IDEAS home Printed from https://ideas.repec.org/a/bes/jnlasa/v100y2005p841-852.html
   My bibliography  Save this article

Measurement Error in Linear Autoregressive Models

Author

Listed:
  • Staudenmayer, John
  • Buonaccorsi, John P.

Abstract

No abstract is available for this item.

Suggested Citation

  • 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.
  • Handle: RePEc:bes:jnlasa:v:100:y:2005:p:841-852
    as

    Download full text from publisher

    File URL: http://www.ingentaconnect.com/content/asa/jasa/2005/00000100/00000471/art00016
    File Function: full text
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search 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. Philip Hans Franses, 2020. "Measurement Error in a First-order Autoregression," Advances in Decision Sciences, Asia University, Taiwan, vol. 24(2), pages 1-14, June.
    2. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2018. "Modeling and forecasting (un)reliable realized covariances for more reliable financial decisions," Journal of Econometrics, Elsevier, vol. 207(1), pages 71-91.
    3. Biørn, Erik, 2012. "The Measurement Error Problem in Dynamic Panel Data Analysis: Modeling and GMM Estimation," Memorandum 02/2012, Oslo University, Department of Economics.
    4. Christophe Chesneau & Salima El Kolei & Fabien Navarro, 2022. "Parametric estimation of hidden Markov models by least squares type estimation and deconvolution," Statistical Papers, Springer, vol. 63(5), pages 1615-1648, October.
    5. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2016. "Exploiting the errors: A simple approach for improved volatility forecasting," Journal of Econometrics, Elsevier, vol. 192(1), pages 1-18.
    6. Daniel Kaufmann, 2020. "Is deflation costly after all? The perils of erroneous historical classifications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(5), pages 614-628, August.
    7. Tu, Yundong & Yao, Qiwei & Zhang, Rongmao, 2020. "Error-correction factor models for high-dimensional cointegrated time series," LSE Research Online Documents on Economics 106994, London School of Economics and Political Science, LSE Library.
    8. 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.
    9. Jingxuan Luo & Lili Yue & Gaorong Li, 2023. "Overview of High-Dimensional Measurement Error Regression Models," Mathematics, MDPI, vol. 11(14), pages 1-22, July.
    10. Biørn, Erik, 2014. "Serially Correlated Measurement Errors in Time Series Regression: The Potential of Instrumental Variable Estimators," Memorandum 28/2014, Oslo University, Department of Economics.
    11. Johannes Bracher & Leonhard Held, 2021. "A marginal moment matching approach for fitting endemic‐epidemic models to underreported disease surveillance counts," Biometrics, The International Biometric Society, vol. 77(4), pages 1202-1214, December.
    12. Florian Peters & Simas Kucinskas, 2018. "Measuring Biases in Expectation Formation," Tinbergen Institute Discussion Papers 18-058/IV, Tinbergen Institute.
    13. Deyuan Li & Chen Ling & Qing Liu & Liang Peng, 2022. "Inference for the Lee-Carter Model With An AR(2) Process," Methodology and Computing in Applied Probability, Springer, vol. 24(2), pages 991-1019, June.
    14. Daniel Kaufmann, 2016. "Is Deflation Costly After All? Evidence from Noisy Historical Data," KOF Working papers 16-421, KOF Swiss Economic Institute, ETH Zurich.
    15. Balakrishna, N. & Kim, Jiwoong & Koul, Hira L., 2020. "Lack-of-fit of a parametric measurement error AR(1) model," Statistics & Probability Letters, Elsevier, vol. 166(C).
    16. Christophe Chesneau & Salima El Kolei & Fabien Navarro, 2017. "Parametric estimation of hidden Markov models by least squares type estimation and deconvolution," Working Papers 2017-66, Center for Research in Economics and Statistics.
    17. Erik Biørn, 2015. "Panel data dynamics with mis-measured variables: modeling and GMM estimation," Empirical Economics, Springer, vol. 48(2), pages 517-535, March.
    18. Geng, Pei, 2022. "Estimation of functional-coefficient autoregressive models with measurement error," Journal of Multivariate Analysis, Elsevier, vol. 192(C).
    19. 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.
    20. Gerd Ronning, 2009. "Stochastische Überlagerung mit Hilfe der Mischungsverteilung," IAW Discussion Papers 48, Institut für Angewandte Wirtschaftsforschung (IAW).
    21. Lenin Arango-Castillo & Francisco J. Martínez-Ramírez & María José Orraca, 2024. "Univariate Measures of Persistence: A Comparative Analysis," Working Papers 2024-11, Banco de México.
    22. Solbu, Erik Blystad & Engen, Steinar & Diserud, Ola Håvard, 2015. "Guidelines when estimating temporal changes in density dependent populations," Ecological Modelling, Elsevier, vol. 313(C), pages 355-376.

    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:bes:jnlasa:v:100:y:2005:p:841-852. 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: Christopher F. Baum (email available below). General contact details of provider: http://www.amstat.org/publications/jasa/index.cfm?fuseaction=main .

    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.