The following is in response to Joe Tomlinson’s article,A New Tool to Calculate Long-Term Care Needs, which appeared last week:
Dear Editor,
I have a question on the important topic of LTC costs and planning: What confused me in the article was that the charts he presents show 25th percentile costs for a 65-year-old couple of $22,823. I was trying to figure out what that number actually means – specifically whether it is a conditional or unconditional value. My understanding based on Congressional reports and other sources is that two-thirds of those 65 and older have zero LTC costs. Consequently, an unconditional distribution of costs should show zeros through the 50th percentile and above. However, I realize that the Congressional report figures may represent a cross section of the population at a given time, and may not be the best figures for estimating the probability of needing LTC. If Joe could clarify for me and explain what I'm missing, I'd be very grateful.
Eric Stubbs
Global tactical portfolio manager and economist
Joe Tomlinson responds:
Thanks for writing. As for probability of needing long-term care, the figure I've seen quoted most often is from the National Clearing House for Long-Term Care Information, which is part of the U.S. Department of Health and Human Services, and that says 70% of individuals age 65 will need some amount of long-term care in the future. The figures in the first chart of my article were unconditional and roughly consistent with the 70% figure, although Jack Paul's modeling is much more fine-tuned than using a rough number like 70%. Note that my figures were for a couple so if each member had a 70% chance of needing some care, that's a 30% chance of not needing care and about a 9% chance of neither member of the couple needing care--30% x 30% = 9%. (The actual percentage of the 30,000 Monte Carlo runs not needing care came to 8.7%, which seemed reasonable to me.)
I think it's likely that cross section numbers like the "2/3 of those 65 and older have zero LTC costs" understate probabilities of needing care, because even those who need care will typically spend only a small portion of their retirement years requiring LTC. So you can have a high probability that someone 65 will need care in their lifetime, but a much smaller number for the share of the retired population requiring care at any given time.
There is a lot of conflicting information in the press about probabilities and potential durations of long-term care needs. These sketchy statistics make it difficult for advisors to have informed discussions with clients and make plans for how to deal with possible LTC needs. What Jack Paul did for his PDRP Plus model was to study a variety of sources of data, and build the model from the most reliable sources.
I hope this answers you question. I appreciate your interest in this topic.
