Syllabus
Research Track - AQME Certificate courses (Graduate Program in Economy) - 9 ECTS
- Introduction to Matlab programming
Introduction to Matlab programming
- Data Management and Programming
Data Management and Programming
Ects : 3
Lecturer :
Total hours : 36
Overview :
This course provides an introduction to programming and to data management, with a data- oriented point of view. The course contains two parts. The data management part introduces the data life cycle in data oriented projects from data collection to data exploration. While the main focus of the course is tabular data, it contains also an introduction to entity-relationship models and to relational databases. The programming part of the course introduces the fundamental aspects of imperative programming and the use of the main Python data structures. The two aspects of the course are tightly integrated: each aspect of data management is illustrated by adapted programming constructs and uses specific data structures from Python. In addition, an introduction to computational complexity is provided and the scalability of all the methods presented in the course is assessed.
Coefficient : 1 (Pour le M1 Affaires Internationales et Développement) 1 (Pour le M1 Quantitative Economics)
Recommended prerequisites :
Most of the course is self-contained but the students are expected to be familiar with all the mathematical tools associated to an economics curriculum: Linear algebra, calculus, continuous optimization, probability and statistics, all at an undergraduate level. A significant part of the examples of data manipulation from the course will make use of this mathematical knowledge. However, the course should be accessible even with only a cursory knowledge of most of the listed concepts.
Learning outcomes :
The first objective of the course is to introduce students to data-driven projects, by presenting the first steps of such projects from data collection to data exploration. Acknowledging the strong limitations of integrated software that rely solely (or mostly) on graphical user interfaces, the second major objective of the course is to provide all the programming knowledge and tools needed to implement all those data management steps, relying on Python language.
After having attended the classes, the students will be able to:
- specify a data management chain adapted to a data-driven project;
- identify the potential data value increase at the different steps of the chain;
- implement those steps in Python: data cleaning, data storage, data aggregation and other requests, data exploration;
- more generally implement non-obvious data manipulation schemes in Python;
- assess the computational complexity of Python scripts
Assessment :
The final grade will be made of two types of grading: A continuous assessment grade, made mostly of grades obtained to quizzes (approximately 50 % of the grade) and integrating oral participation during the class and regular attendance; A grade obtained on a full data-oriented project from data collection to data exploration (preferably done in groups of 2 students).
Bibliography-recommended reading
Python for Data Analysis, Wes McKinney, OReilly, 2017.
- Macroeconometrics
Macroeconometrics
Ects : 6
Lecturer :
- MATTEO MOGLIANI
Total hours : 36
Overview :
This course will provide the fundamental tools in macroeconometrics. It starts providing the basic knowledge on the modelling of univariate time series, the concept of stationarity, the main tools to represent a univariate time series. Then, it will show some extensions to this basic framework (time varying parameters, selection of variables…). The course will also introduce to forecasting. We will then present the modelling of multivariate time series with VAR models, explain how structural VAR analysis is the natural set up to depart from a purely statistical description and provide economic interpretation. Finally, different extensions to this set up will be introduced: time-varying parameters, co-integration, expectations ….
Coefficient : 1
Recommended prerequisites :
statistics, general mathematical background
Learning outcomes :
The objective of the course is to provide the student with the solid theoretical and practical knowledge of the methods used to analyse and model time series data. Practical skills will be acquired through the modelling of economic time series with econometric software (practical sessions under Matlab). After having attended the classes, the students will master the main tools of time series’ modelling and be able to run an empirical work by themselves.
Assessment :
Final Exam (50%) + Final Project in pairs (40%) + Participation (10%)
Bibliography-recommended reading
Hamilton, J.D. (1994). Time Series Analysis, Princeton University Press. Johnston, J. and J.E. DiNardo (2007), Econometric Methods, Mac Graw-Hill Econometric series.
Mandatory courses - 21 ECTS
- Economics of growth
Economics of growth
Ects : 6
Lecturer :
Total hours : 36
Overview :
The course will cover the following topics.
