This system tells you how much in dividend-producing assets you need to cover your monthly living expenses and close the gap between your expenses and your guaranteed income. Also, this system allows you to estimate how your expenses would change if you moved to a different city and how much dividend-producing assets you would need in that new location. The end result is a simple, intuitive unit: the monthly wage drone, or the amount of assets needed to generate enough dividends over the course of a year to fund one month of your life.
TL;DR — The System
- Estimate your monthly expenses (MEE) based on your real spending
- Look up CPI-U (bls.gov) to track inflation
- Look up RPP (bea.gov) to adjust for your city
- Solve for your Monthly Expense Multiplier (MEM): $MEM = \frac{MEE}{CPIU \times (RPP/100)}$
- Freeze MEM — do not change it unless your actual lifestyle changes
- Choose a dividend yield (e.g., ~3.5% for SCHD)
- Calculate your Monthly Wage Drone (MWD): $MWD = \frac{CPIU \times (RPP/100) \times MEM}{\text{Yield}}$
What It Means
- 1 MWD = assets needed to fund 1 month of expenses (via annual dividends)
- 12 MWD = full income replacement
- More than 12 = buffer
What Updates Automatically
- CPI-U → adjusts for inflation
- RPP → adjusts for location
- MEM → stays fixed unless your lifestyle actually changes
What You’re Really Tracking
How many months of your life your portfolio can fund without selling assets
The System, Step by Step
Now we can put all the pieces together.
This looks like a lot at first, but it’s actually a very simple system once you separate the parts and do them in order.
Step 1: Get CPI-U (Inflation)
You’ll need the current CPI-U value.
Look it up at bls.gov and grab the latest value. This is the piece that keeps your system tracking inflation over time.
Step 2: Get RPP (Location)
Next, get the Regional Price Parity (RPP) for your city (or the closest available metro area).
Look it up at bea.gov.
- 100 = national average
- Above 100 = more expensive than average
- Below 100 = cheaper than average
This is the piece that adjusts your expenses based on where you live.
Step 3: Estimate Your Monthly Expenses (MEE)
Now you need a starting point: your actual monthly spending.
Look at your real expenses and come up with a reasonable estimate of what it costs you to live for one month. This does not need to be perfect. It just needs to be honest.
We’ll call this your Monthly Expense Estimate (MEE).
Step 4: Solve for Your Monthly Expense Multiplier (MEM)
Now we define the core relationship:
$$ \text{MEE} = \text{CPIU} \times \left(\frac{\text{RPP}}{100}\right) \times \text{MEM} $$
Solve this for MEM:
$$ \text{MEM} = \frac{\text{MEE}}{\text{CPIU} \times (\text{RPP}/100)} $$
This gives you your Monthly Expense Multiplier (MEM).
This number represents your lifestyle relative to the national baseline. Once you calculate it, it becomes the anchor for your system.
Step 5: Freeze MEM
Once you have MEM, do not keep recalculating it.
You freeze it.
From this point forward:
- CPI-U updates → inflation adjustment
- RPP changes → location adjustment
- MEM stays constant → your lifestyle
You only recalculate MEM if your actual spending changes in a meaningful way beyond inflation (for example, a permanent lifestyle upgrade or downgrade).
Step 6: Choose a Dividend Yield
Now choose the dividend yield you want to use for income generation.
You can use any dividend-focused fund, but I use SCHD.
Based on its historical behavior, I treat 3.5% (0.035) as a reasonable long-term average yield. It tends to move between roughly 3% and 4%, so using the midpoint keeps the system stable without overreacting to market fluctuations.
Step 7: Calculate the Monthly Wage Drone (MWD)
Now we combine everything:
$$ \text{MWD} = \frac{\text{CPIU} \times (RPP/100) \times MEM}{\text{Yield}} $$
If you are using a 3.5% yield:
$$ \text{MWD} = \frac{\text{CPIU} \times (RPP/100) \times MEM}{0.035} $$
This gives you the amount of assets required to generate enough annual dividend income to cover one month of expenses.
Step 8: Interpret the Result
- 1 MWD = covers 1 month of expenses (per year of dividends)
- 12 MWD = covers a full year
- More than 12 = buffer
This turns your portfolio into something intuitive:
Instead of thinking in dollars, you can think in months of life funded.
Step 9: Put It Into a Spreadsheet
At this point, you’ve got a system. Now you want to make it automatic.
A simple spreadsheet lets you plug in updated CPI-U values (and optionally RPP or yield changes) and have everything else update instantly.
Here’s a clean way to set it up:
| Name | Value / Formula | Notes |
|---|---|---|
| CPIU | Manual entry | Look up latest CPI-U (bls.gov) |
| RPP | Manual entry | Look up your city’s RPP (bea.gov) |
| Monthly Expense Estimate (MEE) | Manual entry | Your current monthly spending |
| Monthly Expense Multiplier (MEM) | =MEE/(CPIU*(RPP/100)) | Calculate once, then freeze |
| Frozen MEM | Copy of MEM (paste values) | Do not change unless lifestyle changes |
| Yield | 0.035 | Use your chosen average yield |
| Updated MEE | =CPIU(RPP/100)Frozen MEM | Inflation + location adjusted expenses |
| Monthly Wage Drone (MWD) | =Updated MEE/Yield | Assets needed for one month of expenses |
How to Use It
- Update CPIU whenever new data comes out
- Update RPP if you move or want to model a new city
- Leave Frozen MEM alone unless your lifestyle actually changes
- Adjust Yield only if you change your assumptions
Everything else updates automatically.
