The Ultimate Guide to Safe Withdrawal Rates – Part 10: Debunking Guyton-Klinger Some More

Last week’s post about the Guyton-Klinger Dynamic Withdrawal Rule only scratched the surface and we ran out of time and space. So, today we like to present some additional and detailed simulation data to present at least four areas where Guyton and Klinger are quite confusing and misleading:

  1. The ambiguity between withdrawal rates and withdrawal amounts. A casual reader might overlook the fact that the withdrawal amounts may very well fall outside a guardrail range. Inexplicably, Guyton and Klinger are very stingy with providing information on withdrawal amounts over time. There aren’t any time series charts of actual withdrawals in their paper.
  2. True, Klinger shows time series charts in this paper, but they are only for the median retiree. Does anyone else see a problem with that? The good old 4% rule did splendidly for the median retiree since 1871 so I haven’t really learned anything by looking at the median. Wade Pfau showed (with a Monte-Carlo study) that the GK rule has a 10% chance of cutting withdrawals by 84% after 30 years. It’s very suspicious that the inventors of the rule don’t show more details about the distribution of withdrawals. You could call this either deception or invoke Hanlon’s Razor and blame it on sloppiness and incompetence, and both options are not very flattering.
  3. The Guyton-Klinger rule (even with a 4% initial withdrawal rate) is very susceptible to equity valuations. Results look much worse if you look at the average past retiree with an elevated CAPE ratio (20-30).
  4. Guyton-Klinger doesn’t afford you to miraculously increase your withdrawal amount without any drawback. The higher the initial withdrawal amount the higher the risk of massive spending cuts in the future.

So, let’s get cranking! We present another case study, the dreaded January 2000 retirement cohort, and also subject the Guyton-Klinger Rule to the whole ERN retirement withdrawal simulation engine to see how all the different retirement cohorts going back to 1871 would have fared. That’s over 1,700 cohorts because we insist on doing our simulations monthly, not annually.

2000-2016 case study

We use real, CPI-adjusted returns for stocks and bonds up to December 2016 and then extrapolate equity and bond returns the same way we described in our initial SWR post and in the 2000-2016 case study. If you don’t like that extrapolation exercise up to December 2019, feel free to ignore those data points.

In the chart below we plot the CPI-adjusted real portfolio values under the static 4% rule and the three different Guyton-Klinger rules. The same parameters as last week. The 4% rule looks pretty grim, having exhausted more than 50% of its initial value and quickly depleting more even if equities continue with 6.6% real returns for the next few years.

Not so the GK rules: The 4% rule is now back to over 80% and could as well grow back to 90% of the initial value. The GK-5% rule is hanging in there pretty well and only the GK-6% rule looks a little bit shaky, in that it’s stuck at only 60% of the initial real value and not able to recover even if returns are average the above average priced S&P500 index.

swr-part10-chart02b
Portfolio values (adjusted for CPI) of the January 2000 retirement cohort: Static 4% rule vs. Guyton-Klinger Dynamic rules (20%/10%), 80%/20% S/B portfolios, rebalanced monthly. Year 17-20 (Post-2016) returns extrapolated with average stock returns and 0.5% real bond return.

So far, so good. But just as last week, the time series of actual withdrawal amounts looks not so appetizing. Specifically, all of the GK rules experienced a 50%+ drop in their actual withdrawals and by the end of 2016, they are still between 30 and 40% below their initial withdrawal amount. What’s worse, even with pretty decent extrapolated returns going forward in 2017-2019, withdrawals are stuck at that reduced level.

swr-part10-chart02
Real withdrawal values (per $100 of initial portfolio value) of the January 2000 retirement cohort: Static 4% rule vs. Guyton-Klinger Dynamic rules (20%/10%), 80%/20% S/B portfolios, rebalanced monthly. Year 17-20 (Post-2016) returns extrapolated with average stock returns and 0.5% real bond return.

