Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/65917
Authors: 
Nicoletti, Cheti
Best, Nicky G.
Year of Publication: 
2011
Series/Report no.: 
ISER Working Paper Series 2011-12
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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