An informed strategy for lockdown exit

The only to way to climb back to obstacle-free growth would be more and randomised testing. The government needs to make a much larger financial allocation towards that

Economists have started writing somewhat furiously on the economic impact of Covid-19. One could perhaps argue that this is about the worst time to heed their ad­vice. Things are best left to the medical community and epidemiologists. How­ever, this emerging economic “literature” on Covid (ELC in short) raises some interesting issues that the government might take on board in devising a strategy that balances the need to save lives with the need to save livelihoods.

Here’s how ELC frames the policy problem. The key constraint during a lo­ckdown is the freeze in labour supply that “social distancing” demands. The endeavour then is to find a point in the infection cycle when a stable labour force can re­sume productive activity without the risk of disruption. Clearly there is a strong ca­se for “testing” as much as possible but how can the government use the results to egress from an aggressive containment strategy? [Stock, J H (2020), “Data Gaps and the Policy Response to the Novel Co­ronavirus,” NBER Working Paper 26902].

India’s current testing strategy has two related problems. To begin with, the ro­ughly 200,000 tests that the ICMR has conducted is pitifully inadequate for population of our size. The “rationing” of testing infrastructure has led to an unavoidable focus on those that have pronounced symptoms or with identified infection ri­sk such as foreign travel or contact with infected cases. It measures the rate of in­cidence in a pool of people that have ele­vated Covid risk to begin with. This drives a large bias in the sample. These tests le­ave policymakers no wiser about the rate of infection in the population, the likely fraction of cases in that have either mild or no symptoms or the true mortality rate of the disease.

In the absence of this vital information, the first step towards graded exit strategy in the Home Ministry’s guideli­nes (announced on April 15) seems sensible. It embeds an economic criterion to identify the criticality of a particular sector in preventing a supply shock (food shortage for example) and in generating some employment. Thus agriculture, co­nstruction and MNREGA work figure on top of the list. The risk of an infection spiral is mitigated by banning economic ac­tivity in identified containment zones and extending the curb on movement of workers.  

 

Going forward, more sectors are likely to be added to this list. While this would enable a calibrated economic revival, the strategy has its share of problems. The curb on activity in containment or “red zones” could affect supply chains. A producer in a green zone could see his production hobbled if the factory of a critical input provider happens to fall in red zone.

India is not only an integrated market, but an integrated production complex as well. For many sectors to open shop, exit guidelines will have to look beyond the contaminated versus safe zone approach and consider all the links in the production chain of a good. However, if the government dilutes its containment strategy in the interest of supply or delivery chain preservation, infection rates could in­cre­ase leading to another lockdown and so forth. We might be stuck with intermittent or rolling lockdowns going forward.

Is there a better way of doing this in the medium term? ELC leaves us with so­me provocative questions. At some point should the government take the risk of letting infections increase so that an im­mune work force that could survive a second wave of the virus can emerge? Is “he­rd immunity” the only solution in the absence of a vaccine or effective treatment?

The key decision variable, according to ELC contributors like James Stock (if indeed the government can increase testing exponentially) is the asymptomatic rate (AR) of Covid — the fraction of cases in which the infected show no or only mi­ld symptoms. If this is high, then a large fraction of the labour force can be allowed to resume work. Only the susceptible (the elderly or severely diabetic for instance ) need to be protected. Even if there is a ri­se in the number of infections, economic disruption is likely to be minimal since the disease manifestation would, at wo­rst, be mild. The ultimate benefit would be the so-called herd immunity that the labour pool acquires that should shield it from a second wave of the virus.

China’s example is important here. In­direct estimates peg China’s AR at 86 per cent (Li, R et al. (2020), “Substantial un­documented infection facilitates the rapid dissemination of novel coronavirus,” Science). While the Chinese government did not release this data, it perhaps had some estimate of this rate that gave it the confidence to lift curbs on production fairly early.

Prima facie there is reason to believe that India’s AR would be high. Based on current testing data, the infection rate is remarkably low — about eight per million population compared to 1,200 in the US, 800 in the UK and 56 in China. Some of this could be due to large underreporting of cases. However, a difference of this ma­gnitude with other economies is more li­kely if either the AR is high or if the Indian population is genuinely more resilient to the virus.

The search for a reliable AR does not mean that the entire population the la­bour force needs to be tested. That is cle­arly infeasible. Robust sampling methods that can give us reliable measure of AR based on a representative fraction of the population.

The bottom line is that testing does not merely have to be ramped up; it has to become more randomised. The government needs to make a much larger financial allocation towards testing. The sample survey and its analysis will have to be geared to generating an AR quickly. This might well be the only to way to climb back on higher and obstacle-free growth path.

The  author  is  chief  economist  & executive vice-president, HDFC Bank