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Social Security Agency London Essay

1911 words - 8 pages

Social Security Agency London.
Linear Regression Model Analysi

Table of Contents
1. The Model Content ...................................................................... 2 1.1 1.2 1.3 2 What are the strengths of the model that is used? ...................................................... 2 What are the weaknesses of the model? ..................................................................... 2 How could the model be improved? ............................................................................ 3

The Modelling Process ................................................................... 3 2.1 2.2 2.3 The Modelling Process ...view middle of the document...

Moreover, the new forecasting model balances simplicity and accuracy effectively. The employment of only two input parameters makes it more user-friendly over the existing system where eight complex input parameters are used. The forecasts generated by the new simulation system were found to be within a 10% level of accuracy of the results produced by the existing model. The regression models derived for each of the five dominant salary grades explained at least 98.93% of the variation in payroll costs. Both of the predictors, namely “level of turnover” and “boxmark” distributions, were found to be quite influential in all the regression models through hypothesis testing. Therefore, the new modelling system was able to achieve its objective of reducing forecasting complexity while maintaining accuracy to a large extent.


What are the weaknesses of the model?

The most critical weakness of this model is that the ASD used historical data in building its forecasting model. There is no evidence that the relation between the inputs and outputs of the past data are also valid for the future.

The next weakness is the problem of extrapolation. In its runs, ASD changed the inputs for each grade within ‘realistic ranges’ or ‘extreme levels’ ’that had never occurred in the past’ (Kogetsidis, 2007). There is no guarantee that the future inputs will never go outside of those ranges.

ASD had already chosen three out of eight existing inputs according to their experimental assumptions. However, as it turned out later in the case, one other input out of the rest five inputs might have relatively high impact on the outcome. This indicates that the selection of the inputs to be examined had not followed the right procedure. And, ASD conducted this research in one of its six branches without examining the branch ASD chose represented the whole six branches.

Finally, this model cannot explain the variation i.e., statistical errors, fully. Since the models are made to understand the situation as simple as possible, we cannot expect the perfectness. However, ASD had to investigate whether the rest 1.07 % of the variation had important implications or not.

Page 2


How could the model be improved?

Input analysis should have been carried out on all the eight input parameters used in the existing model. Only three input parameters: spine flow propensities, level of turnover and boxmark distributions were considered in the new model to produce the output, i.e. the change in the average salary cost from the current year to the next. Also, the three input parameters chosen could have been further analysed using other statistical analysis methods, e.g. correlation, instead of just using a graphical method. This would have increased the accuracy of the relationships between the input parameters and the output.

Other qualitative or exogenous information should have been considered. For example in the choice of the five grades out of...

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