Archives Fundings

Coordinators: Per Agrell (CORE), Constantin Blome (CORE and University of Sussex) and Philippe Chevalier (CORE)
Financement: Kronos Group, Belgium
Researcher:/
Date: September 2017-September 2020

The Kronos Group Chair "Stratetic Sourcing and Procurement" is the fruit of a collaboration between Kronos Group and Louvain School of Management of the UCLouvain. The objective of the Chair is to promote research and education in the sourcing and procurement domain, contributing to fostering the profession to continue its transformation into a value creating and strategic profession. The Chair is unique for Belgium and also launching a unique Master's level specialization in sourcing and procurement in Belgium, integrated in Louvain School of Management. The research in the Chair aims at empirical, economic and strategic studies of procurement under transformation, in particular the innovative, ethical and environmental dimensions of the area.
 

Coordinator: Anthony Papavasiliou
Financement: Electrabel
Researcher: /
Date: February 2016-October 2020

The large-scale integration of renewable energy sources is creating increasing needs for flexibility. The optimal dispatch of conventional resources of a sub-hourly time scale in order to prevent binding ramping constraints is increasing the challenges of short-term operations. This project aims at developing optimization models and algorithms that can support the optimal utilization of generator flexibility in short-term operations.

Coordinator: Anthony Papavasiliou
Financement: Fonds de Recherche Pierre et Colette Bauchau
Researcher: Daniel Avila
Date: April 2018-December 2020

Africa has recently set ambitious renewable energy integration targets, best exemplified through the adoption of the African Renewable Energy Initiative (AREI) as well as by the large number of renewable infrastructure projects that are underway. The goals of this project are:

• To develop tools for optimizing the use of electricity in existing electric power systems, in particular optimally managing utility-scale storage in a system dominated by solar production;

• To develop tools for planning for future renewable systems, in particular randomized algorithms for obtaining optimal transmission expansion plans subject to net load and component outage uncertainty with probabilistic guarantees of optimality;

• Operating future distributed energy systems which rely less on centralized fossil fuel resources and more on decentralized renewable resources.

Coordinator: Paul Belleflamme (CORE)
Researcher:Leonardo Madio (CORE)
Date: August 2018-March 2020

This research project aims to investigate how the growing availability of instruments to i) block the invasiveness of ads and profiling, and ii) to protect individual privacy might or might not lead to unintended effects for the different economic agents

 

Move-in Louvain

Coordinator: Vincent Vannetelbosch (CORE)
Researchers: Chenghong Luo, Mariam Nanumyam and Akyal Taalaibekova
Financement: European Commission
Date: January 2017-December 2020

The Innovative Training Network ExSide combines an interdisciplinary research agenda with an innovative European joint doctoral training program, which provides doctoral fellows with a broad range of expertise and skills needed for a thorough analysis of expectation formation processes and their role in economics. Both the research projects and the training activities combine work in behavioral economics, psychoanalysis, opinion formation, network theory, agent-based simulation and economic modelling in different areas. The academic training will be complemented by extensive transferable skills training memasures, intersectoral training measures, provided by non-academic partners, ad career development training. Interaction with stakeholders, policy makers and the general public will play an important role in pursuing the ExSIDE agenda and disseminating the results. The ExSIDE consortium consists of eight leading European Universities and nine non-academic partners..

 

Expectations and Social Influence Dynamics in Economics (ExSIDE)

Coordinators: Johan Eyckmans (KU Leuven), Sandra Rousseau (KU Leuven), Paul Belleflamme (CORE) and Thierry Bréchet (CORE)
Researcher: : Huan Ha
Financement: BELSPO
Date: December 2014-September 2019

The IECOMAT project develops complementary numerical and analytical tools designed to study a particular aspect of sustainable material management, the circular economy. The models to be employed and to be developed range from input-output models over partial, computable and general equilibrium models as well as analytical industrial organisation models of economic incentives. The project will deliver dififerent modeling frameworks, scenario analysis, a wide variety of policy analyses and ultimately an assessment of potential of a more circular economy model for Belgium.
The IECOMAT project brings together a multidisciplinary team of experienced scientists from material and environmental engineering, environmental economics, industrial organisation and stakeholder consultation practice. This multidsciplinary team from a leading Flemisch research institute on sustainable material management (VITO) and two research universities (KU Leuven and UCLouvain) interact intensively. This leads to an interdisciplinary analysis of key scenarios for the Belgian economy. Some specific areas of expertise are subcontracted to national and international secialists in their domain. In all approaches, three fundamental perspectives are included: physical material flows, environmental effects and socio-economic impacts, and business incentives. Therefore, the IECOMAT project is about integrated assessment models for the transition towards a circular economy. In order to strenghthen a transdisciplinary dimension, the input of policy markers, practitioners and business stakeholders is actively sought.

