Here’s the numbers behind some assumptions in the FI for Social Workers Post
Basically I asked 3 Claued, Chat, and Gemini, and then did my own back of the napkin math to make sure it made sense. Here’s what we came up with:
Important Caveat
This estimate is not a direct measurement of the FIRE (Financial Independence, Retire Early) movement’s environmental impact. No peer-reviewed study currently exists that quantifies the carbon footprint reduction attributable to FIRE participants.
Instead, this page presents a rough consumption-based model built from publicly available information about FIRE demographics, spending behavior, consumer carbon intensity, and investment-related emissions. The purpose is to estimate the possible order of magnitude of the movement’s environmental impact, not to provide a definitive figure.
Step 1: Estimating the Size of the FIRE Population
The first challenge is that nobody knows exactly how many people participate in FIRE.
Unlike a professional association or nonprofit organization, FIRE has no membership rolls. Participants are spread across blogs, podcasts, online communities, local groups, and social media.
The estimate used here assumes approximately 3 million U.S. households actively pursuing some form of financial independence.
This figure is not directly measured. It is based on the size and reach of major FIRE communities, including:
- ChooseFI: https://www.choosefi.com
- Mr. Money Mustache: https://www.mrmoneymustache.com
- Early Retirement Extreme: http://earlyretirementextreme.com
- Bogleheads: https://www.bogleheads.org
- Reddit Financial Independence community: https://www.reddit.com/r/financialindependence/
Because this estimate is uncertain, readers should treat 3 million households as a modeling assumption rather than an established fact.
Step 2: Estimating Income and Savings Behavior
FIRE participants are generally believed to earn more than the median U.S. household.
The model assumes:
- Average household income: approximately $130,000
- Average savings rate: approximately 50%
This assumption is consistent with the widespread FIRE guideline that participants should save 40–60% of income to achieve financial independence on an accelerated timeline.
Resources:
- Survey of Consumer Finances (Federal Reserve):
https://www.federalreserve.gov/econres/scfindex.htm - U.S. Census Household Income Data:
https://www.census.gov/topics/income-poverty/income.html - FIRE savings rate discussions:
https://www.mrmoneymustache.com
https://www.choosefi.com
Under these assumptions:
$130,000 income × 50% savings rate = $65,000 annual spending
This implies approximately $65,000 of annual consumption that is avoided or deferred compared to a household spending its entire after-tax income.
Step 3: Estimating Reduced Spending in High-Impact Categories
Not all spending has the same environmental impact.
The model focuses on categories where FIRE participants often report significant reductions:
| Category | Estimated Annual Spending Reduction |
| Transportation Fuel | $3,000 |
| Air Travel | $3,000 |
| Dining Out | $3,500 |
| Consumer Goods | $3,500 |
| New Vehicle Purchases | $4,500 |
| Clothing | $2,000 |
| Recreation | $1,500 |
Total modeled spending reduction:
$21,000 per household annually
This is substantially smaller than the full $65,000 savings assumption and therefore should be considered a conservative subset of potential consumption reductions.
Step 4: Assigning Carbon Intensities
To estimate emissions reductions, spending reductions are multiplied by carbon-intensity factors derived from environmentally extended input-output (EEIO/MRIO) models and transportation emissions data.
Resources:
U.S. EPA Greenhouse Gas Emissions:
https://www.epa.gov/ghgemissions
Our World in Data:
https://ourworldindata.org/co2-and-greenhouse-gas-emissions
EXIOBASE Multi-Regional Input Output Database:
https://www.exiobase.eu
U.S. Bureau of Labor Statistics Consumer Expenditure Survey:
https://www.bls.gov/cex/
International Energy Agency Transport Data:
https://www.iea.org/topics/transport
UK DEFRA Emissions Factors:
https://www.gov.uk/government/collections/government-conversion-factors-for-company-reporting
The model uses the following carbon intensities:
| Category | Carbon Intensity |
| Transportation Fuel | 2.4 kg CO₂e per dollar |
| Air Travel | 1.2 kg CO₂e per dollar |
| Dining Out | 0.6 kg CO₂e per dollar |
| Consumer Goods | 0.4 kg CO₂e per dollar |
| New Vehicle Purchases | 0.12 kg CO₂e per dollar |
| Clothing | 0.4 kg CO₂e per dollar |
| Recreation | 0.3 kg CO₂e per dollar |
Step 5: Vehicle Manufacturing Assumption
Vehicle purchases deserve special explanation.
