Abstract This paper tests the Milton Friedman hypothesis that money growth variability affects the velocity of money. It compares the Federal Reserve’s simple-sum monetary aggregates, the original (non-credit-card-augmented) Divisia aggregates, and the credit-augmented Divisia and credit-augmented Divisia inside monetary aggregates using two classes of empirical models. Standard Granger causality tests and a bivariate structural GARCH-in-Mean VAR model examine how money growth variability affects the consumption and income velocity of money. Using monthly data for the post-2006 period, when all monetary indicators are available, the findings reject the Friedman hypothesis when money supply volatility is modeled explicitly using recent advances in macroeconometrics and financial econometrics. This result is robust to a longer sample extending back to 1967 with monthly and quarterly data, across alternative model specifications. From a policy standpoint, this enhances the predictability and reliability of monetary policy actions aimed at stabilizing the economy using monetary aggregates.

In the context of a structural GARCH-in-Mean VAR model, we investigate the effects of monetary uncertainty on unemployment rates by race and ethnicity in the United States. We find that monetary uncertainty tends to increase unemployment across all levels, with the magnitude of the effect being much larger for Black and Hispanic workers than for their White counterparts. Using impulse response analysis, we also provide evidence that a negative real money supply shock tends to dampen employment across all levels (race and different age cohorts based on gender). We find that in the prime working age group of 25–54 years, the female unemployment rate typically reacts more strongly to shocks involving uncertainty in the real money supply than do male unemployment rates. We also find that for both males and females, the youngest and inexperienced workers are the ones who suffer the most from volatility in the real money supply. We find that monetary uncertainty not only increases unemployment but also exacerbates age, gender, and racial employment disparities.

This paper investigates the effects of remittances shocks and remittances uncertainty on the nominal and the real effective exchange rates of the six top remittance earning low- and middle-income countries, namely, Bangladesh, China, India, Mexico, Pakistan, and the Philippines. We use high frequency data for their floating exchange rate periods. A bivariate structural GARCH-in-Mean VAR is our empirical model to examine the effect of remittances inflow uncertainty on the exchange rates of each country, along with the responses of the exchange rates to positive and negative shocks in remittances. The paper finds that uncertainty in remittances is likely to appreciate the currency of Mexico against the US dollar, but remittances uncertainty has no effect on the exchange rate of the other five countries. Besides, positive and negative shocks in remittances inflow have no effect on the currency exchange rate of India and Pakistan while the exchange rates of other currencies respond at different magnitudes according to the impulse responses drawn from our model.

We assume that some monetary assets are unobserved and that the demand for them affects the demand for observed assets. We develop a model of the demand for both observed and unobserved assets based on the normalized quadratic flexible functional form and augment the Divisia monetary aggregates with unobserved assets. We construct a new set of Divisia aggregates and argue that they are more accurate measures of money in terms of capturing the relationship between velocity and the opportunity cost of holding money, a relationship that has been a major concern in monetary economics for more than half a century.

We contribute to the literature on business cycles by undertaking a comprehensive comparative assessment of the relative importance of supply, demand, and monetary policy shocks in driving macroeconomic fluctuations in the USA, Canada, Japan, the UK, and the euro area. Using structural Bayesian VAR models with sign, magnitude, and zero restrictions, we identify supply, demand, and monetary policy disturbances. We conduct both country-specific and cross-country comparisons, focusing on the post-1990s period when most countries adopted inflation targeting. We find that supply and demand shocks dominate monetary policy shocks in explaining output and inflation dynamics. While output fluctuations are primarily driven by either supply or demand shocks, depending on the country, inflation variation consistently stemmed from demand shocks, with monetary policy shocks typically contributing less than 10 per cent. The findings shed light on the recent drivers of output and inflation across major economies.

This paper investigates the stability of the demand for money in the United States and provides a comparison among the simple-sum monetary aggregates, the original (non-credit-card-augmented) Divisia monetary aggregates, and the credit-augmented Divisia and credit-augmented Divisia inside aggregates. We use quarterly data from the Center for Financial Stability and the Pesaran et al. (2001) bounds test procedure to investigate the long-run relation between the monetary aggregates and their respective user costs. In doing so, we use three classic money demand functions-the log-log, the semi-log, and the Selden and Latan & eacute; specifications. With quarterly data over the 1967:q1 through 2025:q1 period, for which the original Divisia monetary aggregates are available, we find evidence of a stable money demand function only with the Sum M4 aggregate under all money demand specifications, but not with any of the Divisia aggregates. With quarterly data over the post-2006 period, for which the credit-augmented Divisia monetary aggregates are also available, our findings show that the demand for money is stable across all money demand specifications with all of the original Divisia aggregates and the credit-augmented Divisia aggregates (but not with all of the credit-augmented Divisia inside aggregates). We also find evidence of cointegration with the Sum M3 and Sum M4 aggregates under all three money demand specifications, but not with the Fed's Sum M2 aggregate.

