IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v127y2015icp10-13.html
   My bibliography  Save this article

A low dimensional Kalman filter for systems with lagged states in the measurement equation

Author

Listed:
  • Nimark, Kristoffer P.

Abstract

This note describes how the Kalman filter and the Kalman smoother can be modified to allow for the vector of observables to be a function of lagged state variables without increasing the dimension of the state vector in the filter.

Suggested Citation

  • Nimark, Kristoffer P., 2015. "A low dimensional Kalman filter for systems with lagged states in the measurement equation," Economics Letters, Elsevier, vol. 127(C), pages 10-13.
    • Handle: RePEc:eee:ecolet:v:127:y:2015:i:c:p:10-13
    DOI: 10.1016/j.econlet.2014.12.016
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165176514004777
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.econlet.2014.12.016?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. J. Durbin, 2002. "A simple and efficient simulation smoother for state space time series analysis," Biometrika, Biometrika Trust, vol. 89(3), pages 603-616, August.
    2. Kristoffer Nimark, 2009. "Speculative dynamics in the term structure of interest rates," Economics Working Papers 1194, Department of Economics and Business, Universitat Pompeu Fabra, revised Sep 2012.
    3. Hang Qian, 2014. "A Flexible State Space Model And Its Applications," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(2), pages 79-88, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Seeking feedback: Towards a New Keynesian Theory of the Price Level
      by bankunderground in Bank Underground on 2015-07-13 12:30:00

    Citations

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


    Cited by:

    1. Pagan, Adrian & Robinson, Tim, 2022. "Excess shocks can limit the economic interpretation," European Economic Review, Elsevier, vol. 145(C).
    2. Lerby Ergun & Andreas Uthemann, 2020. "Strategic Uncertainty in Financial Markets: Evidence from a Consensus Pricing Service," Staff Working Papers 20-55, Bank of Canada.
    3. Ergun, Lerby & Uthemann, Andreas, 2020. "Higher-order uncertainty in financial markets: evidence from a consensus pricing service," LSE Research Online Documents on Economics 118893, London School of Economics and Political Science, LSE Library.
    4. Kristoffer Nimark, 2007. "Dynamic Higher Order Expectations," 2007 Meeting Papers 542, Society for Economic Dynamics.
    5. Adrian Pagan & Tim Robinson, 2020. "Too Many Shocks Spoil the Interpretation," Melbourne Institute Working Paper Series wp2020n02, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    6. Adrian Pagan & Tim Robinson, 2019. "Implications of Partial Information for Applied Macroeconomic Modelling," Melbourne Institute Working Paper Series wp2019n12, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    7. Hauber, Philipp & Schumacher, Christian & Zhang, Jiachun, 2019. "A flexible state-space model with lagged states and lagged dependent variables: Simulation smoothing," Discussion Papers 15/2019, Deutsche Bundesbank.
    8. Kurz, Malte S., 2018. "A note on low-dimensional Kalman smoothers for systems with lagged states in the measurement equation," Economics Letters, Elsevier, vol. 168(C), pages 42-45.

