Pandemic, Shutdown and Consumer Spending: Lessons from Scandinavian Policy Responses to COVID-19

Abstract

This paper uses transaction data from a large bank in Scandinavia to estimate the effect of social distancing laws on consumer spending in the COVID-19 pandemic. The analysis exploits a natural experiment to disentangle the effects of the virus and the laws aiming to contain it: Denmark and Sweden were similarly exposed to the pandemic but only Denmark imposed significant restrictions on social and economic activities. We estimate that aggregate spending dropped by around 25 percent in Sweden and, as a result of the shutdown, by 4 additional percentage points in Denmark. This implies that most of the economic contraction is caused by the virus itself and occurs regardless of whether governments mandate social distancing or not. The age gradient in the estimates suggest that social distancing reinforces the virus-induced drop in spending for individuals with low health risk but attenuates it for individuals with high health risk by lowering the overall prevalence of the virus in the society.

The shock of lockdown on the spending on wine in the Iberian market: the effects of procurement and consumption patterns

“…In the case of the COVID-19 crisis in the United Kingdom, Chronopoulos et al (2020) observed an increase in grocery spending associated with panic buying during the two weeks following the announcement by the World Health Organisation (WHO) that COVID-19 was a pandemic and there was a reduction in spending between January and June 2020. A similar result was observed in Denmark and Sweden (Andersen et al, 2020) and the United States (Coibion et al, 2020), with a reduction above the average in textiles and travel. To verify what happened in the case of wine, we formulated the following sub-hypothesis: H1.3.…”

“…One of the aspects affected in a crisis is the composition of spending, both due to the change in the quantity purchased and the price paid for the different goods and services included in the shopping basket (Coibion et al, 2020;Andersen et al, 2020).…”

When and How to Lift the Lockdown? Global COVID-19 Scenario Analysis and Policy Assessment using Compartmental Gaussian Processes

“…Because different countries with comparable features apply different policies, the upper-layer GP function f U (X, p) in (4) will learn counterfactual fatality curves for each country under alternative policies that have been tried in other countries (See Fig 2(c)). For instance, we can learn the fatality curves for Scandinavian countries (such as Norway and Denmark) under a hypothetically less restrictive lockdown policy using data from Sweden, which adopted less stringent policy measures [11].…”

“…We characterize each country with a feature vector that comprises economic, social, demographic, environmental and public health indicators; "counterfactual" fatality curves under a hypothetical policy for a given country are thus inferred from "factual" fatality curves of countries "similar" in features wherein this policy was actually implemented. (For example, our model would use data from Sweden to predict what the number of fatalities in Norway would have been under a "herd immunity" policy [11].) We envision that our model would be used by policy-makers to conduct scenario analyses by assessing the volume of COVID-19 fatalities under different possible policiesthis is especially timely as governments seek policies for gradual lifting of lockdown measures [12].…”

Investigating the Epidemiological and Economic Effects of a Third-Party Certification Policy for Restaurants with COVID-19 Prevention Measures

“…A common intervention is to place operating restrictions, if not completely shut down, on restaurants as eating and drinking indoors are associated with high risks of COVID-19 transmission [1][2][3][4] [5] [6]. With consumers also cautious about dining out, food and beverage (F&B) has been one of the hardest hit industries [7][8] [9] [10].…”