Confidence intervals for intentionally biased estimators
Author
Abstract
Suggested Citation
Download full text from publisher
Other versions of this item:
- David M. Kaplan & Xin Liu, 2024. "Confidence intervals for intentionally biased estimators," Econometric Reviews, Taylor & Francis Journals, vol. 43(2-4), pages 197-214, April.
- David M. Kaplan & Xin Liu, 2023. "Confidence Intervals for Intentionally Biased Estimators," Working Papers 2308, Department of Economics, University of Missouri.
References listed on IDEAS
- Kaplan, David M. & Sun, Yixiao, 2017.
"Smoothed Estimating Equations For Instrumental Variables Quantile Regression,"
Econometric Theory, Cambridge University Press, vol. 33(1), pages 105-157, February.
- Kaplan, David M. & Sun, Yixiao, 2012. "Smoothed Estimating Equations For Instrumental Variables Quantile Regression," University of California at San Diego, Economics Working Paper Series qt888657tp, Department of Economics, UC San Diego.
- David M. Kaplan & Yixiao Sun, 2013. "Smoothed Estimating Equations for Instrumental Variables Quantile Regression," Working Papers 1314, Department of Economics, University of Missouri.
- Horowitz, Joel L, 1992. "A Smoothed Maximum Score Estimator for the Binary Response Model," Econometrica, Econometric Society, vol. 60(3), pages 505-531, May.
- Kaplan, David M. & Sun, Yixiao, 2017.
"Smoothed Estimating Equations For Instrumental Variables Quantile Regression,"
Econometric Theory, Cambridge University Press, vol. 33(1), pages 105-157, February.
- Kaplan, David M. & Sun, Yixiao, 2012. "Smoothed Estimating Equations For Instrumental Variables Quantile Regression," University of California at San Diego, Economics Working Paper Series qt888657tp, Department of Economics, UC San Diego.
- David M. Kaplan & Yixiao Sun, 2016. "Smoothed estimating equations for instrumental variables quantile regression," Papers 1609.09033, arXiv.org.
- David M. Kaplan & Yixiao Sun, 2013. "Smoothed Estimating Equations for Instrumental Variables Quantile Regression," Working Papers 1314, Department of Economics, University of Missouri.
- Manski, Charles F., 1975. "Maximum score estimation of the stochastic utility model of choice," Journal of Econometrics, Elsevier, vol. 3(3), pages 205-228, August.
- Fan J. & Li R., 2001. "Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1348-1360, 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.- Javier Alejo & Gabriel Montes-Rojas, 2021. "Quantile Regression under Limited Dependent Variable," Papers 2112.06822, arXiv.org.
- Bruins, Marianne & Duffy, James A. & Keane, Michael P. & Smith, Anthony A., 2018.
"Generalized indirect inference for discrete choice models,"
Journal of Econometrics, Elsevier, vol. 205(1), pages 177-203.
- Anthony A. Smith, Jr. & Michael Keane, 2004. "Generalized Indirect Inference for Discrete Choice Models," Econometric Society 2004 North American Winter Meetings 512, Econometric Society.
- Marianne Bruins & James A. Duffy & Michael P. Keane & Anthony A. Smith, Jr, 2015. "Generalized Indirect Inference for Discrete Choice Models," Economics Papers 2015-W08, Economics Group, Nuffield College, University of Oxford.
- de Castro, Luciano & Galvao, Antonio F. & Kaplan, David M. & Liu, Xin, 2019.
"Smoothed GMM for quantile models,"
Journal of Econometrics, Elsevier, vol. 213(1), pages 121-144.
- Luciano de Castro & Antonio F. Galvao & David M. Kaplan, 2017. "Smoothed instrumental variables quantile regression, with estimation of quantile Euler equations," Working Papers 1710, Department of Economics, University of Missouri, revised 28 Feb 2018.
- Luciano de Castro & Antonio F. Galvao & David M. Kaplan & Xin Liu, 2018. "Smoothed GMM for quantile models," Working Papers 1803, Department of Economics, University of Missouri.
- David M. Kaplan, 2019. "Unbiased Estimation as a Public Good," Working Papers 1911, Department of Economics, University of Missouri.
