Money Matters: Broad Divisia Money and the Recovery of the US Nominal GDP From the COVID-19 Recession

IF 3.4 3区 经济学 Q1 ECONOMICS
Michael D. Bordo, John V. Duca
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Abstract

The rise of inflation in 2021 and 2022 surprised many macroeconomists who ignored the earlier surge in money growth because of past instability in the demand for simple-sum monetary aggregates. We find that the demand for more theoretically based Divisia aggregates can be modeled and that these aggregates provide useful information about nominal GDP. Unlike M2 and Divisia-M2, whose velocities do not internalize shifts in liabilities across commercial and shadow banks, the velocities of broader Divisia monetary aggregates are stable and can be empirically modeled through the Covid-19 pandemic. In the long run, these velocities depend on regulation and mutual fund costs that affect the substitutability of money for other financial assets. In the short run, we control for swings in mortgage activity and use vaccination rates and the stringency of government pandemic restrictions to control for the unusual pandemic effects. The velocity of broad Divisia money declines during crises like the Great and COVID Recessions but later rebounds. In these recessions, monetary policy lowered short-term interest rates to zero and engaged in quantitative easing of about $4 trillion. Nevertheless, broad money growth was more robust in the COVID Recession, reflecting a less impaired banking system that promoted rather than hindered deposit creation. Our framework implies that nominal GDP growth and inflation rebounded more quickly from the COVID Recession versus the Great Recession. Our different scenarios for future Divisia money growth and the unwinding of the pandemic have different implications for medium-term nominal GDP growth and inflationary pressures.

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来源期刊
CiteScore
5.40
自引率
5.90%
发文量
91
期刊介绍: The Journal of Forecasting is an international journal that publishes refereed papers on forecasting. It is multidisciplinary, welcoming papers dealing with any aspect of forecasting: theoretical, practical, computational and methodological. A broad interpretation of the topic is taken with approaches from various subject areas, such as statistics, economics, psychology, systems engineering and social sciences, all encouraged. Furthermore, the Journal welcomes a wide diversity of applications in such fields as business, government, technology and the environment. Of particular interest are papers dealing with modelling issues and the relationship of forecasting systems to decision-making processes.
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