  In this paper we propose a multilevel model specification with time series
components for the analysis of prices of artworks sold at auctions. Since
auction data do not constitute a panel or a time series but are composed of
repeated cross-sections they require a specification with items at the first
level nested in time points. An original feature of our approach is the
derivation of full maximum likelihood estimators through the E-M algorithm. The
data analysed come from the first database of ethnic artworks sold in the most
important auctions worldwide. The results show that the new specification
improves considerably over existing proposals both in terms of fit and
prediction.
