Quantitative Economic Analysis - 296 - 2nd year of master's degree

AQME CERTIFICATE (9 ECTS)

• Machine Learning

  Machine Learning

  Ects : 6

  Lecturer :
  FABRICE ROSSI
  

  Total hours : 36

  Overview :

  The course gives a thorough presentation of the machine learning field and follows this outline:

  1. general introduction to machine learning and to its focus on predictive performances (running example: k-nearest neighbours algorithm)
  2. machine learning as automated program building from examples (running example: decision trees)
  3. machine learning as optimization: empirical risk minimizationlinks with maximum likelihood estimationsurrogate losses and extended machine learning settingsregularisation and kernel methods (support vector machines)
  4. reliable estimation of performances: over fittingsplit samplesresampling (leave-one-out, cross-validation and bootstrap)ROC curve, AUC and other advanced measures
  5. combining models: ensemble techniquesbagging and random forestsboosting
  6. unsupervised learning: clustering (hierarchical clustering, k-means and variants, mixture models, density clustering)outlier and anomaly detection

  Coefficient : 2

  Require prerequisites :

  • intermediate level in either Python or R. Students are expected to be able to perform standard data management tasks in Python or R, including, but not limited to: loading a data set from a CSV filerecoding and cleaning the data set implementing a simple data exploration strategy based on pivot table and on graphical representation
  • intermediate level in statistics and probability. Students are expected to be familiar with: descriptive statisticsconditional probabilities and conditional expectationscore results from statistics: bias and variance concepts, strong law of large numbers, central limit theorem, etc.

  Learning outcomes :

  After attending the course the students will

  • have a good understanding of the algorithmic and statistical foundations of the main machine learning techniques
  • be able to select machine learning techniques adapted to a particular task (exploratory analysis with clustering methods, predictive analysis, etc.)
  • be able to design a model selection procedure adapted to a particular task
  • report the results of a machine learning project with valid estimation of the performances of their model

  Assessment :

  • quizzes and tests during the course
  • machine learning project
• Introduction to Matlab programming

  Introduction to Matlab programming

  Lecturer :
  CEDRIC CROFILS
  

  Total hours : 12
• Python for data science

  Python for data science

  Ects : 3

  Lecturer :
  MOHAMED KHALIL EL MAHRSI
  

  Total hours : 18

  Overview :

  The course is organised as follows.

   

  1 - Introduction to Python Programming

   

  This first part introduces the fundamentals of Python programming. It covers topics such as working with basic built-in types (numbers, strings, booleans, ...), control flow statements, writing reusable code (functions), handling errors and exception that can occur during the execution of Python code, advanced data structures (lists, sets, dictionaries, ...), ...

   

  2 - Scientific Computing With NumPy

   

  This part focuses on using NumPy, a scientific computing package that provides a wide assortment of useful and highly-optimized routines for working with multi-dimensional arrays (matrices, tensors, ...), linear algebra, statistics and random simulation, and much more.

   

  3 - Processing Tabular Data With pandas

   

  The third part of the course is dedicated to pandas, a fundamental Python package when it comes to data science and data analysis. pandas provides functionalities for efficient manipulation of data frames, i.e., tabular data (stored in csv files, Excel sheets, ...). With the help of pandas, you can easily conduct tasks such as data cleaning (filling missing data, replacing outliers, ...), reshaping, merging, ...

   

  4 - Visualizing Data With Matplotlib and seaborn

   

  The last part of the course is a quick introduction to data visualization functionalities in Python using the Matplotlib and seaborn packages. Data visualization is a very powerful tool for making sens of large volumes of data, identifying patterns, and extracting useful insights that can help understand and solve real-world business cases.

  Coefficient : 1

  Recommended prerequisites :

  The course does not assume any prior knowledge in programming in general and Python in particular. However, familiarity with another programming language can be useful in understanding the discussed concepts and topics.

  Require prerequisites :

  You are expected to be familiar with mathematical tools associated to an economics curriculum (linear algebra, calculus, probability, and statistics) at an undergraduate level

  Learning outcomes :

  By the end of this course, you will be able to

  • Write and understand entry-level to intermediate-level code in the Python programming language
  • Use NumPy for scientific computing and efficient manipulation of multi-dimensional arrays and matrices
  • Use pandas to load, manipulate, and analyze tabular data
  • Use Matplotlib and seaborn to visualize data

  Assessment :

  You will be evaluated based on a team project (conducted in pairs) in which you will apply the knowledge and skills you acquired during the course. The project takes the form of an exploratory data analysis in which you will work on a tabular data set in order to extract valuable insights that can help solve a business problem. The expected deliverables of the project are:

  • A 5–10 pages report;
  • The source code (Jupyter notebooks or Python scripts) of your work, either in a Github repository or as a zip file.

