The DOI matches its Crossref record.
Estimating Multiple-Discrete Choice Models: An Application to Computerization Returns
Abstract
Buyers in many markets face multiple-discrete choices: they can purchase multiple-units as well as multiple-brands at the same time. This paper presents a multiple-discrete choice model for the analysis of differentiated products demand. Users maximize profits by choosing the number of units of each brand they purchase. I estimate the model using micro-level data on the demand for personal computers. I use the estimated demand structure to assess the welfare gains from computerization and technological innovation in peripherals. The estimated return on investment in personal computers is 92%. Moreover, a 10% increase in the performance-to-price ratio of microprocessors leads to a 2·2% gain in the estimated user surplus.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
The Internet-of-Things: Review and research directions
Ng, I. C. L., & Wakenshaw, S. Y. L. (2017) · International Journal of Research in Marketing · doi:10.1016/j.ijresmar.2016.11.003 · Cited by 621
Mobile App Analytics: A Multiple Discrete-Continuous Choice Framework1
Han, S. P., Park, S., & Oh, W. (2016) · MIS Quarterly · doi:10.25300/misq/2016/40.4.09 · Cited by 86
Metadata
- Authors
- Hendel, I.
- Venue
- Review of Economic Studies
- Publisher
- Oxford University Press (OUP)
- Published
- 1999-04
- Volume
- 66
- Issue
- 2
- Pages
- 423-446
- ISSN
- 0034-6527 (ISSN-L)
- 1467-937X
- OpenAlex
- W3121740449
- Cited by
- 273
- References
- 0
- FWCI
- 9.59
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Estimating Multiple-Discrete Choice Models: An Application to Computerization Returns. https://app.cochat.ai/papers/10.1111/1467-937x.00093
- The paper
- Hendel, I. (1999). Estimating Multiple-Discrete Choice Models: An Application to Computerization Returns. Review of Economic Studies. https://doi.org/10.1111/1467-937x.00093
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
