• Course title: Mathematics and Statistics for Economics and Finance (Maths Camp)
• Number of ECTS: 6
• Course code: QTECOFIN-1
• Module(s): Module 1
• Language: EN
• Mandatory: Yes

• Understand basic mathematics such as Linear Algebra, and elements of multivariable calculus;• Understand and apply techniques of convex static optimization, dynamic-programming techniques in both discrete and continuous time, and solve systems of difference and differential equations; • Understand Brownian-motion analysis, stochastic difference equations, barriers and smooth pasting for valuation;• Understand random variables, properties of conditional distributions and conditional expectations and how they can be used in probability calculations, multivariate Gaussian random vectors and their properties, basic asymptotic theory including the law of large numbers and the central limit theorem, and the methods of statistical inference, i.e., hypothesis testing and confidence intervals, based on large sample approximations.

Mathematical and statistical methods are central to economics and finance. Economic analysis relies on modelling, which builds upon optimization theory. A thorough analysis of convex optimization in both static and dynamic models is a prerequisite for building and understanding economic models. Most important is optimization under uncertainty, which studies how individuals or firms make decisions in environments with random outcomes and how they cope with uncertainty. Econometric methods are required to quantify the insights gained from economic analysis so that they can help in the formulation of economic policy. The objective of t his course is to teach students the essential mathematics and statistics that is necessary for them to take higher level courses in economics and finance and pursue their research.

 60% of the course grade is based on the final exam, which is closed book and closed notes. The final exam is comprehensive, i.e., it includes all material covered in the class and the homeworks,. The Math and Stat exams (and homeworks) are graded separately. The final grade for the course is the average of the Math and Stat grades40% of the course grade is based on homework assignments (4 Math + 5 Stat). The completed homeworks have to be handwritten and handed in individually 

Bibliography:The required texts for this course are:• Further Mathematics for Economic Analysis (1st or 2nd Edition, 2005 and 2008 resp.) , by Knut Sydsaeter, Peter Hammond, Atle Seierstad, and Arne Strom, FT Prentice Hall. • Probability and Statistics, 4th ed., by Morris DeGroot and Mark Schervish (2012). Chapters 1 – 4 of the text contain a useful summary of the probability prerequisites. All students are required to review this material before coming to class.

• Course title: Advanced Microeconomics
• Number of ECTS: 6
• Course code: QTECOFIN-3
• Module(s): Module 1
• Language: EN
• Mandatory: Yes

Students, who successfully pass this course, will be able to analyze and assess scientific publications in the area of modern Microeconomics. Moreover, they should be sufficiently familiar with modern methodological concepts to apply them in their own research.

 

On completion of the course unit successful students will be able to:

• Analyze and assess scientific publications in the area of modern Microeconomics• Familiarity with modern methodological concepts and ability to apply them in their own research • Reconstruct fundamental game theory models and clearly state their assumptions and predictions and work out the analysis• Convert a standard multi-person decision situation into an analytic model and correctly analyze it• Apply and explain appropriate models or modifications to some real-world issues and work out its policy implications.

 

This course is split up into two parts of equal length. Part I provides an advanced treatment of core topics of modern Microeconomics. We start with Consumer Theory and the Theory of the Firm. Then, we proceed with Partial and (a glimpse of) General Equilibrium Analysis both from a positive and from a normative point of view (Welfare Analysis). Throughout, we emphasize the role of general equilibrium theory as the foundation of modern Microeconomics, Macroeconomics, and Financial Economics.Part II deals with Game Theory. Game theory is a powerful tool for analyzing strategic interactions between players or decision-making units. This course develops an advanced treatment of non-cooperative game theory. Students are introduced to the concepts of game theory and to various methods for solving interactive decision problems. These concepts are applied to Economics and Finance, to firm behavior in markets and different types of market structures. Applications include market competition, auctions, research and development, labor markets, bargaining,  and economic influence, to name a few.

80% written exam20% assignments/homework

Bibliography

The contents of Part I is comprehensively covered in Chapters 1-6 and 10 of the book Microeconomic Theory by Mas-Colell, Whinston, and Green (1995). This book is the ultimate reference of this course.The course will also rely on the book Advanced Microeconomic Theory, 3rd edition, by Jehle and Reny (2011). In its Chapters 1-5 the latter provides a very good summary of the relevant chapters of the bookby Mas-Colell, Whinston, and Green. In addition, there will be handouts. Highly recommended alternative textbooks include the following. A classic reference for graduatecourses in Microeconomics is Hal Varian’s Microeconomic Analysis (Varian (1992)). A very elegant treatment of the main topics of this course can be found in Ariel Rubinstein’s Lecture Notes in Microeconomic Theory – The Economic Agent (Rubinstein (2012). This book can be (legally!) downloaded from the author’s web page. Finally, David Kreps’ recent textbook Microeconomic Foundations – Choice and Competitive Markets (Kreps (2013)) is highly recommended. To brush up your knowledge in Microeconomics, have a look at Intermediate Microeconomics: A Modern Approach by Varian (2010) or Microeconomics by Pindyck and Rubinfeld (2009). Part II follows closely Chapters 7-9 of the book Microeconomic Theory by Mas-Colell, Whinston, and Green (1995).Textbooks on Mathematical Methods: a deeper understanding of the mathematical tools applied in this course may require more than what is covered in a mathematical appendix of a textbook. Simon andBlume (1994), Mathematics for Economists, covers a wide range of relevant topics. Dixit (1990), Optimization in Economic Theory, and Sundaram (1996), A First Course in Optimization Theory, provide a sound introduction to optimization theory. Introductory treatments of some relevant concepts may befound in Sydsæter and Hammond (1995), Mathematics for Economic Analysis or in FundamentalMethods of Mathematical Economics by Chiang (1984). Sydsæter, Strøm, and Berck (2005), Economists’ Mathematical Manual, has a comprehensive collection of useful results and formulae. Issues of mathematical logic and proofs are comprehensively presented in How to Prove It – A Structured Approach by Velleman (2006).

• Course title: Advanced Macroeconomics
• Number of ECTS: 6
• Course code: QTECOFIN-5
• Module(s): Module 1
• Language: EN
• Mandatory: Yes

Part I introduces students to the modern theory of economic growth that studies long-run macroeconomic evolutions. It starts with an empirical look at the growth experience of today’s industrialized countries. Then, the focus will be on theories that explain these evolutions emphasizing the accumulation of physical capital, human capital, and technological knowledge. Throughout, we highlight the role of inter-temporal general equilibrium theory as the conceptual foundation of modern growth theory.

