Economics at your fingertips  

Quantile regression with interval data

Arie Beresteanu and Yuya Sasaki

Econometric Reviews, 2021, vol. 40, issue 6, 562-583

Abstract: This paper investigates the identification of quantiles and quantile regression parameters when observations are set valued. We define the identification set of quantiles of random sets in a way that extends the definition of quantiles for regular random variables. We then give sharp characterization of this set by extending concepts from random set theory. Applying the identification set of quantiles and its sharpness to parametric quantile regression models yields the identification set of the parameters and its sharpness. We apply our methods to data on localized environmental benefits and their impact on house values.

Date: 2021
References: Add references at CitEc
Citations: Track citations by RSS feed

Downloads: (external link) (text/html)
Access to full text is restricted to subscribers.

Related works:
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:

Ordering information: This journal article can be ordered from

DOI: 10.1080/07474938.2021.1889201

Access Statistics for this article

Econometric Reviews is currently edited by Dr. Essie Maasoumi

More articles in Econometric Reviews from Taylor & Francis Journals
Bibliographic data for series maintained by ().

Page updated 2022-01-13
Handle: RePEc:taf:emetrv:v:40:y:2021:i:6:p:562-583