A New Set of Measures on Capital Account Restrictions
Author:
Mr. Jacques A Miniane
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Publication Date:
29 Jul 2004
eISBN:
9781589063235
Language:
English
Keywords:
SP; foreign currency; control program; IMF dummy; EC resident; capital control indices; Capital flows; Capital account; Capital controls; Foreign direct investment; Securities; Global; Africa
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This paper extends the IMF’s post-1996 disaggregated capital account indices back to 1983 for a representative sample of 34 countries. All the information used to construct the indices comes from IMF’s Annual Report on Exchange Arrangements and Exchange Restrictions and is widely available. It is shown that the disaggregated indices do a better job than the pre-1996 single dummy in reflecting both global trends toward capital account liberalization and country-specific liberalization episodes that occurred during the period. Given the frequency of IMF reporting procedures, the disaggregated indices still fail to accurately track temporary control programs designed to fight off crises. Moreover, the lack of systematic information on enforcement means that the indices remain de jure. Some tentative solutions to these limitations are suggested. [JEL C82, F02, F33]

Abstract

This paper extends the IMF’s post-1996 disaggregated capital account indices back to 1983 for a representative sample of 34 countries. All the information used to construct the indices comes from IMF’s Annual Report on Exchange Arrangements and Exchange Restrictions and is widely available. It is shown that the disaggregated indices do a better job than the pre-1996 single dummy in reflecting both global trends toward capital account liberalization and country-specific liberalization episodes that occurred during the period. Given the frequency of IMF reporting procedures, the disaggregated indices still fail to accurately track temporary control programs designed to fight off crises. Moreover, the lack of systematic information on enforcement means that the indices remain de jure. Some tentative solutions to these limitations are suggested. [JEL C82, F02, F33]

A New Set of Measures on Capital Account Restrictions

JACQUES MINIANE*

The Asian crisis of late 1997 and the subsequent collapses in Russia, Brazil, and Argentina have sparked a vigorous debate about how best to improve the current global financial architecture. In this context, recent papers by De Gregorio, Edwards, and Valdés (2000), Edison and Reinhart (2001), and Miniane and Rogers (2003) have tried to assess the effectiveness of capital controls in shaping the size and maturity of capital flows.

One fundamental limitation in the capital controls literature has been the lack of a reliable measure of capital account openness. Capital controls can take many different forms, making it time-consuming to track all changes in restrictions within a single country. Moreover, the construction of any capital controls index raises the problem of aggregation. By how much should a measure drop if a country relaxes one of its many restrictions? Last but not least, the effectiveness of capital controls depends crucially on the government’s willingness and ability to enforce them. Assuming one has qualitative evidence on enforceability, how should it be weighted in the index?

As a result of the lack of a reliable index of capital controls, many studies trying to assess the ability of capital controls to affect financial flows have followed a case-study approach.1 Papers that have attempted to study the effects of capital controls cross-sectionally, such as Grilli and Milesi-Ferretti (1995), have commonly relied on the 0/1 IMF dummies. The pre-1996 editions of IMF’s Annual Report on Exchange Arrangements and Exchange Restrictions (AREAER) provide dummies for all member countries in six separate categories: bilateral payments arrangements with members and nonmembers, restrictions on payments for current account transactions, restrictions on payments for capital account transactions, import surcharges, advance import deposits, and surrender or repatriation requirements for export proceeds. Besides the obvious limitations of a dichotomic dummy, Eichengreen (2001) has pointed out that the dummy for capital account transactions accounts only for restrictions on residents, not on nonresidents.

To remedy the lack of suitable capital control measures, the IMF changed reporting procedures starting with the 1996 edition of the AREAER.2 For each of the above mentioned categories, the “new” AREAER provides dummies in not one but several different subcategories of transactions. In the case of capital account transactions, there are 13 such subcategories, some of which are in turn further disaggregated.3 Moreover, a distinction is now made between controls on inflows and outflows.

The new reporting procedures have prompted several authors, some within the IMF’s staff, to build capital control indices based on the disaggregated AREAER classification (Table 1).4 Barry Johnston and Natalia Tamirisa are rightly credited with initiating this trend (Johnston and Tamirisa, 1998; Tamirisa, 1999 and 2003). The authors build indices for 45 countries by averaging over all possible 0/1 dummies in the new AREAER. Theirs may be the most disaggregated de jure measure yet, but it is limited by the fact that it covers only the post-1996 period.5 Rossi (1999) tries to extend period coverage for a small sample of 15 countries. He builds Johnston and Tamirisa-style indices for 1997 as well as a “subjective” index for 1989. Values for intermediate years are approximated by a linear interpolation if the country experienced a gradual change in restrictions between the endpoints, or by a one-time change otherwise. Brune and others (2001) can only be praised for the coverage of their measure: 173 countries for the period 1973–1999. The index is a sum of 0/1 dummies over 5 different categories, which are in turn an aggregation of the 13 subcategories in the new AREAER.6 Four of the five categories separate controls on inflows and outflows. The main drawback of Brune and others’ data is that they are not publicly available. Also, early editions of the AREAER often lack information to code all five categories, let alone inflows and outflows separately.7 It remains an open question how the authors tackled this problem.

Table 1.

