Reviews the book "The Subterranean Economy," by Dan Bawly.

Reviews the book "Financial Accounting: An Introduction to Concepts, Methods, and Uses," 3rd ed., by Sidney Davidson, Clyde P. Sticney and Roman Weil.

Commercial banks have been the subjects of a large body of empirical research 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 correlation analysis is the statistical technique that is employed. Unlike regression analysis 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 variables 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 ‘tax-loss selling’ hypothesis has frequently been advanced to explain the ‘January effect’ reported in this issue by Keim. This paper concludes that U.S. tax laws do not unambiguously predict such an effect. Since Australia has similar tax laws but a July–June tax year, the hypothesis predicts a small-firm July premium. Australian returns show pronounced December–January and July–August seasonals, and a premium for the smallest-firm decile of about four percent per month across all months. This contrasts with the U.S. data in which the small-firm premium is concentrated in January. We conclude that the relation between the U.S. tax year and the January seasonal may be more correlation than causation.