Knowledge that Transforms

Обсуждаются критические замечания, высказывавшиеся в отношении утверждений о зависимости между выпуском продукции и затратами на ее производство. Разбор проведен на основе статистического анализа реальных данных (как в кратко-, так и в долгосрочном периоде).

A T one time the proposition that an increase in the wage rate would call forth a smaller number of hours of work from an individual laborer was evidently accepted by economists without qualification. For example, Professor Pigou in I920, arguing that the imposition of a tax on a laborer (the opposite of a wage increase) would result in his working more hours, wrote: Since a part of his income is taken away, the last unit of income that is left to him will be desired more urgently than the last unit of income that would have been left to him if there had been no taxation. But the last unit of energy that he devotes to work will not affect him differently from what it did. Consequently, there will be a tendency for him to work a little harder than he would have done otherwise. 1 Again in I928, Professor Pigou put the same arguments more specifically. Then, since income is taken away from the taxpayers, the marginal utility of money to them is raised, but the marginal disutility of work is unchanged. And Professor Pigou continued with a statement on the attainment of an equilibrium position: Hence, unless they are somehow impeded, they will increase the amount of work done, and so of income obtained, up to the point at which the marginal utility of income and the marginal disutility of work done to secure it again become equal-which is obviously the optimum. 2 (Italics in original.) Similarly Professor Knight in I92i argued that if men act rationally, . they will at a higher rate divide their time between wageearning and non-industrial uses in such a way as to earn more money, indeed, but to work fewer hours. 3 (Italics in original.) Both Professor Pigou and Professor Knight based their conclusions on an assumption of diminishing marginal utility of income. The unanimity of expert opinion was broken by Professor Robbins in I930.4 Phrasing his argument in terms of the effort (as distinguished from the money) prices of the goods constituting real income, Professor Robbins pointed out that it is the elasticity of the demand for income with respect to effort that determines the responsiveness of the individual's hours of work to changes in wage rates. If this elasticity is greater than unity, a decrease in wage rates (or the imposition of a tax) will result in fewer hours of labor. If the elasticity is less than unity a decline in wage rates or an increase in taxes will result in more hours of labor.5 Thus Professors Pigou and Knight had implicitly assumed that the elasticity of demand for income in terms of effort is less than unity. Professor Robbins agreed that the deductions of the earlier authors justify the downward slope of a curve representing demand for income in terms of effort prices, but he contended that nothing in their arguments shows that the elasticity of such a curve is necessarily less than unity.6 Professor Paish presented much the same viewpoint as did Professor Robbins, but Professor Paish based his analysis on the demand for leisure, which he treated as a good.7 If income is decreased as a result of an increase in taxation, argued Professor Paish, the result may be either to increase or to decrease a person's demand for leisure. Assuming a flat rate tax increase or a decrease in hourly wages, both aggregate income and marginal income decline. The decline in aggregate income will cause a person to demand fewer hours of leisure. The decrease in marginal income, however, will have the opposite effect; it reduces the cost of addi-

DESPITE extensive controversy and discussion,1 the subject of monetary interest theory still seems to involve a considerable residue of confusion and uncertainty. While the writer does not pretend to be able to unsnarl all the tangled threads of this complex subject, it is hoped that the analysis presented here will serve three somewhat interrelated purposes: (i) to clarify the relation between the Keynesian liquidity preference theory and the loanable funds theory espoused by Robertson, Haberler, and others; (2) to produce a clearer understanding of the relation between stock and flow analysis in monetary theory; and (3) to develop an important distinction between (a) the determination of the rate of interest in a short period when the level of income is not in equilibrium, and (b) the forces that explain the change that occurs in the rate of interest during a longer period as the level of income moves from one equilibrium position to another.

H. W. Singer, Gerald M. Meier, The Terms of Trade and Economic Development: Comment, The Review of Economics and Statistics, Vol. 40, No. 1, Part 2. Problems in International Economics (Feb., 1958), pp. 85-90

