Cantonal taxes
Large postcodes with low taxes: Where to look
You don't always have to move to a tiny village to save on taxes. Some large postcodes combine great infrastructure with a surprisingly low tax bill.
Municipality hub
Gipf-Oberfrick
Gipf-Oberfrick connects 2 postcode pages in Aargau. This hub shows membership, address shares, and demographic context.
- Postcodes
- 2
- Population
- 3'878
- Streets
- 95
- Effective tax rate
- 11.17%
- ESTV: single, CHF 80,000, no church tax
Postcodes in Gipf-Oberfrick
The municipality includes 1 split-postcode cases and 2 locality names. Use the links for address, demographic, and map context.
How this municipality cluster behaves
Gipf-Oberfrick connects these postcodes through one administrative structure.
For ESTV tax year 2024, the standard scenario produces CHF 8'938 total tax, or 11.17% effective.
Related municipality hubs
Blog
Guides for comparing Gipf-Oberfrick
These articles explain how to read postcode, municipality, and demographic data for relocation or comparison work.
Cantonal taxes
How to compare Swiss tax burden by postcode
A reliable comparison keeps the ESTV scenario fixed and checks which municipality supplies the tax result shown for each postcode.
Moving and taxes
How to compare postcodes before you move (and when to stop)
How to read a postcode without giving it more weight than it deserves. We show which signals help and when you should move on to an official check.
Moving and taxes
Moving as a family on CHF 150,000: Which postcodes make sense?
Families earning CHF 150,000 should compare real postcode clusters, not just the absolute lowest headline tax rate. Right now, the top ten are all in canton Geneva.
Postcode and municipality
Swiss postcodes vs municipalities: which unit you should trust
Postcodes and municipalities overlap in Switzerland, but they are not the same thing. Keeping them separate makes tax data and location data easier to read.
Postcode and municipality
Postcode or Municipality: What Are You Comparing?
Why treating a postcode map like a political map is a massive mistake, and how to read the data correctly.