Chapter

VII Indices of Exchange and Capital Controls and Relationships with Economic Development

Author(s):
R. Johnston, and Mark Swinburne
Published Date:
September 1999
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Evaluating the restrictiveness of exchange regimes is a complex task, but in recent years it has been regarded as an important element of reaching a better analytical understanding of the impact of exchange systems on economic performance. This section presents indices of controls on current payments and transfers (denoted by CCI), capital controls (KCI), and exchange and capital controls (ECI). The latter index is an average of the two former indices and represents an overall measure of controls. These indices provide a concise yet comprehensive measure of the prevalence of a member’s exchange and capital controls for policy and research and allow for cross-country comparisons of the relative degree of openness and neutrality of members’ exchange systems. The indices aggregate information from the IMF’s Annual Report on Exchange Arrangements and Exchange Restrictions. In 1997, the AREAER information59 was presented in a new tabular format, which has allowed for the development of these more complete measures.

The indices are estimated for a sample of 41 industrial, developing, and transition economies, with close to complete data for 1996. On average, capital controls are more prevalent and vary more widely across countries than controls on current payments and transfers. Sensitivity analysis demonstrates the general robustness of the indices to the different treatment of specific types of control, for example, international security restrictions and controls on direct foreign investment, and to different weights. The extent of exchange and capital controls, as measured by the indices, is found to be positively related to the size of the parallel, black, or free market premium; volatility of the exchange rate; and the level of trade barriers. Lower levels of exchange and capital controls are found to be associated with a higher level of economic development, higher efficiency and depth of the financial sector, larger trade and capital flows, and greater openness of the economy.

The indices of exchange and capital controls and the index of trade regime restrictiveness characterize the respective aspects of the external sector regime.60 The indices of exchange and capital controls are a useful analogue and counterpart to the index of trade regime restrictiveness, which was developed at the Fund in 1997. Despite its limitations, the trade restrictiveness index was considered to represent a useful tool for classifying the relative restrictiveness of trade regimes and analyzing the progress in trade liberalization.

Literature Review

One conventional approach to measure the restrictiveness of exchange regimes focuses on the assessment of the observable effects of exchange controls, including onshore-offshore interest differentials, the size of the black market premium, deviations from covered interest parity, and capital flows.61 Such measures, however, require a minimum development of financial markets, and measures of the black market premium are not always available or reliable. In addition, the measures might be misleading to the extent that prices are affected by nonpolicy factors, for example, the size of the economy. Likewise, an index of capital mobility, such as, for example, the absolute value of the current account deficit relative to GDP,62 is a useful, albeit imperfect, proxy of the extent of the liberalization of capital controls, partially because it reflects net, rather than gross, capital flows.

An alternative approach is to develop measures of the prevalence of exchange controls on the basis of government regulations. The existence of exchange and capital controls can be indicated by a dummy variable, which is set equal to 1, if the respective control(s) is (are) in place, and zero otherwise. On the basis of AREAER summary tables, Grilli and Milesi-Ferretti (1995) construct dummy variables for restrictions on current account and capital account transactions, and multiple currency practices and empirically analyze the effects of exchange and capital restrictions on inflation, real interest rates, and growth, as well as the factors determining the use of capital controls.63Loungani, Razin, and Yuen (1997) use Grilli and Milesi-Ferretti’s data to examine the effects of capital controls on the output-inflation trade-off. Lewis considers the effects of exchange and capital restrictions, as measured by dummy variables, on the consumption-smoothing behavior.64 Although parsimonious dummy variables are convenient, they reflect the presence only of a particular type or types of control. A potentially more fruitful approach is to develop aggregate indicative measures describing the regulatory regime.

Bartolini and Drazen (1997) suggest aggregating dummy variables into a simple index of capital controls. They base their index on three types of measures: restrictions on payments for capital transactions, multiple exchange rates, and restrictions on repatriation of export proceeds. They assign values to these variables on the basis of AREAER for 73 developing countries. The index of capital controls in developing countries is the sum of dummy variables for individual countries normalized by three times the number of countries. Bartolini and Drazen’s methodology was recently applied to the analysis of capital flows to emerging markets.

Another aggregate measure of exchange and capital controls is presented in the IMF’s review of experience under arrangements supported by the Extended Structural Adjustment Facility (ESAF). The measure used is a simple average of two individual indicators: the level of premium in the parallel exchange market, and the extent of surrender requirements and nonmarket allocation of foreign exchange. Each indicator measures the extent of policy distortions on a six-point scale, whereby higher scores correspond to better policies or fewer distortions.65

Johnston and Ryan (1994) suggest a refined version of the dummy variable technique in an empirical study of the effectiveness of controls in protecting the private capital accounts of countries’ balance of payments. Complementing AREAER information with the OECD Code of Liberalization of Capital Movements, the authors classify capital control regimes into liberal or restrictive, depending on the existence of direct and indirect restrictions on capital movements. The corresponding dummy variable is an improvement over conventional binary measures, as it implicitly incorporates the scope and intensity of capital controls. Moreover, for time-series analysis the authors introduce four additional dummy variables to measure changes in the coverage and intensity of regulations.

Methodological Approach and Data

Data on exchange and capital controls maintained by individual countries are contained in the AREAER. In 1997, the information in the AREAER was presented in a new tabular format, which classified and standardized the information on members’ exchange systems and expanded the coverage of capital controls. Classification of the information in this new tabular format has made it possible to develop and apply more comprehensive indices of the pervasiveness of exchange and capital controls. Like AREAER, the indices consider the restrictive ness of the exchange and capital control regime from an economic rather than the IMF’s jurisdictional perspective.

