Knowledge that Transforms

T HE intent of this study is to ascertain that linear combination of financial characteristics which large industrial corporations with low ratios of earnings per share to common stock price from those with high ratios.' The linear transformation of several variables into a single variate (z) permits the categorization of firms on the basis of whether the z values are greater or less than a predetermined mean value. The proposition which underlies the division of firms into high and low ratio groups is that, if allowance is made for the historical nature of earnings and for market imperfections, the earnings-to-stock-price ratio reflects the composite market valuation of such factors as financial risk and dividend policy.2 With this in mind, it is interesting to inquire whether certain basic measures can be used to differentiate successfully between the two classes. Discriminating variables, that is, financial characteristics chosen to reflect individual elements of risk and other factors which affect e/p ratios, include the ratio of dividends to earnings, the ratio of current assets to current liabilities, the rate of return on additional investment, the relative change in sales, and the comparative stability of the common stock price. The construction of the problem is designed to parallel the thinking of investors and/or financial executives. Despite the apparent continuity of risk gradations, firms tend to be grouped on the basis of low, medium, and high risk; e/p ratios (or their reciprocals) are often used as the initial stratification variable; and attention is customarily directed to the extreme classes. The evaluation of common stock and other corporate securities tends in ddition -to be carried out in terms of certain conventional ratios. Discriminant analysis, as employed here, is not intended as a substitute for multiple regression analysis. Given little knowledge as to the appropriate form and complexity of the general regression function, this approach nonetheless serves as a useful device for observing directly those characteristics which distinguish lowand high-risk categories. The relevant information obtained is large relative to the sample size. The derived relationships may in turn facilitate the formulation of multiple regression functions. The potential utility of the analysis which follows is at least threefold. First, procedures for the selection of underand overvalued stocks may be improved by the introduction of discriminant analysis. If the discriminating index suggests that a firm clearly belongs to one group while its e/p ratio indicates otherwise, some reason exists for believing the company's stock to be underor overpriced. Second, partial conclusions may be drawn as to the influence of changing stock market levels upon the importance of different factors which condition e/p ratios. Distributions of e/p ratios, exhibited in Table i for samples of large industrial firms, reflect (for example) a greater central tendency for the I952-55 period than for I948-5I. If the discriminating function based upon the I952-55 data fails to predict well for the earlier period, there is some presumption that weights of the individual variables have shifted. The index characteristic of discriminant analysis affords certain advantages in this respect. The discriminant function is applicable whatever the level of stock prices, provided the * The helpful assistance of W. W. Cooper and Carl Hensley, Carnegie Institute of Technology, and Charles Christenson, Harvard University, is acknowledged. The computations were performed in the computer center at Carnegie Institute of Technology. I The method employed is described in G. Tintner, Econometrics (New York, 1952), 96-I02. See also M. G. Kendall, The Advanced Theory of Statistics (London, I946), Vol. ii, 34I-48. By best discriminates is meant that the chance of erroneous classification is approximately minimal. 2Earnings-to-stock-price ratios are hereafter referred to as e/p ratios.

Jaroslav Vanek, The Natural Resource Content of Foreign Trade, 1870-1955, and the Relative Abundance of Natural Resources in the United States, The Review of Economics and Statistics, Vol. 41, No. 2, Part 1 (May, 1959), pp. 146-153

I F a speculator makes profits consistently this implies that he possesses the ability to forecast prices or price changes with a fair degree of success. Whether he thereby stabilizes price is another matter. That is the central problem of this article. The proposed theory relating speculators' profits and the stability of prices is intended to be applicable to those commodities traded on organized exchanges by two kinds of people, cspeculators and non-speculators. What distinguishes speculators from other traders in the market is that their profits depend only on the price or price change of the commodity they trade. Non-speculators' profits are determined not only by the price of the commodity traded on the organized exchange but also by the prices of other related commodities. If the non-speculators are hedgers, they can make their profits almost independent of the price level itself. What enters the excess demand curve of the non-speculators is some weighted sum of the prices of the commodities they handle. How-ever, I shall single out only the price of the commodity traded on the organized exchange when I come to discuss their excess demand. Some examples may make my distinction between speculators and non-speculators clearer. In the cotton market a non-speculator may be a textile manufacturer whose profit is a function of the price of raw cotton, cotton textiles, and other inputs besides raw cotton. By hedging or other means he can avoid taking a price risk and can specialize in producing cotton textiles to maximize his profits. In the foreign exchange market, one kind of non-speculator is an importer whose profit depends not only on the exchange rate, but also on shipping costs, the price of the commodity in the two countries, and the like. He too by hedging can avoid bearing the risk of a change in the exchange rate and can specialize in providing a merchandizing service. However, the stock market is not one for which the theory to be described seems applicable, because no reasonable distinction between speculators and other traders can be made. Perhaps the only non-speculators in that market are those corporations engaged in a new stock issue. In what follows I show that for a fairly general model positive speculators' profits imply that they have stabilized the price. My conclusion is the opposite of that reached by Professor Baumol. In a brilliant article recently published, Baumol gives a counter-example to disprove the proposition that if speculators make profits they necessarily stabilize the price.' After presenting my own model I show why Professor Baumol's results are unsatisfactory.

