Our Data Methodology
Transparency is at the core of Remote Wealth. Here is exactly how we source, clean, and calculate our global financial data.
1. Data Sourcing & Aggregation
Our cost of living and salary metrics are not pulled from thin air. We aggregate raw data from a combination of open-source government databases, local real estate listings, and the world's largest crowdsourced pricing databases (such as Numbeo and Expatistan). By combining programmatic scraping of over 140+ core global cities with verified crowdsourced input, we establish a robust baseline.
2. Currency Conversion & Normalization
Because currency markets fluctuate constantly, comparing a salary in Japanese Yen to rent in British Pounds can be misleading if not handled correctly.
- Real-time Exchange Rates: We peg all our baseline calculations to a standard currency (USD) behind the scenes using trailing 30-day average exchange rates to smooth out daily market volatility.
- Net Salary vs. Gross: All salary metrics displayed on Remote Wealth are estimated net (after-tax) salaries, as local tax brackets wildly distort purchasing power.
3. Editorial Verification & Accuracy
Raw data is often flawed. That's why the Remote Wealth Editorial Team manually spot-checks our algorithms. We apply outlier detection filters—if a data source claims rent in Manhattan is $500, our system automatically flags and discards it. Furthermore, we actively update our algorithms to account for global inflation spikes.
Update Frequency
We aim to refresh our core index every quarter. You will always see a "Data Last Updated" timestamp at the top of our city comparison pages, ensuring you are never making financial decisions based on obsolete data.