Quantile regression with aggregated data - Cheti Nicoletti; Nicky G. Best (University of Essex, Institute for Social and Economic Research (ISER), 2011)
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. 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.
Keywords: C18; C21; 330; quantile regression; ecological inference; aggregation bias