed as a proportion of total bank assets (i.e., a percentage breakdown of the balance sheet or a common size statement). These proportions are used in lieu of the more usual financial ratios and no information exogenous to the bank is employed. A recent article by Stowe, Watson, and Robertson [22] examines the rela? tionships between the two sides of the balance sheets of a cross-section of 510 large, nonfinancial corporations. They used canonical correlation analysis to ex? plore relationships between the structure of the left- and right-hand sides of the balance sheet.1 The empirical results suggested several relationships: (1) the firms seemed to use hedging?matching the maturity structure of assets and lia? bilities; (2) some assets such as accounts receivable and real estate could be used as collateral for short-term bank or factor loans and mortgages, respectively; (3) commodity-producing firms should have higher levels of both inventories and accounts payable than service-providing firms; and (4) high-risk businesses may

Life Insurance Company Portfolio Behavior

A simple chance-constrained model of life insurance company portfolio choice is presented in this paper and several hypotheses derived from the model are examined using a cross-sectional, time series panel of 15 annual observations for 92 large U.S. life insurance companies. In addition to the usual yield variables, non-yield variables such as the relative amount of surplus and the cost of reserve liabilities are significant determinants of the composition of life insurance company portfolios. Portfolio adjustments were found to occur more rapidly than previously reported in the literature. A fundamental assumption of microeconomic theory is that economic units are engaged in some optimization process. For example, consumers are assumed to maximize their utility and businesses are assumed to maximize their profits or wealth. The application of optimization techniques to the investment decisions of life insurance companies poses a number of conceptual and empirical problems. In this paper, a simple chance-constrained model of life insurance company portfolio choice is presented and then several hypotheses derived from the model are examined using a cross-sectional, time-series panel of 15 annual observations of 92 large U.S. life insurers. Financial intermediaries such as life insurers often are more difficult to analyze than are non-financial businesses because of basic differences in the properties of financial and tangible assets. Tangible assets are highly specialized in form and use, are held primarily for the physical services they yield directly, are highly complementary, and are characterized by externalities in use. In comparison, financial assets are generalized claims against future production, are highly substitutable, and are much more liquid than real assets. This paper contributes to the existing literature on life insurance investment behavior in three respects.2 The investment choices of individual John D. Stowe, Ph.D., is Assistant Professor of Finance, University of Oklahoma, Norman. He appreciates the valuable counsel of James M. Griffin. 1 See Moore, [14, pp. 11-12]. 2Pesando [15] and Cummins [4] have provided comprehensive econometric studies of the aggregate flow of funds through life insurance companies. Policy loans and mortgage loan holdings were analyzed, respectively, by Schott [17] and by Smith and Sparks [19]. Gentry and Pike [7] analyzed the behavior of the common stock portfolios of 34 insurance companies and found a linear trade-off between risk and return

Univariate and multivariate distributions of the job descriptive index's measures of job satisfaction

Abstract This study examines the univariate and multivariate distributions of the Job Descriptive Indexs (JDI) scales for job satisfaction with work, supervision, pay, promotion, and co-workers. The results indicate that the sample distributions of four of the five scales differ significantly from normality. The exception is satisfaction with work. After normalizing square-root transformations were applied to the nonnormal scales, the results of a test for multivariate normality indicated that the transformed sample data for the satisfaction scales reasonably approximate multivariate normality. The implication for organizational researchers is that the use of univariate statistical procedures that are sensitive to nonnormality is questionable in analyses involving the JDI scales. When it is appropriate to analyze the scales jointly, normalizing transformations are recommended to induce approximate multivariate normality for the joint distribution.

A Multivariate Analysis of the Composition of Life Insurer Balance Sheets

A basic economic decision confronting a life insurer is the mixture of assets to buy and liabilities to sell. The asset and liability structures of life insurers involve interactions among their assets, among their liabilities, and between their assets and liabilities, as well as many regulations and institutional constraints unique to the life insurance industry. The purpose of this paper is, by using canonical correlation analysis, to examine empirical relationships between the structure of the assets and obligations of life insurers. Several significant cross-balance sheet relationships are found for a cross-section of 194 large life insurers.

Microeconomic influences on operating leverage

Abstract The concept of operating leverage generally has been visualized in the context of linear break-even analysis. This paper evaluates the properties of two measures of the degree of operating leverage using a more general short-run microeconomic model of the firm. In this model, the degree of operating leverage is related positively to the price elasticity of demand for a firms output, to its elasticity of supply for an input, and to its output elasticity. In addition, operating leverage measures are usually derived from models inconsistent with firm wealth maximizing behavior and are too simplistiic for complex models with stochastic demand, supply, and production functions.

A Market Timing Myth

Several securities and plannig firms publish a demonstration of the dramatically reduced returms that an investor would see if the investor were out of the market for the 10, 20, 30, or 40 best days over a time period such as 5 to 10 years. They claim this is a demonstration of the pitfalls of market timing. As a counterexample, this article shows the dramatically enhanced returns if the investor is in cash for a similar number of the worst days. The probabilities of picking the best or worst days out of a larger number of days are shown to be minuscule. In fact, the probability of winning a lottery, or even several lotteries in a row, is better than the probability of replicating the investment results these firms are discussing.