- Stylized facts about long run growth – Growth decomposition and the Solow residual
- The impact of growth on economic welfare
- The Solow model and conditional economic convergence
- The Ramsey model
- Externalities and the AK growth model; the role for tax policy
- R&D, innovation and growth (Romer (1990) model)
- Growth in creation / destruction models (Aghion – Howitt model)
- Growth with directed technical change
- Sustainable growth and energy transition analysis
- Economic growth and declining population
Coefficient : 1
Recommended prerequisites :
Mathematics & optimisation
Learning outcomes :
The course will provide students with sound knowledge and understanding of the basis of modern macroeconomic theory regarding long run economic growth. After attending the classes, the students will master the fundamental models of modern macroeconomics in view of analysing the key issues and policies relative to long run economic growth.
Assessment :
60% of the final grade is based on a final exam (closed book exam).
40% is based on regular short quizzes.
Participation in class will be considered as bonus over this grade.
Bibliography-recommended reading
Reference book : Aghion, Philippe and Howitt, Peter “The Economic of Growth”, MIT Press 2008
- Daron Acemoglu, 2002. “Directed Technical Change.” Review of Economic Studies 69(4): 781–809.
- Daron Acemoglu, Philippe Aghion, Leonardo Bursztyn, and David Hemous, 2012,”The Environment and Directed Technical Chang”, American Economic Review 2012, 102(1): 131–166
- Charles I. Jones and Peter J. Klenow (2016) "Beyond GDP? Welfare across Countries and Time", American Economic Review, 2016, 106(9): 2426-2457
- Charles Jones (2022) “The end of economic growth? Unintended consequences of a declining population, American Economic Review, 2022, 112(11): 3489-3527
- Game theory
Game theory
Ects : 6
Lecturer :
Total hours : 36
Overview :
Chapter 1: Normal form games: pure and mixed strategy Nash equilibrium; weakly/strictly dominated strategies , iterated elimination of dominated strategies.
Chapter 2: Dynamic games: Backward induction, subgame perfect Nash equilibrium, repeated games.
Chapter 3: Incomplete information (in static games): Bayesian Nash equilibrium; introduction to some applications (auctions, finance...)
Coefficient : 1
Require prerequisites :
The student must be at ease with some basic mathematical notions such as: derivations, first-order conditions...
Learning outcomes :
The objective of the course is to give some fundamental background in interactive decision making and its applications. After having attended the classes, the students will be able to understand the basic tools of game theory and the importance of this field in economics and finance.
Assessment :
A mid-term exam and a final exam
- Microeconomic theory
Microeconomic theory
Ects : 6
Lecturer :
Total hours : 36
Overview :
The objective of the course is to provide a comprehensive exposition of the way consumers and firms make their consumption and production decisions in a competitive economy and on how prices are determined in the market (partial equilibrium). The consideration of other market structures like monopoly or oligopoly will give an understanding of how market power affects firms’ behavior and the formation of prices.
Planning / Course Schedule
Producers, Consumers, and Competitive Markets
Consumer Behavior
Individual and Market Demand
Duality
Production
The Cost of Production
Profit Maximization and Competitive Supply
The Analysis of Competitive Markets
Market Structure and Competitive Strategy
Market Power: Monopoly and Monopsony
Pricing with Market Power
Monopolistic Competition and Oligopoly
Coefficient : 1
Require prerequisites :
Maths (linear algebra and optimization problems)
Learning outcomes :
This course will provide a formalized exposition of the optimal consumption and production decisions by consumers and firms, which determine the allocation of scarce resources in a competitive economy, where agents are assumed to be price takers. The analysis will provide an understanding of how prices are determined by the interaction of the decisions of consumers and firms. The course will then examine the behaviour of individuals in economies with other institutional frameworks (different market structures).
Students will be provided an intuitive understanding of the economic content of the models, and of their purpose and nature, as well as a clear account of their mathematics.
Assessment :
50%(continuous assessment)+50% final exam result.