Specifically, the AREAER’s tabular presentation identifies 142 individual types of exchange and capital controls. These are aggregated hierarchically into 16 categories; these categories are aggregated into the indices, which measure the pervasiveness of controls on current payments and transfers, capital controls, and exchange and capital controls in their entirety. Individual types of exchange and capital controls and aggregation in categories are shown in Box 7.

Mathematically, the structure of the indices can be described as follows. The existence of control i in country j is represented by a dummy variable Dij, which equals 1 when an individual type of control is in place, and zero otherwise. The index of controls in category k, denoted by CIkj, is defined as the actual number of controls normalized by the total feasible number of controls:66

where Nk denotes the number of controls in category k.

The indices of controls on current payments and transfers and capital controls, denoted by CCIj and KCIj respectively, are defined as averages of the indices of the respective categories, that is,

Box 7.Structure of Indices of Exchange and Capital Controls

Index of Controls on Current Payments and TransfersIndex of Capital Controls
Exchange arrangementPayments for invisible transactions and current transfersProceeds from exports, invisibles, and current transfers
Exchange rate structureRepatriation requirements for export proceeds
DualFreight/insuraneeSurrender requirements for export proceeds
MultiplePrior approvalRepatriation requirements for proceeds from invisibles and current transfers
Exchange taxQuantitative limits
Exchange subsidyIndicative limits/bona fide testSurrender requirements for proceeds from invisibles and current transfers
Forward exchange marketUnloading/storage costs
ProhibitedPrior approvalRestrictions on use of funds
Official cover of forward operations requiredQuantitative limitsControls on capital and money market instruments
Indicative limits/bona fide testOn capital market securities
Arrangements for payments and receiptsAdministrative expensesPurchase in the country by nonresidents
Prior approvalSale or issue locally by nonresidents
Prescription of currency requirementsQuantitative limitsPurchase abroad by residents
Indicative limits/bona fide testSale or issue abroad by residents
Bilateral payments arrangementsCommissionsOn money market instruments
Prior approvalPurchase in the country by nonresidents
OperativeQuantitative limitsSale or issue locally by nonresidents
InoperativeIndicative limits/bona fide testPurchase abroad by residents
Other payments arrangementsInterest paymentsSale or issue abroad by residents
Regional agreementsPrior approvalOn collective investment securities
Clearing agreementsQuantitative limitsPurchase in the country by nonresidents
Barter agreements and open accountsIndicative limits/bona fide testSale or issue locally by nonresidents
Profit/dividendsPurchase abroad by residents
International security restrictionsPrior approvalSale or issue abroad by residents
Quantitative limitsControls on derivatives and other instruments
In accordance with IMFIndicative limits/bona fide testPurchase in the country by nonresidents
Executive BoardPayments for travelSale or issue locally by nonresidents
Decision No. 144-(52/51)Prior approvalPurchase abroad by residents
OtherQuantitative limitsSale or issue abroad by residents
In accordance with UN sanctionsIndicative limits/bona fide testControls on credit operations
Medical costsCommercial credits
Payments arrearsPrior approvalBy residents to nonresidents
OfficialQuantitative limitsTo residents from nonresidents
PrivateIndicative limits/bona fide testFinancial credits
Controls on trade in gold (coins and/or bullion)Study abroad costsBy residents to nonresidents
Prior approvalTo residents from nonresidents
Controls on domestic ownership and/or tradeQuantitative limitsGuarantees, sureties, and financial backup facilities
Indicative limits/bona fide testBy residents to nonresidents
Controls on external tradeSubscriptions and membership feesTo residents from nonresidents
Controls on exports and imports of banknotesPrior approvalControls on direct foreign investment
Quantitative limitsOutward direct investment
On exportsIndicative limits/bona fide testInward direct investment
Domestic currencyConsulting/legal feesControls on liquidation of direct investment
Foreign currencyPrior approvalControls on real estate transactions
On importsQuantitative limitsPurchase abroad by residents
Domestic currencyIndicative limits/bona fide testPurchase locally by nonresidents
Foreign currencyForeign workers’ wagesSale locally by nonresidents
Resident accountsPrior approvalProvisions specific to commercial banks and other credit institutions
Foreign exchange accountsQuantitative limits
Held domesticallyIndicative limits/bona fide testBorrowing abroad
ProhibitedPensionsMaintenance of accounts abroad
Approval requiredPrior approvalLending to nonresidents (financial or commercial credits)
Held abroadQuantitative limits
ProhibitedIndicative limits/bona fide testLending locally in foreign exchange
Approval requiredGambling/prize earningsPurchase of locally issued securities denominated in foreign exchange
Nonresident accountsPrior approval
Foreign exchange accountsQuantitative limitsDifferential treatment of nonresident deposit accounts and/or deposit accounts in foreign exchange
ProhibitedIndicative limits/bona fide test
Approval requiredFamily maintenance/alimonyReserve requirements
Domestic currency accountsPrior approvalLiquid asset requirements
ProhibitedQuantitative limitsInterest rate controls
Approval requiredIndicative limits/bona fide testInvestment regulations
Blocked accountsCredit card use abroadCredit controls
Imports and import paymentsPrior approvalOpen foreign exchange position limits
Foreign exchange budgetQuantitative limitsProvisions specific to institutional investors
Financing requirements for importsIndicative limits/bona fide testLimits (max.) on portfolio invested abroad
Limits (min.) on portfolio invested locally
Minimum financing requirementsCurrency matching regulations on assets/liabilities composition
Advance payments requirement
Advance import deposits
Documentation requirements for release offoreign exchange for imports
Domiciliation requirements
Preshipment inspection
Letters of credit
Import licenses used as exchange licenses
Other
Import taxes collected through the exchange system
Exports and export proceeds
Documentation requirements
Letters of credit
Guarantees
Domiciliation
Preshipment inspection
Other
Export taxes collected through the exchange system

where NCCI and NKCI denote the number of categories in CCI and KCI, respectively. The index of exchange and capital controls, denoted by ECIj is the average of CCIj and KCIj, that is,

