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Chapter 8. Riding Global Waves: The Impact of External Financial Shocks on Emerging Market Economies

Author(s):
Dora Iakova, Luis Cubeddu, Gustavo Adler, and Sebastian Sosa
Published Date:
December 2014
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Author(s)
Gustavo Adler and Camilo E. Tovar A previous version of this work was published under the title “Global Financial Shocks and their Economic Impact on Emerging Market Economies” in the Journal of International Commerce, Economics and Policy, Vol. 4, No. 2.

Several years have passed since the bankruptcy of Lehman Brothers marked the beginning of a global storm that put many advanced economies on the verge of a financial meltdown. Financial risks have receded somewhat since then, but they continue to loom over the world economy, raising questions about the potential impact of global financial shocks on emerging market economies (EMEs).

It is unclear whether these economies are more or less vulnerable to external financial shocks than in the past. Over the past two decades, most EMEs witnessed significant changes in two critical dimensions that are likely to determine the impact of these global shocks on their domestic economies. On the one hand, most went through a marked process of financial integration with the rest of the world, arguably making them more sensitive to global financial conditions.1 On the other, they made marked improvements in key macroeconomic fundamentals, thus becoming more resilient to such shocks.

This chapter studies the impact of global financial shocks on the domestic output of EMEs, with a focus on the role that financial integration and macroeconomic fundamentals play in mitigating or amplifying such an effect. Specifically, the chapter: (1) focuses on the pure effect of external financial shocks by isolating the impact of these events from any contemporaneous trade shocks; and (2) examines how the degree of financial integration and the strength of macroeconomic fundamentals interact with these external disturbances, either to amplify or mitigate their impact on the economy. For this purpose, the chapter assesses the impact of large external financial shocks using a cross-sectional econometric approach based on a quarterly database for 40 emerging market and nine small advanced economies over the period from 1990–2010.

This work is related to several branches of literature. First, it relates to the recent literature on decoupling, which has argued that EMEs have become less dependent on (that is, have “decoupled” from) the economic performance of advanced economies (IMF, 2007). While prompted by the remarkable growth performance of EMEs over the past decade despite slow growth in advanced economies, this view seems to have been vindicated during the 2008–09 global crisis, as many EMEs navigated relatively unscathed through what was clearly the most severe global shock in decades. This study adds to this literature by disentangling and quantifying the specific mechanisms that may amplify and mitigate the output cost to global shocks.

The chapter is also related to a growing literature examining the role of sudden changes in uncertainty—as proxied, for example, by spikes in the S&P 500 Chicago Board Options Exchange Market Volatility Index (VIX)—in driving the business cycle (Bloom, 2009). Uncertainty spikes can have sizable effects on real activity by encouraging a “wait and see” attitude that amplifies economic cycles. Indeed, such spikes have been shown to induce a collapse in investment and private consumption. In addition, such effects are more severe in EMEs than in the United States, possibly due to the role that financial frictions (for example, collateral constraints, liquidity shortages, or currency mismatches) tend to play in EMEs (Carrière-Swallow and Céspedes, 2011). This study relates to this literature to the extent that the identified effects of global financial shocks on domestic output in EMEs—that is, spikes in the VIX—may partly arise from heightened uncertainty. Unlike these other papers, however, the aim here is to disentangle the role of macroeconomic fundamentals and financial integration in amplifying or mitigating the impact of these shocks, rather than to assess the specific role that heightened uncertainty may have.

Finally, this chapter relates broadly to several strands of recent literature examining the role of macroeconomic fundamentals in absorbing external shocks, and the real effects of sudden stops and contagion (Calvo, Izquierdo, and Mejia, 2004; Calvo and Talvi, 2008; Ocampo, 2012). Unlike these studies, however, this study pays special attention to the role of financial integration and its evolution over time in determining EMEs’ vulnerability to exogenous global financial shocks.

The analysis provides several key insights. First, large global financial shocks tend to have a sizable impact on EME output, even after controlling for any associated trade shock (for example, the terms of trade or a drop in external demand).

Second, these shocks have nonlinear effects on EMEs’ domestic output, which varies with the degree of financial integration with the rest of the world and the strength of macroeconomic fundamentals. In particular, exchange rate flexibility has a prominent role buffering the impact of these shocks, especially for highly financially integrated economies. The strength of the external position (current account balance and external debt) is also found to play a similar role.

