Auditing, Sampling, Substantive test, Auxiliary information interval estimation

Walter A. Robbins, Kenneth R. Austin, Disclosure Quality in Governmental Financial Reports: An Assessment of the Appropriateness of a Compound Measure, Journal of Accounting Research, Vol. 24, No. 2 (Autumn, 1986), pp. 412-421

N RECENT YEARS, public and professional interest in schools has been heightened by a spate of reports, many of them critical of current school policy.' These policy documents have added to persistent and long-standing concerns about the cost, effectiveness, and fairness of the current school structure, and have made schooling once again a serious public issue. As in the past, however, any renewed interest in education is likely to be short-lived, doomed to dissipate as frustration over the inability of policy to improve school practice sets in. This frustration about school policy relates directly to knowledge about the educational production process and in turn to underlying research on schools. Although the educational process has been extensively researched, clear policy prescriptions flowing from this research have been difficult to derive.2 There exists, however, a consistency to the research findings that does have an immediate application to school policy: Schools differ dramatically in quality,

Richard A. Young, A Note on "Economically Optimal Performance Evaluation and Control Systems": The Optimality of Two-Tailed Investigations, Journal of Accounting Research, Vol. 24, No. 1 (Spring, 1986), pp. 231-240

The traditional model of collective bargaining confines unions to settlements constrained by the employer's labor demand curve, but an alternative model places wage-employment outcomes on a contract curve that extends beyond the labor demand curve. This paper derives a multidimensional (hedonic) contract-curve model in which employment-security provisions are used to maintain efficient bargains outside the employer's demand curve and distinguishes empirically between the contract-curve and demand-constraint models using data for public school teachers in New York State. Estimates clearly support the contract-curve model over the demand-constraint model by linking the gap between compensation and the value of the marginal product to the strength of employment-security provisions.

When portfolio optimization is implemented using the historical characteristics of security returns, estimation error can degrade the desirable properties of the investment portfolio that is selected. Given the problem of estimation risk, it is natural to formulate rules of portfolio selection within a Bayesian framework. In this framework, portfolio selection is based on maximization of expected utility conditioned on the predictive distribution of security returns. Most researchers have addressed the problem of estimation risk by asserting a noninformative diffuse prior that reduces the detrimental effect of estimation risk, but does not directly reduce estimation error. Portfolio performance can be improved by specifying an informative prior that reduces estimation error. An informative prior that all securities have identical expected returns, variances, and pairwise correlation coefficients is asserted. This informative prior reduces estimation error by drawing the posterior estimates of each security's expected return, variance, and pairwise correlation coefficients toward the average return, average variance, and average correlation coefficient, respectively, of all the securities in the population. The amount that each of these parameters is drawn toward its grand mean depends upon the degree to which the sample is consistent with the informative prior. This empirical Bayes method is shown to select portfolios whose performance is superior to that achieved, given the assumption of a noninformative prior or by using classical sample estimates.

Recent studies indicate that the widespread assumption of parameter stationarity in empirical applications of asset pricing models may be inappropriate. This paper investigates the feasibility of modeling parameter instability as a sequence of persistent stable regimes. Recursive residual and log likelihood techniques are combined to detect and locate shift points. The results indicate that regime shifts are widespread, frequent, and often large enough to significantly effect empirical findings. The nature of the shifts appears to be a rotation of the regression line, indicating that correction of both alpha and beta parameters is required.