Features of Effective Central Banks

The central bank of a country has the core function of managing the monetary policy of the country. They have the challenge of controlling inflation and maintaining price stability. In order to be effective in their core functions, central banks need to have three essential qualities:

Independence

In order to be effective, a central bank must be able to operate independently, and should specially be free from any political influence.

Political parties and central banks may sometimes have opposing goals. For example, if inflation is high, the central banks will want to curb it by reducing the money supply. This can decrease economic growth and may also affect employment. However, politicians may want to boost economic activity and increase employment. If these politicians can influence the central bank, then it will fail in effectively curbing inflation.

Independence should be both operational independence and target independence. Operational independence means the central bank can independently determine the policy rate. Target independence means the central bank can independently set the target inflation rates, time period to achieve it, etc.

Credibility

The second important feature is credibility. People of the country should believe the measures taken by the central bank. To do so, the central banks should also follow their own stated goals.

Transparency

Transparency also helps the central bank in gaining credibility. Transparency means that the central bank periodically discloses the economic environment by publishing reports with important statistics. In the reports, the effective central banks also provide their views on the economic indicators used in setting their monetary policy and how they will be used.

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Data Science in Finance: 9-Book Bundle

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Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.

What's Included:

  • Getting Started with R
  • R Programming for Data Science
  • Data Visualization with R
  • Financial Time Series Analysis with R
  • Quantitative Trading Strategies with R
  • Derivatives with R
  • Credit Risk Modelling With R
  • Python for Data Science
  • Machine Learning in Finance using Python

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