Each index ranges from zero (the lowest extent) to 1 (the highest extent). CCI measures the extent of controls on current payments and transfers, and KCI reflects the pervasiveness of direct controls on capital movements. ECI comprises controls on payments and transfers for current and capital transactions and thus reflects the overall incidence of exchange controls (see Tables 33 and 34 for the list of categories included in the indices).

Table 33.Indices of Categories of Controls on Current Payments and Transfers, 1996
Exchange

Arrangement
Arrangements

for Payments

and Receipts
Resident

Accounts
Nonresident

Accounts
Imports and

Import

Payments
Exports and

Export

Proceeds
Payments for

Invisibles and

Current Transfers
Argentina0.00.20.00.00.00.00.0
Australia0.00.10.00.20.00.00.0
Brazil0.50.50.00.00.50.30.4
Canada0.00.20.30.20.00.00.0
Chile0.50.10.00.00.20.70.0
China0.30.30.50.40.40.00.5
Côte d’lvoire0.00.40.50.20.30.60.5
Czech Republic0.00.10.30.00.00.00.0
Denmark0.00.10.00.00.00.00.0
Egypt0.00.60.30.00.00.00.0
France0.00.10.00.00.10.10.0
Germany0.00.10.00.20.00.00.0
Greece0.00.20.00.00.00.00.2
Hungary0.00.40.30.00.10.00.0
India0.00.50.30.00.00.00.8
Indonesia0.00.30.00.00.40.60.0
Israel0.30.20.30.00.20.00.3
Italy0.00.50.00.20.00.00.0
Japan0.00.10.50.00.00.00.0
Kazakhstan0.00.20.30.00.50.70.4
Kenya0.00.10.00.00.20.00.0
Korea, Republic of0.00.20.00.20.00.00.3
Latvia0.30.20.00.20.00.00.0
Mexico0.00.20.00.20.00.00.0
Morocco0.00.60.50.00.20.10.5
Netherlands0.00.10.00.20.00.00.0
New Zealand0.00.10.00.00.00.00.0
Norway0.00.10.00.00.00.00.0
Pakistan0.30.30.30.20.40.30.5
Philippines0.00.40.00.00.30.10.4
Poland0.00.40.30.00.00.00.2
Russia0.00.60.50.00.30.10.3
Saudi Arabia0.00.20.00.00.00.00.0
South Africa0.00.40.50.40.20.10.4
Spain0.00.30.00.00.00.00.0
Thailand0.00.20.50.20.10.10.0
Tunisia0.00.40.30.00.20.30.3
Turkey0.00.50.00.00.00.60.0
United Kingdom0.00.20.00.00.00.00.0
United States0.00.10.00.20.00.00.0
Uruguay0.30.40.00.00.00.00.0
Summary statistics
Mean0.10.30.20.10.10.10.1
Standard deviation0.10.20.20.10.20.20.2
Minimum0.00.10.00.00.00.00.0
Maximum0.50.60.50.40.50.70.8
Table 34.Indices of Categories of Capital Controls, 1996
Proceeds from Invisibles, Exports, and Current TransfersCapital and Money Market InstrumentsDerivatives and Other InstrumentsCredit OperationsDirect Foreign InvestmentLiquidation of Direct Foreign InvestmentReal Estate TransactionsOperations of Commercial Banks and Other Credit InstitutionsOperations of Institutional investors
Argentina0.00.10.00.00.50.00.30.10.7
Australia0.00.30.30.00.50.00.30.10.0
Brazil0.80.41.01.01.00.00.00.50.3
Canada0.00.00.00.00.50.00.00.00.0
Chile0.61.01.00.81.01.01.00.90.3
China1.01.01.00.81.00.00.70.70.0
Côte d’lvoire0.80.81.00.81.01.00.70.41.0
Czech Republic0.40.60.80.30.00.00.30.30.3
Denmark0.00.00.00.00.00.00.70.00.0
Egypt0.00.10.00.20.51.00.70.30.0
France0.00.60.00.00.50.00.00.00.3
Germany0.00.40.00.00.00.00.00.20.0
Greece0.00.00.00.00.50.00.00.00.0
Hungary0.80.71.00.20.50.00.30.61.0
India1.01.01.01.01.01.00.70.70.0
Indonesia0.20.31.00.50.50.00.70.60.3
Israel1.00.70.50.51.00.00.30.20.3
Italy0.00.10.00.00.00.00.00.10.3
Japan0.00.20.00.20.50.00.00.30.3
Kazakhstan0.61.01.01.01.01.01.00.91.0
Kenya0.00.60.50.00.00.00.30.10.0
Korea, Republic of0.80.81.01.01.00.01.00.40.3
Latvia0.00.00.00.00.50.00.30.10.0
Mexico0.00.31.00.50.50.00.30.40.3
Morocco0.80.90.80.80.51.00.70.60.3
Netherlands0.00.00.00.00.00.00.00.10.0
New Zealand0.00.00.00.00.50.00.30.00.0
Norway0.00.00.00.00.00.00.00.10.3
Pakistan0.80.61.00.71.00.01.00.90.0
Philippines0.00.51.00.80.50.01.00.10.3
Poland0.40.81.00.51.00.01.00.20.0
Russia0.81.01.00.81.01.00.70.50.7
Saudi Arabia0.00.40.30.70.00.00.30.20.0
South Africa1.00.61.00.50.50.00.30.80.3
Spain0.00.00.00.00.50.00.00.20.3
Thailand0.80.91.00.21.00.01.00.50.3
Tunisia1.01.01.00.71.00.01.00.51.0
Turkey0.40.30.00.31.00.00.30.50.3
United Kingdom0.00.00.00.00.50.00.00.10.0
United States0.00.20.00.20.50.00.30.00.0
Uruguay0.00.01.00.00.00.00.00.20.0
Summary statistics
Mean0.30.40.50.40.60.20.40.30.3
Standard deviation0.40.40.50.40.40.40.40.30.3
Minimum0.00.00.01.00.00.00.00.00.0
Maximum1.01.01.01.01.01.01.00.91.0

