VoxEU Column COVID-19 Macroeconomic policy

Financial concerns and the marginal propensity to consume

How would you respond to a one-off change in your income? For example, how would you react to someone handing you £500? Throughout the pandemic a large group of UK households were asked this hypothetical question in a survey. Households were also asked about their debt, savings, and expectations for the future, giving us an opportunity to unpick their responses. We might expect households who are concerned about their financial future to be less eager to spend, preferring to save up for rainier days. The authors of this column find the opposite result: concerned households would spend around 20% more than others.

The COVID-19 pandemic has brought renewed interest to understanding how household spending responds to income changes. The crisis hit incomes for a large share of households and lockdown restrictions meant that the fall in aggregate spending was significant, with large differences across households. Using a large representative survey of UK households, we study in a new paper how household expectations about their future financial situation may affect their short-term marginal propensity to consume (MPC) out of positive income shocks (Albuquerque and Green 2022). Our main findings point to an important role played by household expectations in determining how consumption reacts to shocks.

Household spending out of income transfers has been low during the pandemic

New datasets have allowed economists to estimate households’ MPC – the share of a rise in income that a consumer spends rather than saves – quite swiftly during the pandemic (Baker and Kueng 2021, Vavra 2021). The available evidence points to households mostly saving or paying down debt when receiving a one-off payment (Armantier et al. 2020, 2021, Baker et al. 2020, Coibion et al. 2020, Crossley et al. 2020, Cox et al. 2020, Christelis et al. 2021). But there is evidence that the MPC out of positive income shocks is largest for low-income and liquidity-constrained households, and for households who suffered greater income falls relative to their pre-pandemic income. 

There is less empirical evidence and consensus about the link between household expectations and the MPC. According to precautionary savings models, financially concerned households tend to have lower MPCs, so as to build up savings to mitigate future negative income shocks (Aiyagari 1994, Jappelli and Pistaferri 2014). There is some evidence for the US (Baker et al. 2020) and EA (Christelis et al. 2021) in that direction. But others find little role for individuals’ macroeconomic expectations in explaining differences in MPCs (Coibion et al. 2020). And there is evidence for the UK that individuals who expect their financial situation to worsen or a job loss in the next three months actually report a higher MPC out of a hypothetical transfer (Crossley et al. 2020).  In this post we therefore dig deeper into the link between financial concerns and household spending.

Spending out of a transfer from household survey data

We use granular data covering a balanced panel of 7,000 UK households collected in the Understanding Society Covid-19 Study (Institute for Social and Economic Research 2020). Understanding Society is the UK’s main longitudinal household survey. The Covid-19 Study was introduced to capture experiences of a subset of these households during the pandemic. Our variable of interest, the MPC, is extracted from several questions in July 2020, November 2020, and March 2021 which ask households what they would do over the next three months if they were to receive a one-time hypothetical transfer of £500. 

Figure 1 shows that around 78% of households would not change their spending in response to a one-time payment of £500. Around 18% would spend more, whereas roughly 4% would spend less. The responses are relatively stable across the three survey waves. We then compute the household’s MPC as the reported pound consumption change divided by £500. We assume that MPCs vary between zero and one, so that households who reported they would spend less or the same are re-coded as having an MPC of zero. We find that the average elicited MPC across surveys stands at only 11%.

Figure 1 Households’ response to a hypothetical payment of £500


Financial concerns during the pandemic

The surveys also contained questions about household expectations, which allow us to explore the link between financial concerns and the MPC. These expectations relate to households’ financial situation in the next three months, aligning with the time horizon of the MPC question. Our main measure of financial concerns focuses on households’ perceived likelihood of having difficulties in paying bills and expenses in the next three months (ranging from 0–100%).

In our baseline regressions we transform the financial concerns variable into a binary one, taking the value of one if the household’s expected probability of financial distress is above the median in the sample, and zero otherwise. 

What determines financial concerns?

