Checking date: 15/07/2020

Course: 2020/2021

Topics in applied economics (B)
Study: Master in Economic Analysis (68)

Coordinating teacher: DOLADO LOBREGAD, JUAN JOSE

Department assigned to the subject: Department of Economics

Type: Electives
ECTS Credits: 4.0 ECTS


Students are expected to have completed
Graduate courses in Statistics, Econometrics I and Econometrics II (Master in Economic Analysis)
Competences and skills that will be acquired and learning results.
The goal of this course is twofold. The first half of the syllabus is devoted to get graduate students familiar with a wide range of econometric methods for estimation of SVAR, DSGE and SAM macro models. Special emphasis is placed on the analysis of the transmission and propagation effects on financial, fiscal, monetary and productivity shocks on macro aggregates in product and labour markets. The second half of the course is devoted to estimation and inference in large datasets, including methods like quantile regressions, factor models and machine learning technique. The course will be organized around lectures and paper presentations to provide solid economic theory and econometric background for each topic. The lectures will be complemented with problem sets, that include both theoretical and empirical exercises.
Description of contents: programme
Topic 1. VAR Models in Macro (Brief overview) 1.1 General Framework (VAR, ECM, SVAR) 1.2 Estimation of VAR, ECM, SVAR & Proxy SVAR Models 1.3 Identifying Restrictions: Short & Long-Run, Sign, Heteroskedasticity, IV 1.4 Specifying the Co-integrating Rank 1.5 Bayesian VARs Topic 2. Empirical Applications 2.1 Inflation Shocks and Money Neutrality 2.2 Labour Market Shocks 2.3 Fiscal Shocks 2.4 Identifying Monetary Policy Switching Regimes 2.5 What Do VARs mean when Shocks are Persistent? 2.5. Stock Prices, News Shocks & the Business Cycle 2.6 An Attack on RBC Models: Technology vs. Demand Shocks 2.7 Using DSGE Models to Check Identification in SVARs Topic 3. Miscellanea 3.1 Structural Breaks 3.2 Modelling TS with Changes in Regime through Markov Chains 3.3 Marked-Point Processes in High-frequency data 3.4 Estimation of Taylor Rules & NK Phillips Curves 3.5 Quantile Regression Models 3.6 Large Dimensional Factor Models (Estimation, Forecasting, Breaks, Quantiles) 3.7 Testing for Rational Bubbles. 3.8 Calibration /Estimation of Search & Matching Models Topic 4. Machine Learning Techniques 4.1 Estimating Prediction Error 4.2 Shrinkage and LASSO methods 4.3 Nonlinear methods 4.5 Regression Trees, Random Forests 4.6 Causal Inference with Machine Learning
Learning activities and methodology
State-of- art calibration, simulation and estimation techniques.
Assessment System
  • % end-of-term-examination 70
  • % of continuous assessment (assigments, laboratory, practicals...) 30
Basic Bibliography
  • Cahuc, P. and A. Zylberberg. Labor Economics. MIT Press. 2014
  • Cameron, C. Machine Learning for Microeconomists (slides). 2017
  • Hamilton, J. . Time Series Analysis. Princeton University Press, ch.22 4. . 1994
  • Johansen, S.. Likelihood Based Inference in Cointegrated Autoregressive Models. Oxford University Press. 1995
  • Kilian, L. and H. Lutkepohl. Structural Vector Autoregressive Analysis. Cambridge University Press. 2017
Recursos electrónicosElectronic Resources *
Additional Bibliography
  • Balmaseda, M., Dolado, J. and D. Lopez-Salido . The Dynamic Effects of Shocks to Labour Markets: Evidence from OECD Countries. Oxford Economic Papers 52,3-23 . 2000
  • Banerjee, A., Marcellino, M and C. Osbat. Testing for PPP: Should We Use Panel Data Methods?. . 2002
  • Beaudry, P. and F. Portier . News, Stock Prices and Economic Fluctuations. American Economic Review, 96, 1293-1307. 2006
  • Bernanke, B. and I. Mihov . Measuring Monetary Policy. Quarterly Journal of Economics, 113, 869-902 . 1998
  • Blanchard, O. and D. Quah. The Dynamic Effects of Aggregate Demand and Supply Disturbances. American Economic Review 79, 655-73 6. 1989
  • Blanchard, O. and R. Perotti . An Empirical Characterization of the Dynamic Effects of Changes in Government Spending and Taxes on Output. Quarterly Journal of Economics, 117, 1329-1368. 2002
  • Bullard, J. and J. Keating. The Long-Run Relationship Between Inflation and Output in Postwar Economics. Journal of Monetary Economics 36, 477-96 . 1995
  • Canova, F.. Vector Autoregressive Models: Specificatio, Estimation, Inference, and Forecasting. ch. 2 in Pesaran, M. H and M. Wickens (eds), Handbook of Applied Econometrics, Blackwell. 1995
  • Charnavoki, V. and J. Dolado. The Effects of Global Shocks on Small Commodity-Exporting Economies. New Evidence from Canada. American Economic Journal ¿Macro, 6(2), 207-237. . 2014