Values of the dummy variables are assigned on the basis of the following conventions. The value of 1 corresponds to prohibitions, quantitative limits, approval and registration requirements,67 restrictions on investors’ opportunity set (e.g., the type of securities), and cases where the respective markets are lacking. The value of zero is assigned for statistical measures, administrative verification, optional official cover of forward operations, liberal granting of licenses, and the lack of access to the formal market for foreign exchange transactions. Under the IMF’s jurisdiction, registration or licensing used to monitor rather than restrict payments and verification requirements, such as a requirement to submit documented evidence that a payment is bona fide do not constitute an exchange restriction, unless the process results in undue delays. With indicative limits, authorities approve all requests for foreign exchange for bona fide current international transactions in excess of limits or for transactions for which there is no basic allocation of foreign exchange. If the public is made aware of such a policy, indicative limits do not constitute a restriction.

The above methodology is applied to a cross-sectional sample of 41 industrial, developing, and transition countries, all of which, except two (Brazil and Egypt) have accepted the obligations of Article VIII of the IMF’s Articles of Agreement. The countries are selected to represent various geographical regions and levels of economic development. On average, 99 percent of the relevant data is available for the countries in the sample. The baseline indices are defined as averages of the indices calculated under two alternative assumptions about missing data: controls and no controls. The average error margin due to missing data does not exceed 0.01. However, the interpretation of results for some countries requires caution. The error margins for Poland’s KCI and ECI are 0.07 and 0.04, respectively, and Russia’s KCI is 0.04.

The present approach has a number of advantages over earlier ones. The measures reflect the prevalence of a broad array of individual types of control, and capture a variety of changes in the regulatory regime. The transparent structure of the indices simplifies their interpretation. The indices are also easy to update and to modify by including or excluding individual types of control. Finally, the indices are based on the documented evidence on exchange and capital controls and reflect the minimum subjectivity possible in this type of study.

The indices should be interpreted as indicative measures of the prevalence of exchange and capital controls. The measures do not explicitly take into account the monitoring and enforcement of exchange and capital controls and thus reflect primarily the de jure rather than de facto incidence of controls. Therefore, an estimate of exchange and capital control’s restrictiveness is biased upward for countries with weak enforcement of controls or that developed informal markets to help circumvent controls at a relatively low cost. Beyond the question of enforcement and supervision, there is a different question of the welfare effects of exchange and capital controls. These effects are clearly very difficult to measure. Although a rigorous estimation of the welfare effects of exchange and capital controls is beyond the scope of this study, it examines the robustness of the crosscountry rankings to different weightings (see below for more details). As with all measures constructed on the basis of regulations, selection and classification of individual types of control, and coding of information are subjective.68 The indices do not distinguish individual types of exchange and capital control beyond the AREAER’s classification. Although individual types and categories of control are given equal weighting in the indices and thus the intensity of exchange and capital controls is not taken into account explicitly, the indices are found to be robust to weighing by subjective intensity measures (see below).

Country Indices

Indices of exchange and capital controls are calculated for 41 countries for 1996 (see Table 35 and Figures 9-11). On average, controls on current payments and transfers are less widespread and less variable across countries than capital controls. The breakdown of the source of the exchange restrictiveness by individual categories of controls is presented in Tables 33-34. The latter depend on the actual number of exchange and capital controls normalized by the total feasible number of measures in the respective category.

