Information about Asia and the Pacific Asia y el Pacífico

Chapter 10: Determinants of Capital Flows

Luis Breuer, Jaime Guajardo, and Tidiane Kinda
Published Date:
August 2018
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Yinqiu Lu


Both the volume and the composition of capital inflows to Indonesia have evolved since the global financial crisis.1 The increased volume of capital inflows has helped finance Indonesia’s current account and fiscal deficits, especially since late 2011 when the commodity supercycle ended. Foreign direct investment (FDI) and portfolio inflows have dominated capital inflows to Indonesia. Government bonds, especially those denominated in rupiah, have increasingly attracted foreign investors, and foreign interest has been influenced by global market sentiment, as attested to by several reversals of portfolio inflows.

Indonesia’s external liabilities and debt positions have evolved along with the dynamics of capital inflows. The increase in capital inflows has led to an increase in external liabilities, albeit from a low level. Consistent with the composition of capital inflows, increases in FDI and portfolio liabilities have been the main drivers of the overall increase in foreign liabilities. Regarding currency composition, the share of external debt denominated in rupiah has increased, as foreign holdings of local currency (LCY) government bonds increased almost eightfold from the end of 2009 to the end of 2017, a phenomenon experienced by many emerging market economies.

Empirical analysis indicates that both push and pull factors influence capital inflows to Indonesia. For example, growth and interest rate differentials between Indonesia and the United States seem to account for an important portion of capital inflows. As expected, global risk sentiment is also important. In addition, an expectation that the rupiah will appreciate is associated with more foreign purchases of local currency government bonds.

The rest of the chapter is structured as follows: First, the developments of capital inflows to Indonesia is examined, followed by a discussion of the developments of foreign liabilities and external debt. The drivers for capital inflows to Indonesia are then reviewed, and a conclusion is provided.

Capital Inflow Developments

Capital inflows to Indonesia have increased since the global financial crisis. Their average volume increased from 3.2 percent of GDP in 2005–09 to 4.2 percent of GDP in 2010–2017. From a global perspective, driven by the liquidity released from systemic economies’ unconventional monetary policies, a global search for yield has led to large capital inflows, especially portfolio inflows, to emerging market and developing economies (Sahay and others 2014). Indonesia was not an exception. Although many emerging market and developing economies experienced stable capital inflows during 2013-14 (Figure 10.1, panel 1), capital inflows to Indonesia increased and reached a peak in late 2014, then started to decline but remained at relatively high levels in 2015–17 (Figure 10.1, panel 2).

Figure 10.1.
Capital Inflows

The increase in capital inflows has helped finance Indonesia’s current account and fiscal deficits (Figure 10.2). After the commodity supercycle fizzled in 2011, Indonesia’s current account turned to deficit in 2012 and has remained so since, in parallel with a widening fiscal deficit. Against this backdrop, increasing capital inflows enabled Indonesia to finance a current account deficit and issue additional government securities to meet budgetary needs.

FDI and portfolio inflows dominated capital inflows to Indonesia. They accounted for 51 percent and 43 percent of total cumulative inflows in 2010–17, respectively, and these ratios have remained broadly stable. Other investment inflows became positive (in four-quarter rolling terms) beginning in early 2008, largely because of a pickup in cross-border bank lending to the private sector. However, the recent external deleveraging of the private sector has led to a reversal of other investment inflows (Figure 10.1, panel 2).

Figure 10.2.
Indonesia: Capital Inflows and Current Account Balance

(Percent ofGDP)

Sources: Haver Analytics; and IMF staff estimates.

Note: FDI = foreign direct investment. The decline in FDI inflows in late 2016 was largely due to the tax-amnesty-motivated liquidation of a special-purpose vehicle’s stake.

Similar to other emerging markets, portfolio inflows to Indonesia were influenced by global market sentiment. Because of Indonesia’s close integration with global capital markets, portfolio inflows have followed a clear risk-on and risk-off pattern (Figure 10.3). Because portfolio inflows resumed after the global financial crisis, their main reversals corresponded to changes in global sentiment—the euro area sovereign debt crisis in late 2011, the emerging market volatility transmitted from the reform of China’s exchange rate policy in the second half of 2015 (renminbi reform), and the US elections in late 2016. Portfolio inflows also declined sharply during the 2013 taper tantrum.

Figure 10.3.
Indonesia: Portfolio Inflows

(Billions of US dollars)

Sources: Haver Analytics.

