IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v104y2009i2p53-56.html
   My bibliography  Save this article

Global identification of the semiparametric Box-Cox model

Author

Listed:
  • Komunjer, Ivana

Abstract

We show identifiability of the Box-Cox model under restrictions that do not require the disturbance U to be independent or mean independent of the explanatory variable X. Our restrictions are on the support of the distribution of U given X.

Suggested Citation

  • Komunjer, Ivana, 2009. "Global identification of the semiparametric Box-Cox model," Economics Letters, Elsevier, vol. 104(2), pages 53-56, August.
    • Handle: RePEc:eee:ecolet:v:104:y:2009:i:2:p:53-56
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165-1765(09)00114-1
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Roehrig, Charles S, 1988. "Conditions for Identification in Nonparametric and Parametic Models," Econometrica, Econometric Society, vol. 56(2), pages 433-447, March.
    2. Andrews,Donald W. K. & Stock,James H. (ed.), 2005. "Identification and Inference for Econometric Models," Cambridge Books, Cambridge University Press, number 9780521844413.
    3. N.E. Savin & Allan H. Würtz, 2002. "Testing the Semiparametric Box-Cox Model with Bootstrap," CAM Working Papers 2002-08, University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics.
    4. Rothenberg, Thomas J, 1971. "Identification in Parametric Models," Econometrica, Econometric Society, vol. 39(3), pages 577-591, May.
    5. Komunjer, Ivana, 2007. "Global Identification In Nonlinear Semiparametric Models," University of California at San Diego, Economics Working Paper Series qt8dk0n386, Department of Economics, UC San Diego.
    6. Powell, James L., 1996. "Rescaled methods-of-moments estimation for the Box-Cox regression model," Economics Letters, Elsevier, vol. 51(3), pages 259-265, June.
    7. Khazzoom, J. Daniel, 1989. "A note on the application of the nonlinear two-stage least-squares estimator to a Box-Cox-transformed model," Journal of Econometrics, Elsevier, vol. 42(3), pages 377-379, November.
    8. Foster A. M. & Tian L. & Wei L. J., 2001. "Estimation for the Box-Cox Transformation Model Without Assuming Parametric Error Distribution," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1097-1101, September.
    9. Amemiya, Takeshi & Powell, James L., 1981. "A comparison of the Box-Cox maximum likelihood estimator and the non-linear two-stage least squares estimator," Journal of Econometrics, Elsevier, vol. 17(3), pages 351-381, December.
    Full references (including those not matched with items on IDEAS)

    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.
    1. Daniel Becker & Alois Kneip & Valentin Patilea, 2021. "Semiparametric inference for partially linear regressions with Box-Cox transformation," Papers 2106.10723, arXiv.org.
    2. Savin, N.E. & Wurtz, Allan H., 2001. "Semiparametric Estimation of the Box-Cox Model Preliminary and Incomplete," Working Papers 2001-01, University of Iowa, Department of Economics.
    3. Kazumitsu Nawata, 2013. "A new estimator of the Box-Cox transformation model using moment conditions," Economics Bulletin, AccessEcon, vol. 33(3), pages 2287-2297.
    4. Tito Belchior Silva Moreira & Benjamin Miranda Tabak & Mario Jorge Mendonça & Adolfo Sachsida, 2016. "An Evaluation of the Non-Neutrality of Money," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-20, March.
    5. Andrew Chesher, 2004. "Identification of sensitivity to variation in endogenous variables," CeMMAP working papers 10/04, Institute for Fiscal Studies.
    6. Andrew Chesher & Adam Rosen, 2018. "Generalized instrumental variable models, methods, and applications," CeMMAP working papers CWP43/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    7. Hubner, Stefan, 2016. "Topics in nonparametric identification and estimation," Other publications TiSEM 08fce56b-3193-46e0-871b-0, Tilburg University, School of Economics and Management.
    8. Horowitz, Joel L., 2004. "Semiparametric models," Papers 2004,17, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
    9. Chesher, Andrew, 2007. "Instrumental values," Journal of Econometrics, Elsevier, vol. 139(1), pages 15-34, July.
    10. Arthur Lewbel, 2019. "The Identification Zoo: Meanings of Identification in Econometrics," Journal of Economic Literature, American Economic Association, vol. 57(4), pages 835-903, December.
    11. Timo Dimitriadis & Tobias Fissler & Johanna Ziegel, 2020. "The Efficiency Gap," Papers 2010.14146, arXiv.org, revised Sep 2022.
    12. Batarce, Marco & Ivaldi, Marc, 2014. "Urban travel demand model with endogenous congestion," Transportation Research Part A: Policy and Practice, Elsevier, vol. 59(C), pages 331-345.
    13. Timo Dimitriadis & Tobias Fissler & Johanna Ziegel, 2022. "Characterizing M-estimators," Papers 2208.08108, arXiv.org.
    14. Godfrey, L.G. & Santos Silva, J.M.C., 2007. "A note on variable addition tests for linear and log-linear models," Economics Letters, Elsevier, vol. 95(3), pages 422-427, June.
    15. Andrew Chesher, 2007. "Endogeneity and discrete outcomes," CeMMAP working papers CWP05/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    16. Powell, James L., 1996. "Rescaled methods-of-moments estimation for the Box-Cox regression model," Economics Letters, Elsevier, vol. 51(3), pages 259-265, June.
    17. Jean-Jacques Forneron, 2019. "Detecting Identification Failure in Moment Condition Models," Papers 1907.13093, arXiv.org, revised Oct 2023.
    18. Vieira, Flávio & MacDonald, Ronald & Damasceno, Aderbal, 2012. "The role of institutions in cross-section income and panel data growth models: A deeper investigation on the weakness and proliferation of instruments," Journal of Comparative Economics, Elsevier, vol. 40(1), pages 127-140.
    19. Tansel, Aysit & Keskin, Halil Ibrahim, 2017. "Education Effects on Days Hospitalized and Days out of Work by Gender: Evidence from Turkey," IZA Discussion Papers 11210, Institute of Labor Economics (IZA).
    20. Robert MacCulloch & Silvia Pezzini, 2010. "The Roles of Freedom, Growth, and Religion in the Taste for Revolution," Journal of Law and Economics, University of Chicago Press, vol. 53(2), pages 329-358, May.

    Corrections

    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:eee:ecolet:v:104:y:2009:i:2:p:53-56. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ecolet .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.