The master is designed using “backwards engineering”. The goal is for our graduates to know how markets function and to be able to analyze the data markets generate. This knowledge enables our students to advise companies, governments, organizations and other market participants on a wide range of topics. Our students write a Master’s Thesis where they show that they know the theories and models that explain markets’ outcomes and the methods to analyze the data. To be able to write their Master’s Thesis, our students take a well designed set of courses. To become a market analyst, students learn principles of Microeconomics and Macroeconomics as well as field courses for specific markets and institutions. To become an expert in economic data analysis our students learn computation, estimation, simulation, experimental and policy evaluation methods.
The academic year is divided into five blocks
First block: preliminaries
From early September to early October students review their background knowledge.
- Algebra and Calculus Sets and numbers. Real valued functions of a single variable. Differential calculus with one variable. Integral calculus with one variable. Linear algebra. Real-valued functions of several variables.
- Introduction to Economics Introduction. Economics and Inequality. Economics and Technological Change. Economics and Globalization. Economics and Policy.
- Introduction to Econometrics Matrix Algebra. Fundamentals of Probability Theory. The Simple and Multiple Regression Model.
- Optimization Static Optimization. Unconstrained and constrained optimization. Comparative statics. Difference Equations. Dynamic Optimization in discrete time.
Second block: fundamentals
From October to December students build the basic toolkit of an economist.
- Microeconomics 1. Game theory. Games in normal form: simultaneous- move games. Games of incomplete information. Games in extensive form: sequential-move games. Games with imperfect information. Dynamic games and subgame perfection. 2. Industrial Economics. Imperfect Competition. Monopoly. Oligopoly. Product differentiation. Entry costs. 3. Decision making under uncertainty. Expected Utility Theory. Risk aversion. Investment under uncertainty. Insurance. The value of information.
- Macroeconomics 1. Matlab programming. Basic Operations. Non-linear equations. Plots. Calibration. 2. Overlapping generations model. Social security: fully funded system vs. pay-as-you-go. 3. Growth. Neoclassical growth. Solow-Swan, Ramsey-Cass-Koopmans. 4. Real Business Cycles. Dating business cycles. Stylized facts. Theories of fluctuations. Measuring business cycles.
- Econometrics 1. Regression Analysis. Multicollinearity. Generalized least squares. Heteroskedasticity. Autocorrelation. Numerical optimization. 2. Specification. Measurement errors. Instrumental variables estimation. 3. Qualitative Dependent Variables. Binary outcomes. Ordered models. Multinomial models. 4. Sample selection models. Censored regression. Truncated regression. Other models. 5. Panel data analysis. Pooled regression. Fixed effects estimation. Random effects models. Correlated random effects.
- Quantitative Methods 1. Time Series. Stylized empirical regularities. Impulse Response Function. Stationary ARMA processes. Granger causality. Vector autoregression. Structural VAR. Variance decomposition. Unit roots versus deterministic trends. Structural change – Trend breaks. Trend-cycle decompositions. Error correction models and co-integration. Stochastic volatility. 2. Stata. Data management. Basic commands. Graphs. Matrix commands. Programming. 3. The R programming Language. RStudio. Basic syntax. Data manipulation. Graphs. Descriptive statistical analysis. Loops and functions.
Third and fourth blocks: field subjects
From January to April students take courses to form their expertise in specific fields.
- Behavioral and Experimental Economics Rationality. Time inconsistency. Risk and shape of the utility function. Altruistic giving and conditional cooperation. Social preferences: outcome-based and intention-based models. Strategic interaction: coordination and dominance. Experimental Methodology
- Causal Inference for Social Sciences (Policy Evaluation) Randomized experiments. Regression adjustment. Matching. Inverse probability weighting. Regression discontinuity. Difference-in-differences. Panel data. Structural marginal models. Synthetic control method.
- Monetary Market Evidence on Money, Prices and Output: basic correlations and Co-movements. Classical monetary models: review of the RBC model, the steady state, linear approximation, calibration and simulation, limitations and extensions. The New Keynesian Monetary model: linear approximation, the monetary transmission mechanism and policy analysis.
- Social Choice and Welfare Inequality Measures. Lorenz dominance. Decomposability and subgroup consistency. Social Welfare based (normative) Inequality Measures. Welfare economics. Egalitarian principle. Unanimity principle. The equality-efficiency dilemma. The maximin utility program. The leximin social welfare ordering. Classical Utilitarianism. Social Welfare Orderings. Arrow’s Impossibility Theorems.
- Economic Growth and Development Stylized growth facts. Purchasing power parity and measurement. Neoclassical growth with human capital. Cross-country regressions. Convergence. Endogenous growth, AK model. Technological Change. Growth in a small open economy. Growth Accounting. Development accounting. Total factor productivity: institutions vs. geography; technology vs efficiency. Misallocation of resources.
- Labour Economics Foundations of the Labour Market. Labour supply. Labour demand. Labour market equilibrium. Human Capital. Imperfect Information. Discrimination. Job search and Unemployment. Duration of unemployment. Survival models.
- Energy Markets Electricity markets architecture. The Spanish Electricity Market: the market operator, the system operator and auction mechanism. Market organization elsewhere: central Europe, Scandinavian market, USA market. Strategic models of competition. Auction models. Supply function competition. Forward contracting, interconnections and market integration. Renewable generation. Regulatory framework.
- Cultural Economics Cultural goods and economic characteristics. Demand for cultural goods. Learning-by-consuming and rational addiction models. Non-market valuation techniques. The empirics of cultural demand and participation. Public provision of cultural goods. Cultural industries.
Fifth block: master thesis
From May to July students write their Master’s Thesis.
The purpose is that students implement the skills acquired by writing an essay on a specific subject. Students are expected to show a particular interest in one of the topics. Under the supervision of a Faculty member, the student is required to write an essay containing both a theoretical and an empirical analysis of a specific economic issue. The Master Thesis must be defended orally in late July and handed in by the end of July. View examples of Past Master Theses.