VII Indices of Exchange and Capital Controls and Relationships with Economic Development
- R. Johnston, and Mark Swinburne
- Published Date:
- September 1999
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.
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 Transfers||Index of Capital Controls|
|Exchange arrangement||Payments for invisible transactions and current transfers||Proceeds from exports, invisibles, and current transfers|
|Exchange rate structure||Repatriation requirements for export proceeds|
|Dual||Freight/insuranee||Surrender requirements for export proceeds|
|Multiple||Prior approval||Repatriation requirements for proceeds from invisibles and current transfers|
|Exchange tax||Quantitative limits|
|Exchange subsidy||Indicative limits/bona fide test||Surrender requirements for proceeds from invisibles and current transfers|
|Forward exchange market||Unloading/storage costs|
|Prohibited||Prior approval||Restrictions on use of funds|
|Official cover of forward operations required||Quantitative limits||Controls on capital and money market instruments|
|Indicative limits/bona fide test||On capital market securities|
|Arrangements for payments and receipts||Administrative expenses||Purchase in the country by nonresidents|
|Prior approval||Sale or issue locally by nonresidents|
|Prescription of currency requirements||Quantitative limits||Purchase abroad by residents|
|Indicative limits/bona fide test||Sale or issue abroad by residents|
|Bilateral payments arrangements||Commissions||On money market instruments|
|Prior approval||Purchase in the country by nonresidents|
|Operative||Quantitative limits||Sale or issue locally by nonresidents|
|Inoperative||Indicative limits/bona fide test||Purchase abroad by residents|
|Other payments arrangements||Interest payments||Sale or issue abroad by residents|
|Regional agreements||Prior approval||On collective investment securities|
|Clearing agreements||Quantitative limits||Purchase in the country by nonresidents|
|Barter agreements and open accounts||Indicative limits/bona fide test||Sale or issue locally by nonresidents|
|Profit/dividends||Purchase abroad by residents|
|International security restrictions||Prior approval||Sale or issue abroad by residents|
|Quantitative limits||Controls on derivatives and other instruments|
|In accordance with IMF||Indicative limits/bona fide test||Purchase in the country by nonresidents|
|Executive Board||Payments for travel||Sale or issue locally by nonresidents|
|Decision No. 144-(52/51)||Prior approval||Purchase abroad by residents|
|Other||Quantitative limits||Sale or issue abroad by residents|
|In accordance with UN sanctions||Indicative limits/bona fide test||Controls on credit operations|
|Medical costs||Commercial credits|
|Payments arrears||Prior approval||By residents to nonresidents|
|Official||Quantitative limits||To residents from nonresidents|
|Private||Indicative limits/bona fide test||Financial credits|
|Controls on trade in gold (coins and/or bullion)||Study abroad costs||By residents to nonresidents|
|Prior approval||To residents from nonresidents|
|Controls on domestic ownership and/or trade||Quantitative limits||Guarantees, sureties, and financial backup facilities|
|Indicative limits/bona fide test||By residents to nonresidents|
|Controls on external trade||Subscriptions and membership fees||To residents from nonresidents|
|Controls on exports and imports of banknotes||Prior approval||Controls on direct foreign investment|
|Quantitative limits||Outward direct investment|
|On exports||Indicative limits/bona fide test||Inward direct investment|
|Domestic currency||Consulting/legal fees||Controls on liquidation of direct investment|
|Foreign currency||Prior approval||Controls on real estate transactions|
|On imports||Quantitative limits||Purchase abroad by residents|
|Domestic currency||Indicative limits/bona fide test||Purchase locally by nonresidents|
|Foreign currency||Foreign workers’ wages||Sale locally by nonresidents|
|Resident accounts||Prior approval||Provisions specific to commercial banks and other credit institutions|
|Foreign exchange accounts||Quantitative limits|
|Held domestically||Indicative limits/bona fide test||Borrowing abroad|
|Prohibited||Pensions||Maintenance of accounts abroad|
|Approval required||Prior approval||Lending to nonresidents (financial or commercial credits)|
|Held abroad||Quantitative limits|
|Prohibited||Indicative limits/bona fide test||Lending locally in foreign exchange|
|Approval required||Gambling/prize earnings||Purchase of locally issued securities denominated in foreign exchange|
|Nonresident accounts||Prior approval|
|Foreign exchange accounts||Quantitative limits||Differential treatment of nonresident deposit accounts and/or deposit accounts in foreign exchange|
|Prohibited||Indicative limits/bona fide test|
|Approval required||Family maintenance/alimony||Reserve requirements|
|Domestic currency accounts||Prior approval||Liquid asset requirements|
|Prohibited||Quantitative limits||Interest rate controls|
|Approval required||Indicative limits/bona fide test||Investment regulations|
|Blocked accounts||Credit card use abroad||Credit controls|
|Imports and import payments||Prior approval||Open foreign exchange position limits|
|Foreign exchange budget||Quantitative limits||Provisions specific to institutional investors|
|Financing requirements for imports||Indicative limits/bona fide test||Limits (max.) on portfolio invested abroad|
|Limits (min.) on portfolio invested locally|
|Minimum financing requirements||Currency matching regulations on assets/liabilities composition|
|Advance payments requirement|
|Advance import deposits|
|Documentation requirements for release offoreign exchange for imports|
|Letters of credit|
|Import licenses used as exchange licenses|
|Import taxes collected through the exchange system|
|Exports and export proceeds|
|Letters of credit|
|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).