So, Guyton-Klinger would have been a major letdown for the January 2000 retirement cohort. Especially the initial withdrawal rates above 4% would have caused large and permanent declines in real withdrawal amounts.

1871-2015 retirement cohorts: All CAPE regimes

Of course, we can go only so far with case studies, so we were curious how all the different retirees between 1871 and 2015 would have fared with the Guyton-Klinger rule. Probably better than the crazy worst case scenarios of 1966 and 2000, but how much better?

Let’s look at how the GK rule with a 4% initial withdrawal rate would have fared for retirees between 1871 and 2015. This is for all retirees regardless of initial CAPE Ratio. Also, we don’t want to show just the median but also some left tail stats, namely the minimum withdrawal, the 10th percentile and the 25th percentile. See chart below:

swr-part10-chart03
Distribution of real, CPI-adjusted withdrawal amounts using Guyton-Klinger for 1871-2015 retirement cohorts: 4% initial withdrawal, 30-year retirement, all CAPE regimes, 80% stocks, 20% bonds.

It turns out the median hardly sees any spending cut. The 25th percentile suffers a 20% cut and manages to recover back to 100% after 19 years. The 10th percentile sees a 40% cut and no recovery back to the initial CPI-adjusted amount within 30 years. Just for the record, I find the GK rule better than the static 4% rule because I’d rather cut my consumption by 40% with a 10% probability than run out of money with a 5% probability. But the tail risk scenarios are not appetizing. And we’re not talking about the 0.00001% tail event, but the 10% lower tail! I would consider myself quite risk averse and if the 10th percentile looks awful this rule would be a non-starter. Even folks who are less risk-averse should probably worry at least about the 25th percentile.

Last week we also pointed out the crucial distinction between real inflation-adjusted withdrawal amounts and the withdrawal rates. Withdrawal amounts can have wide swings, while withdrawal rates stay inside the Guyton-Klinger guardrails for the most part.

(side note: There is one exception namely when a market move is large enough that even the x=0.10 adjustment will not take the observed withdrawal rate back inside the guardrails and it takes two months of adjustments to accomplish that. So, don’t be surprised to see a very small percentage of months with rates outside the guardrails.)

In any case, let’s look at the distribution of (real) withdrawal amounts and withdrawal rates over the entire 360 months and all 1,700+ cohorts, see chart below. The top portion is what we really care about, how much we can consume, specifically the percentage of observations that fall into various buckets. The bottom portion is the less-informative figure because that % is multiplied by the current portfolio value, i.e., a moving target. Also, I added three dividers to split the buckets into four sections: Below the lower guardrail (<3.2% in this example), between the lower guardrail and the initial withdrawal rate (3.2-4.0%), between the initial withdrawal amount and the upper guardrail (4.0-4.8%) and above the upper guardrail (4.8%+).

swr-part10-chart04
Distribution of real, CPI-adjusted withdrawal amounts (top) and rates (bottom) over the entire 30-year window using Guyton-Klinger for 1871-2015 retirement cohorts: 4% initial withdrawal, all CAPE regimes, 80% stocks, 20% bonds.

The good news: Guyton-Klinger will likely generate higher withdrawal amounts than the initial. 48.1% of the time we’d even be above 1.2-times above the initial amount. That’s as expected because we already know that the naive 4% rule would have created massive over-accumulation of wealth and the GK rule simply harvests the excess gains.

But GK also forces your withdrawals to below the initial value with a significant probability. 15% probability to withdraw less than 80% of the initial (again, there ‘s no guardrail for the withdrawal amounts, only for the rates). 20.9% probability of falling into the 0.8 to 1.0-times the initial amount.

1871-2015 retirement cohorts: CAPE between 20 and 30

As we pointed out in our post on equity valuations, it’s risky to average over all equity valuation regimes when we already know that today we’re in a world of much more expensive equities relative to earnings. So, let’s run the 4%-GK rule only in the months when we had Shiller CAPE ratios of between 20 and 30 (Current CAPE is at 28!).

