GDP effects of pandemics: a historical perspective

Abstract

The paper estimates dynamic effects of pandemics on GDP per capita with local projections, controlling for the effects of wars and weather conditions, using a novel dataset that covers 33 countries and stretches back to the thirteenth century. On average, pandemics are found to have prolonged and highly statistically significant effects on GDP per capita-a pandemic killing 1% of the population tends to increase GDP per capita by approx. 0.3% after about 20 years. The study of a more detailed dataset available for the UK reveals that this results mainly from an increase in per capita land and a disproportionate impact of pandemics on low-productivity workers, while monetary expansion, institutional change and innovation could also play some role. At the same time, the effects of pandemics are found to vary with scale and across time and countries, with positive effects present following the Black Death and the Spanish flu pandemics, especially in Northern Europe. This suggests that only the largest and most unexpected pandemics have a positive impact on income.

Keywords: Economic history; GDP; Local projection; Pandemic; Tree rings; War.

Fig. 1

Data on the size of the pandemics (% of population killed in a given year, log scale). Source: Own compilation based on various sources—see "Appendix Section 10.1.1" for details

Fig. 2

Cross correlation plots

Fig. 3

GDP per capita in the sample of 33 countries (2011 USD PPP, log scale). Source: Own calculations based on Maddison Project Database, extended with Malanima (2011) for Italy and Prados de la Escosura et al. (2020) for Spain

Fig. 4

Response of GDP per capita to a pandemic resulting in the death of 1% of the population in a given year. Shaded area is a 90% confidence band around response estimates

Fig. 5

Response of GDP per capita to a pandemic event (binary pandemic variable specification). Shaded area is a 90% confidence band around response estimates

Fig. 6

Response of GDP per capita to a war (left panel) and one standard deviation increase in tree ring index (right panel). Shaded areas are 90% confidence bands around response estimates

Fig. 7

Response of GDP per capita, absolute GDP and population in the UK to a pandemic resulting in the death of 1% of the population in a given year. Shaded areas are 90% confidence bands around response estimates

Fig. 8

Response of land per capita, GDP per hour worked and real wages in the UK to a pandemic resulting in the death of 1% of the population in a given year. Shaded areas are 90% confidence bands around response estimates

Fig. 9

Sector responses of per capita output in the UK to a pandemic resulting in the death of 1% of the population in a given year. Shaded areas are 90% confidence bands around response estimates

Fig. 10

Responses of money supply and CPI in the UK to a pandemic resulting in the death of 1% of the population in a given year. Shaded areas are 90% confidence bands around response estimates

Fig. 11

Response of GDP per capita to a pandemic resulting in the death of 1% of the population in a given year: sample subperiods. Shaded areas are 90% confidence bands around response estimates

Fig. 12

Response of GDP per capita to a pandemic: nonlinear specification with respect to the pandemic size. Impulse responses are scaled per 1% annual pandemic death toll

Fig. 13

Mean group estimation for long-sample countries: response of GDP per capita to a pandemic resulting in the death of 1% of the population in a given year. Shaded area is a 90% confidence band around response estimates. Long-sample countries are countries with at least 400 observations: Spain, France, UK, Italy, Netherlands, Poland, Portugal, and Sweden

Fig. 14

Response of GDP per capita to a pandemic resulting in the death of 1% of the population in a given year: Europe (left panel) vs the rest of the world (right panel). Shaded areas are 90% confidence bands around response estimates

Fig. 15

Response of GDP per capita to a pandemic resulting in the death of 1% of the population in a given year: alternative model specifications

Fig. 16

Response of GDP per capita to a pandemic resulting in the death of 1% of the population in a given year: alternative approaches to non-stationarity of GDP per capita

Fig. 17

GDP per capita following a pandemic resulting in the death of 1% of the population in a given year: response to a country-specific shock (left panel) and a common shock (right panel). Shaded area are 90% confidence bands around response estimates

Fig. 18

Response of GDP per capita to a pandemic resulting in the death of 1% of the population in a given year: CCE vs baseline. For CCE, the response to a pandemic resulting in the death of 1% in each of the countries in the sample

Fig. 19

Data on the incidence of wars. Source: Own compilation based on various sources

Fig. 20

Tree ring growth data. Source: Own compilation based on the sources from the NOAA Paleoclimatology database (for details see Table 3)

Fig. 21

GDP per capita data (log scale). Source: Maddison Project Database (2018 edition), Malanima (2011), Prados de la Escosura et al. (2020)

Fig. 22

Response of GDP per capita to a pandemic resulting in the death of 1% of the population in a given year: individual country estimates

Fig. 23

Response of GDP per capita to a pandemic resulting in the death of 1% of the population: nonlinear specification with respect to time

Fig. 24

Response of GDP per capita to a pandemic resulting in the death of 1% of the population in a given year: rolling window estimates

Fig. 25

Response of GDP per capita to a pandemic: nonlinear specification with up to 3rd order polynomials. Impulse responses are scaled per 1% annual pandemic death toll

Fig. 26

Mean group estimation for the full sample: response of GDP per capita to a pandemic resulting in the death of 1% of the population in a given year. Shaded area is a 90% confidence band around response estimates

Fig. 27

Post-WW2 sample: response of GDP per capita to a pandemic resulting in the death of 1% of the population in a given year. Shaded areas are 90% confidence bands around response estimates