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Efficient semiparametric estimation of multi-valued treatment effects under ignorability

Cattaneo, Matias D.·2010·Journal of Econometrics

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Citations

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Show all 6 references

Research works printed but not linked: 23

  1. Abadie, 2006, Large sample properties of matching estimators for average treatment effects, Econometrica, 74, 235, 10.1111/j.1468-0262.2006.00655.x · DOI · Paper page
  2. Ai, 2003, Efficient estimation of models with conditional moment restrictions containing unknown functions, Econometrica, 71, 1795, 10.1111/1468-0262.00470 · DOI · Paper page
  3. Almond, 2005, The costs of low birth weight, Quarterly Journal of Economics, 120, 1031
  4. Bang, 2005, Doubly robust estimation in missing data and causal inference models, Biometrics, 61, 962, 10.1111/j.1541-0420.2005.00377.x · DOI · Paper page
  5. Chen, 2005, Measurement error models with auxiliary data, Review of Economic Studies, 72, 343, 10.1111/j.1467-937X.2005.00335.x · DOI · Paper page
  6. Chen, 2008, Semiparametric efficiency in GMM models with auxiliary data, Annals of Statistics, 36, 808, 10.1214/009053607000000947 · DOI · Paper page
  7. Chen, 2009, Efficient estimation of semiparametric conditional moment models with possibly nonsmooth residuals, Journal of Econometrics, 152, 46, 10.1016/j.jeconom.2009.02.002 · DOI
  8. Firpo, 2007, Efficient semiparametric estimation of quantile treatment effects, Econometrica, 75, 259, 10.1111/j.1468-0262.2007.00738.x · DOI · Paper page
  9. Hahn, 1998, On the role of the propensity score in efficient semiparametric estimation of average treatment effects, Econometrica, 66, 315, 10.2307/2998560 · DOI · Paper page
  10. Heckman, 1998, Matching as an econometric evaluation estimator, Review of Economic Studies, 65, 261, 10.1111/1467-937X.00044 · DOI · Paper page
  11. Hirano, 2003, Efficient estimation of average treatment effects using the estimated propensity score, Econometrica, 71, 1161, 10.1111/1468-0262.00442 · DOI · Paper page
  12. Imai, 2004, Causal inference with general treatment regimes: Generalizing the propensity score, Journal of the American Statistical Association, 99, 854, 10.1198/016214504000001187 · DOI · Paper page
  13. Imbens, 2000, The role of the propensity score in estimating dose–response functions, Biometrika, 87, 706, 10.1093/biomet/87.3.706 · DOI · Paper page
  14. Imbens, G.W., Newey, W.K., Ridder, G., 2006. Mean-squared-error calculations for average treatment effects. Working Paper · DOI
  15. Imbens, 2009, Recent developments in the econometrics of program evaluation, Journal of Economic Literature, 47, 5, 10.1257/jel.47.1.5 · DOI · Paper page
  16. Newey, 1990, Semiparametric efficiency bounds, Journal of Applied Econometrics, 5, 99, 10.1002/jae.3950050202 · DOI · Paper page
  17. Newey, 1994, Convergence rates and asymptotic normality for series estimators, Journal of Econometrics, 79, 147, 10.1016/S0304-4076(97)00011-0 · DOI · Paper page
  18. Pakes, 1989, Simulation and the asymptotics of optimization estimators, Econometrica, 57, 1027, 10.2307/1913622 · DOI · Paper page
  19. Robins, 1995, Semiparametric efficiency in multivariate regression models with missing data, Journal of the American Statistical Association, 90, 122, 10.2307/2291135 · DOI
  20. Robins, 1994, Estimation of regression coefficients when some regressors are not always observed, Journal of the American Statistical Association, 89, 846, 10.2307/2290910 · DOI
  21. Robins, 1995, Analysis of semiparametric regression models for repeated outcomes in the presence of missing data, Journal of the American Statistical Association, 90, 846, 10.2307/2291134 · DOI
  22. Rosenbaum, 1983, The central role of the propensity score in observational studies for causal effects, Biometrika, 70, 41, 10.1093/biomet/70.1.41 · DOI · Paper page
  23. Tanabe, 1992, An exact Cholesky decomposition and the generalized inverse of the variance-covariance matrix of the multinomial distribution, with applications, Journal of the Royal Statistical Society. Series B Methodological, 54, 211, 10.1111/j.2517-6161.1992.tb01875.x · doi:10.1111/j.2517-6161.1992.tb01875.x

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Metadata

Authors
Cattaneo, M. D.
Venue
Journal of Econometrics
Publisher
Elsevier BV
Published
2010-04
Volume
155
Issue
2
Pages
138-154
ISSN
0304-4076 (ISSN-L)
OpenAlex
W1998833647
Cited by
620
References
6
FWCI
4.65
Type
journal article
Language
en
Open access
closed
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)

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CoChat. (2026). Citation check: Efficient semiparametric estimation of multi-valued treatment effects under ignorability. https://app.cochat.ai/papers/10.1016/j.jeconom.2009.09.023
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Cattaneo, M. D. (2010). Efficient semiparametric estimation of multi-valued treatment effects under ignorability. Journal of Econometrics. https://doi.org/10.1016/j.jeconom.2009.09.023

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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.