Home >Industry >Infotech >Digital innovation may be fuelling inequality

Digital innovation and disruption has mainly benefited the rich and worsened inequality, according to a new National Bureau of Economic Research (NBER) working paper by Dominique Guellec and Caroline Paunov of the Organisation for Economic Co-operation and Development.

Digital innovation differs from the technological progress of previous eras in the sense that the final product, say software, is often “non-rivalrous".

In other words, the consumption of that product by one consumer does not affect consumption by another one. Such digital non-rivalry can lead to monopolistic outcomes, with incumbent firms extracting excessive profits. At the same time, the digital market is also prone to sudden disruptions, which induces investors to demand a high return on investment as compensation for the high risks they bear. While disruptive innovation entails higher risks, it also leads to higher gains for some investors, creating a “winner takes all" scenario. The end result has been that gains have been cornered by a few investors, top executives and star employees, according to the authors.

Also read: Digital Innovation and the Distribution of Income (

“You can see the computer age everywhere but in the productivity statistics," Nobel Prize-winning economist Robert Solow once quipped. Newer developments such as artificial intelligence (AI) seem to have met the same fate, shows research by Erik Brynjolfsson of the MIT Sloan School of Management and co-authors. They argue that there are four main reasons as to why technological advances like AI have not resulted in productivity gains. False hopes and misplaced optimism is one possibility. The second possibility is that the productivity outcomes of these technologies have not been captured by current methods of measurement. Another argument is that the gains may be concentrated for a few firms—the superstars, so to say, of the new digital era—without economy-wide effects. Another explanation, partly related to the above argument, is that it may still take some time for the effects of AI to spread throughout the economy, and show up in national account statistics.

Also read: Artificial Intelligence and the Modern Productivity Paradox: A Clash of Expectations and Statistics (

Global warming could reduce China’s manufacturing sector output by 12% over the next 30 years, according to a new NBER paper by Peng Zhang of the Hong Kong Polytechnic University, and co-authors. Analysing the performance of Chinese manufacturing plants between 1998 and 2007, the authors find an inverted U-shape relationship between temperature and productivity, with productivity dropping sharply at very high temperatures. This could be owing to worker fatigue or due to technical reasons which lower the productivity of machinery at high temperatures. The authors warn that losses resulting from global warming alone could shave almost 4% off China’s GDP (gross domestic product) by the mid-21st century.

Also read: Temperature Effects on Productivity and Factor Reallocation: Evidence from a Half Million Chinese Manufacturing Plants (

Demonetization reduced agricultural trade in mandis or regulated markets in India by over 15% within a fortnight, according to a recent working paper by Nidhi Aggarwal, assistant professor at the Indian Institute of Management, Udaipur, and Sudha Narayanan, associate professor at the Indira Gandhi Institute of Development Research. The authors analysed arrivals and prices of major agricultural commodities in around 3,000 wholesale markets or mandis to arrive at these conclusions. Most of the decline was in prices rather than in arrivals. Trade in perishables was significantly affected: the traded value fell by 23% in the week after demonetization with most of the decline being in prices.

Also read: Impact of India’s demonetization on domestic agricultural markets (

In a post for the Economic and Political Weekly, Shubham Kundal and Mukul Agarwal, BTech students from Indian Institute of Technology Delhi, have estimated the economic magnitude of the losses suffered as people lined up in serpentine queues outside automated teller machines (ATMs) in the weeks following demonetization. They estimate the hourly cost of queuing to be Rs283 per hour. This amounted to a 23% loss per transaction, or Rs460 out of the withdrawn Rs2,000, almost akin to a tax on cash withdrawal. The authors used two different methodologies to arrive at this figure. They asked various categories of ATM users, from labourers to housewives, to provide an estimate of how much of Rs2,000 they would be willing to pay to forego standing in a line at the ATM. They also asked respondents to estimate the hourly monetary value of their queuing time. The authors’ research was conducted across four areas of Delhi between 3 December and 12 December.

Also read: Demonetisation: An Estimation of Losses due to ATM Queuing (

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