Wage Functions and Occupational Selection in a Rural Less Developed Country Setting
利用危地马拉五个村庄1974年的数据，估计了农村劳动力在农业和非农工作之间的工资函数与职业选择，揭示了个人特征对工资和行业选择的影响。
ECONOMISTS are just beginning to develop empirical knowledge about the basic relationships that determine the distribution of incomes and allocation of resources in the poor rural regions of the world. Understanding interactions between agriculture and the rest of the economy is particularly important in this context. This paper empirically investigates the allocation of human resources between farm work and other jobs and the compensation received by individuals for their work in agriculture and elsewhere. Specifically, two related tasks are undertaken in this paper: (1) the estimation of wage functions; and (2) the estimation of functions determining the allocation of time among occupations. There have been a series of papers which estimate the earnings function using data from poor countries. (For examples, see Blaug (1974); Chiswick (1977); and Valdes (1971).) However, this study focuses not on total earnings but on the wage rates a person may earn in labor market work, because the wage rate is the relevant price of time for many allocative decisions. For example, in dividing the work year between self-employed farming and work as an employee off the farm, a key price is the potential wage rate the person can earn in the labor market. (For discussion and evidence on this issue, see Sumner (1978).) Recently, a few studies have appeared which illustrate the importance of understanding potential wage variations across individuals in less developed countries. Rosenzweig (1978) uses wage estimates from aggregate Indian data in a model determining the impact of land reform. Bardhan (1979) develops wage functions from a sample survey in rural India as a step in estimating labor supply for rural households. Kusnic and DaVanzo (1980) use wage functions to impute potential incomes and to measure the full income distribution. These previous studies illustrate the importance of understanding the determinants of market wages. The present paper develops wage functions in more detail, focusing especially on industrial differentials. In many rural areas employment opportunities may be usefully categorized into (1) self-employment (mainly on small farms); (2) work for wages on large farms; and (3) work for wages in non-farm industries. The combination of selfemployment and work as an employee is also important in many rural areas in both rich and poor countries. This paper examines the impact of personal characteristics on the choice to participate in work for wages and on the choice of industry. These estimates also form a basis for studying industrial wage differentials. Tentative estimates of the dependence of participation on expected wages are also presented below. The empirical analysis in this paper is based on a 1974 sample of five villages in central Guatemala (see Corona (1978) and Stein (1978)). One village, Petapa, is larger, richer and more urban than the others. It lies south of Guatemala City within commuting distance of the capital. The other villages are outside the capital city region. The population sampled is almost exclusively ladino (Spanish culture as opposed to Indian). Data are available on the earnings, hours of work, industry, age, schooling, literacy, and village of 1,005 male heads of households. Approximately one-third of the sample work as both self-employed farmers and hired workers, and most of these men work on fincas (large plantations). Another quarter of the sample work as self-employed farmers and do no work for wages. The suburban village has mostly nonagricultural workers, whereas the four other villages have predominantly farmers and farm employees. In Received for publication June 21, 1979. Revision accepted for publication December 31, 1980. * North Carolina State University. Research on this paper began while I was a Rockefeller Foundation supported Post-Doctoral Fellow in the Labor and Population Group of the Economics Department of the Rand Corporation and continued at North Carolina State University supported by the Agricultural Research Service. At Rand, Robert Newman served as my research assistant and at N.C. State, James Cochell provided able assistance. I have benefited from the comments of colleagues at both institutions and from members of the Labor Economics Workshop at The University of North Carolina at Chapel Hill. I also thank two anonymous referees for useful suggestions. This is paper number 6558 of the Journal Series of the North Carolina Agricultural Research Service, Raleigh, N.C.