Continuous assessment: overall attendance and participation in class and effort to solve exercises on a weekly basis+ Midterm test.
Bibliography-recommended reading
Main textbooks:
· Robert S. Pindyck, Daniel L. Rubinfeld, “Microeconomics “, Pearson, 2018.
· David Besanko and Ronald R. Braeutigam, “Microeconomics”, 3rd edition, John Wiley & Sons
· Hugh Gravelle and Ray Rees, “Microeconomics”, 2004, 3rd Edition, FT Prentice Hall
· H. Varian, “Microeconomic Analysis”, Norton & Company, Inc., 3rd edition, 1992
- Upgrade in statistical tools
Upgrade in statistical tools
Choose one track
ECONOMICS TRACK
Research Track - AQME Certificate courses (Graduate Program in Economy - 9 ECTS
- Applied Microeconometrics
Applied Microeconometrics
Ects : 6
Lecturer :
Total hours : 30
Overview :
This course focuses on micro-econometrics techniques based on temporal data (cross-sectional and panel) and qualitative dependent variables. The first part will explore possible sources of OLS bias and discuss techniques and estimators to address those biases ( micro-econometrics techniques for temporal data, such as first difference, random effects, fixed effects and difference-in-differences estimators). Non-linear models (Probit, Logit models), as well as selection models (Tobit, Heckman selection models) will be the focus of the second part of the course, as well as the instrumental variable estimator. The main themes are presented under a theoretical perspective, accompanied by empirical applications on Stata.
Coefficient : 1
Require prerequisites :
Statistics and Probability, statistical inference, hypothesis testing, OLS with multiple variables
Learning outcomes :
At the end of the course the students will master the main micro-econometrics techniques for probability models and temporal data and they will be able to critically analyze applied work that employs these types of estimators.
Assessment :
Students will be evaluated in two steps. They will present in pairs a scientific paper among a list provided by the teacher. This will be the same paper to be replicated for the Database and Stata Programming course. The presentation will count for 30% of the final note. The rest of the note will be based on a final written exam scheduled in the exams’ week.
Bibliography-recommended reading
List of scientific papers for students’ presentations will be provided at the beginning of the course. Selected chapters from :
- Wooldridge, J. (2002) "Econometric analysis of cross-section and panel data", MIT Press, Cambridge.
- A. Colin Cameron and Pravin K. Trivedi (2005), "Microeconometrics: Methods and Applications", Cambridge University Press
All slides, datasets, papers and other materials will be available on the MyCourse webpage.
- Microeconometrics : data applications
Microeconometrics : data applications
Ects : 3
Lecturer :
Total hours : 24
Overview :
The course presents the Stata coding language for applying micro-econometrics techniques. In the first part of the course, the main Stata features are explained by focusing on the estimation of econometric models with qualitative variables and selection models. In the second part of the course, students will learn how to analyse temporal and panel data with Stata and how to estimate temporal models, such as random effects, fixed effects and double differences. Moreover, the course will provide students with the appropriate knowledge for reproducing their econometric analyses in a professional format.
Coefficient : 0,5
Recommended prerequisites :
Statistics and Probability, statistical inference, hypothesis testing, OLS with multiple variables
Learning outcomes :
The main objective of this course is to provide students with Stata coding skills for describing and analysing cross-sectional and panel data and for estimating probability and temporal econometric models.
After having attended the classes, the students will be able to describe and analyze phenomena of interest contained in cross-sectional and panel datasets by using Stata. They will be able to conduct econometric analysis concerning probability and temporal models with graphs and tables formatted in a professional manner.
Assessment :
Critical analysis and replication of a research paper’s results in a short dissertation format.
Bibliography-recommended reading
1. Cameron, Adrian Colin, and Pravin K. Trivedi. Microeconometrics using stata. Vol. 2. College Station, TX: Stata press, 2010.
