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How has Covid-19 affected India’s economy?

India has been hit hard by the pandemic, particularly during the second wave of the virus in the spring of 2021. The sharp drop in GDP is the largest in the country’s history, but this may still underestimate the economic damage experienced by the poorest households.

From April to June 2020, India’s GDP dropped by a massive 24.4%. According to the latest national income estimates, in the second quarter of the 2020/21 financial year (July to September 2020), the economy contracted by a further 7.4%. The recovery in the third and fourth quarters (October 2020 to March 2021) was still weak, with GDP rising 0.5% and 1.6%, respectively. This means that the overall rate of contraction in India was (in real terms) 7.3% for the whole 2020/21 financial year.

In the post-independence period, India's national income has declined only four times before 2020 – in 1958, 1966, 1973 and 1980 – with the largest drop being in 1980 (5.2%). This means that 2020/21 is the worst year in terms of economic contraction in the country’s history, and much worse than the overall contraction in the world (Figure 1).

The decline is solely responsible for reversing the trend in global inequality, which had been falling but has now started to rise again after three decades (Deaton, 2021; Ferreira, 2021).

Figure 1: Economic contraction in India and the world during Covid-19

Source: World Economic Outlook, International Monetary Fund, April 2021.
Note: The gross domestic product (GDP) per capita, constant prices is measured at purchase power parity; 2017 international dollars. the GDP per capita of each series is normalised to 100 in 2011. We use population-weighted average as the aggregation method.

What do the main macroeconomic indicators tell us about India’s economy during the pandemic?

While economies worldwide have been hit hard, India has suffered one of the largest contractions. During the 2020/21 financial year, the rates of decline in GDP for the world were 3.3% and 2.2% for emerging market and developing economies. Table 1 summarises macroeconomic indicators for India, along with a reference group of comparable countries and the world. The fact that India’s growth rate in 2019 was among the highest makes the drop due to Covid-19 even more noticeable.

Comparing national unemployment rates in 2020, India’s rate of 7.1% indicates that it has performed relatively poorly – both in terms of the world average and compared with a set of reference group economies with similar per capita incomes. Unemployment rates were more muted within the reference group economies and were also kept low by generous labour market policies to keep people in work.

Despite the scale of the pandemic, additional budgetary allocation to various social safety measures has been relatively low in India compared with other countries. Although the country might look comparable to the reference group in non-health sector measures, the additional health sector fiscal measures are less than half those in the reference group. More worryingly, the Indian government's announced allocation in the 2021 budget for such measures does not show an increase, once inflation is taken into account.

Table 1: Summary of key macroeconomic indicators

 IndiaReference groupWorld
GDP at constant prices 2019 (% change)4.0%3.6%2.8%
GDP at constant prices 2020 (% change)-7.3%-2.2%-3.3%
Unemployment rate 2019 (% of total labour force)5.3%5.5%5.4%
Unemployment rate 2020 (% of total labour force)7.1%6.4%6.5%
Above-the-line additional health sector fiscal measures in response to Covid-19 (% of GDP)0.4%0.9%1.2%
Above-the-line additional non-health sector fiscal measures in response to Covid-19 (% of GDP)3.0%2.8%7.8%
Source: Data on gross domestic product, constant prices (percentage change) is obtained from the World Economic Outlook Database April 2021, International Monetary Fund.
Note: India’s GDP contraction is 8%, according to the International Monetary Fund (IMF) and 7.3% from recent national estimates. Unemployment rates (for youth, adults: 15+) are ILO-modelled estimates as of November 2021 and are obtained from ILOSTAT, International Labour Organization (ILO) and World Bank. Fiscal measures are obtained from Fiscal Monitor Database of Country Fiscal Measures in Response to the COVID-19 Pandemic as of April 2021, International Monetary Fund. The ‘reference group’ refers to the closest peer group statistic under which India falls. The reference group for GDP per capita is the emerging market and developing economies (EMDEs) classification by the IMF. The reference group for the unemployment rate is the low- and middle-income countries (LMICs) classification by the World Bank. The reference group for the fiscal measures is the EMDEs classification by the IMF. See Ghatak and Raghavan (forthcoming) for a comparison of India’s economic and health performance against the reference group.

How has Covid-19 changed income, consumption, poverty and unemployment in India?

While the macroeconomic statistics provide a snapshot of India’s economic position, they hide the large and unequal effects on households and workers within the country.

Both wealth and income inequality has been on the rise in India (Ghatak, 2021). Estimates suggest that in 2020, the top 1% of the population held 42.5% of the total wealth, while the bottom 50% had only 2.5% of the total wealth (Oxfam, 2020). Post-pandemic, the number of poor in India is projected to have more than doubled and the number of people in the middle class to have fallen by a third (Kochhar, 2021).

During India’s first stringent national lockdown between April and May 2020, individual income dropped by approximately 40%. The bottom decile of households lost three months’ worth of income (Azim Premji University, 2021; Beyer et al, 2021).

