IDEAS home Printed from https://ideas.repec.org/p/mcm/deptwp/2012-07.html
   My bibliography  Save this paper

Additive Regression Splines With Irrelevant Categorical and Continuous Regressors

Author

Listed:
  • Shujie Ma
  • Jeffrey S. Racine

Abstract

We consider the problem of estimating a relationship using semiparametric additive regression splines when there exist both continuous and categorical regressors, some of which are irrelevant but this is not known a priori. We show that choosing the spline degree, number of subintervals, and bandwidths via cross-validation can automatically remove irrelevant regressors, thereby delivering 'automatic dimension reduction without the need for pre-testing. Theoretical underpinnings are provided, finite-sample performance is studied, and an illustrative application demonstrates the efficacy of the proposed approach in finite-sample settings. An R package implementing the methods is available from the Comprehensive R Archive Network (Racine and Nie (2011)).

Suggested Citation

  • Shujie Ma & Jeffrey S. Racine, 2012. "Additive Regression Splines With Irrelevant Categorical and Continuous Regressors," Department of Economics Working Papers 2012-07, McMaster University.
    • Handle: RePEc:mcm:deptwp:2012-07
    as

    Download full text from publisher

    File URL: http://socserv.mcmaster.ca/econ/rsrch/papers/archive/2012-07.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. QI Li & Desheng Ouyang & Jeffrey S. Racine, 2013. "Categorical semiparametric varying‐coefficient models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(4), pages 551-579, June.
    2. Peter Hall & Qi Li & Jeffrey S. Racine, 2007. "Nonparametric Estimation of Regression Functions in the Presence of Irrelevant Regressors," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 784-789, November.
    3. Raymond J. Carroll & Arnab Maity & Enno Mammen & Kyusang Yu, 2009. "Nonparametric additive regression for repeatedly measured data," Biometrika, Biometrika Trust, vol. 96(2), pages 383-398.
    4. Shujie Ma & Jeffrey S. Racine & Lijian Yang, 2015. "Spline Regression in the Presence of Categorical Predictors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(5), pages 705-717, August.
    5. Fan, Jianqing & Jiang, Jiancheng, 2005. "Nonparametric Inferences for Additive Models," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 890-907, September.
    6. Simon N. Wood, 2004. "Stable and Efficient Multiple Smoothing Parameter Estimation for Generalized Additive Models," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 673-686, January.
    7. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
    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. Paudel, Krishna P. & Lin, C.-Y. Cynthia & Pandit, Mahesh, 2014. "Environmental Kuznets Curve for Water Quality Parameters at Global Level," 2014 Annual Meeting, February 1-4, 2014, Dallas, Texas 162618, Southern Agricultural Economics Association.
    2. Jean-Thomas Bernard & Michael Gavin & Lynda Khalaf & Marcel Voia, 2015. "Environmental Kuznets Curve: Tipping Points, Uncertainty and Weak Identification," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 60(2), pages 285-315, February.
    3. Pandit, Mahesh & Paudel, Krishna P. & Williams, Deborah, 2014. "Effect of Remittance on Intensity of Agricultural Technology Adoption in Nepal," 2014 Annual Meeting, February 1-4, 2014, Dallas, Texas 162692, Southern Agricultural Economics Association.
    4. Pang Du & Christopher F. Parmeter & Jeffrey S. Racine, 2012. "Nonparametric Kernel Regression with Multiple Predictors and Multiple Shape Constraints," Department of Economics Working Papers 2012-08, McMaster University.
    5. Ferris, J. Stephen & Voia, Marcel C., 2015. "The effect of federal government size on private economic performance in Canada: 1870–2011," Economic Modelling, Elsevier, vol. 49(C), pages 172-185.
    6. Xibin Zhang & Maxwell L. King & Han Lin Shang, 2016. "Bayesian Bandwidth Selection for a Nonparametric Regression Model with Mixed Types of Regressors," Econometrics, MDPI, vol. 4(2), pages 1-27, April.
    7. J. Stephen Ferris & Marcel-Cristian Voia, 2014. "Does Aggregate Government Size Effect Private Economic Performance in Canada?," Carleton Economic Papers 14-13, Carleton University, Department of Economics.
    8. Nicholas M. Kiefer & Jeffrey S. Racine, 2017. "The smooth colonel and the reverend find common ground," Econometric Reviews, Taylor & Francis Journals, vol. 36(1-3), pages 241-256, March.
    9. Lien, Donald & Hu, Yue & Liu, Long, 2017. "A note on using ratio variables in regression analysis," Economics Letters, Elsevier, vol. 150(C), pages 114-117.
    10. Geraldine Henningsen & Arne Henningsen & Christian Henning, 2015. "Transaction costs and social networks in productivity measurement," Empirical Economics, Springer, vol. 48(1), pages 493-515, February.