2. Gentzkow and Shapiro (2014) “Code and Data for the Social Sciences: A Practitioner’s Guide.”
Internet resources:
1. Stata video tutorials: https://www.stata.com/links/video-tutorials/
2. UCLA tips: http://www.ats.ucla.edu/stata/
Mandatory courses - 12 ECTS
- Public economics
Public economics
Ects : 6
Lecturer :
Total hours : 30
Overview :
The aim of the course is to present the basic principles of public economics, showing the link between theoretical analysis and public policy applications in practice. The course will provide:
· An overview the main tools of public economic analysis,
· A presentation of the main market failures and a discussion of government intervention,
· An introduction to taxation
· A presentation of social insurance and redistribution programs
Theoretical concepts will be presented along with empirical evidence. Particular emphasis will be put on the recent empirical advances in public policy analysis.
Coefficient : 1
Recommended prerequisites :
Microeconomics, Econometrics
Learning outcomes :
After having attended the classes, the students should master the analytical tools and empirical methods to analyze the main market failures and the policies implemented to address them. They should also understand the fundamental trade-off between redistribution and efficiency and the challenges posed by the design of a tax/benefit system.
- Industrial Organization
Industrial Organization
Ects : 6
Lecturer :
Total hours : 30
Overview :
The course will analyse the following topics: Static models of oligopoly, Quality and product differentiation ; Tacit collusion ; Asymmetric information (Static competition, Communication, Limit pricing) ; Competition and Investment ; Welfare Standards in Competition Policy. The objective of the course is to provide a presentation of modern industrial organization that blends formal models with real-world applications and derives implications for firm strategy and competition policy.
Coefficient : 1
Learning outcomes :
After having attended the classes, the students will understand strategies chosen by firms with market power and how such firms adapt to different market environments.
Electives - 6 ECTS - Choose 2
- Population Economics
Population Economics
Ects : 3
Lecturer :
Total hours : 24
Overview :
Population economics applies an economic perspective to demography or the analysis of human populations. This course will provide an introduction to selected fields and research areas that are relevant for the economic analysis of populations, incl. family economics, migration economics, health economics and the economics of ageing. We will discuss theoretical models that help to explain, e.g., the relevance of economic factors for marriage and divorce, how income and education affect the number of children born in a family and investment in these children, or how pension policies affect younger generations. We will consider relevant empirical studies that test hypotheses derived from these models and discuss how economic insights might help to address some of the major challenges of the 21st century, such as population growth in low-income countries, international migration and population ageing in high-income countries.
Schedule:
1 Family Economics: Partnership formation and dissolution, intrahousehold decision-making
2 Family Economics: Fertility, Intergenerational links
3 Economics of migration: Determinants of migration, internal and international migration, characteristics of migrants
4 Economics of migration: Migrant’s health, family and labour market outcomes
5 Health Economics: Demand for health, health production and healthcare supply
6 Health Economics: Healthcare spending and health insurance
7 Economics of ageing: Older workers, retirement and pensions
8 Economics of ageing: Healthy ageing and long-term care
Coefficient : 0,5
Require prerequisites :
None.
Learning outcomes :
After completing the course, students will have an overview of some of the most important theories in population economics and the empirical evidence supporting or contradicting these theories. They will be able to discuss economic aspects of family formation, fertility, migration, health and ageing. Students will be able to read and critically assess empirical papers on these topics. The course will provide students with the required background for a specialization in health economics, family economics or the economics of ageing for the Master 2 or a Master thesis project in these research areas.
Assessment :
- Presentation of a research paper (30% of the final grade)
- Written final exam (70% of the final grade)
- Topics in Advanced Industrial Organisation
Topics in Advanced Industrial Organisation
Ects : 3
Lecturer :
Total hours : 21
Overview :
The course on Advanced Industrial Organization is the follow-up of the basic theories and models developed in the Industrial Organization class. We shall first explore the relationships among firms in the specific context of procurement and regulation. We will the introduce social regulation (economic evaluations that can be used in assessing environmental controls, health and safety). We shall then analyze dynamic aspects of competition that represent critical issues in high technology and information technology industries: innovation and persistence of market dominance, network externalities and two-sided markets. In complement to the Course of Industrial Organization, this course aims at covering most models of imperfect competition among firms to propose an analysis of various pricing strategies, marketing strategies and other strategic manipulations that characterize firms’ behavior when they try to gain or maintain market power.
