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Mr. Ayhan Kose
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Mr. Kenneth Rogoff
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Mr. Eswar S Prasad
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Shang-Jin Wei https://isni.org/isni/0000000404811396 International Monetary Fund

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Abstract

This study provides a candid, systematic, and critical review of recent evidence on this complex subject. Based on a review of the literature and some new empirical evidence, it finds that (1) in spite of an apparently strong theoretical presumption, it is difficult to detect a strong and robust causal relationship between financial integration and economic growth; (2) contrary to theoretical predictions, financial integration appears to be associated with increases in consumption volatility (both in absolute terms and relative to income volatility) in many developing countries; and (3) there appear to be threshold effects in both of these relationships, which may be related to absorptive capacity. Some recent evidence suggests that sound macroeconomic frameworks and, in particular, good governance are both quantitatively and qualitatively important in affecting developing countries’ experiences with financial globalization.

Appendix I The First Era of International Financial Integration, 1870-1913

Despite the controversy surrounding today’s trend toward greater globalization, the current degree of international financial integration is no greater than it was in 1870-1913. Technological developments in shipping and communications (such as the introduction of international telegraph links in the 1860s and 1870s) and massive needs for capital to finance investment (especially in railways) in the frontier economies sparked the beginning of the first era of international financial integration. Pre-World War I globalization was famously and colorfully depicted by Keynes (1919): “The inhabitant of London could order by telephone . . . the various products of the whole earth . . .; adventure his wealth in the natural resources and new enterprises of any quarter of the world, and share . . . in their prospective fruits and advantages;. . . [and] couple the security of his fortunes with . . . any substantial municipality in any continent that fancy or information might recommend.” As Keynes pointed out, World War I (and, later, the Great Depression and World War II) and the imposition of capital controls reversed that state of affairs. The movement back toward integration was slow under the Bretton Woods system but accelerated in the 1970s. Arguably, the degree of integration experienced during 1870-1913 was reached again only in the 1990s.

Quantitative indicators of international financial integration support Keynes’s informal description. Obstfeld and Taylor (1998, 2002) show that financial flows from the United Kingdom and some of the more advanced continental European economies to the “emerging markets” of the day (such as Argentina, Brazil, China, Japan, Russia, and Turkey, but also many smaller countries) were very large. For the countries for which data are available, current account surpluses and deficits amounted to substantially larger shares of GDP in 1870-1913 than they do today. Total market capitalization for bonds denominated in pounds sterling issued by emerging markets on the London Stock Exchange was equivalent to about half of the United Kingdom’s annual GDP (Mauro, Sussman, and Yafeh, 2002). Secondary-market trading was active and liquid, with daily yields reported in the press. Newspapers provided timely and abundant information on relevant economic and political events in emerging markets.

Many researchers are comparing that first era of integration with the current era in an effort to obtain clues regarding potential reforms of the international financial architecture. Crises have been more frequent in the post-Bretton Woods era than they were during 1870-1913, but they have often been less costly in terms of output losses (Eichengreen and Bordo, 2002). Crises tended to be country-specific in the past, whereas today they tend to affect several emerging markets at the same time (Mauro, Sussman, and Yafeh, 2002). More generally, despite a similar degree of international integration in both trade and finance, comovement of financial and real variables is higher today than it was in the past. Spreads on bond yields in a common currency today comove across emerging markets to a much higher degree than they did in the past. Moreover, sharp changes in spreads in the 1990s tended to be mostly related to global events, whereas in 1870-1913 they were primarily related to country-specific events, such as major economic reforms or instances of political upheaval. Economic fundamentals (proxied by exports) also comove to a somewhat greater extent today than they did in the past (possibly because emerging markets now have more diversified trade structures and because individual emerging markets today specialize in a few stages of a good’s production sequence). Nevertheless, today’s investors seem to pay less attention to country-specific events than their predecessors did. One possible interpretation is that institutional investors, who seem to represent a greater share of overall investment today than they did in the past, tend to treat emerging markets as a package: when a crisis emerges in one country, they seem to disinvest from several emerging markets en bloc.

Note: This appendix was prepared by Paolo Mauro.

Appendix II Estimating the Benefits of International Financial Integration on Income Levels for Developing Countries Using a Neoclassical Economic Model

A number of papers have attempted to estimate the benefits of international financial integration on the basis of cross-country regressions. The studies that find the largest gains look at the impact of opening the stock market to foreign investors: for example, Bekaert, Harvey, and Lundblad (2002b) and Henry (2003) report growth increases of 1 to 2 percent for five years in a row. It is not obvious, however, how such a result translates into improved domestic welfare. How permanent is the impact of capital account opening on growth? Is the level of output affected in the long run? What share of the output increase is transferred to foreign investors? These questions are crucial in assessing the welfare impact of capital account opening and can be addressed only by looking at the data through the lenses of an explicit model.

Gourinchas and Jeanne (2003b) measure the gains from international financial integration using the neoclassical model of growth. This framework has increasingly been used in recent years to study development and convergence in an international perspective (Hall and Jones, 1999). The calibration methods developed by Hall and Jones and other authors in that literature are applied by Gourinchas and Jeanne (2003b) to estimate the gains from international financial integration.

On the one hand, the neoclassical model is appropriate to measure the gains from integration in terms of international allocative efficiency—for example, the gains that come from the fact that “free capital movements facilitate an efficient global allocation of savings and help channel resources to their most productive uses, thus increasing economic growth and welfare” (Fischer, 1998). On the other hand, this framework does not capture the gains that countries might derive from integration through other, more indirect channels, such as technological diffusion, or from the discipline of international markets on domestic policies.

In the neoclassical framework, cross-country differences in per capita GDP can be decomposed at a given point in time into differences in per capita physical and human capital and in productivity. International financial integration accelerates the growth and convergence of capital-scarce countries by allowing foreign capital to flow into them. In addition, it may accelerate the accumulation of human capital by increasing the real wage and the returns to education. These effects, however, are transitory: the long-run path of per capita GDP is entirely determined by the country’s productivity, which is assumed to be exogenous to the capital account regime.

