Data Methodology
Formulas, scoring vectors, and normalization criteria.
EconMap AI utilizes weighted math models to compute comparison indexes. Here's a brief look into how we compute our scores:
1. Cost of Living Index (COLI)
Calculated relative to New York City as the baseline (NYC = 100).
COLI = (RentWeight × RentRatio) + (FoodWeight × FoodRatio) + (UtilityWeight × UtilityRatio) + (TransitWeight × TransitRatio)
Where RentWeight = 40%, FoodWeight = 30%, Utilities = 15%, Transit = 15%.
2. Net Savings Rate Suitability
Calculates the financial feasibility of a user's net salary against local expense indices.
Savings Index (%) = [(Income - Total Expenses) / Income] × 100
3. AI Migration Points Matching
Immigration pathway percentages (e.g. Express Entry scores) utilize age-point distributions, educational credentials thresholds, language levels (CLB/IELTS conversion matrices), and financial liquid savings caps.