On Hedonic Valuation of Urban Amenities Using Unbalanced Data
研究发现，在享乐估价中分别对住房和劳动力市场进行回归会导致协方差矩阵估计不一致和推断错误，并提出了两种易于实施且一致的估计方法，应用于巴西城市气温升高的估价。
Hedonic valuation of urban amenities often requires estimating housing and labor market regressions. It is difficult to get both types of data for all survey respondents. We show that the common practice of conducting two separate regressions with unbalanced data causes inconsistent covariance matrix estimation and improper inference regarding amenity values. We demonstrate how two easily implementable yet consistent techniques can be used for hedonic valuation with an application in valuing temperature increases in urban Brazil. <i></i>