The “Great Lockdown” and its determinants
Ferraresi M., Kotsogiannis C., Rizzo L., Secomandi R., 2020 – Economic Letters
Since COVID-19 was declared a pandemic in the first months of 2020, governments around the world have struggled to contain its spread and repercussions implementing a vast array of restrictive strategies in terms of timing, stringency, and intensity. Interestingly, their responses have varied significantly for those countries on the same pandemic trajectory. While some countries announced stringent measures, restricting the movement of the population, very early in the pandemic cycle, others took a less restrictive approach. To name a few, Greece and Belarus, for example, took early actions, while Sweden (and UK initially) tried to minimise social and economic disruption cultivating wider immunity. The Czech Republic and the New Zealand on the other hand imposed a lockdown before its first case was even recorded.
Why did countries react so markedly differently? What are the determinants of lockdown measures?
A possible answer is offered by Ferraresi Massimiliano, Kotsogiannis Christos, Rizzo Leonzio, and Secomandi Riccardo in a their article “The ‘Great Lockdown’ and its determinants”, recently published in Economic Letters.
Using data for over 132 countries over the period January to April 2020, the first wave of COVID-19, they investigate the dynamics between the spread of the pandemics and the stringency of measures that followed and, more importantly, the potential role of a broad array of political, economic, and institutional factors in explaining the differential timing and intensity of the undertaken policies across countries.
The analysis is based on an event-study approach, a statistical technique which allows to follow the evolution of governments’ response in terms of stringency of the lockdown strategies adopted over time and across countries since the outbreak of the virus, while controlling for country and daily fixed effects. Yet, since this approach does not allow for other country characteristics to be factored in, the authors group countries in terms of high/low level values in relation to six different dimensions, namely (i) politics, (ii) democracy, (iii) level of development, (iv) digitalization, (v) structure of government, and (vi) degree of openness. The idea is to capture, and therefore compare, the differential reactions of the two groups of countries (high vs low) in adopting lockdown measures while controlling for the same level of the spread of the virus. We classify the country in the low level group when the considered variable is lower than the value assumed at the 75 percentile, while the country is classified as belonging high level group when the considered variable is higher than the value assumed at the 75 percentile.
The spread of the virus is captured by data on the total number of COVID-19 related cases, taken from Johns Hopkins Center for System Science and Engineering. Moreover, to take into account the heterogeneity of the governments’ response, a Government Response Stringency Index (Stringency Index), recently developed by Hale et al., (2020)is employed.
Results may be easily summarized in the figures that follow.
In general, the study finds that the further each country is from the day zero of the pandemic (defined as the day with the first ten Covid-19 cases), the stronger the stringency measure is. However, their level depends on political and socio-economic and institutional characteristics of the countries. To begin with, political factors are considered in Figure 1.
Countries close to the election year might have different incentives to lockdown the economy relative to countries which find themselves in different part of the political cycle. Panel A reveals that countries in a pre-electoral year adopted more stringent measures against the pandemic as compared to countries in other years of the term, suggesting that drastic lockdown measures can be used as a tool to increase the political consensus. This result lends support to the argument that early adoption of measures signals that incumbent politicians care about the health status of their citizens, which after the pandemic has become a very salient policy issue.
Then, in Panel B, the relationship between political stability – a proxy for the level of democracy – and stringency measures is shown: their link is a priori ambiguous. According to the estimates, stringency measures are significantly lower in countries characterised by political instability, thus indicating that political divisions make it harder to introduce stringent lockdowns.
Fig. 1. Stringency of lockdown measures and political factors.
In Figure 2, economic factors are taken into account.
As it is shown in Panel A, developed countries (as measured by their level of Gross National Income – GNI) adopted more stringent measures as compared to developing ones, at least in the initial phase of the pandemic. An explanation for this is that for developing countries the cost of lockdowns, namely the interruption of all economic activities, is much higher than that of developed countries.
In a similar vein, the degree of digitalisation shapes the intensity of the lockdown, as depicted in Panel B of Figure 2. Countries characterised by a low level of digitalisation (those that have a Digital Adoption Index below its 75th percentile) implemented less marked stringency measures than countries with high level of digitalisation (those that have a Digital Adoption Index above its 75th percentile), as the cost borne by low-digitalised countries in locking-down the economy is higher than that of the high-digitalised ones.
Fig. 2. Stringency of lockdown measures and economic factors.
Lastly, Figure 3 shows results for institutional factors and more specifically the link between stringency measures and the degree of decentralization, captured by the variable number of government layers,and the degree of openness, captured by exports plus imports of goods as quota of GDP.
Fig. 3. Stringency of lockdown measures and institutional factors.
In centralised countries (those with a number of government layers lower than its median value, 4) lockdown measures are more stringent than those put in place by decentralised ones, as shown in Panel A. A possible explanation is that in countries where policy making is decentralised coordination across the levels of government can be ineffective. This, to some extent, confirms the existing evidence regarding the difficulties in providing a well-coordinated response to the COVID-19 emergency across government levels experienced by the Latin America countries, and in the U.S.. While decentralisation has been shown to enhance accountability and be conducive to economic growth, when it comes to a collective response necessary to deal with the current pandemic, it fares less well.
Finally, in Panel B, grouping countries in closed (openness indicator below the 75th percentile) and open (openness indicator above the 75th percentile) shows that the higher the level of openness of a country the less significant stringency measure will be adopted. The intuition behind this result is that more open economies react slower in imposing measures because disrupting trade and movement is not only too costly but it also takes time.
To conclude, the main findings of this study can be summarized as follows. Countries characterized by (i) low political stability; (ii) low level of development; (iii) low level of digitalization; (iv) high degree of decentralization; (v) closed-economy, and (vi) being away from electoral years, have adopted less stringent measures.
These observations support the view that a country’s institutional features play a key role in shaping the country’s attitude and response also when the implementation of restrictive measures is at stake. Understanding the determinants of lockdown is therefore very important as are the factors for successful pandemic responses in the future. Next step is understanding the impact of the lockdown on economic outcomes and political institutions. Discussion on this has already started (See Fukuyama, F., The pandemic and political order, Foreign Affairs, July/August 2020.).