Coefficient : 0,5
Learning outcomes :
After attending the classes, the students will have acquired a deep understanding of the advanced methods of quantitative industrial organization and game theory, to study the strategic interaction between firms and regulators, and dynamic competition models.
Assessment :
0.5
Bibliography-recommended reading
Economics of Regulation and Antitrust, Viscusi, Vernon Harrington. The Theory of Industrial Organization, Tirole.
- Measurement issues with applications to GDP, poverty and inequality
Measurement issues with applications to GDP, poverty and inequality
Ects : 3
Lecturer :
Total hours : 21
Overview :
Is GDP a suitable measure of economic and social progress? What makes a distribution of income more or less equal? How to quantify environmental damages?
This course aims at addressing these questions. It is a methodological course that discusses the measurement of economic and social outcomes. Policies are often designed based on indexes and quantitative objectives, while defining those indexes and outcomes is not always straightforward. In this course, we will discuss both the theoretical and empirical aspects of how to construct outcome variables: how are the conceptual choices made in terms of what is included or excluded from the computation of an indicator, and how each component is valued? Which data are used and do they allow to observe the entire phenomenon we want to measure? How do we translate the theoretical concepts into the data?
An introductory session will focus on what to be measured and how to measure it. In particular, it will discuss what the potential biases introduced by data choices (what is the source of the data, the size and representativeness of the sample, etc.). It will be followed by topic sessions on GDP, inequality, employment and unemployment, education, and the measurement of phenomenon that cannot be directly observed.
Coefficient : 0,5
Recommended prerequisites :
Statistics (Basic level)
Graduate Econometrics (M1 mandatory course)
Learning outcomes :
This course will allow students to have a critical eye on how socioeconomic indicators are built. It will provide them with some statistical tools regarding the measurement of phenomenon and cover more specific measurement issues in a range of economic and social dimensions. This reflection will allow students to better understand some of the controversial questions that are discussed in the public debate, and to themselves build social and economic indicators.
This class will be useful to all students, and in particular those who intend to do a PhD dissertation in economics using empirical data, as well as students who plan to work in institutions that produce economic statistics, studies and policy recommendations.
Assessment :
Assessment will be based on a presentation (30%), a project (65%) and participation in class (5%). The presentation will consist in presenting in class a research paper where measurement issues are central (30%). Regarding the project, students will be given a list of questions to choose from and will be asked to reflect on which indicator they could build to address this question.
Bibliography-recommended reading
A specific reading list with articles provided for each lecture
- Business cycles analysis
Business cycles analysis
Ects : 3
Lecturer :
Total hours : 24
Overview :
After presenting the stylized facts about the business cycle, the course will study the canonical real business cycle model that focuses on the role of technological shocks as determinant of macroeconomic fluctuations. We will then consider the role of monetary policy. After presenting some empirical evidence on the role of money, we will study the classical monetary model. The third part of the course is dedicated to the basic new Keynesian model with monopolistic competition and nominal price rigidities. Within this framework, we will study the role of technological shocks as well as monetary policy shock and discuss their empirical relevance regarding business cycles features.
Coefficient : 0,5
Recommended prerequisites :
Macroeoconomics I
Require prerequisites :
Microeconomics at the undergraduate level, good knowledge of optimization tools
Learning outcomes :
The course will provide students with sound knowledge and understanding of the basis of modern macroeconomic theory of business cycles. After attending the classes, the students will master the fundamental RBC and New Keynesian models of business cycles. They will get familiar with the modelling of price rigidities to explore the role of monetary policy within New Keynesian models analytically as well as to assess their quantitative predictions in terms of business cycles features.
