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EU-SILC and the potential for synthetic panel estimates
[journal article]
Abstract In the absence of panel data, researchers have devised alternative methods for estimating synthetic poverty dynamics using repeated cross section surveys. These methods are not only salient in the absence of panel data, but also in contexts where there are concerns over the quality of panel data and... view more
In the absence of panel data, researchers have devised alternative methods for estimating synthetic poverty dynamics using repeated cross section surveys. These methods are not only salient in the absence of panel data, but also in contexts where there are concerns over the quality of panel data and/or the panel data are of insufficient length to analyse medium- to long-term mobility trends. Both of these issues afflict the longitudinal element of the European Survey on Income and Living Conditions (EU-SILC) (Hérault and Jenkins, J Econ Inequ 17(1):51–76, 2019). Using the longitudinal element of EU-SILC, this paper assesses the accuracy of the synthetic panel approach put forth by Dang and Lanjouw (2021). For most conventional poverty lines, the DL approach is found to be highly accurate when the true \(\rho \) is known. Similar to Hérault and Jenkins (J Econ Inequ 17(1):51-76, 2019) the pseudo-panel approach for estimating \(\rho \) is found to be highly sensitive to cohort definition. The longitudinal element of EU-SILC, however, offers a unique route for overcoming this shortcoming.... view less
Keywords
panel; poverty; estimation; cross-sectional study
Classification
Research Design
Methods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methods
Free Keywords
synthetic panel; pseudo-panel; poverty dynamics; EU-SILC
Document language
English
Publication Year
2023
Page/Pages
p. 1247-1280
Journal
Empirical Economics, 64 (2023) 3
DOI
https://doi.org/10.1007/s00181-022-02277-7
ISSN
1435-8921
Status
Published Version; peer reviewed