Thus, the extent to which countries benefit from international integration depends on their degree of capital scarcity. Using data on investment from the Penn World Tables and on human capital from the Barro and Lee datasets, Gourinchas and Jeanne (2003b) compute the level of physical capital, human capital, and productivity for 82 non-OECD countries. They then compare the observed level of physical capital to the theoretical level that should be observed if countries could freely lend or borrow at the world interest rate. The first column in Table A2.1 gives the ratio of observed capital to the level that should prevail under perfect financial integration for different country groupings. Africa, with a ratio larger than one, is found to be a natural exporter of capital.48 Latin America is close to equilibrium and Asia seems to be scarce in capital—mainly because of China and India.49 Thus Latin America should be expected to benefit relatively little from international financial integration, Africa and Asia more so (the former as an exporter, and the latter as an importer, of capital).

Table A2.1.

Non-OECD Countries: Gains from International Financial Integration

article image
Source:This table is based on Tables 4, 8, and 9 in Gourinchas and Jeanne (2003b). Notes: Population weighted averages, 1995. OECD denotes the Organization for Economic Cooperation and Development. Column (I) reports the ratio of the observed capital stock to the capital stock predicted by the neoclassical model under perfect financial integration. Column (2) reports the permanent percentage increase in consumption that yields the same welfare gain as switching from financial autarky to financial openness. Column (3) reports the ratio of labor-augmenting productivity to the U.S. level.

The 82 non-OECD countries in the sample used in Gourinchas and Jeanne (2003b).

These conjectures are vindicated in the second column of the table, which reports the gains from integration in 1995 expressed as a permanent increase in domestic consumption, assuming that countries have the same productivity growth as in the United States. For Latin American countries, opening is found to bring a welfare gain equivalent to a 0.32 percent permanent increase in domestic consumption. For Asian and African countries, the gain is not much larger (1.07 and 0.83 percent, respectively). These small gains (in spite of significant capital scarcity) were made because capital-scarce countries are predicted to eventually accumulate capital even under financial autarky.

Overall, these benefits seem to be considerably smaller than the gains that development economists and policymakers seek to achieve. For the sake of comparison, Gourinchas and Jeanne (2003b) show that eliminating 25 percent of the productivity gap with the United States—an increase in productivity smaller than that experienced in postwar Singapore, Hong Kong, or Israel—yields a welfare benefit that is more than one hundred times larger than that from international financial integration.

The neoclassical framework also suggests that international financial integration does not lead to a significant degree of convergence between developed and developing countries. The reason for that result is straightforward. For international financial integration to have a substantial impact on convergence, capital scarcity would have to be a significant determinant of cross-country inequality in per capita GDP. The data, however, suggest that the opposite is true: developing countries have lower per capita incomes mainly because they are less productive or their economies suffer from domestic distortions, not because they have capital-scarce economies.

To conclude with a caveat, the results in Gourinchas and Jeanne (2003b) should not necessarily be interpreted as evidence that the gains from integration are small in the real world. Rather, these results suggest that if these gains are large, they do not occur primarily through increased international allocative efficiency but through other, more indirect channels that are not captured by the neoclassical model.

Note: This appendix was prepared by Olivier Jeanne.

Appendix III Calculating the Potential Welfare Gains from International Risk Sharing

International financial integration could result in potentially large welfare gains as it allows domestic residents, firms, and countries to smooth fluctuations in their consumption/revenue by diversifying away country-specific risks. For example, during recessions, countries can borrow from international markets and mitigate the adverse impact of declines in aggregate output on consumption and investment. During expansions, they can lend to other countries and/or pay back loans they received during the recessions. Domestic residents and firms can also utilize international financial markets for consumption smoothing and receive large welfare benefits as these markets significantly expand the set of financial instruments available for international risk-sharing purposes. Firms can also invest in plants abroad to protect themselves against shocks associated with domestic cost or productivity changes.

Developing countries, in particular, can obtain large welfare gains through international risk sharing in view of the highly volatile nature of their income and consumption dynamics. Generally speaking, the scope for benefiting from international risk sharing tends to be large when a country’s consumption growth is volatile, positively correlated with domestic output growth, and not highly correlated with world consumption. Recent empirical studies suggest that these features tend to characterize most developing countries. This is particularly the case, on average, for LFI economies; somewhat less so for MFI economies; and still less so for advanced countries.

The potential welfare gains from international risk sharing and the consequent reduction in the volatility of consumption can be calculated using a simple model (details of which are provided later in this appendix).50 In brief, the model compares two scenarios. The first one has no additional risk sharing (relative to what is already implied by observed consumption behavior), but in the second one there is perfect risk sharing so that each country consumes a (constant) fraction of total world consumption. Since total world consumption tends to be less volatile than the consumption of individual countries, the second scenario results in smoother national consumption patterns. The model can be used to generate quantitative estimates of the consumption-equivalent increase in welfare resulting from such reductions in consumption volatility.

Figure A3.1 reports the median gains (in per capita consumption) for each group of economies. The gains are generally inversely proportional to the group’s current degree of financial integration with the world economy. The highly volatile consumption fluctuations faced by LFI economies imply that the benefits from financial integration and consequent reductions in consumption volatility would be very large for them. On average, these benefits would have the same effect as about a 6 percent permanent increase in per capita consumption.51 Even for MFI economies, the potential gains from further international risk sharing are quite large.

Figure A3.1.
Figure A3.1.

Potential Welfare Gains from International Risk Sharing

(Percent of consumption)

Source: Authors’ calculations.Notes: MFI denotes more financially integrated, and LFI denotes less financially integrated, economies.

