Včeraj sem objavil, da je gospodarska aktivnost (aproksimirana s porabo električne energije) aprila padla za četrtino, kar je precej več od prvotnih ocen. Vzrok padca proizvodnje so po eni strani administrativno zaprtje določenih dejavnosti (turizem, večina trgovine, servisi, prevoz itd.), na drugi strani zmanjšanje povpraševanja po končnih izdelkih in prekinitev oskrbovalnih verig s sestavnimi deli (avtomobili, bela tehnika, zabavna elektronika itd.). Oboje pa ima dodatni negativni posredni (spillover) učinek na dobavitelje – saj denimo zaprtje restavracije prizadene tudi dobavitelje hrane, pijače, električne energije, plina itd.
Dvomesečno zaprtje določenega dela gospodarstva ima lahko izjemno velik negativni mulitiplikativni povpraševalni šok na celotno gospodarstvo, katerega učinki pa se zaradi počasnega odpiranja, povečane negotovosti in previdnosti potrošnikov lahko podaljšajo še dolgo v obdobje, ko je začetni šok že mimo. Vendar pa povečanje negotovosti vpliva tudi na splošen upad potrošnje, saj potrošniki zmanjšajo nakupe tudi ostalih storitev, trajnih potrošnih dobrin in nepremičnin, kar prek neposrednih učinkov in dobaviteljskih povezav recesiji šele da pravi zagon. In kot bom pokazal spodaj, bistvo protikriznega ukrepanja je, ob blažitvi negativnih učinkov na zaposlenost, predvsem vzeti veter iz jader povpraševalnemu šoku.
Pravkar objavljena študija za Dansko (Lau Andersen, Toft Hansen, Johannesen & Sheridan, Consumer responses to the COVID-19 crisis: Evidence from bank account transaction data, 2020) je prek spremljanja plačil s plačilnimi karticami pokazala, da se je potrošnja Dancev zaradi korona krize zmanjšala za eno četrtino. To je skladno s tem, kar sem pred dnevi pokazal s pomočjo google mobility data, da je obisk v danskih trgovinah in restavracijah od druge polovice marca do konca aprila upadel za 27% glede na isto obdobje lani. Vendar pa slednje pomeni, da Danci izpada povpraševanja zaradi manjšega fizičnega obiska trgovin in restavracij niso nadoknadili s spletnimi nakupi, kar implicira povečano negotovost potrošnikov in krč v porabi.
Kot kaže študija, se je, ob pričakovanem povečanju nakupov hrane in farmacevtskih izdelkov, najbolj zmanjšala poraba turističnih aranžmajev (-80%), naročil hrane (-65%), profesionalnih storitev (-57%), goriva in prevoza (-52%), storitev zabave (-48%) in trgovine (-29%).
Učinkov na nakup avtomobilov, trajnih potrošnih dobrin ter nepremičnin in gradbenih storitev s tem pristopom seveda ni mogoče zaznati, ker se pač večinoma ne plačujejo s plačilnimi karticami. Študija seveda tudi ne more zaznati posrednih učinkov na dobavitelje in na zmanjšano povpraševanje po njihovih izdelkih in storitvah (za to bi potrebovali podatke o naročilih in plačilnem prometu med podjetji). Ti posredni učinki pa so srednjeročno lahko bistveno močnejši, ker za daljše obdobje znižajo agregatno povpraševanje.
Zanimivo je tudi, da študija ugotavlja, da so trošenje bolj zmanjšali tisti v zasebnem sektorju (večje tveganje izgube službe), tisti z višjimi dohodki in premoženjem (kar je najbrž posledica, da je njihova struktura potrošnje drugačna kot pri tistih z nižjimi dohodki), in starejši (nad 65 let), na katere povečana negotovost bolj vpliva.
Če bi imeli na voljo podobne podatke, bi za Slovenijo verjetno ugotovili podoben vzorec upada porabe potrošnikov. Navedeno implicira, da je v času tovrstne krize nujno omejiti hipni povpraševalni šok, preden se ta razraste in (prek trajnejšega zmanjšanja porabe storitev in trajnih potrošnih dobrin) tudi po koncu prvotnega šoka negativno vpliva na zmanjšanje outputa v teh dejavnostih ter outputa pri dobaviteljih. Iz tega vidika je treba kot nujni ukrep kratkoročno močno spodbujati povečanje trošenja potrošnikov.
