Lecture 18 - Monetary Policy

To begin the lecture, Professor Shiller explores the origins of central banking, from the goldsmith bankers in the United Kingdom to the founding of the Bank of England in 1694, which was a private institution that created stability in the U.K. financial system by requiring other banks to have deposits in it.

Turning his attention to the U.S., Professor Shiller outlines the evolution of its banking system from the Suffolk System, via the National Banking era, to the founding of the Federal Reserve System in 1913. After presenting approaches to central banking in the European Union and in Japan, he emphasizes the federal funds rate, targeted by the Federal Open Market Committee, as well as the recent change to pay interest on reserve balances at the Federal Reserve, enacted by the Emergency Economic Stabilization Act from 2008, as important tools of U.S. monetary policy.

After elaborating on reserve requirements, which are liability-based restrictions, and capital requirements, which are asset-based, he provides a simple, illustrative example that delivers an important intuition about the difficulties that banks have faced during the recent crisis from 2007-2008. This leads to Professor Shiller's concluding remarks about regulatory approaches to the prevention of future banking crises.

1. The Origins of Central Banking: The Bank of England
2. The Suffolk System and the National Banking Era in the U.S.
3. The Founding of the Federal Reserve System
4. The Move to Make Central Banks Independent
5. U.S. Monetary Policy: Federal Funds Rate and Reserve Requirements
6. Capital Requirements, Basel III and Rating Agencies
7. Capital Requirements and Reserve Requirements in the Context of a Simple Example
8. Capital Requirements to Stabilize the Financial System in Crisis Times

https://www.youtube.com/watch?v=\_SpIaGTq0u8

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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.