Monitoring of the economy with mobility and light

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

By Vinayak Chatterjee

Most of the traditional economic indicators in today’s real-time environment become quite redundant for current decision-making the moment they are released. Thus, new types of “high frequency” indicators are increasingly used as surrogates for monitoring the economy, or segments of it, or even specific geographic areas, and for targeted policy measures.

Mint, for example, publishes a monthly macro-tracker based on 16 high-frequency indicators covering consumer economics, production economics, the external sector and comfort of life. The ICRA rating agency tracks 15 high-frequency non-financial indicators; the Reserve Bank of India has an index of economic activity comprising 27 monthly indicators.

Economists and analysts tend to choose from a buffet of available statistics. The most popular are: finance, consumption, employment, movement of goods, vehicle sales and registrations, production, etc. While these indicators are well established in use and interpretation, two new indicators arousing curiosity are mobility and brightness.


Currently, Google’s mobility reports are the pioneers in this space, although other GPS-based measurements mounted on trucks, railroad cars, etc. should all greatly increase the width and depth of this tracking system. The National Informatics Center announced last week that the E-way bill system has been integrated with FASTag RFID systems, and that transport vehicles combined with the movement of goods can now be easily tracked together nationwide. Nitin Gadkari’s recent statement to Parliament that within a year all toll collection in India will be done via a GPS system should lead to a flood of actionable data. Facebook and Apple are also increasingly involved in the dissemination of information on mobility.

Google has released mobility reports that measure state-level public travel in retail and recreation, parks, grocery and drug stores, transit stations, places to go. work and residential areas. It extracts data from Google users who have opted for tracking devices. The reports provide insight into the effectiveness of curfews and closures, as well as indicated increases or decreases in specific activities. The Nomura India Business Recovery Index, which monitors the normalization of economic activity, uses Google’s mobility reports as one of its inputs. The “Tom-Tom Traffic Index” is also growing in popularity. These real-time mobility trackers also help monitor movement and thus make decisions online during natural disasters and unusually large gatherings. It helps decision makers understand the nature and timing of travel, which can then influence decisions about changing hours of operation or delivering essential supplies. Google publishes similar reports for 131 countries.


The luminosity index essentially consists of capturing the visible lights emanating from the earth at night by satellites. The images provide a digital measure of light or dark in selected geographic areas or economic centers, indicating an increase or decrease in activity.

One of the seminal research papers on this topic was published under the auspices of the World Bank, titled “Examining the economic impact of Covid-19 in India through daily electric consumption and nighttime light lighting. »(Authors: Messrs. Beyer, Franco – Bedoya and Galdo). The article confirms a significant 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 experienced a greater drop in nighttime light activity, suggesting additional impacts from changes in voluntary behavior when the risk of infection increases. In almost all major Indian cities, nighttime light intensity was lower between March and September 2020 than it was a year earlier. In Delhi and Mumbai, for example, it has fallen on average by around 10%, ”he says.

Analysis of the data over time revealed that the long-term average growth of real GDP and the nightlights have moved closer to each other. For the entire period (1992 to 2017), the average annual growth in GDP and nightlights was 6.5% and 7.1%, respectively. The qoq movement of GDP clearly depicts a seasonal pattern with a peak in October-December and a trough in April-June. The seasonal movement of nightlights very closely captures the seasonal variations in GDP. Well, the day is not far off when the professional dailies will publish weekly updates on the mobility and luminosity indices.

Vinayak Chatterjee is President of Feedback Infra

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