IDEAS home Printed from https://ideas.repec.org/p/boc/asug06/2.html
   My bibliography  Save this paper

Time series filtering techniques in Stata

Author

Listed:
  • Kit Baum

    (Boston College)

Abstract

I will describe a number of time series filtering techniques, including the Hodrick-Prescott, Baxter-King and bandpass filters and variants, and present new Mata-coded versions of these routines which are considerably more efficient than previous ado-code routines. Applications to an economic time series will be discussed.

Suggested Citation

  • Kit Baum, 2006. "Time series filtering techniques in Stata," North American Stata Users' Group Meetings 2006 2, Stata Users Group.
  • Handle: RePEc:boc:asug06:2
    as

    Download full text from publisher

    File URL: http://repec.org/nasug2006/TSFiltering_beamer.pdf
    Download Restriction: no

    File URL: http://repec.org/nasug2006/tsfiltering.do
    File Function: do-file to reproduce results in talk
    Download Restriction: no

    File URL: http://repec.org/nasug2006/reer.raw
    File Function: raw data file used for results in talk
    Download Restriction: no
    ---><---

    Other versions of this item:

    Citations

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


    Cited by:

    1. El-Shagi, Makram, 2011. "Inflation expectations: Does the market beat econometric forecasts?," The North American Journal of Economics and Finance, Elsevier, vol. 22(3), pages 298-319.
    2. Caporale, Guglielmo Maria & Kang, Woo-Young & Spagnolo, Fabio & Spagnolo, Nicola, 2022. "The COVID-19 pandemic, policy responses and stock markets in the G20," International Economics, Elsevier, vol. 172(C), pages 77-90.
    3. El-Shagi, Makram, 2009. "Inflation Expectations: Does the Market Beat Professional Forecasts?," IWH Discussion Papers 16/2009, Halle Institute for Economic Research (IWH).
    4. Chaubal Aditi, 2018. "P-star model for India: a nonlinear approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(5), pages 1-28, December.
    5. Jetter, Michael, 2014. "Volatility and growth: Governments are key," European Journal of Political Economy, Elsevier, vol. 36(C), pages 71-88.
    6. Vadim Kufenko, 2020. "Hide-and-Seek with time-series filters: a model-based Monte Carlo study," Empirical Economics, Springer, vol. 59(5), pages 2335-2361, November.
    7. Carneiro,Francisco Galrao & Garrido,Leonardo, 2015. "New evidence on the cyclicality of fiscal policy," Policy Research Working Paper Series 7293, The World Bank.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:boc:asug06:2. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Christopher F Baum (email available below). General contact details of provider: https://edirc.repec.org/data/stataea.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.