- de Castro, Luciano & Galvao, Antonio F. & Kaplan, David M. & Liu, Xin, 2019.
"Smoothed GMM for quantile models,"
Journal of Econometrics, Elsevier, vol. 213(1), pages 121-144.
- Luciano de Castro & Antonio F. Galvao & David M. Kaplan & Xin Liu, 2017. "Smoothed GMM for quantile models," Papers 1707.03436, arXiv.org, revised Feb 2018.
- Luciano de Castro & Antonio F. Galvao & David M. Kaplan & Xin Liu, 2018. "Smoothed GMM for quantile models," Working Papers 1803, Department of Economics, University of Missouri.
- Javier Alejo & Antonio F. Galvao & Gabriel Montes-Rojas, 2020. "A first-stage test for instrumental variables quantile regression," Asociación Argentina de Economía Política: Working Papers 4304, Asociación Argentina de Economía Política.
- Patrick Bajari & Jeremy Fox & Stephen Ryan, 2008.
"Evaluating wireless carrier consolidation using semiparametric demand estimation,"
Quantitative Marketing and Economics (QME), Springer, vol. 6(4), pages 299-338, December.
- Patrick Bajari & Jeremy T. Fox & Stephen Ryan, 2006. "Evaluating Wireless Carrier Consolidation Using Semiparametric Demand Estimation," NBER Working Papers 12425, National Bureau of Economic Research, Inc.
- Ichimura, Hidehiko & Todd, Petra E., 2007.
"Implementing Nonparametric and Semiparametric Estimators,"
Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 74,
Elsevier.
- Hidehiko Ichimura & Petra E. Todd, 2006. "Implementing Nonparametric and Semiparametric Estimators," CIRJE F-Series CIRJE-F-452, CIRJE, Faculty of Economics, University of Tokyo.
- Chen, Le-Yu & Lee, Sokbae, 2018.
"Best subset binary prediction,"
Journal of Econometrics, Elsevier, vol. 206(1), pages 39-56.
- Le-Yu Chen & Sokbae Lee, 2016. "Best Subset Binary Prediction," Papers 1610.02738, arXiv.org, revised May 2018.
- Le-Yu Chen & Sokbae (Simon) Lee, 2017. "Best subset binary prediction," CeMMAP working papers CWP50/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Le-Yu Chen & Sokbae (Simon) Lee, 2017. "Best subset binary prediction," CeMMAP working papers 50/17, Institute for Fiscal Studies.
- Delgado, Miguel A. & Rodriguez-Poo, Juan M. & Wolf, Michael, 2001.
"Subsampling inference in cube root asymptotics with an application to Manski's maximum score estimator,"
Economics Letters, Elsevier, vol. 73(2), pages 241-250, November.
- Delgado, Miguel A. & Rodríguez Poo, Juan M. & Wolf, Michael, 2000. "Subsampling inference in cube root asymptotics with an application to manski's maximum score estimator," DES - Working Papers. Statistics and Econometrics. WS 10110, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
- Park, Byeong U. & Simar, Léopold & Zelenyuk, Valentin, 2017.
"Nonparametric estimation of dynamic discrete choice models for time series data,"
Computational Statistics & Data Analysis, Elsevier, vol. 108(C), pages 97-120.
- Byeong U. Park & Leopold Simar & Valentin Zelenyuk, 2016. "Nonparametric Estimation of Dynamic Discrete Choice Models for Time Series Data," CEPA Working Papers Series WP062016, School of Economics, University of Queensland, Australia.
- Park, Byeong U. & Simar, Leopold & Zelenyuk, Valentin, 2017. "Nonparametric estimation of dynamic discrete choice models for time series data," LIDAM Reprints ISBA 2017011, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
- repec:hal:wpspec:info:hdl:2441/3vl5fe4i569nbr005tctlc8ll5 is not listed on IDEAS
- Oliver Linton & Pedro Gozalo, 1996. "Conditional Independence Restrictions: Testing and Estimation," Cowles Foundation Discussion Papers 1140, Cowles Foundation for Research in Economics, Yale University.
