Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/330660 
Year of Publication: 
2025
Citation: 
[Journal:] Journal of Industry, Competition and Trade [ISSN:] 1573-7012 [Volume:] 25 [Issue:] 1 [Article No.:] 17 [Publisher:] Springer US [Place:] New York, NY [Year:] 2025
Publisher: 
Springer US, New York, NY
Abstract: 
This paper empirically analyzes the relation between the widely used agency model and retail prices of e-books sold in the UK. Using a unique cross-sectional data set of e-book prices for a large number of book titles across all major publishing houses, we exploit cross-genre and cross-publisher variation to examine the interplay between the agency model and e-book prices. Since the genre information is ambiguous and even missing for some titles in our original data set, we also apply a latent Dirichlet allocation (LDA) approach to determine detailed book genres based on the book's descriptions. Using propensity score matching, we find that retail prices for e-books sold under the agency model tend to be systematically lower than book titles with similar characteristics sold under the wholesale model, approximately 20%. This result varies with the exact sales rank of a book and is driven by the so-called long tail books. Our results are robust across various regression specifications and double machine learning techniques.
Subjects: 
E-books
Agency agreements
Vertical restraints
Amazon
Propensity score matching
JEL: 
D12
D22
L42
L82
Z11
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

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