How do I use ESPlanner to determine my optimal consumption?

If I understand your question correctly, you want to figure out a way to use ESPlanner, but you want to consume more conservatively than the program recommends, because the recommended consumption is based on mean returns, and you want to plan for low returns, to be safe.

I struggled with this same problem for quite some time before I came up with a solution. It's a solution I'm still not quite comfortable with, but I posted it in an earlier post in this forum, and got a reply from Larry that indicated it's not completely off base.

This may seem complicated at first, but bear with me.

My "ah-ha" was when I decided to think of it from ESP's perspective - what would happen if I spent more conservatively in 2008 than the program recommended (because I want to plan for low returns), but I actually got the mean returns in 2008 that the program is planning for? Well, I would have more money in the bank at the start of 2009 than the program was expecting (since I hadn't spent it). So if I re-ran the program in 2009, the program would tell me I could spend more in 2009 - it would give me a raise.

So I incorporate a "raise" each year in my planning. I use the standard of living tab to adjust my future standard of living by a certain percentage. This lowers my current recommended consumption (which was the desired result, right?).

So how much of a raise do I give myself? That was my second "ah-ha". I use the “Percentile Distribution of Living Standard" graph from the Monte Carlo runs. Ordinarily (without the raise), the Recommended Trajectory runs across the “Percentile Distribution of Living Standard” chart horizontally, and the 25th percentile, for example, slopes downward. The amount of raise I give myself is enough to tilt the whole "Percentile Distribution of Living Standard" graph counter-clockwise just enough that my desired level of risk runs horizontally across the graph. In other words, if I'm willing to accept a risk that there's a 25% chance my living standard will be lower than planned for, and a 75% chance it will be higher, then I tilt the graph until the 25% line runs horizontal. This approach makes some sense, because if my investments do better than the 25th percentile I’m planning for, I really should be able to give myself a raise each year.

For me personally, 25% is too high and 5%, is to low, so I linearly interpolate between the two to get to my desired level of risk (this is easy, because the output is Excel, so I can add equations to the results sheets).

A benefit of this approach is that I can evaluate different portfolios for risk vs reward by implementing a new set of portfolios, running the program, then finding the new standard of living growth rate that tilts the graph to make my desired level of risk horizontal. This allows me to compare the same percentile distribution of living standard between two different asset allocation strategies. If the reward is worth it, the *recommended consumption* will be higher. If the risk is too great, it will be lower, even if the portfolio would return more with mean values. If I were to chose a different level of risk, the results would be different.