Night lights and train trips help India study demonetisation impact
Mumbai: With India still struggling to measure the impact of last year’s unprecedented clampdown on cash—especially on the vast informal sector—some analysts are using innovative indicators to assess the health of the $2 trillion economy.
About 90% of workers and 46% of output fall under the unorganized economy that isn’t fully captured by official data. Poor visibility contributed to a prediction from policy makers that growth would rebound sharply after Prime Minister Narendra Modi’s 8 November 2016, decision to abruptly invalidate 86% of India’s currency in circulation. Instead the expansion has decelerated to a three-year low.
The slowdown is bolstering calls for satellite imagery to peer through the dust of India’s 600,000 villages to gauge activity and for analysis of ticketing across the nation’s vast railway network to study changes to economic migration patterns.
South Asians have long been pioneers of new statistical techniques. Between the 1960s to 1980s, Indians and Pakistanis helped the World Bank create models that have since evolved into modern development indicators, showing that living standards can be measured even in poor countries with large unorganized sectors.
“India was ahead of the world at one time on statistics and perhaps given how advanced it is in information technology it could, in a creative way, be ahead again,” said Martin Rama, chief economist for the South Asia region of the World Bank. “Night light data captures informal economic activity, it is available at high levels of spatial disaggregation, it can be obtained in almost real time, it is relatively cheap to acquire, and it is not subject to politically-motivated interference.”
The World Bank has used nightlight data to study the impact of economic shocks across South Asia. That has included new methods of calculating gross domestic product in India and Sri Lanka, gauging the economic effects of earthquakes and a trade blockade in Nepal, examining fresh violence in Afghanistan, as well as Modi’s cash ban.
It found that at the aggregate level, a comparison of night light intensity suggests only a small dip in economic activity occurred after the high-value notes were invalidated. However, areas that were more informal—rural, with low banking access and few regular wage earners—experienced drops in local GDP in the range of 4.7 percentage points to 7.3 percentage points.
These were temporary too, so India’s surprise growth slump in the April-June quarter is unlikely to be due to demonetisation, except indirectly as the government withdrew some additional spending it had implemented during the demonetisation period, said Rama.
Other analysts such as Rohit Prasad, a professor at the Management Development Institute near New Delhi, are using domestic remittances to study the impact of demonetization. Flows of money from urban to rural areas are a weather vane for the health of the informal sector, he wrote in Mint.
While available data is severely limited, indications are that volumes fell over 50% in November 2016 and slumped more in December. They have since picked up to October 2016 levels, but “actual remittance volumes even as late as August were trailing the values forecasted under the assumption that demonetization had not happened,” he wrote.
About 9 million Indians—the entire population of Austria—migrate across the country each year, according to estimates from the Economic Survey, compiled by Modi’s top economic adviser Arvind Subramanian. Subramanian’s team used railway passenger data to estimate the annual internal migration rate, which showed that rising economic growth boosts migration as rewards exceed the costs of moving.
But, just like official statistics, alternative measures also have their limits.
For instance, Ravi Srivastava, a professor of economics at the Centre for the Study of Regional Development at Jawaharlal Nehru University in New Delhi, says the kind of data being analyzed by Subramanian’s team may not give an accurate picture.
To study actual migration patterns and assess if demonetisation has triggered any changes, analysts need to complement this data with other means of transport. For instance, a farmer from one of the poorest states—Uttar Pradesh—might be riding pillion on a friend’s motorcycle to get to the nearest train station, from where he travels to New Delhi. Then he’d take a bus onward to another state, so just looking at railway routes is insufficient.
“These look like areas where one can do more systematic work,” Srivastava said, “but these would require a detailed analysis supported by the kind of data that may not be publicly available.”
Similarly, when the World Bank asked researchers in South Asia about the obstacles to GDP measurement, inadequacy of survey instruments to capture the formal sector was seen as the most important, followed by misreporting, while technological challenges were mentioned but not at the top of the list.
“These responses suggest that an integrated response is needed to make statistical measurement more credible, and that technology is not the silver bullet that will solve all problems,” Rama said. Bloomberg