T HE importance of fluctuations in index numbers as guides to the formulation of economic policy decisions hardly requires emphasis. Changes in Federal Reserve policy, for example, are based, at least in part, upon price level variations, as measured either by the BLS consumer price index or by the index of wholesale prices. Similarly, many of the economic time series used by the Council of Economic Advisers as indicators of the state of the economy or of fundamental trends within the system are index numbers. And, to an ever increasing extent, the incomes of significant portions of our economy are adjusted periodically in response to movements in price indexes. spite of this situation, these indexes, which underlie so much of our economic life, are basically inadequate as quantitative measures of change. For, first of all, the solution to the problem of correct weighting of the members of the sample is not at all obvious.' But, in addition, the construction of an index number is normally associated with the selection, on an a priori basis, of the sample of commodities which is to be utilized in the evaluation of the index.2 use of such a judgment sample precludes the determination of the extent to which an observed difference in two indexes can be ascribed to sampling errors, rather than to real causes. This defect is extremely important, since index numbers are generally employed for intertemporal, interregional, or intersectoral comparisons, where differences are often quite small, and their significance correspondingly uncertain. Furthermore, the use of an arbitrary fixed sample permits neither changes in product quality nor the introduction or disappearance of consumer products readily to be incorporated into the standard type of index. Any attempt to take such effects into account must of necessity impair the continuity of the index through time. At present, the author knows of no method in use which will allow the realistic evaluation of the statistical errors associated with an index number. view of the practical significance of this problem, it is suggested in this paper that the items used in the computation of an index be chosen in a statistical manner. use of a probabilistic sample would, in principle at least, remove all the above mentioned deficiencies inherent in the normal method of sample selection. And, while the proposed procedure would not solve the problem of appropriate weighting, it would have the further advantage of being in conformity with the modern statistical trend towards the replacement of judgment samples by probability samples. order to test whether the use of a sampling procedure governed by the laws of chance would lead to unforeseen practical complications, it seemed advantageous to apply the method suggested, on a small scale, to a more or less realistic situation. Among other information which could be gained from a preliminary investigation of this nature would be an estimate of the magnitude of the sampling variance, as well as hints regarding the difficulties and problems which might arise in full-scale application. * author is indebted for valuable comments to Professors W. L. Crum, R. Dorfman, E. H. Huntington, and G. Kuznetz. Bureau of Business and Economic Research, University of California, Berkeley, kindly financed the study, and Mr. Kenneth J. Oberman aided in the research. 1 For a discussion of this problem see R. Frisch, Some Basic Principles of Price of Living Measurements, Econometrica, xxii (October I954), 505 f.; and M. J. Ulmer, Economic Theory of Cost of Living Index Numbers (New York, I949). 2 Thus, in describing the procedure employed for the selection of the list of goods included in the index, the BLS writes: In I950 and I95I the Bureau priced and studied the price changes of hundreds of items. Using this information and extensive price records of the past, the Bureau selected about 300 items, which together can be used to estimate the average change in prices of all items in the 'market basket.' U.S. Bureau of Labor Statistics, The Consumer Price Index as revised, I953, Bulletin II40 ('953), 3.

M OST descriptions of the behavior of private saving have dealt separately with net personal saving, net corporate saving, or capital consumption allowances. However, for many analytical purposes, and particularly the appraisal of inflationary or deflationary pressures, it is gross private saving as a whole the sum of these three components -that is crucial, and analysis of the details is of interest mainly in arriving at the implications for this total. Should it appear that total gross private saving bears a more stable relationship to key income or output measures than do its components, analysis could be both simplified and improved by dealing with this total directly. This is, in fact, what the data for past periods show. I recognize that this conclusion is contrary to the common a priori expectation, that it may not hold in the future, and that in retrospect it may appear as merely a statistical oddity. But the record of past experience seems to me clear enough to demand exploration. In the Survey of Current Business for January I955 1 I pointed out that the ratio of gross private saving to gross national product was about the same in I929 and each of the years from I948 through I953. This ratio continued to hold in I954, I955, and, on the basis of preliminary estimates, in I956. In these ten relatively prosperous peacetime years-all those for which estimates are available except for I946 and I947, when the saving rate clearly was sizably distorted by war-time influences gross private saving averaged I4.63 per cent of GNP, and never deviated more than onehalf percentage point from the average.2 The article cited also pointed out that in the 1930-4I period of substantial underutilization of resources, when saving fluctuated much more than GNP, a formula taking account of the difference between current-year GNP and GNP in the most recent year of substantially full employment would satisfactorily describe the saving pattern.3 As a result, gross private saving for the entire I929-56 period, excluding I942-47, is quite satisfactorily described by the following simple formula: Gross private saving = I463 Po .27 (POP.) where PO is the gross national product in the most recent high-employment year (including the current year) and P1 is gross national product in the current year. For high employment years, PO and P1 are the same, and we have simply gross private saving equals I4.63% of gross national product. The gross private saving estimate calculated from this formula for each of the 22 years of the period is compared with reported gross private saving in Table I.4 The mean deviation is $0.7 billion, or 3.I per cent of the average level of reported gross private saving. This is probably within the margin of error of the reported data. Indeed, reported gross private saving is more closely approximated by this formula than by the alternative estimate of gross private saving that can be derived from the national accounts statistics by deducting the government surplus on income and product transactions from gross investment. The difference between the two estimates, which is equal to the statistical discrepancy in the national accounts, averaged $I.o billion. For the ten high-employment years included in the period with which this note is primarily concerned, saving calculated as I4.63 per cent of GNP differs from reported saving by an average of $o.8 billion, or I.9 per cent, and the statistical discrepancy averages $I.3 billion.

IN this paper we present the results of a new study of the demand for passenger automobiles, embodying a number of improvements over the attempts of previous investigators. In particular: (a) some account is taken of the influence of credit conditions on demand; (b) the dynamics of the market derive primarily from the accumulation of a stock of cars rather than from the rate of change of income; (c) the statistical work is carried out in terms of first differences to facilitate testing the influence of the variables. In the final formulation of the demand function, annual retail sales of new passenger automobiles are explained by: (i) real disposable income; (2) the stock of passenger cars on the road, January I; and (3) the average real retail price of new passenger automobiles divided by the average number of months' duration of automobile credit contracts. The price variable is, thus, an index of the monthly payment associated with the purchase of passenger automobiles. Use of this variable involved an estimate of a retail price index and of the number of months' duration of credit contracts. The source and nature of these estimates is taken up in the Appendix. Finally (4), we use a dummy shift variable to account for the special conditions of the automobile market in years of severe production shortage. The demand was estimated by least-squares linear regression with the variables expressed in first differences. For purposes of summary, the results are expressed in Table i as elasticities computed by reference to mean values. The statistical demand schedule fits the observed behavior of the market very well. When the equation is expressed in first differences, the coefficient of multiple correlation is .93. When calculated changes are added to sales of the preceding year, the correlation between actual and predicted levels is .98. It is particularly notable that the sensational rise in demand in