Tools for Implementing Monetary Policy

The central bank of a country employs several tools to implement the country's chosen monetary policy. This article discusses the three primary policy tools used by central banks.

Open Market Operations

Under its open market operations, the central bank engages in buying and selling government securities to increase or decrease the monetary base.

  • Open Market Purchases: The central bank buys government securities to increase the monetary base.
  • Open Market Sales: The central bank sells government securities to decrease the monetary base.

In the US, open market operations are the most important tool used by the Fed, under which it buys and sells US government securities, especially the US Treasury bills. These trades are executed at the Open Market Desk of Federal Reserve Bank of New York.

Such open market operations permanently affect the monetary base in the country. However, sometimes there may be a need to change the monetary base only temporarily. In such case, the following types of transactions are used.

  • Repurchase Agreements (Repos): Under repo transactions, the central bank (Fed in US) purchases securities with a promise that the seller will repurchase them on a specific date at a specific price. The time period is usually two weeks. A repo temporarily increases the money base.
  • Reverse Repos: This is the reverse of a repo, where the central bank (Fed in US) sells securities with a promise that the buyer will sell them back on a specific date at a specific price. A reverse repo temporarily decreases the money base.

Open market operations have several advantages such as, it is in direct control of the central bank, can be conducted quickly, in any size they want, and are easily reversible.

Discount Rates

When banks have temporary shortage of funds, they borrow funds from the central bank. Such a loan is called a discount loan and the bank is said to have received a loan at the "discount window".

The central bank (Fed in US) can change these discount rates to influence the volume of these discount loans. An increase in the discount rate makes these loans less attractive and the volume decreases, and vice verse.

These discount loans have the advantage that they allow the central bank to become the lender of last resort during financial crisis. However, they also have the disadvantage that it's not in full control of the central bank. Even if the rates are increased, the central bank cannot be sure of how much discount loans will be demanded.

In the US, this is called the discount rate, while in Europe the ECB called it refinancing rate. This rate should not be confused with the Fed Fund rate, which is the rate at which the banks lend to each other.

Changes in Reserve Requirements

The central bank can also change the required reserve ratio, which will change the money supply in the economy. An increase in reserve requirement decreases the funds available for lending, which tends to increase the interest rates. Similarly, a decrease in reserve requirements leads to an increase in funds available for lending, which tends to decrease interest rates.

A disadvantage with this method is that if reserve ratio is increased, the banks may not have enough funds in reserve and will have to borrow, sell securities or reduce loans to increase their reserves. This can be costly and disruptive.

Among these three methods, the open market operations are considered the best monetary policy tool.

Related Downloads

Data Science in Finance: 9-Book Bundle

Data Science in Finance Book Bundle

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

Each book includes PDFs, explanations, instructions, data files, and R code for all examples.

Get the Bundle for $29 (Regular $57)
JOIN 30,000 DATA PROFESSIONALS

Free Guides - Getting Started with R and Python

Enter your name and email address below and we will email you the guides for R programming and Python.

Data Science in Finance: 9-Book Bundle

Data Science in Finance Book Bundle

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

Each book comes with PDFs, detailed explanations, step-by-step instructions, data files, and complete downloadable R code for all examples.