Ukrep v to smer je uvedba denimo turističnega vavčerja za porabo doma (vesel sem, da je vlada to idejo posvojila in da bo uvedla turistične bone), vendar to vpliva zgolj na dejavnost gostinstva in turizma (ter omejeno tudi na dobavitelje). Potrebno je spodbuditi splošno povečanje porabe potrošnikov. In ukrep v to smer je začasna uvedba temeljnega dohodka za porabo doma (ki se izplačuje mesečno vse do začetka okrevanja gospodarstva in se mora porabiti do konca decembra 2020). Čas je za temeljni dohodek, financiran s helikopterskim denarjem! Več o tem v ponedeljek.
Spodaj je nekaj izsekov iz omenjene študije za Dansko:
The COVID-19 pandemic has had drastic effects on consumer spending across the world. This column presents evidence based on bank account transaction data from Denmark showing that total card spending was reduced by 25% during the early phase of the crisis. The drop was mostly concentrated on goods and services whose supply is directly restricted by government interventions, suggesting a limited role for spillovers to non-restricted sectors through demand in the short term.
The economic costs of the COVID-19 pandemic are staggering: across the globe, millions of people have lost their jobs and trillions of dollars of stock-market wealth has been destroyed.
A key concern for policymakers is the size and nature of the consumer response. While some economists say the shutdown is, in essence, a supply shock with possible spillovers to the demand side (Baldwin and Weder di Mauro 2020, Guerrieri et al. 2020), others stress that the pandemic may also affect demand directly because the health risk of going to public spaces like shops, restaurants, and hairdressers deters consumption (Eichenbaum et al. 2020).
In either case, the dynamics on the demand side may lead to a recession that persists long after the epidemic has ended (Gourinchas 2020). If consumers respond to mass lay-offs, falling asset prices (Gormsen and Koijen), and an uncertain financial outlook (Baker et al. 2020) by slashing private consumption, the epidemic may mark the beginning of a demand-driven economic meltdown. In the face of this risk, governments have initiated massive programmes to support businesses and households.
In a new paper (Andersen et al. 2020), we use transaction data for card spending in Denmark to study consumer responses in the early phase of the COVID-19 crisis. Transactions have a number of advantages over other data sources in this particular context: they are available at any frequency and in near-real time, allowing researchers to analyse sudden changes in spending with little delay. The level of detail is also extremely high, allowing a breakdown of total card spending in detailed categories.
Our analysis uses transaction data for about 760,000 individuals who hold their main current account at Danske Bank, the largest retail bank in Denmark with a customer base that is largely representative of the Danish population.
We estimate the size of the drop in total card spending and analyse how it varies across sectors of the economy with different levels of exposure to the epidemic and the policy measures introduced to contain it. To understand the mechanisms behind the aggregate spending drop, we also study how spending responses vary across individuals who differ in key dimensions, each representing a particular form of exposure to the crisis.
The COVID-19 crisis in Denmark
In the time period we study, from 1 January to 5 April 2020, the crisis in Denmark was unfolding in the same way as in many other countries. The first case was confirmed on 28 February. On 11 March, the government announced a partial shutdown of the economy: all non-essential parts of the public sector – including schools, libraries, and universities – were shut down, and private-sector employees were urged to work from home. One week later, the government announced further restrictions, shutting down shopping centres, hairdressers, and nightclubs and restricting restaurants to take-away service. The timing and severity of the measures were generally comparable to most of Northern Europe, but less restrictive than in Southern Europe where the virus spread more rapidly.
The shutdown was accompanied by measures to financially support households and businesses. Within the first week after 11 March, the Danish government proposed a series of programmes that received unanimous support in the parliament. The programmes were similar in scale and scope to those launched by many other governments in Europe (Anderson et al. 2020).
How much did total card spending drop?
Figure 1 shows the changes in aggregate daily spending in 2020 for the bank’s customers, measured relative to the average value in 2019. For comparison, the figure also shows aggregate spending for a reference day 364 days earlier, which is always the same day of the week and almost exactly the same place in the monthly and annual spending cycle.
Both series are volatile – with a pronounced weekly cycle with spikes around weekends as well as a monthly cycle with spikes around paydays – but they are strikingly similar in the period before the shutdown on 11 March. After the shutdown, however, there is a clear divergence, with 2020 spending falling short of 2019 levels, as indicated by the shaded area.
Figure 1 Aggregate card spending
Notes: The figure shows the evolution of daily average card spending in 2020 (red line) and on equivalent days in 2019 (grey line), where each series is shown as a percentage of average daily card spending throughout 2019. Labelled ‘paydays’ are the final bank day of the month when the majority of individuals in Denmark receive their salary and/or government transfers.
