Short Biography: He is Director of Statistics Directorate at the High Commission for Planning (HCP) and Director of the National Institute of Statistics and Applied Economics. After spending over 25 years working as a researcher and a full professor of statistics/biostatistics at Laval University and the Université du Québec à Trois-Rivières, Québec, Canada, Belkacem joined the HCP, where he is strongly involved in the production of official statistics in Morocco together with various national and international statistical activities and projects.

Throughout his career, Belkacem has been a researcher at the Montreal Mathematic Research Centre, a member of the Statistical Society of Canada, the Institute of Mathematical Statistics (IMS) and the International Statistical Institute (ISI).

Talk of the title: “On some statistical methods in public health and environmental related problems”

Abstract:

Short Biography: Conférencier international Expert en Energies Renouvelables. Président du réseau universitaire REUNET

Talk of the title: “Quel futur énergétique pour le Maroc à l'horizon 2050 ?”

Abstract: Pays en fort développement, le Maroc est à présent fortement dépendant des importations énergétiques, notamment celle des combustibles fossiles (pétrole, gaz et charbon). Près de 90 % de l'énergie utilisée provient de l'étranger. Ceci pèse lourdement sur la balance des paiements et, dans la mesure où certaines fournitures d’énergie sont subventionnées, sur le budget de l’État.

En raison de l’évolution de l’industrialisation, du développement global de l’économie et de l’augmentation du niveau de vie dans le pays, la demande en énergie croit de 6-7 % par an en moyenne.

Cette dépendance vis-à-vis des importations soulève aussi la question de la sécurité d’approvisionnement énergétique, alors que l’utilisation de ces combustibles fossiles maintient un niveau relativement élevé d’émissions de gaz à effet de serre (GES).

Le Maroc partage donc nombre des défis énergétiques auxquels sont confrontés la plupart des pays du monde, à savoir, comment garantir à la fois la sécurité d'approvisionnement et le respect de l'environnement. Pour répondre à ces enjeux, les autorités marocaines ont mis en place une stratégie volontariste et ambitieuse, dont le principal pilier est le développement des énergies renouvelables. La part de celles-ci va passer à 42 % en 2020 et 52 % en 2030 dans la capacité de production électrique totale du pays.

D’un autre côté, le potentiel des ressources en énergies renouvelables au Maroc (solaire, éolien, biomasse, géothermique, hydraulique, énergie des mers, …) est largement suffisant pour répondre à l’intégralité des besoins énergétiques du pays. L’exploitation intelligente de ce potentiel pourrait permettre au Maroc de se passer complètement des énergies fossiles importées, de contribuer à la protection de l’environnement et de créer de nouvelles richesses. Cependant, certaines des technologies nécessaires pour atteindre cet objectif doivent encore faire l’objet de perfectionnement et de réduction des coûts. Un immense effort de recherche, de développement et de démonstration est donc nécessaire, tant dans le secteur privé que public.

C'est dans ce contexte que la modélisation prospective devient nécessaire pour les chercheurs.

Ma conférence s'articule autour de trois parties :

1. Aperçu de la situation énergétique mondiale et nationale

2. Stratégie énergétique du Maroc à l'horizon 2030

   1. Modélisation d’un futur électrique 100% renouvelable au Maroc à l’horizon 2050 : défis scientifiques, technologiques et économiques.

Short Biography: Raja Chakir holds a degree in statistician engineering from INSEA in Morocco and a PhD in economics from Toulouse School of Economics in France. His thesis work focused on estimating energy demand with panel econometric models. After postdocs at the LSE and at the CNRS, she was recruited as researcher at INRA in 2005 and promoted as research director in 2018. Her research focuses on spatial econometric analysis of land uses and their impacts on the environment with a particular focus on climate change, loss of biodiversity and water quality. She teaches environmental econometrics and methods of environmental goods evaluation inAgroParisTech's Master2 EDDEE, University Paris 1 - La Sorbonne Master 1 Environmental Economics and Sustainable Development and in OCPPC’s Advanced Training in Agricultural Economics and Environment. She has participated in several ANR and European research projects, she also carried out consulting for the World Bank and ADEME.

