The increase in working from home (WFH) for public health reasons during the pandemic has sparked debate over whether this change could become permanent. In this article, I try to sketch some of the (macro) economies of a longer-term post-pandemic shift towards more FMH. I argue that: i) on consumption, it will not affect overall spending, it will just reallocate it across space and sectors ii) in real estate markets, effects depend on supply responses; iii) for production, the cost savings achieved by companies thanks to the reduction in office space do not translate one for one into GDP gains.
This post comes with three qualifiers. First, I’m not considering any epi-macro type feedback effects on public health from the WFH: I’m focusing on a post-covid world where they don’t work. Second, I’m not making any predictions about * if * a shift to WFH will occur – I’m just conducting a “what if” thought experiment. Third, I’m not analyzing whether the WFH makes workers more or less productive in their work: the jury is still out on that, and it’s outside the realm of traditional macro, so I’m leaving that for now. .
Does Increasing WFH Lower Consumer Spending?
No. The simplest theoretical basis is that it changes the places or sectors where people spend money, but not how much they spend.
Many city centers have businesses that depend on the footfall of transient office workers and could be (and have been) hit hard by a reduction in the frequency / volume of office visits: such as coffee shops, venues, etc. lunch or dry cleaners. But the claim that this will lead to lower overall consumer spending reflects a compositional error.
Economic theory says that consumers optimize in two ways: they determine their best spending path over time, and then, during each period, they allocate that spending to maximize the utility of what they buy. Changes in preferences or technological innovations that reduce spending somewhere don’t destroy spending, they just displace it.
Some of this switching is purely spatial – homeworkers buy fewer cafes in city centers and buy more from outlets close to their homes. Part of it is sectoral – money saved on dry cleaning or commuting is spent on other things. Of course, the pandemic saw a sharp drop in consumption – but that was because consumers were physically limited in the scope and timing of their purchases by lockdown measures that will not be present after the pandemic.
Do cost savings on office space stimulate GDP?
May be. But it is less clear than it seems at first glance. A greater FMH means a reduction in the office occupancy rate. Assuming companies that make more FMH reduce office space, there is a cost saving for businesses. But improvements in a company’s bottom line do not automatically translate into higher GDP for UK PLC, as the economics of national accounts are a bit more complex.
The effect on GDP depends on whether the increase in the WFH changes the underlying “production function”, that is, the way in which real estate, labor and capital are combined to produce the output. And if so, how much additional production is created as a result of the “freed up” office space.
First, consider the case where the production function * does not change *. To use a favorite analogy, suppose there is an island where boat owners hire workers to go fishing. One day the owner told the staff to provide their own mosquito nets. The owner sells the nets to the companies, which are then rented or bought by the workers. In fact, the cost of providing mosquito nets has been passed from the employer to the employee, but the production technology is unchanged. If wages stay the same, what the owner gains in cost savings, workers lose. Whether wages adjust or not, production has not changed, so production is not affected.
In terms of FMH, this equates to the case where workers use the same amount of space (but have to acquire it themselves) and produce the same output. There is no net saving of space in the whole economy, no increase in production and therefore the cost savings of the WFH do not increase the GDP.
If, however, these workers do not need to acquire additional space and can still produce the same output as before, then there has * been a change in the overall production technology.
It could differ depending on the worker: For people with a free room functioning as a desk that would otherwise be unused during working hours, or those working elsewhere, no additional space should be acquired. But for others – say a group of young graduates sharing an apartment – getting the extra space to work will likely require a reallocation of economic resources towards it (according to the fishing analogy). And the first estimates are that it could be important.
And an office isn’t just real estate, it’s also furniture, IT equipment and heating / lighting. While space can be provided at virtually zero marginal cost by workers, other elements cannot. Indeed, some research has argued that the lack of economies of scale in energy use in working from home versus working in the office can be substantial.
But let’s assume that not all of the cost savings for WFH companies are pure transfers. So, overall, there is now “free” office space freed up, which can be reused by others. In terms of national accounts, the increase in GDP comes down to any additional production created by the additional activity that occurs in that space. To determine the direct effect on the GDP of the cost savings channel, you must first identify the share of the cost transfer in relation to the change in production function, and then estimate the additional GDP produced by the new “freed up” space. .
Will more FMH affect real estate markets?
Yes – but how exactly depends on the elasticities of supply. Let’s start with simplicity: the above arguments imply a change in demand along two dimensions. First, a relative decrease in the demand for housing in the city center and an increase in the demand for housing further afield. Typically, when you live in a city center, you get less space in exchange for a shorter commute. With more WFH, the value of a shorter commute decreases and the hassle of living in a small place increases. Second, with people wanting more home space to work and a lower demand for office space, this implies a shift in demand from commercial to residential real estate.
The hardest part is how that translates into price versus quantity adjustments. If the supply is perfectly elastic, the supply curve is horizontal and therefore everything happens through quantities, and prices do not change. If supply is completely inelastic, the curve is vertical and any change in demand is fully reflected in prices.
In the very short term, it is reasonable to assume that the supply of most property types is completely inelastic and therefore prices will adjust. Indeed, several articles have highlighted clear differences in the evolution of prices between town centers, suburbs and towns on the rental market.
But in the longer run, which is more economically relevant here, the elasticity of supply is a more complex issue. And it is likely to vary between national jurisdictions and local areas depending on geography, density, planning regulations, and local preferences.
Spatially, long-term supply in large city centers is likely to be quite inelastic in response to a negative shock, as you cannot ‘deconstruct’ houses and turn them into undeveloped land. And there is a larger issue regarding the type of housing: in many places, downtown apartments are small, not designed for the WFH, and reallocation of housing space into larger units is hard.
But on the outskirts of cities, the elasticity could be more elastic. For the United States, there is evidence that in some cities the supply is quite elastic on the sidelines. But in places where city limits are tightly constrained by regulations, it might be more difficult for the offer to respond. To the extent that supply curves are bent (inelastic downward, but elastic upward), a shift in preferences from city centers outward would (all other things being equal) lower the prices of real estate overall due to its asymmetric effect on prices.
On the land use side, the elasticity depends on the ease with which existing buildings can be converted from commercial to residential buildings, and / or outright replacement costs. These costs are partly related to legal obstacles related to the use of land / buildings, and partly to renovation costs – both conversion costs and broader issues regarding the attractiveness of office buildings converted to apartments. . The conversion is economically unviable if the conversion costs exceed the gain of the differential conversion values. The higher the costs, the greater the price response.
If this happens, a greater post-pandemic WFH could have substantial economic implications. This article is just an attempt to sketch the economics of three of the simpler macros.
But even taking the above mechanisms as given, quantifying these wills probably requires new tools and / or more work in areas of little research – such as “GDP office space elasticity”. And there are many other implications not analyzed here – labor markets, income distribution, transport economics, space economics, and broader productivity effects – to name just five.
John Lewis works at the Bank’s Research Center.
If you would like to contact us, please email us at [email protected] or leave a comment below.
Comments will only appear when approved by a moderator and are only published when a full name is provided. Bank Underground is a blog for Bank of England staff to share views that challenge – or support – prevailing political orthodoxies. The opinions expressed here are those of the authors and are not necessarily those of the Bank of England or its political committees.