LSC South East - lsc.gov.uk - Learning and Skills Council

At various stages of the calculations we need to ensure consistency, e.g. that the
participation rates estimated for districts in 2006 are consistent with the published
overall participation rates for the counties, or that the projections for full-time, parttime,
etc. participation rates add up to the overall rate in each year of the forecast.
In effect, this means that one category must always be a residual, i.e. the amount
needed to be consistent with the total for all categories. This implies that any
errors in estimating one category will have corresponding off-setting errors in
another. A further implication is that we can generally have greater confidence in
the estimate of a total than in the estimate for a component category. This should
be borne in mind when interpreting the results of the model. We now explain in
more detail each stage of the forecasting procedure.
1. Estimating district participation rates in the South East in 2006
After some experimentation with different methods we decided the best approach
is to use information from the ILR and PLASC databases. Using these, we obtain
a count of the numbers of full time and part time learners (in both schools and
colleges) in each district. Dividing these by our population estimates gives an
estimate of the district participation rate. Our method can be verified by the fact that
it gives estimates for counties and unitary authorities which are close to those
reported by the DCSF. We can therefore have some confidence that the method
provides reasonably accurate estimates at the district level also.
Hence the participation rate for a district can be calculated as
p
p
district = county
2006
2006
p
p
district
county
PLASC
This is probably best explained by example. To calculate Aylesbury Vale’s
2006
participation rate, we first take the published rate for Buckinghamshire ( p county =
0.720). We then look at the PLASC and ILR data which suggest the district
participation rate for Aylesbury Vale is 0.635 and the county rate is 0.692. Note that
there is a slight discrepancy between the DCSF figure and the PLASC figure for the
county. The PLASC/ILR data suggest that Aylesbury Vale’s figure is about 92% of
the county figure (0.635/0.692). We therefore estimate the district participation rate
0.
635
as 0 . 72
= 0.
660 or 66%. This gives us a figure which is consistent with the
0.
692
published DCSF figure for the county. (This example is for 16 year olds in full time
education.)
Note that, if the DSCF and PLASC/ILR data give the same county participation rate,
the estimated participation rate we use is precisely the PLASC/ILR figure. We only
make adjustments because there are discrepancies between the two sources, and
these are generally quite minor.
Applying this method to all districts in turn, we can estimate the overall district
participation rates. Note that, although the PLASC.ILR data covers full time and part
time learners, it does not include the independent sector, which is included in the
DCSF figure. We assume the full time rates as calculated from PLASC/ILR are the
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