IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v198y2021ics0165176520304274.html
   My bibliography  Save this article

Efficient estimation of multi-level models with strictly exogenous explanatory variables

Author

Listed:
  • Yang, Yimin

Abstract

This paper shows that several moment redundancy results developed for panel data models continue to hold for multi-level models with strict exogenous explanatory variables, which establishes the efficiency of some estimators for multi-level linear models.

Suggested Citation

  • Yang, Yimin, 2021. "Efficient estimation of multi-level models with strictly exogenous explanatory variables," Economics Letters, Elsevier, vol. 198(C).
    • Handle: RePEc:eee:ecolet:v:198:y:2021:i:c:s0165176520304274
    DOI: 10.1016/j.econlet.2020.109667
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165176520304274
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.econlet.2020.109667?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. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
    2. Laszlo Balazsi & Laszlo Matyas & Tom Wansbeek, 2018. "The estimation of multidimensional fixed effects panel data models," Econometric Reviews, Taylor & Francis Journals, vol. 37(3), pages 212-227, March.
    3. Altonji, Joseph G & Segal, Lewis M, 1996. "Small-Sample Bias in GMM Estimation of Covariance Structures," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 353-366, July.
    4. Hausman, Jerry A & Taylor, William E, 1981. "Panel Data and Unobservable Individual Effects," Econometrica, Econometric Society, vol. 49(6), pages 1377-1398, November.
    5. Tauchen, George, 1986. "Statistical Properties of Generalized Method-of-Moments Estimators of Structural Parameters Obtained from Financial Market Data: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(4), pages 423-425, October.
    6. Amemiya, Takeshi & MaCurdy, Thomas E, 1986. "Instrumental-Variable Estimation of an Error-Components Model," Econometrica, Econometric Society, vol. 54(4), pages 869-880, July.
    7. So Im, Kyung & Ahn, Seung C. & Schmidt, Peter & Wooldridge, Jeffrey M., 1999. "Efficient estimation of panel data models with strictly exogenous explanatory variables," Journal of Econometrics, Elsevier, vol. 93(1), pages 177-201, November.
    8. Breusch, Trevor S & Mizon, Grayham E & Schmidt, Peter, 1989. "Efficient Estimation Using Panel Data," Econometrica, Econometric Society, vol. 57(3), pages 695-700, May.
    9. Tauchen, George, 1986. "Statistical Properties of Generalized Method-of-Moments Estimators of Structural Parameters Obtained from Financial Market Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(4), pages 397-416, October.
    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. So Im, Kyung & Ahn, Seung C. & Schmidt, Peter & Wooldridge, Jeffrey M., 1999. "Efficient estimation of panel data models with strictly exogenous explanatory variables," Journal of Econometrics, Elsevier, vol. 93(1), pages 177-201, November.
    2. Chay, Kenneth Y. & Lee, David S., 2000. "Changes in relative wages in the 1980s Returns to observed and unobserved skills and black-white wage differentials," Journal of Econometrics, Elsevier, vol. 99(1), pages 1-38, November.
    3. Petreski, Marjan, 2009. "Analysis of exchange-rate regime effect on growth: theoretical channels and empirical evidence with panel data," Economics Discussion Papers 2009-49, Kiel Institute for the World Economy (IfW Kiel).
    4. Badi H. Baltagi & Chihwa Kao, 2000. "Nonstationary Panels, Cointegration in Panels and Dynamic Panels: A Survey," Center for Policy Research Working Papers 16, Center for Policy Research, Maxwell School, Syracuse University.
    5. Yang, Yimin & Schmidt, Peter, 2021. "An econometric approach to the estimation of multi-level models," Journal of Econometrics, Elsevier, vol. 220(2), pages 532-543.
    6. Ahn, Seung C. & Schmidt, Peter, 1995. "Efficient estimation of models for dynamic panel data," Journal of Econometrics, Elsevier, vol. 68(1), pages 5-27, July.
    7. Eduardo Fé, 2012. "Instrumental variable estimation of heteroskedasticity adaptive error component models," Statistical Papers, Springer, vol. 53(3), pages 577-615, August.
    8. Eduardo Fé Rodríguez, 2009. "Adaptive Instrumental Variable Estimation of Heteroskedastic Error Component Models," Economics Discussion Paper Series 0921, Economics, The University of Manchester.
    9. Farbmacher, Helmut & Tauchmann, Harald, 2021. "Linear fixed-effects estimation with non-repeated outcomes," FAU Discussion Papers in Economics 03/2021, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics, revised 2021.
    10. Sebastian Kripfganz & Claudia Schwarz, 2019. "Estimation of linear dynamic panel data models with time‐invariant regressors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(4), pages 526-546, June.
    11. Windmeijer, Frank, 2005. "A finite sample correction for the variance of linear efficient two-step GMM estimators," Journal of Econometrics, Elsevier, vol. 126(1), pages 25-51, May.
    12. Keskinsoy, Bilal, 2017. "Lucas Paradox in the Short-Run," MPRA Paper 78783, University Library of Munich, Germany.
    13. Park, B. U. & Sickles, R. C. & Simar, L., 1998. "Stochastic panel frontiers: A semiparametric approach," Journal of Econometrics, Elsevier, vol. 84(2), pages 273-301, June.
    14. Jung Hur & Rasyad A. Parinduri & Yohanes E. Riyanto, 2011. "Cross‐Border M&A Inflows And Quality Of Country Governance: Developing Versus Developed Countries," Pacific Economic Review, Wiley Blackwell, vol. 16(5), pages 638-655, December.
    15. Jee-Seon Kim & Edward Frees, 2007. "Multilevel Modeling with Correlated Effects," Psychometrika, Springer;The Psychometric Society, vol. 72(4), pages 505-533, December.
    16. Helmut Farbmacher & Harald Tauchmann, 2023. "Linear fixed-effects estimation with nonrepeated outcomes," Econometric Reviews, Taylor & Francis Journals, vol. 42(8), pages 635-654, September.
    17. Doran, Howard E. & Schmidt, Peter, 2006. "GMM estimators with improved finite sample properties using principal components of the weighting matrix, with an application to the dynamic panel data model," Journal of Econometrics, Elsevier, vol. 133(1), pages 387-409, July.
    18. Amoroso, Sara & Bruno, Randolph Luca & Magazzini, Laura, 2022. "The Identification of Time-Invariant Variables in Panel Data Model: Exploring the Role of Science in Firms’ Productivity," IZA Discussion Papers 15708, Institute of Labor Economics (IZA).
    19. Donald W.K. Andrews & Biao Lu, 1999. "Consistent Model and Moment Selection Criteria for GMM Estimation with Applications to Dynamic Panel Data Models," Cowles Foundation Discussion Papers 1233, Cowles Foundation for Research in Economics, Yale University.
    20. M. Hashem Pesaran & Qiankun Zhou, 2018. "Estimation of time-invariant effects in static panel data models," Econometric Reviews, Taylor & Francis Journals, vol. 37(10), pages 1137-1171, November.

    More about this item

    Keywords

    Efficiency; Multi-level; Strict exogeneity; Redundancy;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

    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:eee:ecolet:v:198:y:2021:i:c:s0165176520304274. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ecolet .

    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.