Efficient propensity score regression estimators of multi-valued treatment effects for the treated
Author
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Sergio Firpo, 2007.
"Efficient Semiparametric Estimation of Quantile Treatment Effects,"
Econometrica, Econometric Society, vol. 75(1), pages 259-276, January.
- Sergio Firpo, 2004. "Efficient Semiparametric Estimation of Quantile Treatment Effects," Econometric Society 2004 North American Summer Meetings 605, Econometric Society.
- Mammen, Enno & Rothe, Christoph & Schienle, Melanie, 2016.
"Semiparametric Estimation With Generated Covariates,"
Econometric Theory, Cambridge University Press, vol. 32(5), pages 1140-1177, October.
- Mammen, Enno & Rothe, Christoph & Schienle, Melanie, 2011. "Semiparametric Estimation with Generated Covariates," IZA Discussion Papers 6084, Institute of Labor Economics (IZA).
- Mammen, Enno & Rothe, Christoph & Schienle, Melanie, 2011. "Semiparametric estimation with generated covariates," SFB 649 Discussion Papers 2011-064, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
- Mammen, Enno & Rothe, Christoph & Schienle, Melanie, 2016. "Semiparametric estimation with generated covariates," Working Paper Series in Economics 81, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
- Mammen, Enno & Rothe, Christoph & Schienle, Melanie, 2014. "Semiparametric Estimation with Generated Covariates," SFB 649 Discussion Papers 2014-043, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
- Cattaneo, Matias D., 2010. "Efficient semiparametric estimation of multi-valued treatment effects under ignorability," Journal of Econometrics, Elsevier, vol. 155(2), pages 138-154, April.
- Bryan S. Graham, 2011.
"Efficiency Bounds for Missing Data Models With Semiparametric Restrictions,"
Econometrica, Econometric Society, vol. 79(2), pages 437-452, March.
- Bryan S. Graham, 2008. "Efficiency bounds for missing data models with semiparametric restrictions," NBER Working Papers 14376, National Bureau of Economic Research, Inc.
- Matias Busso & John DiNardo & Justin McCrary, 2014. "New Evidence on the Finite Sample Properties of Propensity Score Reweighting and Matching Estimators," The Review of Economics and Statistics, MIT Press, vol. 96(5), pages 885-897, December.
- Jinyong Hahn & Geert Ridder, 2013.
"Asymptotic Variance of Semiparametric Estimators With Generated Regressors,"
Econometrica, Econometric Society, vol. 81(1), pages 315-340, January.
- Jinyong Hahn & Geert Ridder, 2010. "The asymptotic variance of semi-parametric estimators with generated regressors," CeMMAP working papers CWP23/10, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Jinyong Hahn & Geert Ridder, 2010. "The Asymptotic Variance of Semi-parametric Estimators with Generated Regressors," Textos para discussão 575, Department of Economics PUC-Rio (Brazil).
- Donald, Stephen G. & Hsu, Yu-Chin, 2014.
"Estimation and inference for distribution functions and quantile functions in treatment effect models,"
Journal of Econometrics, Elsevier, vol. 178(P3), pages 383-397.
- Stephen G. Donald & Yu-Chin Hsu, 2012. "Estimation and Inference for Distribution Functions and Quantile Functions in Treatment Effect Models," IEAS Working Paper : academic research 12-A016, Institute of Economics, Academia Sinica, Taipei, Taiwan.
- Keisuke Hirano & Guido W. Imbens & Geert Ridder, 2003.
"Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score,"
Econometrica, Econometric Society, vol. 71(4), pages 1161-1189, July.
- Guido Imbens, 2000. "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," Econometric Society World Congress 2000 Contributed Papers 1166, Econometric Society.
- Keisuke Hirano & Guido W. Imbens & Geert Ridder, 2000. "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," NBER Technical Working Papers 0251, National Bureau of Economic Research, Inc.
- Jinyong Hahn, 1998. "On the Role of the Propensity Score in Efficient Semiparametric Estimation of Average Treatment Effects," Econometrica, Econometric Society, vol. 66(2), pages 315-332, March.
- Matias D. Cattaneo, 2010. "multi-valued treatment effects," The New Palgrave Dictionary of Economics,, Palgrave Macmillan.
- Sergio Firpo & Cristine Pinto, 2016.
"Identification and Estimation of Distributional Impacts of Interventions Using Changes in Inequality Measures,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(3), pages 457-486, April.
- Firpo, Sergio, 2010. "Identification and Estimation of Distributional Impacts of Interventions Using Changes in Inequality Measures," IZA Discussion Papers 4841, Institute of Labor Economics (IZA).
