Supplementary Appendix: Monetary Regimes, Money Supply and the US Business Cycle Since 1959: Implications for Monetary Policy Today

Supplementary Appendix: Monetary Regimes, Money Supply and the US Business Cycle Since 1959: Implications for Monetary Policy Today

Supplementary Appendix: Monetary Regimes, Money Supply and the US Business Cycle since 1959: Implications for Monetary Policy Today Hylton Hollander∗ and Lars Christenseny August 8, 2018 ∗Corresponding author: Department of Economics, Stellenbosch University, Stellenbosch, 7602, South Africa. E-mail address: [email protected]. yResearch Associate, Department of Economics, Stellenbosch University. Founder and owner of Markets and Money Advisory. Senior Fellow at London's Adam Smith Institute. 1 A Implications of the `liquidity trap' hypothesis and the FTPL In the current economic state of low interest rates and ineffective monetary policy some notable hypotheses have gained traction. One strand of literature, in particular, posits a theory of price level determination based on the interaction between fiscal policy and monetary policy. Cochrane (2014) and Leeper(2016) form the argument by identifying three basic approaches to monetary policy and price level determination: money supply and demand in the spirit of the monetarist MV≡PY tradition; interest-rate controlling New-Keynesian models; and the fiscal theory of the price level (FTPL). Their important critique, as previously raised by Sargent and Wallace(1985), is that the economy is satiated with money when the return on money (or reserves) equals the return on risk-free assets (e.g., Treasury bills). That is, any amount of money will be held at this point, and exchanging treasuries for money has no effect on the economy|the price level is therefore indeterminant. In response to this state of the world, Cochrane(2014) and Leeper(2016) show that a determinant equilibrium necessitates an \active" fiscal policy.1 Indeed, Cochrane(2014) correctly emphasizes that this holds only in the current international monetary system of fiat money and central banks. But if the price level is the price of goods in terms of nominal (government) liabilities (money plus bonds), the question then begs: what determines the price level in a world of free banking with un-backed, de-centralized fiat money? Is there a more fundamental theory of price-level determination that precludes fiscal debt management and present discounted government deficits and surpluses? Understanding the interaction between fiscal and monetary policy certainly needs more atten- tion. Cochrane(2014, p. 78) emphasises the fiscal theory of the price level as follows: \In this way, the Treasury and the Fed acting together do, in fact, institute a system in which the government as a whole sets the interest rate it−1 and then sells whatever facevalue of the debt Bt−1 that [is demanded] . even though the Fed does not directly change the overall quantity of debt, and even though the Treasury seems to sell a fixed quantity, not at a fixed price." The model developed here could easily be extended to incorporate fiscal policy and the government budget (see, e.g., Schmitt-Groh´eand Uribe, 2007), but under the assumption that fiscal policy is \passive" it is not necessary: in Leeper's (1991; 2016) \Regime M" monetary policy controls inflation and fiscal pol- icy ensures government solvency (see also, Cochrane, 2014, p. 91). That said, Leeper's framework falls into the same trap identified by McCallum(1986, p. 156) in relation to Sargent and Wallace (1982), namely that the model \neglects the medium-of-exchange role of money, thereby negating 1\The aggregate price level is a relative price: it measures how much a basket of goods is worth in terms of nominal government liabilities|money plus bonds. This relative price must be determined by the interaction of supply and demand for these government liabilities." (Leeper, 2016, p. 2) 2 the possibility of distinguishing between monetary and non-monetary assets." In contrast, the model developed in Belongia and Ireland(2014) and Ireland(2014), based on Barnett's (1978; 1980) user cost of money and monetary aggregation theory, emphasizes the role of the true aggregate of monetary (liquidity) services demanded. Their shopping time model maintains the core New-Keynesian (IS-LM) framework and ensures that the opportunity cost on this true monetary aggregate is always positive|provided the risk-free rate is not zero. With regards to the zero lower bound, it is not immediately evident that money demand has no satiation point. While the threshold appears to be currently rather high in the market for reserves, Ireland(2009) shows evidence of a finite satiation point for broader monetary aggregates (also illustrated in Figure 1). As this is likely true, then even at zero nominal interest rates the true monetary aggregate| whether currency or highly liquid, risk-free assets|commands some