Title of the talk: "Spatial econometric analysis of land use and climate change" (with Anna Lungarska)

Abstract: Interaction between mitigation and adaptation is a key question for the design of climate policies. In this paper, we study how land use adaptation to climate change impacts land use competition in the agriculture, forest and other land use (AFOLU) sector and how a mitigation policy in agriculture might affect this competition. We use for this purpose two sector-specific bio-economic models of agriculture and forest combined with an econometric land use shares model to simulate the impacts of two climate change scenarios (A2 and B1, 2100 horizon), and a greenhouse gas emissions from agriculture policy consisting of a tax of between 0 and 200 €/tCO2 equivalent. Our results show that both climate change scenarios lead to an increase in the area devoted to agriculture at the expense of forest which could have a negative impact on reducing greenhouse gas emissions responsible for climate change. The mitigation policy would curtail agricultural expansion, and thus could counteract the effects of land use adaptation to climate change. In other words, accounting for land use competition results in a reduction of the abatement costs of the mitigation policy in the agricultural sector.

Short Biography: Sophie Dabo-Niang is professor of Applied Mathematics (Statistics) at University of Lille, laboratory LEM CNRS 9221 and member of INRIA-MODAL team. She completed a 3-years PhD in Statistics from the University Paris 6 in 2002. She is chair of the axis MeQAME (Quantitauve methods in Management and Economics) of LEM and vice-chair of EMS-CDC (European Mathematical Society-Committee of Developing Counties; http://euro-math-soc.eu/committee/developing-countries). Dr. Sophie Dabo-Niang research program is focused on the study of non(semi)-parametric inference of functional and spatio-temporal data. From an applied perspective, she is interested in economics, medical, environmental and hydrological studies. She published more than forty statistical papers.

Title of the talk: "Bridging Functional Data Analysis and Spatial Data Modeling"

Abstract: Spatial statistics includes any (statistical) techniques which study phenomenons observed on spatial sets. Such phenomenons appear in a variety of fields: epidemiology, environmental science, physics, econometrics, image processing and many others. The modelization of spatial data is among the most interesting research subjects in dependent data analysis. This is motivated by the increasing number of situations coming from different fields of applied sciences for which the data are of spatial nature. This is the case for instance in epidemiology, where data are often spatial or space-time, and so spatial location can acts as a surrogate for risk factors. Complex issues arise in spatial analysis, many of which are neither clearly defined nor completely resolved, but form the basis for current researches. This is the case of functional data analysis techniques, which incorporate spatial dependency. We are interested here in semi(non)-parametric spatial regression estimation. More precisely, we estimate regression functions where the explanatory variable is real-valued while covariates are functional random fields. Asymptotic results of the proposed estimator are established. The skills of the methods are illustrated on simulations and real data analysis.

Short Biography: : Ahmed El Ghini is currently an Associate Professor of Econometrics at the Faculty of Law, Economics and Social Sciences (Souissi) in Rabat, Morocco. He has been a Researcher at the National Center for Scientific Research (CNRS) of France, where he was involved in many national and international research projects, and previously an Assistant for Teaching and Research with the EQUIPPE Laboratory “Economie Quantitative, Intégration Politiques Publiques et Econométrie” of the Université Lille Nord de France. He holds a PhD and an MA in Applied Mathematics and Economics from Charles de Gaulle University - Lille 3, and “Diplôme d’Etudes Approfondies” in pure mathematics from Lille 1 University, France and graduated in mathematics from the Faculty of Sciences of Oujda in Morocco. His teaching experiences include probability, statistics, econometrics and financial mathematics at many universities and engineering schools in France and Morocco. His research interests focus on time-series modeling, econometrics, statistics and their applications in economics, environment, energy and finance. El Ghini’s research work is published in peer-reviewed journals and presented at several international conferences.

Ahmed is the coordinator and founding chair of 2 periodic international conferences: Econometrics for Environment (CE²) and Days of Econometrics for Finance (JEF: https://sites.google.com/site/jefconference).

Dr. Ahmed El Ghini awarded many distinctions, in particular “Prix du meilleur chercheur de l’année 2015” in Humanities and Social Sciences from Mohammed V University in Rabat.

