Segment reporting, Quantitive significance criteria, FASB standards, EEC

In a recent article, Modigliani and Pogue [2] raised the issue of “leverage bias” in portfolio performance measures. Specifically, they contended that the value of the Jensen's alpha (α) could be affected by borrowing or lending at the risk-free rate, while the Treynor index (TI) does not suffer from this shortcoming. They illustrated this effect through the use of a graphical example similar to the one in Exhibit I where A and B are two unlevered portfolios with the same α's but different TI's. Modigliani and Pogue argued that by leveraging, i.e., borrowing at Rf, the portfolio with the greater slope (TI), A, could attain a levered portfolio AL which clearly dominates portfolio B. In other L words, the line with the higher TI will dominate the line with a lower TI regardless of α values. This seems to imply that, in general, TI is a better measure of ex post portfolio performance, and that ranking based on TI's is consistent and invariant to the leverage effect, while ranking based on a's is not.

Stochastic Dominance rules are playing an increasingly prominent role in the literature on choice under uncertainty. Their foundation is the mainstream VonNeumann-Morgenstern expected utility paradigm. Their essence is to provide an admissible set of choices under restrictions on the utility functions that follow from prevalent and appealing modes of economic behavior: The admissible sets generated are useful for a large group of individual decision makers and the optimal choice for an individual can then be obtained from among the smaller set of admissible choices.

Journal Article A Note on Feldstein's Criticism of Mean-Variance Analysis: A Reply Get access Martin S. Feldstein Martin S. Feldstein Harvard University Search for other works by this author on: Oxford Academic Google Scholar The Review of Economic Studies, Volume 45, Issue 1, February 1978, Page 201, https://doi.org/10.2307/2297095 Published: 01 February 1978

Journal Article On the Dynamic Behaviour of the Consumer and the Optimal Provision of Social Security Get access Sheng Cheng Hu Sheng Cheng Hu Purdue University Search for other works by this author on: Oxford Academic Google Scholar The Review of Economic Studies, Volume 45, Issue 3, October 1978, Pages 437–445, https://doi.org/10.2307/2297246 Published: 01 October 1978 Article history Received: 01 October 1976 Accepted: 01 June 1977 Published: 01 October 1978

Journal Article On Stochastic Entry and Exit without Expectations Get access Frederick S. Inaba Frederick S. Inaba Washington State University Search for other works by this author on: Oxford Academic Google Scholar The Review of Economic Studies, Volume 45, Issue 3, October 1978, Pages 535–545, https://doi.org/10.2307/2297255 Published: 01 October 1978 Article history Received: 01 February 1976 Accepted: 01 July 1977 Published: 01 October 1978

Journal Article Consumer's Surplus when Consumers are Subject to a Time and an Income Constraint Get access Kenneth S. Lyon Kenneth S. Lyon Utah State University Search for other works by this author on: Oxford Academic Google Scholar The Review of Economic Studies, Volume 45, Issue 2, June 1978, Pages 377–380, https://doi.org/10.2307/2297352 Published: 01 June 1978 Article history Received: 01 January 1976 Accepted: 01 June 1977 Published: 01 June 1978

I. Introduction, 307.—II. Utility functions and differences in tastes, 308.—III. Measuring horizontal equity, 313.—IV. Qualifications, 318.

In this paper an explicit and computationally convenient expansion of the exact finite sample distribution function of a quasi-maximum likelihood spectral estimator is given. In the majority of practical situations it will be necessary to estimate certain nuisance parameters of the distribution. Therefore, a method of evaluating these parameters is suggested and some Monte-Carlo evidence concerning the practical implementation of the results is given. 1 INTRODUCTfON AN EXTENSIVE SET of asymptotic results relating complex statistical analysis to the problems that arise in estimating spectra from the discrete Fourier transforms of time series data has been well established; see, for example, Brillinger [3] and Goodman [6]; and Hannan [11] has recently extended these results to cover the modified Fourier coefficients, proposed by Bingham, Godfrey, and Tukey [1] and defined in (2.3) below. Unfortunately it seems likely that the sample sizes required for one to approach the asymptotic position will not be available when considering the analysis of many economic time series. In a recent article, however, Hatanaka [12] has shown that the elimination of leakage produced by the modified Fourier coefficients is effective for small finite realizations and that it may be possible to recover the loss of degrees of freedom associated with the familiar estimator obtained by averaging over the modified periodogram.2 The purpose of the present paper is to extend these results by using complex statistical analysis to derive expressions for both the form and exact finite sample distribution of a spectral estimator obtained from the modified Fourier coefficients. Thus in the following section a brief exposition of some basic theory is given and a quasi-maximum likelihood estimation procedure is suggested. In Section 3 an exact expression for the finite sample distribution of the proposed estimator is given and shown to incorporate an established distributional result as a particular special case. In the majority of practical situations it will be necessary to estimate certain nuisance parameters of this distribution if it is to be employed and a method of evaluating these parameters is also suggested. It is well known, however, that while the replacement of nuisance parameters by consistent estimates will generally leave asymptotic theory intact the consequences of estimating nuisance parameters are unlikely to be negligible in finite sample theory. Since it is not possible to determine analytically the effect that the estimation of these nuisance parameters will have, the results of some simple Monte-Carlo