  You are expected to present your main findings during a 10-minutes presentation, which will be followed by approximatively 5 minutes of questions.

MANDATORY COURSES

• Master Thesis project

  Master Thesis project

  Ects : 3

  Lecturer :
  LISE PATUREAU
  

  Overview :

  The purpose is to help the student to build his Master thesis subject. The student is expected to work on his own on his Master thesis subject, with the help of her Master supervisor if needed. There is no session in class associated with this course. The student is expected to write a summary of her Master thesis project specifying: the supervisor, the general topic; the summary of the research question and what is the (expected) original contribution ; the data to be used, the method of implementation shall also be clarified.

  Coefficient : Validation

  Learning outcomes :

  Acquire an overview of a research topic, identify the key relevant research papers and the methodology used to address the question

  Assessment :

  There is no grade associated to this course. Validation will be granted if the student provide the summary of the Master thesis project by the due time.

• Conference cycles: International Organizations & Job Market Informations

  Conference cycles: International Organizations & Job Market Informations

  Coefficient : Validation

OPTIONAL COURSE (6 ECTS) MANDATORY WITHIN THE SPECIALIZATION FIELD

Specialization field : Theory

• Methods for public policy evaluation

  Methods for public policy evaluation

  Ects : 6

  Lecturer :
  ERIC BONSANG
  

  Total hours : 27

  Coefficient : 2
• Advanced Macroeconometrics

  Advanced Macroeconometrics

  Ects : 6

  Lecturer :
  FABIEN TRIPIER
  

  Total hours : 27

  Coefficient : 2

Specialization field: Social and Public Policies

• Methods for public policy evaluation

  Methods for public policy evaluation

  Ects : 6

  Lecturer :
  ERIC BONSANG
  

  Total hours : 27

  Coefficient : 2

Specialization field: Macro & Finance

• Advanced Macroeconometrics

  Advanced Macroeconometrics

  Ects : 6

  Lecturer :
  FABIEN TRIPIER
  

  Total hours : 27

  Coefficient : 2

SPECIALIZATION COURSES (12 ECTS) MANDATORY WITHIN THE FIELD

Specialization field: Theory - Mandatory courses

• Behavioral economics and bounded rationality

  Behavioral economics and bounded rationality

  Ects : 3

  Lecturer :
  BERTRAND VILLENEUVE
  

  Total hours : 21

  Overview :

  The objective of the course is to present the most important themes in behavioral economics.

  • Reference-dependent utility, with and without risk
  • Probabilistic judgement and the treatment of information
  • Time preferences
  • Attention and inattention
  • Social preferences

  The course itself will focus on models and their empirical validity. By choice, the course will not be principally about experimental protocols - yet protocols are explained occasionally - but rather on main ideas, results, and debates. The diverse applications will be treated all along.

  Coefficient : 2

  Require prerequisites :

  Expected utility. Basic game theory. Basic probability theory, comprised Bayesian calculus.

  Learning outcomes :

  The topic has reached a certain degree of maturity and it is part of an aspiring economist culture. After attending the classes, the students will be able to read the cutting-edge research on the topic. Given the variety of ways by which standard (non behavioral) models can be tweaked, the course is not intended to promote a particular view, but to help would-be modelers to better motivate their choices.

  Assessment :

  • MCQs all along the classes (50%).
  • Final written exam (50%).

  Bibliography-recommended reading

  Highly recommended for the fascinating and lively excursion across almost all topics: Daniel Kahneman's 2011 book, Thinking Fast and Slow.

  The main reference is the Handbook of Behavioral Economics, Elsevier, 2018 and 2019. All chapters are dense. Some of them are heavily used for the lectures.

• Empirical Industrial Organization

  Empirical Industrial Organization

  Ects : 3

  Lecturer :
  DANIEL HERRERA
  

  Total hours : 21

  Overview :

  In this course we will cover mainstream empirical industrial organization methods used to construct ex-ante, policy-relevant, evaluations. The main goal is to provide a set of tools necessary to undertake empirical analyses typically performed in Empirical Industrial Organization. These methods can be applied in any other field. Most methods that will be reviewed in this course are not limited to empirical IO, but can be used in a variety of different fields such as health, finance, and environmental economics. The course will consider reduced-form estimation papers, seeking to provide insights from data to understand how markets work. To generate policy-relevant counterfactuals, the course will also deal with structural estimation of supply and demand models. Reduced and structural econometrics methods requires the use of programs such as Matlab. Practical tutorials will ensure the implementation of the materials provided in the course.

  Coefficient : 2

  Recommended prerequisites :

  Basic programming skills on Matlab or similar software.

  Require prerequisites :

  Theoretical Industrial Organization and advanced econometrics.

