help sbbq
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Title

    sbbq -- Identify turning points in time series using the BBQ algorithm
        (Harding and Pagan, 2002)

                                        
Syntax

        sbbq [varname] [if] [in] [, options]

    options               Description
    -------------------------------------------------------------------------
      window(#)            window over which local minima and maxima are
                            computed; default is window(2)
      phase(#)             minimum phase length; default is phase(2)
      cycle(#)             minimum cycle length; default is cycle(5)
    -------------------------------------------------------------------------
    by is allowed; see [D] by.


Description

    sbbq generates a new variable "varname_point".  Observation j of the new
    variable equals 1 if varname[j] is a peak, -1 if varname[j] is a trough,
    and 0 otherwise.

    The algorithm identifies potential turning points as the local minima and
    maxima in the series. Candidate points must then satisfy two conditions:
    phases are at least p quarters long, and complete cycles are at least c
    quarters long.


Options

    window(#) determines the number of observations # on both sides over
        which local minima and maxima are computed.  Following Harding and
        Pagan (2002), the default is # = 2.

        A candidate peak is an observation j for which
        varname[j - #], ..., varname[j - 1] < varname[j] >
        varname[j + 1], ..., varname[j + #].

        A candidate trough is an observation k for which
        varname[k - #], ..., varname[k - 1] > varname[k] <
        varname[k + 1], ..., varname[k + #].

    phase(#) imposes that every phase is at least # quarters long. In
        business cycle analysis, a phase is an expansion or a contraction.
        The default is # = 2.

    cycle(#) imposes that every cycle is at least # quarters long. A cycle is
        the period between two peaks or two troughs. The default is # = 5.


Remarks

    In their article, Harding and Pagan (2002) use the insights of Bry and
    Boschan (1971) to produce a business cycle dating algorithm based on
    quarterly data. BBQ stands for "Bry and Boschan Quarterly".
    Nothing prevents the use of this program with monthly data, provided that
    the appropriate options (window, phase, and cycle) are specified.


Example

    . sysuse gnp96, clear

    . generate lgnp = log(gnp96)

    . sbbq lgnp, w(2) p(2)

    . egen min_lgnp = min(lgnp)

    . list date lgnp_point if inlist(lgnp_point,1,-1)

    . tsline lgnp ||
        pcspike min_lgnp date lgnp date if lgnp_point==1 ||
        pcspike min_lgnp date lgnp date if lgnp_point==-1,
        lpattern(dash) leg(order(2 "Peaks" 3 "Troughs"))
        ti("Turning Points in US LogGNP")

                   
Author

    Philippe Bracke, London School of Economics, UK
    p.bracke@lse.ac.uk

                
References

    Bry, G., and C. Boschan (1971).  Cyclical Analysis of Time Series:
        Selected Procedures and Computer Programs, NBER, New York.

    Engel, James (2005). Business Cycle Dating Programs,
        http://www.ncer.edu.au/data

    Harding, D. and A. Pagan (2002).  "Dissecting the cycle: A methodological
        investigation," Journal of Monetary Economics, 49: 365–81.


Acknowledgement

    The GAUSS code made available by James Engel (2005) was essential in
    helping the author writing this program.
    John C. Bluedorn and Andrea Pescatori provided very useful suggestions to