Coordinators: Benoit Nemery (KU Leuven), Isabelle Thomas (CORE), Tim Nawrot (Universiteit Hasselt), Catherine Bouland (Université libre de Bruxelles), Patric Deboosere (Vrije Universiteit Brussels) and An Van Nieuwenhuyse (Institut de Santé Publique, Bruxelles).
Researcher: Sonia Trabelsi
Financement: BELSPO (BRAIN)
Date: July 2015-December 2019

Living in green/blue areas is associated with better health. This may be due to low air and/or noise pollution, opportunities for physical activity, facilitation of social contacts, and promotion of recoverty from fatigue and stress. Yet, socio-economic (SE) factors also explain inequalities in health and access to green/blue spaces. The GRESP-HEALTH project evaluates the associations between living in/close to a green/blue area on morbidity and mortability in Belgium. It assesses all-cause and cause-specific mortality, specific morbidities and perceived health, considering environmental pollutants and SE factors.
The project includes individuals registered in the Belgian censuses of 1991 and/or 2001. Three levels of observation are studies: individual, statistical sector (SS) and group of SS, following individual and ecological designs. Mortality information is based on the National Mortality Database (a linkage between cause-specific mortality (2004-2012) is derived from the IMA (Intermutualistisch Agentschap) database, which contains reimbursement data of prescriptions. For green/blue spaces, the surface, shape, accessibility and type are calculated for each SS. Residential area-specific exposure to air pollutants is obtained rom satellite images. Traffic noise databases are used whenever possible. We will consider SE factors such as material deprivation, education, and occupation. The analyses will be conducted separately in different age specific populations and types of area (urban, sub-urban rural). We will use multilevel models for clustered data within geographical areas. Interactions of green/blue spaces with air pollution and SE factors will be evaluated and stratified analyses in areas with similar SE and environmental characteristics will be performed. Morover, specifici population groups (gender, employment status) will be considered. the GRESP-HEALTH project will improve the scientific knowledge about the hiherto uncertain associations between living close to green/blue spaces and health.

Coordinator: François Maniquet
Researcher: Erika Pini
Financement: FNRS
Date: October 2018-September 2020

In this research, we investigate whether inequality may be responsible for the changes in the political spectrum that have recently occured in many countries, exploring the link between economic inequality, political polarization and participation, as measured by voter turnout. Indeed, the substantial increase in economic inequality that has been registered in many countries during the past decades is not free of consequences in the political sphere. In fact, when economic conditions are harsher, economic policy becomes a salient issue in the political debate and voters' preferences change accordingly. If politicians do not respond by adapting their proposals to the preferences of voters, this can only result in lower electoral participation. However, economic circumstances also affect political competition. In particular, during periods of high economic inequality we observe higher political polarization, which may in turn have a positive effect on voters' participation.
A model of political competition and turnout is dieveloped that is able to explain the relationship between economic inequality and elecltoral participation, by taking into account the effect of inequality on political polarization. We complement the theoretical theory study with an empirical analysis of the effect of inequlaity on polarization and the resulting impact on participation, and, focusing on the uS, we try to separately identify the causal effects of inequality and of polarization on turnout. Finally, we extend the analysis of the triple relation inequality-polarization-turnout to contexts of multi-party competition, by developing a citizen-candidate model, where we endogenize turnout by introuding the mis-match cost as a potential source of abstention. There, we try to explain both the shift of exiting parties towaords more extreme positions, and the emergence of new parties, of which countries like Italy, Spain and Germany are a clear example.

Coordinator: Anthony Papavasiliou (CORE)
Researcher: Gilles Bertrand (CORE)
Financement: FNRS
Date: October 2018-September 2020

The goal of this research is to evaluate the profitability of flexibility assets in the context of the large-scale integration of renewable energy on the electricity market. We characterize a flexible asset as an asset that can quickly adjust the quantity of its output. Some examples of flexible assets are combined cycle gas turbine and mumped hydro storage. This increased integration of renewable nergy results in two paradoxical impacts:
- On the one hand, the increase of renewable production implies that the market requires more flexibility close to real time.
- On the other hand, flexible units are currently being mothballed or retired in Europe due financial losses that are related to high marginal costs, despite the fact that these resources are offering valuable reserve services to the system.
Therefore, in order to ensure power system security, we need to increase the profit of flexible assets. We study this need for extra remuneraiton of flexible assets in two ways:
- We first analyze the market design problem. The idea of this line of research is to evaluate the imapct of a new remuneration strategy, referred to as scarcity pricing, on flexible generator profits.
- We additionally analyze a bidding strategy problem. Our main focus is on the continuous intraday market which is one of the short-term electricity markets that is becoming increasingly important but for which there still exists a limited amount of research. We believe that the CIM is important due to the fact that it allows valuable adjustments to renewable forecast errors, which are becoming increasingly significant in recent years due to the increasing integration of renewable sources.

