The Balance of Payments of a country can be divided into current account and capital account flows. The current account balance of a country indicates the difference between exports and imports of a country. The capital account records the inflows and outflows of capital into and from a country that affect its foreign assets and liabilities. Some of these are investments, loans and debt instruments. Any action of the government or the central bank of a country that tightens or relaxes the inflow or outflow of capital in and out of the country can be called a Capital Control Action (CCA).

CCAs have always been used as policy instruments by the governments and the central banks around the world for macroeconomic management. Developing countries have been using CCAs to protect their currency and economy from the shocks of sudden inflow or outflow of foreign capital caused by any internal or external change. The debate on the usage and efficacy of CCAs as an instrument of monetary policy has been going on for quite some time now.

Essentially, a CCA involves relaxation or tightening of capital flows for a particular asset or a group of assets.  While this policy change has been quantified by economists using various methodologies, the source of data on CCAs has largely remained the same, which is the Annual Report on Exchange Arrangements and Exchange Restrictions (AREAER) published by the IMF. This report contains country-wise information on CCA and has become more detailed over time, providing information pertaining to inflows and outflows of multiple asset categories. Up until 1996, the AREAER database provided very limited information on capital controls. From 1996 onward, it became more comprehensive and started providing disaggregated information on capital controls by asset categories, thereby assisting economists to develop better measures of capital controls.

Quinn in 1997 published a paper where he used the AREAER database to codify the capital controls of 64 countries using a scale of 0 to 14 with 14 being the indicator of least restriction. Quinn’s work was the first instance of quantifying capital controls and can be considered the first generation of quantitative measures for capital account openness.

The second generation of measures for capital account openness came 10 years after Quinn’s work when Chinn and Ito constructed a comprehensive measure of financial openness by deploying dummy variables for the four major indicators in the AREAER database, i.e. presence of multiple exchange rates, current account openness, capital account openness and the requirement to surrender export proceeds. According to them, bringing in current account transactions and exchange rates captures the openness of capital accounts better.

In 2009, Schindler constructed an index to measure the openness or the lack of it on a disaggregated level for multiple asset categories such as money market instruments, shares, bonds and other forms of investment. In 2012, Klein built upon Schindler’s work and proposed an index that considered inflows and outflows separately for each asset category. Klein also made a distinction between controls that are applied to a broad range of assets for a long period (‘walls’) and episodic controls on a narrow range of assets (‘gates’). In 2015, Fernandez along with Schindler and others, fine-tuned the work done by Schindler and Klein and constructed a very comprehensive dataset of capital control measures for 100 countries for 10 categories of assets over a period of 39 years starting from 1975 up until 2013. Schindler, Klein and Fernandez’s work can be called the third generation of measures of capital account openness.

A fundamental flaw with the above measures is that these measures express the openness of capital account or lack of it in binaries, which implies that they do not capture or reflect the degree of openness of a nation’s capital accounts. For example, relaxation of reporting requirements for foreign direct investment while keeping the percentage of investment allowed unchanged is a relaxing action. But this will not be reflected in a measure that expresses itself in binaries of ‘YES’ and ‘NO’ or ‘0’ or ‘1’. Also, all these measures have been derived from the AREAER database which publishes only yearly data, thus limiting the researchers from using their measures to assess the efficacy of CCAs which usually take place more than once a year.

Researchers in India have tried to address this problem. Pandey, Shah, Pasricha and Patnaik in 2016 have constructed a count measure of India’s capital controls by counting the number of CCAs (relaxing or tightening) on a weekly basis, as informed by the Reserve Bank of India through circulars or notifications. This approach appears to be more sensible as it provides information on the progressive tightening or relaxation of capital controls by a country. It is crucial, however, to admit  that even this measure might be susceptible to measurement errors as one CCA can be more intense than a couple of CCAs taken together.

Be that as it may, CCAs will continue to be used as policy instruments for years to come. As data on the announcement and implementation of these actions becomes more accessible, researchers will be able to construct better quantitative measures for assessing the efficacy these actions. Governments and policy makers around the world are bound to benefit from the body of knowledge that these measures will produce.