Part II focuses on stochastic dynamic general equilibrium models to study short run macroeconomic phenomena and economic policy issues. This calls for a good understanding of dynamic optimization problems, dynamic general equilibrium concepts, analytical and/or numerical solution methods. The course covers the benchmark Real Business Cycle Model as well as extensions with labor, capital and goods market frictions. It also considers monetary policy through the lens of the New-Keynesian Model. It includes economic policy simulations. References are recent relevant scientific publications.

 

On completion of the course unit successful students will be able to:

•    Explain and apply the methods of modern macroeconomic theory. The emphasis is on the use of dynamic general equilibrium models to study short run macroeconomic phenomena and economic policy issues. This calls for a good understanding of dynamic optimization problems, dynamic general equilibrium concepts, analytical and/or numerical solution methods.

Part I introduces students to the modern theory of economic growth that studies long-run macroeconomic evolutions. It starts with an empirical look at the growth experience of today’s industrialized countries. Then, the focus will be on theories that explain these evolutions emphasizing the accumulation of physical capital, human capital, and technological knowledge. Throughout, we highlight the role of inter-temporal general equilibrium theory as the conceptual foundation of modern growth theory.  Part II focuses on stochastic dynamic general equilibrium models to study short run macroeconomic phenomena and economic policy issues. This calls for a good understanding of dynamic optimization problems, dynamic general equilibrium concepts, analytical and/or numerical solution methods. The course covers the benchmark Real Business Cycle Model as well as extensions with labour and capital market frictions. It also considers monetary policy through the lens of the New-Keynesian Model. It includes economic policy simulations. Slides are self-contained but references to recent relevant scientific publications are also provided .

80% written exam20% homeworks

Bibliography:• Acemoglu, D., Introduction to Modern Economic Growth, 2009, Princeton University Press (Chapters 1-3, 5,8-11)• Barro, R., and Sala-i-Martin, X., 2004, Economic Growth, MIT Press (Chapters 1-4)  • Wickens,M. Macroeconomic Theory, 2d ed., Princeton University Press, 2012 (especially Chapters 2-5, 7-8).• Blanchard O.J. and S. Fischer, Lectures on Macroeconomics, MIT Press, 1989 (especially Chapter 2, 8)• Heer, B., and A. Maussner (2014), Dynamic General Equilibrium Modeling, 3d edition, Springer, Ch 1.• King R and S Rebelo, Resuscitating Real Business Cycles, Handbook of Macroeconomics, Amsterdam: North-Holland, 1999, volume IB, chapter 14.• Merz M (1995). ’Search in the Labor Market and the Real Business Cycle’, Journal of Monetary Economics, vol. 36, pp. 269-300.• Enders Z, R Kollmann and G Muller (2011). ’Global Banking and International Business Cycles’, European Economic Review, vol. 55, pp. 407-426.• Smets F and R Wouters (2003). ’An Estimated Dynamic Stochastic General Equilibrium Model of the Euro Area’, Journal of the European Economic Association, vol. 1(5), pp. 1123-1175.

• Course title: Advanced Econometrics
• Number of ECTS: 6
• Course code: QTECOFIN-2
• Module(s): Module 1
• Language: EN
• Mandatory: Yes

This course is intended for students enrolled in the Master of Science program in Quantitative Economics and Finance.Ph.D. students interested in learning this material are also welcome. The objective of this course is to familiarize students with microeconometric models and methods that are widely used in economics, finance, and social science research. We will focus on linear models. Nonlinear models are covered in a subsequent course.On completion of the course unit successful students will be able to:• Have a good understanding of some widely used econometric models and techniques used by economists to answer policy related questions• Understand how these models are identified, estimated, and tested, how the asymptotic distributions of the various estimators and test statistics are obtained, and the fundamental assumptions underlying these results. This will not only enable the students to process and interpret empirical data and test whether they are in accordance with economic theory, but should also help them read, understand, and critically evaluate the econometrics articles in peer-reviewed journals encountered during the course of their own research.

COURSE CONTENT1. Basics._ What is a statistical model?_ Interpreting and estimating models of causal relationships with observational data._ Exogenous and endogenous variables._ Reference: Chapter 1 and class-notes.2. Statistics review._ Best linear predictors and best predictors._ Conditional expectations and their properties._ Basic asymptotic theory._ Applications of asymptotic theory to estimation and testing._ Reference: Chapters 2, 3 and class-notes.3. Single equation linear models._ Ordinary least squares._ Consistency and asymptotic normality of OLS estimators._ Estimating heteroscedasticity-robust standard errors._ Problems associated with endogenous regressors._ Prevalence of endogenous regressors in econometric models._ The instrumental variables (IV) solution to endogenous regressors._ Reference: Chapter 4 and class-notes.4. IV estimation of single equation models._ The two-stage least squares (2SLS) estimator and its properties._ The control function estimator and its properties._ Testing for endogeneity._ Relationship between 2SLS and control function estimators._ Reference: Chapters 5, 6 and class-notes.5. Generated regressors and instruments._ OLS with generated regressors._ 2SLS with generated instruments._ Effect of generated regressors and instruments on the properties of estimators._ Specification testing in linear models with generated regressors._ Reference: Chapter 6 and class-notes.6. Generalized method of moments (GMM)_ Econometric models defined in terms of moment conditions._ Under-identified, just-identified and over-identified moment-condition models._ Estimation of just- and over-identified moment-condition models._ Asymptotic properties of GMM estimators._ Two-step optimal GMM estimators._ GMM based hypothesis testing._ GMM based specification testing._ Reference: Chapter 14 and class-notes.7. Systems of equations with exogenous regressors._ Seemingly unrelated regressions (SUR)._ Optimal GMM estimation of SUR models._ Imposing cross-equation restrictions._ Reference: Chapter 7 and class-notes.8. Systems of equations with endogenous regressors._ GMM estimation of SUR with varying instruments._ GMM versus 3SLS._ Reference: Chapter 8 and class-notes.9. Linear simultaneous equations._ Classical supply and demand models._ Natural instruments: identification via exclusion restrictions._ Identification via cross-equation and covariance restrictions._ Reference: Chapter 9 and class-notes.10. Linear panel data models._ Linear panel data models without unobserved effects._ Linear panel data models with unobserved effects._ Estimating fixed effects models under strict exogeneity._ The random effects estimator._ Testing the random effects hypothesis._ Correlated random effects: Hausman-Taylor type models._ Dynamic panel data models and sequential exogeneity._ Reference: Chapters 10, 11 and class-notes.