Table 35.Indices of Exchange Controls, 1996
Exchange and Capital

Controls (ECI)
Current Payment

and Transfers (CCI)
Capital

Controls (KCI)
Netherlands0.030.050.01
Norway0.030.010.05
United Kingdom0.050.030.07
Denmark0.050.020.07
Germany0.050.040.07
New Zealand0.050.020.01
Greece0.060.060.06
Canada0.070.090.06
Italy0.080.100.06
Spain0.080.040.11
United States0.090.050.13
France0.100.040.16
Latvia0.100.100.10
Kenya0.110.050.17
Uruguay0.110.090.13
Argentina0.110.030.19
Australia0.120.040.20
Saudi Arabia0.120.030.21
Japan0.120.090.16
Czech Republic0.190.040.33
Mexico0.210.050.36
Egypt0.210.120.30
Turkey0.260.160.36
Philippines0.320.160.47
Hungary0.330.100.57
Indonesia0.340.180.50
Israel0.350.160.54
Thailand0.400.170.63
Poland0.400.120.69
Korea, Republic of0.400.100.70
South Africa0.430.290.56
Brazil0.460.310.60
Pakistan0.480.310.66
Morocco0.490.270.72
Tunisia0.510.210.81
China0.530.330.73
India0.550.220.87
Chile0.560.220.89
Côte d’Ivoire0.580.340.82
Russia0.590.270.91
Kazakhstan0.620.300.95
Summary statistics
Mean0.260.130.39
Standard deviation0.200.100.30
Minimum0.030.010.01
Maximum0.620.340.95

Figure 9.Index of Controls on Current Payments and Transfers, 1996

Figure 10.Index of Capital Controls, 1996

Figure 11.Index of Exchange and Capital Controls, 1996

Controls on Current Payments and Transfers

The prevalence of controls on current payments and transfers varies across countries. In industrial countries, regulatory regimes on current payments and transfers are virtually free of controls. However, the index CCI is not equal to zero, partly because many industrial countries selectively restrict current payments to selected countries on security grounds. Such measures are included for completeness, since the indices describe exchange controls in general rather than focusing on motivation. Norway has the most liberal regime with a single exchange measure in place: international security restrictions in accordance with United Nations’ sanctions. The United States and Germany impose international security restrictions and have blocked accounts. In the United Kingdom, external trade in some types of gold is subject to licensing and there are international security restrictions. In addition to international security restrictions, Japan maintains controls on exports and imports of banknotes. Foreign exchange resident accounts held domestically are prohibited, and there are controls on foreign exchange resident accounts held abroad. The latter controls were lifted in April 1998 as part of the financial “Big Bang” reform. The indices, however, refer to 1996 and thus reflect the presence of the control in Japan at that time.

In developing and transition economies, controls on current payments and transfers are more prevalent. Of the sample, Côte d’lvoire has the highest CCI of 0.34, reflecting approval requirements for resident foreign exchange accounts, documentation’ requirements on exports and export proceeds, prescription of currency requirements, clearing agreements, payments arrears, controls on trade in gold and exports of banknotes, and controls on payments for invisibles and current transfers (Table 33). The CCI for China of 0.33 reflects approval requirements for resident and nonresident accounts, controls on payments for invisible transactions and transfers, and documentation and financing requirements for imports. Likewise, the CCI for Brazil of 0.31 captures the existence of a dual exchange rate structure, exchange taxes, financing and documentation requirements for imports, prescription of currency requirements, bilateral and clearing payment arrangements, international security restrictions, private payment arrears, controls on trade in gold, controls on exports and imports of banknotes, and controls on payments for invisible transactions and current transfers.

Capital Controls

The indices measuring the extent of capital controls are higher on average than those of current controls, ranging from 0.01 to 0.95 (Table 35). About 46 percent of countries have KCIs below 0.25. Among these countries are industrial economies and some developing and transition economies—Argentina, Kenya, Latvia, and Uruguay—which have liberalized their capital accounts. Chile, Côte d’lvoire, India, Kazakhstan, Russia, and Tunisia have KCIs above 0.75, indicating that they maintain relatively restrictive regimes for capital movements. Table 34 provides a breakdown of the source of the exchange restrictiveness by categories of controls.

Within the sample, Kazakhstan has the highest KCI of 0.95. Capital controls are used extensively for regulating capital and money market transactions, derivatives, credit operations, direct foreign investment and its liquidation, real estate transactions, and provisions specific to institutional investors. Chile’s KCI of 0.89 reflects controls on such categories of transactions as capital and money market instruments, derivatives and other instruments, direct investment and its liquidation, real estate transactions, operations of commercial banks and other credit institutions, and credit operations. Likewise, Russia maintains extensive controls on capital and money market instruments, derivatives and other instruments, direct foreign investment and its liquidation.

Of the sample, the Netherlands has the most liberal regime pertaining to capital movements with the KCI equal to 0.01. The only measure is open foreign exchange position limits for commercial banks; such prudential measures are included in the database for completeness and are generally not considered capital controls. The KCI of the United States is 0.13 owing to controls on capital market securities (purchased locally by nonresidents, and sold and issued by nonresidents), money market securities (sold or issued locally by nonresidents), financial credits (by residents to nonresidents), inward foreign direct investment, and real estate transactions (purchased locally by nonresidents). Japan’s KCI reflects measures on capital market securities, financial credits (by residents to nonresidents), inward direct foreign investment, and provisions specific to commercial banks and other credit institutions (Table 34).

Correlation Analysis

Correlations between the indices of exchange and capital controls and indicators of economic development, trade and investment, trade regime, and financial sector development are presented in Table 36. Data and sources for correlation analysis are described in Table 37. Exchange and capital controls tend to exist in countries with a large parallel, black, or free market premium; a low level of economic development; high volatility of the exchange rate; small trade and investment flows; restrictive trade regime; and an inefficient financial system. Relatively high correlations are found with the parallel, black, or free market premium and the level of tariff barriers; and negative correlations with the degree of economic development and inward portfolio investment as a share of GDP. In addition, extensive controls on current payments and transfers tend to be associated with widespread capital controls. Correlation coefficients measure how strongly the indices and the respective variables are linearly related and do not necessarily imply a causality relation between the indices and these variables.

