To be submitted to VOX EU
Capital Control Measures: A New Dataset
Andrés Fernández, Michael W. Klein, Alessandro Rebucci,
Martin Schindler and Martín Uribe
March 6, 2015
The Great Recession has spurred a reconsideration of the appropriate role of
capital controls. The prevailing view among economists in the 1990s was reflected
in the title of Rudiger Dornbusch’s 1998 article “Capital Controls: An Idea Whose
Time is Gone.” But attitudes began to shift in response to the economic crises in the
late 1990s. More recently, IMF staff studies and policy papers have shown greater
acceptance of the use of capital controls as part of a country’s “policy toolkit” under
certain circumstances, a shift that The Economist magazine dubbed “The
Reformation.”1 Other prominent calls for a greater role for capital controls include
those by Jeanne, Subramanian and Williamson (2012) and Rey (2013). Some of
these policy prescriptions are consistent with a new branch of theoretical research
in which capital controls contribute to financial stability and macroeconomic
management. 2 But these theoretical works stand in contrast to a large number of
empirical analyses that emphasize the ineffectiveness and potential costs of capital
controls.3
See, for example, Ostry, Ghosh, Chamon, and Qureshi (2011). The Economist article appeared in
the April 7, 2011 issue.
1
For just a few examples, see Jeanne and Korinek (2010), Javier Bianchi (2011), and Benigno, Chen,
Otrok, Rebucci and Young (2013, 2014).
2
3
See, for example, Forbes (2007), Klein (2013), and Klein and Shambaugh (2013).
The evolving debate on capital controls highlights the importance of careful
empirical analyses of these policies. One challenge facing researchers in this area is
the availability of indicators of capital controls. We have constructed a new data set
that reports the presence or absence of de jure capital controls, on an annual basis,
for 100 countries over the period 1995 to 2013.4 Like other de jure capital control
panel data sets, ours is based on information in the IMF’s Annual Report on
Exchange Arrangements and Exchange Restrictions (AREAER).5 One contribution
of our work is that we have developed a specific set of rules for coding the narrative
reports in the AREAER, which we present in a technical appendix to our paper.
A distinguishing and important feature of our data set is its disaggregation of
data series down to the level of individual types of transactions between residents
and non-residents, allowing for the construction of separate capital control indices
for both inflows and outflows for ten different asset categories. This level of
disaggregation of the original data makes possible a more detailed and nuanced
analysis of capital controls than with most other capital control indices. For
example, these data allow an examination of the co-movements of controls on
different types of assets and, for a particular set of asset categories, on the comovements of controls on inflows and outflows. Researchers can also construct
more aggregated measures of controls that are well targeted to the specific nature of
See Fernández, Klein, Rebucci, Schindler and Uribe (2015). The data set is available on-line at the
NBER’s International Finance and Macroeconomics Catalogue of Data Sources, at
http://www.nber.org/data/international-finance/ .
4
Two other cross-country data sets that are also based on the AREAER are Quinn (first presented in
1997) and Chinn and Ito (first presented in 2006). Our data set builds on Schindler (2009).
5
the topic being studied; for example, an analysis of interest parity could use an
aggregate of controls on fixed-income securities.
The ten categories of assets in our data set (and their two-letter
abbreviations) are money market instruments (mm, fixed income assets with a
maturity of less than one year), bonds (bo, which have a maturity of one year or
greater), equities (eq), collective investments (ci), financial credits (fc), real estate
(re), commercial credits (cc), derivatives (de), direct investment (di) and guarantees,
sureties and financial backup facilities (gs). Figure 1 presents information on the
prevalence of controls across asset categories, aggregated across countries and years
(the two-letter asset category abbreviations are followed by either i, for controls on
inflows, or o, for controls on outflows, with the 21st category, ldi, representing
controls on the liquidation of direct investment). This figure shows that the
prevalence of controls across countries and across time ranges from 18 percent of
observations (for ldi), to 25 percent (for gsi) to 50 percent or greater (for inflow
controls on rei, mmo, boo, eqo, cio and deo). The figure also demonstrates that, but
for Real Estate and Direct Investment, there is a higher prevalence of controls on
outflows than on inflows.
