The demand for money depends positively on the price level and real income, and negatively on nominal interest rates and wealth. In addition, since the amount of wealth in an economy is fixed, an individual's or firm's wealth is typically tied up between money and bonds. When one of these markets is in equilibrium, so is the other and resultantly money supply is equal to money demand at a particular interest rate. The interest rate affects the movement of the money supply, and Federal Reserve Bank policy influences the short-term interest rate. Monetary policy also affects the price level, while real income in turn affects the movement of money demand. The interaction of money supply and demand leads to a series of equilibriums in the money market. This paper is concerned with the forecasting of money demand changes relative to levels and using price level/inflation, real income, wealth, and interest rate as independent variables. Money demand is approximated by the quantity of M2 money stock, and the price level and interest rate are represented by the consumer price index and 3-month Treasury bills respectively. The forecasting tools used are neural networks and robust multiple linear regression. The efficacy and relative accuracy of the forecasts are determined by performance metrics correlation, root mean square error, and visual analysis. As expected, neural networks yielded a better overall forecast of the changes in money demand. © 2013 The Authors. Published by Elsevier B.V.
Joseph, A., Larrain, M., & Ottoo, R. (2013). Comparing the forecasts of money demand. In Procedia Computer Science (Vol. 20, pp. 478–483). Elsevier B.V. https://doi.org/10.1016/j.procs.2013.09.306