An earlier version of this model used a substantially higher estimate that likely overstated vehicle-related emissions.
To avoid double-counting fuel emissions (which are already captured in the transportation category), the revised model includes only manufacturing-related emissions associated with purchasing new vehicles.
Research summarized by the International Energy Agency and various lifecycle assessment studies suggests that manufacturing a typical internal-combustion passenger vehicle generates approximately 5–6 tonnes of CO₂.
Resources:
International Energy Agency:
https://www.iea.org
ICCT Vehicle Lifecycle Research:
https://theicct.org
Using:
5.6 tonnes CO₂ ÷ $48,000 median new vehicle price
yields:
0.12 kg CO₂ per dollar spent on new vehicles
This should be considered a conservative estimate.
Step 6: Calculating Household Emissions Reductions
Applying the carbon-intensity factors to each spending category:
| Category | Annual Spending Reduction | Carbon Intensity | CO₂e Avoided |
| Transportation Fuel | $3,000 | 2.4 kg/$ | 7.2 t |
| Air Travel | $3,000 | 1.2 kg/$ | 3.6 t |
| Dining Out | $3,500 | 0.6 kg/$ | 2.1 t |
| Consumer Goods | $3,500 | 0.4 kg/$ | 1.4 t |
| New Vehicle Purchases | $4,500 | 0.12 kg/$ | 0.54 t |
| Clothing | $2,000 | 0.4 kg/$ | 0.8 t |
| Recreation | $1,500 | 0.3 kg/$ | 0.45 t |
Total:
Approximately 16 tonnes CO₂e avoided per household annually
Step 7: Scaling to the FIRE Population
Assuming 3 million participating households:
16 tonnes × 3,000,000 households
= approximately 48 million tonnes CO₂e annually
Step 8: Accounting for Investment-Related Emissions
A common criticism of FIRE is that money not spent is usually invested.
Investments are associated with “financed emissions,” which attempt to estimate the emissions attributable to companies owned through stock and bond portfolios.
Resources:
Partnership for Carbon Accounting Financials (PCAF):
https://carbonaccountingfinancials.com
MSCI Climate and Financed Emissions Resources:
https://www.msci.com/our-solutions/climate-investing
Because methodologies vary significantly, financed-emissions estimates should be viewed cautiously.
Using a rough offset estimate of approximately 16 million tonnes CO₂e across the modeled FIRE population yields:
48 million tonnes gross emissions reductions
minus
16 million tonnes financed emissions
equals
approximately 32 million tonnes CO₂e net reduction annually
Final Estimate
Under the assumptions described above:
- Gross estimated reduction: approximately 48 million tonnes CO₂e annually
- Estimated financed-emissions offset: approximately 16 million tonnes CO₂e annually
- Net estimated reduction: approximately 32 million tonnes CO₂e annually
These figures should be interpreted as illustrative estimates rather than definitive measurements.
The primary sources of uncertainty are:
- The true size of the FIRE population.
- The average income and savings rate of participants.
- Actual spending reductions achieved.
- Carbon-intensity estimates for specific spending categories.
- Financed-emissions accounting methodologies.
Our AI overlords say that future research using household expenditure surveys and direct participant data could substantially improve these estimates. I’m not holding my breath. In the meantime, please look this over and see if you notice anything that’s way out of wack. Peer review and all that.
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