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Investigating Difference: Applications of Wealth Ranking and Household Survey Approaches among Farming Households in Southern Zimbabwe
Author(s) -
Scoones Ian
Publication year - 1995
Publication title -
development and change
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.267
H-Index - 93
eISSN - 1467-7660
pISSN - 0012-155X
DOI - 10.1111/j.1467-7660.1995.tb00543.x
Subject(s) - ranking (information retrieval) , sample (material) , survey data collection , agriculture , asset (computer security) , livestock , survey sampling , geography , economics , agricultural economics , socioeconomics , business , statistics , sociology , population , mathematics , demography , computer science , chemistry , computer security , archaeology , chromatography , machine learning , forestry
Wealth ranking and household survey approaches to understanding wealth stratification are applied in tandem for a sample of farming households in southern Zimbabwe. While conventional surveys usually stratify sample populations according to criteria chosen by the researcher, wealth ranking is based on criteria offered by local people. Patterns of wealth and well‐being over time, between ecological zones and in relation to local indicators are explored with focus groups of men and women. The rankings emerging from these discussions are compared with survey data for the same household sample. The wealth rankings are highly correlated with livestock ownership, farm asset holdings, crop harvests and crop sales. Wealth ranks derived from farmers' analyses are then compared with a cluster analysis of the survey data, with both discrepancies and overlaps discussed. It is concluded that wealth ranking provides an accurate indicator of relative wealth and that ranking can be a useful complementary method to be employed alongside survey assessments. In addition, qualitative discussions during ranking exercises reveal details of the historically, socially and economically constructed understandings of wealth and well‐being of different actors. The conventional assumption that surveys always provide ‘better’ data is thus questioned.