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.

MoreLess

Year of publication:	2011-05-13
Authors:	Nicoletti, Cheti ; Best, Nicky G.
Institutions:	ESRC Research Centre on Micro-Social Change, Institute for Social and Economic Research (ISER)

More details

Extent:	application/pdf
Series:	ISER Working Paper Series.
Type of publication:	Book / Working Paper
Notes:	published Number 2011-12
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10009018025