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This paper investigates the impact of CO2 vs CO2 “equivalents” (CO2e) by analyzing fugitive emissions, with a particular focus on Fluorinated gases (F-gases), arising from refrigerant leakages in buildings. F-gases are an especially powerful set of GHGs with a global warming potential hundreds to thousands of times greater than that of CO2.

The significant impact of CO2e is tested by means of an empirical study with current consumption data from German food retail warehouses. This evaluation involves the analysis of the Carbon Risk Real Estate Monitor's country- and property-type specific pathway, coupled with a paired samples t-test to examine the hypotheses. The assessment is undertaken by evaluating the type of gas and the amount of leakage reported in the baseline year, subsequently converting these values to CO2e units.

On average, F-gases account for 40% of total building emissions and nearly 45% of cumulative emissions until 2050. In light of ongoing climate change and the rising number of Cooling Degree Days (CDDs), it becomes imperative to assess both the environmental and economic impact of F-gases and to transition toward environmentally friendly refrigerants.

The analysis sheds light on the seldom-addressed threats posed by CO2e emissions stemming from refrigerant losses. By identifying these threats, investors can devise strategies to mitigate potential future costs and carbon risks.

The purpose of this paper is to investigate the role of distinct types of heating technology and their price impact in German residential real estate markets, considering a wide range of other housing market determinants. The authors aim to test and to verify specifically, whether the obsolescence of heating technology leads to a significant price discount and whether higher technological standards (and environmental friendliness) come with a price premium on the market.

The authors create housing market models for rental and sales segments by constructing generalized additive models with explicit multi-layered spatial components. To elaborate a profound and contemporary answer using these models, the authors perform large-sample regression analyses based on more than 400,000 observations covering German residential properties in 2015.

First and foremost, the heating system indeed shows significant explanatory importance for measuring housing rents and purchasing price. Second, the authors find that it makes a difference whether clean “green” technologies are implemented or whether “brown” systems with obsolete technology or fossil energy sources is on hand. Ultimately, the authors conclude that while low energy consumption indeed comes with a price premium, this needs to be interpreted together with the property’s heating type, as housing markets seem to outweigh the “green premium” by “brown discounts” if low energy consumption figures are powered by a certain type of heating technology system.

Aside of a possible omitted variable bias, the main research limitation is constituted by the integration of asking prices in the analysis, as actual transaction prices are not systematically transparent on national level in Germany. Limitations are discussed at the end of the paper.

This work supports investors who face the challenge of making environmental- and energy-related decisions as well as appraisers who deliver financial fundamentals for such. Third, the paper supports both asset managers as well as investment strategists in argumentation pro-environmental investments beyond all ecological necessity.

This paper contributes to the current discussion on climate change and the eclectic role of real estate in this context. The authors deliver evidence on pricing effects as a measure of socioeconomic acceptance of progressive heating technology and environmental friendliness as an imperative of twenty-first century societies.

This is the first study on “green premiums” or “brown discounts” that includes heating technology as a potential and distinct driver of value and rents. It is a contemporary contribution and delivers original information on the quantitative impact of contemporary and anachronistic technology in heating to researchers as well as investors and appraisers.

The risk management of transitory risk for real assets has gained large interest especially in the past 10 years among researchers as well as market participants. In addition, the recent regulatory tightening in the EU urges financial market participants to disclose sustainability-related financial risk, without providing any methodological guidance. The purpose of the study is the identification and explanation of the methodological limitations in the field of transitory risk modeling and the logic step to advance toward a stochastic approach.

The study reviews the literature on deterministic risk modeling of transitory risk exposure for real estate highlighting the heavy methodological limitations. Based on this, the necessity to model transitory risk stochastically is described. In order to illustrate the stochastic risk modeling of transitory risk, the empirical study uses a Markov Switching Generalized Autoregressive Conditional Heteroskedasticity model to quantify the carbon price risk exposure of real assets.

The authors find academic as well as regulatory urgency to model sustainability risk stochastically from a conceptual point of view. The own empirical results show the superior goodness of fit of the multiregime Markov Switching Generalized Autoregressive Conditional Heteroskedasticity in comparison to their single regime peer. Lastly, carbon price risk simulations show the increasing exposure across time.

The practical implication is the motivation of the stochastic modeling of sustainability-related risk factors for real assets to improve the quality of applied risk management for institutional investment managers.

The present study extends the existing literature on sustainability risk for real estate essentially by connecting the transitory risk management of real estate and stochastic risk modeling.

The purpose of this paper is to analyze potential diversification benefits of American real estate assets for European investors. Since European real estate yields are compressed due to several reasons, including high market liquidity and low interest rates, investment managers seek opportunities to provide attractive risk-return profiles for investors. Therefore, empirical proof for improvements to risk-return profiles is highly necessary in the outlined market environment.

The empirical study uses a classic mean-variance optimization approach. In order to isolate potential diversification benefits two investment environments are compared: first, an optimization for the European investment horizon is carried out. Subsequently, the same optimization is performed for European and American assets. For both scenarios, risk-return profiles are obtained and compared.

Two major findings can be stated: first, higher correlations between European and American markets can be observed for the present data in comparison to older studies. Second, the mean-variance optimization of solely European and then mixed European-American portfolios show improvements in risk-return profiles for the latter. Thus, diversification benefits of American properties for European real estate investors can be confirmed.