Third, greater financial integration does not always increase an economy’s vulnerability to external financial shocks. As a matter of fact, the exchange rate regime is critical in determining this relationship: financial integration amplifies global financial shocks in economies with fixed exchange rate regimes, but mitigates them in economies with more flexible regimes. The corollary of these results is that financially integrated economies with strong fundamentals (especially exchange rate flexibility) are better equipped to cope with global financial shocks than economies with weak fundamentals and limited financial linkages.

The analysis also allows us to assess how the vulnerability of different economies in the sample to an adverse global financial shock varies across regions and time. In particular, simulations of the estimated model—which combine the joint effect of higher financial integration and changing fundamentals to an adverse global financial shock—show that, while still significantly vulnerable, both Latin America and emerging Asia are less sensitive today to these shocks than in the past. By contrast, emerging Europe is found to be more vulnerable on account of both a steep process of financial integration, and the worsening of fundamentals in some key dimensions over the past 10–15 years.

This chapter first discusses the identification of global financial shocks and the behavior of key global variables during these episodes. It documents the evolution of financial integration and key macroeconomic fundamentals across EMEs since 1990. The chapter then discusses the econometric methodology, presents its main findings, and reports simulation results to illustrate the changing vulnerability of EMEs to global financial shocks. The chapter concludes with a discussion of the key takeaways and avenues for further research.

Recurrent Episodes of Global Financial Stress

The VIX has gained acceptance as a summary indicator of global uncertainty or financial stress.2 According to the VIX—and based on a simple statistical analysis that identifies large deviations of the index from its own trend, as in Bloom (2009)—the world has experienced periods of global financial stress every 2½ years on average over the past two decades (Figure 8.1 and Table 8.1). Whether these shocks originated in advanced economies (for example, 9/11 or Lehman) or emerging market economies (for example, the Asian or Russian crises), their repercussions were global,3 and their effects where arguably transmitted to EMEs and small advanced economies through two main channels, as described below.

Figure 8.1Global Financial Shocks

(Deviations of VIX from its trend)

Sources: Haver Analytics; and authors’ calculations.

Note: Shaded areas correspond to episodes of global financial shocks. An episode is identified if the value exceeds its mean by 1.65 standard deviations (as in Bloom, 2009). Episode window starts and ends when the value crosses the one standard deviation threshold. VIX = Chicago Board Options Exchange Market Volatility Index.

Table 8.1Global Financial Shocks, 1990–2011
Days with VIX above
EpisodeStart1PeakEnd11 SD1.65 SD
Gulf War8/3/908/23/901/17/91167163
Asian Crisis10/27/9710/30/971/9/987416
Russian Crisis8/4/9810/8/9810/28/988563
9/119/7/019/20/0111/5/015931
Enron and Iraq War7/3/028/5/024/7/03278244
Lehman9/15/0811/20/085/27/09254227
Greece5/6/105/20/107/1/105623
Europe8/8/118/8/1111/25/11109109
Sources: Haver Analytics; and authors’ calculations.Note: Episodes identified based on deviations of the VIX index from its Hodrick-Prescott trend (Ravn and Uhlig parameters). An episode is identified if the value of the measure exceeds 1.65 standard deviations (SD). VIX = Chicago Board Options Exchange Market Volatility Index.

On the basis of variable being more than one standard deviation above mean.

Sources: Haver Analytics; and authors’ calculations.Note: Episodes identified based on deviations of the VIX index from its Hodrick-Prescott trend (Ravn and Uhlig parameters). An episode is identified if the value of the measure exceeds 1.65 standard deviations (SD). VIX = Chicago Board Options Exchange Market Volatility Index.

On the basis of variable being more than one standard deviation above mean.

Trade Channel

Excluding those episodes linked to geopolitical tensions in the Middle East—leading to spikes in oil prices—all episodes of global financial shocks were accompanied by sharp falls in commodity prices, possibly reflecting expectations of a slowdown of the world economy and thus of demand for these basic products. Indeed, most episodes also led to softer external demand, as suggested by economic activity indicators of large advanced economies (Figure 8.2, top panels).

Figure 8.2Key Variables during Episodes of Global Financial Shocks

Sources: Haver Analytics; IMF, International Financial Statistics; and authors’ calculations.

Note: Months reported on horizontal axis. t = 0 is the start of the episode as identified in Figure 8.1. Percentiles across episodes are reported.