We link the Covid surveys to the Main survey to extract important pre-crisis household characteristics, such as mortgage debt and savings. We then explore which characteristics correlate with financial concerns by running probit panel regressions across the three surveys. We include a large set of household characteristics: socio-demographic variables; financial characteristics; subjective current financial situation; employment information; benefits; and health concerns.

We find that households that are concerned about not being able to pay their bills in the short term are significantly more likely to fall into various groups: already concerned about their current financial situation; liquidity constrained; belong to low-income groups; renters or mortgagors; younger, male, and ethnic minorities; furloughed; reliant on benefits; or employed in industries more heavily impacted by the pandemic. 

The link between financial concerns and spending

We then run several panel regressions to uncover differences in MPCs across households during the pandemic. Our dependent variable is the elicited MPC, ranging between 0 and 1 and our key explanatory variable is the binary financial concerns variable. We include several household controls, such as savings, tenure, income and age, which might be expected to correlate with a household’s spending decisions. In addition to our financial concerns variable, which indicates whether a household believes they will be worse off financially in three months’ time, we also include a variable indicating whether a household is finding it difficult to manage financially now. This allows us to tease out the role of short-term expectations about future financial difficulties. If we did not control for a household’s current financial situation results could just reflect that some households are already struggling and so respond more to an income shock.

Financial concerns over the short term play a key role in explaining differences in MPCs across households during the pandemic. We find that financially concerned households have an MPC that is 2.3 pp larger than households who are not concerned (left bar in Figure 2). That is 20% higher than the sample average. This result is robust to several checks, such as alternative measures of financial concerns, controlling for health-related concerns, and to small changes to the design of the MPC question.

Figure 2 Marginal change in MPC relative to unconcerned households (percentage points)


Notes: Estimates from a random effects model at the individual level, where the dependent variable is the elicited MPC. Controls for full set of household characteristics. Standard errors in parentheses clustered at the individual level. Asterisks, *, **, and ***, denote statistical significance at the 10%, 5%, and 1% levels.

We also check whether past spending cuts, negative income shocks, mortgage debt, and the labour market situation explain why financially concerned households have larger MPCs. We could only find some tentative evidence that part of our result may be driven by different shares of discretionary spending and reliance on benefits, but this is unlikely to play a large role. 

We adapt our baseline specification to make use of the fact that our financial concerns variable ranges from 0% to 100%. We find that households that are moderately concerned, in the 1%-50% probability range, are driving our main results (Figure 2). This suggests that, as long as the subjective probability of being in financial distress in the future is not that large, concerned households will tend to spend a larger fraction of the income windfall than other households. By contrast, households that are certain they will not be able to pay their bills (100% probability) display the smallest MPC; these households save a larger fraction of the transfer to prepare for more challenging times ahead.

While our results may be surprising from the perspective of a classical consumption model, they are less surprising from a behavioural perspective. In behavioural models, households may compartmentalise income and spending into different ‘mental accounts’ and budget within these to help make trade-offs and act as a self-control device (Duxbury et al. 2005, Milkman and Beshears 2009, Kahneman and Tversky 2013). Financially concerned households might be more likely to budget and treat funds within each tagged mental account as distinct and imperfectly substitutable, making them more likely to spend out of a transfer. There is also evidence that different preferences can drive differences in consumption behaviour (Laibson 1998, Aguiar et al. 2020, Vihriälä 2021). For instance, impatience may lead households to bring consumption forwards, and may also correlate with a higher probability of becoming financially distressed in future. 

We have shown that financially concerned households are associated with larger MPCs out of positive income shocks. But what about negative income shocks? Unfortunately, the survey did not include questions about an income fall scenario. We thus check whether financially concerned households that faced income decreases during the pandemic were more likely to cut their spending than unconcerned households that also experienced falls. Our results suggest that financially concerned households who had negative income shocks indeed cut consumption more than unconcerned households, indicating that larger consumption responses of the former group may not be exclusive to scenarios of positive income shocks. 


