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Cited by 513

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

THE INFLUENCE OF EXPERT REVIEWS ON CONSUMER DEMAND FOR EXPERIENCE GOODS: A CASE STUDY OF MOVIE CRITICS*

Reinstein, David A., Snyder, Christopher M.·2005·Journal of Industrial Economics

Abstract

An inherent problem in measuring the influence of expert reviews on the demand for experience goods is that a correlation between good reviews and high demand may be spurious, induced by an underlying correlation with unobservable quality signals. Using the timing of the reviews by two popular movie critics, Siskel and Ebert, relative to opening weekend box office revenue, we apply a difference-in-differences approach to circumvent the problem of spurious correlation. After purging the spurious correlation, the measured influence effect is smaller though still detectable. Positive reviews have a particularly large influence on the demand for dramas and narrowly-released movies. Copyright Blackwell Publishing Ltd. 2005.

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Crossref · 10.1111/j.0022-1821.2005.00244.x

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Metadata

Authors
Reinstein, D. A., & Snyder, C. M.
Venue
Journal of Industrial Economics
Publisher
Wiley
Published
2005-03
Volume
53
Issue
1
Pages
27-51
ISSN
  • 0022-1821
  • 1467-6451
OpenAlex
W3123123052
Cited by
513
References
2
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: THE INFLUENCE OF EXPERT REVIEWS ON CONSUMER DEMAND FOR EXPERIENCE GOODS: A CASE STUDY OF MOVIE CRITICS*. https://app.cochat.ai/papers/10.1111/j.0022-1821.2005.00244.x
The paper
Reinstein, D. A., & Snyder, C. M. (2005). THE INFLUENCE OF EXPERT REVIEWS ON CONSUMER DEMAND FOR EXPERIENCE GOODS: A CASE STUDY OF MOVIE CRITICS*. Journal of Industrial Economics. https://doi.org/10.1111/j.0022-1821.2005.00244.x

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.