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- W2110202953 abstract "The paper investigates the role of multi-level structures in poverty analysis based on household level data. We demonstrate how multi-level models can be applied to standard poverty analysis and highlight its usefulness in terms of assessing the extent community characteristics matter in determining poverty status and dynamics. We provide two applications. The first is an example of a growth model that control for characteristics measured at the initial time period, and considers directly to what extent the same characteristics contribute to explain changes in economic wellbeing over time. In the second application we model the determinants of escaping poverty. Both applications use longitudinal data from Vietnam recorded at two points in time during the nineties, a period where Vietnam experienced strong economic growth. We demonstrate that failing to control for multi-level data structures could give incorrect inference about the effect of covariates of interest. We also demonstrate how the multi-level models can be used for regional and community level policy analysis that otherwise is difficult to implement in more standard regression analysis. NON-TECHNICAL SUMMARY The paper provides an illustration of how multilevel models can be used to correctly handle hierarchical data structures applied to household wellbeing and poverty dynamics. From the models we also demonstrate how to provide recommendations for policy interventions. We present two examples: A growth model with a continuous dependent variable – the log equivalent household expenditure, and a probit model for studying the determinants of poverty exit. In both cases we find that the multilevel structure is highly relevant as attested by the intra-class correlation coefficients. Hence, failing to control for the multilevel structure will influence model predictions in significant ways, leading to possibly incorrect inference about the effect of the covariates. Whereas an alternative approach would be to simply use robust standard errors, this would omit essential information about the multilevel structure relevant for policy analysis. Multilevel models instead give us insight that is otherwise unfeasible in the more standard methods. The growth model separates the initial economic status from the growth effect of the covariates. The estimates related to the initial condition demonstrate that Kinh ethnic origin, education, and living in a community with health facilities, are all associated with higher wealth. In contrast, households with a high percentage of unemployed members and those working in agricultural activities were disadvantaged. Also household size and the number of children are negatively associated with consumption expenditure. These effects are of course, sensitive to the equivalence scale; we adopt here the well used WHO scale which is in line with many previous studies. The growth dimension of the model attests that, on average, household consumption growth rate between the two waves was 17%, a reflection of the economic boom experienced in Vietnam during the nineties. However, the growth trend varied substantially by households and community characteristics. We find that those who were better off initially were not necessarily the same benefiting during the economic boom. For example, households with many children benefited from the economic growth whereas farm households benefited less." @default.
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- W2110202953 date "2007-01-01" @default.
- W2110202953 modified "2023-09-24" @default.
- W2110202953 title "Dynamic multi-level analysis of households' living standards and poverty: Evidence from Vietnam" @default.
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