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difonzo1

Multivariate temporal disaggregation with transversal constraint

CALLING SEQUENCE

[y,res]=difonzo1(Y,x,z,ta,s,typemod)

PARAMETERS

Input

* Y = a (N x M) real vector

  ---> M series of low frequency data with N observations

* x = a (n x M) real vector

  ---> M series of high frequency data with n observations

* z = (n x 1) ---> high frequency transversal constraint with nz obs.

* ta = type of disaggregation

  -ta = 1 ---> sum (flow)

  -ta = 0 ---> average (index)

  -ta = i ---> i th element (stock) ---> interpolation

* s = number of high frequency data points for each low frequency data points

  -s = 4 ---> annual to quarterly

  -s = 12 ---> annual to monthly

  -s = 3 ---> quarterly to monthly

* typemod = model for the high frequency innovations

  -ypemod = 'wn' ---> multivariate white noise

  -typemod = 'rw' ---> multivariate random walk

 

Output

* y = High frequency estimate

* res = a results tlist with:

  - res('meth') = 'Multivariate difonzo'

  - res('typemod') = type of the model for the high frequency innovations

  - res('ta') = type of disaggregation

  - res('nobs_lf') = nobs. of low frequency data

  - res('nobs_hf') = nobs. of high-frequency data

  - res('pred') = number of extrapolations

  - res('s') = frequency conversion between low and high freq.

  - res('diff') = Degree of differencing

  - res('y') = high frequency estimate

  - res('y_lf') = low frequency data

  - res('indicator') = high frequency indicators

  - res('transversal') = data for the transversal constraint

  - res('y_dt') = high frequency estimate: standard deviation

  - res('resid') = high frequency residuals

  - res('resid_U') = low frequency residuals

  - res('beta') = estimated model parameters

  - res('sd') = standard deviation of the estimated model parameters

DESCRIPTION

Temporal disaggregation using the difonzo method of multivariate temporal disaggregation with transversal constraint (low level function that works only with matrices and where all options must be given a value).

EXAMPLE

[y,res] = difonzo1(Y,x,z,0,4,'rw')
// Provides quarterly disaggregation of (23x2) matrix Y (representing 2 annual data) with (92 x 2) matrix x (representing 2 quarterly series)
// and transversality constraint represented by the (92x1) matrix z.
// Annual series are built by averaging quarterly series (4th argument is 0); the order of aggregation is 4 (fifth argument);
// residuals are assumed to follow a multivariate random walk (sixth argument is 'rw').

AUTHOR

Eric Dubois 2005

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