If, on the other hand, people expect the rise in infection rates (and the associated restrictions) to subside relatively quickly – and if there are also no close substitutes for the sorts of spending that expose people to infection risk – one would expect a more marked effect on aggregate consumption, and less expenditure switching. Charts 5(a)-(c) depict some simulations to get these points across. The model they’re based on is extremely simple and stylised. In particular, it assumes that incomes, current and expected, are held fixed, and that there’s no change in the degree of uncertainty about the economic outlook. The only thing that changes is the path, actual and expected, of the pandemic. This is very obviously unrealistic. Household incomes have clearly been affected by the crisis. And we know from long experience that when uncertainty about people’s future incomes goes up, saving rates tend to rise as well. But as we saw earlier, from Chart 4, household incomes have been significantly protected by the furlough schemes, at least as compared with the huge dip in national income. (While this isn’t a free lunch – higher government debt has to be paid for eventually – it does spread out the cost of that dip.) So the assumption 2 In a more general model than the one used here Krueger et al (2020) also point out that the impact of the pandemic on aggregate  spending is lower the closer the degree of substitutability between risky and non-risky consumption.
And at least until resources can move in response, they may at the margin add to aggregate costs and inflation. I wondered about this effect first in the years after the financial crisis, and specifically whether it might help to explain why inflation had been less weak that one might have expected, given the large decline in GDP8. I thought at the time that one indicator of such a demand-driven misallocation might be a noticeable sectoral divergence in prices, mirroring that in demand and marginal costs. Chart 9 plots the sectoral dispersion in inflation rates, across broad components of the CPI, over the past 15 years or so. You can see that there was a spike in the series following the financial crisis and another last year. This isn’t a particularly clean indicator. The effect I’m discussing here involves cross-sectoral shifts in demand specifically. But relative prices can change for other reasons too (sector-specific changes in costs or productivity, for example), in a way that wouldn’t reflect any sort of misallocation of resources. In an effort to isolate areas where demand looks to have been the dominant influence, Chart 10 plots changes in inflation and sales through the course of last year, each dot indicating a different part of consumption, but only for those sectors where the two things went in the same direction9. Tentatively it suggests that, in areas where demand was relatively strong, prices went up by a little more than the equivalent declines in low demand areas.