Earnings, Industry communalities, Market effects

C-V-P Analysis, Cost-Value-Profit analysis, Uncertainty

The Markowitz model for the efficient diversification of investments [12] has, over the years since its original formulation, provided the basis for many investigations into the question of portfolio selection. Amongst the more notable contributions to the theory are the works of Fama [6] and Mandelbrot [11], Smith [17], Latané [10], Arditti [1], and Blume [2].

The purpose of a recent paper by Herbert Grubel and Peter Lloyd [5] was to examine the nature and magnitude of the bias introduced by the neglect of factor substitution between produced and primary inputs when calculating effective rates of protection (ERP). They concluded that the bias from neglecting substitution possibilities between produced and primary inputs is usually small. The purpose of this paper is to make three comments on their conclusions. Firstly, there is an error, or possibly a misprint, which can be misleading. Secondly, because Grubel and Lloyd restrict their calculations to a narrower range of parameter values than is empirically reasonable their results understate the magnitude of the bias which one might reasonably expect to encounter in empirically grounded calculations. Thirdly, Grubel and Lloyd conclude that the bias from neglecting substitution possibilities is usually small 3 without discussing criteria for determining when a bias becomes significant. It is shown here that the magnitude of the bias encountered when using empirically relevant data is very significant because the ranking of production processes by their calculated ERP can vary greatly with biased estimates. These comments have significant implications for the notion that the elasticity of substitution is not an important parameter in calculating the ERP.

LIFO, FIFO, Accounting Ratios, Risk

Bryan Heatcotte, Vincent P. Apilado, The Predictive Content of some Leading Economic Indicators for Future Stock Prices, The Journal of Financial and Quantitative Analysis, Vol. 9, No. 2 (Mar., 1974), pp. 247-258

In the first section of this paper the overidentifying restrictions on a system of linear simultaneous equations are expressed in terms of restrictions on the reduced form parameters. These restrictions provide the basis of a test of the structure using only the unrestricted reduced form parameter estimates. Under Ho the test proposed is asymptotically equivalent to a likelihood ratio test. The test may be applied as a single equation or complete system procedure and it may be presented as either a x2 or an F statistic. The case is also made here for system overidentification tests rather than single equation procedures, the arguments being drawn from the statistical literature on hypothesis testing by induction. The computational advantages of the present proposals are substantial when compared to FIML based likelihood -ratio tests and Monte Carlo experiments confirm that a system version of the test performs well in large samples. The system version of the test behaves like the FIML likelihood ratio test in large sample situations both under Ho and H1. However, the Monte Carlo studies indicate that both the single equation and system versions of the test perform poorly in small samples. THE AIM OF THIS paper is to investigate the possibility of deciding on the specification of a simultaneous equation model prior to the estimation of the structure. A well established test procedure is suggested which uses OLS estimates of the reduced form parameters; it enables the null hypothesis, that the model specified is not significantly different from the model which generated the sample, to be tested. Because of the one-to-one correspondence between the overidentified structure and the restricted reduced form, it is possible to make inferences about the structure from the observed compatibility of the reduced form restrictions with the sample information. In addition, the reduced form restrictions resulting from a particular equation may be isolated and tested separately, if desired. The principle underlying the test would appear to be due to Wald [17J; namely, that if the null hypothesis is correct and the structure postulated as the maintained hypothesis was responsible for the generation of the observed sample, then the unrestricted reduced form parameter estimates will tend, if the sample size is large enough, to satisfy the reduced form restrictions advanced under the maintained hypothesis. A number of problems relating to identification of linear simultaneous equations make life a little difficult and are discussed subsequently. Now, take the linear structure

3. While he discusses it in general terms, Mr. Flick fails to present the proposed reformulation of my approach in concise mathematical terms. Hence I find it impossible to determine to what extent it involves simply introduction of a different terminology rather than a substantively different argument. He introduces the new concept of Pollution Services. If this is done with the intention to present new factual information, effect on the material conclusion reached at the end of the argument to be nil. But even if the additional information thus conveyed is intended to be utilized not in this, but in some other context, I would be inclined to question the appropriateness and the intuitive appeal of this particular concept: while air may be viewed industries of by-products, to what substance would Mr. Flick ascribe the function of relieving the airports of the unwanted byproduct consisting of noise generated by landing and departing aircraft? The quantitative approach to the analysis of environmental repercussion within the framework of generalized input-output analysis outlined by me can and certainly will be superseded by more effective formulations; Mr. Flick's critical remarks and positive proposals do not seem however to point in the right direction. presented in my paper entitled Material Income, Economic Structure, and Environmental Externalities, in Measurement of Economic and Social Performance, edited by Milton Moss, National Bureau of Economic Research Press, New York (forthcoming 1974).

When a continuous time model is estimated from its non-recursive discrete approximation, the presence of identities and exogenous variables in the system does not preclude the use of standard procedures. However, if we wish to use the exact discrete model for estimation purposes, the treatment of identities and exogenous variables is not so straightforward. It is found that the procedure based on the exact discrete model is unlikely to be affected by the presence of identities, but when exogenous variables occur in the system some sort of approximation is usually necessary before the model can be estimated with discrete data. An approximate model is constructed to deal with the latter case and the asymptotic properties of estimators derived from this model are investigated. UNDER CERTAIN CONDITIONS, a stochastic model represented by a system of continuously distributed lags can be regarded as the solution of a system,of linear stochastic differential equations. Two general approaches are available if we wish to estimate the parameters of such a system by conventional methods and with discrete data.2 The first approach (see [1 and 2]) is to take a discrete approximation to the model and estimate the approximate model by standard methods. The second approach makes use of the discrete model which is known to correspond to the continuous time model in the sense that observations at equidistant points in time that are generated by the latter system also satisfy the former. The main advantage of the second approach is that no specification error is involved, so that it is possible in some cases to obtain consistent and asymptotically efficient estimators of the parameters in the model. In addition to the arguments of asymptotic theory, the results of a previous study [8] have given some recommendation to the second approach on the basis of small sampling performance. However, the model used in the sampling experiment of this study was relatively simple and it is the aim of the present paper to discuss the use of the second approach in more complicated models. The complications with which we will be concerned are the presence of identities and exogenous variables; both these complications may be expected to occur in more realistic economic, models. Before the procedure is viable when there are identities in the model, we must ascertain whether the disturbance in the exact discrete model has a non-singular