Government bonds have been the most popular financial instruments for foreign investors (Figure 10.4). Inflows to government bonds accounted for 85 percent of total cumulative portfolio inflows and averaged 1.5 percent of GDP from 2010 to 2017. Global fixed-income investors are attracted by Indonesia’s high government bond yields, relatively high economic growth, and the statutory fiscal deficit limit of 3 percent of GDP, which caps gross fiscal financing requirements. Corporate bonds are the second most popular instrument; however, foreign purchases of corporate bonds have declined since late 2015, following a similar trend in cross-border bank lending. Inflows to central bank bills were influenced by Bank Indonesia’s imposition of a minimum holding period. After Bank Indonesia extended the minimum holding period for central bank bills to six months in May 2011 from one month (imposed in July 2010), foreign investors sold off central bank bills.2 Inflows to equity, relatively small in volume, had been volatile.

Figure 10.4.
Indonesia: Main Components of Portfolio Inflows

(Rolling four-quarter sum, percent of GDP)

Sources: Haver Analytics; and IMF staff estimates.

LCY government bonds have attracted more inflows than those denominated in hard currency. It is estimated that close to 70 percent of the inflows to government bonds went to rupiah-denominated government bonds from 2010 to 2017. Despite some episodes of outflows—such as during the euro area sovereign debt crisis, the taper tantrum, the 2015 renminbi reform, and the 2016 US elections—total cumulative inflows reached US$62 billion during this period, a major source for financing the budget deficit (Figure 10.5).

Figure 10.5.
Inflows to Local Currency Government Bond

(Billions of US dollars)

Sources: CEIC Data Co. Ltd.; Bloomberg L.P.; and IMF staff estimates.

Inflows to LCY government bonds were strong from the beginning of 2016 through the end of 2017, despite some volatility related to the US election. They reached close to US$20 billion in January 2016–December 2017, reflecting a favorable global financial environment, attractive bond yields, and some speculative inflows related to the tax amnesty program. The inflation-adjusted yield of Indonesia LCY government bonds seems comparable to that of other countries (Figure 10.6), and total annual returns on bonds—a combination of high yields and positive valuation (inversely related to the bond yields)—reached 16 percent in US dollar terms at the end of 2017 (Figure 10.7). The returns from exchange rate movements have been volatile and have often been correlated with the return from valuation, attesting to the role of foreign investors in influencing bond yields. For example, returns declined as inflows reversed in October 2016 when foreign investors likely took profits, and the reversal accelerated after the US election. It is estimated that the amount of capital reversal from LCY government bonds reached US$2.2 billion in October 1–November 30, 2016, with the yield on 10year bonds up by 100 basis points. Since then, capital inflows have gradually resumed, accompanied by a decline in bond yields.

Figure 10.6.
Government Bond Real Yield and Credit Rating

(Percent per year, 10-year real yield)

Sources: Bloomberg L.P.; IMF, Information Notice System, and IMF staff estimates.

Note: Real yield is defined as nominal bond yield minus inflation rate. Credit rating represents the average of ratings from S&P, Fitch, and Moody’s for each country. Data are as of October 2017 or latest available.

Figure 10.7.
J.P. Morgan Government Bond Index-EM Global Diversified, 12-Month Return


Sources: Bloomberg L.P.; and IMF staff estimates. Note: EM = emerging market.

The correlations among key types of capital inflows seem to be low based on quarterly balance of payments data (Table 10.1). Low positive correlations point to a small likelihood that foreign investors are engaging in herding behavior during shocks; low negative correlations mean less chance for one type of inflows to compensate for a decline in another type of inflows. The correlation of −1 between FDI debt inflows and debt outflows reflects recurrent short-term intracompany trade credit, which would be recorded as debt inflows and debt outflows in the same quarter. The correlation between FDI and private sector bond inflows is relatively high, probably because they are likely driven by the same underlying factors, such as the outlook for economic activity or commodity prices. The correlation between public bond inflows and public other investment inflows was almost zero, pointing to limited substitution between these two types of government borrowing.