Microdata from the largest private survey in India, CMIE’s ‘Consumer Pyramids Household Survey’ (CPHS), show that per capita consumption spending dropped by more than GDP, and did not return to pre-lockdown levels during periods of reduced social distancing. Average per capita consumption spending continued to be over 20% lower after the first lockdown (in August 2020 compared with August 2019), and remained 15% lower year-on-year by the end of 2020.

Official poverty data are unavailable, and the CPHS data come with a caveat of ‘top’ and ‘bottom exclusions’. For example, official statistics show a rural headcount ratio of 35% in 2017/18 (Subramanian, 2019). But the CPHS data estimate it at 25%, which suggests exclusions at the lower end of the consumption distribution (Dreze and Somanchi, 2021).

Despite these statistical concerns, the CPHS does provide consumption numbers for a large sample of individuals, which can provide insights into changes in consumption levels arising from the pandemic.

Table 2 reports the percentage of people who have monthly consumption expenditure below different cut-off values. The different cut-offs encompass the official poverty lines (which, in any case, have been considered too low by some commentators). The current rural poverty line is set at 1,600 rupees (£15.50) per month or over, and the urban poverty line is 2,400 rupees per month (£23.37) or over.

Based on the latest CPHS data, rural poverty increased by 9.3 percentage points and urban poverty by over 11.7 percentage year-on-year from December 2019 to December 2020. Earlier months of the CPHS show that rural poverty increased by 14.2 percentage points and urban poverty by 18.1 percentage points. Yet the actual increase in poverty due to Covid-19 is likely to be higher than what the CPHS data suggest, as indicated by other surveys.

Table 2: Percentage of individuals by monthly consumption expenditure

Dec 19Dec 20Dec 19Dec 20Dec 19Dec 20 
Rs 1,000 or below6.
Rs 1,600 or below23.531.614.521.727.937.0
Rs 2,000 or below38.348.325.735.744.455.2
Rs 2,400 or below52.162.637.949.559.069.7
Sample size433,021499,879278,759331,809154,262168,070
 Aug 19Aug 20Aug 19Aug 20Aug 19Aug 20
Rs 1,000 or below5.
Rs 1,600 or below21.033.612.022.525.539.5
Rs 2,000 or below34.950.321.937.141.357.5
Rs 2,400 or below48.264.433.451.355.571.5
Sample size570592477237362417321100208175156137
Source: Consumer Pyramids Household Survey (CPHS) for December 2019 and December 2020, and for August 2019 and August 2020.
Notes: Estimates for consumption are calculated by dividing household adjusted total expenditure by household size and weighted using member level country weights. Adjusted total expenditure is the sum total of all consumption goods and services purchased by the household during a month, adjusted using weekly records. Real values are adjusted for inflation using the MOSPI CPI (IW) for urban workers and CPI (AL) for rural workers (Base 2012=100). Headcount ratio is the percentage of individuals who are below the poverty line in urban and rural areas in each year. Poverty line is the inflation-adjusted poverty line in rural areas (Rs 972 in 2011-12 prices) and urban areas (Rs 1410 in 2011-12 prices), which are adjusted to 2012 prices with the RBI CPI(AL) and CPI(IW) for 2011/12-2012/13 respectively. All figures are in December 2019 values and observations with missing regions are dropped. Despite a much larger sample in urban areas, the CPHS also underestimates mean per capita consumption in urban areas, which is likely to reflect their inability to survey high-income urban households. From the draft National Sample Survey Organisation (NSSO) Report on Household Consumer Expenditure for 2017-18, the CPHS estimate of mean per capita consumption in urban areas was 0.8 of the NSSO level for 2017-18. For rural areas, the CPHS estimate is 1.1 of the NSSO level.

Taking into account the general trend of reduction in poverty, an estimated 230 million people in India have fallen into poverty as a result of the first wave of the pandemic (Azim Premji University, 2021).

Table 3 shows that households in the middle of the pre-Covid-19 CPHS consumption distribution saw large drops in spending after the first wave of the pandemic, helping to create a new set of people entering poverty.

The percentage of poor people in the second lowest quintile of pre-Covid-19 consumption jumped from 32% to 60% within a year. This was driven largely by rural areas, where the headcount ratio for the second quintile almost doubled.

In urban areas, the poverty line is set higher due to greater living costs and 72% of people in the second quintile of the urban income distribution were below this poverty line before the pandemic. Within a year, they were joined in urban poverty by many who had higher incomes before. Half of people in the third quintile and 29% of people in the fourth quintile fell below the poverty line after the pandemic.

This sharp rise in poverty after the first lockdown is consistent with a variety of surveys that highlighted the depth of the crisis (Azim Premji University, 2021). Year-on-year urban unemployment rate jumped from 8.8% in April to June 2019 to a staggering 20.8% in April to June 2020 (Government of India National Statistical Office, 2020).