- Escanciano, Juan Carlos & Jacho-Chávez, David T. & Lewbel, Arthur, 2014.
"Uniform convergence of weighted sums of non and semiparametric residuals for estimation and testing,"
Journal of Econometrics, Elsevier, vol. 178(P3), pages 426-443.
- Juan Carlos Escanciano & David Jacho-Chavez & Arthur Lewbel, 2010. "Uniform Convergence of Weighted Sums of Non- and Semi-parametric Residuals for Estimation and Testing," Boston College Working Papers in Economics 756, Boston College Department of Economics, revised 31 Jan 2012.
- Stephen G. Donald & Yu‐Chin Hsu & Garry F. Barrett, 2012. "Incorporating covariates in the measurement of welfare and inequality: methods and applications," Econometrics Journal, Royal Economic Society, vol. 15(1), pages 1-30, February.
- Guido W. Imbens & Jeffrey M. Wooldridge, 2009.
"Recent Developments in the Econometrics of Program Evaluation,"
Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
- Guido Imbens & Jeffrey M. Wooldridge, 2008. "Recent developments in the econometrics of program evaluation," CeMMAP working papers CWP24/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Wooldridge, Jeffrey M. & Imbens, Guido, 2009. "Recent Developments in the Econometrics of Program Evaluation," Scholarly Articles 3043416, Harvard University Department of Economics.
- Imbens, Guido W. & Wooldridge, Jeffrey M., 2008. "Recent Developments in the Econometrics of Program Evaluation," IZA Discussion Papers 3640, Institute of Labor Economics (IZA).
- Guido M. Imbens & Jeffrey M. Wooldridge, 2008. "Recent Developments in the Econometrics of Program Evaluation," NBER Working Papers 14251, National Bureau of Economic Research, Inc.
- A. D. Roy, 1951. "Some Thoughts On The Distribution Of Earnings," Oxford Economic Papers, Oxford University Press, vol. 3(2), pages 135-146.
- Rothe, Christoph, 2010. "Nonparametric estimation of distributional policy effects," Journal of Econometrics, Elsevier, vol. 155(1), pages 56-70, March.
- Michael Lechner, 2002. "Program Heterogeneity And Propensity Score Matching: An Application To The Evaluation Of Active Labor Market Policies," The Review of Economics and Statistics, MIT Press, vol. 84(2), pages 205-220, May.
- Busso, Matias & DiNardo, John & McCrary, Justin, 2009. "New Evidence on the Finite Sample Properties of Propensity Score Matching and Reweighting Estimators," IZA Discussion Papers 3998, Institute of Labor Economics (IZA).
- Rajeev H. Dehejia & Sadek Wahba, 2002.
"Propensity Score-Matching Methods For Nonexperimental Causal Studies,"
The Review of Economics and Statistics, MIT Press, vol. 84(1), pages 151-161, February.
- Rajeev H. Dehejia & Sadek Wahba, 1998. "Propensity Score Matching Methods for Non-experimental Causal Studies," NBER Working Papers 6829, National Bureau of Economic Research, Inc.
- Heckman, James J. & Lalonde, Robert J. & Smith, Jeffrey A., 1999. "The economics and econometrics of active labor market programs," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 31, pages 1865-2097, Elsevier.
- Kosuke Imai & David A. van Dyk, 2004. "Causal Inference With General Treatment Regimes: Generalizing the Propensity Score," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 854-866, January.
- Bhattacharya, Debopam, 2007. "Inference on inequality from household survey data," Journal of Econometrics, Elsevier, vol. 137(2), pages 674-707, April.
- James J. Heckman & Hidehiko Ichimura & Petra Todd, 1998. "Matching As An Econometric Evaluation Estimator," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(2), pages 261-294.
- Ying-Ying Lee, 2014. "Partial Mean Processes with Generated Regressors: Continuous Treatment Effects and Nonseparable Models," Economics Series Working Papers 706, University of Oxford, Department of Economics.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Muhammad Arif & Mudassar Hasan & Ahmed Shafique Joyo & Christopher Gan & Sazali Abidin, 2020. "Formal Finance Usage and Innovative SMEs: Evidence from ASEAN Countries," JRFM, MDPI, vol. 13(10), pages 1-19, September.
- Lee, Ying-Ying & Bhattacharya, Debopam, 2019.
"Applied welfare analysis for discrete choice with interval-data on income,"
Journal of Econometrics, Elsevier, vol. 211(2), pages 361-387.
- Lee, Y-Y. & Bhattacharya, D., 2018. "Applied Welfare Analysis for Discrete Choice with Interval-data on Income," Cambridge Working Papers in Economics 1882, Faculty of Economics, University of Cambridge.
