This study demonstrates a tractable method for analyzing schooling investment with risky incomes. Constant relative risk aversion is assumed, and borrowing in a rudimentary capital market is allowed. A linear, variance-components model on log (real income) is estimated. Only unexplained variation is treated as a source of risk. Illustrative empirical results indicate that students should take either 4 years of college or none at all, depending on time preference, loan availability, and degree of risk aversion. Estimate risk-adjusted rates of return to college exceed 10 percent for some parameter values. Risk adjustments for college rates are small but positive.

Reviews the book "Problems and Approaches to Solutions," 5th ed., by Charles T. Horngren and J. Arthur Leer.

Theory and practice of financial reporting are typically centered on the notion of income measurement. In this article, the authors adopt a fundamental measurement perspective. Income measurement is then argued to exist in a world of complete and perfect markets, but not necessarily otherwise. Hence, at a fundamental level the central feature of financial reporting cannot be income measurement. The writers then offer a reinterpretation of income reporting and accrual notions in terms of a "cost-effective" communication procedure.

Reviews the book "Equity Valuation: Models, Analysis and Implications," by David F. Hawkins and Walter J. Campbell.

Suppose that an investor seeks to maximize the expected value of some utility function U(R), where R is the rate of return this period on his portfolio. Frequently it is more convenient or economical for such an investor to determine the set of mean-variance efficient portfolios than it is to find the portfolio which maximizes EU(R). The central problem considered here is this: would an astute selection from the E,V efficient set yield a portfolio with almost as great an expected utility as the maximum obtainable EU? A number of authors have asserted that the right choice of E, V efficient portfolio will give precisely optimum EU if and only if all distributions are normal or U is quadratic.' A frequently implied but unstated corollary is that a well-selected point from the E, V efficient set can be trusted to yield almost maximum expected utility if and only if the invector's utility function is approximately quadratic, or if his a priori beliefs are approximately normal. Since statisticians frequently reject the hypothesis that return distributions are normal, and John Pratt and Kenneth Arrow have each shwn us absurd implications of a quadratic utility function, some writers have concluded that mean-variance analysis should be rejected as the criterion for portfoliQ selection, no matter how economical it is as compared to alternate formal methods of analysis. Consider, on the other hand, the following evidence to the contrary. Suppose that two investors, let us call them Mr. Bernoulli and Mr. Cramer, have the same probability beliefs about portfolio returns in the forthcoming period; while their utility functions are, respectively,