1 Broad IMF commodity price index, in real terms, adjusted for exchange rate valuation effects (see Adler and Sosa, 2011).

2 Change in cyclical component of industrial production. Weighted average for the United States, Japan, Germany, and France.

3 EMBI = Emerging Market Bond Index. Excludes Gulf War and Asian crisis events, due to lack of data.

4 Flows to emerging market economy (EME) equity and bond mutual funds, in percent of total assets under management. Excludes episodes prior to 2000 due to lack of data.

Financial Channel

At the same time, these episodes were accompanied by sizable re-pricing of sovereign risk—as reflected in the widening of EMBI spreads—and a reversal of capital flows, in some cases very pronounced (Figure 8.2, bottom panels).

Thus, to varying degrees, EMEs are likely to have been affected both through trade and financial channels during these episodes. This chapter focuses on the financial dimension, which may also encompass the effect of spikes on uncertainty as discussed before and its economic impact on EMEs.4

Financial Integration and Economic Fundamentals: Opposing Forces?

It is conjectured here that the impact of global financial shocks on EMEs depends primarily on two main factors (Figure 8.3). On the one hand, an economy’s degree of financial integration with the rest of the world is likely to influence its vulnerability to external financial shocks. While financial integration is a somewhat elusive concept—and has been studied from different angles—one would expect that, all else being equal, a higher degree of integration would increase domestic sensitivity to these shocks.5 To capture this, we focus on the stock of foreign assets and liabilities, relative to GDP, as a measure of financial integration,6 as this indicator is likely to capture both the degree of arbitrage (spillover) between external and domestic financial markets, as well as the potential magnitude of the economic impact of external shocks on the domestic economy.

Figure 8.3Financial Openness

Sources: Updated and extended version of the Lane and Milesi-Ferretti (2007) database; updated version of Chinn-Ito (2008); and authors’ calculations.

Note: LA6 = Brazil, Chile, Colombia, Mexico, Peru, and Uruguay.

1 Foreign assets plus foreign liabilities net of international reserves and official external debt.

2 The index is based on the binary dummy variables that codify the tabulation of restrictions on cross-border financial transactions reported in the IMF’s Annual Report on Exchange Arrangements and Exchange Restrictions (AREAER). Higher values of the index are indicative of a country’s greater degree of capital account openness. Simple averages.

On the other hand, an economy’s strength of economic fundamentals is also likely to buffer or amplify the impact of external shocks. Strong fundamentals can prevent capital outflows in the first place (as investors would be less concerned about creditworthiness) but can also play a role in allowing the economy to adjust more easily to a given shock (for example, by providing more room to undertake countercyclical policies by lowering interest rates, letting the exchange rate depreciate, or using fiscal policy to stabilize domestic demand).

To varying degrees, EMEs across the board have experienced a marked transformation over the past two decades on these two fronts, potentially changing their vulnerability to global shocks. The most prominent transformation has been the increase in financial integration with the rest of the world, mostly resulting from a gradual process of financial liberalization and the withdrawal of restrictions on international capital movements, particular during the 1990s, as shown by the Chinn and Ito index of capital account openness (Figures 8.3 and 8.4). This is visible in Latin America7 and emerging Asia, even more so in emerging Europe, and to an even greater extent in small advanced economies.

Figure 8.4Financial Openness in Emerging Market and Small Advanced Economies

At the same time, many emerging market economies have witnessed a gradual strengthening of their economic fundamentals along a number of dimensions, particularly on the external and fiscal fronts, during the past two decades (Figure 8.5). This has been evident in Latin America and emerging Asia, but less so in emerging Europe.

Figure 8.5Key Macroeconomic Fundamentals in Emerging Market Economies and Small Advanced Economies, 2010 versus 2000

Source: IMF, International Financial Statistics; and authors’ calculations.

Note: LA6 = Brazil, Chile, Colombia, Mexico, Peru, and Uruguay; Other LA = Argentina, Bolivia, Ecuador, Jamaica, Paraguay, and Venezuela.

Since progress along these respective dimensions has opposing and nontrivial implications for the transmission of global financial shocks to EMEs, assessing an economy’s vulnerability to them—and whether that vulnerability has increased or declined over time—requires a multivariate econometric approach that appropriately captures and quantifies the importance of these two opposing forces.

