Principal components analysis may reduce multicollinearity problems common to recreation demand equations. In this analysis, principal components is used to construct indices accounting for the effects of site quality and socioeconomic variables on outdoor recreation demand. These indices provide theoretically consistent and statistically significant demand shift regressors for estimated demand functions.