Our headline estimate is that card spending dropped by around 25% in response to the crisis. Figure 2 illustrates how we get at this number: before the 11 March shutdown, daily spending was on average 2% higher in 2020 than on the 2019 reference day.1 After the shutdown, consumers spent 23% less than in the reference period. Under the assumption that the year-on-year growth from 2019 to 2020 would have remained constant absent the crisis, the difference between these two numbers is the causal effect of the crisis on total spending.
Figure 2 The impact of the COVID-19 crisis on aggregate card spending
Notes: The figure illustrates how we estimate the effect of the crisis on total card spending. The left blue bar shows the average difference in daily spending relative to the reference day for the period 1 January–15 February 2020. The middle bar shows the corresponding average for the period 12 March–5 April 2020. The right red bar shows the difference between these averages, which is our headline estimate of the effect of the crisis.
What did consumers cut back on?
Figure 3 shows similar estimates for selected expenditure groups. Spending responses to the shutdown vary widely across categories: spending in grocery shops and pharmacies is moderately elevated relative to the counterfactual (blue bars), whereas spending on restaurant meals, travel, retail, personal services, fuel, and entertainment exhibit pronounced decreases (red bars).
Figure 3 The impact of the COVID-19 crisis on categories of spending.
Notes: The figure shows the impact of the COVID-19 crisis on spending at different categories of merchant, identified using Merchant Category Codes associated with card payments. Each bar shows the estimated impact on daily spending in the indicated category, measured relative to average daily spending in that category in 2019.
Spending responses are closely linked to the restrictions on mobility and activity imposed by the government to prevent the spread of the virus. Figure 4 makes this point more formally by showing estimates of the spending response for three different sectors: an ‘open’ sector where supply was totally unconstrained by government interventions (e.g. supermarkets, pharmacies, online retail); a ‘constrained’ sector where government interventions had some effect on supply (e.g. offline retail where malls were shut down but high-street shops allowed to remain open); and a ‘closed’ sector where the shutdown led to a near-complete elimination of supply (e.g. travel, restaurants, hairdressers, dentists).
Figure 4 Supply constraints
Notes: The figure shows the impact of the COVID-19 crisis on consumer spending in the open, constrained, and closed sectors of the economy under government controls. See Andersen et al. (2020) for details on how we define each sector.
The three sectors fared very differently: we estimate spending responses of around 10% for the open sector, -40% for the constrained sector, and almost -70% for the closed sector.
It is unsurprising that spending on goods and services produced in the closed sector falls: with supply effectively cut off, spending is bound to decline. The modest increase in spending in the open sector (which accounts for around half of the economy) is noteworthy, however, because it suggests a limited role for negative spillovers of supply shocks through the demand side, at least within the relatively short timeframe covered by our analysis.
Who cut back the most?
Figure 5 shows the impact of the COVID-19 crisis on total spending across groups that were differentially exposed to the pandemic and the shutdown. Three points emerge from the figure.
First, individuals who are financially more exposed to the economic fallout from the crisis – because they work in private businesses directly affected by the shutdown or because they own stocks – reduced spending more than the financially less exposed (public sector employees, non-stock owners). But the differences across these groups are quite modest.
Second, the elderly cut back more than younger individuals did. Since the elderly are more likely to suffer severe health consequences if infected with the virus, this suggests a role for exposure to health risk as a driver of the drop in spending.
Third and finally, direct exposure to the shutdown of economic sectors such as restaurants and international travel correlates strongly with the size of the drop in spending during the crisis: individuals who spent most in these sectors before the shutdown reduced card spending by 12 percentage points more than those who spent the least.
Figure 5 Individual heterogeneity
Notes: The figure shows the impact of the COVID-19 crisis on total card spending for groups of individuals who differ in exposure to particular risks associated with the crisis and the shutdown. Observations are weighted so that each group is representative of the full sample in all observable characteristics, except the one highlighted (see Andersen et al. 2020 for details).
These results provide some insights into the mechanisms underlying the massive drop in aggregate spending. Differential exposure to economic risks and health risks can account for some of the variation in spending responses but not nearly all of it. Pre-crisis spending shares on goods and services provided by the closed sector is clearly the strongest correlate of spending responses.
Vir: Lau Andersen, Toft Hansen, Johannesen & Sheridan, 2020, VoxEU