M1 Economics

The purpose of the Boot Camp is to install software’s that will be used during the master and to initiate students to the basics of their use.
The goal is to train students' computational skills throughout the two years of the master's degree to participate in cutting-edge economic research and public policy analysis.

Septembre.

GIF-SUR-YVETTE

Michael Greinecker (ENS Paris-Saclay).

There will be homework problems counting for 40%, and two exams counting for 30% each.

This course introduces fundamental mathematical methods of use in economics and Econometrics. There will be a focus on basic (point-set) topology (mostly in Eulidean Spaces), basic convex analysis, nonlinear unconstrained and constrained optimization, and an outlook on dynamic optimization methods.

Learning Outcomes
Participants will be able to solve optimization problems and read technical literature involving such problems and related formal methods.

Indicative Contents
Repetition of the essentials of real analysis on the real line. Extending to Euclidean spaces and basic topology via norms and metrics there, including continuity, compactness, completeness, and related concepts. Then we look at some convex analysis, including separation and support theorems. Abstract formulation of convex optimization problems. Then we relate these methods to multidimensional calculus methods and look in some details at Lagrange and Karush-Kuhn-Tucker methods for constrained optimization methods with equality and inequality constraints, respectively. Versions of the envelope theorem for the behavior of solutions to parametric optimization problems. We then look at the principle of dynamic programming with a bit more metric space theory to understand discretete time infinite horizon recursive optimization. Finally, we survey informally several methods to solve dynamic optimization problems in discrete time.

Lecture Notes will be made available before each unit.

Supplementary Readings Sundaram, Rangarajan K. A first course in optimization theory. Cambridge University Press, 1996. - This book is a good general reference for much of what we do in this course. Sadly, there are a lot of typos. Dixit, Avinash K. Optimization in economic theory. Oxford University Press on Demand, 1990. - This book provides a lot of economic intuition for optimization methods but not much formal details. Stokey, Nancy L., Robert E. Lucas JR., with Edward C. Prescott, Recursive methods in economic dynamics. Harvard

Morgan Patty (ENS).

The course is organized around 5 classes of 3 hours and 4 tutorials of 1.5 hours. 1. Introduction and reminders about matrices 2. Useful properties of matrices 3. Matrix tools for optimization (use of Hessian matrix, etc.) 4. Computing linear and non-linear systems (linear and non-linear equations) 5. Stability conditions (phase diagrams, joint spectral radius, etc.).

One final exam.

This course introduces students to the basic linear algebra necessary to understand the operations regarding derivatives of functions with more than one variable to investigate maximum and minimum values of those functions with economic applications in mind. Students will also see how to solve linear and non-linear systems and then how to turn them into problems involving matrices. Finally, they will discover stability conditions of linear and non-linear systems.

Hoy, M., Livernois, J., McKenna, C., Rees, R., Stengos, T., 2011. Mathematics for Economics - 3rd Edition. MIT Press. Aleskerov, F., Ersel, H., Piontkovski, D., 2011. Linear Algebra for Economists. Springer-Verlag Berlin. Bernstein, D.S., 2018. Scalar, Vector and Matrix Mathematics: Theory, Facts, and Formulas - Revised and Expanded Edition. Princeton University Press. Horn, R.A., Johnson, C.R., 2013. Matrix Analysis - 2nd Edition, Cambridge University Press.

Olivier Bos (ENS Paris-Saclay).

Grade are based on a midterm (1/3) and a final test (2/3).

This course aims introducing substantial theoretical concepts and tools to be able to formalize and analyze strategic interactions in macro and microeconomics, and beyond to read theoretical and applied scholar articles on decision theory and game theory. Decision theory studies choices that result in either risky or uncertain outcomes, while game theory is the analysis of strategic interactions between rational agents. Both are dynamic fields, with substantial developments and numerous applications in economics (bargaining, taxation, industrial organization), political sciences (voting, government stability, climate policy), philosophy (social norms), biology (evolution, cooperative/aggressive behavior), computer science…
Students are expected to have a background knowledge in mathematics (analysis, optimization, probability).

