[Excerpt] This paper presents new evidence on the determinants of place-to-place migration in the United States. For understanding the causes of differential migration rates into and out of labor markets, knowledge of place-to-place migration functions is of interest for a number of reasons. Given a thorough understanding of gross place-to-place flows, one can proceed to calculate net flows; the reverse, of course, is not possible. There are also other advantages of place-to-place studies: parallelism to microeconomic behavior, opportunity to investigate specific 'origin-destination match-ups, recognition of the number and location of alternative opportunities for persons residing in different origins, and exploration of possible asymmetries. Following a large body of economic literature, the analytical approach adopted regards migration as a form of human investment. Economic variables used in the empirical-work exhibit effects in the hypothesized direction and explain up to two-thirds of the variance in intermetropolitan migration rates. However, this high degree of explanatory power is achieved only for certain functional specifications involving particular independent variables. Thus, the empirical results confirm the usefulness of the human investment approach to place-to-place migration, but they show too that the economic factors used as explanatory variables must be carefully specified and measured.

Work supported by the RANN Division of the National Science Foundation under Grant #GSF SIA 75-00379.

l'Evolution de Coefficients Input-Output, Economic Applique 16 (1) (1963). Parikh, Ashok, and R. Edwards, Estimation of Gross Domestic Output and Employment by Sectors through Input-Output SSRC Report, unpublished, 1975. Theil, Henri, Applied Economic Forecasting (Amsterdam: North-Holland Publishing Company, 1966). Theil, Henri, and C. B. Tilanus, Demand for Production Factors and the Price Sensitivity of Input-Output Predictions, International Economic Review 5 (1964), 258-272. Tilanus, C. B., Input-Output Experiments, The Netherlands, 1918-61 (Rotterdam: Rotterdam University Press, 1966). United Nations, Input-Output Tables and Analysis, Studies in Methods, series F, no. 14, rev. o (New York: United Nations, 1973).

A recent paper in this REVIEW (LongRasmussen-Haworth, 1977) challenges the view that urban size is a source of income equality. L-R-H develop an econometric model that explains variation in the Gini coefficient of male incomes and family incomes. They conclude that urban size creates a more unequal distribution of urban income (as indicated by a significant negative sign on the SMSA population variable). This paper makes several contributions to our knowledge of urban income distribution. First, unlike previous papers, it develops a theoretical framework for separating the effects of urban size and level of development. Second, it provides a theoretical basis, as well as empirical justification, for the hypothesis that level of development (as measured by urban income level) bears a non-linear relationship to urban income inequality, becoming negative at high levels of income. Third, all authors except L-R-H anticipate to decline while moving up the urban hierarchy (size distribution of cities). This paper makes the point that the urban hierarchyequality hypothesis is partly supported but that the conclusion hinges on the choice of measure. Fourth, virtually all previous research on urban income distribution uses the Gini coefficient as the measure of income inequality. This paper uses three measures to test the sensitivity of conclusions to the choice of measure: the Gini coefficient, the incidence of poverty, and the percentile index. Despite the widespread belief by most economists that efficiency and equity do not go hand-in-hand, the urban size-equality view suggests there is no trade-off between the two. Richardson, for example (1973, p. 53), argues that inequality decreases as we move up the urban hierarchy.1 Most of the empirical work on state, county, and urban income distribution supports this view (Mattila and Thompson, 1968; Hoch, 1972; Farbman, 1974; Aigner and Heins, 1967; AlSumarrie and Miller, 1967; Conlisk, 1967; Murray, 1969; Frech and Burns, 1971; Burns, 1975; Danziger, 1975). Income inequality, as measured by the Gini coefficient, consistently declines with income level of the state, metropolitan area, or county. The incidence of poverty also appears to decline with urban income level (Omrati, 1968; Richardson, 1973). However, only three studies include both population and income level in their testing (Burns, 1975; Danziger, 1975; and Long-Rasmussen-Haworth, 1977), and only the L-R-H research finds both population and income to be significant variables. Both the theoretical argument and the empirical evidence presented in this paper point to the existence of an efficiency-equity trade-off. Previous research on urban income distribution seems to miss the trade-off because the various issues involved have not been clearly separated. Thus, several basic questions surrounding urban income distribution are investigated in this paper: 1. Does urban size, as measured by SMSA population, have a separate effect from level of development? A theoretical basis for a separate inequality-creating effect of urban size is an expected productivity-agglomeration effect which increases the productivity of skilled labor more rapidly than the productivity of unskilled labor. 2. Can we expect level of development, as measured by urban income level, to have a consistent equalizing effect on urban income distribution? A theoretical argument based on an expected amenity-compensation effect leads us

It is generally believed that market power is an important determinant of profits. Although market power is not observable directly, theories of and industry behavior suggest that it may be correlated with easily measurable variables like size, market share and/or industry concentration, and recent growth. If true, these several associations imply a correlation between observable variables, S, which measure size, market share, and recent growth, and (observable) variables, H, which index profitability. These correlations have been demonstrated in empirical literature and have been adduced as evidence of an underlying (casual) correlation between market power (M) and profitability. In fact, it has been claimed that the predicted profitability of each firm, based on models of type under consideration, provides a single integrated estimator of market power held by firm (Shepherd, 1972, p. 35). Such interpretations of S::fl correlations, however, have been questioned seriously on a number of grounds. On one hand, it has been argued that large size, market share and industry concentration should be attributed primarily to efficiency and superior competitive performance rather than to collusion.' The second major line of attack, on other hand, suggests that S::f1 correlations could result from stochastic processes which, of course, do not imply a correlation between market power, or efficiency, and profitability (Mancke, 1974). Our principal concern in present paper is with possible stochastic determinants of profitability. We argue essentially that while ex ante investment opportunities can be randomly distributed, realized rates of return may not generally be specified as fully determined by stochastic processes (cf. Caves, Gale, and Porter, 1977, pp. 668-669). The implications of this argument are explored in a simulation study based on a rudimentary, but representative, model of and industry behavior. The evidence drawn from this experiment does not support view that empirical relationships between profitability and market structure are likely to be result of random processes. The paper is divided into two parts. The principal section develops a simulation model of behavior that incorporates reasonable market features, and examines effects of randomly distributed ex ante investment opportunities in such a setting. A final section contains concluding remarks and suggestions for further research.

McCallum, Bennett T., The Role of Speculation in the Canadian Forward Exchange Market: Some Estimates Assuming Rational Expectations, this REVIEW 59 (May 1977) 145-151. Officer, Lawrence H., and Thomas D. Willet, The Covered Arbitrage Schedule: A Critical Study of Recent Developments, Journal of Money, Credit and Banking 2 (May 1970) 247-257. Stoll, Hans B., An Empirical Study of the Forward Exchange Market under Fixed and Flexible Exchange Rate Systems, Canadian Journal of Economics 1 (Feb. 1968), 55-78.