  Learning outcomes :

  After having attended the classes, the students will have an overview of seminal and recent papers in empirical IO; understand core empirical methods and the data requirements for each method to be implemented. They will also have a working knowledge on Matlab.

  Bibliography-recommended reading

  Entry models and market structure: estimation of fixed costs

  • [***] Berry, S., & Reiss, P. (2007). Empirical models of entry and market structure. Handbook of industrial organization, 3, 1845-1886.
  • [***] T. Bresnahan and P. Reiss, “Econometric Models of Discrete Games,” Journal of Econometrics, 1991a.
  • [***] T. Bresnahan, and P. Reiss, “Entry and Competition in Concentrated Markets,” Journal of Political Economy, 1991b.
  • [***] S. Berry, “Estimation of a Model of Entry in the Airline Industry,” Econometrica, 1992.
  • S. Berry and J. Waldfogel, “Free Entry and Social Inefficiency in Radio Broadcasting,” RAND Journal of Economics, 1999.
  • O. Toivanen, and M. Waterson, “Market Structure and Entry: Where’s the Beef?” RAND Journal of Economics, 2005.
  • K. Seim, “An Empirical Model of Firm Entry with Endogenous Product–Type Choices,” RAND Journal of Economics, 2006.
  • Verboven, F., & Schaumans, C. Entry and competition in concentrated markets with product differentiation. Review of Economics and Statistics, 97(1), 195-209, 2015
  • P. Jia, “What Happens When Wal-Mart Comes to Town: An Empirical Analysis of the Discount Retail Industry,” EMA, November 2008, 1263-316.
  • M. Mazzeo, “Product Choice and Oligopoly Market Structure,” RJE, Summer 2002, 221-42.
  • Schaumans, C. and F. Verboven (2008), "Entry and Regulation: Evidence from Health care Professions," RAND Journal of Economics, 39(4), pp. 949–972.

  Estimation of demand and marginal costs

  • [***] Steven T. Berry, “Estimating Discrete-Choice Models of Product Differentiation,” Rand Journal of Economics, 25, 242-262, 1994.
  • [***] Berry, S., Levinsohn, J., & Pakes, A. (1995). Automobile prices in market equilibrium. Econometrica: Journal of the Econometric Society, 841-890.
  • [***] A. Nevo, “Identification of the Oligopoly Solution Concept in a Differentiated– Prod ucts Industry,” Economics Letters, 1998.
  • [***] Nevo, A. (2000). Mergers with differentiated products: The case of the ready-to-eat cereal industry. The RAND Journal of Economics, 395-421.
  • [***] A. Nevo, “Empirical Models of Consumer Behavior,” Annual Review of Economics, 2011.
  • Berry, S., & Pakes, A. (2007). The pure characteristics demand model. International Economic Review, 48(4), 1193-1225
  • Goldberg, P. K. (1995). Product differentiation and oligopoly in international markets: The case of the US automobile industry. Econometrica: Journal of the Econometric Society, 891-951
  • A. Goolsbee and A. Petrin, “The Consumer Gains from Direct Broadcast Satellites and the Competition with Cable TV,” Econometrica, 2004.
  • C. Knittel and K. Metaxoglou, “Estimation of Random–Coefficient Demand Models: Two Empiricists’ Perspective,” The Review of Economics and Statistics, 2014.
  • A. Nevo, “A Practitioner’s Guide to Estimation of Random–Coefficients Logit Models of Demand,” Journal of Economics & Management Strategy, 2000b.
  • A. Nevo, “Measuring Market Power in the Ready–To–Eat Cereal Industry,” Econometrica, 2001.
• Advanced Game Theory

  Advanced Game Theory

  Ects : 3

  Lecturer :
  FRANCOISE FORGES
  

  Total hours : 18

  Overview :

  The course is divided into two parts. The first part is devoted to so-called “noncooperative games” and concentrates on multistage games with incomplete information played by Bayesian players. The agents’ rationality is analyzed through various solution concepts, capturing backward and/or forward induction. These solution concepts are applied to strategic information transmission and communication. In the second part, we will first focus on a particular class of games of strategic information transmission, the class of unidimensional cheap talk sender receiver-games, and then introduce recent models on the choice of an information structure by a designer (or principal) for an agent or a set of agents who interact strategically in an asymmetric information setting.  

  Coefficient : 2

  Learning outcomes :

  After having attended the classes, the students will be able to read recent academic papers applying game theory to various area of economics and to make use of game theory in their future research work.

