I. Introduction, 592. — II. Organization of the U. S. electric power industry, 593. — III. The yardstick, 595. — IV. Short-run optimization problems of electric utilities, 597. — V. Interfirm coordination in New England, 599. — VI. Conclusions, 612.

Journal Article The Stability of Growth Equilibrium: Comment Get access J. R. Saegent J. R. Saegent Worcester College, Oxford Search for other works by this author on: Oxford Academic Google Scholar The Quarterly Journal of Economics, Volume 76, Issue 3, August 1962, Pages 494–501, https://doi.org/10.2307/1879636 Published: 01 August 1962

Introduction, 186. — I. Surplus disposal and the impairment of agriculture, 187. — II. The use of local currency holdings created out of the proceeds of surplus disposal and inflation, 193.

In this article we derive the exact finite sample frequency functions of the least squares and maximum likelihood estimators of the marginal propensity to consume, assuming the basic stochastic Keynesian model. The properties of these functions are considered in more detail for particular values of the parameters and sizes of sample. It is concluded that, for samples of 10 or more observations, generated by the model considered (with realistic values of the parameters), the maximum likelihood estimator of the marginal propensity to consume is the better general purpose estimator of this parameter. ALTHOUGH THERE have been several major contributions to the large sample theory of estimators of the parameters of simultaneous equation systems,' there is, as yet, virtually no small sample theory for these estimators. With the exception of Nagar's approximations for the bias and moment matrix of k-class estimators,2 evidence concerning the small sample behaviour of various estimators is confined to two types. The first type includes studies in which the parameters of simultaneous equation models have been estimated, by various methods, from real data, so that the resulting estimates can be compared, by either referring to economic theory and other a priori evidence, or testing predictions.3 The value of such studies is limited, however, by unknown errors in both the data and the specification of the models. The second type of evidence is provided by a number of valuable Monte Carlo studies.4 But these too have certain disadvantages as compared with a mathematical study. One is that, in order to investigate the effects of variations in the sample size or the structural parameters, it would be necessary to analyse many different sets of synthetic samples. Another is that the measures obtained from Monte Carlo studies are, themselves, subject to sampling errors. Moreover, in studies based upon no more than 100 synthetic samples, these errors are not negligible.5

SINCE I929 there has been a substantial change in the location of manufacturing in the United States. The direction of redistribution has fairly consistently been from north to south and from east to west. In I929 the South and West together accounted for less than one out of every four United States manufacturing employees and for only one-fifth of value added by manufacture. By I958 1 their share of United States manufacturing had increased to one-third as measured by either variable. This change has had a significant impact on the political, social, and economic life of the nation. The consequences for businessmen, labor leaders, and government officials have been strong, direct, and sometimes painful. Inevitably, the question that arises is why? Why did this change occur? What were the historical developments and economic forces that determined its extent and direction? The purpose of this paper is to delineate the outlines of an answer to this question. In particular, we shall examine and reject the hypothesis that regional shifts in demand or markets were the major determinant of locational change. Area differentials in the rate of growth of manufacturing are the result of area differentials in the rate of growth of individual industries and of area differences in industrial structure. The latter refers to the extent to which an area's industries are those which, at the national level, are experiencing rapid or slow growth. If an area has predominantly fast-growing industries, we say it has a structure. If it has predominantly slow-growing industries, we refer to its structure as unfavorable. 2 The first point to be made is that the redistribution of manufacturing since I929 has been primarily the result of area differentials in the growth of individual industries rather than the result of differences in industrial structure. This need not always be true. The shift of industry to the Southeast in England in the inter-war decades was attributed more to differences in industrial structure than to area differentials in the growth of specific industries.3 In the United States, I929-I954, the comparative growth of manufacturing employment by state, unadjusted, was highly correlated with comparative growth, adjusted for industrial structure. (Spearman's coefficient of rank correlation equals +.8 ii.) Comparative growth, unadjusted, showed no correlation with the extent to which a state had a comparatively favorable or unfavorable industrial structure. (Coefficient of rank correlation equals + .003.) 4 Table i presents the comparative gain or loss of manufacturing in each Census division between I929 and I954, and shows it divided into two parts. The first represents the sum of the comparative gains or losses of individual industries. The second, or remainder, is a rough measure of the influence of industrial structure.5

Tig HE appearance of Business Cycle Indicators pTovides a good opportunity to review some of the National Bureau's recent work on business cycles and forecasting.' It is more than a decade since the Bureau published Moore's Statistical Indicators of Cylical Revivals and Recessions, a paper which attained a degree of popularity unusual for National Bureau publications. 2 Since then, Moore's list of indicators has been kept up to date and widely used. The papers brought together in the present volume represent a comprehensive report on the recent work of Moore and his colleagues on cyclical indicators.3 Business Cycle Indicators consists of two volumes, the second of which is an appendix which describes and gives the monthly or quarterly data for a long list of series. Volume I is in three parts. The first and most important includes excerpts from annual reports of the National Bureau by Fabricant and Burns, Moore's earlier Occasional Papers on statistical indicators and several other papers by Moore, the original paper by Mitchell and Burns on indicators published in I938, a paper by Frank Morris on the predictive value of the leading series, and one by W. A. Beckett reporting on a set of indicators for Canada. Moore's revised list of 26 series is presented in Chapter 3. Part II contains six papers, some previously unpublished, on individual leading indicators -profits, business failures, new incorporations and new business firms, manufacturers' new orders, hours worked, and other labor-market series. Of these, the paper by Zarnowitz on new orders will probably be of greatest interest. None of these chapters is likely to excite the reader; they are all essentially descriptive; and some are outright stodgy in their style and treatment of their subject matter. Part III is concerned with methods of using the individual indicators and diffusion indices on a current basis. Two papers by Shiskin report on the work he has done with the indicators at the Census Bureau. Two others are by Moore. One describes an amplitude adjustment for the leading indicators, and the other deals with the average duration of run as a way of summarizing the current behavior of a group of series. I shall make no attempt to review each of these papers. Instead, in the rest of this article, I shall (i) compare the National Bureau's approach to business-cycle research with that which rests on the use of aggregative models and (2) attempt a general evaluation of the usefulness of economic indicators in short-run forecasting.

W HEREVER the test of implementation Al is applied to prescriptions for policy based on a priori reasoning, the mortality rate in ideas is bound to be high. Washington, D.C. is notoriously the graveyard of fond hopes and high aspirations. It seems fair to suggest that the conventional fate has overtaken a number of the ambitions in the monetary field announced at the outset of the Kennedy administration. Generally speaking, the President's advisers came to Washington persuaded, first, that monetary policy had been too stringent during the Eisenhower years, and, second, that the Board's policy of confining open market operations to the short end represented an unnecessary f orfeiting of a powerful weapon for stabilizing the economy through alteration of the interest rate strutture. But even the first few months of power brought home the realization that the opportunity for monetary leniency, under circumstances in which domestic economic conditions warrant such a policy, is significantly, even embarrassingly, restricted by the nation's balance-of-payments position. Several of the administration's experts had earlier been concerned about the restrictive implications of the external pressures. However, they failed to recognize the full magnitude of the problem, because they did not then appreciate, what experience has since taught: how difficult it is for the Federal Open Market Committee to alter, save temporarily, the interest rate structure by purchasing securities of varying maturities. As a consequence, the nation experienced in the recent recession an unheralded degree of monetary restraint, one which would probably have been regarded as intolerable had it occurred under the previous administration. Perhaps it is wise, however, not to reflect too long on the ironies of politics, but rather, in fairness to the highly qualified men who are the President's advisers, to acknowledge how quickly the lessons have been learned.