Flexible Censored Interval Regression with Experimental Applications

Authors

Daniel Walton, Brigham Young University
James McDonald, Brigham Young University

Keywords

censored interval regression, experimental applications, censored data

College

Family, Home, and Social Sciences

Department

Economics

Abstract

Interval censored data, or grouped data, appears in well-established measurement techniques employed in many economic situations, including experimental economics. Estimation of parameters of models using these data de- pends critically on the model specification and method of estimation. Some methods can yield inconsistent and biased estimators when the distributional assumption of the model is misspecified. Our approach using partially adaptive estimation methods with flexible probability distributions mitigates such issues, including in the presence of heteroskedasticity (nonconstant variance in the explanatory variables) and skewness. In addition, we show that partially adaptive estimation applied in such settings increase the accuracy of estimates significantly, thus making inference stronger.

Recommended Citation

Walton, Daniel and McDonald, James (2016) "Flexible Censored Interval Regression with Experimental Applications," Journal of Undergraduate Research: Vol. 2016: Iss. 1, Article 28.
Available at: https://scholarsarchive.byu.edu/jur/vol2016/iss1/28