We used survey data during the pandemic to explore how households who are concerned about their financial future respond to a hypothetical positive income shock. We find that, contrary to expectations, concerned households intend to spend around 20% more than others. Households that are moderately concerned, rather than those who are certain they will not be able to pay their bills in the near-term, drive our main results. 

Authors’ note: The views expressed in this column represent only our own and should therefore not be reported as representing the views of the Bank of England, the International Monetary Fund, its Executive Board, or IMF management.


Aguiar, M A, M Bils and C Boar (2020), “Who Are the Hand-to-Mouth?”, NBER Working Paper 26643. 

Aiyagari, S R (1994), “Uninsured Idiosyncratic Risk and Aggregate Saving”, The Quarterly Journal of Economics 109(3): 659–684.

Albuquerque, B and G Green (2022), “Financial Concerns and the Marginal Propensity to Consume in COVID Times: Evidence from UK Survey Data”, IMF Working Paper WP/22/47.

Armantier, O, L Goldman, G Kosar, J Lu, R Pomerantz and W Van der Klaauw (2020), “How Have Households Used Their Stimulus Payments and How Would They Spend the Next?”, Liberty Street Economics, 13 October, Federal Reserve Bank of New York.

Armantier, O, L Goldman, G Kosar and W and Van der Klaauw (2021), “An Update on How Households Are Using Stimulus Checks”, Liberty Street Economics, 7 April, Federal Reserve Bank of New York.

Baker, S R, R A Farrokhnia, S Meyer, M Pagel and C Yannelis (2020), “Income, liquidity, and the consumption response to the COVID-19 pandemic and economic stimulus payments”,, 16 June.

Baker, S R and L Kueng (2021), “Household financial transaction data”, NBER Working Paper 29027.

Christelis, D, D Georgarakos, T Jappelli and G Kenny (2021), “Heterogenous effects of Covid-19 on households' financial situation and consumption: Cross-country evidence from a new survey”,, 7 June.

Coibion, O, Y Gorodnichenko and M Weber (2020), “How US consumers use their stimulus payments”,, 7 September.

Cox, N, P Ganong, P J Noel, J S Vavra, A Wong, D Farrell and  F E Greig (2020), “Initial Impacts of the Pandemic on Consumer Behavior: Evidence from Linked Income, Spending, and Savings Data”, Brookings Papers on Economic Activity (Summer): 35–69.

Crossley, T, P Fisher, P Levell and H Low (2020), ”MPCs through COVID: spending, saving and private transfers”, ISER Working Paper Series 2020-14, Institute for Social and Economic Research.

Duxbury, D, K Keasey, H Zhang and S L Chow (2005), “Mental accounting and decision making: Evidence under reverse conditions where money is spent for time saved”, Journal of Economic Psychology 26(4): 567–580.

Institute for Social and Economic Research (2020), “Understanding Society COVID-19 Study, 2020”, UK Data Service. SN: 8644, 10.5255/UKDA-SN-8644-1.

Jappelli, T and L Pistaferri (2014), “Fiscal Policy and MPC Heterogeneity”, American Economic Journal: Macroeconomics 6(4): 107–136.

Kahneman, D and A Tversky (2013), “Prospect Theory: An Analysis of Decision Under Risk”, Chapter 6 in L C MacLean and W T Ziemba (eds), Handbook of the Fundamentals of Financial Decision Making: Part I, World Scientific Book Chapters, World Scientific Publishing Co.

Laibson, D (1998), “Life-cycle consumption and hyperbolic discount functions”, European Economic Review 42(3-5): 861–871.

Milkman, K L and J Beshears (2009), “Mental accounting and small windfalls: Evidence from an online grocer”, Journal of Economic Behavior & Organization 71(2): 384–394.

Vavra, J (2021), “Tracking the Pandemic in Real Time: Administrative Micro Data in Business Cycles Enters the Spotlight”, Journal of Economic Perspectives 35(3): 47–66.

Vihriälä, E (2021), “Commitment in Debt Repayment: Evidence from a Natural Experiment”, available at SSRN.

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