Abstract
Vulnerability to poverty has been proposed in the literature as an ex ante measure of poverty risk useful for the identification of those who may fall into poverty in the future (Zhang and Guanghua 2008). This paper complements the existing literature on vulnerability measures, by investigating empirically how indexes precision varies according to the quantity of information available, in order to understand which is the best predictor of poverty conditional on data at hand. Using the British Household Panel Survey, we show that information quantity affects differently the predictive power of indexes.
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Notes
The values used in the empirical analysis for the additional parameters are the following: for CD rel \(\alpha = 0.5\), CD abs \(\beta = 0.5\), for DFM we use \(\alpha = 0.5\) and \(\gamma = 2\).
In his consumption generating function, Chaudhuri (2003) assumes that the elements of \(X_{h,t}\) are contemporaneously uncorrelated with \(e_{h,t}\) but allows for potential correlation between \(X_{h,t}\) and lagged consumption shocks. If this is the case, the standard within-estimator cannot be used, that is the reason why Chaudhuri (2003) uses first differences of consumption and instruments the changes in the predetermined variables using lagged changes and levels of the same variables. In this case, if income is used rather than consumption, the correlation between \(X_{h,t}\) and lagged shocks should not be an issue.
We recall that, differently from all the other vulnerability indexes, the cross-sectional approach (Chaudhuri 2003) exploits only the information available in 2004.
Results do not change whether we consider different information sets.
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Celidoni, M., Procidano, I. Identification Precision of Vulnerability to Poverty Indexes: Does Information Quantity Matter?. Soc Indic Res 121, 93–113 (2015). https://doi.org/10.1007/s11205-014-0630-x
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DOI: https://doi.org/10.1007/s11205-014-0630-x