The chart with the withdrawal amounts doesn’t look so appealing anymore. Sure, the median is hanging in there pretty well; it dips slightly below 4, but recovers by year 16 only to increase substantially after that to more than 50% above the initial withdrawal amount by year 30. Guyton-Klinger did exactly what it was designed to do: scale up the withdrawals when the market cooperates.

swr-part10-chart05
Distribution of real, CPI-adjusted withdrawal amounts using Guyton-Klinger for 1871-2015 retirement cohorts: 4% initial withdrawal, 30-year retirement, CAPE between 20 and 30, 80% Stocks, 20% Bonds.

But the less fortunate cohorts do much worse. The 25th percentile suffers about two decades of 25% decline of purchasing power. The 10th percentile drops to around 50% below for an entire decade. Of course, both recover back to their original withdrawal amounts but only after 26 and 29 years after retirement, respectively. Ouch!

The same distribution chart as before, see below. You now have a higher than 50% chance of consuming less than the original amount, even a 23.5% percent chance of consuming less than 0.8-times the original amount. All the while, of course, the withdrawal rates stay nicely inside the GK guardrails.

swr-part10-chart06
Distribution of real, CPI-adjusted withdrawal amounts (top) and rates (bottom) over the entire 30-year window using Guyton-Klinger for 1871-2015 retirement cohorts: 4% initial withdrawal, CAPE between 20 and 30, 80% Stocks, 20% Bonds.

What if we increase the withdrawal rate to 5%?

Well, the GK rule was invented to increase the initial withdrawal rate, so let’s see what happens when we push the initial annualized withdrawal to 5% of the portfolio. In the chart below we see that not even the median withdrawal amount can keep up. It drops by a moderate amount, 18% below the initial but it takes almost a quarter century to get back to the initial withdrawal amount. Now even the 25th percentile faces a 50% drop in withdrawals and only recovers after 30 years. The 10th percentile saw a close to 60% drop in consumption and no recovery within 30 years. Not a pretty picture.

swr-part10-chart07
Distribution of real, CPI-adjusted withdrawal amounts using Guyton-Klinger for 1871-2015 retirement cohorts: 5% initial withdrawal, 30-year retirement, CAPE between 20 and 30, 80% Stocks, 20% Bonds.

The same distribution chart as above, but now looking even grimmer. We spend about one-third of the time withdrawing less than 0.8 times the initial amount, one-third of the time between 0.8 and 1.0 times the initial amount and another one-third above the “promised” 5%. Not a very pretty picture. Does anyone still claim that we can hack our initial withdrawal rate to 5% or more in today’s CAPE regime?

swr-part10-chart08
Distribution of real, CPI-adjusted withdrawal amounts (top) and rates (bottom) over the entire 30-year window using Guyton-Klinger for 1871-2015 retirement cohorts: 5% initial withdrawal, CAPE between 20 and 30, 80% Stocks, 20% Bonds.

Another reason we’re no fans of Guyton-Klinger: It’s a “dumb” rule

Ok, to be sure, I’m not saying that Messrs. Guyton and Klinger or the folks who are using the rule are dumb. I’m sure they are all very smart individuals. I’m just saying that the GK method leaves me just as clueless about what’s a safe and appropriate withdrawal rate than before I started working on this topic. We saw above that the rule is quite susceptible to the equity valuation regime (just like the dumb static 4% rule).

To see how fundamentally “dumb” the GK rule actually is, let’s try to do the following thought experiment. Imagine we start GK with a withdrawal rate that’s clearly way too low, say 2% p.a. Nobody has ever depleted a portfolio with such a low target withdrawal rate. In fact, even your truly, your crazy cranky Uncle Ern curmudgeon would not argue for a withdrawal rate lower than 2%. Why would anyone cut the withdrawals below the initial amount? It’s completely uncalled for? But that’s what happens in a non-trivial percentage of cohorts, see chart below:

swr-part10-chart09
Distribution of real, CPI-adjusted withdrawal amounts using Guyton-Klinger for 1871-2015 retirement cohorts: 2% initial withdrawal, 30-year retirement, all CAPE regimes.

