IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Log in (now much improved!) to save this paper

Asymptotically efficient estimation of weighted average derivatives with an interval censored variable

  • Hiroaki Kaido

    ()

    (Institute for Fiscal Studies and Boston University)

This paper studies the identi fication and estimation of weighted average derivatives of conditional location functionals including conditional mean and conditional quantiles in settings where either the outcome variable or a regressor is interval-valued. Building on Manski and Tamer (2002) who study nonparametric bounds for mean regression with interval data, we characterize the identifi ed set of weighted average derivatives of regression functions. Since the weighted average derivatives do not rely on parametric speci fications for the regression functions, the identi fied set is well-defi ned without any parametric assumptions. Under general conditions, the identifi ed set is compact and convex and hence admits characterization by its support function. Using this characterization, we derive the semiparametric efficiency bound of the support function when the outcome variable is interval-valued. We illustrate efficient estimation by constructing an efficient estimator of the support function for the case of mean regression with an interval censored outcome.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.cemmap.ac.uk/wps/cwp031414.pdf
Download Restriction: no

Paper provided by Centre for Microdata Methods and Practice, Institute for Fiscal Studies in its series CeMMAP working papers with number CWP03/14.

as
in new window

Length:
Date of creation: 15 Jan 2014
Date of revision:
Handle: RePEc:ifs:cemmap:03/14
Contact details of provider: Postal:
The Institute for Fiscal Studies 7 Ridgmount Street LONDON WC1E 7AE

Phone: (+44) 020 7291 4800
Fax: (+44) 020 7323 4780
Web page: http://cemmap.ifs.org.uk
Email:


More information through EDIRC

Order Information: Postal: The Institute for Fiscal Studies 7 Ridgmount Street LONDON WC1E 7AE
Email:


References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as in new window
  1. Härdle, W.K. & Tsybakov, A.B., 1992. "How sensitive are average derivatives?," Discussion Paper 1992-8, Tilburg University, Center for Economic Research.
  2. Donald W. K. Andrews & Xiaoxia Shi, 2013. "Inference Based on Conditional Moment Inequalities," Econometrica, Econometric Society, vol. 81(2), pages 609-666, 03.
  3. Wolfgang Härdle & Werner Hildenbrand & Michael Jerison, 1989. "Empirical Evidence on the Law of Demand," Discussion Paper Serie A 264a, University of Bonn, Germany.
  4. Beresteanu, Arie & Molinari, Francesca, 2006. "Asymptotic Properties for a Class of Partially Identified Models," Working Papers 06-07, Cornell University, Center for Analytic Economics.
  5. Charles F. Manski & Elie Tamer, 2002. "Inference on Regressions with Interval Data on a Regressor or Outcome," Econometrica, Econometric Society, vol. 70(2), pages 519-546, March.
  6. Andrews, Donald W.K. & Shi, Xiaoxia, 2014. "Nonparametric inference based on conditional moment inequalities," Journal of Econometrics, Elsevier, vol. 179(1), pages 31-45.
  7. Paul Milgrom & Ilya Segal, 2002. "Envelope Theorems for Arbitrary Choice Sets," Econometrica, Econometric Society, vol. 70(2), pages 583-601, March.
  8. Patrick M. Kline & Andres Santos, 2010. "A Score Based Approach to Wild Bootstrap Inference," NBER Working Papers 16127, National Bureau of Economic Research, Inc.
  9. Victor Chernozhukov & Sokbae Lee & Adam Rosen, 2009. "Intersection Bounds: estimation and inference," CeMMAP working papers CWP19/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  10. Newey, Whitney K & Stoker, Thomas M, 1993. "Efficiency of Weighted Average Derivative Estimators and Index Models," Econometrica, Econometric Society, vol. 61(5), pages 1199-223, September.
  11. Victor Chernozhukov & Wooyoung Kim & Sokbae Lee & Adam Rosen, 2013. "Implementing intersection bounds in Stata," CeMMAP working papers CWP38/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  12. Hirano, Keisuke & Porter, Jack, 2006. "Asymptotics for statistical treatment rules," MPRA Paper 1173, University Library of Munich, Germany.
  13. Hiroaki Kaido & Andres Santos, 2014. "Asymptotically Efficient Estimation of Models Defined by Convex Moment Inequalities," Econometrica, Econometric Society, vol. 82(1), pages 387-413, 01.
  14. Pedro Carneiro & James Heckman & Edward Vytlacil, 2009. "Evaluating marginal policy changes and the average effect of treatment for individuals at the margin," CeMMAP working papers CWP21/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  15. Stoker, Thomas M, 1986. "Consistent Estimation of Scaled Coefficients," Econometrica, Econometric Society, vol. 54(6), pages 1461-81, November.
  16. Maria Ponomareva & Elie Tamer, 2011. "Misspecification in moment inequality models: back to moment equalities?," Econometrics Journal, Royal Economic Society, vol. 14(2), pages 186-203, 07.
  17. Arie Beresteanu & Ilya Molchanov & Francesca Molinari, 2010. "Sharp identification regions in models with convex moment predictions," CeMMAP working papers CWP25/10, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  18. Keisuke Hirano & Jack R. Porter, 2012. "Impossibility Results for Nondifferentiable Functionals," Econometrica, Econometric Society, vol. 80(4), pages 1769-1790, 07.
  19. Y. Nishiyama & P. M. Robinson, 2000. "Edgeworth Expansions for Semiparametric Averaged Derivatives," Econometrica, Econometric Society, vol. 68(4), pages 931-980, July.
  20. Severini, Thomas A. & Tripathi, Gautam, 2001. "A simplified approach to computing efficiency bounds in semiparametric models," Journal of Econometrics, Elsevier, vol. 102(1), pages 23-66, May.
  21. repec:cwl:cwldpp:1840rr is not listed on IDEAS
  22. Powell, James L & Stock, James H & Stoker, Thomas M, 1989. "Semiparametric Estimation of Index Coefficients," Econometrica, Econometric Society, vol. 57(6), pages 1403-30, November.
  23. Cattaneo, Matias D. & Crump, Richard K. & Jansson, Michael, 2014. "Small Bandwidth Asymptotics For Density-Weighted Average Derivatives," Econometric Theory, Cambridge University Press, vol. 30(01), pages 176-200, February.
  24. Arun Chandrasekhar & Victor Chernozhukov & Francesca Molinari & Paul Schrimpf, 2012. "Inference for best linear approximations to set identified functions," CeMMAP working papers CWP43/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  25. Matias D. Cattaneo & Richard K. Crump & Michael Jansson, 2009. "Robust Data-Driven Inference for Density-Weighted Average Derivatives," CREATES Research Papers 2009-46, Department of Economics and Business Economics, Aarhus University.
  26. Coppejans, Mark & Sieg, Holger, 2005. "Kernel Estimation of Average Derivatives and Differences," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 211-225, April.
  27. Powell, James L. & Stoker, Thomas M., 1996. "Optimal bandwidth choice for density-weighted averages," Journal of Econometrics, Elsevier, vol. 75(2), pages 291-316, December.
  28. Pakes, Ariel & Pollard, David, 1989. "Simulation and the Asymptotics of Optimization Estimators," Econometrica, Econometric Society, vol. 57(5), pages 1027-57, September.
  29. Victor Chernozhukov & Han Hong & Elie Tamer, 2007. "Estimation and Confidence Regions for Parameter Sets in Econometric Models," Econometrica, Econometric Society, vol. 75(5), pages 1243-1284, 09.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:ifs:cemmap:03/14. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Emma Hyman)

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 references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.