Business Cycles and Monetary Policy: How Exposed Are You?

Part of Macro Through Households.

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Imagine two individuals with the same annual income. One earns a salary, while the other earns income from business profits. Suppose the economy enters a recession. Will the downturn affect both of them equally?

This question relates to the concept of income cyclicality, which describes how household income responds to economic expansions and contractions. During recessions, aggregate income typically falls and the unemployment rate rises. Households may face a higher risk of job loss and declines in investment income. Entrepreneurs may also experience lower business profits. However, the degree of exposure to the business cycle varies across individuals. In other words, some households’ incomes are more resilient to economic downturns than others.

Economic downturns affect households differently across the income distribution (Bitler and Hoynes, 2015), with evidence pointing to particularly pronounced effects at the lowest income levels (Valizadeh et al., 2025). Across demographic groups, the effects of the Great Recession were felt most strongly by men, Black and Hispanic workers, young workers, and workers with lower levels of education (Hoynes et al., 2012). Social insurance policies can help cushion these effects by mitigating recession-related income risk (Angelopoulos et al., 2022).

The source of an economic downturn also matters. Financial crises can increase income inequality, leaving poorer households relatively worse off (Nguyen, 2022). Beyond income inequality, the relationship between labor income risk and financial market performance also matters for household portfolios. Workers whose downside income risk coincides with poor equity-market performance hold smaller equity shares, which can help limit their combined exposure to simultaneous declines in labor income and financial wealth (Catherine et al., 2024).

Although recessions can severely affect vulnerable groups, high-income households are also exposed to the business cycle. Parker and Vissing-Jorgensen (2010) document an increase in income cyclicality among high-income households in the United States beginning in the early 1980s. Moreover, Guvenen et al. (2014) find that earnings among individuals in the top 1% of the earnings distribution are slightly more cyclical than average. However, substantial differences exist across sectors: top earners in finance and construction have more cyclical earnings than the average worker, whereas those in services have less cyclical earnings.

Understanding the relationship between business cycles and household income is important for analyzing the distributional effects of monetary policy. Although monetary easing can stimulate aggregate demand and increase income, households do not necessarily benefit to the same extent. This matters because, in the framework developed by Kaplan et al. (2018), indirect effects operating through increased labor demand are substantially stronger than the direct effect of intertemporal substitution, i.e., the incentive to shift spending across time in response to changes in interest rates.

Beyond the overall increase in income, the distribution of income gains across households also matters for aggregate consumption. Auclert (2019) identifies three redistribution channels. Two of them, the Fisher channel and the interest rate exposure channel, depend on households’ financial positions, including their assets, liabilities, and exposure to changes in interest rates. The third, the earnings heterogeneity channel, reflects differences in how households’ earnings respond to changes in aggregate economic activity. Its effect on aggregate consumption depends on whether households receiving larger income gains also have higher marginal propensities to consume (MPCs), meaning that they spend a larger share of each additional unit of income.

As I mentioned earlier, expansionary monetary policy can help mitigate the effects of economic contractions, provided it is consistent with stabilizing inflation. Empirical evidence suggests that low-income households tend to have higher MPCs, so their consumption may respond more strongly to income gains generated through this channel, e.g., when improved employment prospects raise their earnings.

These mechanisms raise the question of whether households recognize their own exposure to the business cycle. Roth et al. (2022) find that households are imperfectly informed about their exposure to unemployment risk during recessions. Learning that their exposure is higher increases their demand for information about the likelihood of a recession. Turning to monetary policy, Grigoli et al. (2026) use a household survey with information treatments and find that respondents do not expect monetary policy to affect their incomes, although they recognize its effects on their balance sheets. This finding suggests limited recognition of the indirect income channel of monetary policy transmission.

As the economy evolves, these patterns of heterogeneity may change, as may households’ perceptions of their sensitivity to aggregate economic conditions. The growing use of AI could reduce the costs of acquiring and processing information, helping individuals better understand economic news and make decisions to manage income and unemployment risks. One possibility, viewed through the lens of diagnostic expectations (Bordalo et al., 2022), is that households may overestimate their sensitivity, strengthening incentives for precautionary behavior. At the same time, AI could dramatically change the structure of labor markets and, consequently, the cyclicality of household income. These possibilities raise questions for future research.

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