Genus
Volume 47, Issue 1-2, 1991, Pages 49-62
A probability model for the distribution of the number of migrants at the household level. (Article)
Yadava K.N.* ,
Singh R.B.
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a
[Affiliation not available]
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b
[Affiliation not available]
Abstract
A probability model to characterize the pattern of total number of migrants from a household has been developed. Earlier models which had several limitations have been improved. The assumptions of the proposed model were migrants from a household occur in clusters and may rarely happen, and the risk of migration occurring in a cluster vary from household to household. Data from 3514 households from either semiurban, remote, or growth center villages in India were applied to the proposed probability model. The Rural Development and Population Growth--A Sample Survey 1978 defined household as a group of people who normally live together and eat from a shared kitchen. The people do not necessarily reside in the village, however, but work elsewhere and send remittances. They consider themselves to be part of the household. Observed and expected frequencies significantly agreed only for those in the high social status group (p.05). The mean number of clusters/household was greater for remote villages (.26) than growth center and semiurban villages (.22 and .13, respectively). On the other hand, the mean number of migrants/cluster was smaller for remote villages (2.1) than growth center and semiurban villages (2.17 and 2.62, respectively). These results may indicate that men migrate alone in different clusters from remote villages and men from growth center and semiurban villages migrate with their families in fewer number of clusters. Men from growth center and semiurban villages tended to be well educated and professionals. The mean number of migrants/household was higher for remote villages (.56) than growth center (.47) and semiurban (.33) villages. Commuting to work accounted for this difference.
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Link
https://www.scopus.com/inward/record.uri?eid=2-s2.0-0025717896&partnerID=40&md5=cf6b5f98987fedb55c13ea5d1a91ffcf
ISSN: 00166987
Original Language: English