The Impact of Global Financial Shocks

Sample, Data, and Econometric Approach

To quantify the impact of large external financial shocks on domestic output we undertake a cross-sectional econometric approach based on quarterly observations for a sample of 40 EMEs and nine small advanced economies during seven episodes of global financial shocks (measured by sizable spikes in the VIX index, as defined in Figure 8.1). Of the nine episodes identified earlier, those of Enron and the Iraq War are treated as one, given their close proximity. Similarly, the 2011 event associated with the European crisis is dropped due to insufficient observations (only GDP data up to 2011:Q4 were available on a comprehensive basis).8

The econometric analysis has three key features. First, the dependent variable measuring output performance captures both the depth and duration of each individual episode j (Figures 8.6 and 8.7). Specifically, we compute the cumulative change in the cyclical component of output (Yi, j)—estimated using a standard Hodrick-Prescott filter—over the duration of the episode and the following two quarters (as long as there is no overlap with a subsequent event), in order to capture possible lagged effects of the shock:

Figure 8.6Distribution of Output Performance during Global Financial Shocks

(Cumulative deviations from potential output, in percent of annual GDP)

Source: Authors’ calculations.

Note: Countries are ordered from most to least affected, for each episode. Scales are the same across charts, except for the Lehman event. Horizonal line corresponds to the median value.

1 Cumulative deviations from trend output (Hodrick-Prescott filter) in percent of annual GDP.

Figure 8.7Output Performance during Global Financial Shocks, by Country

(Cumulative, in percent of annual GDP)

Source: Authors’ calculations.

Figure shows cumulative change in the cyclical component of GDP, in percent of (potential) GDP. Dotted lines reflect regional medians.

1 Average of different episodes, excluding cases of identified idiosyncratic events: Asian countries (1997), Russia (1998), Brazil (2002), and Uruguay (2001–02).

2 Greece event of May 2010. The European episode of mid-2011 is not included, because comprehensive GDP data were not available at the time of writing.

A glance at the distribution of our output loss measure suggests that performance varied significantly across both episodes and economies, with some economies displaying sizable output losses and others showing positive growth during these events. The 2008–09 event that followed the bankruptcy of Lehman Brothers deserves special attention not only because of the severity of the shock, but also because, despite the wide dispersion of outcomes, all economies experienced notorious output losses.

The second feature of the economic analysis is that we choose a specification that disentangles the link between domestic output performance and global financial shocks (measured by the VIX) after controlling for any associated effect arising through trade channels. In the absence of comprehensive (country-specific) data on terms of trade and external demand, which would allow for measuring such trade shocks more precisely, we rely on a proxy variable that measures the cumulative loss of exports (in percent of trend) during the episode. Resembling the measure of output performance, this variable captures both the depth and duration of the trade shock during each event. A weakness of this measure is that it is not entirely exogenous, and may lead to over-controlling. For this reason, and to check the robustness of the results, regressions are also run using available series of terms of trade and world GDP instead of exports (which proxy for exogenous trade prices and external demand). Results remain qualitatively and quantitatively unchanged.

The third feature of the analysis is that the specification allows for the financial shock to interact with the economy’s degree of financial integration (defined as total foreign assets plus total foreign liabilities in percent of GDP)9 as well as with measures of economic fundamentals. In this manner we are able to study the amplification or mitigation effect of these country features in the face of a global financial shock. Moreover, we allow for interaction effects between country fundamentals and financial integration.

Thus, the benchmark model is:

where i and j denote country and episode respectively; Expi,j is the cumulative change in de-trended exports (in percent of trend); GFSj is the global financial shock, computed as the average monthly VIX times the length of the episode, in months; Xi,j is the vector of country fundamentals, evaluated at the beginning of each episode; and FIi,j denotes financial integration.

