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Cited by 627

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Local instrumental variables and latent variable models for identifying and bounding treatment effects

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Heckman, James J., Vytlacil, Edward J.·1999·Proceedings of the National Academy of Sciences

Abstract

This paper examines the relationship between various treatment parameters within a latent variable model when the effects of treatment depend on the recipient’s observed and unobserved characteristics. We show how this relationship can be used to identify the treatment parameters when they are identified and to bound the parameters when they are not identified.

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Citations

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Research works printed but not linked: 17

  1. J Neyman Stat Sci 5, 465–480 (1990).
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  12. J Heckman, R Robb Longitudinal Analysis of Labor Market Data, eds J Heckman, B Singer (Cambridge Univ. Press, New York), pp. 156–245 (1985). · DOI · Paper page
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  14. A N Kolmogorov, S V Fomin Introductory Real Analysis, trans. Silverman, R. (Dover, New York, NY, 1970).
  15. C R Rao A Celebration of Statistics, ed S Feinberg (Springer, Berlin, 1986).
  16. C Manski Am Econ Rev 80, 319–323 (1990).
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Metadata

Authors
Heckman, J. J., & Vytlacil, E. J.
Venue
Proceedings of the National Academy of Sciences
Published
1999-04-13
Volume
96
Issue
8
Pages
4730-4734
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2023492742
Cited by
627
References
1
FWCI
8.56
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Local instrumental variables and latent variable models for identifying and bounding treatment effects. https://app.cochat.ai/papers/10.1073/pnas.96.8.4730
The paper
Heckman, J. J., & Vytlacil, E. J. (1999). Local instrumental variables and latent variable models for identifying and bounding treatment effects. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.96.8.4730

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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.