The course is organized around 12 main classes of 3 hours, 8 tutorials of 1.5 hours.
Part I: Decision theory
1. Preferences and choice
preference properties — continuity of preferences — existence of utility function — Utility maximization.
2. Demand Theory
Walrasian Demand — Hicksian Demand — compensated law of demand — Slutsky equation — Roy’s identity
3. Choice under risk
preferences over lotteries — Von Neumann-Morgersten’s theorem — Allais paradox — rank dependent utility model
4. Increasing risk: comparison and measures
risk aversion — measures of risk aversion — stochastic dominance
Part II: Game theory
1. Static games of complete information
strategic form — dominance — Nash equilibrium — mixed strategies — equilibrium existence — correlated equilibrium — equilibrium selection and refinements
2. Dynamic games of complete information
extensive form, subgame-perfection, backwards induction, repeated games
3. Static games of incomplete information
beliefs — Bayesian Nash equilibrium — common knowledge — global games
4. Dynamic games incomplete information
incomplete vs. imperfect information — perfect bayesian Nash equilibrium — signaling games.

Gibbons, R. Game Theory for Applied Economists. Princeton: Princeton University Press, 1992. Mas Colell, A., Whinston, M.D. & Green, J.R. Microeconomic Theory, Chapters 1 & 6, Oxford University Press, 1995. Maschler, M., Solan, E. & Zamir, S. Game theory, Cambridge university press, 2013. Osborne, M.J. & Rubinstein, A. A Course in Game Theory. Cambridge, Massachusetts: MIT Press, 1994.

Septembre - Octobre.

GIF-SUR-YVETTE

Gregory Verdugo, Université Paris Saclay, Evry.

Part 1 Cross-section and Panel data econometrics Chapter 1 Introduction to the linear model Definition Frisch-Waugh theorem Variance decomposition Statistical Properties: bias, variance Confidence interval Hypothesis testing Consistency of the OLS estimator Generalized least squares estimator Chapter 2 Instrumental variable estimator Omitted variable bias analysis The instrumental variable estimator Chapter 3 Linear panel models Notation Pooled OLS estimation Between estimator Fixed effects or within estimator Consistency of within estimator Asymptotic distribution of within estimator Matrix derivation First differences estimator Asymptotic distribution of the first-difference operator Random effect model Chapter 4 Dynamic panel data True state dependence and unobserved heterogeneity Inconsistency of standard panel estimators Arellano-Bond estimator Part 2 Time series econometrics Chapter 1 What is a time series? White noise ARMA models Lag operators and polynomials Manipulating ARMA with lag operators AR(1) to MA() AR(p) to MA(): factoring lag polynomials Multivariate ARMA models Chapter 2 Autocovariance and autocorrelation functions Definitions Autocovariances ant autocorrelations of ARMA processes Yule-Walker equations Multivariate auto- and cross-correlations Partial autocorrelation function Chapter 3 Prediction and Impulse Response Functions Predicting ARMA models Forecasting MA models AR and ARMA models State space representation Forecast from AR(1) representation VARs in vector AR(1) representation Impulse response function Ecole Normale Supérieure Paris-Saclay, CEPS, DER SHS, 4 avenue des sciences, 91190 Gif-sur-Yvette, France Chapter 4 Stationarity Definition: weak and strong stationarity Conditions for stationarity in ARMA Chapter 5 Estimating autoregressions Estimation of an AR(1) Estimation of an AR(p) Choice of the lag length Estimation of VARs Estimation of ARMA(p,q) Chapter 6 Seasonality and Structural changes Seasonality Structural change Chow tests Dummy variables Chapter 7 Models with trend Random walk models Random walk plus drift models Removing the trend: differencing Removing the trend: detrending Dickey-Fuller tests

Final written exam: 80% Project in econometrics: 20%.

The first part of the course presents the basic tools of the econometric analysis of cross-section and panel data. The first chapter presents the linear regression model and the properties of the OLS estimator. The second chapter presents the instrumental variable estimator. The third chapter introduces panel data econometrics. We will also describe static and dynamic panel data analysis techniques that are useful for the analysis of longitudinal datasets.
The second part of the course studies the theory and application of time series methods that are frequently used in macroeconomics and financial econometrics.
For each chapter, we will present recent applications of these techniques from the academic literature in economics. A separate list of applied papers will be provided and some of them will be discussed in class.

• Probability and Statistics (L3)

• Introductory Econometrics (L3).

