Aggregate art price patterns mask a lot of underlying variation--both in the time series and in the cross- section. We argue that, to increase our understanding of the market for aesthetics, it is helpful to take a micro perspective on the formation of art prices, and acknowledge that each...

A new heteroskedastic hedonic regression model is suggested which takes into account time-varying volatility and is applied to a blue chips art market. A nonparametric local likelihood estimator is proposed, and this is more precise than the often used dummy variables method. The empirical...

Art often serves as an investment tool. However, the prices for some of the pieces are not easy to predict, and removing the price uncertainty is crucial to attracting even more investment in the art market. This paper assumes that the reputation of the artists and their social connections can...