Quantile regression with aggregated data
Analyses using aggregated data may bias inference. In this work we show how to avoid or at least reduce this bias when estimating quantile regressions using aggregated information.Â This is possible by considering the unconditional quantile regression recently introduced by Firpo et al (2009) and using a specific strategy to aggregate the data.
|Date of creation:||13 May 2011|
|Date of revision:|
|Contact details of provider:|| Postal: Publications Office, Institute for Social and Economic Research, University of Essex, Wivenhoe Park, Colchester, Essex CO4 3SQ UK|
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