IDEAS home Printed from https://ideas.repec.org/a/spr/sankhb/v78y2016i1d10.1007_s13571-015-0106-2.html
   My bibliography  Save this article

Inferences in Longitudinal Count Data Models with Measurement Errors in Time Dependent Covariates

Author

Listed:
  • Brajendra C. Sutradhar

    (Memorial University)

  • R. Prabhakar Rao

    (Sri Sathya Sai Institute of Higher Learning)

Abstract

Unlike in the independent setup, the measurement error analysis in longitudinal setup especially for discrete responses is not adequately addressed in the literature. In linear longitudinal setup, recently Fan, Sutradhar, and Rao (Sankhya B, 74, 126-148 2012) have introduced a bias corrected generalized quasi-likelihood (BCGQL) approach for the estimation of the regression effects after accommodating both measurement errors in time dependent covariates and correlations of the repeated responses. In longitudinal setup for repeated count data, a similar BCGQL estimating equation for the regression effects is provided by Sutradhar (2013) under the assumption that longitudinal correlation index parameter and measurement error variances are known. In this paper, we offer three main contributions. First, because the BCGQL estimation approach for discrete longitudinal data is complex and less familiar, we provide a complete derivation for this BCGQL estimating equation under the longitudinal count data model subject to measurement errors in time dependent covariates. Second, because the longitudinal correlation index parameter and measurement error variances involved in the model are unknown in practice, and because the main regression parameters can not be estimated without knowing them, we estimate these nuisance parameters consistently by solving appropriate unbiased estimating equations for these parameters. Next, the basic asymptotic properties of the estimators of main regression parameters are indicated.

Suggested Citation

  • Brajendra C. Sutradhar & R. Prabhakar Rao, 2016. "Inferences in Longitudinal Count Data Models with Measurement Errors in Time Dependent Covariates," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 78(1), pages 39-65, May.
    • Handle: RePEc:spr:sankhb:v:78:y:2016:i:1:d:10.1007_s13571-015-0106-2
    DOI: 10.1007/s13571-015-0106-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13571-015-0106-2
    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/s13571-015-0106-2?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. Wooldridge, Jeffrey M., 1999. "Distribution-free estimation of some nonlinear panel data models," Journal of Econometrics, Elsevier, vol. 90(1), pages 77-97, May.
    2. Wansbeek, Tom, 2001. "GMM estimation in panel data models with measurement error," Journal of Econometrics, Elsevier, vol. 104(2), pages 259-268, September.
    3. Taslim S. Mallick & Brajendra C. Sutradhar, 2008. "GQL Versus Conditional GQL Inferences for Non‐Stationary Time Series of Counts with Overdispersion," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(2), pages 402-420, March.
    4. Montalvo, Jose G, 1997. "GMM Estimation of Count-Panel-Data Models with Fixed Effects and Predetermined Instruments," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(1), pages 82-89, January.
    5. Staudenmayer, John & Buonaccorsi, John P., 2005. "Measurement Error in Linear Autoregressive Models," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 841-852, 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. Brajendra C. Sutradhar & Vandna Jowaheer & R. Prabhakar Rao, 2016. "Semi-Parametric Models for Negative Binomial Panel Data," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 78(2), pages 269-303, August.
    2. Biørn, Erik & Han, Xuehui, 2012. "Panel Data Dynamics and Measurement Errors: GMM Bias, IV Validity and Model Fit – A Monte Carlo Study," Memorandum 27/2012, Oslo University, Department of Economics.
    3. Frank Windmeijer, 2006. "GMM for panel count data models," Bristol Economics Discussion Papers 06/591, School of Economics, University of Bristol, UK.
    4. Biørn, Erik, 2012. "The Measurement Error Problem in Dynamic Panel Data Analysis: Modeling and GMM Estimation," Memorandum 02/2012, Oslo University, Department of Economics.
    5. Nan Zheng & Brajendra C. Sutradhar, 2018. "Inferences in semi-parametric dynamic mixed models for longitudinal count data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 70(1), pages 215-247, February.
    6. Erik Biørn, 2015. "Panel data dynamics with mis-measured variables: modeling and GMM estimation," Empirical Economics, Springer, vol. 48(2), pages 517-535, March.
    7. Maria Persson & Fredrik Wilhelmsson, 2016. "EU Trade Preferences and Export Diversification," The World Economy, Wiley Blackwell, vol. 39(1), pages 16-53, January.
    8. Knox, George & Datta, Hannes, 2020. "Streaming Services and the Homogenization of Music Consumption," Other publications TiSEM 0e4d6202-dcc5-4834-ba93-a, Tilburg University, School of Economics and Management.
    9. Bono, Pierre-Henri & David, Quentin & Desbordes, Rodolphe & Py, Loriane, 2022. "Metro infrastructure and metropolitan attractiveness," Regional Science and Urban Economics, Elsevier, vol. 93(C).
    10. Weidner, Martin & Zylkin, Thomas, 2021. "Bias and consistency in three-way gravity models," Journal of International Economics, Elsevier, vol. 132(C).
    11. Stefano Clo & Enrico Marvasi & Giorgio Ricchiuti, 2021. "The Internationalization of State-Owned Enterprises: An Analysis of cross-border M&As," Working Papers - Economics wp2021_06.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    12. Iain M. Cockburn & Megan J. MacGarvie, 2011. "Entry and Patenting in the Software Industry," Management Science, INFORMS, vol. 57(5), pages 915-933, May.
    13. Nathan Craig & Nicole DeHoratius & Ananth Raman, 2016. "The Impact of Supplier Inventory Service Level on Retailer Demand," Manufacturing & Service Operations Management, INFORMS, vol. 18(4), pages 461-474, October.
    14. Piyapas Tharavanij, 2007. "Capital Market, Frequency Of Recession, And Fraction Of Time The Economy In Recession," Monash Economics Working Papers 34-07, Monash University, Department of Economics.
    15. Roxana Gutiérrez-Romero & Nayely Iturbe, 2023. "Why are Mexican politicians being assassinated?: The role of oil theft and narcocracy and the electoral consequences of organized crime," WIDER Working Paper Series wp-2023-7, World Institute for Development Economic Research (UNU-WIDER).
    16. Breinlich, Holger, 2008. "Trade liberalization and industrial restructuring through mergers and acquisitions," Journal of International Economics, Elsevier, vol. 76(2), pages 254-266, December.
    17. Fischer, Stefanie & Royer, Heather & White, Corey, 2018. "The impacts of reduced access to abortion and family planning services on abortions, births, and contraceptive purchases," Journal of Public Economics, Elsevier, vol. 167(C), pages 43-68.
    18. Hussinger, Katrin & Pellens, Maikel, 2019. "Guilt by association: How scientific misconduct harms prior collaborators," Research Policy, Elsevier, vol. 48(2), pages 516-530.
    19. Schertler, Andrea & Tykvová, Tereza, 2011. "Venture capital and internationalization," International Business Review, Elsevier, vol. 20(4), pages 423-439, August.
    20. Mariane Santos Françoso¹ & Nicholas S. Vonortas, 2023. "Gatekeepers in regional innovation networks: Evidence from an emerging economy," The Journal of Technology Transfer, Springer, vol. 48(3), pages 821-841, June.

    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:sankhb:v:78:y:2016:i:1:d:10.1007_s13571-015-0106-2. 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.