IDEAS home Printed from https://ideas.repec.org/a/bla/jtsera/v44y2023i2p247-257.html
   My bibliography  Save this article

Higher‐order asymptotics of minimax estimators for time series

Author

Listed:
  • Xiaofei Xu
  • Yan Liu
  • Masanobu Taniguchi

Abstract

We consider the minimax estimation of time series in view of higher‐order asymptotic theory. Under the framework of Bayesian inference, we focus on the Bayes estimator and the Bayesian Whittle estimator for parameter estimation. It is shown that these estimators are minimax with respect to the Bayes risk of higher‐order bias appeared in their asymptotic expansion. The minimax problem in the boundary issue with parameter on the boundary of parameter space is also discussed. Our theoretical discovery is justified by simulation studies even when the sample size is small.

Suggested Citation

  • Xiaofei Xu & Yan Liu & Masanobu Taniguchi, 2023. "Higher‐order asymptotics of minimax estimators for time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(2), pages 247-257, March.
  • Handle: RePEc:bla:jtsera:v:44:y:2023:i:2:p:247-257
    DOI: 10.1111/jtsa.12661
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/jtsa.12661
    Download Restriction: no

    File URL: https://libkey.io/10.1111/jtsa.12661?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
    ---><---

    References listed on IDEAS

    as
    1. Phillips, P C B, 1991. "To Criticize the Critics: An Objective Bayesian Analysis of Stochastic Trends," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(4), pages 333-364, Oct.-Dec..
    2. Sims, Christopher A & Uhlig, Harald, 1991. "Understanding Unit Rooters: A Helicopter Tour," Econometrica, Econometric Society, vol. 59(6), pages 1591-1599, November.
    3. Adam M Sykulski & Sofia C Olhede & Arthur P Guillaumin & Jonathan M Lilly & Jeffrey J Early, 2019. "The debiased Whittle likelihood," Biometrika, Biometrika Trust, vol. 106(2), pages 251-266.
    4. Yan Liu & Masanobu Taniguchi, 2021. "Minimax estimation for time series models," METRON, Springer;Sapienza Università di Roma, vol. 79(3), pages 353-359, December.
    5. Robinson, Peter M. & Velasco, Carlos, 2000. "Whittle pseudo-maximum likelihood estimation for nonstationary time series," LSE Research Online Documents on Economics 2273, London School of Economics and Political Science, LSE Library.
    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. Marriott, John & Newbold, Paul, 2000. "The strength of evidence for unit autoregressive roots and structural breaks: A Bayesian perspective," Journal of Econometrics, Elsevier, vol. 98(1), pages 1-25, September.
    2. Marcet, Albert & Jarociński, Marek, 2010. "Autoregressions in small samples, priors about observables and initial conditions," Working Paper Series 1263, European Central Bank.
    3. Badi H. Baltagi & Georges Bresson & Anoop Chaturvedi & Guy Lacroix, 2022. "Robust Dynamic Space-Time Panel Data Models Using ε-contamination: An Application to Crop Yields and Climate Change," Center for Policy Research Working Papers 254, Center for Policy Research, Maxwell School, Syracuse University.
    4. Schenkelberg, Heike & Watzka, Sebastian, 2013. "Real effects of quantitative easing at the zero lower bound: Structural VAR-based evidence from Japan," Journal of International Money and Finance, Elsevier, vol. 33(C), pages 327-357.
    5. Stéphane Adjemian & Florian Pelgrin, 2008. "Un regard bayésien sur les modèles dynamiques de la macroéconomie," Economie & Prévision, La Documentation Française, vol. 0(2), pages 127-152.
    6. Magris Martin & Iosifidis Alexandros, 2021. "Approximate Bayes factors for unit root testing," Papers 2102.10048, arXiv.org, revised Feb 2021.
    7. Christopher A. Sims & Tao Zha, 1999. "Error Bands for Impulse Responses," Econometrica, Econometric Society, vol. 67(5), pages 1113-1156, September.
    8. Wachter, Jessica A. & Warusawitharana, Missaka, 2009. "Predictable returns and asset allocation: Should a skeptical investor time the market?," Journal of Econometrics, Elsevier, vol. 148(2), pages 162-178, February.
    9. Tommaso Proietti & Stefano Grassi, 2015. "Stochastic trends and seasonality in economic time series: new evidence from Bayesian stochastic model specification search," Empirical Economics, Springer, vol. 48(3), pages 983-1011, May.
    10. J -P Kreiss & E Paparoditis, 2023. "Bootstrapping Whittle estimators," Biometrika, Biometrika Trust, vol. 110(2), pages 499-518.
    11. Márcio Alves Diniz & C.A.B.Pereira & J.M.Stern, 2008. "FBST for Unit Root Problems," Working Papers 08_11, Universidade de São Paulo, Faculdade de Economia, Administração e Contabilidade de Ribeirão Preto.
    12. Grassi, S. & Proietti, T., 2014. "Characterising economic trends by Bayesian stochastic model specification search," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 359-374.
    13. Loukia Meligkotsidou & Elias Tzavalis & Ioannis D. Vrontos, 2004. "A Bayesian Analysis of Unit Roots and Structural Breaks in the Level and the Error Variance of Autoregressive Models," Working Papers 514, Queen Mary University of London, School of Economics and Finance.
    14. Smoluk, H.J. & Bennett, James, 2008. "Evaluating stock returns with time-varying risk aversion driven by trend deviations from the consumption-to-wealth ratio: An analysis conditional on income levels," Review of Financial Economics, Elsevier, vol. 17(4), pages 261-279, December.
    15. H.J. Smoluk & James Bennett, 2008. "Evaluating stock returns with time‐varying risk aversion driven by trend deviations from the consumption‐to‐wealth ratio: An analysis conditional on income levels," Review of Financial Economics, John Wiley & Sons, vol. 17(4), pages 261-279, December.
    16. Geweke, John, 1994. "Priors for Macroeconomic Time Series and Their Application," Econometric Theory, Cambridge University Press, vol. 10(3-4), pages 609-632, August.
    17. Peter C.B. Phillips, 1992. "Bayes Methods for Trending Multiple Time Series with an Empirical Application to the US Economy," Cowles Foundation Discussion Papers 1025, Cowles Foundation for Research in Economics, Yale University.
    18. Uhlig, H.F.H.V.S., 1996. "Bayesian Vector Autoregressions with Stochastic Volatility," Other publications TiSEM 4fd55395-6830-46a2-9d18-e, Tilburg University, School of Economics and Management.
    19. Goulet Coulombe, Philippe & Leroux, Maxime & Stevanovic, Dalibor & Surprenant, Stéphane, 2021. "Macroeconomic data transformations matter," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1338-1354.
    20. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2014. "On the Rise of Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 14-085/III, Tinbergen Institute, revised 04 Sep 2014.

    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:bla:jtsera:v:44:y:2023:i:2:p:247-257. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0143-9782 .

    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.