Specialization field: Theory - Optional courses (Choose one)

• Asset pricing Theory

  Asset pricing Theory

  Ects : 3

  Lecturer :
  JEROME DUGAST
  

  Total hours : 27

  Coefficient : 2
• Inequality and redistribution

  Inequality and redistribution

  Ects : 3

  Lecturer :
  LAURA KHOURY
  

  Total hours : 18

  Overview :

  In most developed countries, inequality has been rising in recent decades, becoming a key political issue at the center of the public debate. This course aims at understanding the historical evolution of between- and within-country inequality from the late 19th century until today, and what are the key drivers explaining this evolution. How to adequately measure inequality? How does globalization impact global inequality? What is the effect of technological change on labor income inequality? What is the role of public policies in mitigating these effects? We will review economic theories and use up-to-date empirical techniques to address these questions. Through the presentations of recent research papers, students will also get acquainted with the multiple dimensions of inequality (e.g. gender inequality, racial inequality, inequality in education outcomes, etc.).

  Coefficient : 2

  Require prerequisites :

  Statistics (Basic level)

  Microeconometrics (M1 mandatory course)

  Learning outcomes :

  At the end of the course, students should be able to:

  • Describe the evolution of income inequality in developed and developing countries since the 19th century
  • Identify and describe the drivers of the change in labor and capital inequality
  • Understand and use models to rationalize the change in labor and capital inequality
  • Understand and design policy tools that can mitigate inequality through redistribution

  Assessment :

  Assessment will be based on a presentation (30%), a final written exam (65%) and participation in class (5%). The presentation will consist in presenting in class a research paper addressing the question of inequality. The final exam will be a mix of short questions about concepts seen in class and question where the student will be asked to develop his own analysis using the concepts seen in class.

  Bibliography-recommended reading

  A specific reading list is provided at the start of each session.

• Environement and sustainability

  Environement and sustainability

  Ects : 3

  Lecturer :
  ANNA CRETI
  

  Total hours : 21

  Coefficient : 2

Specialization field: Social and Public Policies - Mandatory courses

• Labor & Education economics

  Labor & Education economics

  Ects : 3

  Lecturer :
  EVE CAROLI
  

  Total hours : 24

  Overview :

  This course will cover a number of topics at the frontier of current research in labour economics, among the following:

  • Returns to education
  • Compensating wage differentials
  • Wage inequality
  • Skill-biased technical change
  • Discrimination on the labour market
  • Monopsony on the labour market

  The objective of the course is to provide students with advanced knowledge of a series of topics that are key to public policy in the field of labour. The course will cover both the theoretical and empirical aspects of all topics. It will also systematically discuss the relevant policy implications.

  Coefficient : 2

  Recommended prerequisites :

  Labour Economics (undergraduate)

  Require prerequisites :

  Microeconomics (graduate level)

  Learning outcomes :

  After attending the course, the students will have acquired the tools that are necessary to analyse public policies in the field of labour. They will also have an excellent mastering of the nature of these policies and be equipped to make policy recommendations in the field of labour.

  Assessment :

  Written exam

• Inequality and redistribution

  Inequality and redistribution

  Ects : 3

  Lecturer :
  LAURA KHOURY
  

  Total hours : 18

  Overview :

  In most developed countries, inequality has been rising in recent decades, becoming a key political issue at the center of the public debate. This course aims at understanding the historical evolution of between- and within-country inequality from the late 19th century until today, and what are the key drivers explaining this evolution. How to adequately measure inequality? How does globalization impact global inequality? What is the effect of technological change on labor income inequality? What is the role of public policies in mitigating these effects? We will review economic theories and use up-to-date empirical techniques to address these questions. Through the presentations of recent research papers, students will also get acquainted with the multiple dimensions of inequality (e.g. gender inequality, racial inequality, inequality in education outcomes, etc.).

  Coefficient : 2

  Require prerequisites :

  Statistics (Basic level)

  Microeconometrics (M1 mandatory course)

  Learning outcomes :

  At the end of the course, students should be able to:

  • Describe the evolution of income inequality in developed and developing countries since the 19th century
  • Identify and describe the drivers of the change in labor and capital inequality
  • Understand and use models to rationalize the change in labor and capital inequality
  • Understand and design policy tools that can mitigate inequality through redistribution

  Assessment :

  Assessment will be based on a presentation (30%), a final written exam (65%) and participation in class (5%). The presentation will consist in presenting in class a research paper addressing the question of inequality. The final exam will be a mix of short questions about concepts seen in class and question where the student will be asked to develop his own analysis using the concepts seen in class.

  Bibliography-recommended reading

  A specific reading list is provided at the start of each session.

• Health, welfare and health behavior

  Health, welfare and health behavior

  Ects : 3

  Coefficient : 2

Specialization field: Social and Public Policies - Optional courses (Choose one)

• Behavioral economics and bounded rationality

  Behavioral economics and bounded rationality

  Ects : 3

  Lecturer :
  BERTRAND VILLENEUVE
  

  Total hours : 21

  Overview :

  The objective of the course is to present the most important themes in behavioral economics.

