IDEAS home Printed from https://ideas.repec.org/p/zbw/sfb475/199907.html
   My bibliography  Save this paper

The consistency of s2 in the linear regression model when the disturbances are spatially correlated

Author

Listed:
  • Gotu, Butte

Abstract

Conditions for the consistency of the estimator s2 of the variance of the disturbance a2u under first-order spatial error processes are given.

Suggested Citation

  • Gotu, Butte, 1999. "The consistency of s2 in the linear regression model when the disturbances are spatially correlated," Technical Reports 1999,07, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    • Handle: RePEc:zbw:sfb475:199907
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/77361/2/1999-07.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Davidson, James, 1994. "Stochastic Limit Theory: An Introduction for Econometricians," OUP Catalogue, Oxford University Press, number 9780198774037.
    2. Neudecker, Heinz, 1977. "Bounds for the Bias of the Least Squares Estimator of s2 in the Case of a First-order Autoregressive Process (Positive Autocorrelation)," Econometrica, Econometric Society, vol. 45(5), pages 1257-1262, July.
    3. Dufour, Jean-Marie, 1988. "Estimators of the disturbance variance in econometric models : Small-sample bias and the existence of moments," Journal of Econometrics, Elsevier, vol. 37(2), pages 277-292, February.
    4. Fiebig, Denzil G. & McAleer, Michael & Bartels, Robert, 1992. "Properties of ordinary least squares estimators in regression models with nonspherical disturbances," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 321-334.
    5. Neudecker, H., 1978. "Bounds for the bias of the LS estimator of o^2 in the case of a first-order autoregressive process," University of Amsterdam, Actuarial Science and Econometrics Archive 293026, University of Amsterdam, Faculty of Economics and Business.
    6. Kiviet, Jan F & Kramer, Walter, 1992. "Bias of SDE 2 in the Linear Regression Model with Correlated Errors," The Review of Economics and Statistics, MIT Press, vol. 74(2), pages 362-365, May.
    7. Kramer, Walter & Berghoff, Sonja, 1991. "Consistency of sDE 2 in the Linear Regression Model with Correlated Errors," Empirical Economics, Springer, vol. 16(3), pages 375-377.
    8. Neudecker, H, 1978. "Bounds for the Bias of the LS Estimator of [sigma][superscript]2 in the Case of a First-Order (Positive) Autoregressive Process When the Regression Contains a Constant Term," Econometrica, Econometric Society, vol. 46(5), pages 1223-1226, 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. Song, Seuck Heun & Lee, Jaejun, 2008. "A note on S2 in a spatially correlated error components regression model for panel data," Economics Letters, Elsevier, vol. 101(1), pages 41-43, October.
    2. Prof. Dr. Walter Krämer & Dr. Christoph Hanck, "undated". "OLS-based estimation of the disturbance variance under spatial autocorrelation," Working Papers 7, Business and Social Statistics Department, Technische Universität Dortmund, revised Oct 2006.
    3. Musser, Wesley N., 1992. "A Historical Overview of Estimation of Historical Risk Coefficients," 1992 Quantifying Long Run Agricultural Risks and Evaluating Farmer Responses to Risk Meeting, March 22-25, 1992, Orlando, Florida 307862, Regional Research Projects > S-232: Quantifying Long Run Agricultural Risks and Evaluating Farmer Responses to Risk.
    4. Paulo M. D. C. Parente & Richard J. Smith, 2021. "Quasi‐maximum likelihood and the kernel block bootstrap for nonlinear dynamic models," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(4), pages 377-405, July.
    5. Biqing Cai & Jiti Gao & Dag Tjøstheim, 2017. "A New Class of Bivariate Threshold Cointegration Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(2), pages 288-305, April.
    6. Čížek, Pavel, 2008. "General Trimmed Estimation: Robust Approach To Nonlinear And Limited Dependent Variable Models," Econometric Theory, Cambridge University Press, vol. 24(6), pages 1500-1529, December.
    7. Michelacci, Claudio & Zaffaroni, Paolo, 2000. "(Fractional) beta convergence," Journal of Monetary Economics, Elsevier, vol. 45(1), pages 129-153, February.
    8. Alberto Abadie & Susan Athey & Guido W. Imbens & Jeffrey M. Wooldridge, 2020. "Sampling‐Based versus Design‐Based Uncertainty in Regression Analysis," Econometrica, Econometric Society, vol. 88(1), pages 265-296, January.
    9. Pierre Perron & Yohei Yamamoto, 2022. "Structural change tests under heteroskedasticity: Joint estimation versus two‐steps methods," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(3), pages 389-411, May.
    10. Hendrik Thiel & Stephan L. Thomsen, 2015. "Individual Poverty Paths and the Stability of Control-Perception," SOEPpapers on Multidisciplinary Panel Data Research 794, DIW Berlin, The German Socio-Economic Panel (SOEP).
    11. Brüggemann, Ralf & Jentsch, Carsten & Trenkler, Carsten, 2016. "Inference in VARs with conditional heteroskedasticity of unknown form," Journal of Econometrics, Elsevier, vol. 191(1), pages 69-85.
    12. Pentti Saikkonen & Rickard Sandberg, 2016. "Testing for a Unit Root in Noncausal Autoregressive Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(1), pages 99-125, January.
    13. Martins-Filho, Carlos & Yao, Feng & Torero, Maximo, 2018. "Nonparametric Estimation Of Conditional Value-At-Risk And Expected Shortfall Based On Extreme Value Theory," Econometric Theory, Cambridge University Press, vol. 34(1), pages 23-67, February.
    14. Lee, Yoon-Jin & Okui, Ryo & Shintani, Mototsugu, 2018. "Asymptotic inference for dynamic panel estimators of infinite order autoregressive processes," Journal of Econometrics, Elsevier, vol. 204(2), pages 147-158.
    15. Davidson James & Rambaccussing Dooruj, 2015. "A Test of the Long Memory Hypothesis Based on Self-Similarity," Journal of Time Series Econometrics, De Gruyter, vol. 7(2), pages 115-141, July.
    16. Goldman Elena & Tsurumi Hiroki, 2005. "Bayesian Analysis of a Doubly Truncated ARMA-GARCH Model," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(2), pages 1-38, June.
    17. Chihwa Kao & Lorenzo Trapani & Giovanni Urga, 2012. "Testing for Instability in Covariance Structures," Center for Policy Research Working Papers 131, Center for Policy Research, Maxwell School, Syracuse University.
    18. Antoine Djogbenou & Silvia Gonçalves & Benoit Perron, 2015. "Bootstrap inference in regressions with estimated factors and serial correlation," CIRANO Working Papers 2015s-20, CIRANO.
    19. Qiu, Jin & Ma, Qing & Wu, Lang, 2019. "A moving blocks empirical likelihood method for panel linear fixed effects models with serial correlations and cross-sectional dependences," Economic Modelling, Elsevier, vol. 83(C), pages 394-405.
    20. Koo, Bonsoo & Seo, Myung Hwan, 2015. "Structural-break models under mis-specification: Implications for forecasting," Journal of Econometrics, Elsevier, vol. 188(1), pages 166-181.

    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:zbw:sfb475:199907. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/isdorde.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.