Coordinator: Isabelle Thomas
Research: Arnaud Adam
Financement: FNRS
Date: December 2018-November 2020

The increasing number of trucks on the roads generates number of debates about sustainability. Transport quantitative analysis often rely on spatially aggregated and/or non exhaustive data (samples). This project aims at using unconventional "big data" (generated by on-board mandatory GPS deviceis) for refining freight transport geographies in Belgium. Three questions are raised in this project. (1) Is it possible to characterize each truck trace with on of several indices and make an insightful typology of the spatial shapes of routes ? (2) Is it possible to easily shift from raw GPS data to an origin-destination (places) matrices useful for transport modelling ? (3) How fare are the spatial realities extracted from this origin destination transport modelling or from current knowledge of the Belgian economic geographpy and logisticis organization?
Improving the nowledge in this domain is important for two reasons. Scientifically, it is to understand the geographical complexity of logisticsi and to solve some methodological issues such as to measure (quantify) unambiguously the "traces" of the trucks. In terms of policy issues, t is important to better understand and evaluate the spatial consequences of the kilometric tax in a heterogeneous space (Belgium). It is the actual uniform kilometric taxation environmentally, economically and socially equitable? Could a taxation varying space and time be more efficient? Yet could this new taxation generate new counterproductive effects?

Coordinator: Anthony Papavasiliou
Researcher: Céline Gérard
Financement: FNRS
Date: October 2017 - September 2019

The recent large-scale integration of renewable energies in electric power systems has resulted in various challenges in power system operations, due to the unpredictable, highly variable and non-controllable fluctuation of these resources. This has resulted in a growing demand for the incorporation of lexibility in the Central Western European electricity system in order to balance renewabme supply. Although storage devices can act as a source of flexibility, their cost is prohibitive for offering a definite solution to this problem. However, the only part of the electrical power system that is currently optimized is the high-voltage sytem. Consequently, there is a large amount of unused flexible resources connected to the low voltage system, coming from flexible residential and commercial demand, which can be exploited efficiently in order to break the current barriers that are bounding the growth of renewable energy integration. The project proposes a color - tagging system that - enables consumers to set "traffic lights" on their residential plugs: (i) green color indicates cheap power that can be interrupted at all times; (ii) orange color, power that can be interrupted in emergency conditions, (iii) red color, power that cannot be interrupted. Inspired by existing research on the integration of the color-tagging system into wholesale electricity market (macro scale), the goal of this project is to focus on the application of this demand response scheme at individual households and to infer the level of flexibility that can be leveraged for a consumer without excessively impacting perceived quality of service (microscale).

Coordinator: François Maniquet
Researcher: /
Financement: FNRS
Date: October 2016 - September 2020

This project is aiming to theoretically and empirically explore how the social components of preferences such as identity, social norms and social categories, may help explain the persistence of poverty and social exclusion in rich societies.

Coordinator: Leonardo Iania
Researcher: /
Finance: FNRS
Date: October 2015 - September 2019

This project studies the relationship between uncertainty, macroeconomic fluctuations, financial markets and asset prices. In particular, we are interested at answering of questions such as: How does uncertainty influences macroeconomic variables such as aggregate level of prices or aggregate economic activity? Does the impacpt of uncertainty change in bad times? Is the relationship between macroeconomic and financial variables time dependent? What is the impact of uncertainty on asset prices? We answer these questions by building a macro-finance model. In this setting the dynamics of government bond prices, macroeconomic and finance variables are linked by no arbitrage conditions and uncertainty enters in the model in the form of parameter instability. We develop and apply Bayesian econometrics models to explore instability phenomena and to derive new measures of uncertainty. Bayesian econometrics is well known for its flexibility in modelling uncertainty. Even if the model is initially applied to the government market, it can be used to analyze the relationship between, uncertainty, macroeconomic dynamics and prices of other contracts such corporate bond, swaps or credit derivatives.
Improving our knowledge in this area is crucial for at least two reasons. From an academic perspective, it is interesting to more doeeply understand (1) how the relationship between macro-economic variables, financial variables and asset pricing in time of turbulence, and (2) how uncertainty can influence these variables. This is a new area of research that can improve our understanding of economic models. From an applied perspective, understanding how uncertainty influences macroeconomic conditions or asset prices or the government yield curve is crucial for policy makers, ho aim at improving general economic conditions and the efficiency of financial markets.