Summary of Alternative Capital Control Measures

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Parallel to these de jure, AREAER-based efforts, researchers have been constructing de facto indices of capital account openness.8 Edison and Warnock (2003) compute the ratio of total market capitalization of equities that are available for purchase by foreign investors over total market capitalization.9 While their index has the great advantage of being both monthly and readily interpretable, restrictions on capital inflows for equity purchases are a small subset of possible capital controls. Another de facto index is based on the work of Lane and Milesi-Ferretti (2001) on countries’ net external wealth and consists of the ratio of a country’s portfolio and direct investment assets and liabilities over GDP. This is, in a sense, a capital account counterpart to the trade openness measures commonly used in the literature.

This paper builds on the tradition of disaggregated AREAER-based measures initiated by Johnston and Tamirisa. Specifically, I use text information in the AREAER to extend this methodology back to 1983 for a sample of 34 countries, thus extending period coverage significantly. As will be shown in the paper, the disaggregated indices do a better job than the standard pre-1996 dummy at tracking both global trends towards capital account liberalization as well as country-specific liberalization episodes. Unlike the Johnston and Tamirisa data, my indices do not disaggregate beyond the 13 main subcategories of capital account transactions in the post-1996 classification. Moreover, they do not separate between controls of inflows and outflows despite a priori advantages of doing so, since it is questionable whether the pre-1996 editions of the AREAER contain enough text information for such a disaggregation. The indices are very transparent in this regard, as I have systematically indicated when the coding of a dummy was done through explicit information in the text and when it was the result of logical induction as explained further in the paper. To see why this is relevant information, note that a full 25 percent of the dummies for the early 1980s were coded through logical induction because of a lack of explicit indications.

The paper is organized as follows. Section I presents and justifies the choice of sample countries and explains in detail the sources of information and the methodology used in the construction of the indices. Section II compares the index with the pre-1996 IMF single dummy, as well as with the de facto measure by Lane and Milesi-Ferretti (LMF).10 Section III addresses the limitations of the post-1996 methodology. In particular, the indices miss temporary capital control programs designed to fight off external crises, and their purely de jure nature says nothing about countries’ enforcement of controls. Some possible solutions are suggested. Section IV contains concluding remarks.

I. Sample and Methodology

Countries and Period Covered

The choice of countries in the data set is somewhat arbitrary. The original impulse behind this project was to improve on the existing IMF single dummies to better study whether capital controls insulate countries from foreign monetary shocks (see Miniane and Rogers, 2003). Country selection for the indices was thus restricted by the availability of data necessary to pursue Miniane and Rogers’s research. The list of countries includes Argentina, Australia, Austria, Belgium, Brazil, Canada, Chile, Colombia, Denmark, Ecuador, Finland, France, Germany, Greece, Hong Kong, India, Italy, Japan, Korea, Luxembourg (pooled with Belgium before 1996), Malaysia, Mexico, the Netherlands, Norway, the Philippines, Portugal, Singapore, South Africa, Spain, Sweden, Switzerland, Turkey, the United Kingdom, and the United States. The data are annual and cover the period 1983 to 2000.11

Despite the arbitrariness of the list, it is worth noting that the sample is diverse along several lines. The five main continents are represented, with particular emphasis on Europe, Asia, and the Americas. Countries range from poor (India, Ecuador) to very rich (Germany, Japan, etc.), with intermediate cases like Chile or Mexico. The whole spectrum of exchange rate arrangements is covered, from a full-blown currency board in Hong Kong, to a managed float in countries like Chile, to a free float in several OECD countries. It is hoped that this diversity somewhat compensates for the relative shortness of the list.12

Information Sources

There are many sources of information on capital controls, including country bulletins on laws enacted. A notable source is the AREAER, which not only contains the previously mentioned dummies but also contains very detailed reports on each country’s exchange arrangement, administration of control, prescription of currency, regulations on import and import payments, payments for invisibles, exports and export proceeds, proceeds from invisibles, capital account transactions, and gold. For each country there is also a section called “Changes,” where the date and details of any change in regulations in any of these categories is registered. As we shall see, the “Changes” section played a crucial role for the construction of my data.

I have decided to use the AREAER as the sole source of information. The reasons for this decision are twofold. First, the AREAER is the only publication that records and classifies the information in a systematic way, both throughout the years and, more importantly, throughout the countries. The same cannot be said about local publications, and this becomes an important consideration when constructing an index. Second, the AREAER is easy to access to verify the indices or their extension to a wider sample of countries or years.

Methodology

The “new” AREAER introduced in 1996 subdivides capital account transactions into 13 subcategories, to which I added a fourteenth as explained below:

  • Capital market securities: shares or other securities of a participating nature, and bonds and other securities with an original maturity of more than one year.

  • Money market instruments: securities with an original maturity of one year or less, such as certificates of deposit, Treasury bills, and so forth.

  • Collective investment securities: share certificates or any evidence of investor interest in an institution for collective investment, such as mutual funds.

  • Derivatives and other instruments: refers to operations in other negotiable instruments and nonsecuritized claims not covered under the previous three items.

  • Commercial credits: covers operations directly linked to international trade transactions.

  • Financial credits: credits other than commercial credits.

  • Guarantees, sureties, and financial backup facilities: securities pledged for payment of a contract, such as warrants, letters of credit, and so on.