60% of the course grade is based on the final exam, which is closed book and closed notes. The final exam is comprehensive, i.e., it includes all material covered in the class, the homeworks, and the TA sessions40% of the course grade is based on 5 homework assignments. The completed homeworks have to be handwritten and handed in individually

Bibliography:The required text for this course is1. Econometric analysis of cross section and panel data, 2nd ed., J. M. Wooldridge (2010).All chapter references in the syllabus are to this book.Students interested in additional reading may consider the following references:• “Econometrics,” B. Hansen, 2022.• “Econometric theory and methods,” J. G. MacKinnon and R. Davidson, 2009.• “Mostly harmless econometrics: An empiricist’s companion,” J. D. Angrist and J. S. Pischke, 2008.• “Microeconometrics: Methods and applications,” A. C. Cameron and P. K. Trivedi, 2005. Also by the same authors, “Microeconometrics using STATA,” 2009.• “Panel data econometrics,” M. Arellano, 2003.• “Econometric analysis,” W. H. Greene, 2003.• “Econometrics,” F. Hayashi, 2000.• “An introduction to classical econometric theory,” P. Ruud, 2000.• “Statistics and econometric models,” vol. 1 and 2, C. Gourieroux and A. Monfort, 1995.• “A course in econometrics,” A. S. Goldberger, 1991.• “Large sample estimation and hypothesis testing,” W. K. Newey and D. McFadden, in Handbook of Econometrics, vol. 4, 1994.• “Advanced econometrics,” T. Amemiya, 1985.• “Handbooks of econometrics,” vol. 1 – vol. 6B, 1983 – 2007.

• Course title: Advanced Financial Theory
• Number of ECTS: 6
• Course code: QTECOFIN-4
• Module(s): Module 1
• Language: EN
• Mandatory: Yes

On completion of the course unit successful students will be able to:• rigorously develops the foundations of modern asset pricing theory • introduce students to some key topics in corporate finance• interpret key empirical evidence alongside • be familiar with computing methods to implement and solve models • develop, communicate and execute independent research in financial economics• be familiar with the entire lifecycle of a research project and to manage it according to the highest modern professional standards 

COURSE CONTENT We will tentatively touch on the following topics:1) Introduction to modern research in financial economics2) Theory of choice under uncertainty3) No-Arbitrage Theory and Pricing Kernels4) Equilibrium Asset Pricing5) CAPM and Linear Factor Models: Theory and Evidence6) No-Arbitrage, Pricing Kernels and Equilibrium in Dynamic Economies7) Dynamic Programming and Markov Models8) Consumption-Based Asset Pricing (CBAP)9) CBAP: Habit Models, Long-Run Risk, Rare Disasters10) Production-Based Asset Pricing11) Asset Pricing with Asymmetric Information 12) Capital Structure and Classic Issues in Corporate Finance13) Dynamic Contracting and Quantitative Corporate Finance

40% written final exam20% writting exercices40% research assignment

Bibliography: The main course material is a comprehensive set of slides that I will make available throughout the course. We will not follow any particular book closely in this class, but the following textbooks will be useful references. 1. Huang, Chi-fu and Robert H. Litzenberger, Foundations for Financial Economics, North- Holland, 1988.2. Altug, Sumru and Pamela Labadie, Asset Pricing for Dynamic Economies, Cambridge University Press, 2008.3. Campbell, John, Financial Decisions and Markets: A Course in Asset Pricing, Princeton University Press, 2017.4. Cochrane, John, Asset Pricing, Princeton University Press, 2001.5. Ljungqvist, Lars and Thomas J. Sargent, Recursive Macroeconomic Theory, 2nd Edition, MIT Press, 2004.6. Back, Kerry, Asset Pricing and Portfolio Theory, Oxford University Press, 2010.7. Duffie, Darrell, Dynamic Asset Pricing Theory, Princeton University Press, 20018. Munk, Claus, Financial Asset Pricing Theory, Oxford University Press, 20139. Mas-Colell, Andreu, Michael Whinston and Jerry Green, Microeconomic Theory, Oxford University Press, 201010. Heer, Burkhard and Alfred Maussner, Dynamic General Equilibrium Modeling: Computational Methods and Applications, Springer, 2005.11. Stockey, Nancy, and Lucas, Robert and Prescott, Edward, Recursive Methods in Economic Dynamics, Harvard University Press, 198912. Tirole, Jean, The Theory of Corporate Finance, Princeton University Press, 2006

• Course title: Advanced Empirical Analysis – Economics
• Number of ECTS: 4
• Course code: QTECOFIN-6
• Module(s): Module 2
• Language: EN
• Mandatory: Yes

On completion of the course unit successful students will be able to:

• Convey and discuss fundamental concepts like treatment, causal effects, potential outcomes, Conditional Estimation Function, selection bias, omitted variable bias, random assignment.• Identify selection bias and expected direction of the bias with non-experimental data.• Use regression techniques in randomized experimental frameworks.• Set up instrumental variable estimation to estimate causal links, with knowledge of key related concepts (instrument, first-stage regressions, reduced-form regressions, over identification test, compliant and non-compliant populations).• Appreciate and critique regression discontinuity, difference-in-differences or instrumental estimation.• Develop a sense, a taste for promising empirical research projects.• Apply the tools that produces statistical results (estimates, tables, graphs) for modern empirical papers, mostly meaning scripting in Stata.• Write cogently in about the strengths and weaknesses of research papers, as a referee would for peer review, in professional, academic English.• Have a basic idea what machine learning is good for economists.

This course will be devoted to the issue of estimating causal links in economics using various research designs. The course covers over the new techniques developed to identify causal relationships in economics & finance.The Plan• Chapter 1 Key Concepts: causal relationships, potential outcomes, randomized experiments, selection bias.• Chapter 2 Regression Recap and useful Regression Concepts• Chapter 3 Instrumental Variable Estimation• Chapter 4 Panel Data and Difference in Difference approach.• Chapter 5 Regression Discontinuity Designs.