This paper investigates the effects of monetary policy rate uncertainty in the USA on the policy rates of seven advanced economies—Australia, Canada, Denmark, Euro Area, New Zealand, Sweden, and Switzerland—and seven emerging economies —Brazil, China, India, Indonesia, Russia, Mexico, and Turkey. We employ a bivariate structural GARCH-in-Mean VAR model to examine how US policy rate uncertainty influences the policy rate of each of the advanced and emerging economies. Additionally, we analyze the dynamics of policy rates in response to positive and negative shocks to the US policy rate using impulse response functions. The study utilizes monthly data from the Bank for International Settlements, beginning in January 1991, in line with the inception of the inflation-targeting regime and the availability of data for each country. Our findings reveal that US policy rate uncertainty has a significant and positive spillover effect on the policy rates of four advanced economies, while among emerging economies, one experiences a negative effect and another a positive effect. However, impulse response functions indicate that shocks to the US policy rate impact the policy rates of all advanced and emerging economies, except Turkey, with varying magnitudes.

This paper uses neoclassical monetary demand theory to measure the welfare cost of inflation. It uses the microeconomic- and aggregation-theoretic approach to the demand for money, that integrates the demand for money with the demands for consumption and leisure, and provides a comparison between the consumer surplus approach based on Marshallian demand functions and the compensating variation approach based on Hicksian demand functions. The paper also reports new estimates of the welfare cost of inflation based on Hicksian money demand functions and the compensating variation approach.

Efficiency is a crucial factor in productivity growth and the optimal allocation of resources in the economy; therefore, measuring inefficiency is particularly important. This paper provides a comprehensive review of the latest developments in distance functions and the measurement of inefficiency within the stochastic frontier framework. Recent advances in several related areas are reviewed and evaluated, including various approaches to measuring inefficiency using distance functions, advancements in modeling inefficiency within the stochastic frontier framework, and the most common estimation techniques. A practical guide is provided on when these methods can be applied and how to implement them. The radial, hyperbolic, and directional measures of inefficiency are discussed and assessed. The development of modeling inefficiency concerning its temporal behavior, classification, and determinants is also examined. To ensure the use of appropriate estimation techniques, recent advancements in the most common estimation techniques are reviewed. This paper also addresses the importance of maintaining the theoretical regularity applied by neoclassical microeconomic theory when it is violated, as well as the econometric regularity when variables are non-stationary. Without regularity, inefficiency results can be extremely misleading. The paper discusses significant challenges related to estimation issues that must be managed in future applications. These challenges include the inaccurate choice of functional form, ignoring the possibility of heterogeneity and heteroskedasticity, and suffering from the endogeneity problem. The paper also examines various approaches to addressing these issues, as well as potentially productive areas for future research.

We assess the responses of output and inflation to monetary policy shocks in the context of a Bayesian, monetary structural vector autoregressive model. We allow money supply and leverage measures to enter into the interest rate policy rule and use an identification approach that is by construction devoid of any price puzzles. We provide a comprehensive comparison between monetary policy shocks under a policy regime that follows a standard Taylor rule and those that augment the standard reaction function of the central bank with measures of leverage and the money supply. We find that contractionary monetary policy is more pronounced and persistent when the reaction function of the central bank is augmented with measures of money and leverage than when the reaction function follows a typical Taylor rule. Our results support the use and inclusion of monetary aggregates in monetary policy and business cycle analysis.

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 examines the relative significance of oil supply, oil demand, and monetary policy shocks in explaining US macroeconomic variations. We analyze impulse response functions and variance decomposition to assess the relative importance of these shocks. Using a Bayesian structural VAR framework and the penalty function approach, we identify the shocks of interest. We find that oil supply shocks explain less than 3% of the variation in output, but have a relatively larger impact on inflation, accounting for around 13% of the inflation variation. Oil demand shocks explain 3% of output variation, but contribute significantly to inflation variation (around 16%). In contrast, monetary policy shocks have a greater influence on output, explaining approximately 13% of the observed variation. Monetary policy shocks are also the most influential source of inflation variation, contributing over 24% to the overall variation. Based on historical variance decomposition, we find that the recent inflation surge is attributable to both monetary expansion and oil supply factors. Overall, the study highlights the dominance of monetary policy shocks in explaining US macroeconomic fluctuations, with oil supply and demand shocks playing secondary roles.