Coordinator: François Maniquet
Researcher: Erika Pini
Financement: FNRS
Date: October 2018-September 2020

In this research, we investigate whether inequality may be responsible for the changes in the political spectrum that have recently occured in many countries, exploring the link between economic inequality, political polarization and participation, as measured by voter turnout. Indeed, the substantial increase in economic inequality that has been registered in many countries during the past decades is not free of consequences in the political sphere. In fact, when economic conditions are harsher, economic policy becomes a salient issue in the political debate and voters' preferences change accordingly. If politicians do not respond by adapting their proposals to the preferences of voters, this can only result in lower electoral participation. However, economic circumstances also affect political competition. In particular, during periods of high economic inequality we observe higher political polarization, which may in turn have a positive effect on voters' participation.
A model of political competition and turnout is dieveloped that is able to explain the relationship between economic inequality and elecltoral participation, by taking into account the effect of inequality on political polarization. We complement the theoretical theory study with an empirical analysis of the effect of inequlaity on polarization and the resulting impact on participation, and, focusing on the uS, we try to separately identify the causal effects of inequality and of polarization on turnout. Finally, we extend the analysis of the triple relation inequality-polarization-turnout to contexts of multi-party competition, by developing a citizen-candidate model, where we endogenize turnout by introuding the mis-match cost as a potential source of abstention. There, we try to explain both the shift of exiting parties towaords more extreme positions, and the emergence of new parties, of which countries like Italy, Spain and Germany are a clear example.

Coordinators: Bram de Rock (Université libre de Bruxelles), Johannes Johnen (CORE) and François Maniquet (CORE)
Reseracher: Seyed Hassan Nostratabadi (CORE)
Financement: FNRS
Date: January 2018-December 2021)

Economists evaluate social and economic policies based on their impact on the individual well-being of the members of society. Typically this measurement depends on the crucial assumption that individuals have well-behaved (i.e. transitive and complete) preferences. Motivated by the overwhelming empirical evidence from psychology and behavioural economics, we aim at developing the methodological tools for analysing individual welfare, while allowing fron non-well-behaved preferences (i.e. seemingly inconsistencies in the behaviour of agents). For doing this we will explore an intermediate approach that is in between the agnostic approach (i.e. robust conclusions without specific explanation for the inconsistencies) and the model approach (i.e. an analysis based on a specific model explaining non well-behaved preferences). For the empirical part, we will extensively use the new and largely unexplored MEqIN data set that was gathered by the PIs of this project. This data set allows to compare several methods for measuring well-being and contains detailed information on all the adults of the selected households. In the applications we will restrict our attention to four main dimensions of well-being: health, material well-being, employment status, and the family situation. In this respect we will also recontact the surveyed households to gather extra data related to our research questions and this will make the (publicly available) MEqIN data set even more attractive.

Coordinators: Ivan Markovsky (Vrije Universiteit Brussel), Marc Van Barel (KU Leuven), Mariya Kamenova Ishteva (Vrije Universiteit Brussel), Lieven De Lathauwer (KU Leuven), Bart De Moor (KU Leuven), Panos Patrinos (KU Leuven), Pierre-Antoine Absil (INMA), François Glineur (CORE) and Nicolas Gillis (U Mons)
Researchehr:/
Financement: FNRS
Date: January 208-December 2021

Today's information society is cientered on the collection of large amounts of data, from which countless applications aim at extracting information. They involve the manipulation of matrices and higher-order tensors, which can be viewed as large multi-way arrays containing numerical data. Key to their successful and efficient processing is the proper exploitation of available structure, and in particular low rank. This project aims to contribute innovative structure-exploiting methodos based on the paradigm of low-rank matrix/tensor approximation, with a strong mathematical and algorithmic emphasis, and to apply them to large-scale data analysis, information retrieval and modeing. In WP1, which supports and facilitates progress in the other WPs, we develop robust and computationally efficient algorithms for optimal low-rank approximation w.r.t. a given criterion, including algorithms that extimate the rank whennot specified by the user. In WP2 we use low-rank approaches to tackle the fundamental problem of computing matrix products as cheaply as possible and to perform advanced curve fitting. In WP3 we develop large-scale structure-exploiting algorithms for nonnegative matrix factorization, a powerful tool to extract information from data, and for large-scale pattern recognition, which is as the heart of machine learning. Finally in WP4 we eploit low-rank structure in the esign of globally optimal methods for system identification, model reduction and signal processing