Methodology

This section briefly explains the methodology underlying the calculations of welfare gains summarized above. During the past decade, a growing body of literature has examined the welfare implications of international risk sharing. While some studies focus on the welfare gains based upon consumption series, some others examine the gains from risk sharing using stock-returns data in this literature. In these studies, a consumer/investor is able to increase her current welfare because she is able to reduce the volatility of her marginal utility of consumption/ wealth over her lifetime by pooling country-specific risk associated with the fluctuations in her consumption/wealth.

Most studies in this literature employ dynamic representative agent models and consider a variety of stochastic processes for consumption series.52 The standard approach in these studies involves determining consumption allocations under two different scenarios. Under the first scenario, there is no risk sharing and domestic consumption is equal to domestic output. Under the second scenario, there is often perfect consumption risk sharing, since countries are able to diversify away all country-specific risk associated with fluctuations in domestic consumption.53 Moving from the first scenario to the second one, the volatility of consumption in each country could go down; the pricing of the consumption streams of countries might change; and the cross-country correlations of consumption series could increase. The resulting welfare gains are associated with reductions in the volatility of consumption and/or changes in the pricing of the consumption series. The welfare-gain calculations generate a welfare estimate that is equal to the permanent relative increase in the expected level of consumption that would lead to the same level of welfare under international risk sharing.

As with several earlier studies, standard practice is followed here and consumption allocations under two scenarios are computed using a simple representative agent model economy. In particular, the welfare-gain calculations here closely follow the methodology employed in van Wincoop (1994 and 1999). In the model economy, there are N countries that can trade in claims on their endowment streams when there is perfect consumption risk sharing. Residents in each country have the same preferences and expected utility is equal to

U i = E 0 H e - βt ( C it ) 1 - γ 1 - γ dt

where H denotes the horizon (number of years), γ the rate of relative risk aversion, and cit aggregate consumption by residents of country i.54 The endowment is represented by yit and follows a random walk with drift:

dy it = μy it dt + σ y it d η i

where ηi is a standard Brownian motion. The correlation between the innovations of endowment growth across two different countries is represented by ρ = ik(iK).

In the first scenario, there is no additional risk sharing relative to what is already implied by observed consumption behavior and domestic consumption is equal to domestic output, citit. This consumption allocation generates the following expected utility

U i = 1 - e - νT ν ( c i 0 ) 1 - γ 1 - γ

where ν = β+(γ-1)(μ-0.5γσ2).

In the second scenario, there is perfect consumption risk sharing, since countries are able to diversify away all country-specific risk associated with domestic consumption. This implies that consumption in each country is equal to the per capita world endowment, which is denoted by γW. Aggregate consumption of a representative country in this case follows approximately a random-walk process with variance σW2=σ2((1/N)+(1-1/N)ρ) (see Lewis, 2000). The measure of the welfare gain is the permanent percentage increase in the expected level of consumption that produces an equivalent improvement in welfare. The approximate welfare gain for the representative country is computed using the following formula

W e l f a r e g a i n 0.5 γ d σ 2 r μ ¯ [ 1 H ( r μ ¯ ) e H ( r μ ¯ ) 1 e H ( r μ ¯ ) ]

where μ¯=μ=0.5γσ2 denotes the risk-adjusted growth rate, r=β+γμ¯ the risk-free interest rate, and dσ2=σW2-σ2 the change in the variance of consumption growth.

The main parameters of the model are also taken from van Wincoop (1999). In particular, the riskfree real interest rate is assumed to be 0.85 percent and the coefficient of relative risk aversion is set at 3.55 For each country, the mean growth rate and the variance of per capita domestic consumption, and the correlation between per capita domestic consumption growth and world consumption growth are estimated and these values are used in the calculations. Since the dataset employed covers the 1970-97 period, these gains correspond to a horizon of 28 years. A decrease in the risk-free rate translates into larger welfare gains, and a decrease in the risk-aversion coefficient is associated with smaller gains. The welfare gains get smaller as the correlation between domestic consumption and the world consumption decreases, and they tend to increase as the volatility of consumption increases.

The welfare gains reported in the main text of this paper are consistent with the estimates found in some recent studies. Although some of these studies report relatively small gains, a majority of them find that gains from risk sharing are quite large, especially for developing countries, as is shown in Table A3.1. Van Wincoop (1994) provides a detailed explanation of why various studies report different results. There are four major parameters affecting the magnitude of welfare gains in these studies: (1) the volatility of domestic output, (2) the rate of relative risk aversion, (3) the risk-adjusted growth rate, and (4) the risk-free interest rate. It is easy to understand why some of the studies produce relatively low welfare gains. In some studies (Cole and Obstfeld, 1991; and Obstfeld, 1994b), the risk-free rate is quite high. Some studies assume certain stationary processes for consumption or shock series, which generate low welfare gains because of the low persistence or volatility associated with these processes (Tesar, 1995; and Mendoza, 1995).

Table A3.1.

Summary of Studies on Welfare Gains from International Risk Sharing

article image
Notes: “Small” refers to the studies that report welfare gains of 0.5 percent or less, and “large” refers to the studies that report welfare gains larger than 0.5 percent. MFI denotes more financially integrated, and LFI less financially integrated, countries.

Some studies use data for advanced countries and find large welfare gains through international risk sharing.56 For example, van Wincoop (1996 and 1999) finds that for the OECD countries the potential welfare gains from international risk sharing are between 1.1 percent and 3.5 percent. Several recent studies consider the implications of international risk sharing for developing countries. Athanasoulis and van Wincoop (1997) calculate the estimates of the degree of uncertainty associated with the growth potential of an economy at various horizons. They find that the welfare gain from sharing of risk associated with the growth uncertainty is around 6.5 percent using the data of 49 developed and developing countries. Obstfeld (1995) finds that elimination of consumption variability through risk sharing can result in much larger welfare gains in developing countries and reports that these gains are between 0.54 percent and 5.31 percent for a selected group of developing economies. Pallage and Robe (2003a) find that the welfare gains associated with smoothing consumption fluctuations are much larger for African countries than for the United States and that, depending on the parameterization of the model economy, these gains can easily exceed 10 percent for several African countries.