Round Table on "Economic growth and some related environmental issues in developing economies: Empirical evidences"

(with Raja Chakir, Sophie Dabo and George Marbuah)

Abstract:

Short Biography: : Researcher at the University of Coimbra in the Energy for Sustainability initiative and INESCC, he holds a Ph.D. in Sustainable Energy Systems from the University of Coimbra (UC) and a MBA from Porto Business School. His research interests, are in the areas of energy economics, energy markets and sustainable energy systems. He is author of articles in international peer-reviewed journals and conferences, and also a founding member of the Portuguese Association for Energy Economics. He is the Operations Manager in a combined cycle gas turbine power plant, representing Trustenergy (a joint venture between Engie and Marubeni).

Title of the talk: “Interconnection congestion determinants: the Iberian case”

(with Patrícia Pereira da Silva and Pedro A. Cerqueira)

Abstract: Cross-border interconnection infrastructure is fundamental to optimise daily production, increase the opportunities for operation with renewable energies, promote the competition and enhance the security of supply. The management of limited cross-border interconnections capacity constitutes a challenge, in particular if extensive renewable energy generation is available.

The probability of cross-border interconnection congestion is inhere estimated through the use of non-parametric models, as a function of wind and hydro power, together with the available transmission capacity and electricity demand. The congestion of the cross-border interconnections prevents further optimization of available renewable resources.

Short Biography: : Since 1999, I’m Researcher in Ecodevelopment unit (Avignon, France) UR767, INRA and lead the UbanSIMUL Team (https://urbansimul.fr). My Research area is on Land markets and land policy, Evaluation of territorial policies, Land Use Change models and Spatial Econometrics. I managed since 2001 various research programs on land markets dynamics, on land use change modeling, and on evaluation of impact of rural/land public policy.

I also manage the URBANSIMUL project (2009-2014, 2015-2020 https://urbansimul.fr/urbansimul/presentation.php) that contributes to the development of a server tools on land use management and land-use changes analysis.

Title of the talk: “A space-time-categorical local linear smoother for predicting house prices, followed by a R session on how to use the R package mgwrsar”

(with Davide Martinetti)

Abstract: We recently introduced a new class of data generating processes called MGWR- SAR, in which the regression parameters and the spatial dependence coefficient can vary over the space in order to take into account both spatial heterogeneity and spatial dependence (Geniaux and Martinetti, 2017, R package mgwrsar). The estimator corresponds to a local linear smoother (Cleveland, 1979) with a spatial kernel based on Euclidian distance between observations and a linearization of SAR regression using IV/2SLS method. We propose to improve these DGPs by adding a General Product Kernel that allows to introduce further smoothed variables to go beyond spatial heterogeneity. Firstly, ”time” variable to consider space/time heterogeneity and, secondly, a categorical variable to test the relevance of ”ad hoc” market segmentations. The objective is to fit an even smoother regression model capable of predicting house prices while accounting at the same time for space-time dependencies and housing submarkets. We apply the new estimators to a comprehensive spatial longitudinal database on house sales in the Southeastern French region of PACA. We show that these estimators are more accurate than models integrating exclusively spatial heterogeneity or spatial autocorrelation, based on a comparison of the predictive accuracy of the best linear unbiased prediction (BLUP). The R script related to this article will be commented during the second part of the talk, and an introduction to the mgwrsar package will be proposed.

Short Biography: : Agronomic Engineer from Institut Agronomique et Vétérinaire Hassan II, Rabat (1981), and Ecole Supérieure du Bois, Paris France(1980). Master of Sciences (1988) in economics and PhD in Forestry (19992) from the University of Idaho, USA. Master of Sciences in ICT, University of Louis Pasteur, Strasbourg, France (virtual campus). Full Professor at Ecole Nationale Forestière d’Ingénieurs since 1994, and visiting professor to many universities. Research Fellow in the Royal Institute of Strategic Studies (IRES), Morocco, and in the Institute for Labor Studies (IZA), Germany. His recent research interests deal with integrated natural resources management, environmental assessment, climate change adaptation, and rural development. Author of many publications (book chapters, scientific papers, expertise reports, outreaching documents, etc.), recipient of numerous research grants and consultant for international organizations (UNESCO, ISESCO, UNDP, UNEP, World Bank, FAO, GIZ, ..) and national public and private institutions. Fulbright Alumni, president of the Regional Science Association of Morocco. Lead author for the IPCC fifth report, chapter 5 (coastal zones and low lying areas).

