IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v128y2015icp83-86.html
   My bibliography  Save this article

Optimal asymptotic least squares estimation in a singular set-up

Author

Listed:
  • Diez de los Rios, Antonio

Abstract

In this note, I extend the optimal asymptotic least squares estimation framework to deal with singularities in the asymptotic covariance of the distance function. Further, the relationship between the asymptotic least squares and maximum likelihood estimation frameworks in such a singular set-up is discussed.

Suggested Citation

  • Diez de los Rios, Antonio, 2015. "Optimal asymptotic least squares estimation in a singular set-up," Economics Letters, Elsevier, vol. 128(C), pages 83-86.
    • Handle: RePEc:eee:ecolet:v:128:y:2015:i:c:p:83-86
    DOI: 10.1016/j.econlet.2015.01.006
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165176515000166
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.econlet.2015.01.006?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. Peñaranda, Francisco & Sentana, Enrique, 2012. "Spanning tests in return and stochastic discount factor mean–variance frontiers: A unifying approach," Journal of Econometrics, Elsevier, vol. 170(2), pages 303-324.
    2. Antonio Diez de Los Rios, 2015. "A New Linear Estimator for Gaussian Dynamic Term Structure Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(2), pages 282-295, April.
    3. Gourieroux, Christian & Monfort, Alan & Renault, Eric, 1989. "Testing for Common Roots," Econometrica, Econometric Society, vol. 57(1), pages 171-185, January.
    4. Lawrence J. Christiano & Martin Eichenbaum & Charles L. Evans, 2005. "Nominal Rigidities and the Dynamic Effects of a Shock to Monetary Policy," Journal of Political Economy, University of Chicago Press, vol. 113(1), pages 1-45, February.
    5. Chamberlain, Gary, 1982. "Multivariate regression models for panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 5-46, January.
    6. Giovanni Barone Adesi & Patrick Gagliardini & Giovanni Urga, 2004. "Testing Asset Pricing Models With Coskewness," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 474-485, October.
    7. Cragg, John G. & Donald, Stephen G., 1997. "Inferring the rank of a matrix," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 223-250.
    8. Kodde, D A & Palm, Franz C & Pfann, G A, 1990. "Asymptotic Least-Squares Estimation Efficiency Considerations and Applications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 5(3), pages 229-243, July-Sept.
    9. Martin Pesendorfer & Philipp Schmidt-Dengler, 2008. "Asymptotic Least Squares Estimators for Dynamic Games -super-1," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 75(3), pages 901-928.
    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. Mayer, Walter J. & Liu, Feng & Dang, Xin, 2017. "Improving the power of the Diebold–Mariano–West test for least squares predictions," International Journal of Forecasting, Elsevier, vol. 33(3), pages 618-626.
    2. Antonio Diez de los Rios, 2017. "Optimal Estimation of Multi-Country Gaussian Dynamic Term Structure Models Using Linear Regressions," Staff Working Papers 17-33, Bank of Canada.

    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. Antonio Diez de los Rios, 2017. "Optimal Estimation of Multi-Country Gaussian Dynamic Term Structure Models Using Linear Regressions," Staff Working Papers 17-33, Bank of Canada.
    2. Antonio Diez de Los Rios, 2015. "A New Linear Estimator for Gaussian Dynamic Term Structure Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(2), pages 282-295, April.
    3. Jürgen Bierbaumer-Polly & Werner Hölzl, 2016. "Business Cycle Dynamics and Firm Heterogeneity. Evidence for Austria Using Survey Data," WIFO Working Papers 504, WIFO.
    4. Fousseni Chabi-Yo & René Garcia & Eric Renault, 2005. "The Stochastic Discount Factor: Extending the Volatility Bound and a New Approach to Portfolio Selection with Higher-Order Moments," Staff Working Papers 05-2, Bank of Canada.
    5. Michelle L. Barnes & Fabia Gumbau-Brisa & Denny Lie & Giovanni P. Olivei, 2011. "Estimation of forward-looking relationships in closed form: an application to the New Keynesian Phillips curve," Working Papers 11-3, Federal Reserve Bank of Boston.
    6. Mary A. Burke & Ali Ozdagli, 2023. "Household Inflation Expectations and Consumer Spending: Evidence from Panel Data," The Review of Economics and Statistics, MIT Press, vol. 105(4), pages 948-961, July.
    7. Canova, Fabio & Sala, Luca, 2009. "Back to square one: Identification issues in DSGE models," Journal of Monetary Economics, Elsevier, vol. 56(4), pages 431-449, May.
    8. Manuel Arellano & Stéphane Bonhomme, 2017. "Nonlinear Panel Data Methods for Dynamic Heterogeneous Agent Models," Annual Review of Economics, Annual Reviews, vol. 9(1), pages 471-496, September.
    9. Coublucq, Daniel, 2013. "Demand estimation with selection bias: A dynamic game approach with an application to the US railroad industry," DICE Discussion Papers 94, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    10. Kazuhiko Hayakawa & M. Hashem Pesaran & L. Vanessa Smith, 2023. "Short T dynamic panel data models with individual, time and interactive effects," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(6), pages 940-967, September.
    11. Mayer, Walter J. & Liu, Feng & Dang, Xin, 2017. "Improving the power of the Diebold–Mariano–West test for least squares predictions," International Journal of Forecasting, Elsevier, vol. 33(3), pages 618-626.
    12. Gospodinov, Nikolay & Kan, Raymond & Robotti, Cesare, 2019. "Too good to be true? Fallacies in evaluating risk factor models," Journal of Financial Economics, Elsevier, vol. 132(2), pages 451-471.
    13. Groen, Jan J J & Mumtaz, Haroon, 2008. "Investigating the structural stability of the Phillips curve relationship," Bank of England working papers 350, Bank of England.
    14. Alessio Anzuini & Patrizio Pagano & Massimiliano Pisani, 2007. "Oil supply news in a VAR: Information from financial markets," Temi di discussione (Economic working papers) 632, Bank of Italy, Economic Research and International Relations Area.
    15. Yuriy Gorodnichenko, 2005. "Reduced-Rank Identification of Structural Shocks in VARs," Macroeconomics 0512011, University Library of Munich, Germany.
    16. Victor Aguirregabiria & Pedro Mira, 2013. "Identification of Games of Incomplete Information with Multiple Equilibria and Common Unobserved Heterogeneity," Working Papers tecipa-474, University of Toronto, Department of Economics.
    17. Juan José Echavarría & Andrés González, 2012. "Choques internacionales reales y financieros y su impacto sobre la economía colombiana," Revista ESPE - Ensayos sobre Política Económica, Banco de la Republica de Colombia, vol. 30(69), pages 14-66, December.
    18. Adnan Haider Bukhari & Safdar Ullah Khan, 2008. "A Small Open Economy DSGE Model for Pakistan," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 47(4), pages 963-1008.
    19. Paul De Grauwe, 2014. "Animal Spirits and Monetary Policy," World Scientific Book Chapters, in: Exchange Rates and Global Financial Policies, chapter 18, pages 473-520, World Scientific Publishing Co. Pte. Ltd..
    20. Mumtaz, Haroon & Theodoridis, Konstantinos, 2017. "Common and country specific economic uncertainty," Journal of International Economics, Elsevier, vol. 105(C), pages 205-216.

    More about this item

    Keywords

    Asymptotic optimality; Auxiliary parameters; Minimum distance estimation; Generalized inverse; Singular covariance matrix;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

    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:128:y:2015:i:c:p:83-86. 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.