A Multilevel Model with Time Series Components for the Analysis of Tribal Art Prices

In the present work, we extend the classic multilevel model to include time series components at the second level. In order to show its potentials, we perform an econometric analysis of the Tribal art market. In literature, art prices are modelled through the hedonic regression model, a classic fixed-effect model. We use, instead, a multilevel model for the analysis of Tribal art prices that takes into account the influence of time on artwork prices. Since we do not have repeated measurements of the same items over time, we propose to treat the data as two-level structured in that items are grouped in time points. Hence, the proposed model copes with the time dependence of random effects.