This paper analyzes the role of wealth distribution in macroeconomics through investment in human capital. It is shown that in the presence of credit markets' imperfections and indivisibilities in investment in human capital, the initial distribution of wealth affects aggregate output and investment both in the short and in the long run, as there are multiple steady states. This paper therefore provides an additional explanation for the persistent differences in per-capita output across countries. Furthermore, the paper shows that cross-country differences in macroeconomic adjustment to aggregate shocks can be attributed, among other factors, to differences in wealth and income distribution across countries.

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Income Distribution and Macroeconomics

Suppose that a population of individuals may be grouped according to some vector of characteristics into "clusters," such that each cluster is very "similar" in terms of the attributes of its members, but different clusters have members with very "dissimilar" attributes In that case we say that the society is polarized Our purpose is to study polarization, and to provide a theory of its measurement Our contention is that polarization, as conceptualized here, is closely related to the generation of social tensions, to the possibilities of revolution and revolt, and to the existence of social unrest in general We take special care to distinguish our theory from the theory of inequality measurement We derive measures of polarization that are easily applicable to distributions of characteristics such as income and wealth

On the measurement of polarization

This paper examines the role of secondary data-sets in empirical economic research, taking the field of income distribution as a case study. We illustrate problems faced by users of "secondary" statistics, showing how both cross-country comparisons and time-series analysis can depend sensitively on the choice of data. After describing the genealogy of secondary data-sets on income inequality, we consider the main methodological issues and discuss their implications for comparisons of income inequality across OECD countries and over time. The lessons to be drawn for the construction and use of secondary data-sets are summarized at the end of the paper.

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Promise and Pitfalls in the Use of "Secondary" Data-Sets: Income Inequality in OECD Countries As a Case Study

Inequality, poverty, and development

Lawrence Weiser and Keith Jay have made an important contribution to our efforts to sort out the relative significance of innovational activities, different types of labor skills, and economies of scale as determinants of the commodity structure of international trade. In particular, they provide new evidence substantiating the importance of technological progress as a basis for the U.S. comparative advantage position as well as support for the view that scale economies should be given greater weight than my study indicated. However, there are still a number of questions and problems to be answered before very firm conclusions can be drawn on these matters. In an effort to disentangle the relative importance of the innovational and skill factors, the authors calculate a measure of technical progress for various U.S. manufacturing industries between 1961 and 1967. However, their estimate of technical progress does not take explicit account of changes in the skill levels of industries during that period. Consequently, one still cannot be sure of the extent to which the measure represents innovational activity versus changes in the quality of labor. Although my study indicates that the size of plants in export industries is considerably larger than in import-competing industries, the scale variable did not show up as significant in the various multiple regressions that included such variables as capital/ labor ratios by industry, proportions of various skill groups, and R&D efforts. However, Weiser and Jay do obtain significant multiple regression results for the scale factor when they use Gary Htifbauer's measure of the scale variable and a different dependent variable than the one I uised. Their dependent variable is the ratio of U.S. exports of each industry to the industry exports of eleven leading exporting countries whereas my dependent variable was adjusted U.S. exports minus adjusted U.S. imports. It should be noted that when they used Hufbauer's scale variable and exports minus imports as the dependent variable, they failed to obtain a significant result for the scale variable. To a considerable extent, therefore, the issue seems to come down to what is the best dependent variable to use. Clearly, if one is interested in the best indicator of export performance (as they are), a variable including imports is not appropriate. However, trade theory should, I think, generally focus on net trade flows rather than just exports or imports since the policy variables in which we usually are concerned are framed in net terms, for example, balance-of-trade or net employment effects of trade policy changes. As the authors are aware, it might well be that their scale variable would not show up as significant if they in some way also included the U.S. world import share by industry as part of their dependent variable. It would be interesting, to extend their analysis of trade patterns along these lines as well as by taking account of skill changes in calculating a measure of technical progress.