Broadly speaking, β2 captures the direct effect of the global financial shock, while β3 and β4 capture the interaction effect of the global shock with financial integration and fundamentals, respectively (that is, the amplification or mitigation effect). Finally, the last term (with coefficient β5) is introduced to capture the fact that the role of fundamentals in the face of a global shock may not be independent of the degree of financial integration. However, it is important to keep in mind that, in quantifying the role of fundamentals and financial integration, one must take the total effect of the shock into account. More precisely, under this specification, the marginal effect of a global financial shock (equivalent to a one-point increase in the VIX) is given by:

And the amplification effect of a fundamental (x), included in X, is given by:

The following country fundamentals are explored:10

  • Exchange rate flexibility, as captured by the de facto exchange rate regime classification of Ilzetzki, Reinhart, and Rogoff (2008). The variable, based on the coarse classification, excludes those regimes classified as freely falling or dual markets with missing parallel market data. It is also normalized to range from 0 to 1, with 1 being a freely floating regime and 0 a peg or similar regime.
  • External sustainability measures, as reflected in the current account balance, external debt, net foreign assets, and international reserves, all in percent of GDP.
  • Fiscal position measures (public debt and primary balance, in percent of GDP).
  • Deposit dollarization, from Levy Yeyati (2006) database, augmented to extend country and time coverage, based on IMF country staff reports and country desk information.

A possible shortcoming of the specification (and its selection of fundamentals) is that it does not explore the role of policy responses, which may have varied over time and between economies. However, it is important to keep in mind that policy space at the time of a shock is normally determined by the initial conditions (countercyclical fiscal or monetary policy would normally be possible only if fiscal solvency is not an issue and the monetary/exchange rate framework is sufficiently flexible at the time of the shock). Hence, it is likely that policy response measures would be correlated with some of the measures of country fundamentals already considered in our specification.

A simple bivariate analysis of the data highlights the importance of some of these country features, particularly when the financial shock is of large magnitude. Specifically we find that:

  • A low degree of exchange rate flexibility appears to be associated with sharp economic contractions.
  • This is also the case for a low current account balance, low net foreign assets, and highly dollarized economies.
  • Interestingly, in this simple bivariate analysis, financial integration or the level of international reserves appear to have a muted role.

Although these simple patterns may provide some insights as to the relevance of some variables vis-à-vis others, they should be interpreted with caution, as they may reflect simple correlations with other variables.

Cross-Sectional Results

This section explores a number of specifications of the cross-sectional multivariate setting described above to get a sense of the role that individual variables have in amplifying or mitigating the impact of financial shocks. For simplicity we start with a basic specification that reports the effect of the VIX on our measure of output. From there on, all specifications control for trade effects and include different combinations of macroeconomic fundamentals and their interaction with financial integration, depending on their statistical significance. Table 8.2 presents a summary with the most relevant results.11

Table 8.2Main Results of Cross-Section Estimation
Output Performance1
Dependent VariableBasic ModelMainRobustness
Variable
VIX−0.176***−0.047***0.0100.008
(0.018)(0.017)(0.028)(0.034)
Trade channel0.117***0.113***
(0.019)(0.020)
Terms of trade7.637**
(3.553)
World GDP0.945***
(0.207)
Interaction of VIX with
Financial integration−0.077+−0.123**
(0.049)(0.049)
Current account balance0.001+0.001
(0.001)(0.001)
Exchange rate flexibility−0.096**−0.117**
(0.046)(0.050)
External debt−0.000+−0.000
(0.000)(0.000)
Interaction of VIX with financial integration and
Exchange rate flexibility0.190***0.235***
(0.070)(0.074)
Constant15.757***4.015**3.229*4.976***
(1.756)(1.619)(1.674)(1.819)
Observations337337268268
R-squared0.4180.5620.6410.571
F98.2468.3723.9418.98
Source: Authors’ estimates.Note: See equation (8.2) and main text for an explanation on how to derive the amplification effect of a given fundamental from these estimated coefficients. VIX = Chicago Board Options Exchange Market Volatility Index. Robust standard errors in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.10, + p < 0.15.

Cumulative change of cyclical component of GDP, in percent of trend.

Source: Authors’ estimates.Note: See equation (8.2) and main text for an explanation on how to derive the amplification effect of a given fundamental from these estimated coefficients. VIX = Chicago Board Options Exchange Market Volatility Index. Robust standard errors in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.10, + p < 0.15.

Cumulative change of cyclical component of GDP, in percent of trend.

