Can Subjective Measures for Rapid Assessment of Rural Poverty and Inequality be Useful in Botswana?
AbstractAlthough middle income countries such as Botswana are credited with reliable data that are used in poverty measures, it is sometimes argued that the time lags between data generations or surveys are too wide. The Household Income and Expenditure Survey (HIES) in Botswana takes place every 10 years. The major constraints are capacity and budget considerations. In this article, we propose two subjective measures that have been successfully used elsewhere for adaptation in Botswana. We use data from Nshakazhogwe village case study to test whether these alternative measures of poverty and deprivation are correlated with objective measures of economic deprivation. The Pearson Chi-square tests of independence are applied to examine the independence and the results show that the null-hypothesis that subjective and objective measures of deprivation are independent should be rejected. These results are statistically significant and imply the relationship between the proposed subjective measures and objective variables are systematic in rural Botswana. Even though subjective measures seem to be fairly imprecise indicators of poverty and social disadvantage, the fact that they are statistically significant discriminators is encouraging. If changes in the incidence of poverty using the subjective measures are positively associated with changes based on objective measures, the results could indicate trends in poverty incidence and trigger timely relevant policy responses to address emerging poverty concerns. Finally, the problem of relying only on data generated between long-time intervals from normal in depth statistical surveys that are skill intensive and high cost would be reduced.
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Bibliographic InfoPaper provided by University of Queensland, School of Economics in its series Social Economics, Policy and Development Working Papers with number 123547.
Date of creation: Jun 2008
Date of revision:
Botswana; Rural Poverty; Chi square test; Heads of Household; Community/Rural/Urban Development; Food Security and Poverty; Research Methods/ Statistical Methods;
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