Table 36.Correlations
IndicatorsCurrent Payment and Transfers (CCI)Capital Controls (KCI)Exchange and Capital Controls (ECI)
Exchange system
CCI (1996)1.000.840.91
KCI (1996)0.841.000.99
ECI (1996)0.910.991.00
Monthly percentage change in U.S. dollar exchange rate (1996)0.250.330.32
Monthly percentage change in U.S. dollar exchange rate (1992–96 average)-0.03-0.02-0.02
Parallel, black, or free market premium (c.f. official or interbank market exchange rate) (1996)-0.15-0.02-0.06
Economic development
Purchasing-power-parity-adjusted GNP per capita (in U.S. dollars) (1995)-0.01-0.07-0.05
Trade0.030.020.02
Exports (in million U.S. dollars) (1996)0.100.110.11
Imports (in million U.S. dollars) (1996)0.140.100.12
Trade/GDP (in percent) (1996)-0.090.060.03
Mean tariff rate (in percent) (1995)0.070.210.18
Coverage of tariff lines by nontariff barriers (in percent) (1995)
Capital flows
Direct foreign investment abroad (in million U.S. dollars) (1995)0.250.240.25
Direct foreign investment abroad/GDP (in percent) (1995)0.130.080.10
Direct foreign investment in the country (in million U.S. dollars) (1995)0.070.100.10
Direct foreign investment in the country/GDP (in percent) (1995)-0.20-0.22-0.22
Portfolio investment assets (in million U.S. dollars) (1995)0.230.220.23
Portfolio investment assets/GDP (in percent) (1995)0.150.190.19
Portfolio investment liabilities (in million U.S. dollars) (1995)0.210.230.24
Portfolio investment liabilities/GDP (in percent) (1995)0.080.040.05
Other investment assets (in million U.S. dollars) (1995)0.120.130.13
Other investment assets/GDP (in percent) (1995)0.070.080.08
Other investment liabilities (in million U.S. dollars) (1995)0.190.170.18
Other investment liabilities/GDP (in percent) (1995)0.250.190.21
Other private investment assets (1995)0.110.180.17
Other private investment assets/GDP (in percent) (1995)-0.160.01-0.03
Other private investment liabilities (in million U.S. dollars) (1995)0.200.140.16
Other private investment liabilities/GDP (in percent) (1995)0.310.210.24
Financial sector
Intermediation spread (lending minus deposit rate) (in percent) (1996)0.450.320.37
Spread over LIBOR (deposit rate minus LIBOR) (in percent) (1996)0.310.350.35
Domestic credit provided by banks/GDP (in percent) (1996)-0.04-0.04-0.04
Table 37.Data and Sources for Correlation Analysis
DataPeriodSource
Purchasing-power-parity-adjusted GNP per capita (in U.S. dollars)1995World Bank, 1997, World Development Indicators (Oxford University Press for The World Bank)
Exports (in million U.S. dollars)

Imports (in million U.S. dollars)
1996International Monetary Fund, 1996, Direction of Trade Statistics Yearbook (Washington: International Monetary Fund)
Exports plus imports as a ratio to GDP (in percent)1996Calculated on the basis of International Monetary Fund, 1996, Balance of Payments Statistics (Washington: International Monetary Fund)
Mean tariff rate (in percent)1990–93World Bank, 1997, World Development Indicators (Oxford University Press for The World Bank)
Percentage of tariff lines covered by nontariff barriers (in percent)11990–93World Bank, 1997, World Development Indicators (Oxford University Press for The World Bank)
Domestic credit provided by banks/GDP (in percent)1996Calculated on the basis of International Monetary Fund, 1996, International Financial Statistics Yearbook (Washington: International Monetary Fund)
Intermediation spread (lending minus deposit rate) (in percent)1996Calculated on the basis of International Monetary Fund, 1996, International Financial Statistics Yearbook (Washington: International Monetary Fund)
Spread over London Interbank Organization (LIBOR) (deposit rate minus LIBOR) (in percent)1996Calculated on the basis of International Monetary Fund, 1996, International Financial Statistics Yearbook (Washington: International Monetary Fund)
Parallel, black, or free (c.f. official or interbank market exchange rate) market premium (in percent)1996Calculated on the basis of International Monetary Fund, 1996, International Financial Statistics Yearbook (Washington: International Monetary Fund) and the Global Currency Report (Currency Data and Intelligence, Inc.) (various issues)
Average monthly percentage change in the U.S. dollar exchange rate (in percent)1996Calculated on the basis of International Monetary Fund, 1996, International Financial Statistics Yearbook (Washington: International Monetary Fund)
Direct, portfolio, and other investment (in million of U.S. dollars)1995International Monetary Fund, 1996, International Financial Statistics Yearbook (Washington: International Monetary Fund)
Direct foreign investment/GDP (in percent) Portfolio investment/GDP (in percent) Other investment/GDP (in percent)1995Calculated on the basis of International Monetary Fund, 1996, International Financial Statistics Yearbook (Washington: International Monetary Fund)

Nontariff barriers here cover mostly licensing schemes, quotas, prohibitions, and export restraint arrangements.

Nontariff barriers here cover mostly licensing schemes, quotas, prohibitions, and export restraint arrangements.

