Centre for Research in Economic Development and International Trade

CREDIT 18/01: Assessing cohort aggregation to minimise bias in pseudo-panels


Pseudo-panels allow estimation of panel models when only repeated cross-sections are available. This involves grouping individuals into cohorts and using the cohort means as if they are observations in a genuine panel. Their practical use is constrained by a lack of consensus on how the pseudo-panels should be formed, particularly to address potential sampling error bias. We show that grouping can also create substantial aggregation bias, calling into question how well pseudo-panels can mimic panel estimates. We create two metrics for assessing the grouping process, one for each potential source of bias. If both metrics are above certain recommended values, the biases from aggregation and sampling error are minimised, meaning results can be interpreted as if they were from genuine panels.

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Rumman Khan


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Posted on Thursday 11th January 2018

Centre for Research in Economic Development and International Trade

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