Cross-section and Panel data econometrics Cameron, A. Colin, and Pravin K. Trivedi. Microeconometrics: methods and applications. Cambridge University Press, 2005. Time series Cochrane, J. H. (2005). Time series for macroeconomics and finance. Manuscript, University of Chicago, 1-136. Version Spring 1997; Pictures added Jan 2005 http://econ.lse.ac.uk/staff/wdenhaan/teach/cochrane.pdf Enders, Walter, (2015), Applied econometric time series, Fourth edition, Wiley Software used during tutorials and for the project: R language https://www.r-project.org/ Online references on R: https://cran.r

Septembre - Octobre - Novembre - Décembre.

GIF-SUR-YVETTE

José De Sousa and Matthieu Crozet.

Grades are based on tutorials (25%) and a final exam (75%).

Brief Course Description

This course will provide students with the analytical tools that are essential to understand the process of globalization through the international trade in goods. The lecture focuses on topics that are at the center of the policy debate: why do countries open to trade? What are the gains from trade? What are the distributional impacts of trade between and within countries?

Learning Outcomes

At the end of the course, students are expected to have a good knowledge of the mechanisms and predictions from the traditional models of trade, and from modern trade theories. Students will also be able to read research articles that can be used for the writing of policy notes.

Course Outline (indicative)
Session 1: Trade in the Global Economy
● Defining and measuring globalization
● Broad facts
● Globalization a new phenomenon?
Sessions 2-4: Comparative Advantage and Trade
● Technological differences: The Ricardian model of Trade
● The revival of Ricardo: Eaton and Kortum
● Testing the Ricardian Model
Sessions 5-6: Monopolistic Competition and Trade
● A refresher on monopolistic competition
● Monopolistic competition and trade with homogeneous firms
● Monopolistic competition and trade with heterogeneous firms
● The empirics of firm-level trade
Session 7: The Law of Gravity
● Do the data obey the law of gravity?
● Micro-foundations for the gravity equation
● Applications
Session 8: Quality and trade
● Trade and quality
● Firms’ selection across markets
Session 9-10: Trade and the labor market
● HOV
● Impact of trade on wages and employment
Session 11: Trade policy
● Impact of tariffs, optimal tariffs and pass-through
● Quantifying the trade gains (and loses)
Session 12: Trade elasticities and pass-through
● Models of trade with endogenous markups
● Estimating the trade elasticities and pass-through.

The material covered is not mathematically complex, but it is taught in a formal and rigorous manner, which assumes a good familiarity with basic economic concepts.

Required/Essential Readings

• Feenstra (2009). Advanced International Trade: Theory and Evidence. Princeton University Press. (F) • Combes P.P, Mayer T. and J., Thisse (2008) Economic Geography, Princeton University Press. (CMT).

Recommended/Supplementary Readings Arkolakis, C. (2010), “Market Penetration Costs and the New Consumers Margin in International Trade”, Journal of Political Economy, 118:6. Bernard, A., B. Jensen, S. Redding, and P. Schott (2012), “The Empirics of Firm Heterogeneity and International Trade”, Annual Review of Economics, 4. Blaum, J., C. Lelarge, and M. Peters (2018),

Septembre - Octobre - Novembre - Décembre.

GIF-SUR-YVETTE

Thomas VENDRYES University/ENS Paris-Saclay, CEPS.

1. The Phenomenon of Economic Development 2. Classic Theories and Contemporary Approaches 3. Health and Education 4. Institutions

Written exam at the end of the semester (2hours).

The objective of this course is to provide a presentation of the phenomenon of economic development, and an introduction to development economics. After a general depiction of the process of development, the main theories and schools of thought that structured the related research field are presented. Specific topics are then studied, through classical or contemporary research papers: on the micro side, health and education, and on the macro side, institutions. In all cases, both theoretical approaches and empirical methods will be presented.

For this course, students will need a good mastery of the basic, L3-level, concepts and mechanisms of economic theory and econometrics.

Banerjee & Duflo, Poor Economics, Public Affairs, 2011. de Janvry & Sadoulet, Development Economics - Theory and practice, Routledge, 2016. Perkins, Radelet, Lindauer & Block, Economics of Development (7th ed.), Norton, 2012.

During lectures, specific papers will be presented and discussed, and supplementary readings provided.

Septembre - Octobre - Novembre - Décembre.

GIF-SUR-YVETTE

Pannequin François, ENS Paris-Saclay.

Written report (based on an article and/or an experiment design), possibly in pairs.

