Money Matters: There is No Such Thing as a Money 'Supply'
Monetary literature remains plagued by references to money “supply” at a time when the endogeneity of money is becoming generally accepted. Money endogeneity is not a hypothesis; it is a fact, and one that has existed since a goldsmith-banker wrote out the first receipt (bank note) and handed it to a borrower (as opposed to a depositor of gold coins). The creation of money has always been endogenous, even under the Friedman-Schwartzian Monetarist fixed-money-rule model. Once this is accepted, then it is logical to refer to the quantity or stock of money, and to the supply of bank credit. The household, corporate and government sectors borrow from banks to consume (C) or invest (I), which are the major components of nominal GDP [C + I + net exports (= aggregate demand, AD)]. Domestic credit extension (DCE) thus represents the link between the monetary and real economies. Money creation is the outcome of the change in DCE; the latter, not the change in M, approximates the change in AD (there are other influences). The essence of monetary policy is that the central bank controls the (reference) prime lending rate (PR) of banks via its policy interest rate (PIR), and thereby the demand for bank credit. It controls PR in normal (ie non-QE) times by manipulating the liquidity of banks to a borrowed reserves condition (actual, close to, or threat of), in order to make the PIR effective. The causation path is clear.
Money Creation: Misconceptions: It Begins with a New Deposit
Founded on the money multiplier, the imminent demise of which is not overstated, there exists a profound misconception: that money creation begins with a new deposit. In many cases the source of the new deposit is not specified, and somehow the recipient bank acquires reserves. In other cases the source is specified: cash (ie bank notes and/or coins), which does provide reserves, but the subsequent process is mistreated. The worst offense is to base one of the most significant issues in economics on a supply of bank notes and coins (which is limited because it is a non-interest-bearing asset, and which makes up 2-5% of M3). The analyses presented are partly correct: that new bank loans concurrently create new deposits (money), but the starting point is disingenuous. They also obscure the significant reserves-accommodating role of the central bank as well as the role of its policy interest rate in monetary policy, the essence of which is influencing the demand for bank loans through bank lending rates.
Complexity, Network-Decisions And Alternative Risk Premia: Some New Theories Of Structural Change And Portfolio Decisions.
Structural Change is the basis for many decisions such as government fiscal and monetary policies, government interventions, corporate-expenditure decisions, corporate strategic decisions, portfolio management decisions in finance; household allocation decisions, etc.. Structural change in industries and national economies is increasingly more difficult to detect partly because of the growth and dominance of Complex Systems and “Networks” in modern industries and economies – such Networks and Complex Systems include GVCs (global value chains), retail store networks; franchising networks; internet networks; services networks; credit-chains in industries; online social networks; etc.. The relationship between Complexity and Structural Change is well established in the physics, applied math and economic dynamics literatures. Traditional definitions and modeling of structural change have erroneously focused on changes in labor, technological progress, market share, and or capital – which are grossly inadequate in the new economy and post- global financial crisis (as confirmed by changes in the global retailing and housing industries and other industries). Also the modeling of structural change seems to be constrained by the availability of data, and often omits the relationship between structural change on one hand, and globalization, financial stability and international financial contagion. This article: i) introduces the Operations Strategy Model of structural change, explains how it differs from the Lewis Model of Structural Change; and explains the often omitted relationship between operations strategy (of companies and government agencies) and structural change; ii) introduces other new Complexity-based models/theories of Structural Change in industries; iii) reviews the relationships among Operations Research, Complexity and Structural Change; iv) explains the symbiotic relationship between structural change on one hand, and economic growth, financial stability, financial contagion and globalization; v) discusses the significant gap between academic research and practice and explains some issues and factors that should be considered in the development and testing of structural change models; vi) explains how alternative risk premia can be generated from new models of Structural Change.