Determinants of the Commodity Structure of US. Trade

N this paper the distribution of before-tax income among consumer units in ten other countries is compared with that of the United States, and an attempt is made to explain the differences that are observed. The comparisons are made by selecting, from the relative wealth of American data, distributions that match those for other countries as closely as possible with respect to the strata of society covered, the concept of the incomereceiving unit, the definition of income, and general technique (e.g., whether tax returns or sample surveys or both were the basic source of information). The results are presented in a highly summarized form in Table i. The measures of inequality, the source materials, the way in which different bodies of data were matched, and the biases affecting particular comparisons are discussed in detail elsewhere.' Although we shall summarize some of the general sources of bias affecting the comparisons, our main attention in this paper will be devoted to the explanation of international differences in equality. While the comparisons in Table I still contain unknown margins of error, it seems likely that Denmark, Israel (Jewish population only), and the Netherlands have less inequality than the United States (with more certainty about Denmark than the others); Great Britain, Japan, and Canada about the same degree of inequality (with the first probably having a little less and the last a little more inequality than the United States); and Italy, Puerto Rico, Ceylon, and El Salvador more inequality than the United States (in most probable order of increasing inequality). The position of the last four countries tends to confirm the results of earlier comparisons indicating greater inequality in underdeveloped countries than in developed ones.2 Indeed, the remaining biases in the comparisons probably work in the direction of understating the relative equality in the distribution of income in the United States vis-a-vis the other countries, and, more generally, in the developed vis-a-vis the underdeveloped countries. Among the factors that tend to bias the comparisons so as to underestimate the extent to which the underdeveloped countries have less equality are (i) the frequent inclusion of non-money incomes in the data of developed countries and their exclusion in many distributions of the undeveloped countries, (2) the possibility that the lengthening of the accounting period beyond one year might reduce inequality more in the developed than in the underdeveloped countries, (3) the effect of old age pensions prevalent in the rich but not in the poor countries -in splitting off older individuals from units containing economically active persons and thus increasing the relative number of lowincome units in the rich countries, and (4) the likelihood that high incomes tend to escape measurement to a greater degree in underdeveloped countries which tend to have less efficient tax administration. The major factors working in the opposite direction are (i) the omission of incomes accruing mainly to high income units in the form of capital gains, expense accounts, and other tax-free forms, and (2) the existence of international differences in price structure of such a character that interclass differences in prices reduce the observed inequality in the distribution of money incomes more in poor than in rich countries. Considering the varied aspects of inequality measured by our five indexes, the results ' See Chapter VII of the author's Structure of Income, a forthcoming volume in the monograph series of the University of Pennsylvania's Wharton School Study of Consumer Expenditures, Incomes and Savings. The Study has been supported by a grant from the Ford Foundation. The author wishes to acknowledge helpful comments on an earlier version of this paper made by R. A. Easterlin, I. Friend, L. R. Klein, and S. Kuznets. Mr. Manoranjin Dutta did the statistical work. 2T. Morgan, "Distribution of Income in Ceylon, Puerto Rico, the United States and the United Kingdom," Economic Journal, LXIII (December I953), 82I-34; and S. Kuznets, "Regional Economic Trends and Levels of Living," F. M. Hauser, ed., Population and World Politics (Glencoe, Ill., I958), 79-II7.

https://www.jstor.org/stable/pdfplus/1925690.pdf

International Differences in the Distribution of Income

THIS paper summarizes the results of an exploratory study of wage levels in relation to the foreign trade of the United States.' Attention is concentrated on manufacturing industries, although mining and agriculture are also included. The broad conclusion is that export industries tend to pay higher wages than importcompeting industries (i.e., the industrial classifications within which the largest volume of competitive imports fall). Within the manufacturing sector, the difference is associated with the higher wages paid by durable goods industries as compared with nondurable goods industries; that is, a large part of the difference is connected with the fact that the proportion of durable goods industries is higher among the leading export industries than among the leading import-competing industries. Even greater wage differences are found when the leading export industries are compared with industries producing commodities most vulnerable to further import competition or with industries producing goods that are competitive with highly protected imports. Relatively higher wages have characterized exported manufactures for over half a century. The same tendency for average wages in the export group to exceed those of the import-competing group is found in the mining and agricultural sectors, but for agriculture the analysis of wages in relation to foreign trade is much more tentative. The reconciliation of foreign trade statistics with data on wages, employment, and production for the years I947 and I952 had been accomplished by the Bureau of Labor Statistics in connection with its input-output studies.2 Average hourly earnings, which are used as the measure of wages,3 are either calculated from Census data or taken from B.L.S. estimates. For agriculture, however, there was no source of hourly earnings data, and, as is explained in the section on agriculture, the author has employed a makeshift method based on data of the Bureau of Agricultural Economics.

Wages and Foreign Trade

J OOD prices in Moscow state stores in 1, 1larch I950 were approximately 2.25 to 2.5 times higher than those prevailing in January I936, according to various price indices coimputed below. These indices indicate that the March I950 food prices were, however, about 30 per cent lower than those established in connection with the currency reform and the abolition of rationing in December I947. The construction of consumers' price indices for the Sovi.et Union is subject to a large margin of error because of (i) the paucity of price and consumers' expenditure data and (2) the country's multiple price system. Each of these complications is discussed briefly. The available price data are then tabulated, and, finally, the methods and results of the index number computations are presented.

Irving B. Kravis

Papers

International Differences in the Distribution of Income

Wages and Foreign Trade

Food Prices in the Soviet Union, 1936-50