Title of the talk: “Analysis of the cost of environmental degradation in coastal zones”

Abstract: The major environmental concerns in coastal zones in Morocco are related to the rapid urbanization, the direct discharge of industrial and household solid waste into the sea, the degradation and disappearance of natural resources (wetlands, forests, coastal ecosystems, etc.), destruction of coastal dunes, erosion in sandy beaches, etc. An important cost of environmental degradation will result from these issues. The costs will concern health losses related, water quantity and quality degradation, air pollution, loss of fish captures, loss of amenities, loss of tourism opportunities, loss of biodiversity and many ecosystem services. Evaluation of the cost (degradation, damage) of environmental impact aims to associate monetary values with these impacts. This paper deals with the identification of various costs and methodologies to compute them in order to inform the decision-making processes.

Short Biography: : A post-doctoral researcher at the Department of Economics, Swedish University of Agricultural Sciences in Uppsala, Sweden where he obtained his PhD in Economics. His primary research interests are in empirical macroeconomics, development economics and policy-oriented issues with applications to understanding public debt, economic growth and inflation dynamics among others. He is also interested in research at the intersection between the macroeconomy, environment and natural resources management in sub-Saharan Africa and developing economies’ contexts in general. He has accumulated about a decade’s experience in applied economic and policy research as well as teaching in and outside of the academia with a demonstrated track-record of peer-reviewed technical reports and journal article publications.

Title of the talk: “Spatial analysis of emissions in Sweden”

(with Amuakwa-Mensah, F.)

Abstract: This paper contributes to the environmental Kuznets curve (EKC) literature, which posits an inverted U-shaped relationship between pollution and income, but from a spatial perspective. We explore several spatial statistical and econometric analyses to account for spatial dependence in emissions from carbon dioxide, sulfur dioxide, nitrogen oxides, carbon monoxide, particulate matter (2.5 and 10) and total suspended particulates between all 290 Swedish municipalities. Our results suggest the EKC significantly holds for all but one pollutant (i.e. carbon monoxide) and that this relationship is significantly characterized by spatial dependence. Specifically, we find significant neighborhood effects as well as significant positive economic spillovers at low income which turns negative at high income on both within and inter-municipality air emissions. Our results and hence implications suggest transboundary pollution control policies aimed at abatement would be more effective through enhanced coordination between adjacent municipalities.

Short Biography: : Assistant professor at Delft University of Technology with a Doctorate in Mathematics and Information Science from the University of Amsterdam and M.Sc. degrees in mathematics and theoretical physics from Leiden University. His research interests include automatic control of environmental systems, statistics, and applications of interval analysis. He is chair of the Technical Committee 8.3 on “Environmental Modelling and control” of the International Federation of Automatic Control (IFAC), associate editor of the Hydrological Sciences Journal, chair of the Panta Rhei working group “Natural and man-made control systems in water resources”, and member of the International Commission on Statistical Hydrology of the International Association of Hydrological Sciences (IAHS).

Title of the talk: “Change point analysis for short time series”

(with Alla Kolechkina)

Abstract: In the 21th-century environmental sciences have embraced the idea of change. The effects of climate variability, technological change, and societal change combine to create a more dynamical world. Central in that world is a need to quantify the effects of those changes on the environment in ways that allow a combination of environmental and economic analysis.

In this context statistical analysis of environmental and economic data is still a powerful tool, but its techniques may need to adapt to new circumstances. One example of this is change point analysis. While this is understood in a manufacturing or financial context where long time series are available, it is now also applied to relatively short time series of environmental extremes. For those applications effects due to the finite length of the time series and quantification of the uncertainty of the location of the change are of great interest. For this reason, it was decided to examine and compare the behavior of classical change point analysis tools, a Bayesian method, and a method based on confidence sets.