UID:
almafu_9958120569902883
Umfang:
1 online resource (54 p.)
ISBN:
9786612846090
,
9781462379958
,
1462379958
,
9781455298983
,
1455298980
,
9781282846098
,
1282846094
,
9781455201174
,
1455201170
Serie:
IMF Working Papers
Inhalt:
Many low-income countries continue to describe their monetary policy framework in terms of targets on monetary aggregates. This contrasts with most modern discussions of monetary policy, and with most practice. We extend the new-Keynesian model to provide a role for “M” in the conduct of monetary policy, and examine the conditions under which some adherence to money targets is optimal. In the spirit of Poole (1970), this role is based on the incompleteness of information available to the central bank, a pervasive issues in these countries. Ex-ante announcements/forecasts for money growth are consistent with a Taylor rule for the relevant short-term interest rate. Ex-post, the policy maker must choose his relative adherence to interest rate and money growth targets. Drawing on the method in Svensson and Woodford (2004), we show that the optimal adherence to ex-ante targets is equivalent to a signal extraction problem where the central bank uses the money market information to update its estimate of the state of the economy. We estimate the model, using Bayesian methods, for Tanzania, Uganda (both de jure money targeters), and Ghana (a de jure inflation targeter), and compare the de facto adherence to targets with the optimal use of money market information in each country.
Anmerkung:
"June 2010".
,
Cover Page; Title Page; Copyright Page; Contents; I. Introduction; II. The Model; A. Monetary Policy Under Complete Information; B. Monetary Policy Under Incomplete Information; III. Estimating the Model; A. Bayesian Estimation Strategy; Table 1. Calibrated Parameters; Table 2. Prior and Posterior Distributions for Parameters and Volatilities: Ghana; Table 3. Prior and Posterior Distributions for Parameters and Volatilities: Uganda; Table 4. Prior and Posterior Distributions for Parameters and Volatilities: Tanzania; Table 5. Estimated and Optimal lambda (λ); B. Results
,
IV. Deriving the Optimal LambdaA. Optimal λ Results for Ghana, Tanzania and Uganda; Figure 1. Uganda, Sensitivity Analysis for the Optimal Lambda; Table 6. Inflation and Output Gap Volatility; V. Alternative Rationalizations for the Role of Money in Policy Frameworks in LICs; VI. Conclusion; References; Footnotes
Sprache:
Englisch
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