  • Reference-dependent utility, with and without risk
  • Probabilistic judgement and the treatment of information
  • Time preferences
  • Attention and inattention
  • Social preferences

  The course itself will focus on models and their empirical validity. By choice, the course will not be principally about experimental protocols - yet protocols are explained occasionally - but rather on main ideas, results, and debates. The diverse applications will be treated all along.

  Coefficient : 2

  Require prerequisites :

  Expected utility. Basic game theory. Basic probability theory, comprised Bayesian calculus.

  Learning outcomes :

  The topic has reached a certain degree of maturity and it is part of an aspiring economist culture. After attending the classes, the students will be able to read the cutting-edge research on the topic. Given the variety of ways by which standard (non behavioral) models can be tweaked, the course is not intended to promote a particular view, but to help would-be modelers to better motivate their choices.

  Assessment :

  • MCQs all along the classes (50%).
  • Final written exam (50%).

  Bibliography-recommended reading

  Highly recommended for the fascinating and lively excursion across almost all topics: Daniel Kahneman's 2011 book, Thinking Fast and Slow.

  The main reference is the Handbook of Behavioral Economics, Elsevier, 2018 and 2019. All chapters are dense. Some of them are heavily used for the lectures.

• Empirical Industrial Organization

  Empirical Industrial Organization

  Ects : 3

  Lecturer :
  DANIEL HERRERA
  

  Total hours : 21

  Overview :

  In this course we will cover mainstream empirical industrial organization methods used to construct ex-ante, policy-relevant, evaluations. The main goal is to provide a set of tools necessary to undertake empirical analyses typically performed in Empirical Industrial Organization. These methods can be applied in any other field. Most methods that will be reviewed in this course are not limited to empirical IO, but can be used in a variety of different fields such as health, finance, and environmental economics. The course will consider reduced-form estimation papers, seeking to provide insights from data to understand how markets work. To generate policy-relevant counterfactuals, the course will also deal with structural estimation of supply and demand models. Reduced and structural econometrics methods requires the use of programs such as Matlab. Practical tutorials will ensure the implementation of the materials provided in the course.

  Coefficient : 2

  Recommended prerequisites :

  Basic programming skills on Matlab or similar software.

  Require prerequisites :

  Theoretical Industrial Organization and advanced econometrics.

  Learning outcomes :

  After having attended the classes, the students will have an overview of seminal and recent papers in empirical IO; understand core empirical methods and the data requirements for each method to be implemented. They will also have a working knowledge on Matlab.

  Bibliography-recommended reading

  Entry models and market structure: estimation of fixed costs

  • [***] Berry, S., & Reiss, P. (2007). Empirical models of entry and market structure. Handbook of industrial organization, 3, 1845-1886.
  • [***] T. Bresnahan and P. Reiss, “Econometric Models of Discrete Games,” Journal of Econometrics, 1991a.
  • [***] T. Bresnahan, and P. Reiss, “Entry and Competition in Concentrated Markets,” Journal of Political Economy, 1991b.
  • [***] S. Berry, “Estimation of a Model of Entry in the Airline Industry,” Econometrica, 1992.
  • S. Berry and J. Waldfogel, “Free Entry and Social Inefficiency in Radio Broadcasting,” RAND Journal of Economics, 1999.
  • O. Toivanen, and M. Waterson, “Market Structure and Entry: Where’s the Beef?” RAND Journal of Economics, 2005.
  • K. Seim, “An Empirical Model of Firm Entry with Endogenous Product–Type Choices,” RAND Journal of Economics, 2006.
  • Verboven, F., & Schaumans, C. Entry and competition in concentrated markets with product differentiation. Review of Economics and Statistics, 97(1), 195-209, 2015
  • P. Jia, “What Happens When Wal-Mart Comes to Town: An Empirical Analysis of the Discount Retail Industry,” EMA, November 2008, 1263-316.
  • M. Mazzeo, “Product Choice and Oligopoly Market Structure,” RJE, Summer 2002, 221-42.
  • Schaumans, C. and F. Verboven (2008), "Entry and Regulation: Evidence from Health care Professions," RAND Journal of Economics, 39(4), pp. 949–972.