Coordinator: Anthony Papavasiliou (CORE)
Researcher: Gilles Bertrand (CORE)
Financement: FNRS
Date: October 2018-September 2020

The goal of this research is to evaluate the profitability of flexibility assets in the context of the large-scale integration of renewable energy on the electricity market. We characterize a flexible asset as an asset that can quickly adjust the quantity of its output. Some examples of flexible assets are combined cycle gas turbine and mumped hydro storage. This increased integration of renewable nergy results in two paradoxical impacts:
- On the one hand, the increase of renewable production implies that the market requires more flexibility close to real time.
- On the other hand, flexible units are currently being mothballed or retired in Europe due financial losses that are related to high marginal costs, despite the fact that these resources are offering valuable reserve services to the system.
Therefore, in order to ensure power system security, we need to increase the profit of flexible assets. We study this need for extra remuneraiton of flexible assets in two ways:
- We first analyze the market design problem. The idea of this line of research is to evaluate the imapct of a new remuneration strategy, referred to as scarcity pricing, on flexible generator profits.
- We additionally analyze a bidding strategy problem. Our main focus is on the continuous intraday market which is one of the short-term electricity markets that is becoming increasingly important but for which there still exists a limited amount of research. We believe that the CIM is important due to the fact that it allows valuable adjustments to renewable forecast errors, which are becoming increasingly significant in recent years due to the increasing integration of renewable sources.

 

Coordinator: Isabelle Thomas
Research: Arnaud Adam
Financement: FNRS
Date: December 2018-November 2020

The increasing number of trucks on the roads generates number of debates about sustainability. Transport quantitative analysis often rely on spatially aggregated and/or non exhaustive data (samples). This project aims at using unconventional "big data" (generated by on-board mandatory GPS deviceis) for refining freight transport geographies in Belgium. Three questions are raised in this project. (1) Is it possible to characterize each truck trace with on of several indices and make an insightful typology of the spatial shapes of routes ? (2) Is it possible to easily shift from raw GPS data to an origin-destination (places) matrices useful for transport modelling ? (3) How fare are the spatial realities extracted from this origin destination transport modelling or from current knowledge of the Belgian economic geographpy and logisticis organization?
Improving the nowledge in this domain is important for two reasons. Scientifically, it is to understand the geographical complexity of logisticsi and to solve some methodological issues such as to measure (quantify) unambiguously the "traces" of the trucks. In terms of policy issues, t is important to better understand and evaluate the spatial consequences of the kilometric tax in a heterogeneous space (Belgium). It is the actual uniform kilometric taxation environmentally, economically and socially equitable? Could a taxation varying space and time be more efficient? Yet could this new taxation generate new counterproductive effects?

Coordinator: Anthony Papavasiliou
Researcher: Céline Gérard
Financement: FNRS
Date: October 2017 - September 2019

The recent large-scale integration of renewable energies in electric power systems has resulted in various challenges in power system operations, due to the unpredictable, highly variable and non-controllable fluctuation of these resources. This has resulted in a growing demand for the incorporation of lexibility in the Central Western European electricity system in order to balance renewabme supply. Although storage devices can act as a source of flexibility, their cost is prohibitive for offering a definite solution to this problem. However, the only part of the electrical power system that is currently optimized is the high-voltage sytem. Consequently, there is a large amount of unused flexible resources connected to the low voltage system, coming from flexible residential and commercial demand, which can be exploited efficiently in order to break the current barriers that are bounding the growth of renewable energy integration. The project proposes a color - tagging system that - enables consumers to set "traffic lights" on their residential plugs: (i) green color indicates cheap power that can be interrupted at all times; (ii) orange color, power that can be interrupted in emergency conditions, (iii) red color, power that cannot be interrupted. Inspired by existing research on the integration of the color-tagging system into wholesale electricity market (macro scale), the goal of this project is to focus on the application of this demand response scheme at individual households and to infer the level of flexibility that can be leveraged for a consumer without excessively impacting perceived quality of service (microscale).

