{smcl}
{* 23oct2004}{...}
{hline}
help for {hi:cfitzrw} SSC distribution 30 June 2006
{hline}
{title:Apply Christiano-Fitzgerald Random Walk band pass filter to time series}
{p 8 17}{cmd:cfitzrw}
{it:varlist}
[{cmd:if} {it:exp}]
[{cmd:in} {it:range}]
{cmd:,} {cmdab:plo(}{it:#}{cmd:)}
{cmdab:phi(}{it:#}{cmd:)}
{cmdab:stub(}{it:abbrev}{cmd:)}
{p 4 4}You must {cmd:tsset} your data before using {cmd:cfitzrw}; see help {cmd:tsset}.
If a panel calendar is in effect, the filter can be applied if a single panel is specified
using if or in qualifiers, or with the {cmd:by} prefix. {p_end}
{p 4 4}{cmd:varlist} may contain time-series operators; see help {cmd:varlist}. {p_end}
{p 4 4}{cmd:cfitzrw} filters one or more time series using the Christiano-Fitzgerald
Random Walk band-pass filter described in Christiano and Fitzgerald (2003).
The {cmd:plo()} and {cmd:phi()} arguments specify the minimum period of oscillation and
maximum period of oscillation of the desired component of the time series, where
2 <= {it:plo} < {it:phi} < infinity.
{p_end}
{title:Options}
{p 4 8}{cmd:plo(}{it:#}{cmd:)} and {cmd:phi(}{it:#}{cmd:)} specify the minimum and maximum
period of oscillation to be retained in the time series, and must be given. For quarterly
data, common values are 6 and 32, 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, 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.
{p 4 8}{cmd:stub(}{it:abbrev}{cmd:)}, which must be provided, specifies the "stub" from
which new variable names will be created. Variables created by {cmd:stub} must be new
variables. If the {it:varlist} contains time-series
operators, the dots in their names are replaced by underscores so that the resulting
new variables' names are legal.
{title:Examples}
{p 4 8}{stata "webuse lutkepohl,clear" :. webuse lutkepohl,clear}{p_end}
{p 4 8}{stata "cfitzrw investment, plo(6) phi(32) stub(F)" :. cfitzrw investment, plo(6) phi(32) stub(F)}{p_end}
{p 4 8}{stata "cfitzrw investment income consumption, plo(6) phi(32) stub(filt)" :. cfitzrw investment income consumption, plo(6) phi(32) stub(filt)}{p_end}
{p 4 8}{stata "cfitzrw D.investment, plo(4) phi(12) stub(fl)" :. cfitzrw D.investment, plo(4) phi(12) stub(fl)}{p_end}
{p 4 8}{stata "use http://fmwww.bc.edu/ec-p/data/hayashi/sheston91.dta,clear":. use http://fmwww.bc.edu/ec-p/data/hayashi/sheston91.dta,clear}{p_end}
{p 4 8}{stata "drop if country>4":. drop if country>4}{p_end}
{p 4 8}{stata "tsset":. tsset}{p_end}
{p 4 8}{stata "by country: cfitzrw rgdppc, plo(2) phi(8) stub(SBY)":. by country: cfitzrw rgdppc, plo(2) phi(8) stub(SBY)}{p_end}
{title:Authors}
{p 4 4}Christopher F. Baum, Boston College, USA{break}
baum@bc.edu
{p 4 4}Martha Lopez, Boston College, USA{break}
lopezmo@bc.edu
{title:References}
{p}Lawrence J. Christiano and Terry J. Fitzgerald, The Band Pass Filter, International
Economic Review, 2003, 44(2), 435-465.{p_end}
{p}Pawel Kowal (2005). MATLAB implementation of commonly used filters,
http://ideas.repec.org/c/wpa/wuwppr/0507001.html{p_end}
{title:Acknowledgements}
{p 4 4}The Mata code of this routine was translated from MATLAB code made available by Pawel Kowal (2005).
{title:Also see}
{p 4 13}On-line: {help hprescott} (if installed), {help bking} (if installed), {help tsset}