Appendix IV Contingent Securities for International Risk Sharing

Although international risk sharing seems likely to provide substantial benefits, only a few securities are available to facilitate it. In particular, there exist no securities that allow the international transfer of GDP risk—that is, the risk associated with fluctuations in the aggregate income of the country where one works and lives.

Several ideas have been considered to fill this vacuum, with many authors suggesting a variety of securities whose return would depend on the evolution of a country’s GDP. The best-known proposal has been put forward by Shiller (1993), who suggested the creation of a market for perpetual claims on countries’ GDPs. By going short on these claims, individuals could insure against the aggregate risk of a fall in income in their own countries. This would bring substantial diversification benefits, because correlations of GDP across countries are relatively low. The market infrastructure for such perpetual claims would, however, have to be created essentially from scratch.

A more practical, if less ambitious alternative might be for countries to issue bonds whose returns were indexed to their own GDPs, as was proposed by several authors in the aftermath of the international debt crisis of the 1980s (see Borensztein and Mauro, 2002 for a review of these proposals). This would simply involve adding an indexation clause (for example, on the coupon rate) to otherwise standard debt contracts. Since sovereign debtors’ debtservicing problems often result from adverse macroeconomic conditions, indexed bonds providing for high interest payments in good times and low interest payments in bad times could help reduce the risk of debt crises. They would also provide more room for fiscal policy to respond to domestic economic conditions. Such an indexed bond would be equivalent to a combination of a “plain vanilla” bond and a claim on the country’s GDP with the same maturity. While individual countries would obtain substantial insurance benefits from these indexed bonds, they would probably not have to pay a large insurance premium—compared with the rate on plain vanilla bonds—to induce international investors to hold them. In fact, from the point of view of international investors, GDP risk associated with individual countries is almost fully diversifiable.

Experience to date with GDP-indexed bonds has been limited to a few small issues in the context of Brady-style restructurings. Bosnia and Herzegovina, Bulgaria, and Costa Rica have included clauses in their Brady bonds providing for higher repayments once GDP or per capita GDP reaches a certain level. These clauses have been mainly intended as incentives for investors by enabling them to share in a potential improvement in the repayment capacities of the debtor countries, rather than as a device to make defaults less likely. Similar bonds have provided for an increase in the value of the claim (value recovery) if certain favorable conditions—such as high oil exports or oil prices—are met, notably for Mexico and Venezuela.

Use of this type of security has been limited for a number of reasons. Securities that are unusual or difficult to understand often result in shallow markets and an illiquidity premium. New instruments are costly to develop, yet they can be imitated at low cost. One could also question whether an instrument that provides extensive insurance against risks may result in diminished incentives to invest and effect policy reforms. Perhaps more tangibly, investors may also feel uneasy about an instrument whose return depends on statistics produced by the issuing government itself. One should note, however, that inflation-indexed bonds are used extensively, both by advanced economies such as the United Kingdom and emerging market economies such as Chile.

Official intervention has often been instrumental in facilitating financial innovation—for example, in the introduction of mortgage-backed securities in the United States—and it could also contribute to fostering the development of markets for international sovereign bonds indexed to GDP or related variables. International financial institutions might play a role by, for example, helping guarantee the reliability of national economic statistics.

Appendix V Small States and Financial Globalization

There is no formal definition of a small state, but it is generally accepted that this label applies to sovereign economies with populations of less than 1.5 million people. By this criterion, 45 developing countries (41 of the IMF’s 184 member countries) are small states. See Table A5.1 for some summary statistics comparing small states to other developing countries and industrial countries for the period 1960–2000. Small states are relatively more open to trade, which implies that they are generally more reliant on export earnings than other developing countries. Their production structures and export bases also tend to be less diversified. Although small states have been developing strong trade linkages with the global economy, their financial linkages are weaker. And although the average ratio of the volume of capital flows to GDP is larger for small states than for other developing countries, it is still roughly 25 percent smaller than that for industrial economies. Aid dependency is an important problem in several small states, since foreign aid is still a major source of income.

Table A5.1.

Are Small States Different? Some Summary Statistics, 1960-2000

article image
Source: Kose and Prasad (2003). Note: Financial openness is measured as the ratio of capital inflows and outflows to GDP.

Average output growth has been higher in small states than in other economies over the last four decades. This outcome appears to have been the result of two main factors—the strong trade linkages of small states and their substantially higher investment ratios. Thus, trade openness has had significant benefits for small states.

Small states face a number of disadvantages arising from their narrow and undiversified production and export bases. They are vulnerable to external shocks, since they are relatively more open; their production and export structures are highly specialized; and they rely more on export earnings. In addition, small states have to cope with a variety of inherent disadvantages arising from their locations. Many of them are located far from the major trade centers, which significantly increases the costs of their exports and imports. Because of their locations, many small economies are highly susceptible to natural disasters, such as earthquakes and hurricanes, that can affect an entire country at the same time and, consequently, have devastating economic impacts.

Although there is a long list of special challenges associated with being a small state, most of these are ultimately related to the fact that small states have relatively high output volatility, even after controlling for income level and degree of openness. One reason may be that smaller economies tend to be less diversified and more vulnerable to external shocks. Indeed, the terms of trade fluctuations in small states tend to be more volatile and highly persistent. Consumption risk sharing seems to be a particularly important challenge for small states, since the average ratio of the standard deviation of consumption growth to that of output growth is even higher in these countries. Moreover, foreign aid flows to many small states are highly volatile and tend to be positively correlated with domestic GDP, implying that they might be further contributing to the volatility of income in these countries.

These findings imply that international risk sharing has significant welfare implications for small states. Indeed, for small states, such welfare gains are potentially very large and equivalent to the increase in welfare that would result from a 15 percent permanent increase in the level of consumption. The potential gains for small states are much larger even than those for other developing countries, since consumption is so much more volatile in the former than the latter.