TABLE 10.1.Correlation Coefficients for Items in the Financial Account(2010:Q1–2017:Q4)
FDIDebtDebtBondBond OIOI
FDIEquityInflowsOutflowsPortfolio EquityBond(private)(public) OI (private)(public)
FDI equity
FDI debt inflows0.3
FDI debt outflows−0.3−1.0
Private sector0.30.20.2−0.20.2
Public sector0.−0.1
Other Investment0.10.20.1−0.2−0.2 - 0.1−0.2−0.1−0.2
Private sector0.20.30.3−0.3−0.1 - 0.1−0.20.2−0.2
Public sector−0.10.0−0.20.1−0.1 -0.1−0.1−0.30.0 0.0
Sources: Haver Analytics; and IMF staff estimates.Note: FDI = foreign direct investment; OI = other investment.
Sources: Haver Analytics; and IMF staff estimates.Note: FDI = foreign direct investment; OI = other investment.

However, high-frequency data point to a high correlation between equity and LCY government bond inflows, especially during the early stages of shock episodes. During the taper tantrum and 2015 renminbi reform, both equity and bond inflows to Indonesia declined or reversed, as foreign investors reduced their exposures to emerging markets (Figure 10.8).

Figure 10.8.
Equity and Local Currency Government Bond Inflows

(Billions of US dollars, cummulative since January 1, 2013)

Developments in Foreign Liabilities and External Debt

Capital inflows to Indonesia since the global financial crisis led to an increase in external liabilities, albeit from a low level (Figure 10.9). Indonesia’s foreign liabilities rose from 55 percent of GDP at the end of 2009 to 68 percent of GDP at the end of 2016. Consistent with the dynamics of capital inflows, increases in FDI and portfolio liabilities were the main drivers of the overall increase in foreign liabilities, and their total share in foreign liabilities increased by 12½ percentage points over 2010–16 to 77 percent at the end of 2016.

Figure 10.9.
Foreign Liabilities, by Type

(Percent of GDP)

Sources: Haver Analytics; and IMF staff estimates.

The investor base for Indonesia has shifted toward investors from Europe and the United States (Figure 10.10). Within a larger pie of portfolio claims, investors from the United States and from European financial centers (such as Ireland, Luxembourg, the Netherlands, and the United Kingdom) have seen their shares increase. This increase was observed in both portfolio equity and debt claims for investors from the United States and in debt claims for those from the European financial centers, as global investors were diversifying their portfolio investment into emerging markets. Accordingly, the share of Singaporean portfolio investors has declined. Nevertheless, Singapore investors still accounted for half of total short-term portfolio debt claims.

Figure 10.10.
Indonesia: Portfolio Claims

Sources: IMF, Coordinated Portfolio Investment Survey, and IMF staff estimates.

Despite a recent increase, Indonesia’s external debt remains low. In contrast with the definition of external liabilities, external debt excludes equity FDI and equity portfolio investment. The external-debt-to-GDP ratio increased from 30 percent at the end of 2009 to 34¾ percent at the end of 2017. The share of public debt decreased from 57½ percent to 51¼ percent over the same period, because about 60 percent of the increase in external debt was due to private sector borrowing. Within the private sector, external debt of the nonbank sector stood at 14 percent of GDP, of which 20 percent was borrowed by state-owned enterprises.

Parent and affiliated company debt constitutes a large share of private debt (Figure 10.11). At the end of 2017, one-third of private sector external debt was from either parent or affiliated companies (US$52 billion, 5 percent of GDP), with debt from parent companies accounting for 82½ percent of such debt. The share of intracompany loans in external debt was highest among nonfinancial corporations (about two-thirds). Some of these loans are disguised borrowing through Eurobond issuance, given that the receipts wired back to Indonesia from Eurobonds issued by the special-purpose vehicles set up by domestic companies are registered as intracompany loans in the balance of payments.

Figure 10.11.
Private Sector External Debt

(Billions of US dollars, end of September 2017)

Sources: Bank Indonesia; and IMF staff estimates.

An increasing share of external debt is denominated in rupiah. About 20 percent of Indonesia’s external debt was denominated in rupiah at the end of 2017, up from 10 percent at the end of 2009. This increase in share, in line with developments in portfolio inflows, reflected an increasing share of foreign holdings of LCY government bonds—a close to eightfold increase in the nominal value of foreign holdings and a doubling of the foreign share from year-end 2009 to year-end 2017, following a similar trend in other emerging markets (Figure 10.12, panel 1). As a result, the share of rupiah-denominated government debt almost tripled from 12½ percent at year-end 2009 to 34¾ percent at year-end 2017. Foreign ownership as a share of foreign reserves is relatively high compared with peers (Figure 10.12, panel 2).

