Interview on the Green Value of Real Estate

As climate and energy regulations tighten across Switzerland, the real estate sector is facing a fundamental redefinition of value. What is a building truly worth today if costly renovations will be legally required tomorrow?

In this interview, Eric Jondeau (HEC-UNIL) and Alexandre Pauli (E4S – EPFL) present their latest research on the green value of real estate through a financial lens. Rather than treating sustainability as a premium or “nice-to-have,” this research reframes green value as the absence of financial risk—a critical shift for investors, policymakers, and property owners navigating the transition to a low-carbon built environment.

What is your research about?

Imagine you are buying a used car. You know that in a few years, new laws will ban old, polluting engines from entering the city center. You wouldn’t pay the same price for that car as you would for a new electric one. You would ask for a discount because you know you’ll eventually have to pay for an expensive engine upgrade or stop driving it.

Our research applies this same logic to buildings. We created a financial tool (a valuation framework) that calculates how much value a building loses today because of the renovations it will legally need in the future.

• Instead of just looking at what a building is worth now, we look at the « brown discount“: the loss in value due to future regulatory costs and risks.

• We move away from viewing “green value” as a nice-to-have bonus and instead view it as the absence of financial risk.

Why is it important for the energy transition to look at Swiss buildings?

The Swiss building sector is a massive piece of the climate puzzle, and looking at it is critical for two main reasons:

• Huge Environmental Impact: Buildings in Switzerland account for nearly 40% of the country’s final energy consumption and over 22% of greenhouse gas emissions.
• An Aging, Fossil-Fuel Dependent Stock: Only about17% of Swiss buildings were constructed after 2000. This means the vast majority are older and inefficient. Furthermore, relying on fossil fuels is still the norm here, with heating oil and gas accounting for over 55% of heating sources.

How it affects people: Because Switzerland has a very high percentage of tenants (nearly 58%), there is a “split incentive” problem. Owners pay for renovations, but tenants benefit from lower energy bills. Our research helps align these financial realities so that necessary renovations, which reduce emissions and energy bills, actually get financed.

How does your valuation framework work?

Our framework relies on a Discounted Cash Flow (DCF) model. This is a standard method for valuing assets by estimating the revenues and costs they will generate in the future. However, we added a twist. We simulate two different trajectories for the same building to see the difference in value:

1. The Standard Strategy (Business as Usual): We assume the owner does the minimum. They maintain the building but do not target any specific energy improvements. They renovate parts only when they become obsolete and do not worry about upcoming climate laws.

1. The Constrained Strategy (Regulatory Compliance): We assume the owner must comply with future laws. For example, if the Canton of Geneva requires a certain energy score by 2031, or if there is a federal ban on fossil heaters by 2050, we program the model to force those renovations into the budget before the deadline.

The Calculation: We compare the Net Present Value (NPV) of these two trajectories. The difference between them isthe Brown Discount. It represents the cost of complying with the law. We also use Monte Carlo simulations (running the model thousands of times with random variables) to account for uncertainties like fluctuating construction costs, energy prices, and the “performance gap” (when renovations don’t save as much energy as promised).

What did you find out?

We applied our model to real Swiss real estate portfolios (anonymous Fund 1 and Fund 2) and found several key insights:

• The “Brown Discount” is Real: Buildings that rely on fossil fuels or have poor energy ratings (CECB classes F or G) suffer a substantial discount. For the portfolios we studied, the discount ranged from roughly 0.23% to 1.42% of the value per year, depending on how strict the regulations were (Cantonal vs. Federal scenarios).
• Renovation Reduces Risk: This was a crucial finding. Non-renovated buildings have highly “volatile » values, meaning their future financial performance is very uncertain because they are exposed to regulatory shocks and construction cost spikes.

• • As shown in the data, recently renovated buildings show stronger resilience and visibility on future cash flows.

• • For “Fund 2,” which had deeper renovation needs, the risk of extreme financial loss (Value-at-Risk) increased significantly under strict regulations.

Can you give examples of how the proposed framework could be used in real life?

Our framework is designed to be an operational tool for owners, managers, and investors. They can use it in different ways:

• Strategic Planning for Owners: An owner can use the tool to answer: “Is it better to renovate now, or wait until the law forces me to?” The model quantifies the financial risk of waiting (e.g., potential bottlenecks in construction or rising costs).
• Risk Assessment for Banks/Investors: A bank holding a mortgage portfolio could use this to stress-test their loans. They could ask: “If the Canton of Vaud enforces a C-rating by 2040, how much collateral value do we lose across our portfolio?”.
• Negotiating Property Prices: A buyer can use the calculated “Brown Discount” to negotiate a lower purchase price for an older building, economically justifying the reduction by pointing to the specific future CAPEX (capital expenditures) required by law.

What’s next for this project or future research?

While our framework is a strong step forward, there is still work to be done to refine the accuracy:

• Better Data Granularity: We currently use averages for renovation costs and energy impacts. Future research needs more detailed data on specific technical components and actual renovation costs from the market to be more precise.
• Market Dynamics: Our model assumes owners must renovate. It doesn’t yet account for market reactions, such as the potential for higher rents after renovation (the “green premium” on income),  the impact on the cost of financing, or the risk of stranded assets.

• Macroeconomic Feedbacks: If every building in Switzerland tries to renovate at the same time to meet a 2050 deadline, construction costs will skyrocket, in particular because of labor shortages. Our current model does not yet simulate this system-wide supply/demand tension.