A GREAT deal of interest in metropolitan area analysis centers around the economic impact of autonomous forces upon any of the area's sectors and upon its totality. Researchers have often felt that even approximate knowledge of the structural relationship of the local economy would greatly facilitate their work. An interindustry flow table has been prepared for the St. Louis area, one of the ten largest metropolitan areas in the United States. From such a table it is but a short step to technical coefficients and the inverse matrix. Furthermore, from these tables income and employment multipliers can be estimated. Both are powerful tools in assessing the impact of final demand changes upon the economic activity of a metropolitan area. Much serious criticism has been leveled in the past against area technical coefficients which are deduced from national ones pertaining to an outdated period. This study undertakes to estimate 1955 coefficients with the help of data obtained directly from a sample of private and public bodies which together constitute the St. Louis metropolitan area economy. Based upon this information some activity and impact projections are attempted.

The following sections are included:The Leontief Paradox?Computational Procedures and Statistical DataStatistical Results and Implications

PROFESSOR SAMUELSON's path-breaking article on Interaction Between Multiplier Analysis and Principle of Acceleration appeared in this REVIEW almost twenty years ago. A large literature has developed in which basic ideas of that article have been applied to both business cycle and economic growth problems. In a considerable portion of that literature, Samuelson's warning that the representation is strictly a marginal analysis to be applied to study of small oscillations has been overlooked.' Samuelson's warning can be interpreted as meaning that time series generated by any particular solution of model will determine actual income for only a short time. Given mathematical model, relevant particular solution can change due either to (i) accelerator or multiplier coefficients changing (as Samuelson suggests), or (2) imposition of new initial conditions. Goodwin2 has examined various models in which accelerator coefficient is a variable. These non-linear models are mathematically complex, and specific limit cycles that Goodwin derives obviously are due to special assumptions he makes about how path of income affects accelerator coefficient. Hicks 3 has investigated how an otherwise explosive accelerator model will be affected by floors and ceilings. In this paper such floors and ceilings will be interpreted as imposing new initial conditions, and therefore this paper can be considered a reinterpretation of Hicks's setup.4 We will work with a slightly modified version of Samuelson's model, and assume that

T-flECHNICAL progress has received unprecedented attention by economists in the last few decades, but more because statistical evidence has imposed the subject on them than as a spontaneous development of economic thought. Indeed, the whole neo-classical movement and the increasing modern application of mathematics, which have contributed so much to improving the tools of economic analysis and to conferring rigor and definiteness on economic thought, have preferred to leave technical progress aside. The trouble is that technical changes are hard variables to deal with in analytical terms. The statistical data which have appeared in the last few decades have come as quite a surprise to economists, because their theories, from the Ricardian to the neo-classical, did not lead them to expect such results. I refer in particular to some statistical evidence for the United States and for other capitalistic countries which has shown that, on the average and in the long run, shares of labor and capital in the national product have not changed very much, that wages have not remained at the subsistence level but have risen in proportion to national income, that capital per man has indeed increased but output per man has also increased in proportion, that the rate of remuneration of capital has remained almost constant. In the absence of an economic theory giving a straightforward interpretation of all these outcomes the attention of economists has been called back more and more to changes in technology; and economic statisticians, in trying to evaluate these changes, have followed the easiest way: they have normally taken ratios of production to man-hours (labor productivities) and computed their changes through time. The procedure is very useful for many purposes but, among other limitations for example, the impossibility of taking into account qualitative improvements it has the major defect of referring only to labor, while the production process involves as well other factors of production whose productivity might change in a different way. This leads to different conclusions as to the productivity of the system as a whole. There have been some attempts by economists to complete these evaluations and to introduce capital into the picture, by making use of theoretical notions like the production function, but these attempts in the writer's opinion have neglected an important characteristic of capital that it is reproducible and that its process of production is also subject to technical change. It is my purpose in this paper to go into these problems. I shall try to give a short theoretical economic interpretation of technical change and suggest a procedure for evaluating it, with respect to all factors of production. When particular studies about qualitative improvements are available they may be incorporated in the same framework.