Knowledge that Transforms

In the February 1967 issue of the Review we presented estimates of a relationship between changes in help-wanted advertising normalized for growth in the labor force, and changes in the unemployment rate, and new hires, and a dummy variable reflecting the phase of the business cycle [11]. Two notes by Burch and Fabricant [2] and Gujarati [3] have expanded upon our findings. Each paper presents an alternative model and finds that in its own model the relationship between the unemployment rate and the amount of help-wanted advertising is not stable over the period 1951 through 1966 or 1968. The Burch-Fabricant paper tests for the shift in the coefficient of the reciprocal of the unemployment rate before and after 1957. The Gujarati paper tests for the difference in the slope of the unemployment coefficient in ten different business cycle phases from 1951 to 1968. Both papers seem to explain a greater fraction of the variance of the dependent variable than does our model. However, our dependent variable is the change in the normalized help-wanted advertising index; in the other two papers it is the level. By the usual standards, our ]R2 of 0.82 is at least as good as the somewhat higher correlations produced in the level equations. When the two tests suggested respectively by Burch and Fabricant, and Gujarati were applied to our model, the coefficient of the unemployment rate change variable proved to be stable. We first added a variable which is zero up to 1957 and equal to the change in the unemployment rate after 1957; in effect, the regression coefficient of AU is allowed to change its value in 1957. If this variable is estimated along with the other variables in our model, a simple t test will indicate whether the coefficient did in fact change after 1957. Our original equation for the period 1951-1966, second quarter, is reproduced as (1) below. The estimated equation with the dummy variable added is shown as (2):

for using input-output tables to make intercountry comparisons, including a type of graphic presentation, and to use these procedures to compare the economic structure of the United States with that of the Soviet Union, suggesting possible causes of differences. The United States table used is the 200-sector table for 1947.' Although this is earlier than other available tables, it is larger and thus more flexible to align with another table. The U.S.S.R. table used was derived by Vladimir Treml after extensive estimation of the portions missing in the published version.2

CONOMETRIC studies of absolute prices have generally ignored the corporation income tax as a possible explanatory variable; the public finance literature on the other hand contains much speculation that pricing might be affected by the tax, though it offers little empirical evidence. This paper draws on work in both fields to develop and test tax-price hypotheses against data from the textile and rubber industries. Analysis of price change involves linking the influences of supply and demand. The standard sources of hypotheses about the links are the theories of competition and monopoly. In both cases, the parameters of cost and utility ultimately determine price and quantity, but the emphasis differs as to what are the important decisions of firms in the process. The competitor is a price-taker who decides what quantity to supply; the monopolist may be either a price-taker, or a price-maker whose decision is what price to charge. It seems a common fact of observation that most industrial firms are price-makers who supply the resulting demand, and not vice versa, so for an analysis of prices of such products, monopoly theory is likely to be more fruitful of hypotheses than competitive theory. Our procedure therefore is to regard the industry as a monopolistic firm, and to deduce what industry data would show if this firm followed alternate simple pricing rules: profit maximization, target rate of return, percentage markup over variable costs, and sales maximization subject to a minimum rate of profit. Each rule is formulated in both taxfree and tax-influenced form. Textiles and rubber were chosen both for reasons of data convenience, and because they differ considerably in structure. Yearly data for 1924 through 1962 were drawn from the Treasury Department's Statistics of Income for Corporations, supplemented by the Bureau of the Census Annual Survey of Manufactures and Census of Manufactures, and by Bureau of Labor Statistics indexes of wholesale prices, wages and employment. The time period and data sources were dictated by the need to include both financial and operating information, and periods of both high and low tax rates. Several adjustments were made to the data, the most important of which was to remove, in the interests of sample homogeneity, Miscellaneous Plastics from rubber and Apparel from textiles. Hence the industries are somewhat narrower than those of the published two-digit Standard Industrial Classification. The war years 1942 through 1946, 1951 and 1952 were omitted from all regressions. Lags, differencing, and lack of early-year information restricted the final sample to 1928 through 1962 for rubber, and 1927 through 1962 for textiles. Yearly data for industry aggregates have obvious drawbacks for investigation of this sort. The aggregates are quite broad, and if pricing patterns are discernible in them, the patterns must be generated by average behavior over heterogeneous groups of products. Yearly observations provide little basis for studying lags. But it is an unfortunate reality that most econometric work on prices has been at even higher levels of aggregation than this. One can only caution that all results, including these, must be assessed in the light of the data weaknesses.

