Puzzling Art Market Relationships: Quantifying Provenance to Model Historic Prices of Seventeenth- to Eighteenth-century French Art

Abstract

Previous studies of art price modeling relied on RSR, hedonic, or network modeling techniques to interpret a set of variables’ relationship to perceived art prices. There was an adversity in quantifying provenance record as it proved to be a laborious task riddled with limitations in the dataset. Existing research has not analyzed how aristocratic ownership, art dealers, and auction houses interacted within a given network of the art market. This thesis explores the relationship between provenance and historical seventeenth- and eighteenth-century French art prices in the British and French art market by using a hybrid approach integrating hedonic modeling with network analysis. Using data from the Getty Provenance Index, this study focuses on three provenance indicators: aristocratic ownership, art dealer involvement, and auction house involvement. The key findings supported the importance of auction houses in driving art prices and the heterogenous relationship present within the art market. This work contributes to the growing field of quantitative art market analysis to better understand how art is valued over time.