Auctions and Estimates: Evidence from Indian Art Market

Shailendra Gurjar, Usha Ananthakumar

2022

Abstract

We examine whether presale estimates of paintings by Indian artists are unbiased predictors of the hammer price. Our analysis includes both sold and unsold artworks. Unbiasedness of estimates is tested by performing a two-stage Heckit model on 5,077 artworks auctioned between 2000 and 2018. The results of our study show that presale estimates are upward biased for expensive artworks and downward biased for others. In addition, we also find that in the market for Indian paintings, characteristics of auction, artist, and artwork determine the biasedness of estimates.

Paper Citation

in Harvard Style

Gurjar S. and Ananthakumar U. (2022). Auctions and Estimates: Evidence from Indian Art Market. In Proceedings of the 11th International Conference on Data Science, Technology and Applications - Volume 1: DATA, ISBN 978-989-758-583-8, pages 504-511. DOI: 10.5220/0011317200003269

in Bibtex Style

@conference{data22,
author={Shailendra Gurjar and Usha Ananthakumar},
title={Auctions and Estimates: Evidence from Indian Art Market},
booktitle={Proceedings of the 11th International Conference on Data Science, Technology and Applications - Volume 1: DATA,},
year={2022},
pages={504-511},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011317200003269},
isbn={978-989-758-583-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Conference on Data Science, Technology and Applications - Volume 1: DATA,
TI - Auctions and Estimates: Evidence from Indian Art Market
SN - 978-989-758-583-8
AU - Gurjar S.
AU - Ananthakumar U.
PY - 2022
SP - 504
EP - 511
DO - 10.5220/0011317200003269