6 resultados para MONETARY-POLICY

em Aston University Research Archive


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Using bank-level data from India, we examine the impact of ownership on the reaction of banks to monetary policy, and also test whether the reaction of different types of banks to monetary policy changes is different in easy and tight policy regimes. Our results suggest that there are considerable differences in the reactions of different types of banks to monetary policy initiatives of the central bank, and that the bank lending channel of monetary policy is likely to be much more effective in a tight money period than in an easy money period. We also find differences in impact of monetary policy changes on less risky short-term and more risky medium-term lending. We discuss the policy implications of the findings.

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We estimate the central bank policy preferences for the European Monetary Union and for the UK. In doing so, we extend the theoretical framework suggested by Cecchetti etal. (TheManchesterSchool, Vol. 70 (2002), pp. 596-618), by assuming that policy preferences change across different regimes. Our empirical results suggest that the weight that policy makers put on inflation is typically profound. Furthermore, it appears that volatility shifts of the economic disturbances are the main factor, which generates variation in policy preferences.

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Failure to detect or account for structural changes in economic modelling can lead to misleading policy inferences, which can be perilous, especially for the more fragile economies of developing countries. Using three potential monetary policy instruments (Money Base, M0, and Reserve Money) for 13 member-states of the CFA Franc zone over the period 1989:11-2002:09, we investigate the magnitude of information extracted by employing data-driven techniques when analyzing breaks in time-series, rather than the simplifying practice of imposing policy implementation dates as break dates. The paper also tests Granger's (1980) aggregation theory and highlights some policy implications of the results.

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This paper demonstrates a mechanism whereby rules can be extracted from a feedforward neural network trained to characterize the inflation "pass-through" problem in American monetary policy, defined as the relationship between changes in the growth rate(s) of individual commodities and the economy-wide rate of growth of consumer prices. Monthly price data are encoded and used to train a group of candidate connectionist architectures. One candidate is selected for rule extraction, using a custom decompositional extraction algorithm that generates rules in human-readable and machine-executable form. Rule and network accuracy are compared, and comments are made on the relationships expressed within the discovered rules. The types of discovered relationships could be used to guide monetary policy decisions.

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Using a Markov switching unobserved component model we decompose the term premium of the North American CDX index into a permanent and a stationary component. We establish that the inversion of the CDX term premium is induced by sudden changes in the unobserved stationary component, which represents the evolution of the fundamentals underpinning the probability of default in the economy. We find evidence that the monetary policy response from the Fed during the crisis period was effective in reducing the volatility of the term premium. We also show that equity returns make a substantial contribution to the term premium over the entire sample period.