Figure 10.12.
Foreign Investment Involvement

Foreign holders of LCY government bonds are diverse. About 36 percent of LCY government bonds were held by central banks, foreign governments, and mutual funds at the end of September 2017 (Figure 10.12, panel 3). Central banks and foreign governments found LCY government bonds attractive after the taper tantrum because they provide diversification of investment while reducing the cost of carry of foreign currency reserve holdings (Standard Chartered 2013). Another 42 percent of bonds were held by financial institutions. A relatively high share of foreign investors are benchmark-driven emerging market funds (Figure 10.12, panel 4).

In addition to purchasing and holding LCY government bonds, foreigners also use derivatives to gain similar exposure. Total return swaps (TRSs) and credit-linked notes (CLNs) backed by LCY government bonds are two popular instruments that are normally contracted between global investment banks and foreign investors, who get cash flows from the underlying bonds without holding the cash bonds. When local subsidiaries of global investment banks sell TRSs and CLNs to foreign investors, the total foreign exposure to LCY bonds could be larger than officially reported foreign holdings because local subsidiaries are considered residents. Despite declining from its 2010 peak, the volume of annual CLN issuance averaged US$1.1 billion in 2011–16, roughly 17 percent of the increase in foreign holding of cash bonds (Figure 10.13).3

Figure 10.13.
Change of Foreign Holdings of Local Currency versus Credit-Linked Note Issuance

(Billions of US dollars)

Sources: Bloomberg L.P.; Haver Analytics; J.P. Morgan; and IMF staff estimates.

Drivers of Capital Inflows to Indonesia

There is a rich literature on the drivers of capital flows. The typical analysis adopts the “push versus pull” framework (for example, Fratzscher 2011; Cerutti, Claessens, and Puy 2015). Push factors refer to external supply factors, such as the supply of global liquidity and global risk aversion. Pull factors refer to domestic demand-side factors that attract capital inflows, such as macroeconomic fundamentals, the institutional framework, and policies.4 The IMF devoted a chapter in the World Economic Outlook (IMF 2016b) that explores the drivers of the recent slowdown in net capital flows to emerging market economies; it finds that much of the decline in inflows can be explained by the narrowing growth differentials between emerging market and advanced economies. IMF (2016a) points out that both push and pull factors remain important for capital flows, suggesting that source and recipient country policies play a role. Other recent work on capital flows includes Ghosh and others (2012); Chung and others (2014); Nier, Sedik, and Mondino (2014); and Sahay and others (2014).

Panel Analysis

This examination of the drivers of capital inflows to Indonesia is based on a panel analysis of 34 countries5 with country fixed effects (Hannan 2017) (Table 10.2). The time period is 2009–15 and quarterly data are used to capture the drivers of capital flows after the global financial crisis. Coefficients from the panel analysis are applied to Indonesia-specific factors and global factors to derive the portion of capital inflows that can be explained by each factor.

TABLE 10.2.Capital Inflows(Share of GDP, 2009:Q3–2015:Q4)
VariableTotalPrivateForeign Direct InvestmentPortfolioPortfolio DebtPortfolio EquityOther
Growth differential0.21*0.32**0.070.06*0.07*0.010.07
Interest rate0.31*-*
Trade openness-*− 0.03− 0.03**− 0.01*− 0.02
Reserves0.06**0.07**0.03*0.04**0.04**0.00**− 0.00
Exchange rate0.26− 0.24− 0.03− 0.29− 0.27− 0.090.61
Institutional quality−8.85***− 6.90*− 2.41− 1.79− 1.58− 0.30− 4.69*
Income per capita0.00**0.00***0.00*− 0.000.00− 0.000.00**
Capital account−2.17− 1.95−1.350.381.54− 0.14− 1.34
Financial−19.12− 27.60− 10.311.306.91−2.55− 6.89
Global risk aversion− 0.56− 3.021.96**− 2.41**−1.94**− 0.350.08
Commodity prices− 0.04− 0.00− 0.02**0.010.01− 0.00− 0.03
Global liquidity0.100.070.08*0.080.06− 0.00− 0.06
Us corporate spread0.040.95− 0.940.850.260.260.08
Us yield gap2.070.85− 0.32− 0.15− 0.520.242.22
Constant− 4.525.10− 4.785.321.801.43*− 6.87
Number of809809809809758739787
Number of groups34343434333334
Country fixed effectsYesYesYesYesYesYesYes
Source: Hannan 2017.Note: Standard errors are in parentheses. *p < .1; **p < .05; ***p < .01.
Source: Hannan 2017.Note: Standard errors are in parentheses. *p < .1; **p < .05; ***p < .01.