Table 3: Percentage of individuals who are below the poverty line in middle quintiles of pre-Covid-19 consumption expenditure, August 2019 to August 2020

QuintileAug 19Aug 20Aug 19Aug 20Aug 19Aug 20
Source: Consumer Pyramids Household Survey (CPHS) for August 2019 and August 2020.
Notes: Quintiles are based on 2019 mean per capita consumption levels for each region type. Consumption levels are calculated by dividing household adjusted total expenditure by household size and weighted using member level country weights. Adjusted total expenditure is the sum total of all consumption goods and services purchased by the household during a month, adjusted using weekly records. Real values are adjusted for inflation using the MOSPI CPI (IW) for urban workers and CPI (AL) for rural workers (Base 2012=100). All figures are in December 2019 values and observations with missing regions are dropped.

The pandemic has brought severe economic hardship, especially to young individuals who are over-represented in informal work. India has a large share of young people in its workforce and the pandemic has put them at heightened risk of long-term unemployment. This has negative impacts on lifelong earnings and employment prospects (Machin and Manning, 1999).

A study by the Centre for Economic Performance (CEP at the London School of Economics) analyses the depth of continuing joblessness among younger workers in the low-income states of Bihar, Jharkhand and Uttar Pradesh (see Table 4, Dhingra and Kondirolli, 2021).

The first round of the survey randomly sampled urban workers aged 18-40 during the first lockdown quarter, finding that a majority of them who had work before the pandemic were left with no work or no pay. After the first lockdown in April to June 2020, 20% of those sampled were out of work, another 9% were employed but had zero hours of work and 81% had no work or pay at all.

Ten months on from the first lockdown quarter, 8% of the sample continued to be out of work, another 8% were working zero hours, and 40% had no work or no pay. The rate of no work or no pay was higher (at 47%) among the youngest low-income individuals (those aged 18-25 who had below median pre-Covid-19 earnings).

Table 4: Crisis labour force status of individuals who were employed pre-Covid-19: recontact sample of individuals interviewed during the first lockdown (April to June 2020) and before the second wave (January to March 2021)

April to June 2020January to March 2021January to March 2021
AllAllBelow Median pre-Covid-19 earnings and 18 - 25 years
Out of work last week0.200.080.11
Zero hours last week0.090.080.11
Not paid0.700.290.32
No work/Zero hours/Not paid0.810.400.47
Sample Size32013201542
Source: CEP-LSE Survey 2020 and 2021.
Note: Out of work last week and zero hours last week are indicators for individuals who were unemployed in the week preceding the survey and employed but working zero hours in the week before the survey respectively. Not paid is an indicator for individuals who received no pay in April 2020 in the column of April to June 2020 and those who received no pay during January to March 2021 in all other columns. Median earnings are constructed using average earnings in January and February 2020. 18-25 refers to individuals who are between 18 to 25 years of age at the time of the first survey.

The recovery after the first wave was too muted to get many young Indian workers back into employment. For example, rural migrants continued to be reluctant to return to work in urban areas even before the second wave hit (Imbert, 2021). And the second wave, which started in mid-February and appears to be flattening out in June 2021, heightened these risks of long-term unemployment by increasing the spells of economic inactivity.

What do public health indicators reveal about the impact of Covid-19 on India’s economy?

To avoid another livelihood crisis, India turned to local lockdowns during the second wave of the pandemic. Before the second wave, India’s public health performance (in terms of confirmed cases and confirmed deaths), while not the best, was ahead of several reference group countries. But the second wave has made India’s position significantly worse. The total confirmed cases per million now are comparable to those in the rest the world and the rate of vaccination is lower in India.

While death rates seem lower in India, there is massive underreporting. After accounting for the underreporting within official statistics, India’s total confirmed cases and deaths might exceed that of the rest of the world by a large margin (Gamio and Glanz, 2021).

In the conservative scenario, the total confirmed cases per million are about 13 times larger than in the rest of the world, and the total confirmed deaths per million are about 85% of that in the rest of the world. In the worst-case scenario, India is far behind the rest of the world.

There is an important caveat: while the focus of this article is on India, underreporting of Covid-19 cases and deaths is prevalent globally (Institute for Health Metrics and Evaluation, University of Washington, 2021).

How has India fared so far?

More than a year has passed since India’s first national lockdown was announced. There was talk of a trade-off between lives and livelihoods when the Covid-19 crisis erupted last year. As India struggles in the second wave, it is clear that the country did poorly in both dimensions.

While India’s policy response was strong in terms of some aspects of lockdown stringency, it was ineffective in dealing with both the public health and economic aspects of the crisis. What’s more, it failed to limit the damaging impact of the crisis on the most vulnerable sections of the population.

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Authors: Swati Dhingra and Maitreesh Ghatak
Swati thanks the ERC for Starting Grant 760037.
The authors would like to thank Ramya Raghavan and Fjolla Kondirolli for research assistance
Photo by Shubhangee Vyas on Unsplash
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