True, you’d eventually withdraw much more. There’s a close to 50% chance of a 60%+ rise in the withdrawal amount, but you’d also have a 20% chance of withdrawals falling below the initial amount. That’s unnecessary!

swr-part10-chart10
Distribution of real, CPI-adjusted withdrawal amounts (top) and rates (bottom) over the entire 30-year window using Guyton-Klinger for 1871-2015 retirement cohorts: 2% initial withdrawal, all CAPE regimes.

Conclusion

For full disclosure, we say it again: We like the Guyton-Klinger Rule slightly better than a naive static withdrawal policy like the 4% rule. But Guyton-Klinger suffers from the exact same problems as the 4%: It’s not safe. You replace the small risk of running out of money with the 4% rule with a moderate risk of large spending cuts throughout many years of your retirement with Guyton-Klinger.

As if Guyton-Klinger wasn’t already bad enough with a 4% initial withdrawal rate, jacking up the initial withdrawal rate to 5% or more as GK recommend, especially in today’s environment of expensive equities and low bond yields, would be particularly irresponsible. It’s a bit like sending a novice skier down a double black diamond slope. The helmet (=equivlanet of the guardrails) will likely ensure the poor guy won’t kill himself, but it won’t be a pleasant ride. For us, a dynamic withdrawal rule would have to be a lot smarter than Guyton-Klinger!

Thanks for stopping by today! Please leave your comments and suggestions below! Also, make sure you check out the other parts of the series, see here for a guide to the different parts so far!

Title Picture Source: Pixabay.com

52 thoughts on “The Ultimate Guide to Safe Withdrawal Rates – Part 10: Debunking Guyton-Klinger Some More

  1. Wow, interesting analysis. Beautiful charts! But if you don’t like the regular 4%-rule and Guyton-Klinger is no good what are the alternatives? What would you recommend in retirement? What would you do in your own retirement and what do you recommend for others who are maybe not as tech savvy as you?

    1. Thanks! Great question! I would start with a slightly lower withdrawal rate, say 3.5% and not 4%. I also the rule based on the Shiller CAPE earnings yield. First, it actually gives you some guidance as to what the initial withdrawal rate should be and then subsequently, it tells you how to adjust the withdrawal amounts in response to market swings.
      One caveat, though: Right now the Shiller earnings yield is very low. So using a widely used rule 1%+0.5*1/CAPE would give you a measly withdrawal rate of only 2.8%. Maybe play with the parameters on cfirecim and see which parameterization gives you an acceptable initial withdrawal rate and has relatively stable payouts in the simulation.
      And: needless to say, we will do a post on the CAPE rule in the future!
      Cheers!

  2. ERN, great work once again.

    In respect of the results published by Guyton Klinger and the lack of critical detail, as an alternative explanation to Hanlon’s Razor I would submit Occam’s Razor; the simple explanation being that if the guys that developed the model benefit commercially from having their names associated with it, then data that undermines their case would be inconvenient. So all we need ask is how likely is it that they would have found similar results during their tests as you found from yours. If they didn’t, then their tests were worryingly inadequate, if they did, then their paper was selective in its reporting of the results. Not great however you look at it, is it?

    Thank you for putting the GK model to an independent test.

    After reading your previous analysis I tested simple SWR and Guyton Klinger rules in Excel using expected returns expectations and standard deviation and running Monte Carlo analysis thereon. The results confirm your findings.

    Also thank you for including gold and cash as asset classes in your spreadsheet – a great enhancement.

