Monetary policy is an important tool for stabilising the economy. This was especially evident during and after the 2008-2009 global crisis (Cui and Sterk 2018), with some market commentators even arguing that monetary policy has become ‘the only game in town’ (El-Erian 2016). In the context of the current Covid-19 crisis, central banks have again played an important role (e.g. European Parliament 2021).
While monetary policy is generally designed to affect economic aggregates, the distribution of gains and losses matters for several reasons. First, it shapes the effect on aggregate demand because households differ systematically with respect to the marginal propensity to consume (Kaplan et al. 2018). Second, the revived interest in income inequality (Milanovic 2016) and wealth inequality (Saez and Zucman 2014) have sparked an important debate about how monetary policy affects these phenomena. This question has also attracted significant attention from policymakers, with some arguing that softer monetary policy reduces inequality because it primarily helps lower-skilled workers find jobs (Draghi 2016). But others have emphasised that the well-to-do also benefit through increasing asset prices, meaning the net effect on inequality is ambiguous (Bernanke 2015).
In a recent study, we analyse the distributional effects of monetary policy on income, wealth and consumption (Andersen et al. 2020). Our main data source is individual-level tax records for the entire population of Denmark, with detailed information about income and balance sheets for the period 1987-2014. This equates to more than 70 million individual-year observations. In the tax records, we observe all major components of households' disposable income (e.g. salaries, dividends, and interest expenses) as well as the main balance sheet components (e.g. housing, stocks and debt). We combine the tax records with other administrative data sources, most importantly an auto register with information on car purchases – an important component of durable consumption.
The goal of the study is to estimate how a decrease in the policy rate affects households at each position of the income distribution. A key empirical challenge is that the Danish policy rate may be endogenous to local economic conditions. We address this challenge by exploiting the long-standing commitment of the Danish monetary authorities to exchange rate stability (which implies that Denmark has effectively imported its monetary policy stance from Frankfurt for 35 years). When the ECB changes its leading interest rate, the Danish Central bank typically changes its rate on the same day to restore the interest rate differential that is consistent with a fixed exchange rate. This introduces a source of exogenous variation in the Danish policy rate that we exploit for identification. Concretely, we use changes in the ECB policy rate as an instrument for changes in the Danish policy rate, while controlling exhaustively for the macroeconomic environment, for cross-border spillovers, and for secular trends in inequality.
Our first set of results concern the effects of monetary policy on disposable income. We show that softer monetary policy increases disposable income at all income levels, but that the gains are highly heterogeneous and monotonically increasing in the income level. As shown in Figure 1, a decrease in the policy rate of one percentage point raises disposable income by less than 0.5% at the bottom of the income distribution, by around 1.5% at the median income level, and by more than 5% for the top 1% over a two-year horizon.
Figure 1
We identify the key economic channels underlying this result by considering each component of disposable income separately. Consistent with theory and the perception of policymakers (e.g. Draghi 2016), softer monetary policy has the largest effect on salary income at relatively low income levels, reflecting a sizeable increase in employment for this group. But most other components of disposable income (e.g. gains in the form of higher business income, higher stock market income, and lower interest expenses) contribute to a positive income gradient.
Our second set of results concerns the effects of monetary policy on asset values through changes in property prices and stock prices. We document that softer monetary policy creates capital gains for all income groups, but with a pronounced positive income gradient. As shown in Figure 2, a decrease in the policy rate of one percentage point increases asset values by around 20% of disposable income at the bottom of the income distribution and by around 75% of disposable income at the top over a two-year horizon (implying asset returns on housing and stocks of 6-8%). This suggests that the effects of softer monetary policy through appreciation of assets are generally much larger than the effects through higher disposable income. The income gradient largely reflects that households at higher income levels hold more assets relative to their disposable income, and, to a lesser extent, that the asset returns created by monetary policy are higher.
Figure 2
We also study the distributional effects of monetary policy on consumption and wealth accumulation. The intertemporal budget constraint requires that the gains created by softer monetary policy, whether in the form of disposable income or capital gains, must be either consumed or added to the household's wealth. But by changing market interest rates, monetary policy also changes the trade-off between consumption and savings more broadly, as captured by the intertemporal elasticity of substitution. The results indicate that the consumption and wealth gains of softer monetary policy are both highly unequally distributed.
Theoretically, debt matters directly for exposure to several channels of monetary policy and may further shape consumption responses to the extent that it represents a financial constraint. We show empirically that household debt plays an important role in the transmission of monetary policy. Within income groups, we show that the estimated effects of monetary policy tend to increase monotonically with ex ante leverage. Within groups with similar leverage, the income gradient is generally weaker than in the full sample. Nevertheless, significant heterogeneity remains even after accounting for leverage. Notably, the top-1% stands out with larger gains from softer monetary policy than any other income group at each level of leverage.
Finally, to relate our findings to the broader body of existing research on inequality (e.g. Piketty 2014), we undertake a simulation exercise that summarises the distributional implications of our estimates. The results suggest that softer monetary policy unambiguously increases income inequality by raising the income shares at the top of the income distribution and lowering them at the bottom. As shown in Figure 3, accounting for direct as well as indirect channels, reducing the policy rate by one percentage point raises the share of aggregate disposable income for the top-1% by around 3.5% over a two-year horizon and lowers it by almost 2% for the bottom income group.
Figure 3
References
Andersen, A L, N Johannesen, M Jørgensen and J-L Peydró (2020), “Monetary policy and inequality”, CEPR working paper DP15599.
Bernanke, B (2015), “Monetary policy and inequality”, Brookings Institution Blog, 01 June.
Wei, C and V Sterk (2018), “The powers and pitfalls of quantitative easing”, VoxEU.org, 09 January.
El-Erian, M A (2016), The Only Game in Town: Central Banks, Instability, and Avoiding the Next Collapse, New York, NY: Random House.
European Parliament (2021), “The ECB’s Monetary Policy Response to the COVID-19 Crisis”, ECON in Focus briefing, 09 February.
Draghi, M (2016), “Stability, equity and monetary policy”, 2nd DIW Europe Lecture, Berlin, 25 October.
Greg K, B Moll and G Violante (2018), “Monetary policy according to HANK”, American Economic Review 108(3): 697-743.
Milanovic, B (2016), “Introducing Kuznets waves: How income inequality waxes and wanes over the very long run”, VoxEU.org, 24 February.
Saez, E and G Zucman (2014), “Exploding wealth inequality in the United States”, VoxEU.org, 28 October.