IDEAS home Printed from https://ideas.repec.org/h/nbr/nberch/9993.html
   My bibliography  Save this book chapter

Identification in Control and Econometrics: Similarities and Differences

In: Annals of Economic and Social Measurement, Volume 3, number 1

Author

Listed:
  • R. H. Mehra

Abstract

No abstract is available for this item.

Suggested Citation

  • R. H. Mehra, 1974. "Identification in Control and Econometrics: Similarities and Differences," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 3, number 1, pages 21-47, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberch:9993
    as

    Download full text from publisher

    File URL: http://www.nber.org/chapters/c9993.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Rothenberg, Thomas J, 1971. "Identification in Parametric Models," Econometrica, Econometric Society, vol. 39(3), pages 577-591, May.
    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. David Kendrick, 1976. "Applications of Control Theory to Macroeconomics," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 5, number 2, pages 171-190, National Bureau of Economic Research, Inc.
    2. Peter Walsh & J. B. Cruz, Jr., 1976. "Neighboring Stochastic Control of an Econometric Model," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 5, number 2, pages 211-221, National Bureau of Economic Research, Inc.

    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. Kocięcki, Andrzej & Kolasa, Marcin, 2023. "A solution to the global identification problem in DSGE models," Journal of Econometrics, Elsevier, vol. 236(2).
    2. Carvalho Lopes, Celia Mendes & Bolfarine, Heleno, 2012. "Random effects in promotion time cure rate models," Computational Statistics & Data Analysis, Elsevier, vol. 56(1), pages 75-87, January.
    3. Orazio Attanasio & Sarah Cattan & Emla Fitzsimons & Costas Meghir & Marta Rubio-Codina, 2020. "Estimating the Production Function for Human Capital: Results from a Randomized Controlled Trial in Colombia," American Economic Review, American Economic Association, vol. 110(1), pages 48-85, January.
    4. Daeyoung Kim & Bruce Lindsay, 2015. "Empirical identifiability in finite mixture models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 67(4), pages 745-772, August.
    5. Andrew Chesher & Adam Rosen, 2015. "Characterizations of identified sets delivered by structural econometric models," CeMMAP working papers CWP63/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Gary Koop & M. Hashem Pesaran & Ron P. Smith, 2013. "On Identification of Bayesian DSGE Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(3), pages 300-314, July.
    7. M. Hashem Pesaran & Yongcheol Shin, 2002. "Long-Run Structural Modelling," Econometric Reviews, Taylor & Francis Journals, vol. 21(1), pages 49-87.
    8. Tito Belchior Silva Moreira & Benjamin Miranda Tabak & Mario Jorge Mendonça & Adolfo Sachsida, 2016. "An Evaluation of the Non-Neutrality of Money," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-20, March.
    9. repec:hal:spmain:info:hdl:2441/293qice3lj861rvos9ns14n0h0 is not listed on IDEAS
    10. Irina Zviadadze, 2017. "Term Structure of Consumption Risk Premia in the Cross Section of Currency Returns," Journal of Finance, American Finance Association, vol. 72(4), pages 1529-1566, August.
    11. Orazio Attanasio & Sarah Cattan & Emla Fitzsimons & Costas Meghir & Marta Rubio-Codina, 2015. "Estimating the Production Function for Human Capital: Results from a Randomized Control Trial in Colombia," Cowles Foundation Discussion Papers 1987, Cowles Foundation for Research in Economics, Yale University.
    12. Hamilton, James D. & Wu, Jing Cynthia, 2012. "Identification and estimation of Gaussian affine term structure models," Journal of Econometrics, Elsevier, vol. 168(2), pages 315-331.
    13. Mark P Little & Wolfgang F Heidenreich & Guangquan Li, 2009. "Parameter Identifiability and Redundancy in a General Class of Stochastic Carcinogenesis Models," PLOS ONE, Public Library of Science, vol. 4(12), pages 1-6, December.
    14. Escanciano, Juan Carlos & Hoderlein, Stefan & Lewbel, Arthur & Linton, Oliver & Srisuma, Sorawoot, 2021. "Nonparametric Euler Equation Identification And Estimation," Econometric Theory, Cambridge University Press, vol. 37(5), pages 851-891, October.
    15. Raffaella Giacomini & Toru Kitagawa, 2021. "Robust Bayesian Inference for Set‐Identified Models," Econometrica, Econometric Society, vol. 89(4), pages 1519-1556, July.
    16. Neusser, Klaus, 2016. "A topological view on the identification of structural vector autoregressions," Economics Letters, Elsevier, vol. 144(C), pages 107-111.
    17. Zadrozny, Peter A., 2022. "Linear identification of linear rational-expectations models by exogenous variables reconciles Lucas and Sims," CFS Working Paper Series 682, Center for Financial Studies (CFS).
    18. Peter Davis & Pasquale Schiraldi, 2014. "The flexible coefficient multinomial logit (FC-MNL) model of demand for differentiated products," RAND Journal of Economics, RAND Corporation, vol. 45(1), pages 32-63, March.
    19. Fei Jin & Lung-fei Lee, 2018. "Lasso Maximum Likelihood Estimation of Parametric Models with Singular Information Matrices," Econometrics, MDPI, vol. 6(1), pages 1-24, February.
    20. Brant Abbott & Giovanni Gallipoli & Costas Meghir & Giovanni L. Violante, 2019. "Education Policy and Intergenerational Transfers in Equilibrium," Journal of Political Economy, University of Chicago Press, vol. 127(6), pages 2569-2624.
    21. Pereda-Fernández, Santiago, 2023. "Identification and estimation of triangular models with a binary treatment," Journal of Econometrics, Elsevier, vol. 234(2), pages 585-623.

    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:nbr:nberch:9993. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.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.