Calvià decision profile

Calvià, in structure.

Southwest municipality covering Santa Ponça, Sol de Mallorca and Portals.

High data coverage · 6/7 official metricsCompare with others

Everyday life

Coastal living built around the sea, marinas and an international community.

Trade-off: Homes close to the sea usually carry a premium — check how your budget compares.

Supports

being close to the sea, boating and marinas, golf, an international community, quiet and privacy

Still to check

How busy does the coast get in summer, and does that matter to you?
If you boat, is a berth available, and at what cost?

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Registered price

€5,640 / m²

Calvià · Q4 2025 · Colegio de Registradores de España · partial confidence

This is a structured decision model, not a prediction and not a valuation.

Price direction

+5.2% year on year

Price trend

Calvià · Q4 2025 · Colegio de Registradores de España · partial confidence

Market activity

1,180 registered sales

Transaction volume

Calvià · 2025 · Colegio de Registradores de España · partial confidence

Buyer mix

46.2% of registered purchases

Foreign buyer activity

Calvià · 2025 · Ministerio de Transportes y Movilidad Sostenible · partial confidence

Finance

3.4% average new mortgage

Mortgage context

Spain · Q4 2025 · Banco de España · high confidence · National series applied as context.

Supply

210 permits issued

New-build activity

Calvià · 2025 · INE / Ministerio de Vivienda · low confidence

Regulation

Coastal setbacks apply across the front-line southwest.
Tourist rental licences for detached houses exist but are capped and scarce.

Lifestyle fit

Recorded strengths: Sea access, Marinas, International community, Golf. Build your SWIP profile to personalise this.

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Data quality

High data coverage

Not published: Housing price index

Buyer pressure model

High international participation
46.2% of registered purchases
Lower transaction activity
-4.5% year on year
Rising registered prices
+5.2% year on year
Verified new-build activity recorded
210 permits issued

SWIP analysis

Fewer registered transactions alongside rising registered prices. In a supply-constrained market this pattern is consistent with scarcity rather than weakening demand, but the published data does not by itself distinguish the two.

How this was built

Model rules: No score is produced. Each statement restates one published series; the analysis names the pattern and the limits of reading it.
Input data: Only metrics carried in the SWIP source library. Each figure keeps its publisher, geography, period and confidence.
Periods: Latest published period per series. Periods differ between series and are shown per figure.
Geographies: Geography is stated per figure. Where a municipal figure does not exist, a regional or national series may be shown as context and is labelled as such.
Limitations: Averages are sensitive to the mix of properties that happened to transact. Low-volume municipalities produce volatile averages. Nothing here is a valuation or a forecast.
Interpretation method: Models combine published values using stated rules. No weighting is hidden and no score is generated that the rules above do not fully explain.

Ownership friction model

LOW

2 recorded regulatory considerations
Coastal setbacks apply across the front-line southwest.
Tourist-rental restrictions apply
Regulatory notes
Moderate financing cost
3.4% average rate

How this was built

Model rules: One point per recorded regulatory consideration. Two points where tourist-rental restrictions are recorded. Two points where average financing cost is 4% or above; one point where no official series exists. One or two points for partial or low official data coverage. One point where ownership sits outside SWIP's home jurisdiction. 0–4 LOW · 5–7 MEDIUM · 8+ HIGH.
Input data: Only metrics carried in the SWIP source library. Each figure keeps its publisher, geography, period and confidence.
Periods: Latest published period per series. Periods differ between series and are shown per figure.
Geographies: Geography is stated per figure. Where a municipal figure does not exist, a regional or national series may be shown as context and is labelled as such.
Limitations: Averages are sensitive to the mix of properties that happened to transact. Low-volume municipalities produce volatile averages. Nothing here is a valuation or a forecast.
Interpretation method: Models combine published values using stated rules. No weighting is hidden and no score is generated that the rules above do not fully explain.

Cross-sectional decision profile

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