  • Direct investment.

  • Repatriation of profits or liquidation of direct investment.

  • Real estate transactions.

  • Personal capital movements: not considered in this paper because of a lack of consistent information in past editions of the AREAER.

  • Provisions specific to commercial banks and other credit institutions: regulations that are specific to these institutions, such as monetary and prudential controls.

  • Provisions specific to institutional investors: one common example is a limit on the share of the institution’s portfolio that may be held in foreign assets.

  • Multiple exchange rate arrangements. These are not part of the capital account subdivision of the AREAER, but I felt it was an important form of capital control. The AREAER systematically provides information on multiple exchange rate regimes.

The rules to construct dummies in each category are as follows:

  • The starting point is the disaggregated dummies provided by the 1996 to 2001 editions of the AREAER. Note that these dummies correspond to the period 1995 to 2000, since each edition reports on restrictions existing as of December 31 of the previous year.

  • Using text information in the 1995 edition, I fill as many of the 13 subcategories as possible for the year 1994. The rule is always the following: one if at least one restriction for that item, zero otherwise.

  • The next step is the “Changes” sections of both the 1995 and 1996 editions. For instance, the text in the 1995 edition might not mention anything about subcategory X in 1994, but the “Changes” section in the 1996 edition might refer to the elimination of some restriction in X during 1995. If one subcategory remains blank after completing this process, I assign it the same value it had in 1995. I call this rule “filling by default.”

  • In the rare case that a subcategory has an NA (not available) value for 1995, I keep the NA unless the text has some explicit information for 1994.

  • Once the 1994 indices have been completed, the process is repeated for 1993, 1992, …, back until 1983.

Other elements in the construction of the indices are worth mentioning. First, whereas the post-1996 editions clearly distinguish between controls on inflows and outflows, the text information in pre-1996 editions may not always contain information on both types of flows. My indices then account for restrictions on inflows and outflows without systematically discriminating between the two. This is in contrast with the pre-1996 IMF dummies, which, as noted earlier, are limited to restrictions on outflows. Second, some countries have restrictions on foreign equity participation in some sectors. The new AREAER will compute this as a double restriction in both capital market securities and in foreign direct investment (FDI). I believe this to be double counting and thus compute the measure as a single restriction on FDI. Since no approach is unambiguously correct, I indicate these sensitive cases with a note in the relevant cell on the spreadsheet. Third, many countries have restrictions on foreign investment in sectors related to defense and public order. Contrary to the AREAER, I chose not to consider these as capital controls. I again indicate these sensitive cases with a note.13

Finally, given that the AREAER fails to provide consistent information on whether countries enforce their restrictions, 1 attribute a value of 1 whenever a control exists, regardless of whether it is enforced. These are fully de jure measures. An exception happens whenever the AREAER indicates explicitly that a given restriction has never been used or enforced. In this case I consider it as nonexistent.14 Once again, I report these rare situations with a note in the relevant cell.

II. Comparison with Alternative Measures

Space considerations prevent a display of the 13 dummies for all countries and all years in the paper. An average over the 13 dummies for each country and each year is presented in Table 2. Tables 3 and 4 present the IMF single dummy and the LMF measure, respectively.15

Table 2.

Disaggregated Indices

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Note: For a given country and year, the index represents the average over the 13 different dummies. Source: Author’s own data.
Table 3.

IMF Single-Dummy Indices

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Table 4.

Lane and MiIesi-Ferretti Indices

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Source: Author’s own computations using data provided by Gian-Maria Milesi-Ferretti. Note: The indices are computed as portfolio and direct investment assets and liabilities as a share of GDP.

global Trend Toward Capital Account Liberalization

Most economists agree that in the past two decades the world has slowly but steadily moved toward greater capital account openness. While this trend may have been deeper in developed countries, it was not necessarily restricted to them.16 To see whether the disaggregated indices capture this trend, I computed a global index for each year by simply averaging over the individual country indices. I also computed a global index from the single dummies and the LMF measure.17 As can be seen in Figure 1, the disaggregated global index (labeled “Miniane” index in the figure) exhibits a pronounced and continued downward trend, from a peak near 0.7 in 1983 to a low around 0.41 in 1999–2000. It is also interesting to note that the downward trend seems to accelerate from the late 1980s to early 1990s. As I show in the next subsection, this is precisely the period during which many European and some Latin American countries were opening their capital accounts.

Figure 1.
Figure 1.

Evolution of Global Indices—All Countries

Citation: IMF Staff Papers 2004, 002; 10.5089/9781589063235.024.A004

The single-dummy and LMF measures exhibit a similar downward trend despite a reversal in the mid- to late 1990s for the former.18 An important difference between the three processes is that, in the case of the IMF dummy, the trend is driven solely by developed countries. To illustrate this, Figures 2 and 3 repeat the exercise in Figure 1 by constructing developing and developed countries subindices for each of the three measures.19 All of them fall considerably throughout the period for the group of developed countries, but only the disaggregated and LMF measures fall for developing nations. The IMF dummy is flat (or increases) for much of the period and falls only in the last year of the sample.

Figure 2.
Figure 2.

