Tracking economy with mobility and luminosity

Economists and analysts tend to choose from a buffet of available statistics.

By Vinayak Chatterjee

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Most traditional economic indicators in today’s real-time environment become quite redundant for current decision making by the time they are out. So new types of ‘high frequency’ indicators are increasingly being used as surrogates to track the economy, or segments thereof, or even specific geographies, and for targeted policy measures.

Mint, for example, publishes a monthly macro-tracker based on 16 high-frequency indicators covering consumer economy, producer economy, external sector and ease of living. Rating agency ICRA tracks 15 non-financial high-frequency indicators; the Reserve Bank of India has an Economic Activity Index encompassing 27 monthly indicators.

Economists and analysts tend to choose from a buffet of available statistics. The more popular ones are: financial, consumption, employment, goods movement, vehicular sales and registrations, production , etc. Whilst these indicators are quite established in use and interpretation, two new indicators eliciting curiosity are mobility and luminosity.

Mobility

Currently, Google’s Mobility Reports are the trendsetters in this space, though other GPS-based measures mounted on trucks, railway wagons, etc, are all expected to increase the width and depth of this tracking system significantly. The National Informatics Centre announced last week that the E-way bill system has been integrated with FASTag RFID systems, and transport vehicles combined with goods movement can now be easily tracked together nationally. Nitin Gadkari’s statement in Parliament recently that within a year, all toll collection in India would be through a GPS-based system is expected to lead to a flood of actionable data. Facebook and Apple, too, are getting increasingly involved in disseminating information about mobility.

Google has been publishing Mobility Reports that measure state-wise public movement in areas of retail & recreational, parks, grocery and pharmacy, transit stations, workplaces and residential areas. It pulls data from Google users who have opted into location tracking devices. The reports provide insights into the efficacy of curfews and lockdowns, as well as indicated increases or decreases in specific activities. The Nomura India Business Resumption Index, which monitors economic activity normalisation, uses Google mobility reports as one of its inputs. The ‘Tom-Tom Traffic Index’ is also gaining in popularity. Such real-time mobility trackers also help monitor movements and thus take on-line decisions during natural calamities, and unusually large gatherings. It helps policy makers understand the nature and timing of trips that can then shape decisions regarding change of business hours or delivery of essential supplies. Google issues similar reports for 131 countries.

Luminosity

The luminosity index is basically about capturing visible lights emanating from the earth at night by satellites. The images provide a numerical measure of brightness or dimness in selected geographies or economic centres, pointing to increase or decrease of activity.

One of the defining research papers on this subject has been published under the auspices of the World Bank titled “Examining the economic impact of Covid-19 in India through daily electricity consumption and nighttime light intensity.” (Authors: Messrs Beyer, Franco – Bedoya and Galdo). The paper confirms a meaningful relationship between electricity consumption, nighttime light intensity, and economic activity in India. “During the national lockdown, when restrictions were uniform across the country, districts with higher rates of Covid-19 infections saw larger declines in nighttime light activity, suggesting additional impacts from voluntary behavioural changes when risks of an infection increase. In nearly all large Indian cities nighttime light intensity was lower between March and September 2020 than it was a year before. In Delhi and Mumbai, for example, it declined on average by around 10%,” it says.

Analysis of data over time has revealed that the long-run average growth in real GDP and night lights moved in close proximity to each other. For the overall period (1992 to 2017), average annual growth in GDP and night lights were 6.5% and 7.1%, respectively. The q-o-q movement in GDP clearly depicts a seasonal pattern with a peak during October-December and a trough during April-June. The seasonal movement in night lights captures the seasonal variations in GDP quite closely. Well, the day is not far off when business dailies will carry weekly updates on mobility and luminosity indices.

Vinayak Chatterjee is chairman of Feedback Infra