Eight transparent indexes for retirement decisions.

What it measures

Blends typical housing, groceries, utilities, transportation, and healthcare costs against comparable U.S. metro baselines to estimate purchasing-power differential for a retired household.

Methodology

1. Build a fixed retiree consumption basket (housing, food, utilities, transport, healthcare, leisure).
2. Price the basket in each destination using a rolling 6-month median.
3. Normalize against a U.S. baseline (median mid-cost metro).
4. Publish as an indexed score from 0–100 where higher = greater purchasing-power advantage.

Data sources

• Numbeo cost-of-living datasets (crowd-sourced, cross-referenced)
• Philippine Statistics Authority (PSA) CPI and family expenditure surveys
• Bangko Sentral ng Pilipinas exchange-rate history
• AMRE partner surveys of long-stay rentals and utilities

Limitations

Lifestyle choices, imported goods, and premium services can materially shift real-world costs. Not a personalized budget.

What it measures

Measures proximity and availability of accredited hospitals, English-speaking specialists, pharmacies, and emergency services relative to residential areas.

Methodology

1. Score four subcomponents: tertiary hospital proximity, specialist availability, pharmacy density, and ambulance/response coverage.
2. Weight tertiary and specialist access more heavily for retiree relevance.
3. Adjust for road-network reality (drive time, not straight-line distance).

Data sources

• Department of Health (DOH) facility registry
• PhilHealth accreditation lists
• Joint Commission International (JCI) accreditation database
• AMRE partner hospital network intake

Limitations

Access is not the same as clinical outcomes. This index does not rate individual physicians or predict care experience.

What it measures

Evaluates the density and variety of retiree-relevant lifestyle amenities: restaurants, cafés, parks, cultural venues, wellness, and safety perception.

Methodology

1. Count and diversify-weight lifestyle POIs within reasonable resident travel radius.
2. Blend safety perception (survey) with reported crime rates.
3. Cap any single subcomponent to avoid amenity concentration bias.

Data sources

• Google Places and OpenStreetMap points-of-interest
• Philippine National Police (PNP) crime index by city
• AMRE resident-panel surveys (rolling)

Limitations

Preference-driven. A high score does not mean 'best for you' — it means broadly rich lifestyle infrastructure.

What it measures

Combines fixed-broadband speeds, mobile 4G/5G coverage, and reported outage frequency by area.

Methodology

1. Score median download/upload speeds and latency.
2. Adjust for redundancy (fiber + mobile fallback availability).
3. Penalize destinations with frequent multi-hour outages.

Data sources

• Ookla Speedtest Global Index (per-city aggregates)
• National Telecommunications Commission (NTC) coverage maps
• AMRE resident-panel outage reports

Limitations

Building- and provider-level variance is significant. Confirm service at the actual residence before committing.

What it measures

Measures how easily a resident can reach an international airport, move within the city, and travel to Manila or Cebu hubs.

Methodology

1. Score international-airport drive time and flight frequency.
2. Score intra-city mobility (ride-hail, taxi, public transit).
3. Adjust for road-condition and typhoon-season disruption history.

Data sources

• Civil Aviation Authority of the Philippines (CAAP) airport data
• Department of Transportation (DOTr) route data
• Grab and local ride-hail coverage

Limitations

Traffic and weather can dominate day-to-day experience beyond what any index captures.

What it measures

Captures the availability of retiree-relevant social infrastructure: American/expat groups, faith communities, volunteer opportunities, and regular cultural events.

Methodology

1. Count active groups and event frequency per capita.
2. Weight groups that host recurring (weekly/monthly) programming.
3. Include faith and volunteer channels equally.

Data sources

• Registered civic and expat organizations
• AMRE partner-community rosters
• Event calendars from local government units (LGUs)

Limitations

Community fit is personal. Attend a Discovery Tour or virtual meetup before drawing conclusions.

What it measures

Rates year-round comfort using temperature range, humidity, rainy-season length, and historical typhoon frequency and severity.

Methodology

1. Score comfort against a temperate baseline retirees typically prefer.
2. Penalize prolonged extreme humidity and rainy seasons.
3. Weight typhoon exposure by historical frequency and severity within a 50-km radius.

Data sources

• PAGASA climate normals and typhoon archives
• NOAA and Copernicus regional datasets

Limitations

Comfort is subjective. Climate change may shift multi-year norms — expect ongoing revisions.

What it measures

A composite measure of infrastructure maturity, English proficiency in services, retiree-oriented housing supply, and partner-network depth.

Methodology

1. Aggregate weighted subscores: infrastructure, service English, housing supply, partner depth, emergency preparedness.
2. Require minimum thresholds in healthcare and connectivity before a destination is eligible for a high readiness score.
3. Flag destinations with rapid change (positive or negative) for closer review.

Data sources

• AMRE partner network coverage
• SRRV visa activity trends (PRA public reporting)
• Housing-market supply indicators from partner brokers

Limitations

Readiness measures the ecosystem, not personal readiness. Pair with the Retirement Confidence Score™ for a full picture.