Three Essays on Extremal Quantiles

dc.contributor.advisor

Khan, Shakeeb

dc.contributor.advisor

Maurel, Arnaud

dc.contributor.author

Zhang, Yichong

dc.date.accessioned

2016-06-06T14:36:53Z

dc.date.available

2016-06-06T14:36:53Z

dc.date.issued

2016

dc.department

Economics

dc.description.abstract

Extremal quantile index is a concept that the quantile index will drift to zero (or one)

as the sample size increases. The three chapters of my dissertation consists of three

applications of this concept in three distinct econometric problems. In Chapter 2, I

use the concept of extremal quantile index to derive new asymptotic properties and

inference method for quantile treatment effect estimators when the quantile index

of interest is close to zero. In Chapter 3, I rely on the concept of extremal quantile

index to achieve identification at infinity of the sample selection models and propose

a new inference method. Last, in Chapter 4, I use the concept of extremal quantile

index to define an asymptotic trimming scheme which can be used to control the

convergence rate of the estimator of the intercept of binary response models.

dc.identifier.uri

https://hdl.handle.net/10161/12160

dc.subject

Economics

dc.subject

Extremal

dc.subject

Quantiles

dc.subject

Treatment

dc.title

Three Essays on Extremal Quantiles

dc.type

Dissertation

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