Course Overview: This course provides an introduction to experimental economics. The emphasis will be on the methodology of experimental economics, its relevance to testing economic predictions, and identifying patterns of behaviors. Students will learn how to design experiments and interpret their results. Participation in classroom games will help perfect the understanding of experimental methods.
The course is designed in four parts to favor the practice of experimental economics. The first part is dedicated to the understanding of the experimental method. The second focuses on some fundamental experimental methods to provide behavioral measures. The third part explores the field of social preferences (altruism, trust, reciprocity). The last part is devoted to statistical and econometric methods implemented to exploit experimental data.

Course Outline :
1. Experimental Economics: Principles and Methodology Introduction: Why an experimental approach?
Methodological foundations of experimental economics Rules and procedures in Experimental Design Classroom Experiment: the Voluntary Contributions Game
2. Other-Regarding Preferences
Ultimatum Game
Dictator Game
Trust Game
Gift Exchange Game
3. Decision Theory: Risk Aversion, Ambiguity Aversion, Beliefs The Holt & Laury measure Investment Task Measures
The Bomb Task
Beliefs’ Elicitation and Bayesian Learning
Probability weighting and Prospect Theory
Ambiguity Aversion
4. Auctions
Private value auction
The Winner’s Curse.

Bachelor’s degree in Economics.

• Bardsley N, et al. (2010), Experimental Economics: Rethinking the rules, Princeton University Press. • Dhami S (2016), The Foundations of Behavioral Economic Analysis, Oxford. • Guala F (2005), The methodology of experimental economics, Cambridge: Cambridge University Press. • Holt CA (2019), Markets, Games, and Strategic Behavior: An Introduction to Experimental Economics, Princeton University Press. • Jacquemet N, L’Haridon O, (2018), Experimental Economics: Method and applications, Cambridge: Cambridge University Press. • Kahneman D (2012), Thinking, Fast and Slow, Penguin.

Septembre - Octobre - Novembre.

GIF-SUR-YVETTE

Jérôme Héricourt, UEVE Jean-Noël Senne, Université Paris Saclay.

The grade will be based on 3 elements: • A written exam (50 %) • A presentation of an academic paper during lectures (20 %) • Questionnaires during TD sessions (30 %).

This course is the natural extension of the Intermediate Econometrics course taught in the first semester. It is divided into two blocks (each block being organized in 6 sessions of 3 hours each).
The first block (18h) studies the basic techniques of non-linear econometrics including:
• Lecture 1: Nonlinear Least Squares, Nonlinear 2SLS, and Iterative methods (Newton and Quasi-Newton).
• Lecture 2: Maximum Likelihood estimator.
• Lecture 3: Generalized Method of Moments estimator and binomial outcome models.
• Lecture 4: Discrete choice models: multinomial outcome models.
• Lecture 5: Censored and Truncated; Sample Selection Models.
• Lecture 6: Paper presentations

The second block (18H) presents recent developments in the microeconomic analysis of impact evaluation. This course will explore a wide variety of techniques, such as:
• Lecture 1: Randomized Controlled Experiments (RCT)
• Lecture 2: Advanced Instrumental Variables (IV)
• Lecture 3: Matching Methods (MM)
• Lecture 4: Regression discontinuity (RDD)
• Lecture 5: Difference-in-Differences (DID)
• Lecture 6: Paper presentations
focusing not only on the estimators themselves and why they work, but also on the types of data they require and the assumptions that must hold for the estimates to be valid.
To complement their theoretical knowledge, students will also attend practical econometrics classes (12H).

• Angrist, J. D., & Pischke, J. S. (2009). Mostly harmless econometrics: An empiricist's companion. Princeton university press. • Cameron, A. C., & Trivedi, P. K. (2005). Microeconometrics: methods and applications. Cambridge university press. • Davidson, R., & MacKinnon, J. G. (2004). Econometric theory and methods (Vol. 5). New York: Oxford University Press. • Greene, W. H. (2012). Econometric Analysis 7th ed. Pearson. • Wooldridge, J. M. (2010). Econometric analysis of cross section and panel data. MIT press.

Janvier - Février - Mars - Avril.

GIF-SUR-YVETTE

Vincent Martinet (INRAE and ENS Paris-Saclay).

