IDEAS home Printed from https://ideas.repec.org/a/spr/psycho/v76y2011i1p77-96.html
   My bibliography  Save this article

A Sandwich-Type Standard Error Estimator of SEM Models with Multivariate Time Series

Author

Listed:
  • Guangjian Zhang
  • Sy-Miin Chow
  • Anthony Ong

Abstract

No abstract is available for this item.

Suggested Citation

  • Guangjian Zhang & Sy-Miin Chow & Anthony Ong, 2011. "A Sandwich-Type Standard Error Estimator of SEM Models with Multivariate Time Series," Psychometrika, Springer;The Psychometric Society, vol. 76(1), pages 77-96, January.
  • Handle: RePEc:spr:psycho:v:76:y:2011:i:1:p:77-96
    DOI: 10.1007/s11336-010-9189-x
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11336-010-9189-x
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11336-010-9189-x?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. White, Halbert, 1980. "Using Least Squares to Approximate Unknown Regression Functions," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 21(1), pages 149-170, February.
    2. White, Halbert & Domowitz, Ian, 1984. "Nonlinear Regression with Dependent Observations," Econometrica, Econometric Society, vol. 52(1), pages 143-161, January.
    3. Peter Molenaar, 1985. "A dynamic factor model for the analysis of multivariate time series," Psychometrika, Springer;The Psychometric Society, vol. 50(2), pages 181-202, June.
    4. Stef Buuren, 1997. "Fitting arma time series by structural equation models," Psychometrika, Springer;The Psychometric Society, vol. 62(2), pages 215-236, June.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Guangjian Zhang & Michael Browne & Anthony Ong & Sy Chow, 2014. "Analytic Standard Errors for Exploratory Process Factor Analysis," Psychometrika, Springer;The Psychometric Society, vol. 79(3), pages 444-469, July.

    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. Guangjian Zhang & Michael Browne & Anthony Ong & Sy Chow, 2014. "Analytic Standard Errors for Exploratory Process Factor Analysis," Psychometrika, Springer;The Psychometric Society, vol. 79(3), pages 444-469, July.
    2. Sun-Joo Cho & Sarah Brown-Schmidt & Woo-yeol Lee, 2018. "Autoregressive Generalized Linear Mixed Effect Models with Crossed Random Effects: An Application to Intensive Binary Time Series Eye-Tracking Data," Psychometrika, Springer;The Psychometric Society, vol. 83(3), pages 751-771, September.
    3. Montfort, Kees van & Bijleveld, Catrien, 1997. "Dynamic analysis of multivariate panel data with nonlinear transformations," Serie Research Memoranda 0054, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    4. P.A.V.B. Swamy & I-Lok Chang & Jatinder S. Mehta & William H. Greene & Stephen G. Hall & George S. Tavlas, 2016. "Removing Specification Errors from the Usual Formulation of Binary Choice Models," Econometrics, MDPI, vol. 4(2), pages 1-21, June.
    5. Chamberlain, Gary, 1982. "Multivariate regression models for panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 5-46, January.
    6. Davide Viviano & Jelena Bradic, 2019. "Synthetic learner: model-free inference on treatments over time," Papers 1904.01490, arXiv.org, revised Aug 2022.
    7. Bierens, Herman J., 1990. "Model-free Asymptotically Best Forecasting of Stationary Economic Time Series," Econometric Theory, Cambridge University Press, vol. 6(3), pages 348-383, September.
    8. Yingzhuo Yu & Cesar Escalante & Xiaohui Deng & Jack Houston & Lewell Gunter, 2011. "Analysing scale and scope specialization efficiencies of US agricultural and nonagricultural banks using the Fourier flexible functional form," Applied Financial Economics, Taylor & Francis Journals, vol. 21(15), pages 1103-1116.
    9. Boldea, Otilia & Hall, Alastair R., 2013. "Estimation and inference in unstable nonlinear least squares models," Journal of Econometrics, Elsevier, vol. 172(1), pages 158-167.
    10. Sloczynski, Tymon, 2018. "A General Weighted Average Representation of the Ordinary and Two-Stage Least Squares Estimands," IZA Discussion Papers 11866, Institute of Labor Economics (IZA).
    11. Robert F. Engle & Simone Manganelli, 1999. "CAViaR: Conditional Value at Risk by Quantile Regression," NBER Working Papers 7341, National Bureau of Economic Research, Inc.
    12. Chalfant, James & Wallace, Nancy, 1991. "Testing the Translog Specification with the Fourier Cost Function," CUDARE Working Papers 198581, University of California, Berkeley, Department of Agricultural and Resource Economics.
    13. Joshua D. Angrist & Jörn-Steffen Pischke, 2010. "The Credibility Revolution in Empirical Economics: How Better Research Design Is Taking the Con out of Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 24(2), pages 3-30, Spring.
    14. Gadea Rivas, María Dolores & Gonzalo, Jesús, 2020. "Trends in distributional characteristics: Existence of global warming," Journal of Econometrics, Elsevier, vol. 214(1), pages 153-174.
    15. Su, Liangjun & Jin, Sainan, 2012. "Sieve estimation of panel data models with cross section dependence," Journal of Econometrics, Elsevier, vol. 169(1), pages 34-47.
    16. Philip Rothman & Dick van Dijk & Philip Hans Franses, 1999. "A Multivariate STAR Analysis of the Relationship Between Money and Output," Working Papers 9913, East Carolina University, Department of Economics.
    17. 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.
    18. Levine, David, 1983. "A remark on serial correlation in maximum likelihood," Journal of Econometrics, Elsevier, vol. 23(3), pages 337-342, December.
    19. Shaw, Kathryn L, 1996. "An Empirical Analysis of Risk Aversion and Income Growth," Journal of Labor Economics, University of Chicago Press, vol. 14(4), pages 626-653, October.

    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:psycho:v:76:y:2011:i:1:p:77-96. 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.