100% seminar paperStudents will be required to comment a paper published in the literature facing endogeneity issues and providing a credible identification strategy to estimate the causal links of interest. The students will have to replicate the results of the paper and to offer a critical assessment of the paper. The paper is individual.

Bibliography:

 J.D. Angrist and J-S. Pischke, 2009. Mostly Harmless Econometrics. Princeton University Press.J.D. Angrist and J-S. Pischke, 2015. Mastering ′Metrics – The Path from Cause to Effect. Princeton University Press.G.W. Imbens and D.B. Rubin, 2015. Causal Inference for Statistics, Social and Biomedical Sciences, an Introduction, Cambridge University PressS. Athey, 2018. “The Impact of Machine Learning on Economics,” mimeo.  

• Course title: Advanced Empirical Analysis – Finance
• Number of ECTS: 4
• Course code: QTECOFIN-7
• Module(s): Module 2
• Language: EN
• Mandatory: Yes

On completion of the course unit successful students will be able to:

• i) make students able to start a research project that relies on advanced empirical methods • ii) make students able to read and assess critically empirical research papers • iii) make the students able to apply and implement the methods presented in class.

Outline (indicative)1) A warm up: Why and when can econometrics work?• Econometrics vs Probability • LLN and CLT• Incorporating time dependence• Delta method or how to get the standard errors of almost anything2) A general framework: theory of optimization estimators (aka extremum estimators) • A bird’s eye view on some particular cases: GMM, OLS and MLE• Consistency theorem• Asymptotic normality3) Some variations and extensions** • Identification, Weak identification and weak instruments• Generalized Empirical Likelihood estimators (GEL)4) Elements of Hilbert space theory and the projection theorem• Inner product spaces and Hilbert spaces• Projection theorem• Applications: Conditional expectation, OLS and omitted variable bias, fundamental theorem of asset pricing**5) Hypothesis testing**• Parameter restriction tests vs specification tests • The trinity: LM, LR, and Wald6) More on GMM**• Review of GMM• On weak identification and weak instruments• Test of over identifying restrictions  • Inference with unequal length samples• Two-step estimators 7) Simulation-based estimation and inference methods• Calibration • Simulated method of moments • Indirect inference**8) Elements of Bayesian econometrics• Basics of Bayesian inference• Large sample properties: Bernstein-von Mises theorem• MCMC basics**** indicates topics that less likely to be covered due to time constraints

60% written exam

30% homeworks

10% Pop quiz if necessary

Bibliography:

Hayashi F.: 2000.Econometrics, Princeton University Press. Chap. 2,7-8.Newey, Whitney, and Daniel McFadden, 1994, Large sample estimation and hypothesis testing, in Robert Engle, and Daniel McFadden, ed.: Handbook of Econometrics, Vol. 4 . pp. 2111-2245 (North-Holland: Amsterdam).Singleton Kenneth, Empirical Dynamic Asset Pricing: Model Specification and Econometric Assessment, Princeton University Press, 2006During the course, there may be hand-outs and other material on additional topics relevant for the course and the examination.

• Course title: Applied General Equilibrium Theory
• Number of ECTS: 4
• Course code: QTECOFIN-8
• Module(s): Module 2
• Language: EN
• Mandatory: Yes

On completion of the course unit successful students will be able to:- Derive the first and second fundamental welfare theorem- Prove the existence and uniqueness of Walrasian equilibrium- Understand Pareto optimality and social welfare optima- Discuss exchange and production economies with and without Edgeworth box – Understand technical properties of general equilibrium allocations and CORE- Discuss monopolistic competition in general equilibrium and international trade (Frèchet distribution etc.)- Explain market incompleteness and information issues in general equilibrium- Understand the issues and modeling of informational asymmetries- Discuss signal models, moral hazard, and principal-agent models

Pre-requisite: Advanced Microeconomics IThis course unit aims to introduce advanced microeconomics tools for analyzing the general equilibrium in markets of material goods and financial assets. The course first studies the economics of resource allocations in perfectly competitive markets using the toolbox of the theories of the consumer and the firm. The course studies the properties of existence, local and global uniqueness of equilibria, first and second welfare theorems, decision-making under uncertainty, and consumer and producer surplus. It then elaborates on new general equilibrium models with imperfect competition, monopolistic competition, non-homothetic demand, and heterogeneous firms and consumers (new tools in international trade theory). It finally discusses the existing theory body where market equilibria fail, or information is imperfect or asymmetric.

50% written exam25% presentations25% Class participation and exercises

Bibliography:

Basic book:Microeconomic Theory. Andreu Mas—Colell Michael D. Whinston and. Jerry R. Green. New York Oxford OXFORD UNIVERSITY PRESS 1995.New trade theories:Allen and Arkolakis (2016), Elements of Advanced International Trade. Class notes.Melitz, M. J., .The Impact of Trade on Intra-Industry Reallocations and Aggregate Industry Productivity,.2003, Econometrica, 71(6), 1695-1725.Arkolakis C., S. Demidova, P. Klenow, and A. Rodriguez-Clare, .Endogenous Variety and the Gains from Trade,.2008, American Economic Review, Papers and ProceedingsZhelobodko, Evgeny, Sergey Kokovin, Mathieu Parenti, and Jacques-Francois Thisse. 2012.”Monopolistic competition: Beyond the constant elasticity of substitution.” Econometrica,Vol. 80(6): 2765-2784.Mrazova, Monika, and J. Peter Neary. 2017. “Not so demanding: Demand structure andfirm behavior.” American Economic Review, Vol. 107 (12): 3835-74.Kichko S. and Picard PM. 2020. On the effects of income heterogeneity in monopolistically competitive markets. Higher School of Economics Research Paper No. WP BRP 239/EC/2020.

