Knowledge that Transforms

T HE volume under review is the result of the collective effort of twenty-five economists. It consists of a set of chapters each representing a building block for a large scale model of the United States economy, and an attempt at the end of the volume to put all these blocks together into one coherent and potentially useful structure. To review a volume which ranges so widely over almost all aspects of economics, the reviewer himself would have to be a committee. To review the final model adequately, one would need computer and programing resources which are beyond anything currently available to individuals. I shall, therefore, concentrate on reviewing the volume rather than the final model produced by the Brookings-SSRC group. This may be also desirable, since a final version of the model which the authors would stand by and take responsibility for may not yet exist.' One of the original ideas which led to this volume was that by parceling out different sectors and aspects of the economy to different one could integrate all of the best available theoretical and empirical knowledge into the model and thereby improve it greatly. To a great degree, therefore, the final quality of the model rests on the success with which the individual sectors were specified and estimated. Ideally, the job of a specialist would consist of first surveying the theoretical literature in a field (at the level of an AER or EJ review article), then surveying the associated quantitative-econometric knowledge and evidence, running a race between all the plausible econometric models which have not been eliminated on a priori grounds earlier, and submitting the winner to the final model. Taken seriously, this is a task of very great magnitude. By using the model builders implicitly assumed that much of this has already been accomplished by the specialists in the process of becoming specialists. This may have been a somewhat too optimistic assessment both of the processes of education in economics and the state of research in most of its subfields. Nevertheless, it must be assumed that each of the pieces would try to represent as well as possible the current state of quantitative economic knowledge about the various sectors of the economy. To be useful in constructing an econometric model of the whole economy, one would hope that each of the proffered relationships would be based as much as possible on existing (correct! ) economic theory (which derives the implications of purposive behavior of consumers, producers, and other economic actors from the interaction of their tastes and the constraints facing them) and will reflect those structural and institutional aspects of the economy which remain relatively stable from period to period and not the accidental confluence of different time series. It is in this light that I will examine below the sixteen individual chapters which constitute the bulk of the book.2

ECONOMISTS have recently begun to devote an increasing amount of attention to the relationships among interest rates on various instruments. Rates on instruments which differ with respect to maturity alone, all other features supposedly being held constant, have in particular received a great deal of attention since the publication of Meiselman's [7] work in 1962. While the term structure has certainly received the most concern, import-ant contributions have been made to the broader problem of studying relationships among rates on bonds which differ with respect to features other than maturity.' An especially important aspect of this broader area of research lies in examining the relationships between rates on government and corporate bonds. Knowledge of the characteristics of these relationships is important for an understanding of the paths through which monetary policy affects yields on corporate bonds, and hence, perhaps, expenditures on investment. This paper presents the results of an examination of the relationships among several interest rates on government and corporate bonds for the period January 1951 through December 1960. Monthly data are used, and series for the rates on three-month treasury bills, one, two, three, four, five, ten, and twentyyear government bonds, commercial paper, and Moody's Aaa's and Baa's are studied.2 This list represents an array of instruments ranging over a broad maturity spectrum and featuring various levels of quality. Tools of spectral and cross-spectral analysis are used to study the behavior of the series and the relationships among the series at various important components of oscillation.3 In addition to calculating the standard statistics associated with the spectrum and cross-spectrum, the relatively new tool of complex demodulation is employed to study the seasonal behavior of selected rates.4

T HE appropriations series collected by the National Industrial Conference Board (NICB) come closer than any other data to pinpointing the time of investment decisions. This paper reports a study of the time lags between the basic stimulants of investment output, cash flow, and interest rate and these appropriations. We find that appropriations respond quickly to these incentives. Three points summarize the results for the all manufacturing:

