One main limitation of the existing literature is that most of it uses annual data, and is thus unable to fully reflect changes in regulations at business cycle frequency. With the exception of Ghosh et al. (2017), the data used and the constructed indices of capital flow measure pertain to existing restrictions in place, like the Chinn and Ito (2006) index, rather than to changes in restrictions. These series change very slowly, if at all, and do not reflect changes in regulations at business cycle frequency. Besides some of the papers analyze the use of CFMs only around domestic economic cycles, while the theoretical and policy literature has advocated their use primarily around capital flow cycles.<sup>9</sup> Ghosh et al (2017) is one of the few papers which uses quarterly data, that consists of data on changes in regulations and not merely on existing measures, but is unable to address these issues fully since their database is limited to a rather small number of countries--their data on capital flow measures is for 17 countries.

# **3. A New Data Set on Capital Flow Measures**

# **3.1 Construction of the Data Set**

We construct the data set on CFMs using information provided in the IMF’s Annual Report on Exchange Arrangements and Exchange Restrictions (AREAER). The AREAER presents information in two parts for each member country of the IMF. The first part documents detailed information on existing regulations on all kinds of capital flows. This information, and the coding of regulation based on this information, does not change in response to incremental changes in regulations, when specific regulations are still broadly retained. Many prevalent and widely used series on capital account liberalization (such as Chinn and Ito, 2006 and Schindler, 2009) have been constructed using information contained in this first part of the database. As discussed above, these series are sticky and do not often reflect changes in regulations over time across countries.<sup>10</sup> A second part of the AREAER documents changes in regulations, both liberalization and tightening of the capital account, that were introduced in the preceding year. We compile this information at a quarterly frequency from 1999:Q1 to 2016:Q2 for 47 emerging countries, the same set of countries included in Eichengreen and Gupta (2014).

We first code these data quantitatively giving a higher value for a larger change and a lower value for a change which is deemed to be more marginal. The indices take integer values between 4 and -4. A value of 4 indicates a large liberalization, 0 indicates no change in regulation, and a -4

> 9 In a meta-analysis of more than 30 empirical studies, Magud et al. (2011) find that two prominent rationales for governments to impose capital controls are to lower real exchange rate pressures and reduce the volume of capital flows. 10 A distinct example is the Chinn-Ito index for capital account liberalization for India, which shows that India has had a closed capital account in the last two decades, with very little change in the degree of openness. But in practice, India has consistently, even if incrementally, liberalized its capital account. This includes the liberalization of inflows and outflows of capital by both residents and nonresidents.

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