  • Chen, L., Dolado, J. and J. Gonzalo. Detecting Big Structural Breaks in Large Factor Models. Journal of Econometrics, 180, 30-48. 11. . 2014
  • Chen, L., Dolado, J. and J. Gonzalo. Quantile Factor Models. . 2017
  • Christiano, L.J., Eichenbaum, M. and C. Evans . Monetary Policy Shocks: What Have we Learned and to What End?. in Taylor and Woodford, Handbook of Macroeconomics.. 2000
  • Christiano, L.J., Eichenbaum, M. and R. Vigfusson. The Response of Hours to a Technology shock: Evidence Based on Direct Measures of Technology. Journal of the European Economic Association, 2, 381-395. . 2004
  • Clarida, R., Galí, J and M. Gertler . Monetary Policy Rules in Practice: Some International Evidence. European Economic Review, 42, 1033- 68. 10. . 1998
  • Dolado, J. and J. Jimeno. The Causes of Spanish Unemployment: a Structural VAR Approach. European Economic Review 41, 1281-1307.. 1997
  • Dolado, J. and R. Maria-Dolores . Evaluating Changes in The Bank of Spain's Interest Rate Target: An Alternative Approach Using Marked Point Processes . Oxford Bulletin of Economics& Statistics, 64, 159-82. . 2002
  • Dolado, J., Gonzalo, J. and L. Mayoral . A Fractional Dickey-Fuller Test for Unit Roots. Econometrica, 70, 1963-2006. . 2002
  • Dolado, J., R. Maria-Dolores and F.J. Ruge-Murcia. Nonlinear Monetary Policy Rules: Some New Evidence for the U.S.. Studies in Nonlinear Dynamics and Econometrics, 8, (3). . 2004
  • Dolado, J., R. Maria-Dolores and M. Naveira . Are Monetary-policy Reaction Functions Asymmetric ?: The Role of Nonlinearity in the Phillips Curve. European Economic Review, 49, 485-503. . 2005
  • Erceg, C. J., Guerreri, L. and C. Gust. Can Long-Run Restrictions Identify Technology Shocks?. Journal of the European Economic Association, 3. . 2005
  • Fernández-Villaverde, J. Guerrón-Qintana., P. and J.F. Rubio-Ramírez . Reading the Recent Monetary History of the United States, 1959-2007. Review Federal Reserve Bank of St. Louis, issue May, pp. 311-338, 92, 1-28.. 2010
  • Fernández-Villaverde, J., Rubio-Ramirez, J. F, Sargent, T. and M. Watson . A, B, C, (and D)s for Understanding VARs. American Economic Review 97, 1021-1026.. 2007
  • Galí, J . Technology, Employment and the Business Cycle: Do Technology Shocks Explain Aggregate Fluctuations? . American Economic Review, 89, 249-271.. 1999
  • Galí, J and M. Gertler . Inflation Dynamics: A Structural Econometric Analysis. Journal of Monetary Economics, 44, 195-222. . 1999
  • Galí, J. . The Return of the Wage Phillips Curve. Journal of the European Economic Association, 9, 436-461. . 2011
  • Galí, J. . Notes for a New Guide to Keynes (I): Wages, Aggregate Demand, and Employment. Journal of the European Economic Association, 1(5) 973-1003. . 2013
  • Hamilton, J.. A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle. Econometrica 57, 357-84. . 1989
  • Jermann, U. and V. Quadrini. Macroeconomic Effects of Financial Shocks. American Economic Review, 102, 2012.. 2012
  • Johansen, S. and K. Juselius . Maximum Likelihood Estimation and Inference on Cointegration: With Applications to the Demand for Money. Oxford Bulletin of Economics & Statistics 52, 169-210. . 1990
  • Johansen, S. and M. O. Nielsen . Likelihood Inference for a Fractionally Cointegrated Vector Autoregressive Model. Econometrica, 80, 2667-2733. . 2012
  • Koenker, R, and K.F. Hallock. Quantile Regression. Journal of Economic Perspectives 15 (4), 143-156. 2001
  • Lubik, T. . Estimating a Search and Matching Model of the Aggregate Labor Market. Richmond Fed Economic Quarterly, 95, 101-120 . 2009
  • Mertens, K. and M. Ravn . A Reconciliation of SVAR and Narrative Estimates of Tax Multipliers. Journal of Monetary Economics, 68, S1-S19. . 2014
  • Mullainathan, S. and J. Spiess . Machine Learning: An Applied Econometric Approach. Journal of Economic Perspectives 31 (2), 87-106. 2017
  • Phillips, P.C.B and J. Pu . Dating the Timeline of Financial Bubbles during the Subprime Crisis. Quantitative Economics, 1(2): 455-491. . 2010
  • Stock, J. and M. Watson. Forecasting Using Principal Components from a Large Number of Predictors. Journal of the American Statistical Associatio. 2002
  • Uhlig, H. . What Are the Effects of Monetary Policy on Output? Results from an Agnostic Identification Procedure. Journal of Monetary Economics, 2005, 52(2), pp. 381-419.. 2005
Recursos electrónicosElectronic Resources *
Detailed subject contents or complementary information about assessment system of B.T.
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The course syllabus and the academic weekly planning may change due academic events or other reasons.