Stephen Jenkins: How valid are synthetic panel estimates of poverty dynamics? Evidence from two rich countries
OFS-seminar. Stephen Jenkins is a professor at The London School of Economics and Political Science. He will present the paper "How valid are synthetic panel estimates of poverty dynamics? Evidence from two rich countries", co-authored with Nicolas Hérault, University of Melbourne.
Foto: University of Essex
There is a growing literature that employs repeated cross-section surveys to derive "synthetic panel" data estimates of movements into and out of poverty building on the pioneering study by Dang, Lanjouw, Luoto, and McKenzie ("DLLM", Journal of Development Economics 2014) and the subsequent refinement proposed by Dang and Lanjouw ("DL", World Bank Policy Research Working Paper 6504, 2013). All but one of the applications to date, of which there are now many, have been to middle- and low-income countries.
An on-going issue is the validity of the estimates derived using these methods: how do they compare with estimates derived from genuine household panel data? See the recent validation studies by e.g. Fields and Viollaz (ECINEQ Conference, 2013) and Garcés Urzainqui (ECINEQ Conference, 2017) in addition to the validations undertaken by DLLM, DL, and Cruces et al. (JEI 2015).
Our paper provides new evidence about the validity of synthetic panel estimates, employing household panel data from the British Household Panel Survey and Australian HILDA survey to provide the benchmarks. With these high quality panel data, we can examine a number of aspects that have not received attention in earlier validation studies, e.g. because these panels are much longer-running than any developing country ones. In addition, there is intrinsic interest in extending to rich countries, where poverty dynamics processes are likely to differ from poorer countries. Note too that there are long-standing concerns about the extent of attrition in some datasets forming the longitudinal component of the EU-SILC - most EU Member States count as rich countries - and so our study may provide some guidance about the extent to which synthetic estimates of poverty transition rates might be derived from EU-SILC cross-sectional data instead.