N ONE of the procedures used in the measurement of investment has generated more controversy than the deflation of construction expenditures, for the measured rate of growth of real investment in structures in the United States varies over a wide range depending on which price index is chosen. Deflators proposed for United States construction range from the official Department of Commerce Cost (CCC) used in the United States National Accounts, which implies that real investment in nonresidential structures grew by 228 per cent from 1919 to 1966, to the Bureau of Public Roads (BPR) Composite Highway Index suggested in [7], which implies a much higher 19191966 increase of 47& per cent. Far from achieving a reconciliation between these two alternatives, conflicting conclusions were reached in the most recent detailed studies of the subject. Dacy [2] [3] has proposed a method which yields a 1947-1963 price increase much closer to that of the BPR highway series than that of the CCC index, while Kendrick, R. A. Gordon, and other have cited evidence supporting the much faster long-run upward trend of the CCC.1 A resolution of this conflict would allow us to evaluate and improve United States capital stock data, which have recently been criticized for ignoring an alleged bias in the construction price deflators.2 Can the apparent decline in the United States capital-output ratio between the 1920's and 1950's, for instance, be partly explained by defects in the official construction price indexes? In addition, improved information on construction prices would yield new output and productivity indexes suitable for testing the commonplace proposition that construction is a primitive industry in which efficiency improvements are almost as rare as in barbershops and the United States Post Office.3 This paper examines primary source data on the subject and proposes a new construction price index for the period 1919-1966. The new index is based partly on actual buyers' prices paid for several structural components and partly on an improved version of Dacy's indirect method using aggregative data for the entire contract construction industry. To anticipate the conclusion of the paper, the new index exhibits a long-run trend which is, appropriately enough, halfway between those of the CCC and BPR indexes and suggests that the official data overstate investment in structures in the mid-1920's by more than 35 per cent. The paper also suggests that productivity advances in construction have been surprisingly rapid in the postwar years, in contrast to an apparent stagnation of efficiency in the prewar period.

F. Gerard Adams, Grace Milgram, Edward W. Green, Christine Mansfield, Undeveloped Land Prices During Urbanization: A Micro-Empirical Study Over Time, The Review of Economics and Statistics, Vol. 50, No. 2 (May, 1968), pp. 248-258

OR many years there has been deep concern as to whether a shortage of doctors exists either nationally or in particular localities. This study investigates how well the distribution of the national stocks of medics (the generic term used here to refer to physicians and dentists) among areas corresponds to the distribution of population, and what influence is exerted by other variables such as effective demand for medical service, barriers to migration, and the locational preferences of medics. The unit of area in this study is the state; this is mainly because of availability of data. However, differences of size among the states, as well as in the relative populations of rural and urban areas and in the distribution of the urban population among large and small cities, seriously affect the observations. To remedy the resulting distortions as fully as possible, one of the authors is now analyzing the determinants of physician location among counties with results to be presented in a subsequent paper. However, many more variables for longer periods of time can be analyzed for states as a whole than for smaller sub-divisions.' The substance of our findings is contained in the regressions presented in the various tables. In considering them, the reader should bear in mind the following points: (1) We have analyzed a number of distinct types of medics: All Physicians, Self-employed Physicians and Dentists. Where our findings apply to all types we make generic statements. (2) To avoid discursiveness we discuss only those coefficients believed indicative of pervasive long-run forces affecting the allocation of medics. (3) In section I, the discussion is purely descriptive, i.e., the regression coefficients reflect observed associations but are not estimates of the structural parameters of a particular model. They do, however, have theoretical relevance. Some estimates of demand and supply functions are discussed in section II. (4) The years studied are 1930, 1940, 1950 and 1960 or, for some variables, years close to them. Lack of data for a sufficient number of years makes satisfactory time series analysis impossible. Section III summarizes our findings, and comments briefly upon their empirical implications. Our dictionary of variables is as follows: X (i)-Number of medics in the ith state. X2 -) Population of the ith state. X3()(Total) personal income of the ith state. X4-Volume of training facilities (number of places in medical classes) in ith state. X5-i Barriers to entry (percentage of applicants for licensure who fail examinations) in ith state. X6Population in ith state living in urban areas of more than 2,500 persons. X7-) Average income of medics in ith state.

