We follow Belongia and Ireland (2021) and investigate the role that the Center for Financial Stability credit card-augmented Divisia monetary aggregates could play in monetary policy and business cycle analysis. We use Bayesian methods to estimate a structural VAR under priors that reflect Keynesian channels of monetary transmission, but produce posterior distributions for the structural parameters consistent with classical channels. We also find that valuable information is contained in the credit-augmented Divisia monetary aggregates and that they perform even better than the conventional Divisia aggregates, in terms of highlighting the role of the money supply in aggregate demand.

This paper identifies several ways in which “measurement matters” in detecting quantity-theoretic linkages between money growth and inflation in recent data from the Euro Area, United Kingdom, and USA. Elaborating on the “Barnett critique,” it uses Divisia aggregates in place of their simple-sum counterparts to gauge the effects that monetary expansion or contraction is having on inflationary pressures. It also uses one-sided time series filtering techniques to track, in real time, slowly shifting trends in velocity and real economic growth that would otherwise weaken the statistical money growth-inflation relationship. Finally, it documents how measures of inflation based on GDP were distorted severely, especially in the EA and UK, during the 2020 economic closures. Using measures based on consumption instead, estimates from the P-star model confirm that changes in money growth have strong predictive power for subsequent movements in inflation.

We use the New Keynesian Dynamic Stochastic General Equilibrium (DSGE) framework and Vector Autoregressive (VAR) to investigate the usefulness and relevancy of monetary services, augmented to include credit card transaction services. We use the new credit-card-augmented Divisia monetary aggregates in the models to further the existing research on their usefulness and relevancy. In this research, we compare three different monetary aggregates within the New Keynesian framework: (1) the aggregation-theoretic “true” monetary aggregate, (2) the credit-card-augmented Divisia monetary aggregate, and (3) the simple sum monetary aggregate.

We acquire the following primary results. (1) The credit-card-augmented Divisia monetary aggregate tracks the theoretical (true) monetary aggregate, while simple sum does not. Although this result would be expected from the theory in classical economic models, the result is not an immediate implication of the theory in New Keynesian models and therefore needs empirical confirmation. (2) Under the recursive VAR framework, the credit-card-augmented Divisia monetary aggregate serves as a preferable monetary policy indicator compared to the traditional federal funds rate. (3) On theoretical grounds, we find that the separability condition for existence of a monetary aggregator function could fail, if credit card deferred payment services were excluded from the monetary services block, unless all markets are perfect.

This paper assesses the information content and predictive capabilities of Divisia monetary indicators concerning sector-specific economic activities. Although existing evidence strongly supports the informative nature and predictive potential of various Divisia indicators at an aggregate level, studies focusing on Divisia information content for specific industries are notably sparse. Sector-level data provide a more detailed insight into economic and labor market dynamics. By analyzing comprehensive sector-specific data on real GDP, value added, employment, and unemployment rates across thirteen diverse sectors in the United States, this paper investigates the predictive abilities of narrow and broad Divisia money across three categories (original, credit card-augmented, and credit card-augmented inside money). The results show that narrow Divisia money serve as robust predictors of sector-specific economic and labor market indicators, often surpassing the predictive capacity of the conventional Fed funds rate and slightly outperforming broad Divisia measures in relation to these indicators.

A large literature has shown money demand functions constructed from simple-sum aggregates are unstable. We revisit the controversy surrounding the instability of money demand by examining cointegrating income-money relationships with the Divisia monetary aggregates for the U.S., and compare them with their simple-sum counterparts. We innovate by conducting a more granular analysis of various monetary assets and their associated user costs. We find characterizing money demand with simple-sum measures only works well in a period preceding 1980. Divisia aggregates, their components, and their user costs provide a more reliable interpretation of money demand. Subsample analysis across 1980 and 2008 suggests the instability of money demand is a matter of measurement rather than a consequence of a structural change in agents’ preference for monetary assets.

The paper builds a parsimonious US business cycle SVARMA model, establishing identification conditions for independent monetary shocks. The SVARMA model, utilizing Divisia M3 and Divisia M4, is compared to the simple sum M2. The monetary rule with Divisia M3 yields theoretically consistent results marked by the absence of the usual price and liquidity puzzles. As the Federal Reserve (Fed) took a more hawkish approach to curb inflation, significant increases in US interest rates and declines in monetary aggregates were largely influenced by the Fed’s reaction function, which incorporates the Divisia M3 monetary rule. Findings emphasize the monetary impact on the business cycle, highlighting the significance of Divisia monetary aggregates. Historical and variance decompositions reveal diverse, dynamic effects of monetary shocks on macroeconomic variables. The SVARMA model with Divisia M3 and M4 demonstrates superior performance over simple sum M2 in capturing the time path of monetary shocks.

This paper studies the dynamic interactions between the money supply and the shape of the yield curve in the context of a regime-switching latent factor model. Estimates show that the money supply has important implications for the level, slope, and curvature of the yield curve. Moreover, the Divisia aggregates can provide more information than simple-sum aggregates based on parameter estimates and impulse response functions in understanding the dynamics of the yield curve. The favored broad Divisia aggregate could especially be associated with changes in the yield curve’s level, slope, and curvature over the business cycle. Therefore, this paper highlights the important role of Divisia aggregates in the linkage between financial markets and monetary policy.

We construct a Divisia money measure for U.K. households and private non-financial corporations and a corresponding dual user cost index employing a consistent methodology from 1977 up to the present. Our joint construction of both the Divisia quantity index and the Divisia price dual facilitates an investigation of structural vector autoregresssion models (SVARs) over a long sample period of the type of non-recursive identifications explored by Belongia and Ireland (2016, 2018), as well as the block triangular specification advanced by Keating et al. (2019). An examination of the U.K. economy reveals that structures that consider a short-term interest rate to be the monetary policy indicator generate unremitting price puzzles. In contrast, we find sensible economic responses in various specifications that treat our Divisia measure as the indicator variable.

Using US quarterly data (1967–2023), including inflation’s post-pandemic surge and decline alongside monetary policies characterized by quantitative easing before refocusing on the 2% target, we utilize traditional and novel econometric tools to assess the stability of key macroeconomic variables’ responses to monetary shocks. Our findings confirm the relevance of a broad Divisia aggregate in understanding monetary policy transmission and highlight its empirical importance in explaining output and price dynamics across decades. Time-varying impulse response functions (IRFs) reveal consistent and puzzle-free price responses to Divisia-based monetary shocks throughout the sample, aligning with theory. Time-varying IRFs indicate that pandemic-related outliers in GDP (2020Q2) do not disrupt results. In contrast, Fed Funds rate or shadow policy interest rate shocks often yield puzzling outcomes across earlier and extended periods.