Coordinator: François Maniquet
Researcher: /
Financement: FNRS
Date: October 2016 - September 2020

This project is aiming to theoretically and empirically explore how the social components of preferences such as identity, social norms and social categories, may help explain the persistence of poverty and social exclusion in rich societies.

Coordinator: Leonardo Iania
Researcher: /
Finance: FNRS
Date: October 2015 - September 2019

This project studies the relationship between uncertainty, macroeconomic fluctuations, financial markets and asset prices. In particular, we are interested at answering of questions such as: How does uncertainty influences macroeconomic variables such as aggregate level of prices or aggregate economic activity? Does the impacpt of uncertainty change in bad times? Is the relationship between macroeconomic and financial variables time dependent? What is the impact of uncertainty on asset prices? We answer these questions by building a macro-finance model. In this setting the dynamics of government bond prices, macroeconomic and finance variables are linked by no arbitrage conditions and uncertainty enters in the model in the form of parameter instability. We develop and apply Bayesian econometrics models to explore instability phenomena and to derive new measures of uncertainty. Bayesian econometrics is well known for its flexibility in modelling uncertainty. Even if the model is initially applied to the government market, it can be used to analyze the relationship between, uncertainty, macroeconomic dynamics and prices of other contracts such corporate bond, swaps or credit derivatives.
Improving our knowledge in this area is crucial for at least two reasons. From an academic perspective, it is interesting to more doeeply understand (1) how the relationship between macro-economic variables, financial variables and asset pricing in time of turbulence, and (2) how uncertainty can influence these variables. This is a new area of research that can improve our understanding of economic models. From an applied perspective, understanding how uncertainty influences macroeconomic conditions or asset prices or the government yield curve is crucial for policy makers, ho aim at improving general economic conditions and the efficiency of financial markets.

Coordinators: Tom Lenaerts (Université libre de Bruxelles), Georg Kichsteiger (Université Saint-Louis, Bruxelles), Ana Mauleon (Université Saint-Louis, Bruxelles) and Vincent Vannetelbosch (CORE)
Researcher: Pierre de Callataÿ
Financement: FNRS
Date: January 2018-December 2021)

Whenever people need to decide whom to initiate a strategic interation they use information on their potential partners. As partners are aware of the role this information plays, they will try to control what is made available and will anticipate how their decisions in other situations affect that information, and as a consequence their future interactions. ALthough, group formation and network dynamics are highly influenced by this information-sharing dilemma, there is little insight into which information people prefper to disclose and how this affects trust, group compositions and strategic decision-making. Using methods of experimental economicsand theoretical modeling we here will examine thesentangled dynamics within the context of a sequential prisoners dilemma (SPD) game extended with a partner selection stage. Through three experiments we will investigate what information people disclose in the partner selection stage of the game, whether these differences lead to self-selection and thus different outcomes in cooperation and strust and how, when people can have multiple partners, this disclosure affects network structure. In parallel, but intertwined with the experimental part, minimal models of this co-evolutionary dynamics will be developed and analyzed to provide insight into the borader guidelines that induce self-selection and network stability. These models will probide information concerning the importance of certain parameters in the experiments and will be refined through the experimental results. These refinements should lead to models with certain explanatory capacities, which will be validated using information on a concrete economical situation.

 

Coordinators: Ana Mauleon (Université Saint-Louis, Bruxelles) and Vincent Vannetelbosch (CORE)
Researcher: Pierre de Callataÿ (CORE)
Financement: FNRS
Date: July 2018 - July 2022)

Agents collect (and disclose) information before starting strategic interactions with each other's (including froming groups). This work ambitions to analyze how the information and the strategic interactions affect each other. The analyze of the influence of the available information on the individuals' strategic choices has already received some attention. Yet, this work will have the originality to encompass an analyze of the influence of the strategic interaction on the information collected previously. This means that we will explore a framework where information sharing is an endogenous choice of individuals. Many questions will be addressed in this work, such as: Which kind of information will be disclosed? Which kind of groups agents will form? How this will influence the social welfare? etc.