- Mittelhammer, Ron C. & Judge, George, 2011. "A family of empirical likelihood functions and estimators for the binary response model," Journal of Econometrics, Elsevier, vol. 164(2), pages 207-217, October.
- David Kang & Seojeong Lee & Juha Song, 2025.
"Convergence Rates of GMM Estimators with Nonsmooth Moments under Misspecification,"
Working Papers
423283930, Lancaster University Management School, Economics Department.
- Byunghoon Kang & Seojeong Lee & Juha Song, 2025. "Convergence Rates of GMM Estimators with Nonsmooth Moments under Misspecification," Papers 2501.09540, arXiv.org.
- Lahiri, Kajal & Yang, Liu, 2013.
"Forecasting Binary Outcomes,"
Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1025-1106,
Elsevier.
- Kajal Lahiri & Liu Yang, 2012. "Forecasting Binary Outcomes," Discussion Papers 12-09, University at Albany, SUNY, Department of Economics.
- Ron Mittelhammer & George Judge, 2009.
"A Minimum Power Divergence Class of CDFs and Estimators for the Binary Choice Model,"
International Econometric Review (IER), Econometric Research Association, vol. 1(1), pages 33-49, April.
- Mittelhammer, Ronald C. & Judge, George G., 2008. "A Minimum Power Divergence Class of CDFs and Estimators for Binary Choice Models," CUDARE Working Papers 37759, University of California, Berkeley, Department of Agricultural and Resource Economics.
- Mittelhammer, Ron C Dr. & Judge, George G., 2008. "A Minimum Power Divergence Class of CDFs and Estimators for Binary Choice Models," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt7bc2828q, Department of Agricultural & Resource Economics, UC Berkeley.
- Xin Liu, 2024.
"Averaging Estimation for Instrumental Variables Quantile Regression,"
Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 86(5), pages 1290-1312, October.
- Xin Liu, 2019. "Averaging estimation for instrumental variables quantile regression," Working Papers 1907, Department of Economics, University of Missouri.
- Xin Liu, 2019. "Averaging estimation for instrumental variables quantile regression," Papers 1910.04245, arXiv.org.
- repec:cep:stiecm:em/2012/559 is not listed on IDEAS
- Goldman, Matt & Kaplan, David M., 2017.
"Fractional order statistic approximation for nonparametric conditional quantile inference,"
Journal of Econometrics, Elsevier, vol. 196(2), pages 331-346.
- David M. Kaplan & Matt Goldman, 2015. "Fractional order statistic approximation for nonparametric conditional quantile inference," Working Papers 1502, Department of Economics, University of Missouri.
- Matt Goldman & David M. Kaplan, 2016. "Fractional order statistic approximation for nonparametric conditional quantile inference," Papers 1609.09035, arXiv.org.
- Yingying Dong & Arthur Lewbel, 2015.
"A Simple Estimator for Binary Choice Models with Endogenous Regressors,"
Econometric Reviews, Taylor & Francis Journals, vol. 34(1-2), pages 82-105, February.
- Yingying Dong & Arthur Lewbel, 2004. "A Simple Estimator for Binary Choice Models with Endogenous Regressors," Boston College Working Papers in Economics 604, Boston College Department of Economics, revised 15 Jun 2012.
- Yingying Dong & Arthur Lewbel, 2012. "Simple Estimators for Binary Choice Models with Endogenous Regressors," Working Papers 111204, University of California-Irvine, Department of Economics.
- Yingying Dong & Arthur Lewbel, 2012. "A Simple Estimator for Binary Choice Models With Endogenous Regressors," Boston College Working Papers in Economics 807, Boston College Department of Economics.
- Riccardo Scarpa, 2000. "Contingent Valuation Versus Choice Experiments: Estimating the Benefits of Environmentally Sensitive Areas in Scotland: Comment," Journal of Agricultural Economics, Wiley Blackwell, vol. 51(1), pages 122-128, January.
More about this item
JEL classification:
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
NEP fields
This paper has been announced in the following NEP Reports:- NEP-ECM-2025-03-03 (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:arx:papers:2502.00450. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.