IDEAS home Printed from https://ideas.repec.org/h/eme/aecozz/s0731-9053(2009)0000025006.html

Semiparametric estimation of fixed-effects panel data varying coefficient models

In: Nonparametric Econometric Methods

Author

Listed:
  • Yiguo Sun
  • Raymond J. Carroll
  • Dingding Li

Abstract

We consider the problem of estimating a varying coefficient panel data model with fixed-effects (FE) using a local linear regression approach. Unlike first-differenced estimator, our proposed estimator removes FE using kernel-based weights. This results a one-step estimator without using the backfitting technique. The computed estimator is shown to be asymptotically normally distributed. A modified least-squared cross-validatory method is used to select the optimal bandwidth automatically. Moreover, we propose a test statistic for testing the null hypothesis of a random-effects varying coefficient panel data model against an FE one. Monte Carlo simulations show that our proposed estimator and test statistic have satisfactory finite sample performance.

Suggested Citation

  • Yiguo Sun & Raymond J. Carroll & Dingding Li, 2009. "Semiparametric estimation of fixed-effects panel data varying coefficient models," Advances in Econometrics, in: Nonparametric Econometric Methods, pages 101-129, Emerald Group Publishing Limited.
    • Handle: RePEc:eme:aecozz:s0731-9053(2009)0000025006
    DOI: 10.1108/S0731-9053(2009)0000025006
    as

    Download full text from publisher

    File URL: https://www.emerald.com/insight/content/doi/10.1108/S0731-9053(2009)0000025006/full/html?utm_source=repec&utm_medium=feed&utm_campaign=repec
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://www.emerald.com/insight/content/doi/10.1108/S0731-9053(2009)0000025006/full/pdf?utm_source=repec&utm_medium=feed&utm_campaign=repec
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://www.emerald.com/insight/content/doi/10.1108/S0731-9053(2009)0000025006/full/epub?utm_source=repec&utm_medium=feed&utm_campaign=repec&title=10.1108/S0731-9053(2009)0000025006
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://libkey.io/10.1108/S0731-9053(2009)0000025006?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

    for a different version of it.

    Citations

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


    Cited by:

    1. Tan, Ruipeng & Zhang, Zixuan & Du, Kerui & Lin, Boqiang, 2025. "Energy rebound effect in China: Measurement based on a variable coefficient production function," Ecological Economics, Elsevier, vol. 230(C).
    2. Lamia Beldi & Tarek Ghazouani, 2025. "Nonparametric analysis of the relationship between income inequality and energy consumption in African countries," Natural Resources Forum, Blackwell Publishing, vol. 49(2), pages 1401-1423, May.
    3. Taining Wang & Feng Yao & Jun Cai, 2026. "Nonparametric Estimation of Smooth Coefficients in Fixed-Effect Panel Data Models," Working Papers 26-03, Department of Economics, West Virginia University.
    4. Li, Shuangshuang & Chen, Jianbao, 2026. "Estimation and testing for fixed effects partially linear nonparametric panel regression model with separable spatially and serially correlated error structure," Journal of Multivariate Analysis, Elsevier, vol. 212(C).
    5. Guliyev, Hasraddin, 2025. "Heterogeneous panel data model with sharp and smooth changes: Testing green growth hypothesis in G7 countries," Innovation and Green Development, Elsevier, vol. 4(3).
    6. Zhang, Shangfeng & Zhang, Chaojie & Su, Zitian & Zhu, Mengyue & Ren, Huiru, 2023. "New structural economic growth model and labor income share," Journal of Business Research, Elsevier, vol. 160(C).
    7. Zhao Wang & Yuanlu Suo & Taining Wang & Subal C. Kumbhakar, 2025. "Are operationally efficient firms greener?," Empirical Economics, Springer, vol. 69(5), pages 2627-2669, November.
    8. Yuelin Zheng & Mingquan Wang & Xiaohua Ma & Chunhua Zhu & Qibing Gao, 2024. "The Dynamic Relationship Between Industrial Structure Upgrading and Carbon Emissions: New Evidence from Chinese Provincial Data," Sustainability, MDPI, vol. 16(22), pages 1-19, November.
    9. G. Arghyrou, Michael & Gadea, Maria-Dolores & Kontonikas, Alexandros, 2024. "Private bank deposits and macro/fiscal risk in the euro-area," Journal of International Money and Finance, Elsevier, vol. 140(C).
    10. Sun, Xianming & Xiao, Shiyi & Ren, Xiaohang & Xu, Bing, 2023. "Time-varying impact of information and communication technology on carbon emissions," Energy Economics, Elsevier, vol. 118(C).
    11. Bampinas, Georgios & Mavropoulos, Georgios, 2024. "Asymmetric effects between economic development and fertility: What do 140 years of data tell us?," The Journal of Economic Asymmetries, Elsevier, vol. 30(C).
    12. Nicholas Marinucci & Kris Ivanovski, 2023. "Does Inequality Affect Climate Change? A Regional and Sectoral Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 166(3), pages 705-729, April.
    13. Cruz, Sérgio, 2025. "Income elasticity of electricity demand in the context of Portugal’s energy transition," Utilities Policy, Elsevier, vol. 97(C).
    14. Ren, Xiaohang & An, Yaning & He, Feng & Goodell, John W., 2024. "Do FDI inflows bring both capital and CO2 emissions? Evidence from non-parametric modelling for the G7 countries," International Review of Economics & Finance, Elsevier, vol. 95(C).
    15. Bai, Yu & Marcellino, Massimiliano & Kapetanios, George, 2026. "Mean group instrumental variable estimation of time-varying large heterogeneous panels with endogenous regressors," Econometrics and Statistics, Elsevier, vol. 37(C), pages 26-41.
    16. Suigen Yang & Xiujuan Yang & Xuefei Wang, 2024. "Estimation and Simultaneous Confidence Bands for Fixed-Effects Panel Data Partially Linear Models," Mathematics, MDPI, vol. 12(23), pages 1-18, November.
    17. Ghazouani, Tarek, 2024. "Investigating the dynamic link between globalization and carbon emissions in BRICS nations: Insights from a non-parametric perspective," International Economics, Elsevier, vol. 180(C).
    18. Mohsen Bakhshi Moghaddam & Saeed Moshiri, 2025. "Oil-macroeconomy relationship over time: Does oil still matter?," Empirical Economics, Springer, vol. 69(6), pages 3205-3225, December.
    19. Taining Wang & Feng Yao & Subal C. Kumbhakar, 2024. "A flexible stochastic production frontier model with panel data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(4), pages 564-588, June.

    More about this item

    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:eme:aecozz:s0731-9053(2009)0000025006. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Emerald Support (email available below). General contact details of provider: .

    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.