Trade linkages have already helped many of these economies to increase the size of the markets for their products and benefit from economies of scale. Openness to capital flows would also offer them opportunities to diversify into new sectors, increase investment and growth, and achieve better risk sharing. Both trade and capital flows can also enhance the rate of technology transfers to these economies. Furthermore, globalization offers opportunities for these economies to absorb and adopt best international practices for governance and other institutional structures.

Traditional macroeconomic and structural policy measures are important for deriving benefits from, and reducing the risks associated with, globalization. Small states need to improve their macroeconomic frameworks in order to leave themselves room for maneuver when shocks hit. In addition, poor macroeconomic and structural frameworks could result in the accentuation and increased persistence of the effects of adverse external shocks. Given that aid flows are highly volatile and hard to predict, it is essential for small states to design flexible fiscal frameworks. Moreover, there is increasing evidence that aid flows are used more efficiently in countries with better governance structures and are accompanied by higher inflows of foreign direct investment in countries that employ sound macroeconomic policies.

Appendix VI Data

Unless indicated otherwise, the primary sources for the data used in this paper are the IMF’s International Financial Statistics and the World Bank’s World Development Indicators. The basic data sample comprises 76 countries—21 industrial and 55 developing.57

Industrial Countries

The 21 industrial countries are Australia (AUS), Austria (AUT), Belgium (BEL), Canada (CAN), Denmark (DNK), Finland (FIN), France (FRA), Germany (DEU), Greece (GRC), Ireland (IRL), Italy (ITA), Japan (JPN), Netherlands (NLD), New Zealand (NZL), Norway (NOR), Portugal (PRT), Spain (ESP), Sweden (SWE), Switzerland (CHE), the United Kingdom (GBR), and the United States (USA).

Developing Countries

The developing countries are grouped into more financially integrated (22) and less financially integrated (33) countries as follows:

More Financially Integrated Countries

Argentina (ARG), Brazil (BRA), Chile (CHL), China (CHN), Colombia (COL), Egypt (EGY), Hong Kong SAR (HKG), India (IND), Indonesia (IDN), Israel (ISR), the Republic of Korea (KOR), Malaysia (MYS), Mexico (MEX), Morocco (MAR), Pakistan (PAK), Peru (PER), Philippines (PHL), Singapore (SGP), South Africa (ZAF), Thailand (THA), Turkey (TUR), and Venezuela (VEN); and

Less Financially Integrated Countries

Algeria (DZA), Bangladesh (BGD), Benin (GEN), Bolivia (BOL), Botswana (BWA), Burkina Faso (BFA), Burundi (BDI), Cameroon (CMR), Costa Rica (CRI), Cote d’Ivoire (CIV), the Dominican Republic (DOM), Ecuador (ECU), El Salvador (SLV), Gabon (GAB), Ghana (GHA), Guatemala (GTM), Haiti (HTI), Honduras (HND), Jamaica (JAM), Kenya (KEN), Mauritius (MUS), Nicaragua (NIC), Niger (NER), Nigeria (NGA), Panama (PAN), Papua New Guinea (PNG), Paraguay (PRY), Senegal (SEN), Sri Lanka (LKA), the Syrian Arab Republic (SYR), Togo (TGO), Tunisia (TUN), and Uruguay (URY).

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1

For a historical perspective on international financial integration, see Appendix I.

2

The restriction measure is available until 1995, when a new and more refined measure—not backward compatible—was introduced. The earlier data were extended through 1998 by Mody and Murshid (2002).

3

These stock data were constructed by Lane and Milesi-Ferretti (2001). Operationally, this measure involves calculating the gross levels of FDI and portfolio assets and liabilities via the accumulation of the corresponding inflows and outflows, and making relevant valuation adjustments. A similar measure using the same underlying stock data has been considered by Chanda (2000) and O’Donnell (2001). Other measures of capital market integration include saving-investment correlations and various interest parity conditions (Frankel, 1992). These measures are difficult to operationalize for the extended time period and large number of countries in the data sample used for this paper.

4

An analogy from the literature on international trade may be relevant here. Some countries, owing to their remoteness from major world markets or other unfavorable geographical attributes, have only small trade flows despite having minimal barriers to trade, even after controlling for various other factors. Similarly, certain countries—owing to their remoteness from major financial centers, in terms of either physical distance or historical relationships—may experience limited capital flows despite having relatively open capital accounts (see Loungani, Mody, and Razin, 2003).

5

The dataset used in this paper consists of 76 industrial and developing countries (except where otherwise indicated) and covers the period 1960-99. Given the long sample period, several countries currently defined as industrial (for example, the Republic of Korea and Singapore) are included in the developing country group. The following were excluded from the dataset: most of the highly indebted poor countries (most of which receive official flows), the transition economies of Eastern Europe and the former Soviet Union (owing to lack of data), very small economies (with populations of less than 1.5 million), and trie oil-exporting countries of the Middle East. See Appendix VI for a list of countries and further details on the dataset.

6

A particularly rapid decline in controls occurred during the 1980s, when the members of the European Community, now the European Union, liberalized capital controls. A surge in cross-border capital flows followed.

7

Ishii and others (2002) examine in detail the experiences of a number of developing countries.

8

Not surprisingly, this classification results in a set of MFI economies that roughly corresponds to those included in the MSCI (Morgan Stanley Capital International) emerging markets stock index. The main differences are that we drop the transition economies because of limited data availability and add Hong Kong SAR and Singapore.

9

Note that the scale of the upper panel is twice as big as that of the lower one.

10

Consistent with these results, Taylor and Sarno (1999) find that FDI flows are more persistent than other types of flows. Hausmann and Fernandez-Arias (2000) find weaker confirmation of this result and also note that although the volatility of FDI flows has been rising over time, it remains lower than those of other types of flows. In interpreting these results, there is a valid concern about potential misclassification of the different types of capital flows. Since most of the studies cited here use similar data sources, this is not a problem that can be easily resolved by examining the conclusions of multiple studies.