Assessment :
The final grade will be based on two grades: a mid-term grade (30%) and a final exam grade (70%).
The final grade is based on a final written exam (closed-book exam). The mid-term grade is made on the grade obtained on a homework document. Ideally the homework is on an individual basis, but depending on the number of students to follow the course, the home-work document might be made by a team of max. 2 students. For this homework, the student(s) will have to provide a thoughtful analysis of a research paper (to be chosen within a given list). The student(s) will be assessed on her capacity to explain the paper’s main research question, the modeling assumptions and the main results, as well as the underlying macroeconomic mechanisms. The student(s) will also be evaluated on their ability to have some critical eye on the model’s performances.
Bibliography-recommended reading
- Gali, Jordi, Monetary Policy, Inflation and the Business Cycle: An Introduction to the New Keynesian Framework, Princeton University Press (2d edition)
- King, R., Plosser, C. & Rebelo, S. “Production, Growth and Business Cycles", Journal of Monetary Economics, 1988, vol. 21, pp. 195-232.
- Gali, J, “Technology, Employment and the Business Cycle: Do Technology Shocks explain aggregate fluctuations?" The American Economic Review, 1999, vol. 89, n.1, pp. 249-271
Other references will be provided along the course.
Open your mind - 3 ECTS
- Topics in advanced economic analysis
Topics in advanced economic analysis
DATA TRACK
Mandatory courses - 21 ECTS
- Optimization and numerical methods
Optimization and numerical methods
Ects : 6
Total hours : 24
Coefficient : 1
- Unsupervised learning
Unsupervised learning
Ects : 3
Total hours : 18
Coefficient : 0,5
- Topics in Advanced Industrial Organisation
Topics in Advanced Industrial Organisation
Ects : 3
Lecturer :
Total hours : 21
Overview :
The course on Advanced Industrial Organization is the follow-up of the basic theories and models developed in the Industrial Organization class. We shall first explore the relationships among firms in the specific context of procurement and regulation. We will the introduce social regulation (economic evaluations that can be used in assessing environmental controls, health and safety). We shall then analyze dynamic aspects of competition that represent critical issues in high technology and information technology industries: innovation and persistence of market dominance, network externalities and two-sided markets. In complement to the Course of Industrial Organization, this course aims at covering most models of imperfect competition among firms to propose an analysis of various pricing strategies, marketing strategies and other strategic manipulations that characterize firms’ behavior when they try to gain or maintain market power.
Coefficient : 0,5
Learning outcomes :
After attending the classes, the students will have acquired a deep understanding of the advanced methods of quantitative industrial organization and game theory, to study the strategic interaction between firms and regulators, and dynamic competition models.
Assessment :
0.5
Bibliography-recommended reading
Economics of Regulation and Antitrust, Viscusi, Vernon Harrington. The Theory of Industrial Organization, Tirole.
- Industrial Organization
Industrial Organization
Ects : 6
Lecturer :
Total hours : 30
Overview :
The course will analyse the following topics: Static models of oligopoly, Quality and product differentiation ; Tacit collusion ; Asymmetric information (Static competition, Communication, Limit pricing) ; Competition and Investment ; Welfare Standards in Competition Policy. The objective of the course is to provide a presentation of modern industrial organization that blends formal models with real-world applications and derives implications for firm strategy and competition policy.
Coefficient : 1
Learning outcomes :
After having attended the classes, the students will understand strategies chosen by firms with market power and how such firms adapt to different market environments.
- Programming and web data collection
Programming and web data collection
Ects : 3
Total hours : 18
Coefficient : 0,5
Open your mind - 3 ECTS
- Topics in advanced economic analysis
Topics in advanced economic analysis
Electives - Choose for 6 ECTS
- Population Economics
Population Economics
Ects : 3
Lecturer :
Total hours : 24
Overview :
Population economics applies an economic perspective to demography or the analysis of human populations. This course will provide an introduction to selected fields and research areas that are relevant for the economic analysis of populations, incl. family economics, migration economics, health economics and the economics of ageing. We will discuss theoretical models that help to explain, e.g., the relevance of economic factors for marriage and divorce, how income and education affect the number of children born in a family and investment in these children, or how pension policies affect younger generations. We will consider relevant empirical studies that test hypotheses derived from these models and discuss how economic insights might help to address some of the major challenges of the 21st century, such as population growth in low-income countries, international migration and population ageing in high-income countries.
