A central question for monetary policy is how changes in the policy rate affect household spending and saving. Economic theory has highlighted various potential transmission channels, including intertemporal substitution, income effects, and wealth effects (Bernanke and Gertler 1995, Christiano et al. 2005, Kaplan et al. 2018; Auclert 2019). In these models, households are modeled as rational agents who perfectly anticipate the macroeconomic effects of monetary policy implied by the model. 

However, more recent literature using survey data has shown that households’ understanding of monetary policy is quite limited and households’ reactions are often difficult to reconcile with model predictions. Coibion et al. (2022, 2023) show that central bank communication significantly moves household inflation expectations. Andre et al. (2022) document large differences between the subjective models of households and experts. Roth et al. (2023) use survey expectations in a structural framework to recover plausible aggregate responses. What has been missing is a unified decomposition linking the two halves of transmission: how policy changes reshape households’ expectations, and how those revised expectations independently affect behaviour.

In a recent paper (Grigoli et al. 2026), we provide such a decomposition using a large-scale survey of US households. Respondents are first asked how a hypothetical change in the federal funds rate would affect key macroeconomic variables, such as interest rates, inflation, wages, unemployment, house prices, and stock prices. In addition, we use a large set of randomised information treatments to generate exogenous variation in household expectations, allowing us to estimate how each expectation affects consumption and portfolio decisions while holding others fixed. Combining the two steps yields a full channel-by-channel decomposition.

A different transmission mechanism

In standard New Keynesian models, an increase in policy rates reduces consumption primarily through the intertemporal substitution effect, with higher real interest rates encouraging households to postpone spending. Recent theoretical developments featuring liquidity constrained agents also underscore the possibility of strong income effects. In contrast, our evidence suggests that households rely on a different mental model. When asked how they would respond to a rise in the federal funds rate, households report that they would reduce their spending, particularly on durable goods. At first glance, this aligns with the intended effects of monetary tightening. However, the underlying mechanism differs markedly from the one emphasised in standard models.

First, households believe that policy rate hikes will increase – not reduce – inflation. To better understand this result, we asked respondents to explain the perceived link between interest rates and inflation. The dominant explanation is a cost-based narrative: higher interest rates raise borrowing costs for firms and households, which are then passed through into higher prices – the cost-channel logic of Ravenna and Walsh (2006). This interpretation is intuitive and consistent with the price puzzle in the empirical monetary literature, especially over the first year following a rate hike (Christiano et al. 1999). When interest rates rise, consumers observe higher mortgage rates, more expensive credit card debt, and rising financing costs for businesses. These visible effects may dominate more abstract general equilibrium considerations, such as reduced demand and lower inflationary pressures over time. 

Second, households react to higher expected inflation by reducing – not increasing – consumption. This effect contrasts with standard intertemporal substitution effects. A possible interpretation is that households associate higher inflation with higher uncertainty, which in turn reduces consumption for precautionary reasons. 

This transmission mechanism running via inflation expectation effects accounts for most of the decline in consumption following a monetary policy tightening, particularly over horizons of six to twelve months after the interest rate hike (Figure 1). Borrowing costs also contribute to lower spending, but less so. Income and wage expectations play almost no role, largely because households do not perceive a link between policy rates and their own earnings.

Figure 1 Channel decomposition of monetary policy transmission to household consumption

Percent change for a one percentage-point increase in the FFR

Notes: Each coloured bar is the product of the perceived effect of an FFR hike on a given macro variable and the estimated pass-through from beliefs about that variable into household consumption. The black dot is the net total. 

A similar transmission mechanism extends beyond consumption decisions. When faced with higher interest rates, households report reallocating their portfolios away from risky assets such as stocks and toward safer assets such as bank deposits. This reallocation is again driven largely by inflation expectations and perceived changes in economic conditions.

Implications

Our findings have implications both for how monetary transmission is modelled and for how it might be communicated. 

On the modelling side, the results call for a reconsideration of how households perceive the effects of monetary policy, as well as how they react to changes in expected inflation. In particular, the analysis underscores the presence of a strong cost-channel mechanism driving households’ perceptions and reactions to monetary tightening, which sits awkwardly with the disinflationary intent of policy rate hikes. 

On the communication side, the analysis underscores the need to better inform the broader public about the disinflationary effects of monetary tightening. At the same time, if households were persuaded about that policy rate hikes lower inflation, this would dampen the contractionary impact on consumption.  

References

Andre, P, C Pizzinelli, C Roth, and J Wohlfart (2022), “Subjective Models of the Macroeconomy: Evidence from Experts and Representative Samples”, Review of Economic Studies 89(6): 2958–2991.

Auclert, A (2019), “Monetary Policy and the Redistribution Channel”, American Economic Review 109(6): 2333–2367.

Bernanke, B and M Gertler (1995), “Inside the Black Box: The Credit Channel of Monetary Policy Transmission”, Journal of Economic Perspectives 9(4): 27–48.

Christiano, L, M Eichenbaum, and C Evans (1999), “Monetary Policy Shocks: What Have We Learned and to What End?”, in J B Taylor and M Woodford (eds), Handbook of Macroeconomics, Vol. 1A, Elsevier, pp. 65–148.

Christiano, L, M Eichenbaum, and C Evans (2005), “Nominal Rigidities and the Dynamic Effects of a Shock to Monetary Policy”, Journal of Political Economy 113(1): 1–45.

Coibion, O, D Georgarakos, Y Gorodnichenko, and M Weber (2023), “Forward Guidance and Household Expectations”, Journal of the European Economic Association 21(5): 2131–2171.

Coibion, O, Y Gorodnichenko, and M Weber (2022), “Monetary Policy Communications and Their Effects on Household Inflation Expectations”, Journal of Political Economy 130(6): 1537–1584.

Georgarakos, D, O Coibion, Y Gorodnichenko, and G Kenny (2024), “The Causal Effects of Inflation Uncertainty on Households’ Beliefs and Actions”, NBER Working Paper 33014.

Grigoli, F, D Sandri, Y Gorodnichenko, and O Coibion (2026), “Monetary Policy According to Households: Perceptions, Reactions, and Channels”, CEPR Discussion Paper 21408.

Kaplan, G, B Moll, and G Violante (2018), “Monetary Policy According to HANK”, American Economic Review 108(3): 697–743.

Ravenna, F and C E Walsh (2006), “Optimal Monetary Policy with the Cost Channel”, Journal of Monetary Economics 53(2): 199–216.

Roth, C, M Wiederholt, and J Wohlfart (2023), “The Effects of Monetary Policy: Theory with Measured Expectations”, manuscript.