Panel Paper: The Impacts of India’s Cash Ban: Evidence Using Regression Discontinuity Design

Thursday, November 7, 2019
Plaza Building: Concourse Level, Governor's Square 10 (Sheraton Denver Downtown)

*Names in bold indicate Presenter

Mel George, University of Maryland


This paper presents a study of the importance of the transaction role of cash in a country’s economy by analyzing a unique episode in the history of monetary economics. On November 8th, 2016, the Government of India unexpectedly declared much of the existing currency in circulation illegal tender, effective at midnight. Referred to as “demonetization", this policy resulted in a sharp decrease in the availability of cash which could be used in transactions because printing press constraints prevented the immediate replacement of the demonetized currency with new notes. The withdrawn notes, amounting to US$320 billion at the time, represented 86 percent of the total currency value in circulation in India. By making the notes worthless almost overnight, the government hoped to destroy large piles of black money hidden away by tax evaders. In addition, the government claimed the plan would strike a major blow against corruption and counterfeiting and would kick-start India’s transition into a digital, cashless world. In a country with a huge informal economy, dependent on cash transactions, demonetization was a big political gamble, too. Demonetization occurred in an otherwise stable macroeconomic environment and did not affect other hallmarks of monetary policy such as the overall liabilities of the Reserve Bank of India (RBI) or the target interest rate. Thus, the experiment offers a unique opportunity to observe the importance of cash as a facilitator of transactions.

In the paper, we use a Regression Discontinuity Design (RDD) approach to demonstrate the impacts of the demonetization measure. The measure has not been deeply analysed in the literature since the Government of India has not provided a report or data pertaining to the step. Other studies have also used only national aggregate time series to demonstrate the effects. Using RDD allows us to use novel data sets to develop conclusions. We use nightlights data from satellites as a proxy for economic activity and employment surveys to measure economic activity including in the informal sector; debit/credit cards and e-wallet transactions data; banking data on deposit and credit growth; and wholesale prices for essential commodities and agricultural produce. We examine the effects on banking, unemployment & economic activity, agriculture & household spending, taxation and terrorism incidents using cash in the economy as the independent variable. The results on the changes in the relationship to cash availability are shown for a cross section of Indian states and how the impact has varied across demographics. The results show that the policy represented a liquidity shock that altered the evolution of the economy and the monetary cone, and changed consumer preferences.

We conclude that unlike in the cashless limit of new-Keynesian models for economies with well-developed financial markets, in modern India cash serves an essential role in facilitating economic activity.