OK - doing this helped for the Time Series project, so I'm going to start off again.

Here's my idea of what we have to do if you've chosen the Dummy Variables project:

1. Run through the examples starting on Page 20 of the project template found in: http://www.neas-seminars.com/discussions/shwmessage.aspx?ForumID=171&MessageID=5014. This should make you familiar with how inflation affects the residual plot. Essentially you should test with large discrete changes to the inflation rate (this should cause a V-shape in the residual plot), constant (continuous) inflation (this should result in a smooth curve), and increase in the stochasticity ie - sigma (random fluctuations should "obscure" the residual plot - in english, this means that the y-values will be more dispersed at each x-value).

[NEAS: Discrete change ÿ V-shape or upside-down V-shape

Continuous change

ÿ parabolic shape

Use a low

σ, such as 1%, to see the expected shape of the residual plot. Use a higher σ, such as 10%, 20%, or 50%, to see the effects of stochasticity.]

2. Throw in dummy variables - at this point you should make the decision of whether or not you are going to use a discrete change or continuous change inflation rate (choose only one), we should only use low sigmas. Your analysis will differ if you choose discrete or continuous, each are explained in the above project template on pages 24 and 25 respectively.

[NEAS: If the residual plot has a V-shape or an upside-down V-shape, use a dummy variable of D × (X₂ – k), where k is the value of X₂ at the apex or nadir of the V.]

3. After your dummy variable analysis you should have another residual plot (of course you will need to do the regressions with the Excel add-in) and if all worked correctly the plot should have three lines (residuals vs x₁, residuals vs x₂, and residuals vs x₃) all horizontal. You should probably do some verification that your plots are correct using the methods described on page 21 of the project template.

[NEAS: Plot against X₁ and X₂.]

4. Write-up - follow the criteria outlined in the project template on page 26.

[NEAS: The write-up is important; the SOA wants to see that candidates understand how to use the statistical concepts.]

Joey,

Can you clarify what you suggest to do in step 2.  Specifically what do you mean by "Throw in Dummy Variables"?

 

Thanks