- Young-Min Ju & Myoung-Jae Lee, 2017. "Control Function Approach for Partly Ordered Endogenous Treatments: Military Rank Premium in Wage," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(6), pages 1176-1194, December.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Lee, Ying-Ying, 2018. "Efficient propensity score regression estimators of multivalued treatment effects for the treated," Journal of Econometrics, Elsevier, vol. 204(2), pages 207-222.
- Ying-Ying Lee, 2014. "Partial Mean Processes with Generated Regressors: Continuous Treatment Effects and Nonseparable Models," Economics Series Working Papers 706, University of Oxford, Department of Economics.
- Carlos A. Flores & Oscar A. Mitnik, 2009.
"Evaluating Nonexperimental Estimators for Multiple Treatments: Evidence from Experimental Data,"
Working Papers
2010-10, University of Miami, Department of Economics.
- Flores, Carlos A. & Mitnik, Oscar A., 2009. "Evaluating Nonexperimental Estimators for Multiple Treatments: Evidence from Experimental Data," IZA Discussion Papers 4451, Institute of Labor Economics (IZA).
- Carlos A. Flores & Oscar A. Mitnik, 2009. "Evaluating Nonexperimental Estimators for Multiple Treatments: Evidence from Experimental Data," Working Papers 2010-9, University of Miami, Department of Economics.
- Ying-Ying Lee, 2018. "Partial Mean Processes with Generated Regressors: Continuous Treatment Effects and Nonseparable Models," Papers 1811.00157, arXiv.org.
- Chunrong Ai & Oliver Linton & Kaiji Motegi & Zheng Zhang, 2021.
"A unified framework for efficient estimation of general treatment models,"
Quantitative Economics, Econometric Society, vol. 12(3), pages 779-816, July.
- Chunrong Ai & Oliver Linton & Kaiji Motegi & Zheng Zhang, 2018. "A Unified Framework for Efficient Estimation of General Treatment Models," Papers 1808.04936, arXiv.org, revised Aug 2018.
- Chunrong Ai & Oliver Linton & Kaiji Motegi & Zheng Zhang, 2019. "A Unified Framework for Efficient Estimation of General Treatment Models," CeMMAP working papers CWP64/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Ai, C. & Linton, O. & Motegi, K. & Zhang, Z., 2019. "A Unified Framework for Efficient Estimation of General Treatment Models," Cambridge Working Papers in Economics 1934, Faculty of Economics, University of Cambridge.
- Wei Huang & Oliver Linton & Zheng Zhang, 2021.
"A Unified Framework for Specification Tests of Continuous Treatment Effect Models,"
Papers
2102.08063, arXiv.org, revised Sep 2021.
- Huang, W. & Linton, O. & Zhang, Z., 2021. "A Unified Framework for Specification Tests of Continuous Treatment Effect Models," Cambridge Working Papers in Economics 2113, Faculty of Economics, University of Cambridge.
- Pedro H. C. Sant'Anna, 2016. "Program Evaluation with Right-Censored Data," Papers 1604.02642, arXiv.org.
- Alejo, Javier & Galvao, Antonio F. & Montes-Rojas, Gabriel, 2018. "Quantile continuous treatment effects," Econometrics and Statistics, Elsevier, vol. 8(C), pages 13-36.
- Carlos A. Flores & Oscar A. Mitnik, 2013.
"Comparing Treatments across Labor Markets: An Assessment of Nonexperimental Multiple-Treatment Strategies,"
The Review of Economics and Statistics, MIT Press, vol. 95(5), pages 1691-1707, December.
- Carlos A. Flores & Oscar A. Mitnik, 2011. "Comparing Treatments across Labor Markets: An Assessment of Nonexperimental Multiple-Treatment Strategies," Working Papers 2011-10, University of Miami, Department of Economics.
- Huber, Martin, 2019.
"An introduction to flexible methods for policy evaluation,"
FSES Working Papers
504, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
- Martin Huber, 2019. "An introduction to flexible methods for policy evaluation," Papers 1910.00641, arXiv.org.
- Ai, Chunrong & Linton, Oliver & Zhang, Zheng, 2022. "Estimation and inference for the counterfactual distribution and quantile functions in continuous treatment models," Journal of Econometrics, Elsevier, vol. 228(1), pages 39-61.
- Rothe, Christoph, 2016. "The Value of Knowing the Propensity Score for Estimating Average Treatment Effects," IZA Discussion Papers 9989, Institute of Labor Economics (IZA).
- Sant’Anna, Pedro H.C. & Song, Xiaojun, 2019.
"Specification tests for the propensity score,"
Journal of Econometrics, Elsevier, vol. 210(2), pages 379-404.