• Course title: Master Thesis
• Number of ECTS: 10
• Course code: QTECOFIN-9
• Module(s): Module 2
• Language: EN
• Mandatory: Yes

• Course title: The Economics of Gender
• Number of ECTS: 2
• Course code: QTECOFIN-20
• Module(s): Module 2
• Language: EN
• Mandatory: No

On completion of the course unit successful students will be able to: • to advance their knowledge of the foundation of economics of gender.• be able to critically assess and analyse scholarly articles through weekly readings.• learn to critically assess whether gender is a dimension to consider in research• relate the academic articles taught in class to the experiences of generations of women in their families through exchanging with these women

Pre-requisite: Econometrics; MicroeconomicsIn this course, we will seek answers to following questions: Why are men paid more than women? Why do men and women work in different occupations? What explains the rise in labour force participation of women in the post-World War II era? Why are there now more women than men enrolled in colleges and still women are underrepresented in the top management positions? Why female entrepreneurial activity tends to below and concentrated in certain sectors, such as the food or garment industry? What is the role of parents’ attitudes and beliefs on math performances of daughters? Do families make financial decisions as one economic unit or do different members bargain with one another? Are there physiological differences between men and women which explain differences in behaviour? The answer to some of these questions has been the research agenda of Claudia Goldin (Harvard), who received the Nobel Prize in Economics in 2023. The content of this course builds upon the work of Goldin and many other economists in the economics of gender.We will apply economic models (e.g. consumer choice, human capital, and discrimination) to explore the answers to these questions. However, the course will also examine historical and cultural trends and empirical studies that attempt to answer these questions with data.There is not yet a textbook for the economics of gender, so we will use series of required readings from economic journals. Most of the readings are available on-line and will be provided by the professor in Moodle. Many of the readings that are printed in economic journals such as the American Economic Review, Quarterly Journal of Economics and Journal of Political Economy are available through JSTOR (journal archive), available on UL campuses.

100% Presentations

Bibliography: I. Introduction: What are the issues in economics of gender? Goldin, Claudia. 2006. “The Quiet Revolution That Transformed Women’s Employment, Education, and Family,”  American Economic Review, 96 (2): 1-21.Qian, Nancy. 2008. “Missing Women and the Price of Tea in China: The Effect of Sex-specific Income on  Sex Imbalance.” Quarterly Journal of Economics, 123(3): 1251-1285.II. Economics of Marriage, Family and Gender RolesGoldin, Claudia and Lawrence F. Katz. 2002. “The Power of the Pill: Oral Contraceptives and Women’s Career and Marriage Decisions.” Journal of Political Economy, 110 (4): 730-770.Alesina, Alberto, Paola Giuliano and Nathan Nunn. 2013. “On the Origins of Gender Roles: Women and the Plough.” Quarterly Journal  of Economics, 128(2): 469-530.Ana Tur-Prats; Family Types and Intimate Partner Violence: A Historical Perspective. The Review of Economics and Statistics 2019; 101 (5): 878–891.Bertrand Marianne, Emir Kamenica and Jessica Pan. 2015. “Gender Identity and Relative Income within   Households.” Quarterly Journal of Economics, 130(2): 571-614.Becker, Anke, On the Economic Origins of Restrictions on Women’s Sexuality (2019). CESifo Working Paper No. 7770Myers, Caitlin Knowles.  “The Power of Abortion Policy: Re-examining the Effects of Young  Women’s Access to Reproductive Control.” Journal of Political Economy.Lapatinas, Litina, Zanaj, “Economic complexity and gender norms”, DEM Discussion Paper, 2024.III. Women and Household Finance IssuesFrancesco D’Acunto, Ulrike Malmendier, Michael Weber, 2020.  “Gender Roles and the Gender Expectations Gap“, https://bfi.uchicago.edu/working-paper/gender-roles-and-the-gender-expectations-gap/ Simone G. Schaner , Erica M. Field , Rohini Pande , Natalia Rigol, Charity M. Troyer Moore, 2020, “On Her Own Account: How Strengthening Women’s Financial Control Impacts Labor Supply and Gender Norms”, https://conference.nber.org/conf_papers/f141645.Emma Riley, “Resisting Social Pressure in the Household Using Mobile Money: Experimental Evidence on Microenterprise Investment in Uganda”, 2020, Luigi Guiso and Luana Zaccaria, “From Patriarchy to Partnership: Gender Equality and Household Finance”, 2020, https://conference.nber.org/confer/2020/SI2020/GE/GuisoPaper.pdfAna Maria Montoya, Alex Solis, Raimundo Undurraga , Eric Parrado, 2020, “Bad Taste: Gender Discrimination in the Consumer Credit Market”, http://dx.doi.org/10.18235/0001921IV. Gender and the labor market outcomesBlau, Francine D. and Lawrence M. Kahn. 2017. “The Gender Wage Gap: Extent, Trends, and Explanations.” Journal of Economic Literature, 55(3): 789-865.Card, David and Abigail Payne. 2017. “High School Choices and the Gender Gap in STEM.” NBER WP 23769.Fernandez, R., A. Fogli, and C. Olivetti (2004). Mothers and Sons: Preference Formation and Female Labor Force Dynamics. The Quarterly Journal of Economics 119 (4), 1249–1299.Flory, Jeffrey, Andreas Leibbrandt, and John List. 2015. “Do Competitive Work Places Deter Female Workers? A Large-scale Natural Field Experiment on Job-Entry Decisions.” Review of Economic Studies, 82(1): 122-15Fogli, A. and L. Veldkamp (2011). Nature or Nurture? Learning and the Geography of Female Labor Force Participation. Econometrica 79 (4), 1103–1138.Goldin, Claudia and Cecelia Rouse. 2000. “Orchestrating Impartiality: The Effect of ‘Blind’ Auditions on Female Musicians.” American Economic Review 90(4): 715-741Goldin, Claudia, Lawrence Katz, and Ilyana Kuziemko. 2006. “The Homecoming of American College Women: The Reversal in the Gender Gap in College,” Journal of Economic Perspectives, 20(4): 133-156.Jensen, R. (2012). Do Labor Market Opportunities Affect Young Women’s Work and Family Decisions? Experimental Evidence from India. The Quarterly Journal of Economics 127 (2), 753–792Leibbrandt, Andreas and John List. 2015. “Do Women Avoid Salary Negotiations? Evidence from a Large Scale Natural Field Experiment.” Management Science, 61(9): 2016-2024.Lundborg, Petter, Erik Plug, and Astrid Würtz Rasmussen. 2017. “Can Women Have Children and a Career? IV Evidence from IVF Treatments.” American Economic Review, 107(6): 1611-37.Niederle, Muriel and Lise Vesterlund. 2007. “Do Women Shy Away from Competition? Do Men Compete Too Much?” The Quarterly Journal of Economics, 122 (3): 1067-1101.

