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This paper aims to develop a conceptual understanding and a methodological approach for calculating residential net initial yields for both a buy-to-hold and rental investment strategy from hedonic models.

The markets modelled comprehend of dwellings for rent and sell in Germany. For each of them, two regression models are estimated to extract implicit prices and rents for an artificial identical dwelling and estimate the willingness to pay for the same asset from both a buy-to-hold and rental investment strategy.

The 3,381 estimated net initial yields in the 161 German markets showed a spatial pattern with the biggest and most attractive cities showing the lowest yields and a self-adjusting process in the markets surrounding the top cities. The net initial yields over time show that prices have increased stronger than rents, leading to rock bottom yields for residential assets and a significant premium in comparison to government bond yields. The approach responds to the spatial hierarchy of markets in Germany, meaning that the level of the estimated yields is accurate and achievable from an investment perspective.

The investment case in residential markets is certainly unique as net initial yields are scarce, especially due to the relatively low number of investment comparables. The paper sheds light on this problem from a conceptual and methodological perspective and confirms that investment yields are deducible by making usage of hedonic models and big data.

In the era of digitalization and big data, residential assets are mostly brought to the market via digital multiple listing systems. Transparency is an essential barrier when assessing the pricing conditions of markets and deriving investment decisions. Although international brokers do provide detailed investment comparables on – mostly commercial – real estate markets, the residential sector remains a puzzle when it comes to investment yields. The paper sheds light on this problem.

This paper aims to investigate the foreclosure discount for the German residential market in the years from 2008 to 2011.

The determinants of the foreclosure discount are estimated in a hedonic price model. The analysis is based on a unique data set compiled from three different data sources with 135,000 foreclosed properties.

The findings reveal that residential units in foreclosures are sold at a discount of 19 per cent compared to residential units with similar characteristics that are not in foreclosure. Second, a regional pattern can be observed, with discounts being negatively correlated to unemployment risk and liquidity. Third, the model with interaction terms shows that foreclosure discounts are linked to specific property characteristics. Fourth, these object-related risks are typically smaller than regional risks or locational risks.

Given the highly fragmented system of Gutachterausschüsse in Germany, who are responsible for collecting transaction data, we were not able to directly analyze transaction data, but only a proxy for this price information.

The results can be important for financial institutions that are trying to assess the risk of lending for a specific object in a specific location. So far, banks primarily try to assess the default risk of private lenders by analyzing the debtor’s financial position and the quality of the property. The analysis provides insights into which characteristics of a property might imply additional risk, and in which region these risks are biggest.

To the best of the authors’ knowledge, this is the first attempt to analyze the foreclosure discount for the German housing market.

Germany has a polycentric city structure. This paper aims to reduce complexity of this structure and to find a reliable classification scheme of German housing markets at city level based on 17 relevant market parameters.

This paper uses a two-step clustering algorithm combining k-means with Ward’s method to develop the classification scheme. The clustering process is preceded by a principal component analysis to merely retain the most important dimensions of the market parameters. The robustness of the results is investigated with a bootstrapping method.

It is found that German residential markets can best be segmented into four groups. Geographic contiguity plays a specific role, but is not a main factor. Our bootstrapping analysis identifies the majority of pairwise city relations (88.5%) to be non-random.

A deeper discussion concerning the most relevant market parameters is required. The stability of the clusters is to be re-investigated in the future, as the bootstrapping analysis indicates that some clusters are more homogeneous than others.

The developed classification scheme provides insights into opportunities and risks associated with specific city groups. The findings of this study can be used in portfolio management to reduce unsystematic investment risks and to formulate investment strategies.

To the best of the authors’ knowledge, this is the first paper to offer insights into the German housing markets which applies principal component, cluster and bootstrapping analyses in a sole integrated approach.

The purpose of this paper is to investigate the effect of energy consumption on the financial performance of German residential buildings in a large panel framework. The authors provide evidence that energy efficiency in the residential sector is a relevant factor affecting both tenant investment decisions and consequently the performance of investor portfolios.

Based on the IPD Database and information from the German statistical office, the authors create portfolios of buildings across several energy consumption levels in order to describe the energy pricing mechanism in the context of total return and rent price. Furthermore, the authors apply conditional and unconditional regressions over the period of 2008 and 2010, to accurately quantify the energy price premium in the German residential market.

The descriptive portfolio results show that energy‐efficient buildings yield an up to 3.15 percent higher return and 0.76 €/m² higher rent than inefficient buildings. Furthermore, the regression results indicate that a one percent decline in energy consumption affects the total return of buildings positively by +0.015 percent. The hedonic results additionally show that one percent energy conservation boosts rent prices by +0.08 percent and market value by +0.45 percent, ceteris paribus.

Overall, the study presents an alternative methodology for describing and estimating hedonic datasets and offers some initial empirical evidence on the energy price premium in German residential markets. The paper contributes to prior European studies regarding the use and implications of energy performance certificates and confirms their significant impact on residential housing performance variables.

With a view to the unconventional monetary policy measures implemented in the euro area in recent years, this study aims to investigate whether the recent house price increases in Germany are signals of an incipient overheating of the German housing market.

This paper presents a valuation measure for residential property based on a large and exhaustive regional panel data set for Germany. The fitted house prices from a panel regression at the district level, taking into account spatial spillovers, are taken as a measure of the fundamental equilibrium house prices, which can be aggregated for various regional subsets.

