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Estimating Farmworker Population Size in New York State Using a Minimum Labor Demand Method

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  Journal of Agricultural Safety and Health. 11(3): 335-345. (doi: 10.13031/2013.18576) @2005
Authors:   G. Earle-Richardson, P. L. Jenkins, S. Stack, J. A. Sorensen, A. Larson, J. J. May
Keywords:   Farmworker estimates, Geographic distribution, Migrant farmworkers, Seasonal farmworkers, Agricultural workers

Assessment of health needs and services for hand-harvest farmworkers requires reliable population estimates. In New York State, the only publicly available source for these is the Department of Labor (DOL). However, published production data exist that may enable estimation of minimum labor demand (MLD) for hand-harvest labor. Our objective was to develop an estimation process for minimum labor demand (MLD) for hand-harvested crops in NYS and contrast the results with DOL estimates. Four crop strata (below ground, ground, bush/vine, and orchard) were identified. MLD (measured in worker-seasons) was estimated by dividing the total annual harvest hours required for each crop stratum by the total hours worked by one worker in a season for that crop stratum. The MLD estimate of the total number of worker seasons combined for all strata (14,121) was higher than that of the DOL (8,230). Harvest acreage was unavailable for 21% of the 991 county-crop combinations studied; therefore, data were imputed from other sources. Within these strata, the greatest difference was found for ground crops, where the DOL count was 28% of the size of the MLD estimate. DOL and MLD estimates were closest in orchard crops (DOL 109% of MLD). Publicly available data provide a potentially valuable source of information for estimation of the MLD. Use of these methods implies that the DOL may substantially underestimate the size of this population. Differences seen between the two methods were sensitive to the crop type. County-level farm surveys to verify MLD estimation factors would enhance the methods accuracy.

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