2013 Spillover Report - Analytical Underpinnings and Other Background

International Monetary Fund

doi:10.5089/9781498341547.007.A001

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2013 Spillover Report - Analytical Underpinnings and Other Background

Author: International Monetary Fund

Publication Date:: 03 Jul 2013

ISBN:: 9781498341547

Language:: English

Keywords:: PP; exchange rate; financial market; monetary policy; quantitative easing; real GDP; fed funds rate; global economy; fiscal cliff; foreign exchange

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High uncertainty in general, and high policy uncertainty more specifically, can have important impact on global investment and output growth. Much of the recent policy uncertainty emanated from the United States and Europe—the world’s two largest economies. Spillovers from policy uncertainty can occur through several channels. Trade can be affected if increased policy uncertainty adversely affects economic activity and import demand in the United States and Europe. Policy uncertainty could also raise global risk aversion, resulting in sharp corrections in financial markets and capital outflows from emerging markets. This background note attempts to quantify the impact of U.S. and European policy uncertainty on other regions. Specifically, it addresses the following questions: What do we mean by policy uncertainty? How well can we measure it? How has policy uncertainty in the United States and Europe evolved during the past several decades? And how large are the spillovers to economic activity in other regions? The analysis suggests that sharp increases in U.S. and European policy uncertainty in the past have temporarily lowered investment and output in other regions to varying degrees. It also suggests that a marked decrease in policy uncertainty in the United States and Europe in the near term could help boost global investment and output.

Abstract

Cross-Country Studies

I. Stabilization Dividends

1. Spillovers from Policy Uncertainty in the United States and Europe¹

1. A common view is that high uncertainty in general, and high policy uncertainty more specifically, has held back global investment and output growth in the past two years. Much of the policy uncertainty emanated from the United States, with the debt ceiling dispute in August 2011 and negotiations about the “fiscal cliff” in December 2012. Policy uncertainty has also been elevated in Europe, especially in the aftermath of Greek Prime Minister George Papandreou’s call for a referendum on the Greek bailout plan (and his subsequent resignation) in November 2011, and during the negotiations about a pan-European crisis response through much of 2012. Policymakers and business leaders across the globe worry about the implications of such uncertainty in the United and States and Europe—the world’s two largest economies.

2. Spillovers from policy uncertainty can occur through several channels. Trade can be affected if increased policy uncertainty adversely affects economic activity and import demand in the United States and Europe. Policy uncertainty could also raise global risk aversion, resulting in sharp corrections in financial markets and capital outflows from emerging markets.

3. This background note attempts to quantify the impact of U.S. and European policy uncertainty on other regions.² Specifically, it addresses the following questions: What do we mean by policy uncertainty? How well can we measure it? How has policy uncertainty in the United States and Europe evolved during the past several decades? And how large are the spillovers to economic activity in other regions?

4. The analysis suggests that sharp increases in U.S. and European policy uncertainty in the past have temporarily lowered investment and output in other regions to varying degrees. It also suggests that a marked decrease in policy uncertainty in the United States and Europe in the near term could help boost global investment and output.

Uncertainty and economic activity

5. The idea that uncertainty can adversely affect economic activity dates back to John Maynard Keynes (1936), who argued that investment is the most volatile component of aggregate activity because it is dependent on views about the future, which are most uncertain. The idea was formalized in a number of theoretical models, ranging from Bernanke (1983) to Bloom (2009). Temporary increases in uncertainty make it worthwhile to delay investment, because investment is impossible or costly to undo or change. Investment tends to recover once uncertainty dissipates, and can overshoot as a result of pent-up demand. The same holds true for consumption of durables, which is subject to the same forces.

6. Two critical challenges arise in trying to estimate the spillover effects of policy uncertainty. First, it is necessary to ensure that causality is not running in the opposite direction—that policy uncertainty in the United States and Europe is not being driven by developments in economic activity elsewhere. For the most part, this is a plausible assumption—spikes in policy uncertainty are often associated with domestic economic and political events, or with global geopolitical events that can be considered exogenous to most individual countries (Figure 1.1). To the extent that specific events could result in reverse causality (for example, the Russian and Long-Term Capital Management crises in 1998 resulted in a spike in policy uncertainty), the analysis verifies that the results hold even when these events are excluded.

