View: Categorise districts by their disease-load and projected growth against potential economic gains

Indian farmers are currently struggling to harvest and sell their rabi crops, and will soon need to prepare for the kharif season.By Jyotsna Jalan & Arijit Sen

As the first phase of countrywide Covid-19 lockdown came to an end on April 14, GoI immediately announced a second lockdown till May 3. On April 15, it announced guidelines for the resumption of work, including agricultural, and reopening manufacturing establishments from April 21. While prolonging stringent lockdowns may ‘flatten the

curve’, the inordinate economic costs this imposes upon the country in general, and upon its poorest citizens in particular, are dire.

As an April Centre for Economic Policy Research(CEPR) report (bit.ly/2z3Ends) states, India’s lockdown ‘is not a choice between lives on the one hand and loss of economic production on the other… it is a question of lives versus lives’.

Recognising this, many have urged for selective relaxation of lockdowns. On its part, GoI is reportedly collecting data to fine-tune district level lockdowns by differentiating between Red, Amber and Green districts on the basis of Covid-19 penetration. This challenging exercise will need to balance a district’s disease-load and its projected growth against potential economic gains from relaxing lockdowns.

We focus on one part of this exercise by limiting attention to predominantly agricultural districts. Indian farmers are currently struggling to harvest and sell their rabi crops, and will soon need to prepare for the kharif season. While the agricultural sector has been exempted from the continuation of lockdown till May 3 in Wednesday’s announcement, countrywide lockdowns are nevertheless impeding farm activities — by restricting labour movement, access to farm machinery and trading opportunities in mandis.

Choose the Colour

In this context, here are four observations: (1) Covid-19 penetration in rural districts has been much lower than in urban districts, and there is significant variation in Covid-spread across districts; (2) district borders can be sealed and interventions can be contained within districts (as revealed by the ‘Bhilwara’ experience in Rajasthan); (3) agriculture allows for relatively greater social-distancing than many manufacturing activities; and (4) marginal farmers and farm labourers constitute a large part of India’s economically vulnerable population.

We identify 481 predominantly rural agricultural districts (in each district, at least 60% of the population lives in

rural areas and the net sown area is at least 35% of total area) that contain 76% of India’s population. We find that 270 of these districts have not yet been penetrated by Covid-19, and are thus prime candidates for ‘unlocking’.

For the 211 affected agricultural districts, we determine two district-level variables (as on midnight, April 13): ‘disease-load’, which counts all infections in a district arising from contacts within India; and ‘disease-growth index’, a weighted average of 24-hour changes in disease-load over April 6- 13, with greater weights on more recent changes to incorporate growth acceleration/deceleration.

Districts have been categorised into good, average and bad, in each dimension. For disease-load, districts

carrying more than three times the average-load are deemed ‘bad’, while those carrying less than the averageload are ‘good’. For disease-growth, all districts with growth-indices greater than 1 are considered bad, and all with non-positive growth-indices, good.

Then, taking a conservative stance, we categorise a district to be Green (candidate for mild lockdown restrictions) only if it is good in both categories, to be Red (stringent restrictions) whenever it is bad in at least one category, and Amber (moderate restrictions) in all other cases.

Such a mapping exercise has, so far, identified — among rural agricultural districts — 111 Green districts, 72

Amber districts, and 28 Red districts. We have focused only on the agricultural sector. But the identified districts

do have — in some cases, substantial — industrial and urban areas. Appropriate lockdown policies for these areas have to be designed separately.

Even within agriculture, the government needs to consider the following additional issues. First, the economic value of the increased agricultural output arising from lockdown relaxation from different districts needs to be imputed, so that higher-value Green and Amber districts can be ‘opened up sooner’.

Second, recognising the need for transporting perishable products to eventual buyers and less-perishable products to storage facilities, the government has to envision a freight network among rural and urban districts. Just as medical professionals and equipment are essential to fighting Covid-19, freight trains and associated personnel have been rightly considered to be essential in the postApril 20 guidelines for resuming work.

Getting It Right

Third, unanticipated shocks will undoubtedly alter disease trajectories over time. The administration has to be ready, and willing, to appropriately recategorise districts in response to such shocks.

Recognising all the difficulties in implementing ‘selective lockdowns’ on the ground, here are some fundamental principles behind categorising rural districts for lockdown relaxation. And while this categorisation exercise is challenging, doing the same for the urban districts will constitute a much bigger challenge — where more variables need to be incorporated in the cost-benefit analysis. Alas, playing god is never easy.


Jalan and Sen are professors of economics, Centre for Studies in Social Sciences, Kolkata, and Indian Institute
of Management, Kolkata, respectively

Source: indiatimes.com