The analysis shows that cyclical factors are significant for capital inflows to Indonesia (Figure 14.14). Growth and interest rate differentials between Indonesia and the United States seem to account for an important portion of capital inflows.

Figure 10.14.
Drivers of Capital Inflows

(Percent of GDP)

Sources: CEIC Data Co. Ltd., Haver Analytics; and IMF staff estimates.

Global risk aversion is also important. More global risk aversion leads to low inflows, in particular for some components such as portfolio debt. However, the estimation does not seem to be able to capture the large fluctuations in capital inflows. For example, the reversal related to the taper tantrum, which is likely partly due to large temporary shifts in market expectations regarding the course of monetary policy in the United States, is difficult to control for in a regression using quarterly data (IMF 2016b).


The availability of daily data on capital inflows allows us to analyze the impact of high-frequency market sentiment on capital inflows to Indonesia. A generalized autoregressive conditional heteroscedasticity (GARCH) model is used to analyze the main drivers of capital inflows to LCY government bonds, one of the key types of capital inflows to Indonesia. The GARCH framework, a standard tool for modeling volatility in financial economics, allows the impact of regressors on the mean and volatility of the dependent variable to be estimated. The sample data consist of daily observations covering the period January 1, 2010, to November 30, 2017.

The empirical model of the capital inflows to Indonesia is as follows:


Equation (7.1) is the mean equation, in which ct represents he capital inflows to LCY government bonds, ϕi is the autoregressive term incorporating the persistence of the capital inflows, βmXtm reflects the impact of exogenous factors on capital inflows, and εt is the error term. In equation (7.2)—the conditional variance equation—σt is the standard deviation, γj is the GARCH term, and αi is the ARCH effects.’

Variables most relevant for foreign investors’ returns are chosen as the explanatory variables. The first is the expected movement of the rupiah against the US dollar. The change in the threemonth nondeliverable forwards (NDF) rate is used to represent this expectation.6 The hypothesis is that a more appreciated forward exchange rate would persuade foreign investors to purchase more bonds. The second is the difference between the five-year government bond yield and the time deposit rate. While this is a driver mostly for local investors (mainly banks), it could also indirectly influence foreigner investors, given that a larger difference would support the positive price dynamics from local investors. The third is the Chicago Board Options Exchange Volatility Index (VIX) indicator, which could capture the impact of global financial conditions and hence the perceived risks of exposure to Indonesian risk.7 Higher market volatility should dent foreign interest in LCY bonds. To reduce the endogeneity of capital inflows, lags of the explanatory variables are used with the lags in both the mean and variance equations chosen based on their significance. A dummy for the bond auction dates has been introduced into the model to control for inflows related to auctions; however, it does not turn out to be statistically significant.

The estimation results confirm the main hypothesis (Table 10.3). An expectation that the rupiah will appreciate is associated with more foreign purchases of bonds; a wider spread of the bond yield over the time deposit rate would encourage more foreign participation; and an increase in global risk aversion is associated with a decline in foreigner investors’ exposure to Indonesian risk. Foreign capital inflows have strong persistence given that inflows usually generate positive, though diminishing, momentum in the next two days.

TABLE 10.3.Estimated GARCH Parameters
CoefficientStandard Errorz-Statisticp-value
Mean equation
Variance equation
Adjusted R20.14
Sources: Bloomberg L.P.; MoF; and IMF staff estimates.
Sources: Bloomberg L.P.; MoF; and IMF staff estimates.


Capital inflows have benefited Indonesia, allowing the country to finance current account and fiscal deficits. At one-half of total capital inflows to Indonesia, FDI flows have acted as a long-term stable source of capital as well as a source of new technology and management practices. Portfolio inflows—in particular, inflows to LCY government bonds—have enabled the government to borrow externally in domestic currency at a reasonable rate. Other investment flows complemented the domestic banking system in supplying the private sector with credit for trade or longer-term investment.

In the meantime, capital inflows have also transmitted global risks to Indonesia. Capital inflows tend to come in waves and could transmit global shocks to domestic financial markets. Since the global financial crisis, Indonesia has witnessed several episodes of reversal or sharp declines of capital inflows. During these episodes, not only bond markets but also equity and foreign exchange markets came under pressure.

