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help for couliari
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Apply Corbae-Ouliaris frequency domain filter to time series

Syntax

        couliari varlist [if exp] [in range] , s(#) e(#) stub(abbrev)

    couliari is for use with time-series data. You must tsset your data
    before using couliari; see help tsset. couliari supports the by prefix,
    which may be used to operate on each time series in a panel.

    varlist may contain time-series operators; see help varlist.

Description

    couliari applies the frequency domain filter of Corbae, Ouliaris and
    Phillips (2002) and Corbae and Ouliaris (2006) to one or more time series
    in varlist. Series can be stationary, or can have a unit root. It tends
    to produce output similar to the Baxter-King (1999) filter, though
    without the end-point issue (it estimates end-points directly). The
    filtered series and smoothed series are placed in new variables,
    specified with the stub() option. The smoothed variables are identified
    by "_sm" in their names.  The s() and e() arguments can either specify
    the minimum period of oscillation and maximum period of oscillation of
    the desired component of the time series, with 2 < s < e < infinity, or
    the desired frequencies, with 0 < s < e <= 1. couliari does not allow
    gaps within the observations of the time series.

Options

    s(#) and e(#) specify the minimum and maximum period of oscillation to be
        retained in the time series, either as the number of periods or as
        the frequencies expressed as fractions of pi. s(#) and e(#) are
        required. For quarterly data, common values are 6 and 32 periods
        (frequencies 1/16 and 1/3) , which preserve the components of the
        data with period between 1.5 and 8.0 years. For monthly data, common
        values are 18 and 96 periods (frequencies 1/48 and 1/9), which
        preserves the component of the data with period between 1.5 and 8.0
        years. For annual data, common values are 2 and 8 (frequencies 1/4
        and 1).

    stub(abbrev), which must be provided, specifies the "stub" from which new
        variable names will be created. Variables created by stub must be new
        variables. If the varlist contains time-series operators, the dots in
        their names are replaced by underscores so that the resulting new
        variables' names are legal.

Examples

    . webuse lutkepohl,clear

    . couliari investment, s(6) e(32) stub(FD)

    Same as above, expressing s() and e() as fractions of pi

    . couliari investment, s(1/6) e(1/3) stub(FDpi)

    Several variables

    . couliari investment income consumption, s(6) e(32) stub(filt)

    Time series operators

    . couliari D.investment, s(4) e(12) stub(fl)

    Application in a panel:

    . use http://fmwww.bc.edu/ec-p/data/hayashi/sheston91.dta,clear

    . drop if country>4

    . tsset

    . by country:couliari rgdppc, s(2) e(8) stub(fd) k(3)

    . egen double fd_sm = rowtotal(fd_rgdppc_sm_*)

    . drop fd_rgdppc_sm_*

    . egen double fd_res = rowtotal(fd_rgpdpc_*)

    . drop fd_rgdppc_*


Author

    Jorge Pérez, Inter-American Development Bank
    jperezperez@iadb.org

References

    Baxter, Marianne and Robert G. King (1999). "Measuring Business Cycles:
    Approximate Band-Pass Filters for Economic Time Series", Review of
    Economics and Statistics 81(4), pp. 575-593.

    Corbae, Dean, Sam Ouliaris and Peter C.B. Phillips (2002). "Band Spectral
    Regression with Trending-Data", Econometrica 70 (3), pp.  1067-1109.

    Corbae, Dean and Sam Ouliaris (2006). "Extracting Cycles from Non
    stationary Data", Econometric Theory and Practice: Frontiers of Analysis
    and Applied Research Cambridge Cambridge and New York.

    Ouliaris, Sam (2009) "Ideal Band Pass Filter For
    Stationary/Non-Stationary Series"
    http://forums.eviews.com/viewtopic.php?f=15&t=1513

Acknowledgements 

    This command was translated from Eviews code in Ouliaris(2009). The stata
    syntax was drawn from the commands bking and hprescott by Christopher F.
    Baum and Martha Lopez.

Disclaimer

    This program is provided without warranty of any kind. The author is not
    responsible for any cost derived by the usage of this program.

Also see