Aaron Clements-Partridge and Ryland Thomas
Broad money aggregates failed policymakers when used as an intermediate target in the 1980s, but they appeared to predict the post-pandemic inflation. Where does that leave their role in setting monetary policy today? That was the topic of a recent workshop hosted by the Bank on ‘Analysing the Information Content of Money’ which brought together academic experts and central bank staff to review the evidence. In this blog we offer our key takeaways from the workshop. We argue that there is value in understanding developments in the broad money data. While it shouldn’t assume special status, money provides an alternative lens through which to assess and communicate medium-term risks to the inflation outlook.
There are strong theoretical reasons to believe that changes in money balances can contain information about the outlook for nominal spending or price level. Intuitively, broad money is a measure of potential spending power, capturing the stock of liquid assets – mostly deposits – held by households and companies. This is described more formally in economic theory – most simply by the Quantity Theory of Money, in which nominal spending is required to be equal to the stock of money multiplied by the speed at which it circulates around the economy (ie its velocity).
A key challenge has always been whether velocity is stable and predictable enough for these relationships to be useful. A stylised fact over the long sweep of history, is that the correlation between money and nominal spending is clearer at longer horizons but noisier at the business cycle frequency, with all frequencies exhibiting phase shifts in the apparent lag-lead relationship Chart 1 shows the relationship at different frequencies in the UK going back to the late C18th (Thomas).
Chart 1: UK broad money and nominal GDP (NGDP) correlations at different frequencies
Notes: This uses Multiresolution Analysis (MRA) based on the wavelets filter to isolate movements in money and nominal spending at different frequencies (Percival and Walden (2000)). rxy is the correlation coefficient between money and nominal spending at each of the frequencies shown.
Presenters at the workshop offered a range of evidence that the money data can contain useful information for assessing the inflation outlook. For the economies covered, including money in empirical models helped to identify the underlying shocks driving inflationary pressure and clarified the transmission of conventional and unconventional monetary policies (eg Mandler, Bhadury and Binner).
Additionally, there was competing evidence on the exact role for money relative to other factors in explaining short-run movements in inflation and output. For example, the post-pandemic rebound in money velocity – reflected in stronger nominal spending growth following a large build up of money holdings – suggests that the unwinding of monetary imbalances was a potentially important part of the narrative underpinning the emergence of inflationary pressures from late 2021 onwards. The relative importance given to this versus other factors varied across presentations (eg Reynard, Duca and Mandler), however, owing in part to varying experience across countries. For the UK, we believe it was right to assess the risks to the outlook for nominal spending from the build-up of primarily household deposits across 2020–21. But supply-chain disruptions were the main reason that inflation picked up in late 2021 and higher energy prices likely triggered a faster rebound of velocity than otherwise would have been the case from 2022. Above all, the UK experience suggests understanding the interaction between the state of liquidity and the impact of supply and commodity price shocks is important for monetary policy (Thomas).
For us, the workshop also highlighted four important considerations when working with the money data.
First, it reinforced our view that that indicators that try to identify any persistent disequilibria in money holdings are likely to be more useful than focusing on volatile high-frequency movements in money. The workshop presentations by Reynard and Duca emphasised the potential significance of money ‘overhangs’ which can help explain inflation in Switzerland and the US. The underlying logic is that when increases in the money supply cannot be accounted for by underlying changes in money demand (M*), that signals nominal spending is likely to be stronger going forward to reconcile the two in the medium term. These approaches rely crucially on sufficiently good estimates of underlying money demand. This can be highly challenging given it’s unobserved, but we agree with Huw Pill that economists face similar challenges when estimating other unobserved ‘star’ variables such as the natural rate of interest (R*) and potential supply (Y*), to construct other indicators of inflationary pressure such as the interest rate- or output-gap. So money is no different in this regard. Both Reynard and Duca demonstrated that improving estimates of money demand is possible if underlying drivers can be identified and structural changes in the financial system relevant for the economy concerned are understood.