D IFFERENTIATING a production function with respect to capital and labor yields equations for the marginal productivity of capital and the marginal productivity of labor. The variables that determine the marginal products in these equations are the same as those in the production function. If the data used to estimate the parameters of the production function are inserted into the equations for the marginal products, the marginal productivities of both capital and labor can be estimated empirically. The same data and equations also make it possible to determine the causes of any changes in the marginal products. How much of the rising marginal productivity of labor is caused by technical progress; how much is caused by a rising capital-labor ratio? If the economy is in equilibrium and there are no economies or diseconomies of scale, actual and marginal returns should be identical. Any differences between the estimated marginal products and the actual returns to capital and labor means that the economy is in disequilibrium; the size of the differences measures the extent of disequilibrium. If disequilibrium does exist, what causes the observed pattern? What are its implications for investment decisions in both human and physical capital? This paper applies the above approach to the American economy from 1929 to 1965.

U NTIL the mid-1950's, the traditional view on the consumption of housing had been that the elasticity of housing consumption with respect to current income was less than unity.' However, recent literature on the theory of consumption function [15] [4] has pointed out that, in relating income to consumption, the concept of income should be that of permanent income rather than current or measured income, and that the use of measured income imparts a downward bias in estimating the effect of permanent income on consumption. Since housing consumption in particular may also be affected by the long-run prospect of income rather than by a single-year measured income, the permanent income elasticity may be higher than the previous estimates of the measured income elasticity of housing. The change in the concept of income encouraged a number of economists to test the effect of permanent income on housing consumption. Maisel and Winnick [14] tested the permanent income hypothesis of housing consumption by utilizing the I950 Survey of Consumer Expenditures. Contrary to the permanent income hypothesis, however, they reported that housing consumption was no more responsive to changes in permanent income than to changes in measured current income. Subsequently Margaret Reid [19] conducted an extensive cross-sectional study by using housing and income data obtained primarily from the 1950 Housing Census. Differing from Maisel and Winnick, Reid found that the demand for housing was indeed more responsive to changes in permanent income. Moreover, Reid's estimates of the permanent income elasticity of housing were substantially greater than one, and in fact ranged from 1.5 to 2. On the other hand, the author's recent time-series analyses [10] [11] indicated that while housing demand was more responsive to changes in permanent income, the permanent income elasticity of housing was still less than unity. The purpose of this paper is to obtain the cross-sectional estimates of permanent income elasticity on the basis of the 1960-1961-1962 reinterview Surveys of Consumer Finances. This study has three distinct features. First, this study differs from other housing studies in that it uses the instrumental variable method along the lines suggested by Livitan [12]. Livitan has recently shown that, for any year of analysis, the use of a lagged or future measured income as an instrumental variable yields a powerful test of the permanent income hypothesis. Second, since this study utilizes threeyear reinterview data, as a result both one-year and two-year lagged or future incomes can be used as instrumental variables. Due to the lack of data, Livitan [12] could not experiment with a two-year lagged or future income as an instrumental variable in his analysis of total consumption. Both Livitan [13] and Friedman [5], however, agreed that it is highly desirable to use a two-year lagged or future income as an instrumental variable. Finally, this paper develops and uses an extended version of Livitan's instrumental variable method in order to take account of the case in which a lagged or future income may not be a perfect instrumental variable for permanent income. The cross-sectional estimates of permanent income elasticity so estimated are substantially * The author is Professor of Economics at the University of Wisconsin-Milwaukee and a member of the Social Systems Research Institute at the University of Wisconsin, Madison. He is grateful to Melvin Lurie and Keith Phillips for their helpful comments on the initial draft of this paper. The author, however, remains responsible for the views expressed in this paper. This study was originally supported by the National Science Foundation under grant GS-631 and later by the Graduate School of the University of Wisconsin-Milwaukee. The data used in the study originally came from the Surveys of Consumer Finances conducted by the Survey Research Center, University of Michigan, in cooperation with the Board of the Governors of the Federal Reserve System. The author is indebted to the Social Systems Research Institute for making available the data coded on magnetic tapes. 1 For a brief account of the early history of housing studies, see the author's paper [10, pp. 82-83].