T HIS paper represents recent estimates of the rate of growth of output and labor productivity in wholesaling and retailing foods of farm origin destined for United States civilian consumption.' Technically, primary interest in the paper is in the results of using different measures of output for a trade group. These measures include an index of gross output and two indexes of net output, a double-deflated value added series and a margin-weighted series. The double-deflated value added series is nearest to an ideal measure of unduplicated output, whereas the margin-weighted index is a compromise usually dictated by available data.2 Margin-weighted net output indexes were used by Barger [2], Kendrick [5], and Alterman and Jacobs [1] in order to measure net output in total trade. As far as I know, there have been no previous attempts to estimate double-deflated value added net output for trade. I know of no previous studies of labor productivity in food trade. The major findings presented in this paper are: (a) net output per man-hour in wholesaling and retailing farm-originated foods grew at an average yearly rate of 2.8 per cent from 1929 to 1958, substantially faster than in the private nonfarm sector but less than in agriculture; (b) the double-deflated value added measure of net output rose significantly more than the margin-weighted measure during the period; and (c) gross output grew at about the same average yearly rate for the three decades as a whole as net output measured by doubledeflated value added.

CONVENTIONAL price theory predicts that industries in which output is produced by a few dominant firms may, in the long run, earn higher rates of return on the owners' investment than the opportunity cost of the equity capital, commonly called the normal or competitive rate of return. The emphasis on the long run recognizes that actual profit rates differ from normal in the short run for reasons independent of the number of sellers, e.g., changes in demand or cost which raise or lower profits until the reallocation of resources pushes the industry toward long-run equilibrium. The word may indicates that seller concentration is a necessary, but not sufficient, condition. For instance, if the few sellers fail to cooperate with regard to price and output, profits well turn out to be normal. Or, if entry is relatively easy, the oligopolists set a price close to the competitive level in order to discourage potential entrants. A price policy so designed is called pricing, the limit being that price above which entry would be attracted.' Joe Bain has examined the latter possibility by measuring the influence of barriers to entry, classified as very high, substantial, and moderateto-low, on the profit rates of the leading firms in a sample of oligopolistic industries for the periods 1936-1940 and 1947-1951.2 He expected that the price and the monopoly price would probably coincide in the very high barrier class while oligopolists in markets with substantial or moderate barriers might find it profitable to set an entry-forestalling price below the monopoly level, a price which approaches the competitive price as entry barriers decrease. Therefore, profit rates should decline as barriers to entry decrease. Bain found a distinct difference between the average profit rates of those industries in the very high barrier category and those in the other classes. No such clear difference appeared between the substantial and the moderate-to-low barrier classes. He further found . . that seller concentration alone is not an adequate indicator of the probable incidence of extremes of excess profits and monopolistic output restriction. The concurrent influence of the condition of entry should clearly be taken into account.' The purpose of this paper is to present the results of research into the relationship between seller concentration, barriers to entry, and profit rates for 1950 to 1960 to determine whether the pattern Bain found holds for a period of time that was not part of the Great Depression or of rapid postwar inflation. The findings support Bain's results, suggesting that a beginning has been made toward the accumulation of some evidence regarding the influence of two major aspects of market structure on rates of return.

T HAS long been recognized that a good economic forecast should consist of several components. In addition to predicting turning points, a forecast should theoretically include some statements about the timing of the and the amplitude and duration of the subsequent movement. If the forecaster makes quarterly quantitative estimates of GNP, he is, in fact, estimating all of the aforementioned components. However, when forecasters use other types of predictions, they usually do not provide estimates of the timing or amplitude. This is especially true when analysts speak of the forecasting behavior of the leading series and/or the rate of change methods. While has been considerable discussion about the success of these methods in forecasting turning points, I very little is known about other aspects of their forecasting behavior. It has generally been concluded, that, in practice, the leading series and rate of change methods predict every turning point of a predictand such as the Federal Reserve Board's Index of Industrial Production, but they also display a large number of false leads. As for their other forecasting characteristics, Moore2 has concluded that some information about the amplitude of a recession could be obtained about six months after the movement first began. Finally Wright and Okun have attempted to estimate the dates of turning points, I but no attempt has been made to attach probabilities to the predicted dates of turning points. Our paper will present one method for attaching probabilities to the turning point forecasts which are obtained from using the leading series and diffusion indexes. The probability must refer to the likelihood of the predictand's occurring in a given time interval. Statements such as there will be a turn or there is an X per cent chance of a turn are tautologies, for sooner or later will be a turn. Thus to have any usefulness, the probabilities must be attached to specific time periods. In the following section we shall outline the methodology of the study, discuss the data to which this methodology was applied, and finally present the results.