Second, it seems clear that the relationship between money and inflation is highly state-contingent and that understanding the nature of the underlying shocks and wider economic conditions is key to interpreting developments in the money data. As an example of this, Boucinha (ECB) noted that precautionary behaviour at the height of the Covid-19 pandemic pushed up on money demand, so higher money holdings were less of a risk to inflation at that point in time.
Third, we recognise strong arguments for analysing both simple-sum aggregates and Divisia measures of money and don’t see a need to choose between them. The key advantage of simple-sum money aggregates is that they facilitate analysis of money within a wider framework of banks’ and private sector balance sheets. For example, the proximate drivers of money creation can be identified via its counterparts on banks’ balance sheets, such as lending to the private sector and QE. The US evidence suggests that Divisia money has more information content in relation to nominal spending decisions, however, given it puts greater weight on the types of deposits most likely to be used for transactional rather than savings purposes. This is likely to be especially important if different types of monetary asset are poor substitutes for each other (Binner for the UK).
Fourth, analysing money at a sectoral level seems especially helpful for identifying the mechanisms of adjustment following disequilibria. In the UK, the relationships between money and spending have often appeared clearer at a sectoral level (Cloyne et al (2015)). Changes in sectoral money holdings can also be related to the flow of funds arising from changes in the portfolio of financial assets by different sectors, such as households substituting between deposits and equities. So, the extent to which money over- or under-hangs are concentrated in specific sectors is likely to affect the channels through which they unwind. The presentation by Castaneda demonstrated the relationship between financial sector money holdings and share prices in the UK and US. The link between household money and house prices also emerged as a result worth exploring further, given the supporting evidence in Congdon (2026). Given all of this, a key question was how central banks should assess and communicate risks from money growth looking ahead. In his keynote address, Michael Bordo argued forcefully that, despite the dominance of the New Keynesian approach to setting monetary policy in many central banks, monetary aggregates still played a role in assessing and communicating inflation risks. That role he argued should take the form of a crosscheck using an explicit nominal trends framework for risk assessment to go alongside a traditional New Keynesian analysis of the relevant channels of transmission (see an interpretation of this in Figure A from the presentation by Thomas). This was reinforced in the panel session by Huw Pill, who suggested that central banks’ focus on money had waned too far since the money targeting failures in the 1980s. That had undermined the value of presenting money as a risk‑assessment tool which, retrospectively, would have been useful in the pandemic. Charles Goodhart agreed and argued that when large money gaps emerge, central banks should understand and explain the source of the overhang and communicate the potential risks, even if the assessment ends up being that they pose little risk to inflation. Larry Goodman concurred and pointed to a number of episodes in the last 25 years when strong US Divisia money growth might have provided useful early warnings that, had there been more focus on these, might have prompted helpful discussions with respect to monetary policy and financial stability.
Figure A: A conventional New Keynesian (NK) approach and an alternative nominal trends framework for assessing the risks from money
Conclusion
We think the current evidence supports using money data as a crosscheck on other indicators as a prompt to ensure any key risks apparent in this data have been understood and communicated by monetary policy makers. We dub this the ‘canary in the coalmine’ approach. Although there are communication challenges around complex monetary concepts, we think that clear and regularly repeated external narratives are part of the answer and these should be done in an explicit nominal trends framework to avoid the message being lost in translation. To some extent this has already been a feature of MPC communications in past Monetary Policy Reports, where the gap between money and simple estimates of trend have been discussed (Chart 2). In future we intend to improve our toolkit to project money gaps over the forecast horizon which will facilitate scenario-style analysis. That way, when money talks (or the canary tweets) the MPC can communicate the risks in the right language.
Chart 2: Broad money (M4ex) to nominal GDP ratio (inverse velocity) relative to pre-pandemic trend
Aaron Clements-Partridge works in the Bank’s Monetary and Financial Conditions Division and Ryland Thomas works in the Bank’s Monetary Policy Strategy Division.
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