- Pedro H. C. Sant'Anna & Xiaojun Song, 2016. "Specification Tests for the Propensity Score," Papers 1611.06217, arXiv.org, revised Feb 2019.
- Frölich, Markus & Huber, Martin & Wiesenfarth, Manuel, 2017.
"The finite sample performance of semi- and non-parametric estimators for treatment effects and policy evaluation,"
Computational Statistics & Data Analysis, Elsevier, vol. 115(C), pages 91-102.
- Frölich, Markus & Huber, Martin & Wiesenfarth, Manuel, 2015. "The Finite Sample Performance of Semi- and Nonparametric Estimators for Treatment Effects and Policy Evaluation," IZA Discussion Papers 8756, Institute of Labor Economics (IZA).
- Frölich, Markus & Huber, Martin & Wiesenfarth, Manuel, 2015. "The finite sample performance of semi- and nonparametric estimators for treatment effects and policy evaluation," FSES Working Papers 454, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
- Guido W. Imbens & Jeffrey M. Wooldridge, 2009.
"Recent Developments in the Econometrics of Program Evaluation,"
Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
- Guido Imbens & Jeffrey M. Wooldridge, 2008. "Recent developments in the econometrics of program evaluation," CeMMAP working papers CWP24/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Wooldridge, Jeffrey M. & Imbens, Guido, 2009. "Recent Developments in the Econometrics of Program Evaluation," Scholarly Articles 3043416, Harvard University Department of Economics.
- Imbens, Guido W. & Wooldridge, Jeffrey M., 2008. "Recent Developments in the Econometrics of Program Evaluation," IZA Discussion Papers 3640, Institute of Labor Economics (IZA).
- Guido M. Imbens & Jeffrey M. Wooldridge, 2008. "Recent Developments in the Econometrics of Program Evaluation," NBER Working Papers 14251, National Bureau of Economic Research, Inc.
- Rahul Singh & Liyuan Xu & Arthur Gretton, 2020. "Kernel Methods for Causal Functions: Dose, Heterogeneous, and Incremental Response Curves," Papers 2010.04855, arXiv.org, revised Oct 2022.
- Difang Huang & Jiti Gao & Tatsushi Oka, 2022.
"Semiparametric Single-Index Estimation for Average Treatment Effects,"
Papers
2206.08503, arXiv.org, revised Apr 2024.
- Difang Huang & Jiti Gao & Tatsushi Oka, 2022. "Semiparametric Single-Index Estimation for Average Treatment Effects," Monash Econometrics and Business Statistics Working Papers 10/22, Monash University, Department of Econometrics and Business Statistics.
- Farrell, Max H., 2015.
"Robust inference on average treatment effects with possibly more covariates than observations,"
Journal of Econometrics, Elsevier, vol. 189(1), pages 1-23.
- Max H. Farrell, 2013. "Robust Inference on Average Treatment Effects with Possibly More Covariates than Observations," Papers 1309.4686, arXiv.org, revised Feb 2018.
- Jones A.M & Rice N, 2009. "Econometric Evaluation of Health Policies," Health, Econometrics and Data Group (HEDG) Working Papers 09/09, HEDG, c/o Department of Economics, University of York.
- Hugo Bodory & Lorenzo Camponovo & Martin Huber & Michael Lechner, 2020.
"The Finite Sample Performance of Inference Methods for Propensity Score Matching and Weighting Estimators,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(1), pages 183-200, January.
- Bodory, Hugo & Camponovo, Lorenzo & Huber, Martin & Lechner, Michael, 2016. "The finite sample performance of inference methods for propensity score matching and weighting estimators," Economics Working Paper Series 1604, University of St. Gallen, School of Economics and Political Science.
- Bodory, Hugo & Camponovo, Lorenzo & Huber, Martin & Lechner, Michael, 2016. "The Finite Sample Performance of Inference Methods for Propensity Score Matching and Weighting Estimators," IZA Discussion Papers 9706, Institute of Labor Economics (IZA).
- Bodory, Hugo & Huber, Martin & Camponovo, Lorenzo & Lechner, Michael, 2016. "The finite sample performance of inference methods for propensity score matching and weighting estimators," FSES Working Papers 466, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
More about this item
Keywords
propensity score; multi-valued treatment; semiparametric efficiency bound; unconfoundedness; generated regressor;All these keywords.
JEL classification:
- C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
NEP fields
This paper has been announced in the following NEP Reports:- NEP-ECM-2015-01-26 (Econometrics)
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:oxf:wpaper:738. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Anne Pouliquen (email available below). General contact details of provider: https://edirc.repec.org/data/sfeixuk.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.