11

The stock market liberalization index is based on two indices constructed by the International Finance Corporation (IFC) for each country—the Global Index (IFCG) and the Investable Index (IFCI). The IFCG represents the full market, while the IFCI represents the portion of the market available to foreign investors, where availability is determined by the IFC based on legal and liquidity criteria. Edison and Warnock (2001) propose using the ratio of the market capitalization of the IFCG to that of the IFCI as a measure of stock market liberalization. This ratio provides a quantitative measure of the degree of access that foreign investors have to a particular country’s equity markets; one minus this ratio can be interpreted a measure of the intensity of capital controls in a country.

12

The World Bank’s Global Development Finance report for 2001 notes that FDI in Latin America’s financial sector has come about through the purchases of privately owned domestic banks, which have driven up the share of banking assets under foreign control to 25 percent in 1999 from 8 percent in 1994. In East Asia, foreign investors have purchased many local banks in financial distress, leading to an increase in the share of banking assets under foreign control to 6 percent in 1999 from 2 percent in 1994.

13

The presence of mutual funds in MFIs has grown substantially during the 1990s. For example, dedicated emerging market equity funds held $21 billion in Latin American stocks by the end of 1995. By the end of 1997, their holdings of these assets had increased to $40 billion. While mutual funds’ growth in Asia has been less pronounced, the presence of mutual funds is still important in many countries in that region. See Eichengreen, Mathieson, and Chadha (1998) for a detailed study of hedge funds.

14

The relevant cross-country comparison would, of course, be in terms of risk-adjusted rates of reform on capital. Brooks (2000) examines the impact of demographic trends—including projections of fertility rates in different groups of countries—on North-South capital flows. Attanasio and Violante (2000) have argued that the global welfare effects of enabling such capital flows could be quite large. This assumes a lack of large labor mobility from the South to the North, which could dampen demographic shifts and also influence relative rates of return on capital.

16

Table 3.1 reports the growth rates of real per capita GDP in constant local currency units. The exact growth rates and country rankings may change if different measures, such as per capita GDP in dollar terms or on a PPP (purchasing power parity) basis, are used.

17

This extends the survey in the IMF’s World Economic Outlook, October 2001 and Edison, Klein, Ricci, and Sløk (2002).

18

There is some evidence that different types of capital flows may have different effects on growth.

19

See Hall and Jones (1999); Senhadji (2000); Acemoglu, Johnson, and Robinson (2001); Easterly and Levine (2001); and Rogoff (2002) on the role of productivity differences in explaining cross-country differences in income. Gourinchas and Jeanne (2003b) is the only paper that has made a direct comparison between gains from international financial integration and those from a rise in productivity. In a calibrated model, they show that the welfare gain from perfect financial integration is roughly equivalent to a 1 percent permanent increase in consumption for the typical non-OECD economy. By contrast, a productivity increase of the order of magnitude experienced in postwar Republic of Korea yields a welfare benefit that is more than a hundred times larger. The low gains from international financial integration come from the fact that less developed countries are, on average, not very far from their potential level of capital. Non-OECD countries are less developed not primarily because they are capital scarce but because productivity is constrained by the quality of institutions, economic policies, and other factors (see Appendix II).

20

See Ishii and others (2002) for relevant country cases.

21

This point is stressed in the IMF’s World Economic Outlook, September 2002.

22

This subsection draws heavily on Kose, Prasad, and Terrones (2003a).

23

Appendix III discusses the possibility and the limitation of using contingent securities, such as GDP-index bonds, to help reduce income volatility, especially that associated with debt crises.

24

The figure shows the median standard deviation of income growth for each country group, based on standard deviations calculated for each country over a 10-year rolling period.

25

It should be noted that despite the increase in the 1990s, the volatility of both private and total consumption for the MFI economies is, on average, still lower than for LFI economies.

26

For the financial integration measure used in this paper, the threshold occurs at a ratio of about 50 percent of GDP. The countries in the sample that have degrees of financial integration above this threshold are all industrial countries.

27

The notion of procylicality discussed here is that capital inflows are positively correlated with domestic business cycle conditions in these countries.

28

The World Bank’s Global Development Finance report for 2001 also finds some evidence of such procyclicality and notes that the response of capital inflows is typically twice as large when a developing country faces an adverse shock to GDP growth as when it faces a favorable shock. This is attributed to the fact that credit ratings are downgraded more rapidly during adverse shocks than they are upgraded during favorable ones.

29

In fact, in the 1990s, the ERM (exchange rate mechanism of the European Monetary System) crisis was the only significant one among industrial countries. The prolonged Japanese recession is, in some sense, a crisis, although the protracted nature of Japan’s decline, which has not featured any sudden falls in output, would not be consistent with a standard definition of a crisis.

30

Currency crises can also affect firms (Jirectly and, by exacerbating the problems of the banking sector, can lead to a broader credit crunch, even for productive and solvent firms. Mishkin (1999) argues that the credit crunches resulting from sharp contractions in domestic bank credit following financial crises have been instrumental in aggravating these crises and reducing investment and economic activity. Rodrik and Velasco (2000) note that difficulties in rolling over short-term debt during crises rapidly squeeze the availability of liquidity, with immediate effects on investment and output.

31

This paper examines bond, equity, and syndicated loan flows to Brazil, Mexico, the Republic of Korea, and Thailand over the period 1990-2000.

32

Notwithstanding the differences in the types of sensitivities to industrial country business cycle conditions, the fact remains that FDI flows are generally less volatile and less sensitive to the factors discussed here than either portfolio flows or bank lending.

33

These authors use standard measures of financial sector development that are based on the competitive structure and the size of the financial intermediation sector in each country.

35

See Glick and Rogoff (1995) for an empirical analysis of how country-specific productivity shocks affect national investment and the current account. These authors show how the responses to such shocks depend crucially on the persistence of the shocks. Kose, Otrok, and Whiteman (2003) examine the impact of world and country-specific factors in driving fluctuations in output, consumption, and investment.

