Interval Response Data in Experimental Economics

• Activity Number: 419
• Type: Contributed
• Date/Time: Tuesday, August 11, 2015 : 2:00 PM to 3:50 PM
• Sponsor: Business and Economic Statistics Section
• Author(s): Daniel Walton* and James McDonald and Olga Stoddard
• Companies: Brigham Young University and Brigham Young University and Brigham Young University
• Keywords: experimental economics ; maximum likelihood ; generalized distributions ; heteroskedasticity ; interval data

Abstract

Many empirical applications in the experimental economics literature involve interval response data. Various methods have been considered to treat this type of data. One approach assumes that the data correspond to the interval midpoint and then utilize ordinary least squares to estimate the model. Another approach is to use maximum likelihood estimation assuming that the underlying variable of interest is normally distributed. In the case of distributional misspecification, or with heteroskedasticity, these estimates can yield inconsistent estimators. In this paper we apply a method which helps reduce the distributional misspecification problem by assuming a distribution which can accommodate a wide variety of distributional specifications. The methods are applied to the problem of estimating individual discount rates in a field experiment. The underlying data are seen to exhibit skewness which is inconsistent with the assumption of normality and impacts the parameter estimates.