positive finite transactions value (Yeager, 1986). In effect, all perfectly substitutable, perfectly liquid assets will inherit this valuable attribute. In the context of macroeconomic models, the demand for fiat money depends on whether we expect it will hold its exchange value in the future: its discounted present value. By backward induction, money would be valueless today if we knew with certainty that money will be valueless at some given date in the future. But if money has positive value in all future periods we can proceed. This is basically illustrated by assuming all wealth (assets) are in the households utility function, and their corresponding rate of return has some implicit transactions value, no matter the illiquidity or riskiness|someone, somewhere is willing to trade for that asset. This is effectively Say's Law: the supply of any good, including fiat money and specie, generates a demand for all other goods (see, e.g., Yeager(1986)). Further, I am essentially proposing some measure of \moneyness" attached to any item of value, to which, as it approaches perfect substitutability with money it will approach the finite value of liquidity (transactions) services. 3 B Descriptive statistics .20 .12 RR/TCD .08 RR/(TCD+CURR) .16 RR/M1 .04 RR/MZM .00 .12 -.04 -.08 .08 -.12 -.16 .04 -.20 -.24 .00 -.28 1960 1970 1980 1990 2000 2010 1960 1970 1980 1990 2000 2010 Figure B.1: Left panel: Effective reserve ratio (RRt=Mt = rrt). Right panel: Log-difference effective reserve ratio (RRt=MZMt = rrt). Sample: 1959Q1−2016Q03. C Simulation IRFs −3 m x 10 v p y 0.06 2 0.06 0.04 0.04 0.04 0 0.02 0.02 0.02 −2 0 0 0 5 10 15 20 5 10 15 20 5 10 15 20 5 10 15 20 −4 r int x 10 int_T pii 4 0 0 0.04 2 −0.02 −0.02 0.02 0 0 −0.04 −0.04 −0.02 −2 5 10 15 20 5 10 15 20 5 10 15 20 5 10 15 20 ytilde h fr 10 0.04 0.1 5 0.02 0.05 0 0 0 −5 5 10 15 20 5 10 15 20 5 10 15 20 Interest targeting (GM) regime (ν = 11; ν =12) Interest sensitive regime (ν = ν =1) Flexible prices (ν =ν =1) h fr h fr h fr Figure C.2: Positive money supply shock. 4 −3 m x 10 v p y 0.015 1 0 0.01 0.01 0 0 −0.01 0.005 −1 −0.01 0 −2 −0.02 −0.02 5 10 15 20 5 10 15 20 5 10 15 20 5 10 15 20 −3 −4 r x 10 int x 10 int_T pii 0.01 6 1 0.01 4 0 0 0.005 2 −1 −0.01 0 0 −2 −0.02 5 10 15 20 5 10 15 20 5 10 15 20 5 10 15 20 ytilde h fr 0.01 0 0 0 −0.01 −1 −0.01 −0.02 −0.02 −0.03 −2 5 10 15 20 5 10 15 20 5 10 15 20 Interest targeting (GM) regime (ν = 11; ν =12) Interest sensitive regime (ν =ν =1) Flexible prices (ν =ν =1) h fr h fr h fr Figure C.3: Positive money demand shock. −3 −3 −3 x 10 m x 10 v p x 10 y 10 −1 0.015 −2 8 −1.5 −4 0.01 6 −2 −6 4 −2.5 0.005 −8 2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12 −3 −4 x 10 r x 10 int pii rmc 2 4 0.02 0.02 3 0 0.01 0.01 2 −2 0 0 1 −4 0 −0.01 −0.01 2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12 −4 −3 x 10 h x 10 fr z n 0 −0.5 −0.005 0.01 −1 −1 −0.01 0.005 −2 −3 −1.5 −0.015 0 2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 8 10 12 Interest sensitive money rule Interest insensitive money rule Flexible prices Figure C.4: Negative technology shock. 5 D Estimation results D.1 Historical decompositions 0.4 2.5 Initial values Initial values 2 0.3 1.5 epsil_md epsil_md 0.2 1 epsil_ms epsil_ms 0.1 0.5 0 0 epsil_i epsil_i −0.5 −0.1 epsil_z epsil_z −1 0 20 40 60 80 100 120 140 160 180 0 20 40 60 80 100 120 140 160 180 Figure D.5: Historical decomposition (1959Q1−2007Q3): Output (left panel); Price-level (right panel). D.2 Estimation diagnostic statistics 6 SE_epsil_z SE_epsil_i SE_epsil_ms SE_epsil_md 2300 2260 2300 2300 2200 2200 2200 2240 2100 2100 2100 2000 2220 2000 2000 0.04 0.06 0.08 2.5 3 3.5 4 0.1 0.15 0.2 0.02 0.03 0.04 0.05 −3 x 10 eta_c eta_m eta_n alppha 2260 2260 2260 2260 2250 2250 2250 2250 2240 2240 2240 2240 2230 2230 2230 4 4.5 5 4 5 6 0.6 0.8 1 1.2 1.4 0.5 0.6 0.7 0.8 0.9 theta_p nu_h nu_fr rho_h 2400 2253 2300 2500 2200 2252 2200 2000 2000 2251 2100 1800 2250 2000 1500 0.85 0.9 0.95 0.4 0.6 0.8 30 40 50 60 0.5 0.6 0.7 0.8 0.9 rho_fr kapa_pi kapa_y rho_z 2255 2255 2254 2260 2250 2252 2250 2240 2245 2250 2245 2240 2248 2220 0.120.140.160.18 0.2 1 1.5 2 0.4 0.6 0.8 0.7 0.75 0.8 rho_i rho_ms rho_md 2255 2260 2255 2250 2250 2250 2240 2245 2230 2245 0.99750.9980.99850.9990.9995 0.82 0.84 0.86 0.88 0.9985 0.999 0.9995 log−post log−lik kernel SE_epsil_z SE_epsil_i SE_epsil_ms SE_epsil_md 1000 200 50 50 500 100 0 0 0 0 0.02 0.04 0.06 0.08 0.1 0.02 0.04 0.06 0.08 0.1 0.1 0.2 0.3 0.02 0.04 0.06 0.08 0.1 eta_c eta_m eta_n alppha 2 2 1 5 0.5 1 1 0 0 0 0 1 2 3 4 5 4 5 6 0 1 2 0.4 0.6 0.8 theta_p nu_h nu_fr rho_h 50 5 1 0.1 0 0 0 0 0.6 0.7 0.8 0.9 0 5 10 20 40 60 80 100 120 0.2 0.4 0.6 0.8 1 rho_fr kapa_pi kapa_y rho_z 10 2 20 5 1 1 10 0 0 0 0 0.2 0.4 0.6 0.8 0.5 1 1.5 2 2.5 0 0.5 1 0.5 0.6 0.7 0.8 0.9 rho_i rho_ms rho_md 400 20 500 200 10 0 0 0 0.98 0.99 1 0.5 0.6 0.7 0.8 0.9 0.98 0.99 1 Figure D.6: Top panel: log-data density.

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