Why This Works
This spreadsheet preserves the structure of the system:
- CPIU → handles inflation
- RPP → handles location
- MEM → locks in your lifestyle
- Yield → converts expenses into required assets
Once it’s set up, you don’t need to rethink anything. You just update inputs and read the result.
What Problem Does This Solve?
Most people face the same basic problem in retirement planning: their guaranteed income—things like pensions and Social Security—does not fully cover their desired living expenses. That leaves a gap, and the question becomes: how much in assets do I need to fill that gap reliably?
You can answer that question in abstract terms—total portfolio size, withdrawal rates, percentages—but those tend to feel disconnected from real life. They don’t map cleanly onto the thing you actually care about, which is covering your monthly expenses.
So instead of thinking in terms of a giant lump sum, I wanted a unit that directly connects assets to lived reality.
That’s where the idea of the monthly wage drone comes in.
A monthly wage drone is defined as the amount of assets required to generate enough dividend income, over the course of a year, to cover one month of living expenses. It translates portfolio size into something tangible: one unit equals one month of expenses.
Once you have that unit, the problem becomes much clearer. If one monthly wage drone covers one month, then twelve of them cover a full year of expenses. And if your pension and Social Security already cover part of that, you can directly measure how many “months” your portfolio needs to supply.
Instead of asking, “Do I have enough?” you can ask a much more concrete question: How many months of my life does my portfolio currently fund?
Background
I’ve already written what I consider to be a very important article about building savings drones. If you’ve made it this far without reading that one, you should go back and read it at some point, because this builds directly on that framework.
At a high level, this entire system depends on two pieces of government data that solve two different problems: time and place.
First, there’s CPI-U, the Consumer Price Index for All Urban Consumers, published by the U.S. Bureau of Labor Statistics (BLS). CPI-U tracks changes in the price of a broad basket of goods and services over time, which makes it the standard measure of inflation. If CPI-U goes up, that means, in general, things cost more than they used to.
That matters because your estimate of how much it costs you to live tends to lag behind reality. You usually figure out your monthly expenses once—maybe by looking at your spending—and then you carry that number around in your head. Meanwhile, prices are changing constantly. Rent goes up, groceries creep higher, services get more expensive, but your mental estimate doesn’t automatically update. CPI-U gives you a way to correct for that by tying your expense estimate to something that actually moves with inflation.
But CPI-U only handles time. It assumes you’re living in an “average” place.
That’s where the second piece comes in: Regional Price Parities (RPP), published by the U.S. Bureau of Economic Analysis (BEA). RPP measures how price levels differ across regions, using 100 as the national average. A value above 100 means a region is more expensive than average, and a value below 100 means it’s cheaper.
RPP is useful because it lets you estimate how your living expenses would change if you moved from one place to another. Instead of guessing or relying on rough proxies, you can scale your expenses based on a standardized measure of regional cost differences. Combined with CPI-U, this gives you a way to adjust your expenses both over time and across locations.
The final piece of the puzzle is income.
Most people do not receive enough from pensions and Social Security to fully cover their living expenses. That means their portfolio has to fill the gap. One way to do that is by selling assets over time, but that approach has a built-in problem: if you’re forced to sell during a down market, you’re locking in losses relative to the long-term value of those assets.
That’s why many people, myself included, prefer to rely on dividends.
Dividends allow you to generate income without selling shares. As long as the underlying companies continue to pay, you receive a stream of cash that is much less sensitive to short-term market fluctuations than share prices. The price of a stock can swing wildly from day to day, but dividend payments tend to move slowly and, in strong companies, often grow over time.
One fund that stands out in this space is :contentReference[oaicite:0]{index=0}.
SCHD tracks an index that screens U.S. companies for both dividend quality and financial strength. It starts with companies that have a consistent history of paying dividends, then filters and ranks them based on factors like cash flow, return on equity, dividend yield, and dividend growth. The result is a portfolio tilted toward established, profitable companies that not only pay dividends, but have a track record of sustaining and increasing them.
Over long periods, this combination has produced a steadily growing stream of income while also maintaining competitive total returns relative to broad market indexes. That makes it a useful foundation for thinking about how a portfolio can generate income to support living expenses without relying on selling assets at potentially unfavorable times.
How I Got Here in the First Place
This started with the savings drone idea.
Once I had that framework built, I realized I was already holding most of the pieces I needed to answer a different question: how do I keep my monthly expense estimate honest over time? The problem is that your sense of “what it costs to live” gets stale. You figure it out once, maybe by looking at your spending, and then you just kind of carry that number forward in your head while inflation quietly chips away at it.
So I started looking for a way to tie my monthly expenses to something that actually moves with inflation. CPI-U was the obvious anchor since it’s the government’s broad measure of consumer prices, and I was already using it elsewhere. That gave me a way to scale expenses over time, but it still assumed I was living in an “average” place, which I very much am not.
That’s where the second piece came in.
I went looking for some way to compare the cost of living between cities. My first thought was to use something like median home values as a proxy, but that’s a pretty blunt instrument and it only captures one slice of the cost picture. Then I found RPP—Regional Price Parities, published by the U.S. Bureau of Economic Analysis.
RPP does exactly what I needed. It compares the price level of goods and services across regions, using 100 as the national average. So if a city has an RPP of 111.5, it means prices there are about 11.5% higher than average. If it’s 91.9, prices are about 8.1% lower than average. That gave me a clean, standardized way to scale expenses up or down depending on where I live.
And that mattered to me because I’m planning around a move. San Diego is expensive, and New Orleans is not. Based on the RPP values, New Orleans comes in at roughly 18% cheaper than San Diego, which is a big enough difference that I don’t want to ignore it or hand-wave it away. I want a system that actually reflects that change.
Once I had CPI-U handling time and RPP handling location, the rest of the system basically fell into place.