  Estimation of demand and marginal costs

  • [***] Steven T. Berry, “Estimating Discrete-Choice Models of Product Differentiation,” Rand Journal of Economics, 25, 242-262, 1994.
  • [***] Berry, S., Levinsohn, J., & Pakes, A. (1995). Automobile prices in market equilibrium. Econometrica: Journal of the Econometric Society, 841-890.
  • [***] A. Nevo, “Identification of the Oligopoly Solution Concept in a Differentiated– Prod ucts Industry,” Economics Letters, 1998.
  • [***] Nevo, A. (2000). Mergers with differentiated products: The case of the ready-to-eat cereal industry. The RAND Journal of Economics, 395-421.
  • [***] A. Nevo, “Empirical Models of Consumer Behavior,” Annual Review of Economics, 2011.
  • Berry, S., & Pakes, A. (2007). The pure characteristics demand model. International Economic Review, 48(4), 1193-1225
  • Goldberg, P. K. (1995). Product differentiation and oligopoly in international markets: The case of the US automobile industry. Econometrica: Journal of the Econometric Society, 891-951
  • A. Goolsbee and A. Petrin, “The Consumer Gains from Direct Broadcast Satellites and the Competition with Cable TV,” Econometrica, 2004.
  • C. Knittel and K. Metaxoglou, “Estimation of Random–Coefficient Demand Models: Two Empiricists’ Perspective,” The Review of Economics and Statistics, 2014.
  • A. Nevo, “A Practitioner’s Guide to Estimation of Random–Coefficients Logit Models of Demand,” Journal of Economics & Management Strategy, 2000b.
  • A. Nevo, “Measuring Market Power in the Ready–To–Eat Cereal Industry,” Econometrica, 2001.
• Environement and sustainability

  Environement and sustainability

  Ects : 3

  Lecturer :
  ANNA CRETI
  

  Total hours : 21

  Coefficient : 2

Specialization field: Macro & Finance - Mandatory courses

• International Trade & International Macroeconomics

  International Trade & International Macroeconomics

  Ects : 3

  Lecturer :
  GIANLUCA OREFICE
  

  Total hours : 24

  Overview :

  The course is a topics course on international trade and macroeconomics, which covers the recent advances in international trade and macroeconomics with an emphasis on the role of firm heterogeneity. Starting from recent models of international trade with heterogeneous firms (Melitz 2003; Chaney 2008) and its effects on the labor market, the course will rely on the theoretical modelling of the New Open Economy Macroeconomy framework (Obstfeld & Rogoff, 1995), which embeds explicit microfoundations in a dynamic general equilibrium perspective. The first part of the course will provide students with the essential tools to study the optimal international strategy of firms with different levels of productivity. The second part of the course studies the recent advances in international macroeconomics that incorporate these elements from the international trade literature, by modeling the role of the extensive margin of trade à la Melitz (2003) in an international macroeconomic setting.

   

  Part 1 – The New New Trade Theory and the Heterogeneity of firms

   

  - International Trade with Heterogeneous Firms (Melitz 2003)

  - FDI with Heterogeneous Firms: Helpman, Melitz and Yeaple (2004)

  - Trade Liberalization, Labor Market, Homogeneous Firms (Trefler 2003, Kovak 2013)

  - Liberalization, Labor Market, Heterogeneous firms (Helpman and Itskhoki 2010)

   

  Part 2 – International Macroeconomics

   

  - Trade costs, trade integration and international macroeconomic puzzles

  - Firm heterogeneity, firm dynamics and international fluctuations

  - Trade, granularity and business cycles

  - The macro consequences of economic uncertainty in a globalized world

  Coefficient : 2

  Recommended prerequisites :

  Having followed a course on Macroeconomics of Fluctuations (Master 1 level) and a course in International trade (Master 1 level) is recommended

  Learning outcomes :

  The objective of the course is to provide students with the key topics in the field of international trade and international macroeconomics and the modelling framework to address them. A specific focus will be made on the role of firm heterogeneity in shaping international trade flows as well as macroeconomic fluctuations in an international set-up. The students will be trained to read leading research articles on these issues. After attending the classes, the students will have a sharp understanding of the optimal international strategy of firms, and how such trade microfoundations shed new light on long-standing or novel questions in international macroeconomics. They will also master the cutting-edge research at the frontier between international macroeconomics and international trade, and how to think about economic policy in this global framework.

  Assessment :

  Mode of Assessment

   

  Final grade: 60%

  Mid-term grade: 40%

  The mid-term grade will consist of a short essay written by each student individually. In this essay, the student will choose his/her favourite paper covered during classes. A first part of the essay will consist in summarizing the paper and putting it in perspective to the existing literature. In the second part of the essay, the student will focus on the main achievements/merits of the paper, and on the potential criticisms (if any). The essay should be no longer than 10 pages (police 12) (bibliography excluded). The essay is expected to be send to both teachers one month after the end of the course.

  The final grade will be based on a written final exam, covering both parts of the course. It will be a closed-book exam.