36

For instance, a shock to GDP growth in one country may be transmitted gradually through trade channels but could far more quickly have an impact on economic activity in another country via correlations in stock market fluctuations. If the two countries were perfectly integrated through trade and financial linkages, this outcome could, of course, simply reflect an optimal risksharing arrangement.

37

Contagion effects aside, Kose, Prasad, and Terrones (2003b) find that increasing financial linkages have only a small effect on cross-country output and consumption correlations.

38

Kim, Kose, and Plummer (2001) examine the roles of fundamentals-based contagion and pure contagion during the Asian crisis.

39

Claessens and Forbes (2001) contains a compilation of essays on the different dimensions of contagion effects. Boyer, Gibson, and Loretan (1999) and Forbes and Rigobon (2001) argue that the evidence for pure contagion, as opposed to the alternative of fundamentals-based contagion, is very weak. Corsetti, Pericoli, and Sbracia (2002) argue that, under more general assumptions, there is greater evidence of the former type of contagion. Bayoumi and others (2003) find evidence of “positive” contagion related to herding behavior in capital inflows to emerging markets.

40

See, for example, Frankel and Rose (1996), Radelet and Sachs (1998), and Rodrik and Velasco (2000).

41

Some authors have found that the currency composition of external debt also matters. Carlson and Hernandez (2002) note that during the Asian crisis, countries with more yendenominated debt fared significantly worse. These authors attribute this to the misalignment between the countries’ de facto currency pegs and the denomination of their debt.

43

Krueger and Yoo (2002) discuss the interactions of crony capitalism and capital account liberalization in setting the stage for the currency-financial crisis in the Republic of Korea. See also Mody (2002).

44

Of course, foreign direct investment could have its own problems, which one might discover in the future. Moreover, the distinction between FDI and other types of capital flows is not always straightforward (Hausmann and Fernandez-Arias, 2000).

45

The term corruption should be regarded here as a shorthand for weak public sector governance. Existing empirical measures of different dimensions of public sector governance tend to be highly correlated with each other, making it difficult to identify their individual effects.

46

Of the 45 host countries studied in Wei (2000a), corruption is rated by Business International in a range from 1 to 10. The average rating is 3.7, and the standard deviation is 2.5. The (highest marginal) corporate tax rate in the sample ranges between 10 percent and 59 percent, with a mean of 34 percent and a standard deviation of 11 percent.

47

It is noteworthy that institutional investors, including such bellwethers as the California Public Employees’ Retirement System (CalPERS) in the United States, are now explicitly linking their investment strategies to measures of good governance.

48

Although African countries have a much lower level of capital per capita than developed economies, they are not capital-scarce countries owing to their low total factor productivity as well as the low levels of efficiency with which they accumulate human and physical capital.

49

The averages are population weighted, and China and India represent more than one-half of the population in the sample.

50

The calculations closely follow the methodology employed in van Wincoop (1994 and 1999).

51

Although the actual welfare estimates depend on the parameterization of the model, the general flavor of these results is unaffected by the choice of parameter values.

52

Whereas the literature based upon consumption/output series employs general-equilibrium models with utility depending on the level of consumption, the literature based upon equity returns generally uses partial-equilibrium models with utility directly depending upon wealth. The approach using equity-returns data involves devising an optimum portfolio composed of domestic and foreign stocks that minimizes variance and maximizes returns.

53

Some studies also consider the welfare implications of imperfect risk-sharing arrangements involving transactions with risk-free bonds (see Kim and Kim, 2003; and Kim, Kim, and Levin, 2003).

54

It is assumed that all consumption goods are tradable. It is possible to consider a utility formulation with separable tradable and nontradable consumption goods. Sharing of risk associated with the fluctuations in nontradables consumption is not possible, however, and our dataset does not allow us to make a distinction between tradable and nontradable consumption.

55

Since these approximate calculations ignore the pricing problem of international claims, they do not include the welfare changes associated with the pricing of countries’ endowment streams. In countries with highly volatile consumption fluctuations, the welfare losses from price changes can be quite large. As the volatility of consumption increases, however, the welfare gain from risk sharing rapidly rises and outweighs the losses owing to the pricing of consumption streams. Van Wincoop (1994) provides an extensive discussion of the gains associated with these price changes using the data for the OECD countries.

56

Calculations of the gains from international risk sharing based upon stock returns produce much larger welfare gains estimates than those based upon international consumption data. Lewis (1999) examines this issue and finds that the major differences are due to the much higher volatility of stock returns and the implied intertemporal substitution in marginal utility. She reports that the gains from international risk sharing based upon stock returns are quite large—between 10 and 50 percent. LeBaron (2002) claims that these gains have gotten smaller during the past 15 years.

57

The following are excluded from the analysis: small countries (those with populations below one million), transition economies, some oil producers, and other countries with incomplete or clearly unreliable data.

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206. The Dominican Republic: Stabilization, Structural Reform, and Economic Growth, by Alessandro Giustiniani, Werner C. Keller, and Randa E. Sab. 2001.

205. Stabilization and Savings Funds for Nonrenewable Resources, by Jeffrey Davis, Rolando Ossowski, James Daniel, and Steven Barnett. 2001.

204. Monetary Union in West Africa (ECOWAS): Is It Desirable and How Could It Be Achieved? by Paul Masson and Catherine Pattillo. 2001.

203. Modern Banking and OTC Derivatives Markets: The Transformation of Global Finance and Its Implications for Systemic Risk, by Garry J. Schinasi, R. Sean Craig, Burkhard Drees, and Charles Kramer. 2000.

202. Adopting Inflation Targeting: Practical Issues for Emerging Market Countries, by Andrea Schaechter, Mark R. Stone, and Mark Zelmer. 2000.

201. Developments and Challenges in the Caribbean Region, by Samuel Itam, Simon Cueva, Erik Lundback, Janet Stotsky, and Stephen Tokarick. 2000.

200. Pension Reform in the Baltics: Issues and Prospects, by Jerald Schiff, Niko Hobdari, Axel Schimmelpfennig, and Roman Zytek. 2000.