Coordinators: Hans Keune (Universiteit Antwerpen), Hilde Bastiaens (Universiteit Antwerpen), Tim Nawrot (Universiteit Hasselt), Roy Remmen (Universiteit Antwerpen) and Isabelle Thomas (CORE).
Researchers: Madeleine Guyot and Sonia Trabelsi
Financement: BELSPO
Date: July 2017-December 2021

The NAMED project investigates how the built and non-built environment impact the mental wellbeing of Brussels' citizens. Several international studies have shown that the built environment has negative impacts on mental health, while others highlighted the beneficial impacts of natural areas on this component, stress, but also more generally on wellbeing. In Belgium, only limited research is currently available. The NAMED project tackles the topic with different research perspectives. From a quantitativei perspective, his data are used to investigate the relationships between mental health and the built/non-built environment, while accounting for demographic, socioeconomic factors, lifestyle, air and noise pollution. In parallel, from a qualitative analysis perspective, Brussels residents are interviewed to record individual perceptions about the quality of their living environment, on their mental wellbeing and on the link between those two. Local stakeholders and experts are also consulted through focus groups and extended peer evaluation of the results. By gathering specialists in social, geographical, medical, epidemiology sciences and involving citizens and local stakeholders of the Brussels-Capital Region, the project intends to combine discipliens and perspectives in order to get a comprehensive understanding of the topic.

Coordinators: Johan Eyckmans (KU Leuven), Sandra Rousseau (KU Leuven), Paul Belleflamme (CORE) and Thierry Bréchet (CORE)
Researcher: : Huan Ha
Financement: BELSPO
Date: December 2014-September 2019

The IECOMAT project develops complementary numerical and analytical tools designed to study a particular aspect of sustainable material management, the circular economy. The models to be employed and to be developed range from input-output models over partial, computable and general equilibrium models as well as analytical industrial organisation models of economic incentives. The project will deliver dififerent modeling frameworks, scenario analysis, a wide variety of policy analyses and ultimately an assessment of potential of a more circular economy model for Belgium.
The IECOMAT project brings together a multidisciplinary team of experienced scientists from material and environmental engineering, environmental economics, industrial organisation and stakeholder consultation practice. This multidsciplinary team from a leading Flemisch research institute on sustainable material management (VITO) and two research universities (KU Leuven and UCLouvain) interact intensively. This leads to an interdisciplinary analysis of key scenarios for the Belgian economy. Some specific areas of expertise are subcontracted to national and international secialists in their domain. In all approaches, three fundamental perspectives are included: physical material flows, environmental effects and socio-economic impacts, and business incentives. Therefore, the IECOMAT project is about integrated assessment models for the transition towards a circular economy. In order to strenghthen a transdisciplinary dimension, the input of policy markers, practitioners and business stakeholders is actively sought.

Coordinators: Benoit Nemery (KU Leuven), Isabelle Thomas (CORE), Tim Nawrot (Universiteit Hasselt), Catherine Bouland (Université libre de Bruxelles), Patric Deboosere (Vrije Universiteit Brussels) and An Van Nieuwenhuyse (Institut de Santé Publique, Bruxelles).
Researcher: Sonia Trabelsi
Financement: BELSPO (BRAIN)
Date: July 2015-December 2019

Living in green/blue areas is associated with better health. This may be due to low air and/or noise pollution, opportunities for physical activity, facilitation of social contacts, and promotion of recoverty from fatigue and stress. Yet, socio-economic (SE) factors also explain inequalities in health and access to green/blue spaces. The GRESP-HEALTH project evaluates the associations between living in/close to a green/blue area on morbidity and mortability in Belgium. It assesses all-cause and cause-specific mortality, specific morbidities and perceived health, considering environmental pollutants and SE factors.
The project includes individuals registered in the Belgian censuses of 1991 and/or 2001. Three levels of observation are studies: individual, statistical sector (SS) and group of SS, following individual and ecological designs. Mortality information is based on the National Mortality Database (a linkage between cause-specific mortality (2004-2012) is derived from the IMA (Intermutualistisch Agentschap) database, which contains reimbursement data of prescriptions. For green/blue spaces, the surface, shape, accessibility and type are calculated for each SS. Residential area-specific exposure to air pollutants is obtained rom satellite images. Traffic noise databases are used whenever possible. We will consider SE factors such as material deprivation, education, and occupation. The analyses will be conducted separately in different age specific populations and types of area (urban, sub-urban rural). We will use multilevel models for clustered data within geographical areas. Interactions of green/blue spaces with air pollution and SE factors will be evaluated and stratified analyses in areas with similar SE and environmental characteristics will be performed. Morover, specifici population groups (gender, employment status) will be considered. the GRESP-HEALTH project will improve the scientific knowledge about the hiherto uncertain associations between living close to green/blue spaces and health

Coordinator: Anthony Papavasiliou
Researcher: /
Finance: Francqui Foundation
Date: September 2018 - August 2021