  Bibliography-recommended reading

  Part I: International trade

  • Brainard, S.L. (1997) “An Empirical Assessment of the Proximity- Concentration Trade-off Between Multinational Sales and Trade,” American Economic Review, 87(4), pages 520-544 (suggested reading)
  • Melitz, M., Helpman, H. and S. Yeaple (2004) “Export Versus FDI with Heterogeneous Firms”, American Economic Review 94: 300-316 (compulsory reading).
  • Pavcnik (2002) “Trade Liberalization, Exit, and Productivity Improvements: Evidence from Chilean Plants”, The Review of Economic Studies 69, January 2002, pp. 245-76 (suggested reading).
  • Trefler D. (2004) “The Long and Short of the Canada-U.S. Free Trade Agreement”, American Economic Review 94: 870-895 (compulsory reading).
  • Helpman H. and Itskhoki (2010) “Labour Market Rigidities, Trade and Unemployment”, Review of Economic Studies, 77(3): 1100-1137 (compulsory reading).
  • Kovak, B. (2013) “Regional Effects of Trade Reform: What is the Correct Measure of Liberalization”, American Economic Review, 103(5): 1960-1976 (compulsory reading).
  • Autor D., Dorn D., and G. Hanson (2013) “The China Syndrome: Local Labor Market Effects of Import Competition in the United States”, American Economic Review, 2013, 103(6), 2121–2168 (compulsory reading).
  • Kovak, B and R. Dix-Carneiro (2017) “Trade Liberalization and Regional Dynamics”, American Economic Review, 107(10): 1908-2946 (suggested reading).

   

  Part II: International Macroeconomics

  • Backus, David K.; Kehoe, Patrick J.; Kydland, Finn E. (1995), "International Business Cycles: Theory and Evidence", in Cooley, Tom (ed.), Frontiers of Business Cycle Research, Princeton University Press (compulsory reading)
  • The Six Major Puzzles in International Macroeconomics: Is There a Common Cause?, Maurice Obstfeld, Kenneth Rogoff. in NBER Macroeconomics Annual 2000, Volume 15, Bernanke and Rogoff. 2001 (compulsory reading)
  • Ghironi, Fabio, and Ma rc Melitz. 2005. “International Trade and Macroeconomic Dynamics with Heterogeneous Firms.” Quarterly Journal of Economics 120: 865-915 (compulsory reading)

   

  The short essay for the international macro part can be chosen in the following list of papers - which can be amended along the course depending on the number of students and their interests.

  • Barratieri, Alessandro, Cacciatore, Matteo, Ghironi, Fabio; « Protectionism and the business cycle », Journal of International Economics, vol. 129, 2021, p. 1-21
  • Monetary policy, firm heterogeneity, and product variety, Hamano, Masashige and Zanetti, Francesco, European Economic Review, Vol. 104, 2022
  • Cacciatore M., Ghironi F., “Trade, unemployment, and monetary policy”, Journal of International Economics, 2021
  • di Giovanni, Julian, Levchenko, Andrei and Mejean, Isabelle "The Micro Origins of International Business-Cycle Comovement", American Economic Review, Vol 108, 2018
  • di Giovanni, Julian, Levchenko, Andrei and Mejean, Isabelle "Large Firms and International Business Cycle Comovement", American Economic Review P&P, 107(5):598-602, 2017,
  • Acemoglu, Daron, Akcigit, Ufuk and Kerr, William, “Networks and the macroeconomy: An empirical exploration”, NBER Macroeconomics Annual, 2016, vol 30 (1).
  • Kleinert, Jorn, Martin, Julien and Toubal, Farid, “The Few Leading the Many: Foreign Affiliates and Business Cycle Comovement”, American Economic Journal: Macroeconomics 2015, 7(4)
  • Dario Caldara, Matteo Iacoviello, Patrick Molligo, Andrea Prestipino and Andrea Raffo "The economic effects of trade policy uncertainty", Journal of Monetary Economics, Volume 109, January 2020.
  • Steinberg, J. "Brexit and the macroeconomic impact of trade policy uncertainty", Journal of International Economics, 117, 175-195, 2019.
• Business Cycles and Stabilization policies

  Business Cycles and Stabilization policies

  Ects : 3

  Lecturer :
  ANNE EPAULARD
  

  Total hours : 24

  Coefficient : 2

Specialization field: Macro & Finance - Optional courses (Choose 2)

• Asset pricing Theory

  Asset pricing Theory

  Ects : 3

  Lecturer :
  JEROME DUGAST
  

  Total hours : 27

  Coefficient : 2
• Behavioral economics and bounded rationality

  Behavioral economics and bounded rationality

  Ects : 3

  Lecturer :
  BERTRAND VILLENEUVE
  

  Total hours : 21

  Overview :

  The objective of the course is to present the most important themes in behavioral economics.

  • Reference-dependent utility, with and without risk
  • Probabilistic judgement and the treatment of information
  • Time preferences
  • Attention and inattention
  • Social preferences

  The course itself will focus on models and their empirical validity. By choice, the course will not be principally about experimental protocols - yet protocols are explained occasionally - but rather on main ideas, results, and debates. The diverse applications will be treated all along.