    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. Michael S. Delgado & Daniel J. Henderson & Christopher F. Parmeter, 2014. "Does Education Matter for Economic Growth?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(3), pages 334-359, June.
    2. Nolwenn Roudaut & Anne Vanhems, 2012. "Explaining firms efficiency in the Ivorian manufacturing sector: a robust nonparametric approach," Journal of Productivity Analysis, Springer, vol. 37(2), pages 155-169, April.
    3. Arribas Ivan & Perez Francisco & Tortosa-Ausina Emili, 2010. "The Determinants of International Financial Integration Revisited: The Role of Networks and Geographic Neutrality," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(1), pages 1-55, December.
    4. James Bugden & Robert Waschik & Iain Fraser & Jeffrey S. Racine, 2016. "Parametric and non-parametric analysis of tax changes," Global Business and Economics Review, Inderscience Enterprises Ltd, vol. 18(5), pages 533-549.
    5. Li, Degui & Linton, Oliver & Lu, Zudi, 2015. "A flexible semiparametric forecasting model for time series," Journal of Econometrics, Elsevier, vol. 187(1), pages 345-357.
    6. Hsiao, Cheng & Li, Qi & Racine, Jeffrey S., 2007. "A consistent model specification test with mixed discrete and continuous data," Journal of Econometrics, Elsevier, vol. 140(2), pages 802-826, October.
    7. Nicholas M. Kiefer & Jeffrey S. Racine, 2017. "The smooth colonel and the reverend find common ground," Econometric Reviews, Taylor & Francis Journals, vol. 36(1-3), pages 241-256, March.
    8. Daniel J. Henderson & Léopold Simar & Le Wang, 2017. "The three s of public schools: irrelevant inputs, insufficient resources and inefficiency," Applied Economics, Taylor & Francis Journals, vol. 49(12), pages 1164-1184, March.
    9. Marijn Verschelde & Marijke D’Haese & Glenn Rayp & Ellen Vandamme, 2013. "Challenging Small-Scale Farming: A Non-Parametric Analysis of the (Inverse) Relationship Between Farm Productivity and Farm Size in Burundi," Journal of Agricultural Economics, Wiley Blackwell, vol. 64(2), pages 319-342, June.
    10. Jesús Peiró-Palomino, 2016. "Social Capital and Economic Growth in Europe: Nonlinear Trends and Heterogeneous Regional Effects," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(5), pages 717-751, October.
    11. Mariam Camarero & Jesús Peiró-Palomino & Cecilio Tamarit, 2017. "External imbalances and growth," Working Papers 2017/02, Economics Department, Universitat Jaume I, Castellón (Spain).
    12. Henderson, Daniel J. & Papageorgiou, Chris & Parmeter, Christopher F., 2013. "Who benefits from financial development? New methods, new evidence," European Economic Review, Elsevier, vol. 63(C), pages 47-67.
    13. Christopher F. Parmeter & Jeffrey S. Racine, 2018. "Nonparametric Estimation and Inference for Panel Data Models," Department of Economics Working Papers 2018-02, McMaster University.
    14. Daniel J. Henderson, 2009. "A Non‐parametric Examination of Capital–Skill Complementarity," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(4), pages 519-538, August.
    15. Jean Pierre Huiban & Camilla Mastromarco & Antonio Musolesi & Michel Simioni, 2016. "The impact of pollution abatement investments on production technology: new insights from frontier analysis," SEEDS Working Papers 0716, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Jul 2016.
    16. Michael S. Delgado & Nadine McCloud, 2017. "Foreign direct investment and the domestic capital stock: the good–bad role of higher institutional quality," Empirical Economics, Springer, vol. 53(4), pages 1587-1637, December.
    17. Li, Degui & Simar, Léopold & Zelenyuk, Valentin, 2016. "Generalized nonparametric smoothing with mixed discrete and continuous data," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 424-444.
    18. Abhijit Sharma & Alastair Bailey & Iain Fraser, 2011. "Technology Adoption and Pest Control Strategies Among UK Cereal Farmers: Evidence from Parametric and Nonparametric Count Data Models," Journal of Agricultural Economics, Wiley Blackwell, vol. 62(1), pages 73-92, February.
    19. Tingting Cheng & Jiti Gao & Xibin Zhang, 2019. "Nonparametric localized bandwidth selection for Kernel density estimation," Econometric Reviews, Taylor & Francis Journals, vol. 38(7), pages 733-762, August.
    20. Jeffrey S. Racine, 2016. "A Correction to "Generalized Nonparametric Smoothing with Mixed Discrete and Continuous Data" by Li, Simar & Zelenyuk (2014, CSDA)," Department of Economics Working Papers 2016-01, McMaster University.

    More about this item

    Keywords

    B-spline; discrete; kernel;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:mcm:deptwp:2012-07. 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: https://edirc.repec.org/data/demcmca.html .

    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.