Results suggest that exchange rate flexibility is fundamental in buffering large global shocks, while higher financial integration, current account deficits, and external debt tend to amplify them. Interestingly, and despite our priors, a number of variables were found to have a muted effect. International reserve buffers were found to have no statistically significant role in buffering global shocks. In the case of fiscal variables, we failed to find any significant role for debt levels.12 Although the primary fiscal balance was found to play a mitigating role—a stronger position mitigates the impact of the shock—its statistical significance disappeared when other fundamentals were included, no doubt suggesting a strong cross-correlation. Finally, the degree of dollarization did not appear to be significant either.13

Recall that the amplification effect of a fundamental (x) is given by equation (8.4). To illustrate such an effect, we use the estimated coefficients to obtain the predicted impact of a global financial shock (measured as a 10-point increase in the VIX) for different degrees of financial integration and fundamentals (Figure 8.8). The analysis shows that:

  • For the median EME—with a de facto crawling peg—higher financial integration tends to increase vulnerability to global financial shocks.
  • The role of financial integration in mitigating or amplifying financial shocks, however, greatly depends on the economy’s exchange rate regime. That is, greater financial integration amplifies the shock under fixed rate regimes but mitigates it under floating regimes.14
  • At the same time, for most levels of integration, greater exchange rate flexibility reduces the output cost of the global shock. Such a mitigation effect is particularly pronounced for high levels of financial integration.
  • As expected, larger current account deficits make an economy more vulnerable, although the effect is of small magnitude.
  • Similarly, high levels of external debt make an economy more vulnerable to financial shocks, irrespective of the level of financial integration.

Figure 8.8Macroeconomic Fundamentals and the Impact of Global Shocks

Source: IMF staff calculations.

Note: Impact of 10-point Chicago Board Options Exchange Market Volatility Index (VIX) shock for different levels of financial integration and fundamentals (other variables unchanged, at median emerging market value).

1 Cumulative deviations from trend output in percent of trend.

2Total foreign assets plus total foreign liabilities, as percent of GDP. Reported levels correspond to deciles 20–80.

3 Percent of GDP. Levels correspond to deciles 20–80.

Overall, these results support the notion that financially integrated EMEs with strong fundamentals (especially exchange rate flexibility) are better equipped to cope with global financial shocks than economies where fundamentals are weak or that have fewer financial linkages. Although not analyzed in detail here—mainly due to data limitations—the buffering effect provided by strong fundamentals probably operates in two ways: first, by mitigating capital outflows if an adverse global shock occurs, and second, by lowering the economic impact of any resulting capital outflows. Some preliminary evidence of the importance of the first effect is discussed in IMF (2012).

Assessing Vulnerabilities: Simulation Analysis

Finally, we make use of the benchmark model to determine the estimated impact of different financial shocks witnessed in the past two decades across different regions (Figure 8.9). Specifically, the simulations take as input the values of economic fundamentals and financial integration corresponding to 1997 (right before the Asian crisis), 2008 (right before Lehman), and 2010 (right before Greece’s event). This exercise unveils how the degree of vulnerability of different regions has diverged over time. While Latin America and emerging Asia have seen a gradual improvement (becoming less sensitive to these shocks), particularly since 1997, emerging Europe has systematically moved in the opposite direction.15 As a result, while the estimated impact of a 10-point VIX shock on Latin America and Asia is today about 0.34 percentage points of GDP, the impact on emerging Europe reaches about 0.57 percentage points of GDP. To give a sense of magnitudes, these estimates imply that a Lehman-type event (with an average 40-point increase in the VIX over a year) would have an impact equivalent to about 1¼ percent of GDP loss in Asia and Latin America, and 2¼ percent of GDP in emerging Europe, even after controlling for the associated external trade shock.

Figure 8.9Impact of Global Shock

(Output effect of a 10-point VIX shock, in percent of annual GDP)

Source: IMF staff calculations.

Note: Estimated impact, evaluated for value of fundamentals before Asian crisis, Lehman crisis, and Greece event. Median value of fundamentals for each group is used. EM = emerging market; SAM = small advanced market; VIX = Chicago Board Options Exchange Market Volatility Index.

1 Brazil, Chile, Colombia, Mexico, Peru, and Uruguay.

2 India, Indonesia, Korea, Malaysia, Philippines, and Thailand.

3 Bulgaria, Czech Republic, Hungary, Poland, Romania, and Russia.

4 Australia, Canada, Finland, Hong Kong SAR, Israel, New Zealand, Norway, Singapore, and Sweden.

These results suggest that improvements in fundamentals over the past 20 years in Latin America and Asia have more than offset the potentially greater vulnerability arising from increased financial integration. In emerging Europe, on the other hand, both fundamentals (identified as relevant by the econometric exercise) and financial integration have moved in the direction of making the region more vulnerable to global financial shocks.