Schedule:
1 Family Economics: Partnership formation and dissolution, intrahousehold decision-making
2 Family Economics: Fertility, Intergenerational links
3 Economics of migration: Determinants of migration, internal and international migration, characteristics of migrants
4 Economics of migration: Migrant’s health, family and labour market outcomes
5 Health Economics: Demand for health, health production and healthcare supply
6 Health Economics: Healthcare spending and health insurance
7 Economics of ageing: Older workers, retirement and pensions
8 Economics of ageing: Healthy ageing and long-term care
Coefficient : 0,5
Require prerequisites :
None.
Learning outcomes :
After completing the course, students will have an overview of some of the most important theories in population economics and the empirical evidence supporting or contradicting these theories. They will be able to discuss economic aspects of family formation, fertility, migration, health and ageing. Students will be able to read and critically assess empirical papers on these topics. The course will provide students with the required background for a specialization in health economics, family economics or the economics of ageing for the Master 2 or a Master thesis project in these research areas.
Assessment :
- Presentation of a research paper (30% of the final grade)
- Written final exam (70% of the final grade)
- Business cycles analysis
Business cycles analysis
Ects : 3
Lecturer :
Total hours : 24
Overview :
After presenting the stylized facts about the business cycle, the course will study the canonical real business cycle model that focuses on the role of technological shocks as determinant of macroeconomic fluctuations. We will then consider the role of monetary policy. After presenting some empirical evidence on the role of money, we will study the classical monetary model. The third part of the course is dedicated to the basic new Keynesian model with monopolistic competition and nominal price rigidities. Within this framework, we will study the role of technological shocks as well as monetary policy shock and discuss their empirical relevance regarding business cycles features.
Coefficient : 0,5
Recommended prerequisites :
Macroeoconomics I
Require prerequisites :
Microeconomics at the undergraduate level, good knowledge of optimization tools
Learning outcomes :
The course will provide students with sound knowledge and understanding of the basis of modern macroeconomic theory of business cycles. After attending the classes, the students will master the fundamental RBC and New Keynesian models of business cycles. They will get familiar with the modelling of price rigidities to explore the role of monetary policy within New Keynesian models analytically as well as to assess their quantitative predictions in terms of business cycles features.
Assessment :
The final grade will be based on two grades: a mid-term grade (30%) and a final exam grade (70%).
The final grade is based on a final written exam (closed-book exam). The mid-term grade is made on the grade obtained on a homework document. Ideally the homework is on an individual basis, but depending on the number of students to follow the course, the home-work document might be made by a team of max. 2 students. For this homework, the student(s) will have to provide a thoughtful analysis of a research paper (to be chosen within a given list). The student(s) will be assessed on her capacity to explain the paper’s main research question, the modeling assumptions and the main results, as well as the underlying macroeconomic mechanisms. The student(s) will also be evaluated on their ability to have some critical eye on the model’s performances.
Bibliography-recommended reading
- Gali, Jordi, Monetary Policy, Inflation and the Business Cycle: An Introduction to the New Keynesian Framework, Princeton University Press (2d edition)
- King, R., Plosser, C. & Rebelo, S. “Production, Growth and Business Cycles", Journal of Monetary Economics, 1988, vol. 21, pp. 195-232.
- Gali, J, “Technology, Employment and the Business Cycle: Do Technology Shocks explain aggregate fluctuations?" The American Economic Review, 1999, vol. 89, n.1, pp. 249-271
Other references will be provided along the course.
