Abstract
A growing literature uses repeated cross-section surveys to derive ‘synthetic panel’ data estimates of poverty dynamics statistics. It builds on the pioneering study by Dang, Lanjouw, Luoto, and McKenzie (Journal of Development Economics, 2014) providing bounds estimates and the innovative refinement proposed by Dang and Lanjouw (World Bank Policy Research Working Paper 6504, 2013) providing point estimates of the statistics of interest. We provide new evidence about the accuracy of synthetic panel estimates relative to benchmarks based on estimates derived from genuine household panel data, employing high quality data from Australia and Britain, while also examining the sensitivity of results to a number of analytical choices. Overall, we are more agnostic about the validity of the synthetic panel approach applied to these two rich countries than are earlier validity studies in their applications focusing on middle- and low-income countries.
Highlights
There is a growing literature that employs repeated cross-section surveys to derive ‘synthetic panel’ data estimates of poverty dynamics statistics building on the pioneering study by Dang et al (2014, hereafter ‘DLLM’) providing bounds estimates and the innovative refinement proposed by Dang and Lanjouw (2013, hereafter ‘DL’) providing point estimates of the statistics of interest
Because the British Household Panel Survey (BHPS) and HILDA are much longer-running household panels than those for any developing country – we use data collected annually over 18 years for the BHPS, and over 15 years for HILDA – we can provide a detailed assessment of the extent to which the accuracy of synthetic panel estimates of poverty dynamics statistics vary according to the year or period studied
We show for Australia and Britain that DL-method point estimates of poverty dynamics statistics are distinctly less accurate than estimates derived in earlier validity studies, all of which focus on low- and middle-income countries
Summary
There is a growing literature that employs repeated cross-section surveys to derive ‘synthetic panel’ data estimates of poverty dynamics statistics building on the pioneering study by Dang et al (2014, hereafter ‘DLLM’) providing bounds estimates and the innovative refinement proposed by Dang and Lanjouw (2013, hereafter ‘DL’) providing point estimates of the statistics of interest. Because the BHPS and HILDA are much longer-running household panels than those for any developing country – we use data collected annually over 18 years for the BHPS, and over 15 years for HILDA – we can provide a detailed assessment of the extent to which the accuracy of synthetic panel estimates of poverty dynamics statistics vary according to the year or period studied Estimates of the cohort regressions used to derive DL rho (see Section 2) are available from the authors on request
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