Evolution of Global Indices—Developed Nations

Citation: IMF Staff Papers 2004, 002; 10.5089/9781589063235.024.A004

Figure 3.
Figure 3.

Evolution of Global Indices—Developing Nations

Citation: IMF Staff Papers 2004, 002; 10.5089/9781589063235.024.A004

Showing a more detailed perspective, Table 5 computes pairwise time-series correlations between global indices. While these are generally high (above 75 percent), they fall substantially to around 50 percent in the case of the developing countries’ single-dummy subindex. Table 5 also computes for each of the three measures the share of countries for which the country-specific index was higher on average in the first half than in the second half of the period. That share is 100 percent, 82 percent, and 36 percent for the LMF, disaggregated, and single-dummy measures, respectively. In the case of developing countries, the IMF single dummy falls from the first to the second half in just 17 percent of the countries. In short, the single dummies belie the fact that liberalization has also occurred in developing nations, albeit at a slower rate than in developed ones.

Table 5.

Summary Statistics for Global Trends

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Source: Author’s own computations. Note: The liberalization measure computes the percentage of countries in which the value for the second half of the period was lower than for the first half.

Cross-Sectional Comparisons

To compare the indices not through time but cross-sectionally, Table 6 ranks the countries from most to least open according to the three measures. For each measure, a country’s index is computed as the average value across all years in the sample. Note that, in the case of the single dummies, all countries up to the United States rank as equally open, and all countries below Brazil as equally closed.20 Reassuringly, the rankings are pretty similar across measures. If one decomposes the sample in three groups according to the IMF single dummy (above the United States, between the United States and Brazil, and below Brazil), then five out of nine countries in the top group also rank among the top nine in the two other measures.21

Table 6.

Cross-Sectional Comparison

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Source: Author’s own computations. Notes: The ranking is from most to least open. In the IMF dummy ranking, all countries above the United States are tied with the United States, and all countries below Brazil are tied with Brazil. An asterisk denotes that the country appears in the same group in all three measures (see text for details).

For the middle and lower groups, this number is 6 out of 13 and 6 out of 10 respectively. In other words, the measures agree pretty closely about which countries are very open or very closed and less so about the middle ground.

If one computes cross-country correlations (also in Table 6), the correlation is highest between the two AREAER-based measures (73 percent). This is not surprising given that they share a common source of information. Correlations remain relatively high (around 60 percent) with respect to the LMF measure. Finally, note that many countries in the single-dummy classification are shown as having no restrictions in any year (see Table 3). This is a fallacy that is refuted by the text in the AREAER itself. Indeed, no country in the disaggregated sample ever shows an index of zero for any year. This can be partly explained by the fact that the single dummies account only for controls on outflows as noted by Eichengreen (2001).

Country-Specific Liberalization Episodes

So far, comparisons between measures have dealt with general time-series or cross-sectional trends. The purpose of this section is to study specific liberalization episodes and show how these episodes are tracked by the disaggregated index but not by the single dummy. The LMF measure cannot be used to date liberalization episodes, as it shows a rather smooth opening throughout the period for all countries in the sample. Table 7 summarizes the measures undertaken during 16 liberalization/ tightening episodes captured by the disaggregated index.22

Table 7.

Summary of Main Liberalization/ Tightening Episodes Captured in the Data

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Japan’s Big Bang

One of the most talked about liberalization processes has been Japan’s Big Bang. Launched in late 1995, the Big Bang is a staggered but far-reaching reform of the financial sector, which policymakers hope will help the country tap more efficiently into its deep reserves of savings. The list of liberalizing measures pertaining to various items in the capital account includes the following:23 elimination of the approval period for outward direct investments in all but some sectors, elimination of the 5-3-3-2 rule for pension fund managers,24 elimination of the waiting period to resell yen-denominated securities issued abroad to Japanese residents, elimination of the waiting period for loans extended by residents to nonresidents, and liberalization of foreign currency-denominated external loans by insurance companies.

The disaggregated index drops by 50 percent during the short period under consideration, from 0.46 in 1995 to 0.23 in 1998. Japan still had restrictions left at the end of 1998, such as ceilings on the investment in foreign currency-denominated bonds by credit cooperatives, limits on the share of their total assets insurance companies can invest in securities issued by nonresidents, and controls on inward direct investment, which prevented the index from dropping even further. Strikingly enough, the single dummy shows Japan as having no controls before the Big Bang. This is obviously erroneous in light of what has been said, even accounting for the fact that the dummy tracks only controls on outflows.

Liberalization episodes in Europe

Parallel to the creation of the European single market in goods and services, Articles 56 and 57 of the European Union Treaty call for the lifting of all restrictions on capital movements among Member States and between Member States and third countries, the latter with some qualifications. This pushed many European countries to liberalize their capital accounts in the mid- to late 1980s.

One such country is Austria. In 1989, the country started by eliminating virtually all restrictions on long-term capital transfers and pursued its efforts through 1991 when it abolished all remaining foreign exchange controls. Some restrictions on inward direct investment and the establishment of foreign banks remained. The disaggregated index for Austria does indeed fall from 0.69 in 1988 to 0.31 in 1991. Another interesting case is Denmark, which opted for a one-shot rather than a staggered approach, and on October 1, 1988, eliminated all restrictions on inward and outward capital transfers while maintaining some prudential measures regulating net positions in foreign currencies. Once again, the disaggregated index reflects the nature of these changes and falls from 0.62 in 1987 to 0.15 in 1988.