    1. Hi WN! Thanks! That’s exactly my thinking: There is no good alternative: either they didn’t think about the distribution or they did but didn’t show it. Hey, if it brings business to their firm, why bother to mention the side effects. 🙂
      That’s great that you replicated the large drawdowns in a Monte Carlo study. Good to know that two methods yield similar results!!!
      Have fun with the Gold and Cash asset returns. I played around a bit and found that gold can improve the fail-safe WRs. A little bit. At the margin. Gold worked well both in the 70s and the 2000s. Definitely food for thought!

  3. I have a very different experience around G-K. I’ve played with the framework in cFIREsim, and I like it a LOT. They key for me was playing around with the parameters to get a *far* better result than you see with their typical suggested parameters. Perhaps this is a modification to the original G-K, but it’s a fairly simple one. cFIREsim offers a guardrail that is relative to the initial portfolio, not the future values. This keeps the withdrawals from falling below a reasonable level and still somewhat outperforms a plain withdrawal plan.

    Also, tweaking the parameters allows for a lot of interesting variations.

    I’ve found that using parameters which won’t raise your withdrawal without being in a very safe zone, but will raise it significantly, with ones that will cut only by a little (1-2%, so basically just not increase with low inflation or a bit less than moderate to high inflation), result in portfolios with very high success rates over 60 years. I used Exceeds 10 cut 2, Fall 40 Raise 8 with 4% initial and a 3.5% (of initial inflation adjusted) downside guardrail, no upside guardrail. This resulted in two failures (1906) at year 43, and 1902 at year 59, with *no* withdrawals ever below 3.5% inflation adjusted. It also resulted in roughly 2/3 of the portfolios increasing by year 20 and onward. The median withdrawal was nearly 5% of initial for years 20-40 and over 6% of initial for years 40-60.

    I think for my own purposes, using a slightly smaller initial withdrawal rate with 3.5% initial, hard 3.25% downside guardrail (again, of initial portfolio after inflation adjustment). Exceeds 50 cut 1, Fall 20 raise 5. This gave a median of (all percentages of initial portfolio) 3.8% first 20 years, 5.5% y20-40 and 7% y40-60. No failures, no paths even *close* to failure (smallest portfolio 35% of initial inflation adjusted), so unlikely that a month by month with the same data would show a failure. Something like 75% of paths had an increase from initial in y20 and beyond. Dropping at some point to the guardrail was about a -1sigma result, so around 15% of the time in y20+.

    I feel like that’s pretty good too. I think incorporation CAPE could probably add something here, but I’m not sure that these plans are actually inferior to a pure CAPE strategy at all.

    My take — if you consider G-K as a *framework* and play with the parameters intelligently, you can get paths that work *very* well and play into our hedonic impulses (be conservative about upping, rarely retrench and when doing so, keep it light enough that we might not actually notice (lots of early retirees don’t increase their budgets with inflation in retirement). If you look only at the common suggestions for those parameters, I agree with your analysis completely — there’s *way* too much variance. But it’s designed to be a framework. IMO that’s the whole point of their work, and seeing it that way, I’m impressed. I think G-K deserves a rework with this in mind.

    1. Thanks for your reply! What equity/bond share did you use in your simulations? It doesn’t really matter because your claim that GK “works” over 60 years is incorrect, both for the 75%/25% default setting as well as for all other stock/bond weights I tried.

      very high success rates over 60 years. I used Exceeds 10 cut 2, Fall 40 Raise 8 with 4% initial and a 3.5% (of initial inflation adjusted) downside guardrail, no upside guardrail. This resulted in two failures (1906) at year 43, and 1902 at year 59, with *no* withdrawals ever below 3.5% inflation adjusted. It also resulted in roughly 2/3 of the portfolios increasing by year 20 and onward.