On average, the more extensive are restrictions on current account transactions, the more extensive are capital controls.69 The indices are highly and positively correlated with each other, with correlation (Figure 12) coefficients ranging from 0.84 to 0.99. One possible explanation of this result is that controls on current payments and transfers may be imposed in an attempt to manage capital flows. For instance, controls on payments for invisible transactions and current transfers are often introduced when limiting capital flight.

Figure 12.Controls on Current Payments and Transfers and Capital Movements

The extent of exchange and capital controls is inversely related to the level of economic development (Figure 13). Correlation coefficients between the indices and purchasing power parity adjusted GNP per capita range from -0.64 for CCI to -0.68 to ECI. To the extent that cross-country results can be interpreted as time series for a representative country, they would imply that, on average, exchange and capital controls tend to be liberalized as the economy develops over time. Figure 13, in addition, suggests that the extent of exchange and capital controls varies across countries with relatively low levels of development. Countries with relatively high levels of development and liberal capital account regimes continue to maintain a number of measures for prudential reasons, for example, open foreign exchange position limits that, as already noted, are covered in the AREAER database for completeness.

Figure 13.Exchange and Capital Controls and GNP Per Capita

The direction of causality between the level of economic development and the extent of exchange and capital controls is ambiguous. On one hand, by helping to preserve domestic savings, exchange and capital controls might promote domestic investment and thus growth—although the evidence that exchange and capital controls have been effective in protecting the balance of payments is weak.70 On the other hand, extensive government intervention is likely to distort prices and thus reduce efficiency and economic growth.

Furthermore, the extent of exchange and capital controls may depend on the level of economic development, partly because tax and financial systems tend to be more developed in countries with higher per capita income. An extensive system of exchange and capital controls is often part and parcel of more general financial repression and weak budgetary and tax systems.

Exchange and capital controls tend to act as a trade barrier.71 Specifically, the indices are inversely related to exports and imports with correlation coefficients ranging from -0.32 to -0.41. The extent of exchange and capital controls is also negatively, albeit weakly, correlated with the openness of the economy, defined as the ratio of exports plus imports to GDP. These results may reflect both the size and openness of the economy: smaller and more open economic countries are more prone to external shocks and thus are more likely to impose exchange and capital controls to try to mitigate such shocks. However, the effectiveness of exchange and capital controls tends to be lower in a more open economy, implying an inverse relationship between openness and exchange and capital controls.

As policy measures, exchange and capital controls tend to complement trade policy instruments, particularly tariff barriers. Correlation between the indices and mean tariff rates ranges from 0.52 to 0.54 (Figure 14). A positive relationship between the indices and nontariff measures is weaker with correlation coefficients 0.19-0.21.72 Weaker correlation may be due to lower reliability of data on nontariff barriers, which are less transparent than tariff ones.

Figure 14.Exchange and Capital Controls and Tariff Barriers

Exchange and capital controls are negatively correlated with different types of capital flows: inflows and outflows of direct, portfolio, and other investment. As a share of GDP, capital flows are also negatively related to the extent of exchange and capital controls. Exchange and capital controls have a relatively high negative correlation with direct foreign investment abroad (the respective correlation coefficient for ECI is -0.49), and portfolio investment liabilities and assets (-0.43 and -0.35, respectively), but less so on other private investment assets (-0.28). In contrast, the impact on the inflow of direct foreign investment (-0.08) and other private investment liabilities (-0.05) is relatively small. The level of trade and investment flows is affected by many factors other than exchange and capital controls, for example, the terms of trade or the relative rates of return. This may partly explain why some countries with relatively restrictive systems of exchange and capital controls could still attract large capital inflows and experience rapid trade growth. The statistical analysis, however, indicates that on average, more extensive exchange and capital controls are associated with lower levels of trade and investment.

Exchange and capital controls tend to be associated with low efficiency and depth of the financial sector, as evidenced by positive correlation coefficients of 0.27-0.28 between the indices and the intermediation spread (i.e., the difference between the lending and deposit rates), and negative correlation coefficients of 0.43-0.46 between the indices and the domestic credit provided by banks as a share of GDP. Exchange and capital controls are also typical in economies with a large spread between the deposit rate and London interbank offered rate (LIBOR) for U.S. dollars; the respective correlation coefficients are 0.38-0.40. One possible interpretation of the result is that exchange and capital controls tend to discourage capital inflows and are associated with higher nominal interest rates due to larger interest payments on government debt or higher inflation, or both.

The extent of exchange and capital controls is positively related to the size of the parallel, black, or free market premium, as compared with official or interbank market exchange rate (correlation coefficients range from 0.46 to 0.53). Information on the black market premium is not always reliable. Nevertheless, the black market premium often indicates the circumvention of restrictive exchange regulations. The relatively high correlation between the size of the black market premium and the indices would confirm this.

The indices are positively related to volatility in exchange rates (correlation coefficients of 0.37-0.49). One interpretation may be that countries with more volatile exchange rates have more incentives to introduce exchange and capital controls. In practice, the success of exchange and capital controls in stabilizing the exchange rate is likely to be limited, particularly in the medium term, because of imperfect enforcement, avoidance, and evasion. Thus, another interpretation is that volatility in exchange rates and reliance on exchange and capital controls are both evidence of poor economic performance and structural weakness in the economy and financial system.