    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. Francisco Barillas & Kristoffer Nimark, 2012. "Speculation, risk premia and expectations in the yield curve," Economics Working Papers 1337, Department of Economics and Business, Universitat Pompeu Fabra, revised Nov 2013.
    2. Yasutomo Murasawa, 2016. "The Beveridge–Nelson decomposition of mixed-frequency series," Empirical Economics, Springer, vol. 51(4), pages 1415-1441, December.
    3. Hauber, Philipp & Schumacher, Christian & Zhang, Jiachun, 2019. "A flexible state-space model with lagged states and lagged dependent variables: Simulation smoothing," Discussion Papers 15/2019, Deutsche Bundesbank.
    4. Takahashi, Makoto & Watanabe, Toshiaki & Omori, Yasuhiro, 2016. "Volatility and quantile forecasts by realized stochastic volatility models with generalized hyperbolic distribution," International Journal of Forecasting, Elsevier, vol. 32(2), pages 437-457.
    5. Xianguo HUANG & Roberto LEON-GONZALEZ & Somrasri YUPHO, 2013. "Financial Integration from a Time-Varying Cointegration Perspective," Asian Journal of Empirical Research, Asian Economic and Social Society, vol. 3(12), pages 1473-1487.
    6. Laura E. Jackson & M. Ayhan Kose & Christopher Otrok & Michael T. Owyang, 2016. "Specification and Estimation of Bayesian Dynamic Factor Models: A Monte Carlo Analysis with an Application to Global House Price Comovement," Advances in Econometrics, in: Dynamic Factor Models, volume 35, pages 361-400, Emerald Group Publishing Limited.
    7. Del Negro, Marco & Giannone, Domenico & Giannoni, Marc P. & Tambalotti, Andrea, 2019. "Global trends in interest rates," Journal of International Economics, Elsevier, vol. 118(C), pages 248-262.
    8. Aloy Marcel & Tong Charles Lai & Peguin-Feissolle Anne & Dufrénot Gilles, 2013. "A smooth transition long-memory model," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(3), pages 281-296, May.
    9. Rob Luginbuhl, 2020. "Estimation of the Financial Cycle with a Rank-Reduced Multivariate State-Space Model," CPB Discussion Paper 409, CPB Netherlands Bureau for Economic Policy Analysis.
    10. Martín Almuzara & Dante Amengual & Gabriele Fiorentini & Enrique Sentana, 2022. "GDP Solera. The Ideal Vintage Mix," Working Papers wp2022_2204, CEMFI.
    11. Vasco Cúrdia & Marco Del Negro & Daniel L. Greenwald, 2014. "Rare Shocks, Great Recessions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(7), pages 1031-1052, November.
    12. Falk Bräuning & Siem Jan Koopman, 2016. "The dynamic factor network model with an application to global credit risk," Working Papers 16-13, Federal Reserve Bank of Boston.
    13. repec:rim:rimwps:24-08 is not listed on IDEAS
    14. Jebabli, Ikram & Arouri, Mohamed & Teulon, Frédéric, 2014. "On the effects of world stock market and oil price shocks on food prices: An empirical investigation based on TVP-VAR models with stochastic volatility," Energy Economics, Elsevier, vol. 45(C), pages 66-98.
    15. Mesters, G. & Koopman, S.J., 2014. "Generalized dynamic panel data models with random effects for cross-section and time," Journal of Econometrics, Elsevier, vol. 180(2), pages 127-140.
    16. Iacopini, Matteo & Poon, Aubrey & Rossini, Luca & Zhu, Dan, 2023. "Bayesian mixed-frequency quantile vector autoregression: Eliciting tail risks of monthly US GDP," Journal of Economic Dynamics and Control, Elsevier, vol. 157(C).
    17. Yoo, Do-il, "undated". "Vegetable Price Prediction Using Atypical Web-Search Data," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 236211, Agricultural and Applied Economics Association.
    18. Todd E. Clark & Taeyoung Doh, 2011. "A Bayesian evaluation of alternative models of trend inflation," Working Papers (Old Series) 1134, Federal Reserve Bank of Cleveland.
    19. Marek Jarociński & Michele Lenza, 2018. "An Inflation‐Predicting Measure of the Output Gap in the Euro Area," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(6), pages 1189-1224, September.
    20. Ishihara, Tsunehiro & Omori, Yasuhiro & Asai, Manabu, 2016. "Matrix exponential stochastic volatility with cross leverage," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 331-350.
    21. Nakajima, Jouchi & Kasuya, Munehisa & Watanabe, Toshiaki, 2011. "Bayesian analysis of time-varying parameter vector autoregressive model for the Japanese economy and monetary policy," Journal of the Japanese and International Economies, Elsevier, vol. 25(3), pages 225-245, September.

    More about this item

    Keywords

    Kalman filter; Lagged observables; Kalman smoother; Simulation smoother;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: 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:127:y:2015:i:c:p:10-13. 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.