Anthony Papavasiliou has received the 2018-2021 Francqui Foundaiton research professorship. The Francqui Foundation grants a mandate from Francqui Research Professor at the University for a period of 3 years (2018-2021), a period of 2 years, followed by a third year after approval by the FDoundation during the course of the mandate. With this mandate, the Foundation gives the opportunity to a professor or a young researcher to dedicate himself to research, with a reduced teaching assignment.
The mandate is aimed at researchers, for whom a reduction of the teaching assignment represents added value for the university of the candidate; it is aimed, in particular, at professors or young researchers of an exceptionally high level, whose research is part of a current and interesting field of research and whose scientific an international influence contributes to an elevated standing of the institution.
Professor Papavasiliou will use this opportunity in order to advance the research within his PhD group, and strengthen collaborations with international research group. Regular visits are foreseen at Harvard University, hosted by Professor William Hogan.

Coordinators: Ana Mauleon (UniversitéSaint-Louis, Bruxelles) and Wouter Vergote (UniversitéSaint-Louis, Bruxelles)
Researcher: Jérôme Dollinger
Financement: Fédération Wallonie-Bruxelles
Date: October 2015 - September 2020

The global objective of the research project is to deepen our understanding of social and economic networks by bridging the gap between two approaches to network economics: the social networks approach and the Industrial Organization (IO) approach. The research activities will be articulated around the following three axes:
- limited farsightedness in network formation;
- networks in the knowledge economy;
- group symbols and conventions in networks.

Coordinators: Benoit Macq(ELEN), Raphael Jüngers(INMA) and François Glineur (INMA and CORE)
Researcher: /
Financement: Région Wallonne
Date: August 2017 - July 2020

BIDMED wishes to explore the applicability and use of "Big Data" digital technologies in the heathcare sector, with a specific objective of enhancing the accessibility to proton therapy, the advanced radiotherapy modality for which the Walloon company IBA is known as the world leader. To this end, IBA will partner with the specialist of medical image management Telemis, as well as the engineering ICTEAM institute from UCLouvain. The consortium is completed by contributions from the operational proton therapy facilities from Sweden.
BIDMED aims at improving the performances and reducing costs associated with proton therapy, at all stages of the equipment lifecycle. At the installation, "machine learning" techniques will be applied to automatize the system calibration. For the equipment maintenance, statistical analysis of the equipment monitoring data as well as predictive analytics will enable predictive interventions and help troubleshooting by a better identification of the root failure causes. During routine operations, the comprehensive analysis of data from multiple workflows will help implementing clinical scenarios with enhanced outcomes either for the patient (adaptive treatments) or for the equipment (rules or guidelines for improved scheduling of the activities in the rooms).
Next to these primary objectives, the project will also enable Telemis to expand their own business, through the procurement of deodicated PACS systems to be integrated with the proton therapy equipment, and by adopting the "smart maintenance" innovations into their monitoring system.

Coordinator: Anthony Papavasiliou (CORE)
Researcher: Ilyes Mezghani (CORE)
Financement: Engie
Date: October 2016 - September 2020

The proliferation of distributed renewable resources at the distribution level, coupled with the presence of significant amounts of local flexibility in the residential and commercial sector, implies that a substantial amount of intelligence will have to be integrated at the distribution level of electric power systems. Moreover, the distribution system operator will need to assume a more active role in the operation of electric power systems and electricity markets, and its interaction with the transmission system operator will need to be clarified. The goal of this research is to model schemes for coordinating TSO-DSO interaction, and to develop scalable optimization algorithms for coordinating the optimal dispatch of transmission and distribution level resources which can deal with the large scale of the problem and the non-linear representation of power flow at the distribution level.

Coordinator: Anthony Papavasiliou
Researcher:/
Financement: Electrabel
Date: February 2016 - October 2020

The large-scale integration of renewable energy sources is creating is increasing needs for flexibility. The optimal dispatch of conventional resources of a sub-hourly time scale in order to prevent binding ramping constraints is increasing the challenges of short-term operations. This project aims at developing optimization models and algorithms that can support the optimal utilization of generator flexibility in short-term operations.

Coordinators: Philippe Chevalier (CORE) and Isabelle Thomas (CORE)
Researcher: Henry Dehaybe
Financement: Logistics in Wallonia(Walloon Competitiveness Cluster dedicated to Transport, Logistics and Mobility) and N-Side
Date: December 2016 - December 2020

This project proposes to facilitate access to advanced data analytics to SME's for supply chain management and optimization via the development of a flexible and modular platform. The PRESupply platform aims to increase the value of decisions that affects several parts of the supply chain using an integrated and predictive approach.