The Effect of Common Sources of Regression Error on Benefit Estimates

Abstract

Discussions of the sources of error in recreation demand analysis are common in the existing literature. The most traditional line of thought (e.g., Gum and Martin) considers the error component in predicting the individual's recreation behavior to arise from unmeasured socioeconomic factors. Others (e.g., Hanemann) attribute at least some of this error to fundamental randomness in human behavior. Applied statisticians (e.g., Hiett and Worrall) on the other hand, suggest that recall of annual number of recreational trips (i.e., the quantity demanded) is subject to substantial error. Still others (e.g., Brown, et al.) have argued that recall of explanatory variables, such as travel expenses, contains error. Despite the discussion of potential error sources, there is no work which relates the sources of error in the demand relationship with benefit measurement.1 Of practical importance in recreational demand estimation is whether error assumptions have an influence on welfare measures, since it is for public policy decision purposes that recreational demand estimation is usually undertaken. Will the estimated consumer surplus derived from demand analysis be independent of the assumed source of the error in the regression? The purpose of this paper is to explore how the assumptions about sources of error influence estimates of recreation benefits. A discussion of the various sources of error in de-