헤도닉 분위 회귀 모형을 이용한 작품 가격 결정 요인 분석

Abstract

Purpose: Recently, the art market has been attracting several investors owing to growing interest toward alternative investment. In this study, to enhance our understanding of the art market, we test the pricing difference in artwork under various segments and further study the return on investment. Methods: The hedonic pricing approach investigates the relation between characteristics of artworks and their corresponding prices. Thus, our model, based on hedonic quantile regression, considers a complete characterization of the conditional distribution for the response variables. Results: We used segmented art market data collected between 2014 and 2018 from South Korea. The results of hedonic quantile regression show no evidence that more expensive artworks tend to generate higher returns. The artworks traded in the online art market follow a different pricing mechanism compared to those in the offline art market. The return on investment for arts in general shows a downward trend, and online auctions result in lower financial returns. Conclusion: We investigate the relation between art pricing factors and financial returns in the segmented art market using hedonic quantile regression empirically. We may consider the absence of masterpiece artworks, which generate the “masterpiece effect” in auctions, for further research.