Robust Instrumental Variables and Accelerated Life Regressions

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Creator: 

Acharya, Anand

Date: 

2016

Abstract: 

This thesis considers the econometric problem of endogeneity in an accelerated life regression model. The proposed instrumental variables inference, based on inverting a pivotal statistic, is exact regardless of instrument quality. A (i) least squares statistic and (ii) distribution-free linear rank statistic allowing censoring are provided. A simulation confirms that the quality of exogenous variation determines an instrument’s informative content. We provide an empirical illustration with an original prospectively collected ob- servational data set, in which, the trauma status of a pediatric critical care patient instruments a possibly confounded illness severity index in a length of stay regression for a specific pediatric intensive care population. Results suggest a clinically relevant bias correction for routinely collected patient risk indices that is meaningful for informing policy in the health care setting.

Subject: 

Economics

Language: 

English

Publisher: 

Carleton University

Thesis Degree Name: 

Doctor of Philosophy: 
Ph.D.

Thesis Degree Level: 

Doctoral

Thesis Degree Discipline: 

Economics

Parent Collection: 

Theses and Dissertations

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