The course is organized around 6 main classes of 3 hours 1. Introduction to the topic 2. Intertemporal optimization in discrete time 3. Dynamic programming and time-consistency 4. Optimal control in continuous time: basics 5. Optimal control: advanced considerations (constrained problems, infinite horizon, etc.) and particular features (discontinuous controls, bang-bang solutions, etc.) 6. Alternatives to the discounted utility model and a short introduction to viability theory along with 4 tutorials of 1.5 hours a. The cake-eating economy in discrete time b. Dynamic programming in practice c. The cake-eating economy in continuous time d. The simple fishery problem

Evaluation is based on a final written exam.

This course aims at introducing the main tools used to model the dynamic aspects of economic problems. It addresses “fundamental methods,” with an emphasize on mathematical aspects and the way to interpret them in economic terms. As such, the course is not about dynamic economics and its results; it will not go deep into a specific topic, e.g., macroeconomic dynamics, but aims at providing the knowledge needed to address any topic from a dynamic perspective. In particular, the course discusses intertemporal equilibria analysis, dynamic programming, and optimal control. It focuses on so-called mechanistic models, i.e., models in which the economy evolves according to some explicit rules. As such, we will not consider statistical approaches or dynamic econometrics.
Students are expected to have a sufficient background in economics (microeconomics,
macroeconomics - comparative statics, decision theory, social choice theory) and in mathematics (static optimization, advanced calculus).

Economic Modelling 1 Decision, Coordination, Social Optimality.

Léonard D. and Long N.V. (1992) Optimal control theory and static optimization in economics. Cambridge University Press. Seierstad A. and Sydsæter K (1987) Optimal Control Theory with Economic Applications. North-Holland, Advanced textbooks in economics (Volume 24). Takayama A. (1974) Mathematical Economics. The Dryden Press: Hinsdale, Illinois.

Supplementary Readings To be displayed during the course.

Janvier - Février - Mars - Avril.

GIF-SUR-YVETTE

François Pannequin and Morgan Patty.

Grades are based on a midterm (50%) and a final test (50%).

This course aims at providing the theoretical tools to understand the main issues of industrial organization, competition policy and asymmetric information.

Course Outline
I. Industrial Organization
a. Perfect Competition (Partial Equilibrium Analysis),
b. Monopoly (Lerner Index, Price Discrimination, Ramsey’s Rule),
c. Simultaneous Oligopoly (Bertrand, Cournot),
d. Non-Simultaneous Oligopoly (Stackelberg, Partial Monopoly)
e. Product differentiation (Hotelling)
f. Pricing strategies
g. Theory of competition policy (tacit collusion, mergers, entry deterrence)
II. Asymmetric information
a. Hidden information (including the revelation principle)
b. Case study: insurance markets
c. Hidden action
d. Advertising
e. Warranties
f. Branding
g. Bundling
III. Incomplete contracts
a. From Complete to Incomplete Contracts
b. Firm Theory
c. The Hold Up Problem
d. The Offer Game (Public and Private Contracts).

Bolton, P., Dewatripont, M., 2005. Contract Theory. MIT Press. Pindyck, R.S., Rubbinfield, D.L., 2013. Microeconomics - 8th Edition. Pearson. Salanié, B., 2005. The Economics of Contracts, A Primer - 2nd Edition. MIT Press. Tirole, J., 1994. The Theory of Industrial Organization. MIT Press.

Janvier;Février;Mars;Avril.

GIF-SUR-YVETTE

Michel GUILLARD (Université d’Évry-Val-d’Essonne & Université Paris-Saclay).

1. Money and Public Finance (a) The household program in a monetary economy (b) The Treasury, the central bank and the government budget constraint (c) Equilibrium and the Ricardian equivalence 2. The Flexible Price Equilibrium (a) The flexible price model (b) The real equilibrium (c) Monetary equilibra 3. Foundations of the New Keynesian Model (a) The household program in a multiple goods economy (b) The firms program: Imperfect competition and nominal rigidities (c) Equilibrium and properties of the simple “3-equation model” 4. Fiscal and Monetary Policy in the NK Model (a) Fiscal Policy in “normal time” and in exceptional time (b) Rules vs discretion: the credibility problem of the central bank (c) Monetary and Fiscal policy in practice

Tutorials preparation, in-class tests, and class participation (30%) Final exam (70%).