      You conveniently ignore the 1965/66 episode. Because you pick 60-year windows, the latest start date is 1957 (or maybe 1958). Small tip: use the same parameters but with a 50-year horizon (set retirement year = 2017, end = 2066). You’ll see that most starting dates in the mid-1960 run out of money within 50 years. And thus, they will not last for 60 years either. I used 75/25 (default setting), 60/40, 50/50, 80/20, 100/0 but I’m pretty sure everything else will run out of money as well.

      using a slightly smaller initial withdrawal rate with 3.5% initial, hard 3.25% downside guardrail (again, of initial portfolio after inflation adjustment). Exceeds 50 cut 1, Fall 20 raise 5. This gave a median of (all percentages of initial portfolio) 3.8% first 20 years, 5.5% y20-40 and 7% y40-60. No failures, no paths even *close* to failure (smallest portfolio 35% of initial inflation adjusted),

      Same as before. You will run out of money with 1965 and 1966 start dates. Believe me, there is no way to make this Guyton-Klinger safer than it is. But just for the record: Your “safe” rule with 3.5% initial and 3.25% lower fixed guardrail is pretty much exactly what I propose personally, see the remaining parts of my SWR series. That would survive in most cases (but still not in 1965/66, so you need some additional downside flexibility). And then using a GK style method to walk up the withdrawals is not a bad idea either. My main criticism of the GK rule was that some uninformed folks are spreading the myth that GK can somehow make the SWR higher than 4%. You showed to me that even with 3.25-3.5% it’s not entirely safe. I generally like the rules-based approach but still prefer the CAPE-based rule.

  4. You really make it seem really easy along with your presentation but I in finding this topic to be really one thing that I think I would by no means understand. It sort of feels too complex and extremely extensive for me. I’m taking a look ahead in your next submit, I’ll try to get the dangle of it!

  5. Love your scrutinizing and depth of analysis! Great stuff. That said….

    In ALL of your analyses in this series you seem to be erroneously stuck on the percentage of the initial corpus amount that remains after running these scenarios for a few decades – e.g. hereinabove with 20 years. And you keep drawing negative conclusions such as one is “only left with 60% of the initial investment”.

    But so what? As an early retiree at 47, after 20 years I’m fine with having “only” 60% of my initial investment remaining. I only have another 20 years to go. Not to mention Social Security. So it seems you have an inherent bias against depleting ANY percentage of the initial corpus of funds after ANY period of time, even many decades.

    But pretermitting those who are leaving money behind after death, it is expected and completely acceptable to have a greatly reduced portfolio after 20-30 years.

    What am I missing?

    1. Thanks. You are missing multiple things.
      I have explained, in great detail, how to properly take into account:
      1) future cash flows such as Social Security and Pensions: Parts 4 and 17
      2) capital depletion vs. capital preservation: I guess all parts, but especially part 2
      I’ve explained how to do your own SWR analysis taking into account those additional personal, idiosyncratic factors like pensions and different final value targets: Part 7 and especially Part 28.
      I’ve also done case studies for people:
      https://earlyretirementnow.com/2018/01/17/ten-lessons-from-ten-safe-withdrawal-rate-case-studies/
      with exactly those issues and I have recommended a higher than 4% SWR initially with exactly the aim of (potentially) depleting the portfolio a little bit just in time when Social Security and pensions kick in.

      However, when I did the Guyton-Klinger study here (and many other facets of the SWR analysis like Prime Harvesting, Glidepaths, etc.) I like to use a more generic numerical example. If you want to translate those calculations back to an actual person, 47 years old, the wife is 42, Social Security income of $17,589.56987546784 at age 69, bequest target of $560,698, etc. then it’s your job, not mine to make the necessary adjustments. Maybe all of this would have given you a SWR of 4.355%. But then the main message of this post (and Part 9) still stands: a Guyton-Klinger method is no panacea. If you retire at the wrong time you’ll potentially face long and deep cuts in your withdrawal amounts. But the main message is much easier to see without too many loose parts.

