# How monetary policy affects the distribution of income

The rich, the poor and the rest: how monetary policy affects the distribution of income

To fully understand the distributive consequences of monetary policy, we need to examine its impact on the entire income distribution and not just on summary measures of inequality like the Gini coefficient. Using uncensored administrative income data for Sweden, this column shows that while an easing of monetary policy significantly affects income across the income distribution, it does so relatively more in the tails, providing a U-shaped response model. Bottom effects are mainly due to changes in labor income, while top effects are mainly due to disparities in capital income.

Growing levels of income inequality over the past decades in most advanced economies have raised concerns about the stability of more unequal societies. Discussions about the drivers and consequences of increasing income inequality have reached academic circles (Andersen et al. 2021, Dolado et al. 2021) as well as the central banking community (Mersch 2014, Bernanke, 2015), policy makers paying increasing attention to the distributive effects of monetary policy interventions. Yet the way in which monetary policy decisions affect individuals’ income and hence its distribution is ambiguous as different channels of the monetary policy transmission mechanism operate in opposite directions (Coibion â€‹â€‹et al. 2014). For example, as argued by Draghi (2016), if monetary policy is able to stimulate the real economy and reduce unemployment, the poorest households, which are generally most affected by fluctuations in the labor market, would be the poorest households. main beneficiaries of expansionist interventions. On the other hand, if the impact of a change in monetary policy on the real economy is considerably weaker than that on asset prices, for example on stock prices, an expansionary intervention could disproportionately favor the poorest households. wealthy (Acemoglu and Johnson 2012). Thus, to fully understand the distributive consequences of monetary policy, it is necessary to determine not only its overall effects on the distribution of income, but also what are the respective roles of the different channels in the conduct of the aggregate effect.

In a recent study, we contribute to this understanding by presenting new empirical findings on the individual-level income effects of monetary policy shocks (Amberg et al. 2021). Together, our information sheds light on the overall distributive effects of monetary policy, as well as their underlying drivers. Our analysis is conducted on the basis of an administrative panel dataset comprising detailed and uncensored income data for every legal resident in Sweden over the period 1999-2018. Thus, unlike survey data which is generally top-coded, we are able to show that taking into account the far right of the distribution (the top 1%) is essential to better understand how monetary policy shapes the income of individuals. Our sample includes 73.5 million individual observations and 6.4 million unique individuals. To identify exogenous monetary policy interventions, we apply the most recent advanced high-frequency strategy. We construct monetary policy surprises as changes in the yield of Swedish Treasuries around the dates of policy announcements, while also controlling for the potential informational effects of monetary policy. Then, we perform a local projection regression of the evolution of the income of individuals over a given period on the identified monetary policy shock, allowing the estimated slopes to vary according to the income groups to which they belong.

Figure 1 presents our main findings. It describes the effects on total income of an expansionary monetary policy intervention consisting of a 25 basis point cut in the main policy rate controlled by the Riksbank. Income groups are shown on the horizontal axis. We sort individuals into eleven income groups, which correspond to the deciles of the distribution of past average income, except for the top decile, which is split in two: from the 90th to the 99th and above the 99th, respectively. This allows us to capture the revenue dynamics at the very top of the distribution. While monetary policy shocks have large and statistically significant effects on total income across the income distribution, these effects are particularly large at the ends. Specifically, a 25 basis point cut in the policy rate increases the total incomes of the poorest and richest individuals by 2.3% and 3.1%, respectively, while the corresponding response for middle-income individuals is 0.6%. Therefore, the effects of currency shocks on total income are 4 to 5 times weaker in the middle of the distribution than at the ends, resulting in a pronounced U-shaped trend in the total income response. Note also that the response to total income is almost three times greater in the top percentile than in the rest of the top decile; therefore, there is substantial heterogeneity within the top decile of the income distribution.

**Figure 1 **The effects of a shock of â€“25 basis points on total income over a two-year horizon

Next, Figure 2 shows the effects on each of the two main components of total income: labor income and capital income. The labor income response is large and statistically significant in the bottom two deciles, but small and statistically insignificant in the rest of the distribution. The response from capital income, on the other hand, is statistically significant across the entire income distribution except for the bottom decile. The effect is particularly large at the top – for example, the response of capital income is about seven times greater in the top percentile than in the middle part of the income distribution. The underlying drivers of the strong responses of total income at the top and bottom of the income distribution are therefore different: labor income at the bottom and capital income at the top.

Furthermore, we argue that the heterogeneity of the labor income response on the income distribution is explained by the income heterogeneity channel, i.e. there is a higher sensitivity from labor income to monetary shocks at the bottom than elsewhere in the distribution. The heterogeneity of the capital-income response is, on the contrary, entirely due to the income composition channel, i.e. to the fact that capital income constitutes a larger share of total income for people with high income than for low and middle income people. income individuals. On the other hand, the sensitivity of capital income to monetary shocks is fairly stable on the distribution of income.

**Figure 2** The effects of a shock of â€“25 basis points on labor and capital income over a two-year horizon

What do the full effects of currency shocks on income imply for aggregate income inequality? To answer this question, we undertake a counterfactual exercise. We start by calculating the values â€‹â€‹of a number of conventional indices of income inequality on the basis of real microdata, and then simulate the effects over two years of a currency shock of â€“25 basis points. Finally, we calculate the inequality measures for the simulated income distribution and compare them to their initial values â€‹â€‹on the real data in the absence of the expansionary shock. The results are mixed. The Gini coefficient changes very soon after the easing of monetary policy, as the large upward and downward effects largely offset each other. On the contrary, some measures of inequality like higher income shares indicate higher income inequality, while others like the standard deviation of the logarithm of income indicate a decrease in income inequality.

Our results imply that the most commonly used aggregate measures of income inequality – in particular the Gini coefficient – are not well suited to characterize the distributive effects of monetary policy. Rather, fully understanding the distributive consequences of monetary policy requires a thorough analysis of the impact of monetary policy on the entire income distribution, which can only be done with large-scale individual administrative data and not censored like ours.

## The references

Acemoglu, D and S Johnson (2012), â€œWho Captured the Fed? “, *The New York Times.*

Amberg, N, T Jansson, M Klein and A Rogantini Picco (2021), â€œFive Facts about the Distributional Income Effects of Monetary Policyâ€, Sveriges Riksbank Working Paper No. 403.

Andersen, AL, N Johannesen, M JÃ¸rgensen and JL PeydrÃ³ (2021), â€œSofter monetary policy increases inequality,â€ VoxEU.org, April 19.

Bernanke, B (2015), â€œMonetary Policy and Inequality,â€ Brookings Institution Blog, June 1.

Coibion, O, Y Gorodnichenko, L Kueng and J Silvia (2014), â€œInnocent passers-by? Monetary policy and inequalities in the United StatesÂ», VoxEU.org, October 25.

Dolado, J, G Motyovszki and E Pappa (2018), â€œMonetary policy and inequalities: a new channelâ€, VoxEU.org, May 17.

Draghi, M (2016), â€œStability, equity and monetary policyâ€, 2nd DIW Europe conference.

Mersch, Y (2014). â€œMonetary policy and economic inequalitiesâ€, opening speech, Corporate Credit Conference, Zurich, October 17.