199. Ghana: Economic Development in a Democratic Environment, by Sergio Pereira Leite, Anthony Pellechio, Luisa Zanforlin, Girma Begashaw, Stefania Fabrizio, and Joachim Harnack. 2000.

198. Setting Up Treasuries in the Baltics, Russia, and Other Countries of the Former Soviet Union: An Assessment of IMF Technical Assistance, by Barry H. Potter and Jack Diamond. 2000.

197. Deposit Insurance: Actual and Good Practices, by Gillian G.H. Garcia. 2000.

196. Trade and Trade Policies in Eastern and Southern Africa, by a staff team led by Arvind Subramanian, with Enrique Gelbard, Richard Harmsen, Katrin Elborgh-Woytek, and Piroska Nagy. 2000.

195. The Eastern Caribbean Currency Union: Institutions, Performance, and Policy Issues, by Frits van Beek, José Roberto Rosales, Mayra Zermeno, Ruby Randall, and Jorge Shepherd. 2000.

194. Fiscal and Macroeconomic Impact of Privatization, by Jeffrey Davis, Rolando Ossowski, Thomas Richardson, and Steven Barnett. 2000.

193. Exchange Rate Regimes in an Increasingly Integrated World Economy, by Michael Mussa, Paul Masson, Alexander Swoboda, Esteban Jadresic, Paolo Mauro, and Andy Berg. 2000.

192. Macroprudential Indicators of Financial System Soundness, by a staff team led by Owen Evans, Alfredo M. Leone, Mahinder Gill, and Paul Hilbers. 2000.

191. Social Issues in IMF-Supported Programs, by Sanjeev Gupta, Louis Dicks-Mireaux, Ritha Khemani, Calvin McDonald, and Marijn Verhoeven. 2000.

190. Capital Controls: Country Experiences with Their Use and Liberalization, by Akira Ariyoshi, Karl Habermeier, Bernard Laurens, Inci Ötker-Robe, Jorge Iván Canales Kriljenko, and Andrei Kirilenko. 2000.

189. Current Account and External Sustainability in the Baltics, Russia, and Other Countries of the Former Soviet Union, by Donal McGettigan. 2000.

188. Financial Sector Crisis and Restructuring: Lessons from Asia, by Carl-Johan Lindgren, Tomás J.T. Baliño, Charles Enoch, Anne-Marie Guide, Marc Quintyn, and Leslie Teo. 1999.

187. Philippines: Toward Sustainable and Rapid Growth, Recent Developments and the Agenda Ahead, by Markus Rodlauer, Prakash Loungani, Vivek Arora, Charalambos Christofides, Enrique G. De la Piedra, Piyabha Kongsamut, Kristina Kostial, Victoria Summers, and Athanasios Vamvakidis. 2000.

186. Anticipating Balance of Payments Crises: The Role of Early Warning Systems, by Andrew Berg, Eduardo Borensztein, Gian Maria Milesi-Ferretti, and Catherine Pattillo. 1999.

185. Oman Beyond the Oil Horizon: Policies Toward Sustainable Growth, edited by Ahsan Mansur and Volker Treichel. 1999.

184. Growth Experience in Transition Countries, 1990-98, by Oleh Havrylyshyn, Thomas Wolf, Julian Berengaut, Marta Castello-Branco, Ron van Rooden, and Valerie Mercer-Blackman. 1999.

183. Economic Reforms in Kazakhstan, Kyrgyz Republic, Tajikistan, Turkmenistan, and Uzbekistan, by Emine Giirgen, Harry Snoek, Jon Craig, Jimmy McHugh, Ivailo Izvorski, and Ron van Rooden. 1999.

182. Tax Reform in the Baltics, Russia, and Other Countries of the Former Soviet Union, by a staff team led by Liam Ebrill and Oleh Havrylyshyn. 1999.

181. The Netherlands: Transforming a Market Economy, by C. Maxwell Watson, Bas B. Bakker, Jan Kees Martijn, and Ioannis Halikias. 1999.

180. Revenue Implications of Trade Liberalization, by Liam Ebrill, Janet Stotsky, and Reint Gropp. 1999.

179. Disinflation in Transition, 1993-97, by Carlo Cottarelli and Peter Doyle. 1999.

178. IMF-Supported Programs in Indonesia, Korea, and Thailand: A Preliminary Assessment, by Timothy Lane, Atish Ghosh, Javier Hamann, Steven Phillips, Marianne Schulze-Ghattas, and Tsidi Tsikata. 1999.

177. Perspectives on Regional Unemployment in Europe, by Paolo Mauro, Eswar Prasad, and Antonio Spilimbergo. 1999.

176. Back to the Future: Postwar Reconstruction and Stabilization in Lebanon, edited by Sena Eken and Thomas Helbling. 1999.

175. Macroeconomic Developments in the Baltics, Russia, and Other Countries of the Former Soviet Union, 1992-97, by Luis M. Valdivieso. 1998.

174. Impact of EMU on Selected Non-European Union Countries, by R. Feldman, K. Nashashibi, R. Nord, P. Allum, D. Desruelle, K. Enders, R. Kahn, and H. Temprano-Arroyo. 1998.

173. The Baltic Countries: From Economic Stabilization to EU Accession, by Julian Berengaut, Augusto Lopez-Claros, Françoise Le Gall, Dennis Jones, Richard Stern, Ann-Margret Westin, Effie Psalida, and Pietro Garibaldi. 1998.

172. Capital Account Liberalization: Theoretical and Practical Aspects, by a staff team led by Barry Eichengreen and Michael Mussa, with Giovanni Dell’ Ariccia, Enrica Detragiache, Gian Maria Milesi-Ferretti, and Andrew Tweedie. 1998.

Note: For information on the titles and availability of Occasional Papers not listed, please consult the IMF’s Publications Catalog or contact IMF Publication Services.

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  • Figure A3.1.

    Potential Welfare Gains from International Risk Sharing

    (Percent of consumption)

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