MA Advanced Macroeconomics

This is the class website for University College Dublin module MA Advanced Macroeconomics (ECON 41620) taught by Prof. Karl Whelan in the Spring term of 2015.

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.

Information and Assessment

Here is a handout with a syllabus and a full reading list.

Here is a description of the final exam (last update March 26) and here is last year’s final exam.

Lecture Notes

1. Introduction: Time Series and Macroeconomics

2. Vector Autoregressions

3. Examples of VAR Studies

4. VARs With Long-Run Restrictions

5. Latent Variables: The Kalman Filter

6. Solving Models with Rational Expectations

7. The Real Business Cycle Model

8. The Phillips Curve

9. The Modern New-Keyesian Model (Technical background notes).

10. Estimating DSGE Models

11. The Smets-Wouters Model

 

RATS Programmes and Data

RATS programme generating charts for the first lecture. (Data set and required HP-filter programme.)

Two RATS programmes for Monetary Policy VARs: Identification One and Identification Two (Data Set).

RATS replication files for the Laubach-Williams paper.

RATS programme that produces RBC graphs in Part 7 (using Binder-Pesaran)

 

Dynare Programmes

Dynare is software that works with Matlab to solve and simulate DSGE models.  You can download it here and here is a page has a quick guide to getting started.

A large number of macroeconomic models from academic papers have been coded up in Dynare and made freely available, most notably at Volker Wieland’s Macro Model Database.  See below for a number of papers and corresponding Dynare programmes.

Programme for the RBC model in Part 7

A simple new Keynesian model.

Dynare can also estimate DSGE models using Bayesian techniques. Here is a link to a working example, including data, by Joao Madeira from the University of York.

 

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.

Simon Jackman (2000). Estimation and Inference via Bayesian Simulation: An Introduction to Markov Chain Monte Carlo.

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.  (Working paper version)

St. Louis Fed: Oil Prices: Is Supply or Demand behind the Slump?

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).

Christina Romer and David Romer (2004). A New Measure of Monetary Shocks: Derivation and Implications

Olivier Coibion (2011). Are the Eff ects of Monetary Policy Shocks Big or Small?”

Olivier Blanchard and Danny Quah (1989). The Dynamic Effects of Aggregate Demand and Supply Disturbances (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.

Thomas Laubach and John C. Williams (2001). Measuring the Natural Rate of Interest. Updated estimates from the Laubach-Williams model from the San Francisco Fed.

Robert Lucas (1976). Econometric Policy Evaluation: A Critique.

Nicholas Higham and Hyun-Min Him (2002). Numerical Analysis of a Quadratic Matrix Equation.

Harald Uhlig (1995). A Toolkit for Analyzing Nonlinear Dynamic Stochastic Models Easily.

Timothy Cogley and James Nason (1995). Output Dynamics in Real-Business-Cycle Models.

Milton Friedman: The Role of Monetary Policy.

Robert J. Gordon: The History of the Phillips Curve: Consensus and Bifurcation

John M. Roberts. New Keynesian Economics and the Phillips Curve (JSTOR).

Richard Clarida, Jordi Gali, and Mark Gertler (1999). The Science of Monetary Policy: A New Keynesian Perspective.

Jordi Gali and Mark Gertler (1999). Inflation Dynamics: A Structural Econometric Analysis

Jeremy Rudd and Karl Whelan (2005). Modelling Inflation Dynamics: A Critical Review of Recent Research

Julio Rotemberg and Michael Woodford (1997). An Optimization-Based Econometric Framework for the Evaluation of Monetary Policy.

Alistair Hall, Atsushi Inoue, James Nason and Barbara Rossi (2010). Information Criteria for Impulse Response Function Matching Estimation of DSGE Models.

Peter Ireland (2004).  A Method for Taking Models to the Data.

Francisco Ruge-Murcia (2007). Methods to Estimate Dynamic Stochastic General Equilibrium Models.

Jesus Fernández-Villaverde (2009). The Econometrics of DGSE Models.

Frank Smets and Rafael Wouters (2007). Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach. (ECB working paper version here; appendix with full model here).

Chris Sims at INET conference: How Empirical Evidence Does or Does Not Influence Economic Thinking. Video and slides.