This thesis identifies monetary policy shocks employing vector autoregressions (VAR) for open economies, using Canada and the UK as case studies. The main argument is that if the information set in the monetary policy reaction function in a VAR model is different from that of a central bank, then the policy reaction function is incorrectly identified. The incorrect policy function then yields mis-measured policy shocks, which in turn generates misleading results. First I examine the macroeconomic variables a central bank considers to make monetary policy decisions and then I formulate monetary policy functions by using those variables. Having identified the monetary policy function by incorporating the set of variables actually observed by the central bank, this thesis concludes that most of the previous puzzling results about the effects of monetary policy shocks might be due to incorrectly identifying the policy reaction function.
Sims (1980) suggested the use of impulse responses from the VAR model for policy analysis. Subsequently, a great deal of VAR literature has been developed to better estimate the impulse responses of various macroeconomic variables due to monetary policy shocks (see Christiano, Eichenbaum and Evans (1999) for details). Bernanke and Blinder (1992) argued that innovations in the federal funds rate, identified in a recursive approach, are in some respects better measures of monetary policy shocks than are innovations in monetary aggregates for the US.
This argument was challenged by Gordon and Leeper (1994). Using innovations both in the federal funds rate and monetary aggregates in a recursive approach, they found dynamic responses that are at odds with what we expect from monetary policy shocks. Identifying contractionary policy shocks with innovations in the ratio of non-borrowed reserves to total reserves in a recursive VAR model, Eichenbaum and Evans (1995) reported a persistent appreciation of the US dollar for a prolonged period of time. Using the same policy instrument in a recursive VAR approach for the US, Strongin (1995) found a strong liquidity effect but an insignificant effect on the price level due to monetary policy shocks.
Sims (1992) pointed out that innovations in any type of monetary aggregates may not correctly represent changes in monetary policy, since they might reflect some other shocks in the economy, such as the money demand shocks. Therefore he suggested using innovations in short-term interest rates as policy shocks. But using short-term interest rates as policy instruments in a recursive approach for G-7 countries, Grilli and Roubini (1995) found that home currencies depreciate in response to innovations in home interest rates for every country except the US.
Contents
Abstract
Co-Authorship
Dedication
Acknowledgements
List of Figures
Chapter 1 Introduction
Chapter 2 Real and Nominal Effects of Monetary Policy Shocks
2.1 Introduction
2.2 Nominal Interest Rate Decomposition
2.3 Canadian Monthly Data
2.4 Inflationary Expectations and the Ex ante Real Interest Rate
2.5 The Identification of Monetary Policy Shocks
2.6 Estimation
- 2.6.1 The Basic Model
2.6.2 The Augmented Model
2.7 Conclusion
Chapter 3 Monetary Transmission Mechanism in a Small Open Economy: A Bayesian Structural VAR Approach
3.1 Introduction
3.3 Canadian Monthly Data
3.4 A Structural VAR Model with Block Exogeneity
- 3.4.1 Identification of Monetary Policy
3.4.2 A Bayesian Approach of Imposing Restrictions and Estimation
3.5 Empirical Evidence of the Effects of Monetary Policy Shocks
3.6 Conclusion
Chapter 4 Identifying a Forward-looking Monetary Policy in an Open Economy
4.1 Introduction
4.2 Research Context
4.3 Monthly Data for the UK
4.4 Identification of the Forward-Looking Monetary Policy in a Structural VAR Model
4.5 Empirical Evidence of the Effects of Monetary Policy Shocks
4.6 Conclusion
Bibliography