The objective of this course is to present to students the theoretical foundations of the workhorse short-term macroeconomic model (the so-called "3-equation New Keynesian model") and its implications for economic policy.
It builds on the methodological background of the course “Macroeconomics 1: Theory and Applications”, using a simplified version of the RBC model, without capital accumulation, in order to introduce money, competition imperfections and micro-founded nominal rigidities.
This framework is then used to study the effects and usefulness of monetary and fiscal policies in response to different macroeconomic shocks (financial, energy, climate, etc.).

The main source of material for this course will be the lecture notes (on eCampus) CHALLES, EDOUARD (2019), Macroeconomic Fluctuations and Policies, MIT Press. CHUGH, SANJAY (2015), Modern Macroeconomics, MIT Press. GALÍ, JORDI (2015). Monetary Policy, Inflation, and the Business Cycle: An Introduction to the New Keynesian Framework, Second Edition, Princeton University Press. Main reference. ROMER, DAVID (2019). Advanced Macroeconomics, Fifth Edition, McGraw Hill. WALSH, CARL (2010). Monetary Theory and Policy, The MIT Press Cambridge, Massachusetts, London. WICKENS, MICHAEL (2012)

Natacha Raffin (CEPS).

1. Public spending and State formation 2. Wealth inequality 3. Introduction to optimal taxation 4. Labor income taxation and redistribution 5. Capital taxation 6. Public goods and externalities 7. Introduction to Social choice

To validate the course, students are required to attend all lectures and actively participate in class and to take the exams: One mid-term exam during tutorials and a final exam.

The objective of this course is to present an introduction to public economics, with
special emphasis on public spending, normative theories of government intervention
and redistribution, taxation and transfer policies, social preferences.

This course is based on a solid microeconomic background. A great source which starts with the basics is:

• Varian, H. R. Microeconomic Analysis, Norton, New York, 3rd edition.

• Varian, H. R. Intermediate Microeconomic : a modern approach, Norton, New York, 7th edition.

• This course is mathematically intensive, it is worth reviewing secondary school mathematics for a good mastering of the course.

Those references below are recommended readings. Atkinson, A.B. and J. Stiglitz, Lectures on Public Economics, New York: McGraw Hill, 1980. [New edition Princeton University Press, 2015] Auerbach, A. and M. Feldstein, eds., Handbook of Public Economics, 4 Volumes, Amsterdam: North Holland, 1985, 1987, 2002, and 2002. Gruber, J. Public Finance and Public Policy, 6th Edition. New York: Worth Publisher, 2019. Kaplow, L. The Theory of Taxation and Public Economics. Princeton University Press, 2008. Mirrlees, J. Reforming the Tax System for the 21st Century The Mirrlees Review, Oxford University

Janvier - Février - Mars - Avril.

GIF-SUR-YVETTE

Xiangyu QU (CNRS).

1. The industrialization of Knowledge production: to investigate changes in knowledge production, we consider a parallel approach as in tranditional industrialization, replacing capital with data. 2. Data as fuel for growth: to investigate if data accumulation is an engine of growth as well as capital, labor and technology. 3. Data, firm size and investors’ changing trading strategies: to understand if data contribute to big firms more. 4. Measuring and Valuing Data in Market Prices: to understand how much data is in the market and what is its value. 5. Data Platforms: Lots of data is collected by intermediaries who creat the transaction data, like amazon, alibaba. We will study the platform strategies and competition.

Evaluation/Assessment : Project or written exam.

A growing number of companies derive most of their value not from physical assets, but from intangibles ones, like data. Data and new data technologies are changing consumption, production, labor and valuation. Does this transformation from an industrial economy to a data economy bring with it new economics? Is the accumulation of data contributing to big firms getting bigger ? Can changes in data technology explain some of the decline in the labor share? How should we measure or value data when it is often traded at zero price, bartered for a user’s access to a digital service? Finally, can the accumulation of data be an engine of growth? This course deploys information economics tools to understand the data economy, derives new approaches to measuring data and develops a standard economic framework that can be used for data policy evaluation.

1. “The Changing Economics of Knowledge Production”, Simona Abis and Laura Veldkamp, Working paper. 2. “Impact of Artificial Intelligence on the Labor Market”, Michael Webb, Working paper 3. “A growth model of the data economy”, Maryam Farboodi and Laura Veldkamp, Working paper. 4. “Th race between man and machine: Implications of technology for growth, factor shares and employment”, Daron Acemoglu and Pascual Restrepo, Amercian Economic Review 108(6): 1488-1542. 5. “Robots and jobs: Evidence from US labor markets, Daron Acemoglu and Pascual Restreepo, Journal of Political Economy 128(6): 2188

Janvier - Février - Mars - Avril.

