In his October 22 blog post, Michael Kitces points out several of the problems associated with Monte Carlo modeling and determination of "safe withdrawal rates" based on assumptions about future experience that will not be realized. Mr. Kitces suggests that the solution lies in "reframing" the model outcomes. He says, "consider what happens if we actually call it a probability of adjustment, instead of a probability of failure. When we frame the outcomes as failures, the nature [sic] response from clients is to think up terrible images of what failure might look like, and then seek to avoid it at all costs. But when we frame the outcomes as “adjustments” it leads to very different – and much more productive – conversations instead, such as “How big would the adjustment be? When would I have to make the adjustment? How will I know when it’s time to adjust?”
He also expresses concerns about surpluses that are ignored in the safe withdrawal rate determination, saying, "it’s not just the probability of failure that’s misnamed. It’s also the probability of success, which is more like a probability of Excess. It’s the likelihood of having excess money left over, and sadly makes no distinction about how much will be left over! A Monte Carlo analysis in traditional retirement planning software treats having $1 left over the same as $1M and the same as $10M – they’re all “successes” – yet clients would react to this very differently. When you call it a probability of “excess” it again raises the question “how much of an excess are we talking about?” and a more productive conversation."
While I agree with Mr. Kitces' assessment of the problems, in my opinion, reframing the outcome is not the answer. The actuarial approach suggested in this website automatically provides valuable input for Mr. Kitces "productive conversations." As indicated in my previous post, retirees need to wean themselves off the safe withdrawal rate Kool-Aid and live with the fact that that sometimes their spending budget may increase or decrease in real terms from year to year, depending on actual investment experience and spending.