The single dummy also captures these liberalization events, as can be seen in Table 3, even though the values of 1 and zero overstate the level of restrictiveness before liberalization and understate it after. But for other European countries, the single dummy completely missed the liberalization episode. In the case of Greece, the dummy keeps a value of 1 up to 1995. However, Greece had previously undergone major reform starting in 1986 with the elimination of all restrictions applying to residents of other European Community (EC) countries and moving to the authorization granted in 1987 to repatriate capital and profits in respect to borrowings from non-EC countries; the full liberalization in 1989 of direct investments in EC countries by residents of Greece; the authorization granted in 1992 to acquire dividends, bonds, and shares issued in non-EC countries under the same conditions applied to EC member countries; and culminating in 1994 with the elimination of all remaining controls on short-term capital movements. Contrary to the common IMF measure, the disaggregated index in Table 2 closely tracks liberalization, falling from 0.92 in 1985 to 0.62 in 1990 to 0.08 in 1994.

Norway is another case where the disaggregated index picks up the opening of the capital account missed by the single dummy. Among other measures passed by Norway in 1989 one finds authorization granted to residents to provide commercial and financial guarantee obligations abroad with no permission from the Bank of Norway, authorization granted to nonresidents to issue bonds denominated in kroner in Norway subject to a license, and authorization for nonresidents to purchase bonds with a maturity of at least one year. While the disaggregated index falls from 0.69 in 1988 to 0.23 in 1989, the AREAER dummy remains equal to 1 up until the introduction of disaggregated indices.

Liberalization episodes in Latin America

Argentina is a well-known case of liberalization in an emerging economy. Starting with Carlos Menem’s rise to power in 1989, Argentina embarked on a far-reaching liberalization of the economy, including an opening of the capital account.25 Among the measures undertaken one can find the liberalization of international credit operations in December of 1989, or the liberalization of FDI contained in the Economic Emergency Law of September 1989. Indeed, the disaggregated measure falls from 0.75 in 1988 to 0.31 in 1996. The latter figure can be explained by the fact that Argentina left some restrictions in place: for example, mutual funds could not invest more than 25 percent of assets under management in non-Mercosur securities, and issues of derivatives by nonresidents required approval above and beyond that requested from domestic residents. Liberalization was also tracked by the IMF dummy, with one major caveat: the change in the dummy was recorded in 1993, a full four years after the main package of liberalization measures. And once again, the zero value of the index post-1993 overstates the degree of capital account openness.

Another Latin American country to have experienced an opening of its capital account between 1983 and 2000—albeit more gradually and with some setbacks—is Ecuador. Opening measures spread across many years have included a relaxation of foreign equity participation ceilings in July 1987 and the elimination of limits on profit remittances in June 1991. As of December 2000, Ecuador still retained controls on the issue of money market and collective investment instruments by nonresidents and required approval from the Central Bank for all foreign loans. When one looks at the disaggregated measure, it falls gradually from 0.85 in 1983 to 0.39 in 2000, with an increase in 1985. Puzzlingly enough, the IMF dummy has a value of zero in 1983–85, not at all consistent with the text information in the AREAER, which does signal substantial controls on inflows and outflows. After increasing in 1986 (consistent with the change in 1985 in the disaggregated measure), the IMF dummy falls back to zero in 1988. This is once again contradicted by the text information. Finally, the single dummy becomes 1 in 1993 at a time of partial easing of restrictions. The value of the IMF dummy does not seem close to representing actual policies in the country.

III. Limitations of the Measure (and Some Possible Solutions)

This section addresses some of the obvious and not so obvious limitations of the disaggregated measure and proposes tentative solutions. Arguably, the single greatest liability of the measure is that it does not discriminate between controls on inflows and outflows; the reasons for this choice on a pre-1996 AREAER-based measure have already been discussed.26

Missing on Liberalization and Tightening Episodes

A limitation of the data is that they miss important capital control programs instituted in the midst of external crises. Indeed, part of the reason why capital controls are back in vogue is the perception that Malaysia escaped a harsher fate during the recent Asian crisis by imposing a one-year holding period for nonresidents’ portfolio capital in September 1998.27 As can be seen in Table 2, these controls are not “recorded” in the indices. Similarly, the indices do not show any evidence of the temporary control programs instituted in Portugal, Spain, or Sweden at the height of the 1992 exchange rate mechanism (ERM) crisis, such as Spain’s imposition of a compulsory one-year, non-interest-bearing deposit to be held at the Central Bank.28 There are two main reasons why the data fail to capture these episodes. First, the AREAER shows restrictions in place as of December 31 of each year: measures that are put in place for some months and then removed may not get factored into the index. Second, controls that are still in place as of December 31 of the year will not affect the index if they come on top of other existing restrictions in that subcategory. This is what happened in the case of Malaysia, a country that already had restrictions in all capital markets’ subcategories.

