This is the class website for University College Dublin module MA Advanced Macroeconomics (ECON41620) taught by Prof. Karl Whelan in the Spring term of 2016.
The focus in this course will be on the methods that modern macroeconomics uses to model and understand time series fluctuations in the major macroeconomic variables. The first part of the course focuses on Vector Autoregression studies and Dynamic Stochastic General Equilibrium models. Later lectures focus on modelling the interactions between the financial sector and the macroeconomy.
Here is a handout with a syllabus and a full reading list.
Here is information on the midterm exam.
Here are guidelines on the format and content of the final exam.
Here is last year’s final exam
RATS Programmes and Data
RATS replication files for the Laubach-Williams paper.
Readings and Useful Links
John Cochrane (2005). Time Series for Macroeconomics and Finance (Chapters 2, 3, 5 and 7).
Christopher Sims (1980). Macroeconomics and Reality. (JSTOR).
Lutz Kilian (1998). Small-Sample Confidence Intervals for Impulse Response Functions.
Marta Bańbura, Domenico Giannone, and Lucrezia Reichlin (2008). Large Bayesian VARs.
Lutz Kilian (2009). Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market. (Here is the working paper version)
Christiane Baumeister and Lutz Killian (2016). Forty Years of Oil Price Fluctuations: Why the Price of Oil May Still Surprise Us.
Olivier Blanchard and Roberto Perotti (2002). An Empirical Characterization of the Dynamic Effects of Changes in Government Spending and Taxes on Output (JSTOR).
James Stock and Mark Watson (2001). Vector Autoregressions.
Glenn Rudebusch (1998). Do Measures of Monetary Policy in a Var Make Sense?(JSTOR).
Christopher Sims (1998). Comment on Glenn Rudebusch’s Do Measures of Monetary Policy in a Var Make Sense? (JSTOR).
Jordi Gali (1999). Technology, Employment and the Business Cycle: Do Technology Shocks Explain Aggregate Fluctuations? (JSTOR).
Karl Whelan (2009). Technology Shocks and Hours Worked: Checking for Robust Conclusions.