Econometric Analysis of the Agricultural Labor Market

Tyrchniewicz, Edward W.; Schuh, G. Edward

doi:10.2307/1237773

Cited by 31 publications

(13 citation statements)

References 15 publications

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“…Particularly useful descriptions of the important changes are contained in Schertz (1975), Cochrane, Wilcox andHerdt (1973), Tweeten (1970), and Peterson and Hayami (1977). Analyses of the impact of these changes on farm labor are provided by Gisser (1967), Tyrchniewicz andSchuh (1969), andRosine andHeimberger (1976). The considerable degree of regional specialization of agricultural production by product, combined with the differential rates of decline in man-hours of work across agricultural products, produced significantly different rates of decline in farm employment among the regions of the country.…”

Section: Trends In Teenage Employmentmentioning

confidence: 99%

The Decline in Black Teenage Employment: 1950-1970

Cogan

1981

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This paper examines the causes of the decline in black male teenage employment from 1950 to 1970. During this period, the employment-to-population ratio of black youth (age 16-19) declined from 46.8 percent to 27 percent.The white teenage employment ratio, in contrast, remained constant. The primary source of the decline is traced to the virtual demise of the market for low-skilled agricultural labor. All of the black teenage employment decline during this period occurs in the South. The employment ratio among those living outside the South actually increases. Within the South, the entire decline in employment is accounted for by a reduction in agricultural employment.This study argues that technological progress is the principal cause of the agricultural employment decline among black youths. Spurred by the rapid advance and adoption of labor-saving technology, southern agricultural production was transformed from a relatively labor intensive process to a highly capital intensive one. As a result, the demand for low-skilled agricultural labor plummeted. By 1970, a formerly important source of black youth employment virtually ceased to exist.Black teenagers who were displaced from agricultural work were not absorbed by the nonagricultural sector. An additional finding of this paper is that the federal minimum wage acted as an isnportant barrier to nonagricultural employment in the South. The raw data reveal significant reductions in black teenage employment growth in precisely those industries where coverage of the minimum wage was increased: retail trade, construction, and the service sector.Regression estimates indicate a quantitatively large minimum wage effect.

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Section: Trends In Teenage Employmentmentioning

confidence: 99%

The Decline in Black Teenage Employment: 1950-1970

Cogan

1981

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“…Among the factors hypothesized to be important in addition to income differentials in off- [3,12,16,23,24,31], assets or capital [3,16,31], employment opportunities outside agriculture [6,17,24,30,31], education [3,6,16], price [13], and number of job holdings [21]. The age variable is a proxy for future expectations and motivation.…”

Section: Determinants Of Farm/non-farm Migrationmentioning

confidence: 99%

“…It has been hypothesized that the farm operator's transition is not only determined by the relative labor return from farm and non-farm work but also by the return to the other factors owned, such as land and capital [30]. In addition, the economic structure including distance to major trade centers is different for Census Divisions within the Prairie region.…”

Section: Determinants Of Farm/non-farm Migrationmentioning

confidence: 99%

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Migration Analysis and Farm Number Projection Models: A Synthesis

MacMillan

Tung

Tulloch

1974

American J Agri Economics

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Alternative farm number projection models are examined for the Canadian Prairie Provinces including a synthesis of Markov transition probabilities and migration functions. The procedure indicates a potential for overcoming deficiencies of standard farm projection models. Explanatory variables include: oH-farm work, age of operators, capital, and regional economic structure.A CRITICAL analytical requirement for adequate planning for low income problems of farm operators is a model which explains changes over time in farm operator numbers by receipts class. In Manitoba the government has outlined a "stay option" with the policy intent of decreasing the past reductions in farm operator numbers. Clawson expressed the opinion in 1963 that U. S. farm policy has been excessively preoccupied with agricultural supply and demand relations, price supports, surpluses, and related problems [1].Current criticisms of U. S. agricultural policy have made the same point in concluding that the needs of low income farm operators are not being met [20]. Policy planning and evaluation requires an improvement in methods of projecting farm target clientele by receipts class.Past trends illustrate dramatic decreases in farm numbers since the historic peak in the late thirties. The theoretical explanation derived from economic theory and structural analysis of the agricultural industry is straightforward. Given an income inelastic domestic demand, limited export demand for agricultural products, increasing economies of size in farm production, substitution of capital for labor in agriculture, and a high growth rate and high absolute level of wages in the non-farm sectors, decreasing numbers of farm operators are required over time to meet national agricultural production requirements.Farm number projection models have not included relationships which identify the structural significance of the factors outlined. Prior models *Assistance with calculations by G. Gislason is acknowledged, as well as helpful comments by C. F. Framingham, E. W. Tyrchniewicz, and two anonymous reviewers. JAMES A. MACMILLAN is professor and F. L. TUNG and JOHN R. TULLOCH are research assistants in agricultural economics at the University of Manitoba.292 used in projecting farm numbers can be grouped into four categories:1. Age-demographic [1]. 2. Markov chain projection assuming constant transition probabilities [4,10,11,14].3. Requirements based on assumed future average output per farm [2,15].4. Simultaneous analysis of the demand and supply of farm labor [30,32,33]. The age-demographic analysis is the simplest. Entrance and exit of farm operators are projected by age classes over a time period. Markov chain applications are based on the assumption that current values of economic variables depend on the preceding values of the same variables [18] .The requirements approach derives farm operator numbers from projected market-clearing output of agricultural products by means of the projected ratio of average output per farm. Simultaneous demand and supply analysi...

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The heterogcneous nature of the farm workforce has increasingly been recognized in econometric analyses of agricultural labour. Models have been developed for hired labour [ 6 ] , for family and non-family components of the farm workforce [4, 101, and for farm operators, unpaid family workers and hircd labour in simultaneous systems [9]. The models for the hired component have a well-established conceptual foundation, whereas models for the family components are generally specified by analogy with theories of hired labour demand and supply.

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confidence: 99%