IDEAS home Printed from https://ideas.repec.org/a/spr/sankha/v85y2023i1d10.1007_s13171-020-00239-8.html
   My bibliography  Save this article

Asymptotic Inferences in a Doubly-Semi-Parametric Linear Longitudinal Mixed Model

Author

Listed:
  • Brajendra C. Sutradhar

    (Memorial University)

  • R. Prabhakar Rao

    (Sri Sathya Sai Institute of Higher Learning)

Abstract

Warriyar and Sutradhar (Brazilian J. Probab. Stat., 28, 561–586, 2014) studied a semi-parametric linear model in a longitudinal setup with Gaussian errors, where the main regression parameters were estimated using an efficient GQL (generalized quasi-likelihood) estimation approach, and the efficiency properties of the estimators were examined through a simulation study. In this paper we provide a generalization of their linear semi-parametric regression model to a wider setup where the error distributions are relaxed and errors are assumed to follow a four-moments based semi-parametric structure leading to a doubly semi-parametric model. On top of regression parameters and nonparametric function estimation, this doubly semi-parametric nature of the model makes the four-moments based variance and correlation parameters estimation quite challenging. We resolve this computational issue analytically by developing exact formulas for all necessary higher order moments. As the longitudinal studies involve large number of independent individuals providing repeated responses, we study the asymptotic properties of the estimators and make sure that the estimators including the estimator of nonparametric function are consistent.

Suggested Citation

  • Brajendra C. Sutradhar & R. Prabhakar Rao, 2023. "Asymptotic Inferences in a Doubly-Semi-Parametric Linear Longitudinal Mixed Model," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 214-247, February.
    • Handle: RePEc:spr:sankha:v:85:y:2023:i:1:d:10.1007_s13171-020-00239-8
    DOI: 10.1007/s13171-020-00239-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13171-020-00239-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s13171-020-00239-8?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. Bun, Maurice J.G. & Carree, Martin A., 2005. "Bias-Corrected Estimation in Dynamic Panel Data Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 200-210, April.
    2. Pagan,Adrian & Ullah,Aman, 1999. "Nonparametric Econometrics," Cambridge Books, Cambridge University Press, number 9780521355643, October.
    3. Allen Fleishman, 1978. "A method for simulating non-normal distributions," Psychometrika, Springer;The Psychometric Society, vol. 43(4), pages 521-532, December.
    4. Naisyin Wang & Raymond J. Carroll & Xihong Lin, 2005. "Efficient Semiparametric Marginal Estimation for Longitudinal/Clustered Data," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 147-157, March.
    5. Sneddon, Gary & Sutradhar, Brajendra C., 2004. "On semiparametric familial-longitudinal models," Statistics & Probability Letters, Elsevier, vol. 69(3), pages 369-379, September.
    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. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
    2. repec:hal:spmain:info:hdl:2441/dambferfb7dfprc9m052g20qh is not listed on IDEAS
    3. repec:spo:wpmain:info:hdl:2441/7182 is not listed on IDEAS
    4. Sebastian Weber, 2009. "European Financial Market Integration: A Closer Look at Government Bonds in Eurozone Countries," Working Paper / FINESS 1.1b, DIW Berlin, German Institute for Economic Research.
    5. Harding, Don & Pagan, Adrian, 2011. "An Econometric Analysis of Some Models for Constructed Binary Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 86-95.
    6. Doole, Graeme J. & Romera, Alvaro J. & Leslie, Jennifer E. & Chapman, David F. & Pinxterhuis, Ina (J.B.). & Kemp, Peter D., 2021. "Economic assessment of plantain (Plantago lanceolata) uptake in the New Zealand dairy sector," Agricultural Systems, Elsevier, vol. 187(C).
    7. Menzel, Konrad, 2014. "Consistent estimation with many moment inequalities," Journal of Econometrics, Elsevier, vol. 182(2), pages 329-350.
    8. Xueying Zheng & Wing Fung & Zhongyi Zhu, 2013. "Robust estimation in joint mean–covariance regression model for longitudinal data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 65(4), pages 617-638, August.
    9. Ural Marchand, Beyza, 2012. "Tariff pass-through and the distributional effects of trade liberalization," Journal of Development Economics, Elsevier, vol. 99(2), pages 265-281.
    10. Ichimura, Hidehiko & Todd, Petra E., 2007. "Implementing Nonparametric and Semiparametric Estimators," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 74, Elsevier.
    11. Daniel Buncic, 2012. "Understanding forecast failure of ESTAR models of real exchange rates," Empirical Economics, Springer, vol. 43(1), pages 399-426, August.
    12. Dauda Mohammed, 2014. "Causality Test Of Business Risk And Capital Structure In A Panel Data Of Nigerian Listed Firms," Accounting & Taxation, The Institute for Business and Finance Research, vol. 6(2), pages 85-99.
    13. Fosgerau, Mogens & Bierlaire, Michel, 2007. "A practical test for the choice of mixing distribution in discrete choice models," Transportation Research Part B: Methodological, Elsevier, vol. 41(7), pages 784-794, August.
    14. In Choi & Sanghyun Jung, 2021. "Cross-sectional quasi-maximum likelihood and bias-corrected pooled least squares estimators for short dynamic panels," Empirical Economics, Springer, vol. 60(1), pages 177-203, January.
    15. David Fairris & Gurleen Popli & Eduardo Zepeda, 2008. "Minimum Wages and the Wage Structure in Mexico," Review of Social Economy, Taylor & Francis Journals, vol. 66(2), pages 181-208.
    16. Emna Trabelsi, 2016. "Transparency on inflation of OECD countries? An Application of LSDVC Estimator on a dynamic Panel Model," Economics Bulletin, AccessEcon, vol. 36(2), pages 1095-1126.
    17. Javier Parada Gómez Urquiza & Alejandro López-Feldman, 2013. "Poverty dynamics in rural Mexico: What does the future hold?," Ensayos Revista de Economia, Universidad Autonoma de Nuevo Leon, Facultad de Economia, vol. 0(2), pages 55-74, November.
    18. Mohamed CHIKHI & Claude DIEBOLT, 2022. "Testing the weak form efficiency of the French ETF market with the LSTAR-ANLSTGARCH approach using a semiparametric estimation," Eastern Journal of European Studies, Centre for European Studies, Alexandru Ioan Cuza University, vol. 13, pages 228-253, June.
    19. Joseph G. Altonji & Rosa L. Matzkin, 2001. "Panel Data Estimators for Nonseparable Models with Endogenous Regressors," NBER Technical Working Papers 0267, National Bureau of Economic Research, Inc.
    20. Inanoglu, Hulusi & Jacobs, Michael, Jr. & Liu, Junrong & Sickles, Robin, 2015. "Analyzing Bank Efficiency: Are "Too-Big-to-Fail" Banks Efficient?," Working Papers 15-016, Rice University, Department of Economics.
    21. Joel L. Horowitz, 2012. "Nonparametric additive models," CeMMAP working papers CWP20/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    22. Robert Breunig & Alison Stegman, 2005. "Testing For Regime Switching In Singaporean Business Cycles," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 50(01), pages 25-34.

    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:spr:sankha:v:85:y:2023:i:1:d:10.1007_s13171-020-00239-8. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.