      Also for the record, I stand by the main message that over a 50+ year retirement horizon, you cannot afford to lose 40% after 20 years. Very similar to the (mortgage) amortization math, you can afford only very little principal loss over the first 10-20 years, just like you’d pay down only very little principal during the first third or half of the mortgage.

      1. Thanks so much for the prompt and thoughtful reply ERN. Speaking of unique situations and idiosyncrasies, and putting aside G-T for the moment, I do have one such factor/future event that is fairly idiosyncratic to me – but not so much so that others won’t likewise experience it or something similar to it, and I’m surprised/disappointed it hasn’t been addressed more often in the FIRE community.

        In my case I am referring specifically to a future substantial windfall in the form of life insurance proceeds from a second to die policy on my parents’ lives (I am fortunate in that I am an only child and both the owner, trustee (it’s in a trust) and sole beneficiary of same). So while there is a 100% chance I (or my estate if I pre-decease them) will eventually receive those (non-taxed:) funds, it is of course impossible to say exactly when. However, based on mortality tables and the like, I know with quite high certainty that it will (sadly) occur in the next fifteen years (their combined age is 160).

        I know some of the more advanced retirement calculators can factor in this kind of thing, but they seem sort of generic and I would love to have you take a gander at my particular numbers and situation as you mentioned having done for others. I basically treat it as having a reduced retirement horizon/need of only 15 years max, as the amount is substantial enough (for my spending habits) to almost certainly provide me with more money than I will need going forward, even factoring in inflation and even if it isn’t invested and does not grow. I am, however, now responsible for paying the future policy premiums – and due to parents advanced age now the premiums have recently increased substantially and may amount to up to $15K/year due to rising mortality charges (while I was able to determine the $15k max after much wrangling with insurer to finally obtain an accurate “in force ledger”, how much the below $15k it could be is impossible to determine because the policy is an extremely convoluted adjustable universal life policy, the value and hence premiums for which fluctuate based on interest rates. Suffice it to say that even as a lawyer and with help from other experts the nuances remain infinitely complex).

        I am sure there are many other FIRE folks that are also fortunate enough to know they will be receiving a future windfall of one kind or another – whether life insurance or trust or general inheritance (some may know when and some may not) – but are similarly having a difficult time factoring such in to the SWR analysis. So speaking for myself and others similarly situated, I’d love to see you cover this in a future post.

        In any event, I would love to get your advice on my specific situation and numbers. If you’d be kind enough to reach out to me at the email address I assume you have or let me know how to email you directly I’d greatly appreciate it! I would be happy to reasonably compensate you for your time!

        And again, keep up this great work. It’s fascinating, if sometimes over my head. I could discuss Hegel or Nietzsche or the writing of Vonnegut and John Fowles all day long, but math and numbers are a far cry from philosophy, logic, literature and law 🙂

        1. I’m not ERN, but I’m seeing this because you’re in a subthread where I left a comment.

          This is a fairly strange situation. it’s a bit unusual that the policy in question wasn’t set up to require limited cash inputs. This sounds like the case of a permanent policy that was not really as good a deal as it sounded, and probably fallen prey to overoptimistic illustrations and then not monitored closely enough.

          I’d have to know a lot more details, like what the cash value and tax basis for the policy are. It’s plausible that your best bet is to cash it in now, or, if possible depending on the company and contract, lower the death benefit so that the policy is self-sustainable or close.

          Generally, the agent or the client has made a mistake somewhere if a policy that long-standing (presumably) comes back and starts charging a high premium.

          Is this the amount that’s getting charged against cash value? Or is it an amount that you’re expected to put in every year going forward?

          If you want to pm me on reddit: gnomeozurich, I’ll send an email where you can forward a copy of the in force illustration you got out of the insurer. I am a financial planner and insurance agent who sometimes (rarely) sets up policies like this for families with very high income or closely held businesses. I also see and analyze existing policies that have issues like you describe. Unfortunately, I’ve found that even most agents don’t really understand these policies any more than they have to in order to sell some. This may have been that situation, or it may have been set up by somebody who retired/moved and just hasn’t been monitored properly.