Besides emergency tightenings, the data also miss some noteworthy liberalizations. For instance, Brazil’s index value remains equal to 1 up until 1997, when it drops slightly to 0.92. But Brazil underwent an opening of its capital account before 1997. Starting in 1992, the country liberalized the participation by foreigners in the privatization process, nonfinancial residents were permitted to invest up to US$1 million abroad without prior approval, corporations established in Brazil were authorized to issue and place abroad securities that could be converted into equity, prepayment of foreign borrowing and import financing was permitted, and the minimum period for the renewal and extension of foreign credit was lowered. But why didn’t the index fall? Consider the possibility to invest up to US$1 million abroad with no approval. This is certainly less restrictive than the previous situation where every single investment required authorization, but absence of full liberalization means the FDI category will still show a value of 1. The same happens with the lowering of the minimum period for renewal of foreign credit.

One possible solution to the problems recorded in this subsection would be to follow Cardoso and Goldfajn’s (1997) methodology. They track every single capital control enacted in Brazil from 1983 to 1995. Every time a new control is put in place or an existing one becomes more stringent, their index goes up by 1, and the opposite happens following the relaxation or abandonment of existing measures. However, such a time-consuming undertaking may not be realistic for a sample of 34 countries.

Enforcement of Controls

Besides the severity of controls, the question remains as to what extent the controls are effectively enforced. In this respect, de facto measures such as Edison and Warnock’s and Lane and Milesi-Ferretti’s provide only partial answers. An alternative solution would be to weight the disaggregated indices by indirect proxies for enforcement, such as Transparency International’s Corruption Perceptions Index. Even though some relatively uncorrupted countries may lack the means to enforce controls effectively, corruption indices are likely to be a good proxy for enforceability. The Transparency International measures are available for all the countries in the sample. They cover only the past eight years, but this is a small price to pay given that corruption is a relatively slow-changing phenomenon.

Data Frequency

There is no denying that a monthly rather than an annual index could be of great use for many research projects. It is theoretically possible to construct a monthly index from the yearly AREAER data in a reasonably time-efficient manner. Take for a given country its yearly index. If there is no change between years t and (t + 1), then all months of (t + 1) stay equal to the yearly (t + 1) index. Whenever there is change from year to year, one can identify the subcategories where the change occurred from the disaggregated information in the yearly index. The “Changes” section of the year (t + 1) edition of the AREAER will then specify the exact date of change in those subcategories. It remains to be seen whether one would obtain enough monthly variance for such an index to be of any use.

Are All Categories Relevant Throughout the Sample Period?

There is a risk that some of the post-1996 subcategories rendered important through financial innovation may have been irrelevant at the beginning of the sample period. This problem can be measured indirectly by computing the proportion of times that a given subcategory was filled by default rather than through explicit information. Indeed, for the year 1983, the categories “collective investment securities” and “derivatives and other instruments” were filled by default in 50 percent of the cases, versus 25 percent for all categories combined. There is no easy answer to this problem, but the usefulness of explicitly stating how a dummy was coded again becomes apparent. A researcher using the data can easily weight each subcategory by the proportion of countries in which the subcategory was coded through explicit information. This would indeed have assigned the smallest weight to the two categories mentioned above. Alternatively, one could exclude a subcategory if it was filled by default in more than x percent of the cases and examine the robustness of the final indices to reasonable changes in x.

IV. Conclusion

This paper adds to the growing list of capital control measures that build on the post-1996 disaggregated methodology. The indices, nominally 13 times more precise than the common IMF single dummy, do a better job at tracking both world trends toward greater capital account openness and specific liberalization episodes that occurred in various countries under study. The indices could be improved in several directions: greater country/year coverage, greater disaggregation, better consideration of the severity of the controls or their actual enforcement, better tracking of temporary capital control measures to fight speculative attacks, and more careful distinction between controls on inflows and outflows. As they stand, they are an important step forward relative to the previous IMF measures. They complement without substituting other indices recently published in the literature, sometimes through better country coverage and sometimes through greater disaggregation or explicit consideration of missing information. Together with these other indicators they can be of considerable help for researchers trying to quantify the costs and benefits of capital controls, a major issue in the current reformulation of the global financial architecture.

REFERENCES

  • Bekaert, Geert, and Campbell Harvey, 2000, “Foreign Speculators and Emerging Equity Markets,” Journal of Finance, Vol. 55 (April), pp. 565–613.

    • Search Google Scholar
    • Export Citation

  • Brune, Nancy, Geoffrey Garrett, Alexandra Guisinger, and Jason Sorens, 2001, “The Political Economy of Capital Account Liberalization.” Available via the Internet: www.international.ucla.edu/profile/ggarrett/article.asp?parentid=3683.

    • Search Google Scholar
    • Export Citation

  • Camdessus, Michel, 1998, “Capital Account Liberalization and the Role of the Fund.” remarks during the IMF seminar on Capital Account Liberalization, Washington, March. Available via the Internet: www.imf.org/external/np/speeches/1998/030998.htm.

    • Search Google Scholar
    • Export Citation

  • Cardoso, Eliana, and Ilan Goldfajn, 1997, “Capital Flows to Brazil: The Endogeneity of Capital Controls,” IMF Working Paper 97/115 (Washington: International Monetary Fund).

    • Search Google Scholar
    • Export Citation

  • De Gregorio, José, Sabastian Edwards, and Rodrigo Valdés, 2000, “Controls on Capital Inflows: Do They Work?” Journal of Development Economics, Vol. 63 (October), pp. 59–83.

