IDEAS home Printed from https://ideas.repec.org/p/mia/wpaper/2015-01.html
   My bibliography  Save this paper

Single-Step Estimation of a Partially Linear Model

Author

Listed:
  • Daniel J. Henderson

    (Department of Economics, Finance and Legal Studies, University of Alabama)

  • Christopher F. Parmeter

    (Department of Economics, University of Miami)

Abstract

In this paper we propose an asymptotically equivalent single-step alternative to the two-step partially linear model estimator in Robinson (1988). The estimator not only has the potential to decrease computing time dramatically, it shows substantial finite sample gains in Monte Carlo simulations.

Suggested Citation

  • Daniel J. Henderson & Christopher F. Parmeter, 2015. "Single-Step Estimation of a Partially Linear Model," Working Papers 2015-01, University of Miami, Department of Economics.
    • Handle: RePEc:mia:wpaper:2015-01
    as

    Download full text from publisher

    File URL: http://bus.miami.edu/_assets/files/repec/WP2015-01.pdf
    File Function: First version, 2015
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Finan, Frederico & Sadoulet, Elisabeth & de Janvry, Alain, 2005. "Measuring the poverty reduction potential of land in rural Mexico," Journal of Development Economics, Elsevier, vol. 77(1), pages 27-51, June.
    2. Panayiota Lyssiotou & Panos Pashardes & Thanasis Stengos, 2002. "Age effects on consumer demand: an additive partially linear regression model," Canadian Journal of Economics, Canadian Economics Association, vol. 35(1), pages 153-165, February.
    3. Daniel L. Millimet & John A. List & Thanasis Stengos, 2003. "The Environmental Kuznets Curve: Real Progress or Misspecified Models?," The Review of Economics and Statistics, MIT Press, vol. 85(4), pages 1038-1047, November.
    4. Henderson,Daniel J. & Parmeter,Christopher F., 2015. "Applied Nonparametric Econometrics," Cambridge Books, Cambridge University Press, number 9780521279680, November.
    5. Richard Blundell & Frank Windmeijer, 2000. "Identifying demand for health resources using waiting times information," Health Economics, John Wiley & Sons, Ltd., vol. 9(6), pages 465-474, September.
    6. Banerjee, Abhijit V & Duflo, Esther, 2003. "Inequality and Growth: What Can the Data Say?," Journal of Economic Growth, Springer, vol. 8(3), pages 267-299, September.
    7. Martins-Filho, Carlos & Yao, Feng, 2012. "Kernel-based estimation of semiparametric regression in triangular systems," Economics Letters, Elsevier, vol. 115(1), pages 24-27.
    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. Yixiao Jiang, 2020. "A Hausman Test for Partially Linear Models with an Application to Implied Volatility Surface," JRFM, MDPI, vol. 13(11), pages 1-12, November.

    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 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.
    2. Qian, Junhui & Wang, Le, 2012. "Estimating semiparametric panel data models by marginal integration," Journal of Econometrics, Elsevier, vol. 167(2), pages 483-493.
    3. Das, Monica & Basu, Sudip R., 2023. "Inclusive bank based financial development in countries with special needs: A semiparametric analysis," Economic Analysis and Policy, Elsevier, vol. 80(C), pages 740-753.
    4. Almeida, Alexandre N. & Santos, Augusto S. & Halmenschlager, Vinícius & Gilio, Leandro & Diniz, Tiago B. & Ferreira, Alexandre A. S., 2016. "Flexible-fuel automobiles and CO2 emissions in Brazil: a semiparametric analysis using panel data," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235733, Agricultural and Applied Economics Association.
    5. Alexandra-Anca Purcel, 2020. "New insights into the environmental Kuznets curve hypothesis in developing and transition economies: a literature survey," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 22(4), pages 585-631, October.
    6. Delgado, Michael S. & Parmeter, Christopher F., 2014. "A simple estimator for partial linear regression with endogenous nonparametric variables," Economics Letters, Elsevier, vol. 124(1), pages 100-103.
    7. Grossmann, Volker, 2008. "Risky human capital investment, income distribution, and macroeconomic dynamics," Journal of Macroeconomics, Elsevier, vol. 30(1), pages 19-42, March.
    8. David H. Bernstein & Christopher F. Parmeter, 2017. "Returns to Scale in Electricity Generation: Revisited and Replicated," Working Papers 2017-08, University of Miami, Department of Economics.
    9. Almeida, Alexandre N. & Bravo-Ureta, Boris E., 2019. "Agricultural productivity, shadow wages and off-farm labor decisions in Nicaragua," Economic Systems, Elsevier, vol. 43(1), pages 99-110.
    10. Günther Rehme, 2007. "Education, Economic Growth and Measured Income Inequality," Economica, London School of Economics and Political Science, vol. 74(295), pages 493-514, August.
    11. Jun, Bogang & Hwang, Won-Sik, 2012. "Financial Hurdles for Human Capital Accumulation: Revisiting the Galor-Zeira Model," MPRA Paper 46317, University Library of Munich, Germany.
    12. Battisti, Michele & Gatto, Massimo Del & Parmeter, Christopher F., 2022. "Skill-biased technical change and labor market inefficiency," Journal of Economic Dynamics and Control, Elsevier, vol. 139(C).
    13. Benabou, Roland, 2005. "Inequality, Technology and the Social Contract," Handbook of Economic Growth, in: Philippe Aghion & Steven Durlauf (ed.), Handbook of Economic Growth, edition 1, volume 1, chapter 25, pages 1595-1638, Elsevier.
    14. Shinhye Chang & Rangan Gupta & Stephen M. Miller, 2018. "Causality Between Per Capita Real GDP and Income Inequality in the U.S.: Evidence from a Wavelet Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 135(1), pages 269-289, January.
    15. Verner, Dorte, 2005. "Poverty in rural and semi-urban Mexico during 1992-2002," Policy Research Working Paper Series 3576, The World Bank.
    16. Atems, Bebonchu, 2013. "The spatial dynamics of growth and inequality: Evidence using U.S. county-level data," Economics Letters, Elsevier, vol. 118(1), pages 19-22.
    17. Cristiano Perugini & Gaetano Martino, 2008. "Income Inequality Within European Regions: Determinants And Effects On Growth," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 54(3), pages 373-406, September.
    18. Charlotte Bartels & Simon Jäger & Natalie Obergruber, 2024. "Long-Term Effects of Equal Sharing: Evidence from Inheritance Rules for Land," The Economic Journal, Royal Economic Society, vol. 134(664), pages 3137-3172.
    19. Subal C. Kumbhakar & Christopher F. Parmeter & Valentin Zelenyuk, 2022. "Stochastic Frontier Analysis: Foundations and Advances I," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 8, pages 331-370, Springer.
    20. Dierk Herzer & Philipp Hühne & Peter Nunnenkamp, 2014. "FDI and Income Inequality—Evidence from Latin American Economies," Review of Development Economics, Wiley Blackwell, vol. 18(4), pages 778-793, November.

    More about this item

    Keywords

    Cross-validation; bandwidth; bias; Monte Carlo; Kernel Publication Status: Under Review;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

    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:mia:wpaper:2015-01. 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: Daniela Valdivia (email available below). General contact details of provider: https://edirc.repec.org/data/demiaus.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.