To further illustrate a use of our data set, Figure 2 shows the correspondence
of countries’ controls on inflows and outflows for indicators that aggregate across
categories of assets and years. The left panel presents this information for the 42
High income countries and the right panel for the 58 Medium and Low Income
countries. The sizes of the bubbles in these figures reflect the number of countries
in a small range. The two panels of this figure show a somewhat higher prevalence
of outflow controls than of inflow controls, which is more pronounced for the
Medium and Lower Income countries than for the High Income countries. There is
a relatively high correlation of inflow and outflow controls on a country-by-country
basis (for both sets of countries, the correlation is about 0.8).
These figures show just a small range of the rich set of opportunities
presented by this data set. Three of us have already used these data to show that
the presence of capital controls is relatively stable, and they are imposed in an
acyclical manner (Fernández, Rebucci and Uribe 2013). We also show, in our
working paper, that these data can be used to distinguish between narrowly
targeted, episodic capital controls and longstanding, widely-imposed controls, a
distinction that Klein (2012) makes between “gates” and “walls.”
The debate over capital controls will likely continue to be one of the central
topics related to the discussion of the international monetary system. We hope that
our contribution of this data set helps to inform this debate.
Figure 1: Proportion of Observations With Controls
By Asset Category and Direction of Restriction
.55
.5
.45
.4
.35
.3
.25
.2
.15
.1
.05
fc
i
fc
o
cc
i
cc
o
gs
i
gs
o
di
i
di
o
ld
i
m
m
m i
m
o
bo
i
bo
o
eq
eq i
o
ci
i
ci
o
de
de i
o
re
i
re
o
0
Asset Category and Direction (Inflow (i) or Outflow (o)) of Restriction
Figure 2: Inflow Controls vs. Outflow Controls
Countries' Average Values for all Ten Assets, 1995 - 2012
.75
0
.25
.5
Inflow Controls
.5
.25
0
Inflow Controls
.75
1
58 Medium & Low Income Countries
1
42 High Income Countries
0
.25
.5
.75
Outflow Controls
1
0
.25
.5
.75
Outflow Controls
1
References
Bianchi, Javier (2011), “Overborrowing and Systemic Externalities in the Business
Cycle”, American Economic Review, 101(7): 3400–26.
Benigno, Gianluca, Huigang Chen, Chris Otrok, Alessandro Rebucci and Eric R.
Young, (2013), “Financial Crises and Macro-Prudential Policies”, Journal of
International Economics, 89(2): 453-470.
_________________________________, (2014), “Capital Controls or Exchange Rate
Policy? A Pecuniary Externality Perspective,” CEPR Discussion Paper no. 9936.
Chinn, Menzie D. and Hiro Ito (2006). “What Matters for Financial Development?
Capital Controls, Institutions, and Interactions”, Journal of Development
Economics, 81(1): 163-192.
Dornbusch, Rudiger (1998), “Capital Controls: An Idea Whose Time is Gone”,
mimeo.
Fernández, Andrés, Alessandro Rebucci, and Martín Uribe (2014), “Are Capital
Controls Countercylical?” mimeo, Columbia University.
Fernández, Andrés, Michael W. Klein, Alessandro Rebucci, Martin Schindler and
Martín Uribe (2015), “Capital Controls Measures: A New Dataset” NBER Working
Paper no. 20,970.
Forbes, Kristin (2007), “One Cost of Chilean Capital Controls: Increased Financial
Constraints for Smaller Traded Firms,” Journal of International Economics, 71: 294
– 323.
Jeanne, Olivier and Anton Korinek (2010), “Excessive Volatility in Capital Flows: A
Pigouvian Taxation Approach”, American Economic Review Papers and Proceedings,
100(2): 403 – 407.
Jeanne, Olivier, Arvind Subramanian, and John Williamson (2012), “International
Rules for Capital Controls”, VOX EU, 11 June.
Klein, Michael W. (2013), “Capital Controls: Gates versus Walls”, VOX EU, 17
January, 2013.
_________________, and Jay Shambaugh (2013), “Is There a Dilemma with the
Trilemma?” VOX EU, 27 September.
Ostry, Jonathan, Atish Ghosh, Marcos Chamon, and Mahvash S. Qureshi (2011),
“Capital Controls: When and Why”, IMF Economic Review, 59(3): 562–580.
Quinn, Dennis (1997), “The Correlates of Change in International Financial
Regulation”, American Political Science Review, 91(3): 531–51.
Rey, Hélène (2013), “Dilemma not Trilemma: The Global Financial Cycle and
Monetary Policy,” VOX EU, 31 August.
Schindler, Martin (2009), “Measuring Financial Integration: A New Data Set”, IMF
Staff Papers, 56(1): 222–38.