A Mixed Index Approach to Identifying Hedonic Price Models

Recent literature suggests identifying house price hedonic models by using instrumental variables, spatial statistics, the borders approach, panel data, and other techniques. We introduce a mixed index model to identify house price hedonic regressions. We compare the performance of the mixed index model to a traditional hedonic model and to a hedonic model that includes characteristics of the buyer of each house. We find the mixed index model outperforms the other models based on bootstrap distributions of predicted housing values, prediction variance, and predicted policy effects. The mixed index model distributions are less skewed and kurtotic than the other models, suggesting that the mixed index model more closely satisfies the classical linear regression assumption of normally distributed errors. Compared to the mixed index model, the traditional hedonic overstates the importance of school quality to house price and understates the importance of environmental quality to house price