IDEAS home Printed from https://ideas.repec.org/a/taf/emetrv/v17y1998i3p227-273.html
   My bibliography  Save this article

Selection of regressors in econometrics: parametric and nonparametric methods selection of regressors in econometrics

Author

Listed:
  • Pascal Lavergne

Abstract

The present paper addresses the selection-of-regressors issue into a general discrimination framework. We show how this framework is useful in unifying various procedures for selecting regressors and helpful in understanding the different strategies underlying these procedures. We review selection of regressors in linear, nonlinear and nonparametric regression models. In each case we successively consider model selection criteria and hypothesis testing procedures.

Suggested Citation

  • Pascal Lavergne, 1998. "Selection of regressors in econometrics: parametric and nonparametric methods selection of regressors in econometrics," Econometric Reviews, Taylor & Francis Journals, vol. 17(3), pages 227-273.
    • Handle: RePEc:taf:emetrv:v:17:y:1998:i:3:p:227-273
    DOI: 10.1080/07474939808800415
    as

    Download full text from publisher

    File URL: http://www.tandfonline.com/doi/abs/10.1080/07474939808800415
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/07474939808800415?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

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

    References listed on IDEAS

    as
    1. Lavergne, Pascal, 2001. "An equality test across nonparametric regressions," Journal of Econometrics, Elsevier, vol. 103(1-2), pages 307-344, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Maslov, Alexander, 2010. "Функция «Производство-Потребление» Как Методологическое Обоснование Эффективности Региональной Господдержки (На Примере Юфо) [Function "production-consumption" as methodological substanti," MPRA Paper 42767, University Library of Munich, Germany.
    2. El Ghouch, Anouar & Genton, Marc G. & Bouezmarni , Taoufik, 2012. "Measuring the Discrepancy of a Parametric Model via Local Polynomial Smoothing," LIDAM Discussion Papers ISBA 2012001, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    3. Christophe Bontemps & Grayham E. Mizon, 2008. "Encompassing: Concepts and Implementation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(s1), pages 721-750, December.
    4. Anouar El Ghouch & Marc G. Genton & Taoufik Bouezmarni, 2013. "Measuring the Discrepancy of a Parametric Model via Local Polynomial Smoothing," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 40(3), pages 455-470, September.

    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. Gao, Jiti & King, Maxwell, 2003. "Estimation and model specification testing in nonparametric and semiparametric econometric models," MPRA Paper 11989, University Library of Munich, Germany, revised Feb 2006.
    2. Li, Qi & Hsiao, Cheng & Zinn, Joel, 2003. "Consistent specification tests for semiparametric/nonparametric models based on series estimation methods," Journal of Econometrics, Elsevier, vol. 112(2), pages 295-325, February.
    3. Scholz, Achim & Neumeyer, Natalie & Munk, Axel, 2004. "Nonparametric Analysis of Covariance : the Case of Inhomogeneous and Heteroscedastic Noise," Technical Reports 2004,28, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    4. Liangjun Su & Xi Qu, 2017. "Specification Test for Spatial Autoregressive Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(4), pages 572-584, October.
    5. Christopher F. Parmeter & Jeffrey S. Racine, 2018. "Nonparametric Estimation and Inference for Panel Data Models," Department of Economics Working Papers 2018-02, McMaster University.
    6. Lavergne, Pascal & Maistre, Samuel & Patilea, Valentin, 2014. "A Significance Test for Covariates in Nonparametric Regression," TSE Working Papers 14-502, Toulouse School of Economics (TSE).
    7. Sokbae Lee & Yoon-Jae Whang, 2009. "Nonparametric Tests of Conditional Treatment Effects," Cowles Foundation Discussion Papers 1740, Cowles Foundation for Research in Economics, Yale University.
    8. Lavergne, Pascal & Patilea, Valentin, 2008. "Breaking the curse of dimensionality in nonparametric testing," Journal of Econometrics, Elsevier, vol. 143(1), pages 103-122, March.
    9. Sun, Yiguo, 2006. "A Consistent Nonparametric Equality Test Of Conditional Quantile Functions," Econometric Theory, Cambridge University Press, vol. 22(4), pages 614-632, August.
    10. Srihera, Ramidha & Stute, Winfried, 2010. "Nonparametric comparison of regression functions," Journal of Multivariate Analysis, Elsevier, vol. 101(9), pages 2039-2059, October.
    11. Lapenta, Elia & Lavergne, Pascal, 2022. "Encompassing Tests for Nonparametric Regressions," TSE Working Papers 22-1332, Toulouse School of Economics (TSE).
    12. Gao, Jiti, 2007. "Nonlinear time series: semiparametric and nonparametric methods," MPRA Paper 39563, University Library of Munich, Germany, revised 01 Sep 2007.
    13. Wenceslao González-Manteiga & Rosa Crujeiras, 2013. "An updated review of Goodness-of-Fit tests for regression models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(3), pages 361-411, September.
    14. Liangjun Su & Stefan Hoderlein & Halbert White, 2013. "Testing Monotonicity in Unobservables with Panel Data," Boston College Working Papers in Economics 892, Boston College Department of Economics, revised 01 Feb 2016.
    15. Lyubchich, Vyacheslav & Gel, Yulia R., 2016. "A local factor nonparametric test for trend synchronism in multiple time series," Journal of Multivariate Analysis, Elsevier, vol. 150(C), pages 91-104.
    16. Sianesi, Barbara, 2017. "Evidence of randomisation bias in a large-scale social experiment: The case of ERA," Journal of Econometrics, Elsevier, vol. 198(1), pages 41-64.
    17. Ian Christensen & Fuchun Li, 2013. "A Semiparametric Early Warning Model of Financial Stress Events," Staff Working Papers 13-13, Bank of Canada.
    18. Elia Lapenta & Pascal Lavergne, 2022. "Encompassing Tests for Nonparametric Regressions," Papers 2203.06685, arXiv.org, revised Oct 2023.
    19. Khismatullina, Marina & Vogt, Michael, 2023. "Nonparametric comparison of epidemic time trends: The case of COVID-19," Journal of Econometrics, Elsevier, vol. 232(1), pages 87-108.
    20. Áureo de Paula & Xun Tang, 2020. "Testable implications of multiple equilibria in discrete games with correlated types," CeMMAP working papers CWP56/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    More about this item

    Keywords

    Selection of regressors; Discrimination; JEL Classification: Primary C52: Secondary C20;
    All these keywords.

    JEL classification:

    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General

    Statistics

    Access and download statistics

    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:taf:emetrv:v:17:y:1998:i:3:p:227-273. 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: the person in charge (email available below). General contact details of provider: http://www.tandfonline.com/LECR20 .

    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.