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This paper aims to assess the consequences of credit risk downgrades on credit default swaps (hereafter CDS) written on financial companies from two different perspectives, namely the overall stress level observed on the market and the rating agency performing the downgrade.

The authors' study relies on several wavelet analyses performed on different subsamples of data coming from the iTraxx index, the downgrade dates ranging between October 28, 2005 and February 3, 2015. This study highlights that both the overall stress level and the rating agency taking actions do have an influence on how market players will react.

The authors' study points out that market players will anticipate and react to downgrades in different ways depending on the level of stress. Feedback effects are observed after the downgrade only during periods of tension. From a rating agency point of view, the authors' study shows that the market share as well as the reputation of each agency have an influence on the aftermaths of a downgrade.

To the authors' knowledge, this paper is the first one relying on wavelet to analyse the consequences of a downgrade on CDS market. The use of this methodology allows to capture the multiple impacts of a downgrade through time and, therefore, to analyse the dynamics triggered on the market by a negative rating event. Moreover, the study of the downgrades' repercussions of each of the main rating agencies underlines a psychological dimension in the way market players react to a downgrade.

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.

The purpose is twofold. First, this study aims to establish that black box tree-based machine learning (ML) models have better predictive performance than a standard linear regression (LR) hedonic model for rent prediction. Second, it shows the added value of analyzing tree-based ML models with interpretable machine learning (IML) techniques.

Data on Belgian residential rental properties were collected. Tree-based ML models, random forest regression and eXtreme gradient boosting regression were applied to derive rent prediction models to compare predictive performance with a LR model. Interpretations of the tree-based models regarding important factors in predicting rent were made using SHapley Additive exPlanations (SHAP) feature importance (FI) plots and SHAP summary plots.

Results indicate that tree-based models perform better than a LR model for Belgian residential rent prediction. The SHAP FI plots agree that asking price, cadastral income, surface livable, number of bedrooms, number of bathrooms and variables measuring the proximity to points of interest are dominant predictors. The direction of relationships between rent and its factors is determined with SHAP summary plots. In addition to linear relationships, it emerges that nonlinear relationships exist.

Rent prediction using ML is relatively less studied than house price prediction. In addition, studying prediction models using IML techniques is relatively new in real estate economics. Moreover, to the best of the authors’ knowledge, this study is the first to derive insights of driving determinants of predicted rents from SHAP FI and SHAP summary plots.

The purpose of this paper is to better understand the constraints related to developing small-scale public-private partnerships (PPPs) and how to reduce them.

The paper provides a general review of the characteristics of small-scale PPPs and identifies overarching concerns.

The paper finds for small-scale PPPs constraints with respect to the definition, government processes and procedures, transaction costs, public capacity and institutional structure; important issues of transaction costs, minimum size requirement and increasing popularity and recommendations for further development.

Since most small PPPs are conducted by cities and regional governments, many local bodies would benefit from a better understanding of small-scale projects, helping to develop standard documentation, which is especially relevant for small-scale projects given their relatively large transaction and bid costs, supporting the long-term growth of small PPPs.

Small-scale PPPs have different characteristics compared with large projects and these characteristics should be studied separately. Although the benefits of small-scale projects are undeniable, relatively few have been undertaken relative to the substantial requirement. A more thorough understanding of the constraints related to developing small-scale PPPs and how to reduce them would help the subset of small projects to reach its full potential. This paper serves as a first step, clearing the ground for further research in specific areas.

Since 2005, Belgian housing prices have strongly increased. As the timing coincides with the implementation of a new fiscal package in order to stimulate homeownership, our study attempts to provide an understanding whether the mortgage interest and capital deduction (MICPD) policy has had the side-effect of increasing housing prices while, at the same time, controlling for key housing price determinants.

A fixed-effects regression model is used on a panel dataset of the three Belgian regions over the period 1995–2015.

Estimations are carried out separately for different house types, being useful as our empirical analysis ascertains a significant price-increasing effect for ordinary houses and apartments but a significant price-reducing effect for villas. In addition, we find, among other things, that interest rates' influence has been less substantial than commonly thought.

These results are relevant for all governments willing to stimulate homeownership through fiscal stimuli.

The purpose of this paper is to develop a better understanding of the debt structuring of project finance (PF) loans and the main drivers affecting the maturity of bank loans in infrastructure deals. When banks grant loans to a project, they have two decision variables: the interest margin or the spread and the maturity of the loan. Although several studies analyze the drivers of the spread, few studies in the literature look at the maturity of bank loans. As infrastructure projects are typically highly leveraged, the structuring of bank lending is an important parameter in the financial viability of the project.

The paper develops a regression analysis of the loan’s maturity on four categories: characteristics of the project, political risk of the country where the project is executed, the macro-economic setting and the regulatory framework. By using a new data set of InfraDeals containing data on bank loans of more than 1,800 infrastructure projects worldwide from 1997 to 2016, this paper reveals new insights on the debt structuring of banks for PF loans.

The results indicate that the maturity of bank loans granted to infrastructure deals is predominantly driven by political risk and regulation, rather than the structuring of the project. This implicates that the region where the deal is closed weighs more heavily than the specificities of the project itself.

The results have important policy implications. The paper allows to develop a better understanding on how political risk and new regulation, like Basel III, might affect the PF market. The paper is the first one finding empirical evidence of the impact of Basel III regulation on PF lending. By delving deeper into the political risk variable, the authors formulate several recommendations to mitigate political risk.

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 purpose of this paper is to develop a better understanding of the pricing decisions of banks for project finance (PF) loans and the main drivers affecting the cost of debt in infrastructure deals. As infrastructure projects are typically highly leveraged, the cost of bank lending is an important driver of the overall funding costs for the project.

First, the paper provides a general review of the drivers of the cost of funds in PF. Second, the paper develops a regression analysis of the loan’s spread on four categories: project, loan, bank characteristics and the economic environment. By using a new data set of InfraDeals containing data on bank spreads of more than 700 infrastructure projects worldwide from 2006 to 2016.

The results show that the cost of debt is predominantly affected by the market and the business cycle, rather than the structuring of the project. This implicates that the timing when the deal is closed weighs more heavily than the specificities of the project itself.

The results have important policy implications. As PF deals are often paid for by taxpayers, this paper could help policymakers to use public funds for infrastructure in the most efficient way.

One weakness of existing studies in PF loan pricing is that they undervalue the role of the economic environment in the cost of debt. Few studies in the literature include macroeconomic control variables in their model and the others do not seem to find significant results. This paper reveals new insights on the pricing decisions of banks for PF loans.

In this paper, we will address privacy and trust issues that arise in more advanced software systems. Though a lot of information is currently available in electronic form, not all of it should widely be accessible to everybody. The involved parties need full control on how their data are used and who has access. If the system consists of autonomous software agents, this problem requires extra attention and new working principles. We illustrate this in the case of a communication platform for multimodal transport. The major aim of the communication platform is to enhance exchanging information and to ultimately improve organisation/collaboration within the transport sector. A better informed view of the transport sector will facilitate better considered decisions for users of the communication platform. The software system merits credibility by accurately modelling all the relevant real world interactions of potential users of the system. We opted for a connectivity solution in which software agents act as representatives of the parties involved. All agents can be equipped with human‐like skills and qualities such as intelligence, autonomy, and the ability to cooperate, coordinate and negotiate. We demonstrate how cooperation between parties can be achieved while respecting their sensitivity concerning information.