Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/65917 
Year of Publication: 
2011
Series/Report no.: 
ISER Working Paper Series No. 2011-12
Publisher: 
University of Essex, Institute for Social and Economic Research (ISER), Colchester
Abstract: 
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.
Subjects: 
quantile regression
ecological inference
aggregation bias
JEL: 
C18
C21
Document Type: 
Working Paper

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