Arguing that the beliefs that there were no energy shortages in the US before the 1970s and that large-scale rationing requires government price controls are clearly wrong, the authors analyze the extent of the shortage, the nature of the rationing program, and the structure of the petroleum industry. They argue that regional isolation, industry concentration, and the vertical integration of the larger firms made rationing possible. In the absence of laws requiring rationing or setting prices, they focus on the hypothesis that the oil companies held prices down because they were afraid of hostile government actions. 22 references, 2 figures, 1 table.

ABSTRACT Many investors occasionally receive what they believe to be nonpublic information about a security. Others feel that by applying superior analytical skills to public information, they are able to arrive at valuable insights that are not generally appreciated. In either case, there is a substantial opportunity for profit if the investor is correct. The investor must be correct on two counts. First, the estimate of the worth of the information must be reasonably accurate in terms of its impact on the price of the stock, and second, the investor must make a realistic assessment of the likelihood that the market already has received the information or insight in question. This paper is concerned only with the latter problem. The probability distribution of the date on which the market receives information already in the hands of the investor is calculated for a simple model of information propagation. It is then shown how this probability distribution can be brought to bear on the management of a portfolio.

Many investors occasionally receive what they believe to be nonpublic information about a security. Others feel that by applying superior analytical skills to public information, they are able to arrive at valuable insights that are not generally appreciated. In either case, there is a substantial opportunity for profit if the investor is correct. The investor must be correct on two counts. First, the estimate of the worth of the information must be reasonably accurate in terms of its impact on the price of the stock, and second, the investor must make a realistic assessment of the likelihood that the market already has received the information or insight in question. This paper is concerned only with the latter problem. The probability distribution of the date on which the market receives information already in the hands of the investor is calculated for a simple model of information propagation. It is then shown how this probability distribution can be brought to bear on the management of a portfolio.

Abstract ABSTRACT: Little is known about the speed and accuracy of aggregate taxpayer response to an income tax law change. Using a multiple time series model, it was found that individuals and corporations quickly and relatively accurately adjust their income tax prepayments in response to a tax increase.

Applying Fishburn's [4] conditions for convex stochastic dominance, exact linear programming algorithms are proposed and implemented for assigning discrete return distributions into the first- and second-order stochastic dominance optimal sets. For third-order stochastic dominance, a superconvex stochastic dominance approach is defined which allows classification of choice elements into superdominated, mixed, and superoptimal sets. For a choice set of 896 security returns treated previously in the literature, 454, 25, and 13 distributions are in the first-, second-, and third-order convex stochastic dominance optimal sets, respectively. These optimal sets compare with admissible first-, second-, and third-order stochastic dominance sets of 682, 35, and 19 distributions, respectively. The applicability of superconvex stochastic dominance for continuous distributions defined over a bounded interval is then shown. The difficulties in identifying the elements of the superdominated set for distributions defined over the entire real line are demonstrated in the determination of the dominated choices for a set of normally distributed mutual fund returns previously examined by Meyer [9]. Specifically, we find that the dominated set determined by Meyer is too large.

Focuses on the reproduction of predatory pricing in laboratory environment. Definition on predatory pricing; Methods used to construct experimental design; Effect of predation on price increase and efficiency. Focuses on the reproduction of predatorypricing in laboratory environment. Definition on predatorypricing; Methods used to construct experimental design; Effect of predation on price increase and efficiency.

ABSTRACT Applying Fishburn's [4] conditions for convex stochastic dominance, exact linear programming algorithms are proposed and implemented for assigning discrete return distributions into the first‐ and second‐order stochastic dominance optimal sets. For third‐order stochastic dominance, a superconvex stochastic dominance approach is defined which allows classification of choice elements into superdominated, mixed, and superoptimal sets. For a choice set of 896 security returns treated previously in the literature, 454, 25, and 13 distributions are in the first‐, second‐, and third‐order convex stochastic dominance optimal sets, respectively. These optimal sets compare with admissible first‐, second‐, and third‐order stochastic dominance sets of 682, 35, and 19 distributions, respectively. The applicability of superconvex stochastic dominance for continuous distributions defined over a bounded interval is then shown. The difficulties in identifying the elements of the superdominated set for distributions defined over the entire real line are demonstrated in the determination of the dominated choices for a set of normally distributed mutual fund returns previously examined by Meyer [9]. Specifically, we find that the dominated set determined by Meyer is too large.