- Applied Microeconometrics
Applied Microeconometrics
Ects : 6
Lecturer :
Total hours : 30
Overview :
This course focuses on micro-econometrics techniques based on temporal data (cross-sectional and panel) and qualitative dependent variables. The first part will explore possible sources of OLS bias and discuss techniques and estimators to address those biases ( micro-econometrics techniques for temporal data, such as first difference, random effects, fixed effects and difference-in-differences estimators). Non-linear models (Probit, Logit models), as well as selection models (Tobit, Heckman selection models) will be the focus of the second part of the course, as well as the instrumental variable estimator. The main themes are presented under a theoretical perspective, accompanied by empirical applications on Stata.
Coefficient : 1
Require prerequisites :
Statistics and Probability, statistical inference, hypothesis testing, OLS with multiple variables
Learning outcomes :
At the end of the course the students will master the main micro-econometrics techniques for probability models and temporal data and they will be able to critically analyze applied work that employs these types of estimators.
Assessment :
Students will be evaluated in two steps. They will present in pairs a scientific paper among a list provided by the teacher. This will be the same paper to be replicated for the Database and Stata Programming course. The presentation will count for 30% of the final note. The rest of the note will be based on a final written exam scheduled in the exams’ week.
Bibliography-recommended reading
List of scientific papers for students’ presentations will be provided at the beginning of the course. Selected chapters from :
- Wooldridge, J. (2002) "Econometric analysis of cross-section and panel data", MIT Press, Cambridge.
- A. Colin Cameron and Pravin K. Trivedi (2005), "Microeconometrics: Methods and Applications", Cambridge University Press
All slides, datasets, papers and other materials will be available on the MyCourse webpage.
Academic Training Year 2025 - 2026 - subject to modification
Teaching Modalities
All courses in the first year of the Master’s in Quantitative Economics are taught in English and in lecture format. In some cases, part of the session may be devoted to correcting exercises and/or data processing. The first semester starts in early September with a 10-day refresher training course in statistical tools and Matlab programming. The first semester then lasts 12 weeks, with foundational courses in economics (Macroeconomics I, Microeconomics I, Game Theory), alongside two courses in data processing and analysis: Macroeconometrics and Data Management and Programming. Students are introduced to Matlab, Dynare and R software. All courses are mandatory, and amount to 30 ECTS credits. Courses and final exams end in December of the academic year.
The second semester expands on the lessons of the first semester. In terms of theory, this involves integrating market failures and frictions into economic analysis (Microeconomics II, Industrial Organization). A topical lecture also raises students’ awareness on how economic research can help addressing a selected set of contemporary issues at the heart of policy and economic debates. In terms of quantitative methods, instruction focuses on techniques for analyzing individual and qualitative data using Stata (Microeconometrics, with Application to Stata). In addition to these required courses, students choose two among five optional courses (Health Economics ; Measurement issues with applications to GDP, poverty and inequality ; International Trade ; Macroeconomics II ; Advanced Industrial Organization). Each student must earn 30 ECTS credits by the semester's end. Courses are spread out over 12 weeks from January to April, and exams are held in early May. Students are then strongly encouraged to pursue an internship, although this will not earn ECTS credits.
After the Master first year, the students can opt for a gap year before pursuing in one of the two Master 2 tracks. Only gap year projects that include a relevant pr ofessional experience (internship of short-term contract) and/or an exchange study program through the QTEM network will be accepted by the Master 2 directors. Applicants should have a strong and reliable project and shall discuss with the targeted Master 2 director during the Master first year to better prepare this gap year in line with the Master 2 training.
Internships and Supervised Projects
Students are not required to do an internship during the first year of their Master's in Quantitative Economics. However, they are strongly encouraged to pursue one after the second semester’s exams, although this will not earn ECTS credits.
Research-driven Programs
Training courses are developed in close collaboration with Dauphine's world-class research programs, which ensure high standards and innovation.
Research is organized around 6 disciplines all centered on the sciences of organizations and decision making.
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