Écoles, masters et doctorats / Schools, Masters and Doctorates / Enseignements / Teachings
Teachers : Jaime MONTES LIHN (Post-doctorant). Prerequisite : Students are expected to read before each session the compulsory readings regarding the topic that will be discussed in the workshop. Pedagogical Format : Workshop Course validation : - Active participation to class discussion (30% of ﬁnal grade). - Students are requested to conduct their own research study, in groups, and to write a paper where they will analyze and discuss their results. Students will collect (through questionnaires) and analyze (with R software) social network data. This paper should include at least the following sections : Introduction, Theoretical Framework, Hypotheses, Data Analysis (of social network data), and Conclusion (70% of ﬁnal grade). Pedagogical Method : 6 classes x 2 hours. Course Description : The study of social networks focuses on the interdependencies between individuals, organizations and their relational context. This original perspective, that starts from the appraisal of structural properties, will be the base of our approach when analyzing regulation processes and economic activities through different case studies. This course has two objectives : (1) Introduce students to the main concepts used in social network analysis. Empirical examples will be explored to illustrate how social networks may shed light on issues such as unemployment in urban areas or the process of public regulatory policy ; (2) Allow students to develop research hypotheses and analyze empirical data. R (free software) will be used for social network analysis and visualization. The course will alternate between case studies and hands-on practice. Required reading : Session 1 : Wasserman, S., & Faust, K. (1994). Social network analysis : Methods and applications (Vol. 8). Cambridge University Press. (Chapter 1 “Social Network Analysis in the Social and Behavioral Sciences” + Sections 4.1 “Why Graphs ?”, 4.2 “Graphs” and 4.3 “Directed Graphs” of Chapter 4 “Graph and Matrices”) ; Seesion2 : An Introduction to Network Analysis with R and statnet (pages 1 to 5) https ://statnet.org/trac/raw-attachment/wiki/ Resources/introToSNAinR_sunbelt_2012_tuto-
rial.pdf ; Lazega, E. (2009), Theory of cooperation among competitors : A neo-structural approach, Sociologica http ://elazega.fr/media/ pdf/art/CooperationAmongCompetitorsSociologica2009.pdf ; Seesion 3 : An Introduction to Network Analysis with R and statnet (pages 6 to 12) https ://statnet.org/trac/raw-attachment/wiki/ Resources/introToSNAinR_sunbelt_2012_tutorial.pdf ; Daraganova, G., & Pattison, P. (2013). Autologistic actor attribute model analysis of unemployment : dual importance of who you know and where you live. Exponential Random Graph Models for Social Networks : Theory, Methods and Applications, 237-247.
INTRODUCTION TO THE INSURANCE INDUSTRY
Semester : Autumn Number of hours : 24 Language of tuition : English
Opened to the exchange program
Teachers : Amal AOUAM (Senior Manager, Mazars), Otto STRASSZER (Senior Manager, Mazars). Prerequisite : None. Pedagogical Format : Elective Course validation : Credits : 2. Continuous assessment grade. Workload : An interactive learning format. Each class will contain lecture and cases. Pedagogical Method : 12 seminars of 2h by week (24h). Course Description : The objective of this course is to learn about the global insurance industry from an economic, regulatory and ﬁnancial point of view. Insurance companies have developed a speciﬁc business model that makes them a key player in the overall economic landscape. Indeed, they offer their customers to relieve them from their many critical risks, e.g. Property loss, death, markets volatility. As a result, insurance companies are challenged by uncertainty at every step of the production cycle, e.g. pricing, investing, paying beneﬁts. In a context of a moving economic and regulatory world, insurers have to manage risks and make decisions accordingly. 1471