Titel:The Impact of the Agency Model on E-book Prices: Evidence from the UK
Autor:Gail, Maximiliam Maurice
Weitere Verfasser:Klotz, Phil-Adrian
Veröffentlicht:2021
URI:https://archiv.ub.uni-marburg.de/es/2024/0687
URN: urn:nbn:de:hebis:04-es2024-06873
DOI: https://doi.org/10.17192/es2024.0687
ISSN: 1867-3678
DDC:330 Wirtschaft
Publikationsdatum:2024-01-19
Lizenz:https://creativecommons.org/publicdomain/mark/1.0

Dokument

Schlagwörter:
double machine learning, Amazon, agency, resale price maintenance, e-books, Latent Dirichlet allocation

Summary:
This paper empirically analyzes the effect of the widely used agency model on the retail prices of e-books in United Kingdom. Using a unique cross-sectional data set of e-book prices for a large sample of book titles across all major publishing houses, we exploit cross-genre and cross-publisher variation to identify the mean effect of the agency model on e-book prices. Since the genre information is ambiguous and even missing for some titles in our original dataset, we use a Latent Dirichlet Allocation (LDA) approach to determine detailed book genres based on the book's descriptions. We find that e-book prices for titles that are sold under the agency model are 36% cheaper than titles sold under the wholesale model on average. Our results are robust to different specifications, a Lewbel instrumental variable approach, and machine learning techniques.


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