An 18th century French banker and philosopher named Richard Cantillon noticed an early version of this phenomenon in a book he wrote called ‘An Essay on Economic Theory.’ His basic theory was that who benefits when the state prints a bunch of money is based on the institutional setup of that state. In the 18th century, this meant that the closer you were to the king and the wealthy, the more you benefitted, and the further away you were, the more you were harmed. Money, in other words, is not neutral. This general observation, that money printing has distributional consequences that operate through the price system, is known as the “Cantillon Effect.”
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This theory doesn’t imply that money creation is always biased towards the powerful, only that how money travels matter. There is no inherent money neutrality, such neutrality must be constructed by institutional arrangements. Much of the New Deal in the 1930s and 1940s was designed to build alternative channels for lending so that small business, industry and individuals could have access to money as quickly as big banks.
The Reconstruction Finance Corporation, government procurement, the Federal Housing Administration, the Federal Reserve, agricultural credit supports, Federal Home Loan Banks, credit unions, and regulations like Regulation Q were all mechanisms to insure the flow of money would be neutral. The International Monetary Fund was originally created to ensure money neutrality on a global basis.
So we can now see that the hollowing out or subversion of these institutions since the 1980s is designed to ensure they would be non-neutral, and tilted towards the powerful. Since 1981, increasingly the only channels that work to move money creation are the Federal Reserve to Wall Street, as well as the backstop to mortgages, who could get money to new homebuyers through mortgage lenders. Housing has been a key driver in both recessions and recoveries for a lot of reasons, but also for a simple one. It’s one of the few ways to get money into the hands of normal people in America at scale.
From the article:
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