Students must complete 60 ECTS credits (European Credit Transfer and Accumulation System)

Compulsory courses:  30 ECTS (6 courses)
Optional courses:       10 ECTS (2 courses)
Final Master thesis:    20 ECTS

Each course is 5 ECTS credits (European Credit Transfer System) except otherwise specified. The Master is taught entirely in English.

Compulsory courses

• Techniques of Statistical Analysis I

For Group 1, the course provides the elementary statistical knowledge needed for the analysis of quantitative data. It covers descriptive statistics, statistical inference, and linear regression. Students will come away with the skills needed to conduct basic statistical analysis of social science data on their own, and with the foundation needed for more advanced courses on quantitative analysis.

The course for Group 2 builds on students’ knowledge of basic statistics to deepen their understanding of linear regression techniques, placing special emphasis on model specification and the problems that occur when regression assumptions do not hold. The course takes students from classical linear regression into generalized linear models. It combines theoretical presentation and discussion of each subject with hands-on applications using Stata.  

• Techniques of Statistical Analysis II

For Group 1, the content of the course is similar to the one corresponding to ‘Techniques of Statistical Analysis I’ for Group 2 (see above). It builds on students’ knowledge of basic statistics to deepen their understanding of linear regression techniques, placing special emphasis on model specification and the problems that occur when regression assumptions do not hold. The course takes students from classical linear regression into generalized linear models. It combines theoretical presentation and discussion of each subject with hands-on applications using Stata

The course for Group 2 provides advanced statistical knowledge for the analysis of quantitative data in empirical social science research. The course is problem-based, that is the theory is always presented in the context of a practical problem needing a solution. In order to provide the applied skills needed for professional social science research, the course is taught using the statistical software Stata and R.

• Demographic Changes and Social Dynamics

The course introduces the key topics of demographic change and social dynamics, both from a macro-level and from a micro-level perspective. A particular emphasis is put on the issues of changing life courses. The students will acquire the capacity to understand the scope and patterns of recent fertility and nuptiality changes in developed countries and the main theoretical contributions made by demographers, sociologists, and economists to explain demographic changes. Special attention will be devoted to introducing the tools that are used to study demographic behaviour in the current scientific literature. Contemporary research papers are used to enlighten each of the topics of the course.

• Analysis of Social Inequalities

In this course, we will cover to what extent inequalities have indeed changed over time and how they differ across countries. We will discuss some of the societal developments often held responsible for these developments such as globalization or recent demographic changes (see above ‘Demographic Changes’ course). This discussion of recent themes will be backed-up by an overview of the traditional tools and measures used by sociologists to measure and analyse inequality. Sociological approaches will be regularly complemented by insights from economics.

• Social Policy and the Welfare State

The aim of the course is to provide students with a clear idea of the diversity of European social policies, of their historical and political origins, and to allow for the assessment of their performance. The course will also provide an in-depth account of current welfare reforms, in light of their historical development. Important social science analysis concepts (de-/re-commodification, path dependency...) will also be used in order to understand the issues at stake in recent debates concerning the welfare state and the trajectories of their reforms.

• Family, Gender and Society

The course adopts a comparative, theoretical and applied perspective, and has two main aims: first, to cover recent theories and empirical studies on family dynamics (partnering, fertility, divorce) and how families provide welfare and also reproduce social inequalities. We also examine how social and family policies influence behaviour and outcomes. Second, it aims to help students link theory to empirical analysis. Students will be asked to propose an ideal theoretical model to predict a socio-demographic event, and they will translate the theoretical model into an empirical application with real data.
 

Optional courses

• Health and Inequality

This course focuses on the linkages between society and health inequalities, presents evidence and examples of new research in this area, and offers a forum to explore the policy application of these perspectives. Particular emphasis is put on definitions, theoretical models, empirical analyses and policies and interventions to tackle health inequalities. Additionally, strengths and limitations of a number of fundamental topics related with the generation of knowledge (e.g. public health and social epidemiology), social determinants (e.g. employment and working conditions), and “social mechanisms” (e.g., social class, gender, geography) will be discussed. Finally, policies and interventions on health inequalities including examples and entry-points for change as well as priorities for action will also be discussed.

• Research and Data Analysis Seminar

This course is a very first introduction to Stata, a powerful statistical software that allows conducting quantitative analyses and that is very popular among social scientists. This course is mainly applied and students will be using the software from the first class. They will learn know how to carry out all the data management that is needed before carrying out advanced analysis such as multivariate regression or any of the other techniques that will be taught in the statistics courses. The course will show how to open datasets, exploring them, checking missing values, producing frequency tables, creating variables, etc. The former are the minimum learning outcomes, but we may get a bit further if the rhythm of the class allows it. This course is a very first introduction to the software Stata and thus no previous knowledge of Stata is required.

• Labour Market and Employment Policies

The transition from Industrial to Post-Industrial societies has generally entailed a dilemma between unemployment and inequality. For many societies, such a dilemma has turned unemployment into a central challenge for governments. After historically revising the evolution of labour markets in Europe, the effect of globalisation and the national institutions shaping the entry into the labour market, the course will explore the determinants and levels of unemployment in comparative perspective. It will analyse different policies against unemployment and the results these policies have had. The situation of women and ethnic minorities will be especially addressed in the last two weeks of the course.

• Migration and Society

The course will explore the role of migration in contemporary society.  Students will learn to think from three perspectives:  1) from the context of reception, 2) from the context of origin, and 3) from neither/both (i.e. transnationalism).  The primary focus of analysis will be on migration to developed countries, particularly the European and North American migration flows.  However, these three perspectives will allow students to account for the multiple dimensions of what has become a controversial and fundamental engine of social, cultural, and economic change in both the developing and developed world.

• Fundamentals of Political and Social Research

This course covers basic issues in epistemology, research design, and research methods. We will ask the broader question of how one can generate useful knowledge in the social sciences. The first part of the course will focus on theory construction and the generation of causal arguments. The second part of the course will examine topics in empirical research design and hypothesis testing. Throughout the course, the students will work on the step-by-step formulation of their own research designs.

• Qualitative Research Methods 

The central aim of this course is to prepare students to design and conduct qualitative research in a variety of different settings, while providing them with a critical understanding of the different theoretical approaches that inform the methodological debates within this paradigm of research. A particular emphasis will be placed on the issues of diversity. We will explore the variety of ways through which qualitative research strategies can deal with the complexities related to migration, race, ethnicity, gender, class, religion, culture, etc.
 

Research Component

• Final Master Thesis (20 ECTS)