          1. Yeah, it doesn’t look like this was a well thought-through financial decision. I’ve seen this kind of policy recommended as an estate tax hedge. But the only people who got a hedge out of this is the insurance agent.
            But that said, it’s a sunk cost now. Would be interesting to see some of the parameters of this policy.

            1. Yeah, these policies sometimes make sense for estate planning where there is a lot of illiquid wealth, like a private business. They can also make sense as a bond replacement if they’re set up when young and healthy enough. But the ones I’ve set up would never come back on you at a late date like this unless someone had raided a big portion of the cash value. There were a bunch of policies writting in the 90s and 00s that were illustrated at 8-9%/year, and I see those all the time, eating their cash value or getting ready to lapse. If the client is lucky, they show them to me in a review while they still have plenty of cash value, before the insurance they often don’t even need anymore eats up almost all of it and they start getting bills.

              But I agree there’s a big sunk cost — a lot of policies that never should have been written are better kept than cashed in once they’ve been held for 5-10 years.

        2. Thanks!
          That’s a very interesting problem. I once did a case study on whether it’s worthwhile to keep or caah out a WLI contract just like the one you have (joint survivor):
          https://earlyretirementnow.com/2018/07/05/case-study-whole-life-insurance/
          Are the premium payments fixed or will they increase? Increase in a predictable or unpredictable way? Will the death benefit increase over time, e.g., due to dividends? Can you use the dividends to cover some of the premium payments?
          It sounds to me like what you’re proposing is actually the right approach: Set some horizon of ~15 years and assume you pay the premium untuil then but then also receive the lump sum. There is the option to enter these kinds of supplemental cash flows in the retirement calculator worksheet I created, see Part 28. It essentially boils down to a two-stage retirement problem for you.
          If you take a shot at it, feel free to show me the worksheet and I can see if you did it right.

          1. Thanks guys. For some reason I’m not receiving email alerts for comment replies. My parents bought the policy back in 1994 before going to a Europe for a month. My father is a physician (still practicing after almost 60 years!) and had and still has a very high income. It was extremely high back then, and they had a high net worth, so it was indeed intended to be a tax efficient estate planning tool. But physicians are notoriously poor with their money, and this is true of my father. So the policy may not have been the best choice.

            However, it worked out extremely well for me, bc the policy paid for itself for decades. But for some reason I mostly disregarded it until I received a notice of potential lapse for nonpayment bc, as noted above, the premiums and cash value began getting eaten up by mortality charge because my parents are now 84 and 76. I think I also assumed years ago that I’d never be able to afford the premiums or that for whatever reason I wouldn’t care about the policy from a cost-benefit perspective.

            Then came a sudden dislike for the practice of law, an assistant quitting and a gf breakup, along with MMM, a ton of FIRE research and analysis and a realization a year or so ago that the policy was actually my key to freedom and retiring early! I realize don’t that even if I had to pay a couple hundred thousand dollars over the course of 10-15 years it was undoubtedly a virtually certain super sweet investment/payoff.

            I too initially looked into selling the policy but the long and short of it is that the value isn’t as high as one might expect, because parents are in good health. Might be able to squeeze a net of $150k out of it but the hassles associated with it – e.g. submitting tons of medical records, possible physical exams, etc – coupled with the more important fact of a certain $1M tax free in a reasonableness number of years led me to conclude I should keep it.

            I just lost a bunch of additional text but I basically said that premiums are guaranteed not to exceed $15k/year and could be much lower depending on interest rates, which is guaranteed to be at least 4%. No dividends. Cash value is approx $30k now.

            I would gladly share policy and or the ledgers I’ve got if we can connect off blog. ERN should have my email and I’m on Reddit at Attorney-On-FIRE.

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