    • Search Google Scholar
    • Export Citation

  • Dooley, Michael, 1996, “A Survey of Literature on Controls over International Capital Transactions,” Staff Papers, International Monetary Fund, Vol. 43 (December), pp. 639–87.

    • Search Google Scholar
    • Export Citation

  • Edison, Hali J., and Carmen M Reinhart, 2001, “Stopping Hot Money,” Journal of Development Economics, Vol. 66 (December), pp. 533–53.

    • Search Google Scholar
    • Export Citation

  • Edison, Hali J., and Francis EWarnock, 2003, “A Simple Measure of the Intensity of Capital Controls,” Journal of Empirical Finance, Vol. 10, No. 1/2, pp. 81–103.

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    • Export Citation

  • Edison, Hali J., M. Klein, L. Ricci, and T. Sløk, 2002, “Capital Account Liberalization and Economic Performance: Survey and Synthesis,” IMF Working Paper 02/120 (Washington: International Monetary Fund).

    • Search Google Scholar
    • Export Citation

  • Eichengreen, Barry J., 2001, “Capital Account Liberalization: What Do Cross-Country Studies Tell Us?” World Bank Economic Review, Vol. 15 (October), pp. 341–65.

    • Search Google Scholar
    • Export Citation

  • Fieleke, Norman S., 1994, “International Capital Transactions: Should They Be Restricted?” New England Economic Review, March–April, pp. 27–39.

    • Search Google Scholar

  • Grilli, Vittorio, and Gian Maria Milesi-Ferretti, 1995, “Economic Effects and Structural Determinants of Capital Controls,” Staff Papers, International Monetary Fund, Vol. 42 (September), pp. 517–51.

    • Search Google Scholar
    • Export Citation

  • Henry, Peter B., 2000, “Stock Market Liberalization, Economic Reform, and Emerging Market Equity Prices,” Journal of Finance, Vol. 55 (April), pp. 529–64.

    • Search Google Scholar
    • Export Citation

  • International Monetary Fund, 1984–2001, Annual Report on Exchange Arrangements and Exchange Restrictions (Washington).

    • Search Google Scholar

  • Johnston, R. Barry, and Natalia T. Tamirisa, 1998, “Why Do Countries Use Capital Controls?” IMF Working Paper 98/181 (Washington: International Monetary Fund).

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  • Kaplan, Ethan, and Dani Rodrik, 2001, “Did the Malaysian Capital Controls Work?” NBER Working Paper 8142 (Cambridge: National Bureau of Economic Research).

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  • Lane, Philip, and Gian Maria Milesi-Ferretti, 2001, “The External Wealth of Nations: Measures of Foreign Assets and Liabilities for Industrial and Developing Countries,” Journal of International Economics, Vol. 55, No. 2, pp. 263–94.

    • Search Google Scholar
    • Export Citation

  • Miniane, Jacques, and John H. Rogers, 2003, “Capital Controls and the International Transmission of U.S. Money Shocks,” International Finance Discussion Paper No. 778 (Washington: Board of Governors of the Federal Reserve System).

    • Search Google Scholar
    • Export Citation

  • Organization for Economic Cooperation and Development, various issues, Code of Liberalization of Capital Movements (Paris: Organization for Economic Cooperation and Development).

    • Search Google Scholar

  • Quinn, Dennis, 1997, “The Correlates of Change in International Financial Regulation,” American Political Science Review, Vol. 91 (September), pp. 531–51.

    • Search Google Scholar
    • Export Citation

  • Rossi, Marco, 1999, “Financial Fragility and Economic Performance in Developing Economies—Do Capital Controls, Prudential Regulation, and Supervision Matter?” IMF Working Paper 99/66 (Washington: International Monetary Fund).

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  • Tamirisa, Natalia T., 1999, “Exchange and Capital Controls as Barriers to Trade.” IMF Staff Papers, Vol. 46 (March), pp. 69–88.

  • Tamirisa, Natalia T., 2003, “Trade in Financial Services and Capital Movements,” Journal of Financial Services Research, 24 (August), pp. 47–60.

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    • Export Citation
*

Jacqucs Miniane is an Economist in the African Division of the IMF Institute. This project began as part of a summer internship in the Exchange Regime and Market Operations Division of the Monetary and Exchange Affairs Department (now Monetary and Financial Systems Department). The author wishes to thank the Division members for suggesting this project and in particular Bernard Laurens and Virgilio Sandoval for clarifying many important issues pertaining to the classification of capital account restrictions. The editors of IMF Staff Papers and two referees provided very useful comments and criticisms of an earlier draft. Gian Maria Milesi-Ferretti kindly provided the Lane and Milesi-Ferretti data. The complete data set can be obtained from the author at jminiane@imf.org.

1

See Dooley (1996), Eichengreen (2001), and Edison and others (2002) for surveys of the capital controls literature.

2

Note that the new reporting procedures covered only 52 countries in the first year and were subsequently extended to all the member countries.