Sensitivity Analysis

Sensitivity analysis examines robustness of the indices to various factors. This analysis indicates that the results are robust with respect to the intensity (severity) of controls and are not seriously affected by different treatment of such measures as international security restrictions, controls on inward and outward direct foreign investment, controls on liquidation of foreign direct investment, and provisions specific to commercial banks and other credit institutions. The indices are also robust to alternative assumptions about missing data.

Intensity of Controls

Welfare effects of different exchange and capital controls tend to vary. For example, price-based measures are likely to be less restrictive than quantity based measures, and an outright prohibition is likely to be more distortionary than a bona fide test. To assess the significance of various types of measures for the indices, the individual types of control were classified into three groups—mildly restrictive, restrictive, and highly restrictive—on the basis of a survey of ten IMF staff experts on exchange systems. To minimize subjectivity, the survey was organized according to the conventional Delphi method. This method was developed in 1948 to deal with communication distortions typically found in groups: inter alia, domination of the group by one or several individuals, pressures to conform to peer group opinion, and so on. During the survey, the anonymity of experts should be preserved. Individual expert judgments from the first round are aggregated in the form of summary statistical measures and comments and are communicated back to the participants during the second round, thus allowing for feedback, social learning, and modification of prior judgments. The objective of the subsequent rounds is to develop a consensus among experts.

In the first round, experts classified exchange and capital controls by their intensity, assuming perfect enforcement and effectiveness of exchange and capital controls. The qualitative judgments were converted into quantitative measures of intensity: intensity was set equal to ⅓ wherever the measure was classified as mildly restrictive, ⅔ as restrictive, and 1 as highly restrictive. The indices were calculated as an arithmetic weighted mean of the intensity measures and dummy variables reflecting the presence of individual types of control.

Aggregated results of the first round and index estimates were communicated to experts in the second round of the survey. Experts had an option of modifying their earlier judgments and were requested to check whether index estimates complied with their knowledge of the exchange systems in the selected countries. The final round of the survey led to a reasonable consensus among experts’ judgments. Consensus was defined as the mean estimate, mean plus the standard deviation, and mean minus the standard deviation corresponding to the same class of intensity. Consensus did not emerge for the following 5 out of 142 measures: international security restrictions in accordance with UN sanctions, prohibition of foreign exchange accounts, barter agreements and open accounts, open foreign exchange position limits, and the purchase of money market instruments in the country by nonresidents. Because consensus was reached for about 97 percent of individual types of control, the number of the survey rounds was limited to two, and mean estimates of intensity were used in the sensitivity analysis for all types of control.

A comparison of these indices with ones calculated without intensity measures demonstrates their robustness with respect to intensity (the Spearman’s rank correlation coefficients are above 0.95). Thus, even without allowing explicitly for the intensity of the measures, the indices tend to reflect the intensity of exchange controls. This is because the indices aggregate information about exchange and capital controls in a hierarchical way—from individual controls to categories to indices—and are based on AREAER’s classification, which already implicitly incorporates information about the intensity of exchange and capital controls in the classification.

The indices were also recalculated excluding controls on international security restrictions, controls on direct foreign investment, and controls on commercial banks and other credit institutions, to examine whether the indices are sensitive to controls for national interest or prudential reasons, or both. Sensitivity analysis demonstrates robustness of results with respect to the above-mentioned changes in the indices’ structure (the Spearman’s rank correlation is above 0.95). The above measures are included in the structure of the baseline indices for completeness, since the indices focus on exchange and capital controls in general, that is, independently of the motivation for controls.

Conclusion

The study presents aggregate indices of controls on current payments and transfers and capital movements. The indices reflect the incidence of 142 individual types of exchange and capital control, as classified in the IMF’s 1997 Annual Report on Exchange Arrangements and Exchange Restrictions. In a cross-country sample of 41 countries, capital controls are found to be more prevalent on average and to have a higher crosscountry variation than controls on current payments and transfers. More extensive exchange and capital controls are associated with larger parallel, black, or free market premium; more volatile exchange rate, higher trade barriers, and more inefficient financial sector. Negative correlation is found with the level of economic development, and trade and investment flows measured in absolute terms and as a ratio to GDP. The indices are robust to weighting by the intensity of controls and certain changes in specification.

Note: This section was prepared primarily by Natalia Tamirisa.

Data in the 1997 issue of AREAER refer to 1996.

See Sharer and others (1998). The indices characterize the two aspects of the regulatory regime pertaining to the external sector: trade and exchange. The trade restrictiveness index evaluates the restrictiveness of trade regimes on the 10-point integer scale, taking into account information on the average tariff rate, the number of sectors covered by nontariff barriers, and the percent of production or trade covered by nontariff barriers.

See, for example, Dooley and Isard (1980).

A similar approach has been used to describe the presence of capital controls in the member countries in Mathieson and Rojas-Suárez (1993).

See Gwartney, Lawson, and Block (1996) for a similar approach of rating the freedom to engage in international capital transactions.

For an analogous approach applied to the evaluation of the extent of market access commitments under the General Agreement on Trade in Services see Hoakman (1995).

Similarly, registration requirements are treated as restrictions in World Bank (1997).

See, for example, Grilli, Masciandaro, and Tabellini (1991) and Cukierman, Webb, and Neyapti (1992) for examples of indices of central bank independence.

Grilli and Milesi-Ferretti (1995) find a similar result in a sample of 61 countries.

See the appendix to Section V for results of an empirical analysis of the rule of exchange and capital controls as a barrier to trade

Although exchange and capital controls are sometimes defined as nontariff barriers, the measures of nontariff barriers here exclude exchange and capital controls.

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