Empirical analysis indicates that several factors are influencing capital inflows to Indonesia. For example, growth and interest rate differentials between Indonesia and the United States are positively associated with capital inflows. As expected, an increase in global risk aversion deters foreign purchase. In addition, an expectation of the appreciation of the rupiah is associated with more foreign purchases of LCY government bonds.

As noted in Chapter 2 (“Twenty Years after the Asian Financial Crisis”), Indonesia’s resilience to external shocks has strengthened. However, given the volatile nature of capital inflows, more could be done to further enhance resilience. Structural reforms to attract more FDI inflows would be welcome given that they are less volatile compared with other types of capital inflows. The recently partially liberalized FDI regime is a welcome step in the right direction. More domestic savings, including public sector saving, would help reduce reliance on foreign capital. This would require strengthening revenue collection in the post—commodity boom era. In addition, a deep domestic capital market would help accommodate the surges and sudden stops in capital inflows caused by the narrow investor base and low market liquidity that make the government bond market susceptible to heightened market volatility.


    CeruttiEugenioStijnClaessens andDamienPuy. 2015. “Push Factors and Capital Flows to Emerging Markets: Why Knowing Your Lender Matters More Than Fundamentals.” IMF Working Paper 15/127International Monetary FundWashington, DC.

    ChungKyuilJong-Eun LeeElenaLoukoianovaHail Park andHyunSong Shin. 2014. “Global Liquidity through the Lens of Monetary Aggregates.” Economic Policy30 (82): 23190.

    FratzscherMarcel. 2011. “Capital Flows, Push versus Pull Factors and the Global Financial Crisis.” ECB Working Paper 1364European Central BankFrankfurt.

    GhoshAtish R.JunKimMahvashS. Qureshi andJuanZalduendo. 2012. “Surges.” IMF Working Paper 12/22International Monetary FundWashington, DC.

    HannanSwarnali Ahmed. 2017. “The Drivers of Recent Capital Flows in Emerging Markets.” IMF Working Paper 17/52International Monetary FundWashington, DC.

    International Monetary Fund (IMF). 2016a. “Capital Flows—Review of Experience with the Institutional View.” IMF Policy Paper Washington DC.

    International Monetary Fund (IMF). 2016b. “Understanding the Slowdown in Capital Flows to Emerging Markets.” In World Economic Outlook: Too Slow for Too Long. Washington, DC.

    NierErlendTahsinSaadi Sedik andTomasMondino. 2014. “Gross Private Capital Flows to Emerging Markets: Can the Global Financial Cycle Be Tamed?IMF Working Paper 14/196International Monetary FundWashington, DC.

    SahayRatnaVivekAroraThanosArvanitisHamidFaruqeePapaN’DiayeTommasoMancini-Griffoli and an IMF Team. 2014. “Emerging Market Volatility: Lessons from the Taper Tantrum.” IMF Staff Discussion Note 14/09International Monetary FundWashington, DC.

    Standard Chartered Bank. 2013. “Local Markets Compendium 2013.” London, United Kingdom.

The author thank Viacheslav Ilin and Agnes Isnawangsih for excellent research assistance.

Capital inflows are defined as net acquisition of domestic assets by nonresidents.

The minimum holding period was reduced to one month in September 2013 and to one week in September 2015.

Information about the volume of TRSs is difficult to gather. There is no information about the volume of CLNs that have been issued by local subsidiaries of global investment banks.

For more details on the factors and policies in Indonesia that would boost growth and attract more capital, see Chapter 3, “Boosting Potential Growth.”

Albania, Brazil, Bulgaria, Chile, China, Colombia, Costa Rica, Croatia, Ecuador, Egypt, El Salvador, FYR Macedonia, Guatemala, Hungary, India, Indonesia, Jordan, Kazakhstan, Latvia, Lithuania, Malaysia, Mexico, Paraguay, Peru, Philippines, Poland, Russia, Saudi Arabia, South Africa, Sri Lanka, Thailand, Turkey, Ukraine, Uruguay.

Onshore forward exchange rates have been tried as well, but they have weaker forecast power despite the correlation coefficient having the expected sign.

The five-year credit default swap of Indonesia has been tried as well, but because the credit default swap and VIX are highly correlated, the one with more predictive power is chosen, which is the VIX.

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