• Course title: Topics in Regional and Urban Economics
• Number of ECTS: 2
• Course code: QTECOFIN-11
• Module(s): Module 2
• Language: EN
• Mandatory: No

On completion of the course unit successful students will be able to:-  explain the capital location in the new economic geography-  discuss urban models and endogenous location of economic activities-  discuss urban issues in migration, work from home, green amenities-  discuss land rent and real estate markets in cities-  explain the foundation of gravity models-  discuss the quantitative urban economics models

Pre-requisite: Good micro-economic and mathematical background is expected at the beginning of the courseThis course unit aims to introduce advanced economic theory of modern regional and urban economics. The course first studies the location of capital and population across regions in the New Economic Geography paradigm (Krugman Nobel Prize). It permits us to understand regional disparities and policy implications in terms of employment capital structure. It then discusses various monopolistic setups, new trade theories, and classical urban theories that permit to study of gravity equations, welfare improvements, and the endogenous formation of cities. The course also discusses the role of amenities, agglomeration externalities, transport congestion, and labor markets. It finally discusses the role of real estate markets in the location of individuals and industries. The course is based on good micro- and macro-economic knowledge.The course content changes every year according to current theoretical research and students’ suggestions.The course develops active research skills through literature reading, model presentation, and writing skills.

40% oral exam40% presentations20% participation

Bibliography:

 