Conclusions

Emerging market economies continue to be vulnerable to large global financial shocks, as made evident by the behavior of capital flows in and out of these economies during periods of global financial stress. However, despite the increasing degree of financial integration of EMEs, such vulnerability appears to have declined over time for some regions (Latin America and Asia), reflecting to a large extent marked improvements in fundamentals. A key factor determining these effects in many of these economies, particularly in Latin America, has been progress toward greater exchange rate flexibility which is found here to mitigate the impact of adverse financial shocks, particularly in highly financially integrated economies. Economies in both regions have also made improvements in external sustainability (current account and external debt), a key dimension determining the impact of financial shocks. Overall, these results support the notion that financially integrated EMEs with strong fundamentals (especially exchange rate flexibility) are better equipped to cope with global financial shocks than economies where fundamentals are weak or that have fewer financial linkages. Of course, this does not make them immune to adverse shocks, but at least it may help them sail more safely over global financial waves.

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1Of course, increased financial integration may also have brought other benefits (for example, risk-sharing, better international allocation of savings, transfer of financial expertise). These, however, are beyond the scope of this chapter.
2The exact interpretation of spikes in the VIX is still a matter of debate in the academic literature. Bloom (2009), however, shows that the VIX is strongly correlated with measures of uncertainty, including financial variables. This lends support to its use as a measure of global financial stress. See also Carrière-Swallow and Céspedes (2011).
3Kaminsky and Reinhart (2003) study under what conditions financial turbulence that originated in certain EMEs spread globally to other emerging and advanced economies. They argue that these episodes only spread when the local shock affects asset markets in one or more of the world’s financial centers; otherwise spillovers are confined to economies in the same region. Or to put it differently, for a shock to become systemic it has to reach the financial center. This conclusion supports the choice of the VIX as a global shock measure.
4Trade shocks (particularly those arising from commodity price fluctuations) are the subject of analysis in Chapter 4.
5Financial integration may have other potential positive side effects—for example, risk-sharing or higher long-term growth—that are not considered in our analysis.
6We also explore a similar measure that excludes international reserves and official external debt, as these components are unlikely to be channels of transmission of external shocks. On the contrary, these components of the international investment position tend to be countercyclical. Stylized facts and econometric results, however, do not change significantly with this alternative measure.
7Within Latin America, this trend has not been homogeneous across different countries. Countries in the LA6 group (Brazil, Chile, Colombia, Mexico, Peru, and Uruguay) and the Central American countries have led the pace of integration within the region, while other countries in South America have moved in the opposite direction, particularly over the past decade.
8It is important to highlight that, in contrast to most studies that rely on annual data, our analysis is based on quarterly data, allowing us to measure more precisely the output costs of global financial shocks. For most countries, the constructed dependent variable uses quarterly GDP data. In some instances, however, quarterly GDP series are extended by chaining them with variance-adjusted indicators of economic activity or industrial production.
9The measure is constructed with data from the updated and extended version of the Lane and Milesi-Ferretti (2007) database. Econometric results also hold for a measure of financial integration that strips holdings of international reserves, as well as official loans. Such adjustment is meant to better capture those assets and liabilities that would be sensitive to global shocks.
10Other economy characteristics that may also be relevant—such as exchange rate misalignment, measures of strength of the financial system, financial regulation, macroprudential policies, and so on—are not included in the econometric exercise due to data limitations.
11See Adler and Tovar (2012) for more details.
12It is certainly possible that the limited information content that can be extracted from a simple debt-to-GDP ratio in assessing creditworthiness may be behind the lack of significance of debt levels in our regressions.
13Arguably the measure fails to properly capture the extent of currency mismatches in the financial system. Unfortunately, comprehensive data on currency mismatches at a quarterly frequency are not available.
14A possible interpretation is that closer financial ties with the rest of the world can help mitigate financial shocks by keeping lines of credit open during these events, provided that the more procyclical (for example, speculative) flows can be mitigated with an appropriate degree of exchange rate floating.
15While the results for emerging Europe for 1990–2008 are consistent with the well-known buildup of vulnerabilities during this period, a further increase in vulnerability since 2008 may seem at odds with the adjustment efforts seen in many of these economies after the Lehman crisis. This result reflects the fact that our measure of financial integration shows further increases for Eastern Europe, mainly on account of a fall in the denominator (nominal GDP in foreign currency).

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