Real money demand and supply meets Federal debt

Abstract

This article presents the empirical results of an econometric investigation of the demand and supply of real money (M2) with real Federal debt in the USA economy as a Vector Auto-Regressions (VARs) system. This allows the study to focus on the crucial variables of fiscal and monetary policies, specifically the debt (wealth-creating instruments), the real monetary base and the relevant rates of interest. The long- and short-run effects of these variables over the quarterly data, spanning from 1960 to 2007, are analysed. Clearly, this is a well-researched field, where others have published excellent work, although this investigation differs in its choice of variables. The idea is to explain the dynamics and mechanisms of adjustment, generally left unexplained by economic theory.

Notes

¹For an overview of the VARs analysis, see Juselius (2006).

²Given the large theoretical discussion as well as the empirical evidence reported by De Grauwe and Polan (2005) and Morana and Bagliano (2007), it was decided to include inflation into the ‘picture’. For an overview, see Chapter 8 in Bårdsen et al. (2005).

³Assuming the term structure of interest, the study adopts data on 3-month, 10-year and 20-year as well as 30-year yields on Treasury Bills, although initially there were several gaps that needed to be estimated. The study filled the gap between 1987Q1 and 1993Q3 by using the 3-month, the 10-year and the 30-year as interest rate differences to explain the changes in the 20-year rate. Then the analysis employed differences in the 3-month, the 10-year and 20-year rates (including the estimates) to derive the 30-year over the period 1959Q1 to 1976Q4 in the first instance, and then subsequently between 2002Q1 and 2005Q4 to complete the series.

⁴It was found that it was possible to substitute the real debt sold to the Federal Reserve System (P_B Δ B_f ) instead of the real monetary base, although the real high-powered money variable produced superior results. It was, however, not possible to include both because of the one-to-one similarity between the two that led to multicollinearity.