|Korea, Republic of||0.0||0.2||0.0||0.2||0.0||0.0||0.3|
|Proceeds from Invisibles, Exports, and Current Transfers||Capital and Money Market Instruments||Derivatives and Other Instruments||Credit Operations||Direct Foreign Investment||Liquidation of Direct Foreign Investment||Real Estate Transactions||Operations of Commercial Banks and Other Credit Institutions||Operations of Institutional investors|
|Korea, Republic of||0.8||0.8||1.0||1.0||1.0||0.0||1.0||0.4||0.3|
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).
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.
|Exchange and Capital|
and Transfers (CCI)
|Korea, Republic of||0.40||0.10||0.70|
|Maximum||0.62||0.34||0.95|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.
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).
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.
|Indicators||Current Payment and Transfers (CCI)||Capital Controls (KCI)||Exchange and Capital Controls (ECI)|
|Monthly percentage change in U.S. dollar exchange rate (1996)||0.25||0.33||0.32|
|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|
|Purchasing-power-parity-adjusted GNP per capita (in U.S. dollars) (1995)||-0.01||-0.07||-0.05|
|Exports (in million U.S. dollars) (1996)||0.10||0.11||0.11|
|Imports (in million U.S. dollars) (1996)||0.14||0.10||0.12|
|Trade/GDP (in percent) (1996)||-0.09||0.06||0.03|
|Mean tariff rate (in percent) (1995)||0.07||0.21||0.18|
|Coverage of tariff lines by nontariff barriers (in percent) (1995)|
|Direct foreign investment abroad (in million U.S. dollars) (1995)||0.25||0.24||0.25|
|Direct foreign investment abroad/GDP (in percent) (1995)||0.13||0.08||0.10|
|Direct foreign investment in the country (in million U.S. dollars) (1995)||0.07||0.10||0.10|
|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)||0.23||0.22||0.23|
|Portfolio investment assets/GDP (in percent) (1995)||0.15||0.19||0.19|
|Portfolio investment liabilities (in million U.S. dollars) (1995)||0.21||0.23||0.24|
|Portfolio investment liabilities/GDP (in percent) (1995)||0.08||0.04||0.05|
|Other investment assets (in million U.S. dollars) (1995)||0.12||0.13||0.13|
|Other investment assets/GDP (in percent) (1995)||0.07||0.08||0.08|
|Other investment liabilities (in million U.S. dollars) (1995)||0.19||0.17||0.18|
|Other investment liabilities/GDP (in percent) (1995)||0.25||0.19||0.21|
|Other private investment assets (1995)||0.11||0.18||0.17|
|Other private investment assets/GDP (in percent) (1995)||-0.16||0.01||-0.03|
|Other private investment liabilities (in million U.S. dollars) (1995)||0.20||0.14||0.16|
|Other private investment liabilities/GDP (in percent) (1995)||0.31||0.21||0.24|
|Intermediation spread (lending minus deposit rate) (in percent) (1996)||0.45||0.32||0.37|
|Spread over LIBOR (deposit rate minus LIBOR) (in percent) (1996)||0.31||0.35||0.35|
|Domestic credit provided by banks/GDP (in percent) (1996)||-0.04||-0.04||-0.04|
|Purchasing-power-parity-adjusted GNP per capita (in U.S. dollars)||1995||World Bank, 1997, World Development Indicators (Oxford University Press for The World Bank)|
|Exports (in million U.S. dollars)|
Imports (in million U.S. dollars)
|1996||International Monetary Fund, 1996, Direction of Trade Statistics Yearbook (Washington: International Monetary Fund)|
|Exports plus imports as a ratio to GDP (in percent)||1996||Calculated on the basis of International Monetary Fund, 1996, Balance of Payments Statistics (Washington: International Monetary Fund)|
|Mean tariff rate (in percent)||1990–93||World Bank, 1997, World Development Indicators (Oxford University Press for The World Bank)|
|Percentage of tariff lines covered by nontariff barriers (in percent)1||1990–93||World Bank, 1997, World Development Indicators (Oxford University Press for The World Bank)|
|Domestic credit provided by banks/GDP (in percent)||1996||Calculated on the basis of International Monetary Fund, 1996, International Financial Statistics Yearbook (Washington: International Monetary Fund)|
|Intermediation spread (lending minus deposit rate) (in percent)||1996||Calculated 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)||1996||Calculated 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)||1996||Calculated 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)||1996|
|Direct, portfolio, and other investment (in million of U.S. dollars)||1995||International 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)||1995|
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 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.
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.
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).
See Taylor (1996).
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).
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.