GIF-SUR-YVETTE

Caroline ORSET, Associate Professor, AgroParisTech-Université Paris-Saclay.

1. Introduction Property Rights, Externalities, and Environmental Problems 2. Course 2 Imperfect market structures and Coase theorem Introduction to Benefit-Cost analysis 3. Course 3 Decision making criteria 4. Course 4 Dynamic Efficiency and Sustainable Development Efficient intertemporal allocation 5. Course 5 Energy and mineral markets 6. Course 6 Water and land markets and pollution 7. Course 7 Forest and fisheries markets 8. Course 8 Economics of Pollution Control Population growth and economic growth 9. Course 9 Climate Change and poverty 10. Course 10 The Quest for Sustainable Development Animal welfare economics

Dissertation and oral presentation on a topic of the course.

The course provides students with the skills to assess, analyze and recommend economic policies and strategies to tackle environmental issues such as pollution, climate change, renewable energy, and biodiversity conservation.
More specifically, we will study the effectiveness of incentive tools for public decision-makers intended to improve environmental quality and promote sustainable development (Pigovian tax, emission rights trading systems, nudges, etc.), or on their social acceptability. Then, we will analyze firms' green business strategies such as their investments in cleaner technologies (innovation), product labeling or socially responsible investments to improve their competitiveness while respecting the environment. Finally, we will discuss how firms (industrial lobby) and influence groups (NGOs, consumer lobby) can influence environmental economic policies and human behavior and the consequences on biodiversity, ecosystems, and animal welfare.

None.

1. Buchholz, W., Rubbelke, D. (2019). Foundations of environmental economics. 2. Harris, J.M., Roach, B. (2018). Environmental and natural resource economics-a contemporary approach. 4e edition. 3. Mariel, P. et al. (2021). Environmental valuation with discrete choice experiments – Guidance on design, implementation, and data analysis. 4. Nakayama, K., Miyata, Y. (2019). Theoretical and empirical analysis in environmental economics. 5. Tietenberg, T., Lewis, L. (2018). Environmental and natural resource economics, 11th edition.

Supplementary Readings 1. David J. Lewis, David M. Kling, Steven J

GIF-SUR-YVETTE

José De Sousa, Université Paris-Saclay.

Grading is based on a research project on gender and discrimination or/and a referee report on suggested papers.

This course uses basic microeconomic theory and recent empirical studies to examine the causes and consequences of gender and racial differences in economic outcomes. Topics covered include the labor force participation choices, the gender gap in earnings, occupational choices, fertility decisions, and human capital investment.

Course Outline
1. Definitions, Broad Facts, and Road Map for the Course
2. Divergent Paths
3. Taste-Based Discrimination
4. Orchestrating Impartiality
5. Statistical Discrimination
6. The Gender Earnings Gap in the Economy and the Gig Economy
7. Do Quotas Work?
8. Algorithmic Bias.

 Blau F.D. & L.M. Kahn. 2017. "The Gender-Wage Gap: Extent, Trends, and Explanations". Journal of Economic Literature 55(3), 789–86.  Cook C., Diamond R., Hall J., List J., and &. Oyer, 2021, The Gender Pay Gap in the Gig Economy: Evidence from over a Million Uber Drivers, Review of Economic Studies, 88(5), 2210–2238.  Goldin C. & C. Rouse. 2000. "Orchestrating impartiality: The impact of “blind” auditions on female musicians". American Economic Review, 90(4) 715–741.  Goldin C. Career & Family: Women's Century-Long Journey toward Equity. Princeton NJ: Princeton University Press; 2021.

Sup

Janvier - Février - Mars - Avril.

GIF-SUR-YVETTE

All potential faculty members teaching in the Master.

To be annonced.

Write a literature review that takes stock on the state and limitations of knowledge within a specific domain at the frontier of research.

Novembre - Décembre - Janvier - Février.

GIF-SUR-YVETTE

Students will be required to work in groups of 2 or 3 to apply standard statistical and econometric methods to real data sets, write a short essay and deliver their main results in an oral presentation.

Décembre - Janvier - Février - Mars - Avril.

GIF-SUR-YVETTE