3

The following subcategories are related to capital account transactions: capital market securities, money market instruments, collective investment securities, derivatives and other instruments, commercial credits, financial credits, guarantees, sureties, and financial backup facilities; direct investment, liquidation of direct investment, real estate transactions, personal capital movements, provisions specific to commercial banks and other credit institutions; and provisions specific to institutional investors. These subcategories are in turn disaggregated in the new AREAER.

4

Table 1, based on a similar table by Edison and others (2002), summarizes the main features of various indices presented in this paper.

5

Tamirisa (2003) also exploits the Organization for Economic Cooperation and Development’s (OECD) Code of Liberalization of Capital Movements for years back to 1990. This publication provides information similar to what appears in the AREAER and is equally disaggregated. The main drawback is that the data arc restricted to OECD countries.

6

One of the categories deals with proceeds from invisible transactions, which is separate from capital transactions in the AREAER.

7

As will become clear, many of the dummies in my sample did indeed lack explicit information. Given the coverage of Brune and others (2001) of very poor countries with sparse information and their separation of controls on inflows and outflows, the problem is likely to be even more pervasive in their sample.

8

There are also measures that take advantage of de jure AREAER information without following the disaggregated methodology. A good example is Quinn (1997), who docs not disaggregate over several subcategories of transactions but takes into account the severity of restrictions. This is an important step, but severity is a subjective concept, as is the aggregation over restrictions that vary in their degree of restrictiveness. Also, note that most of Quinn’s data is not publicly available.

9

There are some adjustments for cross-holdings of equities, state ownership, and so forth. Note that the Edison and Warnock index can be related to the measures by Bekaert and Harvey (2000) or Henry (2000), who construct dummies to date stock market liberalization periods.

10

Comparison with the Rossi (1999) and Johnston and Tamirisa (1998) measures is not possible because of their different country/period coverage. Quinn has made only four years of data publicly available, and the Brune measure is not available al all.

11

The paper later discusses a possible method to make the indices monthly in a relatively time-efficient manner.

12

The medium-term goal is to extend the data to a wider sample of countries.

13

These small changes explain why my disaggregated indices may differ slightly from those published by the IMF for the years 1995–2000.

14

One such example is restrictions on FD1 instituted in the United Kingdom in 1973.

15

No dummies are provided for Switzerland before 1995. There are no data for Greece in the LMF measure, and Luxembourg is pooled with Belgium.

16

The following section addresses specific liberalization episodes in both developing and developed countries. Also, in the words of Michel Camdessus, then the IMF’s managing director: “There is also a considerable amount of work to be done at the national and international level to ensure that the preconditions for the freedom of capital movements arc in place. But the big picture is clear: there is an irreversible trend toward capital account convertibility….” (Camdessus, 1998).

17

In Table 4 we can see that a higher value of the LMF measure means more openness, in contrast to the other two indices. For comparability purposes the LMF global index is computed from 1 minus the original LMF value.

18

Even though the LMF index appears to have the most pronounced downward trend, cardinal comparisons between indices are not possible since they measure very different things.

19

I used two criteria for categorizing countries: whether the country is considered “emerging” and included in JP Morgan’s Emerging Markets Bond Index (EMBI), and the World Bank’s World Development Indicators, which classify a country as high income if annual GNP/capita exceeds US$9,076. Both criteria lead to the same selection except for South Korea, which was categorized as developing following the EMBI.

20

See Table 3 for country details. This bundling of countries results from the crudeness of the 0/1 dummy. No two countries are tied in the disaggregated and LMF measures.

21

Countries that appear in the same group in all three measures are marked with an asterisk in Table 6.

22

A liberalization is defined as a decline of at least 0.3 in the index. The set of liberalizations is quite robust to reasonable changes in this value. Note that some noteworthy capital control programs are not summarized in the table, as they are not captured by the index. These are mostly programs put in place in the midst of external crises. The next section addresses this issue in detail.

23

A more detailed account appears in various editions of the AREAER publication.

24

This rule required managers to hold 50 percent or more of assets under management in bank deposits, bonds, or loans; 30 percent or less in stocks; 30 percent or less in foreign currency-denominated assets; and 20 percent or less in real estate property.

25

Argentina has reversed this trend in the past couple of years following the country’s financial collapse. Reversal is not captured in the indices since it occurred after the end of the sample period.

26

Quinn’s measure does not discriminate between the two types of flow either. Edison and Warnock (2003) measure only controls on inflows. One could, in principle, separate assets and liabilities in the Lane and Milesi-Ferretti measure, but the fact that one side is greater than the other may not mean different degrees of restrictiveness for inflows and for outflows.

27

See Edison and Reinhart (2001) and Kaplan and Rodrik (2001) for formal analyses of Malaysia’s experience.

28

See Fielecke (1994) and Edison and Reinhart (2001) for an analysis of controls implemented during the ERM crisis.

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Cover IMF Staff Papers
IMF Staff Papers, Volume 51, No. 2
Author:
International Monetary Fund. Research Dept.
Volume/Issue:
Volume 2004: Issue 002
Publisher:
International Monetary Fund
ISBN:
9781589063235
ISSN:
1020-7635
Pages:
224
DOI:
https://doi.org/10.5089/9781589063235.024
Figure 1.

Evolution of Global Indices—All Countries
Figure 2.

Evolution of Global Indices—Developed Nations
Figure 3.

Evolution of Global Indices—Developing Nations