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Andrés Fernández, Mr. Michael W Klein, Mr. Alessandro Rebucci, Mr. Martin Schindler, and Martin Uribe
This paper presents a new dataset of capital control restrictions on both inflows and outflows of 10 categories of assets for 100 countries over the period 1995 to 2013. Building on the data in Schindler (2009) and other datasets based on the analysis of the IMF’s Annual Report on Exchange Arrangements and Exchange Restrictions (AREAER), this dataset includes additional asset categories, more countries, and a longer time period. The paper discusses in detail the construction of the dataset and characterizes the data with respect to the prevalence and correlation of controls across asset categories and between controls on inflows and controls on outflows, the aggregation of the separate categories into broader indicators, and the comparison of this dataset with other indicators of capital controls.
Andrés Fernández, Mr. Michael W Klein, Mr. Alessandro Rebucci, Mr. Martin Schindler, and Martin Uribe

Front Matter Page Institute for Capacity Development Contents Abstract I. Introduction II. Constructing the Capital Control Indicators III. Characteristics of the Capital Control Indicators IV. Aggregate Indicators V. Conclusions VI. References Tables Table 1: Asset and Transaction Categories for Capital Control Measures Table 2: Countries In Data Set, By Income Groups, With Open/Gate/Wall Category Table 3: Prevalence of Controls, 100 Countries, 1995 – 2013, by Asset Sub-Categories Table 4: Cross-Category Correlations, All

Andrés Fernández, Mr. Michael W Klein, Mr. Alessandro Rebucci, Mr. Martin Schindler, and Martin Uribe

asset categories and also compares an aggregated index of our data with two aggregate indicators that are commonly used in panel estimation, those first introduced in Quinn (1997) and in Chinn and Ito (2006) . We offer some concluding comments in Section 5 . II. Constructing the Capital Control Indicators Cross-country time series of capital controls typically draw from the IMF’s Annual Report on Exchange Arrangements and Exchange Restrictions (AREAER). 9 The capital control measures presented in this paper are also based on the de jure information

C. Emre Alper, Ms. Wenjie Chen, Mr. Jemma Dridi, Hervé Joly, and Mr. Fan Yang

since the ratification of the CM protocol is evaluated. To that end, a summary review of laws and regulations on the movement of capital across the EAC borders is provided, based on the EAC CM Scorecards (2014 and 2016). 1 Second, openness to capital flows is assessed using two capital control indicators, based on de jure information available in the IMF’s Annual Report on Exchange Rate Arrangements and Exchange Rate Restrictions (AREAER). 2 Third, deviations from the covered interest parity (CIP) condition are analyzed, based on available data on nondeliverable

Mr. Giovanni Dell'Ariccia, Mr. Paolo Mauro, Mr. Andre Faria, Mr. Jonathan David Ostry, Mr. Julian Di Giovanni, Mr. Martin Schindler, Mr. Ayhan Kose, and Mr. Marco Terrones

2005, while only 4 countries opted to fully close their capital accounts between 1995 and 2005. 4 Figure 3.3. Capital Controls by Financial Openness and Income Group Sources: IMF, Annual Report on Exchange Arrangements and Exchange Restrictions (AREAER) ; and IMF staff calculations. Notes: Based on a sample of 74 countries for which data on de facto globalization and de jure capital controls are available for the entire sample period. The graph depicts unweighted averages of countries' capital controls, using the IMF's binary capital controls indicator

Mr. Emre Alper, Ms. Wenjie Chen, Mr. Jemma Dridi, Mr. Herve Joly, and Mr. Fan Yang
This paper assesses the extent of economic and financial integration among the East African Community (EAC) along a number of dimensions and, where possible, whether integration has increased in the wake of the major regional integration policy milestones.
Ms. Diva Singh

similar to the one used earlier and includes 76 countries between the mid-1980s and 2014. In light of the endogeneity of the integration variable with respect to growth, the baseline model uses an instrumental variable (IV) panel estimator with the following instruments: the first lag of the integration variable; the capital controls indicator by Fernández and others (2015) ; the occurrence of a banking crisis 10 years earlier; and a subcomponent of the ICRG political risk index, which describes the extent to which profits can be transferred or repatriated out of a

Mahir Binici, Michael M. Hutchison, and Mr. Martin Schindler
How effective are capital account restrictions? We provide new answers based on a novel panel data set of capital controls, disaggregated by asset class and by inflows/outflows, covering 74 countries during 1995-2005. We find the estimated effects of capital controls to vary markedly across the types of capital controls, both by asset categories, by the direction of flows, and across countries' income levels. In particular, both debt and equity controls can substantially reduce outflows, with little effect on capital inflows, but only high-income countries appear able to effectively impose debt (outflow) controls. The results imply that capital controls can affect both the volume and the composition of capital flows.
Mahir Binici, Michael M. Hutchison, and Mr. Martin Schindler

model is estimated using panel methods and fixed effects and includes a host of well-known determinants of capital flows in addition to our indicators of legal restrictions on asset categories. Our main finding is that existing, more aggregated capital control indicators hide substantial variation in the effects of capital controls across the various subcomponents of capital flows. We find that capital controls are effective in limiting capital outflows on equity-like instruments (equity and FDI) and debt instruments. However, controls affect capital flows only

Mr. Alessandro Prati, Mr. Martin Schindler, and Mr. Patricio A Valenzuela
We provide new firm-level evidence on the effects of capital account liberalization. Based on corporate foreign-currency credit ratings data and a novel capital account restrictions index, we find that capital controls can substantially limit access to, and raise the cost of, foreign currency debt, especially for firms without foreign currency revenues. As an identification strategy, we exploit, via a difference-in-difference approach, within-country variation in firms' access to foreign currency, measured by whether or not a firm belongs to the nontradables sector. Nontradables firms benefit substantially more from capital account liberalization than others, a finding that is robust to a broad range of alternative specifications.