This paper investigates the optimal monetary instrument in a New-Keynesian model with multiple monetary assets. We compare a standard interest rate rule to a k-percent rule for three alternative monetary aggregates determined within our model: the monetary base, the simple sum measure of money, and the Divisia measure. Welfare results are striking. While the interest rate dominates the other two monetary aggregate k-percent rules, the Divisia k-percent rule outperforms the interest rate rule. Next we study the ability of Granger Causality tests – in the context of data generated from our model – to correctly identify welfare improving instruments. We find the interest rate Granger Causes both output and prices at extremely high significance levels. The same result is obtained for monetary base and the simple-sum monetary aggregate. The test results for Divisia are the weakest as Divisia fails to Granger Cause prices. We conclude that if the choice of instrument is based solely on its propensity to Granger Cause macroeconomic targets, a central bank may choose an inferior policy instrument.

This paper derives the user cost of monetary assets and credit card services with interest rate risk under the assumption of intertemporal non-separability. Barnett and Su (2016) derived theory permitting inclusion of credit card transaction services into Divisia monetary aggregates. The risk adjustment in their theory is based on consumption capital asset pricing model (CCAPM) under intertemporal separability. The equity premium puzzle focusses on downward bias in the CCAPM risk adjustment to common stock returns. Despite the high risk of credit card interest rates, the risk adjustment under the CCAPM assumption of intertemporal separability might nevertheless be similarly small. While the known downward bias of CCAPM risk adjustments are of little concern with Divisia monetary aggregates containing only low risk monetary assets, that downward bias cannot be ignored, once high risk credit card services are included. We believe that extending to intertemporal non-separability could provide a non-negligible risk adjustment, as has been emphasized by Barnett and Wu (2015). In this paper, we extend the credit-card-augmented Divisia monetary quantity aggregates to the case of risk aversion and intertemporal non-separability in consumption. Our results are for the “representative consumer” aggregated over all consumers. While credit-card interest-rate risk may be low for some consumers, the volatility of credit card interest rates for the representative consumer is high, as reflected by the high volatility of the Federal Reserve’s data on credit card interest rates aggregated over consumers. One method of introducing intertemporal non-separability is to assume habit formation. We explore that possibility.

We propose a distress measure for national banking systems that incorporates not only banks’ CDS spreads, but also how they interact with the rest of the global financial system via multiple linkage types. The measure is based on a tensor decomposition method that extracts an adjacency matrix from a multi-layer network, measured using banks’ foreign exposures obtained from the BIS international banking statistics. Based on this adjacency matrix, we develop a new network centrality measure that can be interpreted in terms of a banking system's credit risk or funding risk.