Abstract
The model describes the demand and supply of low-skill labor (private household workers, other service workers, and nonfarm laborers) by state. The parameters of the model are estimated primarily with data aggregated from the March 1970 Current Population Survey for 43 states and groups of states by a simultaneous-equations method. The estimates indicate that demand is slightly inelastic, while both primary (heads of families) and secondary (other family workers) supplies are backward bending, with the large states being on the negatively sloped range. For all but the smallest states, the explanatory power of the model as a whole in 1969 is good. The incidence of poverty in the United States has proved remarkably resistent to a variety of social programs designed to narrow income disparities among families. It is partly for this reason that there is widespread interest in new approaches to closing the poverty gap. The negative income tax, family allowances, wage subsidies, and training subsidies are among the most widely discussed of these approaches. Central issues in nearly all discussions are the effect Dr. Crandall is in the Department of Economics, Massachusetts Institute of Technology; Dr. MacRae is on the Senior Research Staff of the Urban Institute; and Dr. Yap is in the Department of Economics of the State University of New York at Binghamton. * This research was supported by funds from the Office of the Assistant Secretary for Policy, Evaluation, and Research, U.S. Department of Labor, and the Social and Rehabilitation Service, U.S. Department of Health, Education, and Welfare. Opinions expressed are those of the authors and do not necessarily represent the views of the Urban Institute, U.S. Department of Labor, or U.S. Department of Health, Education, and Welfare. We wish to thank Christine deFontenay and Christopher Gibbons for proficuous programming assistance and Judith Greenwald and Valerie James for valuable research assistance. We are grateful to Herrington Bryce, Alan Fechter, Charles Holt, and Terence Kelly for helpful comments. [Manuscript received October 1973; accepted June 1974.] The Journal of Human Resources * X * 1 This content downloaded from 207.46.13.120 on Wed, 14 Sep 2016 05:49:23 UTC All use subject to http://about.jstor.org/terms 4 I THE JOURNAL OF HUMAN RESOURCES of such proposals upon the incentive to work and the distribution of the benefits and costs of these programs between the subsidized and unsubsidized. Many of the uncertainties surrounding new proposals for social programs may be traced to lack of information on very basic parameters of low-skill labor markets. The poor are poor in part because they have little human capital and are, therefore, relegated to lower skill jobs. In order to evaluate the aggregate work incentive effect of any direct income maintenance program information on the wage and income responses of the low-skill labor supply is needed. Similarly, if the choice of policy instrument is to be wage or training subsidies, knowledge of lowand intermediate-skill labor demand elasticities would be especially useful. Moreover, when the choice among competing strategies to raise incomes of the poor must be made, a consistent framework in which to evaluate demand-oriented and supply-oriented programs is crucial. Much of our empirical knowledge about labor market parameters has been derived from separate studies of either demand or supply, but few studies have attempted to estimate a market model of demand and supply utilizing simultaneous-equation techniques.1 This is particularly true of the market for lowskill labor, the market most relevant for an evaluation of policies dealing with poverty. Clearly, a complete, detailed model of the operation of labor markets in these skill categories is needed if sound judgments on the wage and employment effects of alternative policy strategies are to be reached. The purpose of this paper is to develop an econometric model of the low-skill labor market. We begin by reviewing the labor demand and supply theory which is used in formulating the model. The data and method of estimation employed in the model are described. Then we present the parameter estimates and compare the values predicted by the entire model with the actual values used to estimate the model.
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