[R-SIG-Finance] Time series temporal disaggregation (or: going from low frequency to higher frequency)

[John Frain]

Several Official Bodies (Central Banks Eurostat etc) use Chow-Lin
interpolation to derive  quarterly data from annual or monthly from
quarterly.  It may be the case that the higher frequency data have
only recently been produced.  I don't know if anyone has produced any
R routines but if you google "Chow-Lin interpolation" you will
probably find implementations in Matlab or Gauss that should transfer
easily to R.  My implementation in RATS can  be accessed at
ideas.repec.org/p/cbi/wpaper/2-rt-04.html.  This contains an
explanation of the methodology and references to the original papers.

The research section of the Eurostat website also contained some
relevant material.

Best Regards

John

2009/10/30 Brian G. Peterson <brian at braverock.com>:
> Axel Leroix wrote:
>>
>> Hi,
>> This is a newbie question. I would to be able to convert annual time
>> series of flow data into quarterly data. I wonder if there is any existing
>> R-function which permits to do it? In what package ?
>>  I the archive, i found that some poeple speak about "tempDis" package for
>> performing time series temporal disaggregation, but when I try to download
>> it I can not found it in the list of proposed packages.  Thank you in
>> advance for your help.
>>
>
> Well, as discussed multiple times on this list, going from annual (or any
> lower frequency) data to quarterly (or any higher frequency) data is
> questionable at best.  Think data snooping or look-ahead bias in your
> modeling.
>
> Going the other direction, from say daily (or any higher frequency)  to
> monthly (or any lower frequency) , is easily accomplished with to.period for
> price/value data or Return.cumulative for returns data.
>
> If you really do want to go in the black-magic direction of going from
> annual to quarterly, first make sure that the "annual" data was not first
> reported as monthly data or quarterly data (this is true for almost all
> macroeconomic series) and then go back to the source data at a higher
> frequency.
>
> If even this is not possible, and you insist on the highly dubious practice
> of taking an annual number and turning it into four quarterly numbers, see
> the various na handling methods provided by the zoo package, most likely
> na.approx or na.spline.
>
> Regards,
>
>    - Brian
>
> --
> Brian G. Peterson
> http://braverock.com/brian/
> Ph: 773-459-4973
> IM: bgpbraverock
>
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-- 
John C Frain, Ph.D.
Trinity College Dublin
Dublin 2
Ireland
www.tcd.ie/Economics/staff/frainj/home.htm
mailto:frainj at tcd.ie
mailto:frainj at gmail.com