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fernandez1

Temporal disaggregation using the Fernandez method

CALLING SEQUENCE

[y,res]=fernandez1(Y,x,ta,s)

PARAMETERS

Input

* Y = a (N x 1) vector of low frequency data

* x = a (n x p) matrix of high frequency indicators (without intercept)

* ta = type of disaggregation:

  -  n=-1 (default) ---> sum (flow)

   - n=0 ---> average (index)

   - n=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

 

Output

* y = High frequency estimate

* res = a results tlist with:

  - res('meth') = 'Fernandez'

  - 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('p') = number of regressors (including intercept)

  - res('y') = high frequency estimate

  - res('y_lf') = low frequency data

  - res('indicator') = high frequency indicators

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

  - res('y_up') = high frequency estimate: sd + sigma

  - res('y_lo') = high frequency estimate: sd - sigma

  - res('resid') = high frequency residuals

  - res('resid_lf') = low frequency residuals

  - res('beta') = estimated model parameters

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

  - res('tstat') = estimated model parameters: t ratios

  - res('aic') = Information criterion: AIC

  - res('bic') = Information criterion: BIC

DESCRIPTION

Temporal disaggregation using the Fernandez method of multivariate temporal disaggregation (low level function with matrices only all parameters given).

EXAMPLE

load(GROCERDIR+'\data\xesp.dat')
[y,res] = fernandez1(Y,x,-1,4);
// If Y and X are taken from the database GROCERDIR+'\macros\grocer\db\xesp.dat',
// provides quarterly disaggregation of the (22x1) matrix Y
// (representing annual Spanih exportations) with the (88x1) matrix x.
// Annual series are built by summing quarterly series (3rd arg set to -1);
// the order of aggregation is 4.

AUTHOR

Eric Dubois 2005

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