Co-Authors: Shiela Camingue-Romance; Irfan Qureshi; Shu Tian.

To halt the spread of Covid-19, Asian countries have imposed varying forms and degrees of restrictions, ranging from nationwide lockdown – e.g., India and Malaysia – to much more targeted policy responses – e.g., Japan and Korea. The diversity of restrictions across the region reflects the diversity of technological, administrative, and other country-specific factors. For example, Korea did not have to resort to stringent restrictions because it has a technologically advanced contact tracing system. But the Korean experience is unlikely to be relevant to countries that do not have advanced technology and strong administrative capacity.

Countries have implemented a great variety of containment policy measures – workplace and school closures, travel bans and limitations on movement, closure of public transport, restrictions on gatherings, and cancellations of public events. To enable cross-country analysis of overall effects, we make use of a readily available "stringency index" that consolidates these measures, with values shown in Figure 1 for economies in Asia. Indirectly, the stringency of policy measures can be inferred from mobility loss, as plotted against the stringency index in the figure. Both measures are taken as averages over monthly data for the period March to May, 2020. Taiwan lies at one extreme with very limited restrictions and little loss of mobility, the Philippines at the opposite extreme with heavy restrictions and severe loss of mobility.

Empirical evidence from a few selected economies suggests that containment measures are an effective public health approach to flatten the pandemic curve and significantly reduce the number of fatalities.* However, while these measures may stem the transmission of the pandemic, they tend to incur short-term economic costs. Intuitively, containment measures disrupt production and transportation, thus crimping economic activity.

To examine the impact of pandemic-induced policy measures on economic activity, we estimate the following fixed-effects model, controlling for the implementation of fiscal and monetary policy measures:

The equation is made up of two blocks: the containment block and the macro policy block. The containment block includes the Stringency Index (SI), which measures restrictions on behavior for economy i in month t, and Mobility (M), which measures the change in movement trends of people across different categories or places. The macro policy block includes announced Fiscal Stimulus (FS) measures and Monetary Policy Indicators (MPI), including both an interest rate and a measure of central bank assets. All macro policy variables are measured at time t-1 assuming a one month lag before policies have an impact. The model posits effects on economic activity (Y) measured in two aspects: growth in Industrial Production, which captures manufacturing, mining, and utilities; and growth in Retail Sales, which captures purchases of finished goods and services by consumers and businesses.

The data cover the period December 2019 to May 2020 at monthly frequency. The sample includes 46 economies, seven of which are Asian (Hong Kong, Indonesia, Japan, Kazakhstan, Korea, Malaysia, and Taiwan). Data are available for about 120 observations

Figure 2 summarizes the estimated impact of containment stringency and changes in mobility on both industrial output and retail sales. In general, we can infer that economies that impose tighter containment suffer greater economic consequences. Specifically, a 1% increase in mobility leads to an expected increase of 0.52% in industrial output growth and a 0.76% increase in retail sales growth. The stringency index, however, seems to be insignificantly related to economic activity. A possible explanation for this result is that since there are multiple components of the stringency index, it may be that some types of containment measures have an effect while others do not, and a more refined measure would be needed to discern this. For instance, among different types of containment measures, workplace closures, stay-at-home orders, and cancellation of events may be more costly in terms of impact on economic activity (even as they are more effective in flattening Covid-19 infections), while other components of the index may be less costly.

What do the results of the analysis imply for macro policy? Many countries have deployed large fiscal stimulus programs and eased their monetary policies since the Covid-19 outbreak began. But it is difficult to disentangle the effectiveness of fiscal and monetary policy from the impact of mobility loss and other Covid-related damages. Further, many other factors also influence economic resilience. For example, financial technology can improve the access of underserved vulnerable groups to finance, which boosts their economic resilience. Therefore, a more thorough analysis is required to assess the effectiveness of fiscal and monetary policy in countering the effects of the virus and measures aimed at fighting it.

Finally, while containment measures deployed by many countries have reduced mobility, the reverse should also hold. That is, a reduction in the stringency of containment should in principle increase mobility. Economies that are easing containment measures should thus see gains in mobility, which are likely to boost economic activity. The rapid and robust recovery of the Chinese economy since the relaxation of restrictions is testament to the positive economic impact of greater mobility. Indeed China is one of the few major global economies that will grow rather than contract this year. Nevertheless, policymakers should consider country-specific factors in easing containment measures. Regardless of income and development level, countries should give priority to limiting the spread of the virus so as to flatten the pandemic curve and significantly reduce the number of new infections and fatalities. After all, unless and until the pandemic is contained, at least to some extent, consumer and business confidence is bound to remain fragile, which will inhibit economic activity.

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*See Kraemer et al., 2020; Chinazzi et al., 2020; Tian et al., 2020; Hsiang et al., 2020; Deb et al., 2020.

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Co-authors Shiela Camingue-Romance, Irfan Qureshi, and Shu Tian are with the Asian Development Bank.