How to stimulate rapidly changing life circumstances?

The planner offers plenty of flexibility and can handle many complicated real-world scenarios, but sometimes it can be tough to figure out how to do it. Check out this forum for discussion of how to model things like selling a house, long-term care expenses, and much more.
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oniasiu
Posts: 1
Joined: Wed Feb 23, 2011 11:41 am

How to stimulate rapidly changing life circumstances?

Post by oniasiu » Wed Feb 23, 2011 11:47 am

Hello,

I love the monte carlo stimulator. I was wondering if it was possible to stimulate graduating from professional school with a estimated 4-5 year additional training where I am still eligible for full roth ira deposit and then going to subsequent ineligibility except for a deferred tax plan and taxable account only? By which I mean say from 24 to 34, I can contribute to a roth but then from 35 to retirement at 65 I can only contribute to a deferred tax plan (TSP) and taxable accounts only. Thank you for the response in advance.

jimr
Posts: 557
Joined: Thu Feb 28, 2008 6:48 pm

Re: How to stimulate rapidly changing life circumstances?

Post by jimr » Wed Feb 23, 2011 2:45 pm

I think the best way to model this type of thing is to use the "additional inputs" feature of the planner.

When you click the additional inputs button on the upper right side of the planner window, a popup window should appear that allows you to be very specific with planner inputs. For each type of cash flow (eg taxable savings, tax deferred savings, retirement expenses, etc) you can enter and annual amount and a start and end year for that cash flow. For one-time items you can enter the amount with the start and end years set to the same year. Using this approach, I think you can model everything you describe.

The level of detail you're contemplating makes sense to me, but I'll supply one caveat though - Author Bill Bernstein mentioned in his Retirement Calculator From Hell series that a Monte Carlo result probably has a built-in error of at least 20% because of inherent uncertainty in the inputs to the model. That means that no matter how precise you are, statistically there's not much difference between an 80% probability of success and a 99% probability of success.

Jim

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