Which Quantile is the Most Informative? Maximum Likelihood, Maximum Entropy and Quantile Regression

Anil K. Bera, Antonio Galvao, Gabriel Montes-Rojas () and Sung Y. Park

Chapter 7 in Econometric Methods and Their Applications in Finance, Macro and Related Fields, 2014, pp 167-199 from World Scientific Publishing Co. Pte. Ltd.

Abstract: The following sections are included:IntroductionMaximum Likelihood and Maximum EntropyA Z-estimator for Quantile RegressionMonte Carlo SimulationsEmpirical Illustration: The Effect of Job Training on WagesConclusionsAppendixReferences

Keywords: Financial Econometrics; Applied Econometrics; Econometric Theory and Methods (search for similar items in EconPapers)
Date: 2014
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.worldscientific.com/doi/pdf/10.1142/9789814513470_0007 (application/pdf)
https://www.worldscientific.com/doi/abs/10.1142/9789814513470_0007 (text/html)
Ebook Access is available upon purchase.

Related works:
Working Paper: Which quantile is the most informative? Maximum likelihood, maximum entropy and quantile regression (2010)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wsi:wschap:9789814513470_0007

Ordering information: This item can be ordered from

Access Statistics for this chapter

More chapters in World Scientific Book Chapters from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().