T HIS paper presents an econometric analysis of the behavior of wages and prices in the American steel industry and the experience with steel imports during the 1950's and 1960's. The results presented are a portion of a larger, and as yet unfinished, effort to explain profit in the steel industry by estimating an equation for each economically meaningful component of the industry's income statement and then combining the equations to form a complete system. Modern empirical investigation of the determinants of wages, prices, and imports has developed in two distinct contexts. First, in response to widespread public concern over rising wages and prices during the 1950's, economists derived and tested a series of new formal models (generally embodied in a single central regression equation) to describe the processes at work. As time has passed more models have been proposed, early formulations have been elaborated and extended, and more data have become available for testing. In general, however, these models have stayed at the economywide level, and little has been done to disaggregate them by industry classification. Second, the wage-price subsections of large macro-econometric models have attempted to provide a complete explanation of the inflationary process, but as with the single equation studies, there has been little analysis of the mechanism in any individual sector. This paper draws upon the theories and models which have been developed for economy-wide studies, modifies them where necessary, and applies them to the steel industry. The next three sections present the formulation and estimation of equations for the steel wage rate, the wholesale price index for steel, and the ratio of imports to domestic shipments. Then, with the aid of the estimated relationships, some short-run projections are made; finally, the analysis is summarized.

The problem was reduced to the apparently simple one of estimating the elasticity of substitution between capital and labor in the production functions of differing industries and determining whether these elasticities varied widely or were basically the same. After a lapse of eight years, however, the existence of factor reversal is still an unresolved question. In his 1967 summary article Marc Nerlove could write:

S. R. Johnson, Peter A. Haigh, Agricultural Land Price Differentials and Their Relationship to Potentially Modifiable Aspects of the Climate, The Review of Economics and Statistics, Vol. 52, No. 2 (May, 1970), pp. 173-180

T HE geographical distribution and mobility of the labor force have received considerable attention in the literature. However, while various factors have been proposed to explain these phenomena, a satisfactory formal theory of the migration and subsequent location of the labor force, susceptible to empirical verification, has not yet evolved. With this study, we hope to contribute to this evolution by developing and empirically testing a more refined theoretical model through the use of a rich but seldom exploited body of statistical data. One dominant emphasis in the existing literature is on the wage or income differential thesis. Raimon [1], in an analysis of the patterns of interstate migration in the United States from 1950 to 1958, found significant rank correlations between percentage changes in population arising from migration and (1) levels of average per capita income (r = .75), and (2) average earnings of employed workers (r = .85). His results are supported by Gallaway, Gilbert and Smith [21], who in a study of interstate migration for a later period, suggest that income differentials are statistically significant in explaining interstate migratory patterns over the interval 1955-1960. On the other hand, Nelson's study [31] of interstate migration during the periods 1935-1940 and 1949-1950 shows no relationship between migration and income differentials; and Easterlin's European emigration study [4] concludes that per capita income, used by itself, was a poor predictor of migration rates. Finally, Fleischer's analysis [51] of postwar Puerto Rican migration to the United States shows that the ratio of gross hourly earnings in the source and receiving areas was, by itself, a very poor predictor. A second emphasis in the literature concerns what one might loosely call the job vacancy thesis. Except for Nelson, there is general agreement about the importance of this variable, whether it is expressed in terms of percentage changes in employment over states (Raimon), unemployment differentials (Gallaway, et al.), the ratio of unemployment levels in source and receiving areas (Fleischer), or cycles in economic activity (Easterlin). Along similar lines, Bjork [6] introduced an index of demand for migrant labor 1 based on the belief that the economic growth of the United States during the period 1880-1950 was accompanied by a dramatic differential growth in demand for agricultural as opposed to nonagricultural labor and by differential rates of natural increase of the population over states. Although their evidence is circumstantial and indirect, both Nelson and Fleischer hypothesize that the role of information afforded by the presence of friends and relatives is a significant variable affecting the magnitude of migratory movements. This opinion is shared by Kirk and Huyck [7], who assert that, . . in the choice of alternative overseas destinations the emigrant will almost always forego theoretical maximum opportunity for the practical advantages of locating among relatives, friends, and countrymen overseas. The interpretation of the results recorded above is rendered difficult not only because of differing definitions of the variables, but also because of the identification problem implicit in some of the models. We contend that the apparently contradictory findings with respect

T HE present study applies the two-stage least squares principle to a nonlinear least squares estimation method; the nonlinear least squares method is based on Marquardt's maximum neighborhood method. The method is applied to the CES production functions of the Canadian manufacturing industries. Section II explains the application of the nonlinear least squares method to the CES production functions; in section III the estimated results are presented; section IV gives some qualifications to the results obtained in the present study.