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Monetary policy analysis at a non-linear and a Bayesian framework
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Davradakis, Emmanuel (2004) Monetary policy analysis at a non-linear and a Bayesian framework. PhD thesis, University of Warwick.
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Official URL: http://webcat.warwick.ac.uk/record=b1750375~S15
Abstract
In this thesis, we examine potential non-linear behaviour in central banks’ response with regards to the instrument used for the conduct of monetary policy. The central bank of interest is the Bank of England (BoE). The model that is proposed here is a threshold model for the interest rate that encapsulates a random walk and a Taylor rule reaction function exhibited by the respective interest rate. We examined whether there is a threshold for inflation up to which interest rate exhibits a random walk behaviour, while above that threshold interest rate under consideration reverts to a forward-looking Taylor rule.
The analysis proceeds by examining the properties of a general model according to which the interest rate can be into three regimes depending on whether inflation takes values inside a band or outside that band. This model nests three distinct models, namely a two-regime two-Taylor rules model, a two-regime one- Taylor rule one-random walk model and a linear Taylor rule model. In this setup, we provided supportive empirical evidence for this non-linear behaviour of the interest rate, both prior and post the introduction of the inflation targeting scheme at the United Kingdom (UK).
At the final step of our analysis, we attempted to specify a model for narrow money demand Ml in the euro area in a non-linear context given the favorable leading indicators property Ml has with respect to real Gross Domestic Product (GDP) growth. The unsatisfactory performance of the conventional cointegrating analysis implied that potential sources for this might rest either in the short or in the long-run behavior of the money demand relationship. In the long-run side, we employed a Random Coefficients (RC) estimation of various money demand specifications that did not produce significant estimated coefficients. Respectively, for the short-run dynamics of the money demand relationship, we employed a Bayesian Vector Error Correction Model (BVECM) making use of the random walk averaging priors. This approach succeeded to capture reality in a more accurate way, in terms of the estimated income and interest rate elasticities. The proposed model outperformed in forecasting real money balances an Autoregressive (AR) Process and a Vector Error Correction Model (VECM) benchmark model. However, the BVECM proposed failed to outperform the benchmark models considered in forecasting the the logarithm of the GDP.
Item Type: | Thesis (PhD) | ||||
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Subjects: | H Social Sciences > HG Finance | ||||
Library of Congress Subject Headings (LCSH): | Monetary policy, Econometric models, Banks and banking, Banks and banking, Central | ||||
Official Date: | July 2004 | ||||
Dates: |
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Institution: | University of Warwick | ||||
Theses Department: | Department of Economics | ||||
Thesis Type: | PhD | ||||
Publication Status: | Unpublished | ||||
Supervisor(s)/Advisor: | Taylor, Mark P., 1958- , Elisson, Martin | ||||
Extent: | 224 leaves : charts | ||||
Language: | eng |
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