Books:Fujita Thisse (2004) Economics of Agglomeration. Cambridge University Press.Baldwin,  Forslid,  Martin,  Ottaviano  and  Robert-Nicoud  (2003)  Economic Geography and Public Policy, Princeton University Press.Henderson  and  Thisse  (2003),  Handbook  of  Urban  and  Regional  EconomicsDuranton, G., Henderson, V., & Strange, W. (Eds.). (2015). Handbook of regional and urban economics. Elsevier.Trade and GeographyFujita, Krugman and Venables. 1999. The Spatial Economy, MIT Press Belleflamme, Paul & Picard, Pierre & Thisse, Jacques-Francois, 2000. “An Economic Theory of Regional Clusters,” Journal of Urban Economics, Elsevier, vol. 48(1), pages 158-184, July.Krugman. 1991. “Increasing Returns and Economic Geography,” Journal of Political Economy Picard, Pierre M. & Zeng, Dao-Zhi, 2005. “Agricultural sector and industrial agglomeration,” Journal of Development Economics, Elsevier, vol. 77(1), pages 75-106, June.Okubo, Toshihiro & Picard, Pierre M. & Thisse, Jacques-François, 2010. “The spatial selection of heterogeneous firms,” Journal of International Economics, Elsevier, vol. 82(2), pages 230-237, November.Behrens, Kristian & Picard, Pierre M., 2011. “Transportation, freight rates, and economic geography,” Journal of International Economics, Elsevier, vol. 85(2), pages 280-291.Allen and Arkolakis. 2014. “Trade and the Topography of the Spatial Economy,” Quarterly Journal of Economics GravityAnderson, J., .A Theoretical Foundation for the Gravity Equation,.1979, American Economic Review, 69(1), 106-116.Krugman, P., .Scale Economies, Product Differentiation, and the Pattern of Trade,.1980, American Economic Review, 70(5), 950-959.CitiesLucas & Rossi-Hansberg, “On the Internal Structure of Cities,” Econometrica (2002) Mossay, Pascal & Picard, Pierre M. & Tabuchi, Takatoshi, 2020. “Urban structures with forward and backward linkages,” Regional Science and Urban Economics, Elsevier, vol. 83(C).Redding and Sturm, “The Economics of Density: Evidence from the Berlin Wall,” Econometrica (2015). Emmanuelle Augeraud-Veron & Francisco Marhuenda & Pierre M. Picard, 2019. “Local Social Interaction and Urban Equilibria,” CREA Discussion Paper Series 19-17, Center for Research in Economic Analysis, University of Luxembourg.Rossi-Hansberg, “Cities under Stress,” Journal of Monetary Economics (2004) Rossi-Hansberg, “Optimal Urban Land Use and Zoning,” Review of Economic Dynamics (2004) Agglomeration Forces Duranton & Puga, “Micro-Foundations of Urban Agglomeration Economies,” Handbook of Urban and Regional Economics (2004) Greenstone, Hornbeck & Moretti, “Identifying Agglomeration Spillovers: Evidence from Winners and Losers of Large Plant Openings,” Journal of Political Economy (2010) Rosenthal & Strange, “Evidence on the Nature and Sources of Agglomeration Economies” Handbook of Urban and Regional Economics, (2004) Externalities Carlino, Chatterjee, & Hunt, “Urban Density and the Rate of Invention,” Journal of Urban Economics (2007) Ciccone and Hall, “Productivity and the Density of Economic Activity,” American Economic Review (1996) Henderson & Arzaghi, “Networking Off Madison Avenue,” Review of Economic Studies (2008) Moretti, “Workers’ Education, Spillovers and Productivity,” American Economic Review (2004) Pascal Mossay & Pierre Picard, 2019. “Spatial segregation and urban structure,” Journal of Regional Science, Wiley Blackwell, vol. 59(3), pages 480-507, June.Rossi-Hansberg, Sarte, & Owens, “Housing Externalities,” Journal of Political Economy (2010) Saxenian, “Inside-Out: Regional Networks and Industrial Adaptation in Silicon Valley and Route 128,” Cityscape: A Journal of Policy Development and Research (1996) Amenities and disamentiesSchindler, Mirjam & Caruso, Geoffrey & Picard, Pierre, 2017. “Equilibrium and first-best city with endogenous exposure to local air pollution from traffic,” Regional Science and Urban Economics, Elsevier, vol. 62(C), pages 12-23.Glaeser, Kolko & Saiz, “Consumer City,” Journal of Economic Geography (2000) Rappaport, “Consumption Amenities and City Population Density,” Regional Science and Urban Economics (2008)Rappaport, “Moving to Nice Weather,” Regional Science and Urban Economics (2007)Pierre M. Picard & Thi Thu Huyen TRAN, 2021. “Geographical Stratification of Green Urban Areas,” Journal of Economic Geography.Pierre M. Picard & Thi Thu Huyen Tran, 2021. “Green Urban Areas,” Journal of Environmental Economics and Management.Kyriakopoulou and Xepapadeas (2017). Atmospheric Pollution in Rapidly Growing Industrial Cities:  Spatial Policies and Land Use Patterns, Journal of Economic Geography, vol 17(3): p. 607-634.Kyriakopoulou and Picard (2020), On the Design of Sustainable Cities: Local Traffic Pollution and Urban Structure, Forthcoming Journal of Environmental Economics and Management.Labor Markets and SortingPicard, Pierre M. & Toulemonde, Eric, 2006. “Firms agglomeration and unions,” European Economic Review, Elsevier, vol. 50(3), pages 669-694, April.Picard, Pierre M. & Toulemonde, Eric, 2004. “Endogenous qualifications and firms’ agglomeration,” Journal of Urban Economics, Elsevier, vol. 55(3), pages 458-477, May.Baum-Snow & Pavan “Understanding the City Size Wage Gap,” Review of Economic Studies (2011)De la Roca & Puga, “Learning by Working in Big Cities,” working paper (2012)Glaeser & Mare, “Cities and Skills,” Journal of Labor Economics (2001)Picard, Pierre M. & Zenou, Yves, 2018. “Urban spatial structure, employment and social ties,” Journal of Urban Economics, Elsevier, vol. 104(C), pages 77-93.Picard, Pierre M. & Wildasin, David E., 2011. “Outsourcing, labor market pooling, and labor contracts,” Journal of Urban Economics, Elsevier, vol. 70(1), pages 47-60, July.Teulings & Gautier, “Search and the City,” Regional Science and Urban Economics (2009)Transport Costs and Congestion ForcesBaum-Snow & Kahn. “The Effects of Urban Rail Transit Expansions: Evidence from Sixteen Cities,”Brookings-Wharton Papers on Urban Affairs (2005)Baum-Snow, “Did Highways Cause Suburbanization,” Quarterly Journal of Economics (2007)Duranton & Turner “The Fundamental Law of Road Congestion,” American Economic Review (2011)Duranton & Turner, “Urban Growth and Transportation,” Review of Economic Studies, forthcoming (2011)Monte, Redding and Rossi-Hansberg. “Commuting, Migration, and Local Employment Elasticities”working paper (2015)Saiz, “The Geographic Determinants of Housing Supply,” Quarterly Journal of Economics (2010)Measuring AgglomerationCombes, Duranton, Gobillon, & Roux, “The Productivity Advantages of Large Cities: DistinguishingAgglomeration from Firm Selection,” Econometrica (2012)Duranton & Overman, “Testing for Localisation Using Micro-Geographic Data,” Review of EconomicStudies (2005)Ellison & Glaeser, “Geographic Concentration of Industry,” American Economic Review (1999)Ellison, Glaeser & Kerr, “What Causes Industry Agglomeration? Evidence from CoagglomerationPatterns,” American Economic Review (2010)Decomposing Agglomeration Through TheoryAlbouy, “Are Big Cities Bad Places to Live? Estimating Quality of Life across Metropolitan Areas,”working paper (2012)Albouy, “What are Cities Worth? Land Rents, Local Productivity and the Capitalization of AmenityValues,” Review of Economics and Statistics (2015)Behrens, Mion, Murata, & Südekum, “Spatial Frictions,” working paper (2013)Desmet & Rossi-Hansberg, “Urban Accounting and Welfare,” American Economic Review (2011)Desmet & Rossi-Hansberg, “Analyzing Urban Systems: Have Mega-Cities Become Too Large?,” The Urban Imperative: Towards Competitive Cities, Oxford UP (2015)Systems of CitiesIoannides & Overman “Zipf’s Law for Cities: An Empirical Examination,” Regional Science and Urban Economics (2001)Soo, “Zipf’s Law for Cities: A Cross-Country Investigation,” Regional Science and Urban Economics (2005)Behrens, Duranton, & Robert-Nicoud, “Productive cities: Sorting, Selection, and Agglomeration,” Journal of Political Economy (2014)Gabaix, “Zipf’s Law for Cities: An Explanation,” Quarterly Journal of Economics (2004)Henderson, “The Sizes and Types of Cities,” American Economic Review (1974)Krugman, “Increasing Returns and Economic Geography,” Journal of Political Economy (1991)Mossay, P. & Picard, P.M., 2011. “On spatial equilibria in a social interaction model,” Journal of Economic Theory, Elsevier, vol. 146(6), pages 2455-2477. Rossi-Hansberg & Wright, “Urban Structure and Growth,” Review of Economic Studies (2007)Housing and Real EstateCampbell, Giglio, & Pathak, “Forced Sales and House PricesDavis & Heathcote, “The Price and Quantity of Residential Land in the US,” Journal of Monetary Economics (2007)Glaeser & Gyourko, “The Impact of Zoning on Housing Affordability,” Economics Policy Review (2003)Glaeser & Gyourko, “Urban Decline & Durable Housing,” Journal of Political Economy (2006)Landvoigt, Piazzesi, and Schneider, “The Housing Market(s) of San Diego,” American Economic Review (2015)Mian & Sufi, “The Consequences of Mortgage Credit Expansion: Evidence from the U.S. Mortgage Default Crisis,” Quarterly Journal of Economics (2009)Quigley & Raphael, “Regulation and the High Costs of Housing” American Economic Review (2005)Stroebel, “Asymmetric Information about Collateral Values,” Journal of Finance (2015)

• Course title: Sustainable Development
• Number of ECTS: 2
• Course code: QTECOFIN-19
• Module(s): Module 2
• Language: EN
• Mandatory: No

On completion of the course unit successful students will be able to: – The student can understand how the  economic growth is related to sustainable development, especially  the environmental economics. – Obtain the first knowledge about what are the limits of growth from environmental economic point of view, what could be the potential solutions and the limitations. – Ask the first economic question how sustainable development could be possible.

A short review of definitions about sustainable development.The relationship between economic growth and sustainable development.Classical studies of Macroeconomics and Environment – DICE model revisit.Technological change, pollution and policy induced technology change.Biodiversity and economic growth.

