Depends on the market movements, right? The point is to mitigate against sequence of returns risk. Michael Kitces has written at least 3 posts about it. Here's the most recent one. I'm not sure if he's concluded what the actual ending effect is though, other than stating that it is beneficial.

Over at Early Retirement Now, they've concluded that doing this when CAPE is greater than 20 increases your success rate by 10%-ish. So while not a dramatic jump, it is definitely in the statistically significant range. Conversely, you could use it to retire earlier with a higher withdrawal rate.

From this post:

Likewise, if I’m OK with a 5% failure probability conditional on a CAPE>20, then the static stock allocation of 80% would give me an SWR of 3.47%. The glidepaths would have allowed between 3.57% and 3.63%. Only an additional 0.16%, but that’s about 5% more consumption every year!

Is that significant enough? I'm not sure. But I'm also not sure that looking at every result is all that meaningful (because good years to retire are going to work no matter what). It certainly seems to help stem the tide of poor returns when I have run simulations based on the 2000 retiree. It increased portfolio balances by 8% after 5 years compared to static AA. (Admittedly with some pretty perfect hindsight timing.)

Kitces simulations are limited because he only considers 4% WR, 30-year retirement and constant ramp-up time.

He finds best success rate goes from something like 94.6% to 95.1%, which is just 1-2 starting years (not sure of his methodology).

I made more extensive simulations here:

https://forum.mrmoneymustache.com/welcome-to-the-forum/cfiresim-severely-overestimates-success-rates-for-mustachians/msg1634628/#msg1634628If you look at other WR (4.5%, 5%), you'll see that a glide path actually

*hurts* success rates as often as it helps. Given that there is so little historical data, the effect is probably insignificant, i.e. the "advantage" he finds could have been a disadvantage just by adjusting slightly some parameters.

If you condition this on CAPE, significance is even lower. So, those simulations are interesting and can yield useful results if the magnitude of the effect is large, but they should be taken with a grain of salt if not.

Kitces says this in the article: "Notably, there’s still far more research to be done to optimize the exact shape and the slope of the V-shaped equity glidepath and the bond tent."

but actually with the data we currently have, there's not much more research we can squeeze out of this, I'm afraid.