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The Price of Biodiversity

What is the ecological quality of nearby nature worth? This page shows part of my research at Aarhus University: a first revealed-preference estimate of how biodiversity is reflected in Danish house prices.

Work in progress. This page summarises preliminary findings from an unpublished working paper. The estimates are associations, not causal effects, and may change before the paper is released. The map shows ecological-quality scores, not property valuations.

An implicit price of zero

When a road or a building is appraised, its costs and benefits are weighed in money. Biodiversity usually enters that calculation at zero. That reflects missing measurement rather than a lack of value.

Denmark has a national map of ecological quality, the Biodiversitetskort, that scores every part of the country for its potential to support wild species. My research asks a simple question: do Danish homebuyers pay more to live near higher-quality nature, and if so, how much?

Ecological quality across Denmark

Average score within one kilometre of the homes sold in each parish, across about 964,000 recorded home sales, 2015 to 2025. Pick an index below. Darker always means richer nature.

Index:

Use the arrow keys to move through parishes one by one, or use the Find a parish selector below. Press Enter to repeat the selected parish. The selected parish is announced in text below the map.
Bioscore (1 km mean)

Static map of Denmark shaded by average ecological-quality bioscore per parish. Coastal areas, north Zealand and the central Jutland lakes show the highest ecological quality. Dense cities and intensively farmed areas show the lowest.

The interactive version of this map needs JavaScript. The figure above shows the same data: the average ecological quality within one kilometre of homes in each Danish parish.

How to read this. The colour shows the Biodiversitetskort score, a measure of habitat quality and the presence of species of conservation concern, averaged over the homes sold in each parish. A higher score means richer potential for wildlife. The colours sort parishes into six groups by rank, from very low up to the top few percent. They show how each parish compares with the rest of Denmark, not against a fixed standard, so the top group means among the richest parishes nationally, not a perfect score. This is not a property valuation, and it does not tell you what nature is worth for any individual home. Parishes with fewer than 30 sales are left grey because their average is too noisy to show.

What the three indices mean. The Biodiversitetskort score is the sum of two parts, a species score and a landscape score. The toggle above maps each on its own.

0 to 19 · species + landscape

Composite (bioscore)

The full Biodiversitetskort score, species records and landscape quality together. This is the measure behind the price estimate.

0 to 9

Species (artsscore)

Threat-weighted records of red-listed wildlife actually observed nearby. It leaves out the coast and the other landscape proxies.

0 to 10

Landscape (proxyscore)

Habitat, wetlands, hedgerows, old forest, low nitrogen and coastal proximity, the conditions that predict where wild species are likely to live.

What the split shows. The price premium comes out about the same whether it is measured on the full score or on the species part alone. Because the species part leaves the coast out, this points to homebuyers valuing biodiversity itself, not just being near the sea.

View the data as a table

What homebuyers reveal

Three findings from the analysis, stated in round numbers because the work is still preliminary.

~3%

Nature has a price

Homes surrounded by higher-quality nature sell for more. A one-step increase in the local bioscore is associated with about 3 percent higher prices, roughly DKK 60,000 to 70,000 for a typical home.

~⅔

Mostly about who lives where

Around two-thirds of that raw difference reflects wealthier buyers choosing to live near nature, rather than the price of nature itself. The premium that remains, comparing homes within the same neighbourhood, is smaller but still present.

< 1 km

A local effect

The premium is strongest for nature within a few hundred metres of the home and fades to nothing within a few kilometres. That is what you would expect for something experienced on a daily walk.

How far the premium reaches

The cards above are round-number summaries, and this chart is the estimate behind the local one. Each line is the price premium for a one standard deviation increase in ecological quality, measured over a widening circle around the home, from 100 metres out to 5 kilometres. Close to the home the premium is about 3 percent per standard deviation, and it fades to about zero by 5 kilometres, the range you would expect for something experienced on a daily walk. The species score, which leaves the coast out, almost matches the composite, while the landscape score is weaker. That points to homebuyers valuing biodiversity itself rather than nearness to the sea.

Show:

Each score is measured against its own spread, so the three lines can be compared directly.

Turn a line off to compare, or hover a distance to read the exact premium and its 95 percent range.

These are associations, measured after comparing homes in the same parish and the same quarter, and are best read as an upper bound rather than a causal effect.

How it is measured

The estimate comes from a hedonic price model: about 850,000 geocoded home sales, the subset of the roughly 964,000 recorded sales shown on the map with complete information on every home characteristic and control the model requires, with controls for the size, age, and construction of each home, its energy rating, distance to the coast and to transport, noise exposure, and the general greenness of the surroundings. Comparing homes within the same parish and the same quarter separates the role of ecological quality from the many other things that drive prices.

Greenness is not the same as biodiversity. A mown lawn and a species-rich meadow can look equally green from a satellite. The model holds greenness constant, so the estimate reflects ecological quality rather than just the amount of vegetation.

Across the roughly 964,000 home sales the two barely track each other, with satellite greenness and the composite ecological-quality score correlating at about r = 0.10, and they pull apart most in intensively farmed areas, where a bright green field can score low.

Satellite greenness
Map of Denmark shaded by satellite greenness. Farmland across Jutland and Funen shows as deep green, while coasts, dunes, heaths and city centres are paler.
Ecological quality
The same map of Denmark shaded by the composite ecological-quality bioscore. The farmland belt that looked green now scores low, while coasts, dunes and the central-Jutland lake district score high.
The two maps shade the same country by greenness and by ecological quality. Much of the farmland across Jutland and Funen looks green from a satellite but scores low for wildlife, so parishes like Lysabild and Skamby rank near the top for greenness and near the bottom for ecological quality. Places built on dunes, heath and coast, like Skagen and Rømø, run the other way.

What this is, and what it is not

What it is

  • A first revealed-preference estimate of the value of biodiversity quality in a Danish property market.
  • A way to replace the implicit zero in cost-benefit analysis with an evidence-based number.
  • A full account, including how much of the raw premium is explained by who lives where.

What it is not

  • A property valuation, or a price for the nature near any single home.
  • A causal claim. These are associations, with the limits any observational study carries.
  • A finished result. The paper is unpublished and the numbers may change before release.

Where this fits

This is part of my PhD at Aarhus University on measurement, uncertainty, and decision-making in infrastructure and environmental policy. The aim is to give cost-benefit analysis a defensible price for biodiversity, so that the value of nature is counted rather than assumed away.

A short summary of the working paper sits with my other research. A link to the full paper will be added when it is released.

Data sources

Ecological quality: Biodiversitetskort (bioscore, 2021 edition), Danish Centre for Environment and Energy (DCE), Aarhus University.
Parish boundaries: DAGI, Styrelsen for Dataforsyning og Infrastruktur (SDFI) via Dataforsyningen, licensed CC BY 4.0.
Property transactions: compiled from public Danish property records, 2015 to 2025.
Greenness: Normalized Difference Vegetation Index from Sentinel-2 imagery.

Interested in this work?

I am always glad to discuss biodiversity valuation, environmental cost-benefit analysis, and the economics of nature.