The estimation results suggest that apartment prices over the past years substantially exceeded the fundamental price suggested by the model, in particular in the big cities. Single-family houses appear to be markedly overvalued mainly in the cities. The low level of interest rates in recent years appears to have contributed to the emergence of misalignments.

Exploiting the variation across local housing markets, the estimation approach provides value-add for the estimation of house price valuation results in various regional subsets, as conventional time-series approaches to valuing property are subject to severe data limitations in the case of Germany.

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 purpose of this paper is to test the asymptotic properties and prediction accuracy of two innovative methods proposed along the hedonic debate: the geographically weighted regression (GWR) and the generalized additive model (GAM).

The authors assess the asymptotic properties of linear, spatial and non-linear hedonic models based on a very large data set in Germany. The employed functional form is based on the OLS, GWR and the GAM, while the estimation methodology was chosen to be iterative in forecasting, the fitted rents for each quarter based on their 1-quarter-prior functional form. The performance accuracy is measured by traditional indicators such as the error variance and the mean squared (percentage) error.

The results provide evidence for a clear disadvantage of the GWR model in out-of-sample forecasts. There exists a strong out-of-sample discrepancy between the GWR and the GAM models, whereas the simplicity of the OLS approach is not substantially outperformed by the GAM approach.

For policymakers, a more accurate knowledge on market dynamics via hedonic models leads to a more precise market control and to a better understanding of the local factors affecting current and future rents. For institutional researchers, instead, the findings are essential and might be used as a guide when valuing residential portfolios and forecasting cashflows. Even though this study analyses residential real estate, the results should be of interest to all forms of real estate investments.

Sample size is essential when deriving the asymptotic properties of hedonic models. Whit this study covering more than 570,000 observations, this study constitutes – to the authors’ knowledge – one of the largest data sets used for spatial real estate analysis.

This study aims to answer the following questions which have not been investigated in the literature to the best knowledge: Is there any bubble in the German housing sector between 2005–2009 and 2012–2017? and Is there any linkage between economic policy uncertainty and the housing sector price index?

This study aims to shed some light on the German’s housing sector by investigating the housing sector bubble and the causal link between the housing sector index and economic policy uncertainty in Germany, using GSADF, Granger causality, Toda Yamamoto causality and wavelet coherence tests.

The findings reveal that there are some bubbles in the housing sector in Germany for the periods investigated, there is a positive correlation between economic policy uncertainty and housing sector price index at different frequencies and different periods and between 2008 and 2009 and between 2011 and 2013, economic policy uncertainty leads housing sector price index. The consistency of the findings from wavelet coherence is confirmed by the outcomes of Granger causality and Toda Yamamoto causality tests.

To the best knowledge, this is the first study that empirically investigates the relationship between the housing sector and EPU using a novel wavelet econometric method. In addition, this paper extends the research focused on the associations between the housing sector and EPU, by checking the bubbles in the market in different time horizons by using the longest available data span. Furthermore, the consistency of the findings from wavelet causality is confirmed by the outcomes of Granger causality and Toda Yamamoto causality tests. Finally, compared to the previous literature on the relationship between housing and EPU, the study uses a hedonic index for housing for the first time in the case of Germany.

The purpose of this paper is to analyse the influence of regulations, perceptions, and promotions on the emergence of an innovation system for wood‐framed multi‐storey buildings in Germany, Sweden and the United Kingdom (UK).

This descriptive paper made a qualitative analysis of information collected mainly from secondary sources such as reports, newspapers, journal publications, conference proceedings and general internet search.

Results showed that the conditions for market growth of multi‐storey construction seemed to be the most favourable in Sweden followed by the UK and Germany. The regulations are stringent in Germany, followed by the UK and Sweden. In all countries, the construction professionals seemed to have negative perceptions regarding engineering properties of wood. Similar negative perceptions exist among the general public in Germany and the UK, but not in Sweden. The wood construction promotional activities in Germany and the UK are directed to all types of houses, while in Sweden multi‐storey buildings are targeted.

An important implication of this paper was that it highlighted the usefulness of cross‐country surveys at the European level, in order to better understand observed differences in the adoption of innovative systems. However, there might be shortcomings in the comparability of the information across the countries analysed because it was difficult to make an objective assessment of the claims made in some of the information sources. Also, there was varying and limited information about the survey methodologies used in some of the reviewed studies.

The study showed that market intervention is needed to promote radical or really new innovations such as wood construction. The variations in the promotional measures undertaken partly explained the variations in growth of wood construction system in the three countries.

The paper applied a theoretical framework on technology transition to analyse emergence of wood construction system in Germany, Sweden and the UK. The framework can be applied to analyse the development of wood construction system in other countries also.

The purpose of this paper is to assess the impact of the Energy Performance Certificate (EPC) on the Italian real estate market, focusing on old buildings. The contribution of EPC labels to house prices and to market liquidity was measured to analyze different aspects of the selling process.

A traditional hedonic model was used to explain the variables of listing price, transaction price, time on the market and bargaining outcome. In addition to EPC labels, the building construction period and the main features of apartments were included in the model. A sample of 879 transactions of old properties in Turin in 2011-2014 was considered.

A first hedonic model let us suppose that low EPC labels (E, F and G) were priced in the market although EPC labels explained only 6-8 per cent of price variation. A second full hedonic model, which included apartment characteristics, revealed that EPC labels had no impact on prices.

In Italy EPC has been mandatory for house transactions since 2009, so there are few studies on the effect of EPC on the Italian real estate market at least to our knowledge. Furthermore, unusually for the Italian context, in this paper also transaction prices were analyzed, in addition to the more frequently used listing prices.