  Coefficient : 2

  Require prerequisites :

  Expected utility. Basic game theory. Basic probability theory, comprised Bayesian calculus.

  Learning outcomes :

  The topic has reached a certain degree of maturity and it is part of an aspiring economist culture. After attending the classes, the students will be able to read the cutting-edge research on the topic. Given the variety of ways by which standard (non behavioral) models can be tweaked, the course is not intended to promote a particular view, but to help would-be modelers to better motivate their choices.

  Assessment :

  • MCQs all along the classes (50%).
  • Final written exam (50%).

  Bibliography-recommended reading

  Highly recommended for the fascinating and lively excursion across almost all topics: Daniel Kahneman's 2011 book, Thinking Fast and Slow.

  The main reference is the Handbook of Behavioral Economics, Elsevier, 2018 and 2019. All chapters are dense. Some of them are heavily used for the lectures.

• Quantitative International Economics

  Quantitative International Economics

  Ects : 3

  Lecturer :
  FARID TOUBAL
  

  Total hours : 21

  Coefficient : 2

MANDATORY COURSES

• PhD Proposal / Internship

  PhD Proposal / Internship

  Ects : 6

  Coefficient : Validation

Master Thesis

• Master Thesis Defense

  Master Thesis Defense

  Ects : 18

  Total hours : 11

  Coefficient : Validation
• Master Thesis support seminar

  Master Thesis support seminar

  Total hours : 27

  Coefficient : Validation

SPECIALIZATION COURSES (6 ECTS) MANDATORY WITHIN THE SPECIALIZATION FIELD

Specialization field: Theory

• Banking economics

  Banking economics

  Ects : 3

  Lecturer :
  SYLVAIN CARRE
  

  Total hours : 18

  Overview :

  1. Basic concepts in banking economics. The Diamond-Dybvig model. Financial instability issues: bank runs and bank panics.

  2. Solutions to financial instability. Ex-ante and ex-post liquidity provision. Interbank markets, lender of last resort. Deposit insurance and moral hazard.

  3. Financial fragility: fire sales, cash-in-the-market pricing.

  4. Capital and Liquidity regulation: the Basel III framework.

  5. Shadow banking: the Gennaioli-Shleifer-Vishny model.

  6. Introduction to banking under asymmetric information: the impact of transparency and regulatory disclosure policies on financial fragility.

  Coefficient : 2

  Learning outcomes :

  Maîtriser les outils de base de modélisation moderne en Banque. Comprendre comment ces outils permettent de comprendre les problèmes bancaires traditionnels, ainsi que ceux plus récents (shadow banking, arbitrage règlementaire). Comprendre le rôle de la régulation dans la résolution de ces problèmes, tant son aspect "bilan" (Basel III), que "informationnel" (e.g. divulgation des résultats de stress-tests).

• Individual and collective decisions

  Individual and collective decisions

  Ects : 3

  Lecturer :
  JEAN-PHILIPPE LEFORT
  

  Total hours : 15

  Coefficient : 2

Specialization field: Social and Public Policies

• Advanced Health economics

  Advanced Health economics

  Ects : 3

  Lecturer :
  BRIGITTE DORMONT
  

  Total hours : 21

  Coefficient : 2
• Policies in developing countries

  Policies in developing countries

  Ects : 3

  Lecturer :
  OLIVIA BERTELLI
  

  Total hours : 18

  Coefficient : 2

Specialization field: Macro & Finance

• Banking economics

  Banking economics

  Ects : 3

  Lecturer :
  SYLVAIN CARRE
  

  Total hours : 18

  Overview :

  1. Basic concepts in banking economics. The Diamond-Dybvig model. Financial instability issues: bank runs and bank panics.

  2. Solutions to financial instability. Ex-ante and ex-post liquidity provision. Interbank markets, lender of last resort. Deposit insurance and moral hazard.

  3. Financial fragility: fire sales, cash-in-the-market pricing.

  4. Capital and Liquidity regulation: the Basel III framework.

  5. Shadow banking: the Gennaioli-Shleifer-Vishny model.

  6. Introduction to banking under asymmetric information: the impact of transparency and regulatory disclosure policies on financial fragility.

  Coefficient : 2

  Learning outcomes :

  Maîtriser les outils de base de modélisation moderne en Banque. Comprendre comment ces outils permettent de comprendre les problèmes bancaires traditionnels, ainsi que ceux plus récents (shadow banking, arbitrage règlementaire). Comprendre le rôle de la régulation dans la résolution de ces problèmes, tant son aspect "bilan" (Basel III), que "informationnel" (e.g. divulgation des résultats de stress-tests).

• Advanced environmental macroeconomics

  Advanced environmental macroeconomics

  Ects : 3

  Lecturer :
  GAUTHIER VERMANDEL
  

  Total hours : 15

  Coefficient : 2