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Currently, residential forecasting literature is limited with few to no forecasting papers that consider residential prices and energy consumption for the selling and rental market within a single study. The purpose of this paper is to study the prices and energy usage for both markets by combining an explanatory model with the predictions of a predictive model, which will lead to a better understanding of the forecasting results.

This study presents an econometric comparison between 508,612 selling properties and 174,007 rental properties transacted in Flanders between January 2019 and December 2023. The authors study their prices and energy usage by combining the causal results of a hedonic price model (HPM) with the predictions of an autoregressive integrated moving average model (ARIMA).

The authors find that both markets are extremely sensitive to changes in related factors, whereby selling prices are primarily influenced by macroeconomic factors, but rental prices and especially energy usage are also sensitive to market standards. Policies that target energy efficiency can therefore steer its future trend. In addition, in line with previous literature, the HPM shows an increasingly strong relationship between residential prices and energy efficiency over the years, indicating that these steering energy policies also indirectly monitor residential prices.

This study underscores the importance of integrating the results of an explanatory model with a predictive model. It demonstrates that combining them provides a more comprehensive understanding which is helpful for policymakers, real estate professionals and investors during their decision-making process.

The current literature has not investigated the perceived value of energy efficiency by households, regardless of financial benefits. Furthermore, there is a severe lack of research that investigates the effectiveness of the current format of EPC-labels. Therefore, the purpose of this paper is twofold: to study how households value energy efficiency in the housing market, regardless of price effects.

This study uses multiple hedonic regression models to analyse 706,778 Flemish properties for sale or rent between 2019 and 2023. The data is provided by Immoweb – the largest online real estate platform in Belgium. Given that the selling market is driven by different mechanisms than the rental market, the data set was divided in sold (522,164 listings) and rented properties (184,614 listings).

The ambiguous results of the A-label in the selling market indicate that the “class evaluation effect” found in related markets which use labels (e.g. household appliances) is also present in the housing market. However, the results of the other (lower) labels clearly show that owners do value energy improvements within labels, and this effect becomes stronger as the EPC-label becomes better. The rental market shows the opposite results. Energy improvements are only valued if they translate into a financial benefit. Taking these findings into account, the second part of this research shows that rescaling the EPC-label creates an incentive for improvements within labels.

This paper provides novel insights by studying the perceived value of energy efficiency in the absence of financial benefits and critically studying the effectiveness of the EPC-labels in their current shape. By investigating both the sales and rental market, the authors are able to make a comparison which creates valuable insights for academia, governments and real estate professionals.

The current literature on energy certificates shows that Energy Performance Certificate labels have an important effect on real estate prices. However, interestingly, the limited studies that address the rental market find significantly lower price premiums than the sales market. The purpose of this paper is to add to this literature, by doing a comparative analysis of price premiums in the sales and rental market in Flanders (Belgium).

This study uses a hedonic regression model to analyze 177,670 real estate listings between 2016 and 2021. The data is provided by Immoweb – the largest online real estate platform in Belgium. The data set was divided in sold and rented properties: the authors evaluated 126,217 sales listings and 51,453 rent listings.

The results confirm that energy efficient properties generate a price premium, but that this premium is significantly larger in the sales market than in the rental market. In addition, the findings indicate that both investors and landlords could benefit strongly from renovating dwellings – especially when renovating from an F label to an A label.

Previous research focuses strongly on the sales market, although in many countries the rental market is similar in size and responsible from much energy consumption. Interestingly, the few studies that are addressing the rental market, find singificantly smaller price premiums than in the sales market. The findings add to this literature tradition and offer a comparative analysis of price premiums in the sales and rental market in Flanders. This allows us to not only show the similarities between both markets but also highlight the differences – creating valuable insights for academia, governments and real estate professionals.

Literature has already analysed the relation between a property’s time on market (TOM) and other housing characteristics, but few to none include the property’s energy performance certificates (EPC) and none make a comparison between the selling and rental market. This paper aims to address these gaps by studying the relationship between TOM, price and EPC in both markets.

By introducing a combination of alternative tests, this study confirms a causal relation between TOM and price in the cross-sectional data. This allows this study to use a two-stage least square model and analyse 392,498 Flemish sale and rental properties transacted between 2019 and 2023.

The results indicate that both sale and rental properties with higher prices increase the TOM by 4–6 days, and this effect is even stronger in the selling market when the value-added tax is included. This study also finds that EPC labels have a complex relation with the time on market. A-labelled properties tend to increase the transaction time between 10 and 54 days, but B- and C-labelled properties decrease TOM between 20 and 30 days. In addition, the poorer performing labels (E and F) react differently across markets because of market-specific policies.

This paper provides novel insights by studying the relationship between TOM and EPC while also considering TOM’s endogenous relationship with the price. We control for these relationships in both the selling and rental market.