Assuming rational expectations, a specialization of Ross' Arbitrage Pricing Theory is used to obtain a simple securities market valuation formula when dividends follow linear stochastic processes. The implications of this model for the use of accounting data to measure risk and for capital budgeting are explored. A new measure of riskiness based on accounting data is derived, and the use of risk-adjusted discount rates is evaluated.

Journal Article A Model of Promotional Competition in Oligopoly Get access Richard Schmalensee Richard Schmalensee University of California, San Diego Search for other works by this author on: Oxford Academic Google Scholar The Review of Economic Studies, Volume 43, Issue 3, October 1976, Pages 493–507, https://doi.org/10.2307/2297228 Published: 01 October 1976 Article history Received: 01 May 1974 Accepted: 01 July 1975 Published: 01 October 1976

Journal Article Market Structure, Durability, and Maintenance Effort Get access Richard Schmalensee Richard Schmalensee University of California, San Diego, and Catholic University of Louvain Search for other works by this author on: Oxford Academic Google Scholar The Review of Economic Studies, Volume 41, Issue 2, April 1974, Pages 277–287, https://doi.org/10.2307/2296716 Published: 01 April 1974

In many markets, sellers have imperfect information about the costs of sales to different buyers, and the pattern of competitive pricing depends on the information available. In order to analyze the equity implications of public policies requiring information suppression, non-utilitarian measures of the horizontal and vertical dimensions of pricing inequity caused by cross-subsidization are proposed and examined. Better information generally reduces vertical inequity, but if information about buyers is initially poor, additional imperfect information may increase horizontal inequity. If information is initially good, more information generally lowers both dimensions of inequity.

This paper reports on an experimental study of expectation formation-and revision in a time series context. In an adaptive expectations framework, it is shown that the speed of adjustment seems to fall in turning point periods. Expectations are considered as probability density functions, and a scoring system is devised and employed that gives subjects an incentive to report a measure of the dispersion of these functions. This measure, which is inversely related to the confidence with which expectations are held, seems to be inversely related to past forecasting performance. THIS PAPER REPORTS an empirical exploration of the way individuals form and hold expectations about future values of time series variables. In the application of economic models in which expectations about the future play a major role in determining behavior, these expectations are rarely directly observable, and the econometrician is generally forced to assume that a technical rule generates expectations as a simple function only of past observations. One way to see what sort of technical rules make sense in such applications might be to attempt to use this indirect approach to discriminate among possible functional forms. Usually, however, this is computationally burdensome and not terribly revealing. Another approach, currently receiving attention, involves direct analysis of realworld expectations data.2 A third approach, and the ope followed here, is to create and analyze an experimental situation in which the rule followed must be technical because no information other than the past history of the time series in question is available. The main reason for the attractiveness of the experimental approach here, however, lies in the two aspects of expectation formation with which this study is principally concerned. The first of these concerns the influence of turning points in a time series context. The basic hypothesis is due to F. M. Fisher [9, p. 48]:

N theoretical discussions industrial organization specialists often indicate a preference for comprehensive or summary concentration indices over the more readily available concentration ratios. Such indices consider the entire size distribution of sellers in a market, and they give weight to both fewness of sellers and inequality of market shares. The most popular such measure is probably the H index of Hirschman (1945) and Herfindahl (1950). (See Hart (1975) for a discussion of alternatives and a list of references.) Let P1 be the share of the largest firm in an industry, measured in terms of sales, employment, or whatever scale variable is considered most relevant, let P2 be the share of the second largest firm, and so on, in a market with N sellers. Then H is defined by

US antitrust policy takes as its objective consumer welfare, not total economic welfare. With that objective, Joe Bain's definition of entry barriers is more useful than George Stigler's or definitions based on economic welfare. It follows that economies of scale that involve sunk costs may create antitrust barriers to entry. A simple model shows that sunk costs without scale economies may discourage entry without creating an antitrust entry barrier.(This abstract was borrowed from another version of this item.)

A half-century ago, Joseph Schumpeter (1950 Chapters 5–8) presented a vision of modern capitalism in which monopolies are common but frequently swept aside by a “perennial gale of creative destruction” (p. 84). This gale is driven not by price competition, but by “competition from the new commodity, the new technology ... competition which strikes not at the margins of the profits of the existing firms but at their foundations and their very lives” (p. 84). I focus here on the personal-computer (PC) software (hereafter simply “software”) industry, which resembles this vision. I discuss some important issues this industry poses for antitrust policy and, in the final section, illustrate with examples from the Microsoft case.

HD28 .M414 no.1531-, 84,