Tale of Two Cities An Econometric Analysis of East & West Coast Fine Art Galleries
By Daniella Victoria Paretti
Abstract
In a 2021 report published alongside Art Basel and UBS, renowned cultural economist Dr.
Clare McAndrew posited that the value of art sales in 2020 amounted to an impressive $50 billion
(although this actually marks an over 10-year low). It is no secret that the global art markets are
extremely lucrative, attracting the interest of industry magnates and business tycoons alike.
Though it is important to note that art markets are historically quite distinct from their normal good
counterparts — the sector is laden with issues regarding transparency, high barriers to entry, and
hiding of wealth. Amidst the COVID-19 pandemic, however, the tides began to turn; online
platforms for museums, auction houses, and galleries were employed more than ever before,
effectively modernizing the antiquated industry and expanding its reach to new consumers. How
has this trend of digitalization changed and improved art markets? More specifically, how can data
analytics and other technological resources serve the interests of private galleries? Using sales data
from a parent gallery with multiple locations across the United States (each displaying similar
works/artists), I have conducted a number of qualitative and statistical analyses to identify key
differences between the West and East coast locations. In short, the gallery on the West coast sold
more works and at a lower average cost than its counterpart, providing key insights into this local
market’s consumer base. Beyond this, factors like size, medium, and artist gender were found to
have statistically significant effects on the ultimate sale price and turnover rate of works. My
findings suggest that means of data analytics should be utilized by all actors in the art markets to
optimize their approach to business, as well as understand their consumers better than ever before.
Professor Michelle Connolly, Faculty Advisor
Professor Hans Van Miegroet, Faculty Advisor
JEL classification: Z11, C10, J11, O33
User Loyalty and Willingness to Pay for a Music Streaming Subscription
By Nell Jones
Music streaming has increased industry revenue and displaced piracy, but limited profits for artists. In this thesis, I examine user loyalty to streaming platforms, focusing on the asset specificity of features and estimating what users are willing to pay for each of these features. A structural equation model of survey data shows that feature satisfaction positively affects both asset specificity of and overall satisfaction with streaming platforms, strengthening user loyalty. Using conjoint analysis, I estimate that users are willing to pay at least $14.40 for platforms that offer algorithm, playlist and social features, and the ability to download music.
Advisors: Professor Michael Munger, Professor Grace Kim | JEL Codes: Z1, Z11, M21
Increased Foreign Revenue Shares in the United States Film Industry: 2000 – 2014
By Victoria Lim
The American film industry, which has historically been driven by the domestic market, now receives an increasing proportion of its revenue from abroad (foreign share). To determine the factors influencing this trend, this paper analyzed data from 11 countries of 2,337 American films released during 2000 – 2014. Both film and country attributes were analyzed to determine each attribute’s effect on foreign share, whether its effect size has changed over time and whether each attribute has changed in frequency amongst films released. The results identified six attributes, star actors, sequels, releases in top markets, release time lag, GDP growth and a match in language, that contributed to the increase in foreign share over this period.
Advisor: James Roberts, Kent Kimbrough | JEL Codes: F40, L82, Z11 | Tagged: Foreign Share, International Box Office Revenue, Motion Picture Industry
Optimal Ordering in Sequential English Auctions: A Revenue-Comparison Model for 18th Century Art Auctions in London and Paris
By Amaan Mitha
We develop a model based on several auction parameters to test the widely held notion that in a sequential English auction, it is optimal for the seller to arrange the lots in order of decreasing value. We test this model against two datasets of 18th century auctions, one of various auctions from Paris and the other from Christie’s sales in London. We find that the Paris data support the claim, while the Christie’s data seem to refute the optimal strategy. We also find a rationale for bidders in the Christie’s auctions to alter their strategies, accounting for the discrepancy.
Advisor: Neil De Marchi | JEL Codes: D4, Z11 | Tagged: Auctions, English Auction, Lot Ordering, Optimal Auction Strategy, Sequential Auctions
