Understanding the unequal nature of India’s economic recovery

That the Indian economy is recovering from the pandemic’s disruption is an undisputable fact
While consumption for all kinds of transportation fuel – petrol, diesel and aviation turbine fuel (ATF) – fell sharply during the first lockdown, petrol and diesel led the recovery as restrictions were eased in 2020, a trend which continued in 2021.(File photo)
While consumption for all kinds of transportation fuel – petrol, diesel and aviation turbine fuel (ATF) – fell sharply during the first lockdown, petrol and diesel led the recovery as restrictions were eased in 2020, a trend which continued in 2021.(File photo)
Updated on Dec 27, 2021 12:57 AM IST
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That the Indian economy is recovering from the pandemic’s disruption is an undisputable fact. However, what is under doubt is not the existence of the recovery itself, but the nature of it. 

Here are four charts which suggest that India’s growth might have become more unequal in its post-pandemic phase.

The different trajectories of fuel consumption

Because the pandemic forced imposition of social distancing norms, tracking mobility levels became among the most important indicators of restoration of economic activity in the post-pandemic phase. 

Mobility levels have been increasing consistently in India, if data from Google Mobility indices is to be believed.

However, what is also true is that most technology-based mobility indicators – they use Internet-based devices to track mobility – have a formal sector bias. 

The Nomura India Business Resumption Index (Nibri) for example, uses the Apple Driving Index, which sources data from persons with access to Apple devices. This source – the poor are less likely to be using mobile Internet devices – introduces a pro-rich bias in these indicators.

Tracking fuel consumption from the petroleum ministry’s database offers some evidence into this bias and highlights a class aspect to restoration of mobility, and by extension, economic activity in the Indian economy. 

While consumption for all kinds of transportation fuel – petrol, diesel and aviation turbine fuel (ATF) – fell sharply during the first lockdown, petrol and diesel led the recovery as restrictions were eased in 2020, a trend which continued in 2021. 

This was understandable as there were significant restrictions on air travel even after the easing of lockdown restrictions. 

However, this trend has reversed in the past few months and it is ATF consumption which is closing its gap with pre-pandemic consumption levels, while the consumption of petrol and diesel has actually shown a dip. 

Numbers speak for themselves. Consumption of petrol-diesel as a share of pre-pandemic levels (2019-20) has actually lost momentum in the last two months whereas this trend is not to be seen in the consumption of ATF. 

Even LPG consumption shows a similar trend as petrol-diesel.

While predicting the exact reason for this trend is an exercise in speculation, the adverse impact of higher petrol-diesel and LPG prices on consumption, and hence mobility, cannot be ruled out. 

End consumers of ATF are richer than those who consume petrol-diesel. A March 2021 HT analysis by Vineet Sachdev cited data from a survey commissioned by the petroleum ministry to argue that the poor have a large share in consumption of petrol and diesel in India.

Difference in revival of two-wheeler and passenger car sales

The demand for two-wheelers and passenger cars are a widely accepted proxy for purchasing power of the non-rich and rich in India. 

Data from the Centre for Monitoring Indian Economy (CMIE) shows that the two were moving broadly in tandem the year before the pandemic struck. This seems to have changed after the pandemic. 

While the sale of passenger cars saw a sharp revival in the first quarter of 2021-22, this was not the case for two-wheeler sales. 

A November 2021 Bloomberg Quint story quoted a Bajaj Auto Ltd (an important two-wheeler manufacturer in India) official describing the two-wheeler demand as being “stressed”. 

To be sure, sales data for both cars and two-wheelers has been contaminated because of the supply-side problem due to shortage of microchips. Still, the divergence in trajectory of revival in demand for cars and bikes underlines the class-difference in purchasing powers post pandemic.

The class-difference in economic sentiment

The persisting stress in the RBI’s Consumer Confidence Surveys (CCS) has been among the most important indicators of general stress levels in the economy.

While the RBI’s CCS is important statistical evidence, it has two important limitations. CCS is only conducted in urban areas (13 major Indian cities to be precise) and it does not give a class-wise break-up of economic sentiment.

CMIE’s consumer sentiment numbers can fill an important gap here. The Index of Current Economic Conditions in the CMIE’s consumer pyramid survey is based on comparison of financial condition of households compared to a year ago, and their perception about whether or not this is a good time to buy consumer durables such as televisions and two-wheelers etc. 

The Index of Current Economic Conditions highlights the class-wise disparity when it comes to the pandemic’s impact. 

This index was broadly same across different income categories – they vary from less than 1 lakh per year to more than 10 lakh – in November 2017. 

While the richest started increasing their gap, it was still not very high until November 2019. This gap increased in a big way by November 2020 and has still not closed in a significant manner in November 2021, the latest period for which monthly data is available. 

If the Indian economy has to achieve a sustainable growth trajectory, it is crucial that the economic sentiment of the non-rich recovers as well. 

This is all the more important given the fact that some of the pent-up demand from the rich, both for goods as well as services (vacations for example) could begin to dissipate going forward.

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  • ABOUT THE AUTHOR

    Roshan Kishore is a journalist with Hindustan Times in New Delhi. He focuses on political economy issues with a data-driven approach.

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