In this paper, we are motivated by the fast growing literature that investigates the performance of Divisia monetary aggregates. We construct Divisia monetary aggregates for India using monthly data form January 2001 to March 2020 and present a comprehensive comparison across the Indian Divisia monetary aggregates at four levels of monetary aggregation, M1, M2, M3, and M4. We do so in the context of three classes of empirical models. In particular, we compute correlations between the cyclical components of the Divisia monetary aggregates and the cyclical component of the industrial production index. We test for Granger causality running from the Divisia monetary aggregates to industrial production. We also test for time-varying Granger causality. We find that the levels of the Divisia monetary aggregates Granger cause economic activity in India during normal times, but the causal link broke during and in the aftermath of the extremely unusual circumstances of the Covid-19 crisis.

This chapter reviews the current mainstream approach to monetary policy based on the New Keynesian model. The chapter discusses monetary policy strategies that central banks could use to promote price stability and relates them to recent monetary policy practices in advanced and emerging economies. The chapter also addresses the role of money in monetary policy and business cycle analysis and argues that the New Keynesian model provides a narrow view of the monetary transmission mechanism. The chapter argues that there is a meaningful role for properly measured monetary aggregates in dynamic stochastic general equilibrium models, and that central banks around the world could achieve more favorable macroeconomic outcomes by paying attention to these monetary aggregates.

In this paper, we compare the dynamics of the growth rates of the original Divisia monetary aggregates, the credit card-augmented Divisia monetary aggregates, and the credit card-augmented Divisia inside monetary aggregates. This analysis is based on the methods of recurrence plots, recurrence quantification analysis, and visual boundary recurrence plots which are phase space methods designed to depict the underlying dynamics of the system under study. We identify the events that affected Divisia money growth and point out the differences among the different Divisia monetary aggregates based on the recurrence and visual boundary recurrence plots. We argue that the broad Divisia monetary aggregates could be used for monetary policy and business cycle analysis as they are exhibiting less fluctuation compared to the narrow Divisia monetary aggregates. They could positively affect policy decisions regarding environmental choices and sustainability. We also point out the changes in the monetary dynamics locating the 2008 global financial crisis and the Covid-19 pandemic.

This paper uses neoclassical microeconomic theory to investigate the demand for energy and interfuel substitution in India at the sectoral level. It makes full use of the relevant economic theory and econometrics and generates inference in terms of Allen and Morishima elasticities of substitution that are internally consistent with the data and nonlinear models used. The results indicate that the interfuel substitution elasticities are consistently below unity in the household and power sectors, revealing the limited ability to substitute between major energy commodities in these two sectors. However, significant substitution relationships are found in the industrial and transportation sectors, suggesting that energy price changes in these sectors will significantly shift the demand for energy and consumption. Based on measured elasticities of substitution, we also discuss implications of energy price shocks on inflation and inflation targeting strategies by the central bank.

How does uncertainty originating from the future path taken by monetary policy enacted by the Federal Reserve in the United States affect the business confidence in other advanced economies? Does US monetary policy uncertainty affect economic activity in the United States and in Canada, France, Germany, Italy, Japan, and the United Kingdom. Motivated to answer these questions, we use monthly data and a bivariate GARCH-in-Mean VAR model. We also use a multivariate structural VAR model and a different measure of US monetary policy uncertainty, achieving identification by a combination of short-run and long-run restrictions. Our evidence shows that US monetary policy uncertainty, irrespective of how it is measured, has negative effects on the business confidence and output in the advanced G7 economies.

This paper revisits the empirical relationship between interest rates and money demand from a novel perspective, i.e., information theory. Particularly, we utilize the model-free transfer entropy to quantify the flow of information from interest rates to monetary aggregates and present three findings. First, we document a hump-shaped informational link between interest rate and M1 monetary aggregate, with a rounded high point in the late 1980s and early 1990s. Second, we identify three structural shifts in the information transmission from interest rate to M1. The first two breakpoints occurred in the early 1980s and mid-1990s, likely as a response to the removal of Regulation Q and the introduction of sweep technology, respectively. The third shift took place during the relatively less-explored period of the early 2000s. Finally, we unravel a previously unreported pivotal distinction between the first two changepoints despite the apparent similarity in inducing money demand instability: the 1980s financial deregulations facilitate the transmission of information, whereas the 1990s financial reforms acted as an impediment to the information flow. Our results are robust to alternative entropy measures.

How does oil price uncertainty affect consumer sentiment in advanced economies? Is the response of consumer sentiment to exogenous positive and negative oil price shocks symmetric or asymmetric? Motivated to answer these questions, this paper provides a comprehensive examination of the effects of real oil price shocks on consumer sentiment in the G7 economies in the context of two classes of empirical models. With the application of a bivariate structural GARCH-in-Mean VAR model we find that (in general) oil price uncertainty has a negative and statistically significant effect on consumer sentiment in the G7 countries. Moreover, using a test of symmetry, we find that the relationship between oil prices and consumer sentiment is in general asymmetric.JEL Classification: C32, D12, Q43, O57