The empirical study reveals diversification benefits for European investors. Thus, the asset allocation of European investors could be affected by allocating capital toward the USA in order to improve risk-return profiles.

The value of the paper is a precise analysis of two markets, namely Europe as well as the US. Thus, the paper isolates the practical implications for European investors, who are trying to improve risk-returns profile by allocating capital toward the USA.

This study examines whether green buildings enjoy more favorable financing terms compared to their non-green counterparts, exploring the presence of a green discount in commercial real estate lending. Despite the extensive research on green premiums on the equity side, lending has received limited attention in the existing literature, even as regulations have increased and ambitious net-zero targets have been set in the banking sector.

In this study, the authors leverage a unique dataset comprising European commercial loan data spanning from 2018 to 2023, with a total loan value exceeding €30 billion. Hedonic regression analysis is used to isolate a potential green discount. Specifically, the authors rely on property assessments conducted by lenders to investigate whether green properties exhibit lower interest rate spreads and higher loan-to-value (LTV) ratios.

The findings reveal the existence of a green discount in European commercial real estate lending, with green buildings enjoying a 5.35% lower contracted loan spread and a 3.92% lower target spread compared to their non-green counterparts. However, this analysis does not indicate any distinct advantage in terms of LTV ratios for green buildings.

This research contributes to a deeper understanding of the interaction between green properties and commercial real estate lending, offering valuable insights for both lenders and investors.

This study, to the best of the authors’ knowledge, represents the first of its kind in a European context and provides empirical evidence for the presence of a green discount.

On the basis of corporate wholesale and hypermarket stores, this study aims to investigate the relationship between energy consumption, physical building characteristics and operational sales performance and the impact of energy management on the corporate environmental performance.

A very unique dataset of METRO GROUP over 19 European countries is analyzed in a sophisticated econometric approach for the timeframe from January 2011 until December 2014. Multiple regression models are applied for the panel, to explain the electricity consumption of the corporate assets on a monthly basis and the total energy consumption on an annual basis. Using Generalized Additive Models, to model nonlinear covariate effects, the authors decompose the response variables into the implicit contribution of building characteristics, operational sales performance and energy management attributes, under control of the outdoor weather conditions and spatial–temporal effects.

METRO GROUP’s wholesale and hypermarket stores prove significant reductions in electricity and total energy consumption over the analyzed timeframe. Due to the implemented energy consumption and carbon emission reduction targets, the influence of the energy management measures, such as the identification of stores associated with the lowest energy performance, was found to contribute toward a more efficient corporate environmental performance.

In the context of corporate responsibility/sustainability of wholesale, hypermarket and retail corporations, the energy efficiency and reduction of carbon emissions from corporates’ real estate assets is of emerging interest. Besides the insights about the energy efficiency of corporate real estate assets, the role of the energy management, contributing to a more efficient corporate environmental performance, is not yet investigated for a large European wholesale and hypermarket portfolio.

A green agenda has become a growing subject throughout an increasing number of European listed real estate companies over the last decade. The focus on sustainability is presumably not only goodwill or legislation driven but is rather a benefit driven action to achieve an economic surplus. The purpose of this paper is the development of an adequate sustainability definition, the investigation of the effect of a sustainability agenda on a company level, and the identification of possible financial benefits.

This is an explorative qualitative and quantitative study. First, the authors developed a four‐bottom‐line real estate sustainability agenda in accordance with the guidelines of the European Public Real Estate Association and the Global Reporting Initiative. Second, the study examines 80 European listed real estate companies from 2006 until 2009, and third, the study applies a panel analysis with conditional and unconditional regression techniques.

After classifying firms across different levels of sustainability intensity and quantifying the impact of an intensive green agenda the authors found a positive linkage between a green agenda and a green performance, especially in terms of an increased ability to generate revenues and a decreased level of idiosyncratic stock volatility. As a result, green commitments are not merely altruisms but are economically driven instead.

This paper gives, to the authors' knowledge, a first insight of how European real estate listed companies behave in terms of corporate social responsibility. The study contributes to the theoretical literature of corporate sustainable real estate companies by establishing an economic transmission mechanism as well as providing empirical evidence in favour of responsible activities.

The paper aims to estimate the effect of energy efficiency on the Market Value of office buildings and consider whether this effect increases over time.

The authors analyze a dataset of office building valuations from 2009 to 2011, provided by the German Investment Property Database. The authors use hedonic regression models to determine the effect of energy efficiency and energy consumption on Market Values. Using generalized additive models (GAM) for modeling nonlinear covariate effects, the authors control for further building characteristics and location. Due to the small sample size, the authors introduce an innovative econometric approach that mitigates this problem.

Mainly due to the small sample size, and in spite of the newly developed econometric methodology, the authors do not find clear evidence of the relationship between energy efficiency and the Market Value. However, the study nonetheless provides interesting insights into the composition of office building Market Values in Germany.

In addition to the empirical results for the German office market, the main contribution of this paper lies in the econometric methodology. Beside the application of cutting-edge statistical techniques, the authors develop a method for handling datasets, for which the variable of interest is rarely observed, leveraging on the total available data. Thus, the methodology offers promising prospects for future research in similar settings.