EXAMPLE
bounds() load(GROCERDIR+'\data\EtalCalInsee.dat'); [yhf,retal] = etalcalinsee('consameu','cammeu','bench=''consmmeu''','s=12','alpha=0.15') ; |  |  |
Disaggregation using Insee's method
[yhf,retal] = etalcalinsee(namey,arg1, ,argn)
namey= low frequency series
arg1,...,argn= strings that can be
.'alpha =xx' where w is significance level for the constant default 0.1, that is 10%
.'ny_prov =n' where n is the number of known annual data that are ignored in the diseggregation process
.'mod=''rw''' if the residuals are supposed to be a RW or 'mod=''ar''' if the residuals are supposed to be an AR(1) (default: model with maximum likelihood is chosen)
.'bench=''xxx''' where xxx is the name of the series the user wants to compare the result with (for instance to compare the method with another one)
.'noprint' if the user does not want to print the results
yhf= the disaggregated series
retal= a results tlist with:
- retal('meth') = 'Insee''s disaggregation'
- retal('lf y') = annual series
- retal('y estim') = annual transformed series (that is differentiated if residuals follow a RW, levle if not)
- retal('lf x') = a (N x 1) vector of annual data
- retal('x estim') = a (N x 1) vector of transformed annual data
- retal('x trim') = a (n x k) matrix of exogenous high frequency indicators
- retal('nobs') = # of observations in the regression
- retal('resid estim') = a (n x 1) vector of regression residuals
- retal('beta') = estimated coefficients of the annual regression
- retal('tstat') = t stats
- retal('pvalue') = pvalue of the betas
- retal('prescte') = boolean indicating the presence or absence of a constant in the regression
- retal('llike') = the log-likelihood
- retal('rho') = autcorrelation coefficient of residuals:
. if rho = ]-1,1[ then the model is estimated in levels
. if rho = 1 then the model is estimated in differences
- retal('trend') = trend
. retal('trend') = 1 if retal('prescte') = %t and rho = 1
. retal('trend') = 2 if retal('prescte') = %t and rho ~= 1
. retal('trend') = 0 in other cases
- retal('y last values') = provisional value for y (and therefore not used in estimation)
- retal('hf x') = a (n x k) matrix of exogenous high frequency indicators
- retal('high freq') = a scalar, the indicators frequency
- retal('freq ratio') = a scalar, the ratio of high to low frequency
- retal('aug lf x') = (N x l) matrix of regressors, including the constant or trend if necessary
- retal('aug hf x') = (n x l) matrix of regressors, including the constant or trend if necessary
- retal('lf yhat') = (N x 1) adjusted low frequency y
- retal('lf resid') = (N x 1) low frequency residual
- retal('forecasted lf resid') = low frequency residual extended to the incomplete year with the estimated model
- retal('hf resid') = high frequency residual in TS form
- retal('hf yhat') = high frequency adjusted y
- retal('prests') = boolean indicating the presence or absence of a time series in the regression
- retal('namey') = name of the y variable
- retal('namex') = name of the x variables
bounds() load(GROCERDIR+'\data\EtalCalInsee.dat'); [yhf,retal] = etalcalinsee('consameu','cammeu','bench=''consmmeu''','s=12','alpha=0.15') ; | | |