RetireSmartZIP™ • Data & Methodology

How RetireSmartZIP Uses Data

RetireSmartZIP uses ZIP-level housing, climate, healthcare, cost, tax, geography, and demographic data to help surface tradeoffs before you make a retirement move.

We show structured signals. You decide what works for your retirement.

Topics include retirement cost of living, property taxes, state income taxes, healthcare access, climate patterns, ZIP-level housing affordability, and retirement location comparisons.

Core Principle

Retirement decisions happen at the ZIP-code level.

City and state averages can be useful starting points, but they often hide the differences that matter in daily retirement life. RetireSmartZIP is designed to make those ZIP-level differences easier to see.

What RetireSmartZIP Does

Decision support, not automatic recommendations

RetireSmartZIP is designed to help you evaluate retirement locations and understand where retirement could work — before you make a move.

Instead of ranking “best places,” the ZIP Explorer surfaces ZIP-level differences across housing, climate, healthcare, cost, tax, and geography so you can evaluate tradeoffs.

We do not make decisions for you. We provide structured signals so you can make better ones.

Data Sources

What the Explorer uses

  • U.S. Census ACS — population and demographics
  • Zillow — home values and housing trends
  • NOAA — climate normals and seasonal patterns
  • Healthcare datasets — hospital access and provider availability
  • Tax Foundation and public tax datasets — state and local tax estimates
  • Geographic datasets — ZIP centroids and metro mapping
Key Assumptions

How signals are interpreted

  • Distances are measured from the center of each ZIP code
  • Healthcare reflects access, not quality
  • Climate is based on long-term averages
  • Housing reflects most recent available market data
Cost & Tax Model

How RetireSmartZIP estimates local tax burden

RetireSmartZIP includes a directional Cost & Tax Snapshot designed to help show how taxes and cost of living can affect the real monthly affordability of a ZIP code during retirement.

  • Property tax estimates are modeled using county-level effective property tax rates applied to local housing values.
  • Sales tax estimates are based on combined state and local sales tax rates using a baseline monthly spending assumption.
  • State income tax estimates are modeled using approximately $60,000 in annual household income for both single and married filing scenarios.
  • These values are combined into a simplified monthly “Tax Reality” estimate to help surface hidden affordability differences between ZIP codes.

Income-tax estimates compare a single filer versus a married joint-filing household using the same approximate household income baseline.

Tax estimates are based on public datasets including Tax Foundation data and other public tax sources. Values are directional estimates only and should not be considered tax, financial, or legal advice.

Data Freshness

Different datasets update differently

  • Population: ACS 5-year estimates, latest available
  • Housing: updated periodically from Zillow datasets
  • Climate: NOAA long-term averages
  • Healthcare: latest available provider and hospital data
  • Cost & Tax: periodic updates from public tax and cost datasets

RetireSmartZIP prioritizes consistency and coverage across ZIP codes.

Limitations

What to keep in mind

  • Data may lag real-world conditions
  • ZIP-level aggregation can hide neighborhood differences
  • Healthcare access does not guarantee provider availability
  • Tax estimates may differ from actual filing outcomes
What This Is Not

RetireSmartZIP is not financial advice

  • Not financial advice
  • Not tax advice
  • Not a ranking system
  • Not a recommendation engine

RetireSmartZIP is a decision-support tool — not a decision engine.

Ready to see the data in action?

Open the Explorer and compare ZIPs using housing, climate, healthcare, cost, tax, and local context. You can also read our retirement articles for additional planning context.

Open Explorer