100% presentations

Bibliography:• Acemoglu D. U. Akcigit, D. Hanley and W. Kerr (2016). Transition to clean technology, Journal of Political Economy, 124(1), 52-104. • Dasgupta P.   The Economics of Biodiversity: The Dasgupta Review. 2021. • Hotelling H. (1931). The economics of exhaustible resources. Journal of Political Economy. 39(2), 137-175. • Maria C. and S. Smulders (2017).    A paler shade of green: Environmental policy under induced technical change . European Economic Review, 99, 151-169.• Hassler J. and P. Krusell (2018). Environmental macroeconomics: The case of climate change in Handbook of Environmental Economics, Volume 4, Chapter 8.• Stokey N. (1998). Are there limits to growth? International Economic Review, 39(1), 1-31. • Xepapadeas A. (2005). Economic growth and the environment in Handbook of EnvironmentalEconomics, Volume 3, Chapter 23.

• Course title: Risk Management
• Number of ECTS: 2
• Course code: QTECOFIN-13
• Module(s): Module 2
• Language: EN
• Mandatory: No

On completion of the course unit successful students will be able to:• Become familiar with the range of risks facing corporations and learn how to measure and manage these risks. The discussion will focus on various aspects of market risk.• Become familiar with the salient features of speculative asset returns.• Apply state-of-the-art risk measurement and risk management techniques, which are nevertheless tractable in realistic situations.• Use derivatives in risk management.• Understand the current academic and practitioner literature on risk management techniques.

Pre-requisite: Student should have completed basic finance coursesThis course deals with the ways in which risks are quantified and managed by (financial) institutions. It suggests a relatively sophisticated approach to risk measurement and risk modeling. We document key features of risky asset returns and then construct tractable statistical models that capture these features. Among the topics covered is the nature of financial risks, how financial institutions quantify and manage their market risk exposure, how they model volatility and correlations, and how they price options.

70% presentation30% participation

Bibliography:“Elements of Financial Risk Management”, 2nd edition by Peter Christoffersen, Academic Press, ISBN 978-0-12-374448-7.

• Course title: Behavioral Economics and Finance
• Number of ECTS: 2
• Course code: QTECOFIN-12
• Module(s): Module 2
• Language: EN
• Mandatory: No

On completion of the course unit successful students will be able to: • Know anomalies in finance and economics• Know the foundations of behavioral finance and behavioral economics

Pre-requisite: The course requires knowledge of game theory, and basic knowledge of maths and statistics.The course introduces students to theories of behavioral economics and finance. Departing from the standard paradigm in economics, expected utility theory, we pinpoint empirical anomalies. The course presents models of prospect theory, noise trader risk, psychological game theory, bounded rationality that help to rationalize the divergence between observed behavior and theory. The course is structured in four chapters; Behavioral Decision Theory; Intertemporal Choice Behavior; Inefficient Markets; Behavioral Game Theory.

100% written exam

Bibliography:

Dhami, Sanjit, 2016, Foundations of behavioral economic analysis. Oxford University PressMas Colell, Andreu, Whinston and Green, 1995, Microeconomic Theory. Oxford University PressShleifer Andrei, 2001, Inefficient markets – An introduction to behavioral finance. Calderon Lectures in Economics.Thaler, Richard (ed.), (1992), Advances in Behavioral Finance, Russell Sage Thaler, Richard (ed.) (1994), Quasi-Rational Economics, Russell Sage FoundationThaler, Richard (ed.), (2005), Advances in Behavioral Finance II, Russell Sage Further readings will be communicated during the lectures.

• Course title: Financial Stability: Theory and Policy
• Number of ECTS: 2
• Course code: QTECOFIN-15
• Module(s): Module 2
• Language: EN
• Mandatory: No

On completion of the course unit successful students will be able to:• Understand key measures of financial stability and bank stress tests• Distinguish which regulatory authorities exercise micro- and macro-prudential policy• Use the Kiyotaki-Moore model in order to understand how credit cycles can create an environment that encourages excess risk-taking by banks.• Use the Brunnermeier-Sannikov framework in order to address and understand questions of financial stability

Pre-requisite: A graduate course in calculus, dynamic optimization, statistics, micro and macro economicsFinancial instability deals with topics ranging from understanding the risk of bankruptcy of a single financial institution, to understanding the risk of having “domino-effects” with some financial institutions causing total, economy-wide crises. The course has three distinct goals. The first goal is to define the key broad questions of financial stability, in order to encourage students to think about a long-term research agenda on the subject. The second goal is to provide an overview of the regulatory authorities that collect data and exercise micro- and macro-prudential policy, and a description of the (statistical) tools these authorities use in order to detect and to describe financial-instability risk, i.e., liquidity risk, the risk of financial-instability contagion, and systemic risk. The third goal is to familiarize students with the state-of-the-art research ideas and tools to deal with financial stability. Specifically, the course will present theoretical models of credit cycles, models of inside-money and liquidity, and models connecting endogenous financial-stability risk with macroeconomic performance. The course will address the new policy-evaluation opportunities opened by these state-of-the-art models.

70% written exam30% Homework assignment

Bibliography:Acharya, V., L. Pedersen, T. Philippon, and M. Richardson, (2017) “Measuring systemic risk”, The Review of Financial Studies, 30 (1), 2-47.Brunnermeier, M. and Y. Sannikov, (2014) “A macroeconomic model with a financial sector”, American Economic Review, 104, 379-421.Robert E. Hall (2010), Forward-Looking Decision Making: Dynamic Programming Models Applied to Health, Risk, Employment, and Financial Stability, the Gorman Lectures, Princeton University Press.Jin, X. and F. Nadal De Simone, “Banking Systemic Vulnerabilities: A Tail-risk Dynamic CIMDO Approach”, Journal of Financial Stability, vol. 14, 2014, pp. 81-101.Jin, X. and F. Nadal De Simone, “A Framework for Tracking Changes in the Intensity of Investment Funds’ Systemic Risk”, Journal of Empirical Finance, 2014, Vol. 29, pp. 343-368.Kiyotaki, Nobuhiro & Moore, John (1997). “Credit Cycles”. Journal of Political Economy, 105,  211–248Georges Ugeux (2014) “International Finance Regulation:The Quest for Financial Stability, Wiley FinanceBrunnermeier, M., S. Merkel, and Y. Sannikov, (2020): Lectures on Macro, Money, and Finance – A Heterogeneous-Agent Continuous-Time Approach, book draft