Abstract
ObjectiveThis study considered the role of institutional, cultural and economic factors in the effectivemess of lockdown measures during the coronavirus pandemic. Earlier studies focusing on cross-sectional data found an association between low case numbers and a higher level of cultural tightness. Meanwhile, institutional strength and income levels revealed a puzzling negative relationship with the number of cases and deaths.MethodsData available at the end of September 2021 were used to analyse the dynamic impact of these factors on the effectiveness of lockdowns. The cross-sectional dimension of country-level data was combined with the time-series dimension of pandemic-related measures, using econometric techniques dealing with panel data.FindingsGreater stringency of lockdown measures was associated with fewer cases. Institutional strength enhanced this negative relationship. Countries with well-defined and established laws performed better for a given set of lockdown measures compared with countries with weaker institutional structures. Cultural tightness reduced the effectiveness of lockdowns, in contrast to previous findings at cross-sectional level.ConclusionInstitutional strength plays a greater role than cultural and economic factors in enhancing the performance of lockdowns. These results underline the importance of strengthening institutions for pandemic control.
Highlights
Instead of investigating the pandemic at a point in time, we investigate the factors that affect the efficacy of the lockdown measures over time
The first lag addresses the reverse causality between the lockdown measures and the new cases
In the absence of any rule of law (ROL), a 10-unit increase in lockdowns leads to a 6% reduction in the new cases, on average
Summary
Instead of investigating the pandemic at a point in time, we investigate the factors that affect the efficacy of the lockdown measures over time. We use daily data on new cases, tests, vaccinations, and lockdowns. Our dependent variable is new cases in a country. The first lag addresses the reverse causality between the lockdown measures and the new cases.
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