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Quantile Regression

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eBook not available for this title

Authors:	Lingxin Hao and Daniel Q. Naiman
Publisher:	Sage
Copyright:	2007
ISBN-13:	978-1-4129-2628-7
Pages:	126; paperback

Authors:	Lingxin Hao and Daniel Q. Naiman
Publisher:	Sage
Copyright:	2007
ISBN-13:
Pages:	126; eBook
Price:	$0.00

Authors:	Lingxin Hao and Daniel Q. Naiman
Publisher:	Sage
Copyright:	2007
ISBN-13:
Pages:	126; Kindle
Price:	$

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Comment from the Stata technical group

Quantile Regression, by Lingxin Hao and Daniel Q. Naiman, provides an excellent introduction to quantile-regression methods. The intuitive explanations and many examples make this book easy to read and understand. An appendix provides Stata commands to replicate the examples using the datasets available at http://www.ams.jhu.edu/~hao/QRbook_data_codes/.

After showing the advantages that quantile regression has over least squares, the authors discuss the estimation technique, the statistical inference, and how to interpret the results. The example-based approach is exceptionally clear and avoids swamping the reader in technical details.

The final section of the monograph applies the techniques to changes in U.S. income equality between 1991 and 2001. This application illustrates both how to use the methods and how to interpret the results.

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