7. The second challenge is to avoid attributing to policy uncertainty the effects of other factors, such as more general economic uncertainty, shifts in consumer or business confidence, or fluctuations in economic activity. This challenge is addressed by controlling for such variables, which is important because these variables tend to move together—uncertainty tends to rise and confidence tends to fall during downturns in economic activity. This means that various measures of uncertainty could be picking up actual changes in economic prospects, not just the uncertainty surrounding economic prospects.

Measuring economic policy uncertainty

8. The analysis starts with the measures of U.S. and European economic policy uncertainty constructed by Baker, Bloom, and Davis (2012). These measures use news-based indicators of policy-related economic uncertainty (the relative frequency of newspaper articles that refer to “uncertainty,” “economy,” and “policy”), the number of expiring tax provisions, and the dispersion in economists’ forecasts about government spending and inflation levels.³ These measures are combined to construct monthly indices of policy uncertainty dating back to 1985 for the United States and to 1997 for Europe.

9. This measure of economic policy uncertainty is not without issues. First, the news-based component is an indirect measure, and ascertaining whether it is measuring policy uncertainty properly is hard. Second, many expiring tax code provisions are regularly renewed and are unlikely to be a major source of uncertainty. Finally, the forecast dispersion components might rise because of other factors—inflation forecasts could become more dispersed because of uncertainty about oil or food prices, for example, and not because of uncertainty about monetary policy.

10. To address the first concern, Baker, Bloom, and Davis (2012) offer several “proof of concept” tests. For example, they construct a similar news-based measure for financial uncertainty by searching for news articles containing “uncertainty,” “economy,” and “stock market” and show that the constructed index tracks the Chicago Board Options Exchange Market Volatility Index (VIX) closely. They also note that their measure of policy uncertainty is highly correlated with other policy-uncertainty measures, such as those of Fernández-Villaverde and others (2011) and Born and Pfeifer (2011), which are constructed using very different methodologies.⁴ With regard to the second and third issues, the results reported below are robust to excluding the tax-expiration and forecast-dispersion components of the policy-uncertainty measure and relying solely on the news-based measure of policy uncertainty.

The evolution of U.S. and European policy uncertainty

11. Policy uncertainty tends to spike in response to identifiable economic, financial, and geopolitical events (Figure 1.1). Uncertainty shocks, identified by vertical lines in Figure 1.1, are defined as periods during which the Hodrick-Prescott detrended value of the index exceeds its mean by more than 1.65 standard deviations, following Carrière-Swallow and Céspedes (2011). As noted by Baker, Bloom, and Davis (2012), many of the spikes in policy uncertainty are associated with identifiable events. For example, U.S. policy uncertainty spiked after the start of the Gulf War in August 1990, the September 11, 2001, terrorist attacks, and the run-up to the Iraq War in early 2003. More recent spikes in U.S. policy uncertainty have been associated with economic and financial events, including the recession-induced monetary and fiscal easing in January 2008, the bankruptcy of Lehman Brothers in September 2008, the debt ceiling dispute in August 2011, and the fiscal cliff negotiations in late 2012.

12. European policy uncertainty also spiked following the September 11 attacks and again in early 2003 with the signing of the EU Treaty of Accession (the single largest expansion of the European Union), which compounded the uncertainties from the Iraq War. Other events associated with high European policy uncertainty include the Greek bailout request in May 2010, the call in November 2011 for a Greek referendum on the terms of the bailout, and discussions on the EU-wide policy response to the expanding crisis in 2012.

13. These events raised uncertainty about economic policies, but they also raised general financial and economic uncertainty and caused a drop in confidence—making it critical to control for these other correlates. Policy uncertainty tends to move with general economic uncertainty—whether measured by indicators of financial uncertainty (such as implied stock market volatilities) or of economic uncertainty (such as the dispersion of economists’ GDP forecasts; Figure 1.2, panels 1 and 2). There are divergences, however. Most notably, general economic uncertainty has retreated from its 2008 highs, whereas policy uncertainty has remained high and has even increased. The correlation between confidence indicators (Figure 1.2, panels 3 and 4) and policy uncertainty is also evident but imperfect, making it possible to include them as control variables in the analysis.

Spillovers from policy uncertainty

14. The policy-uncertainty shocks in the United States and Europe are regressed on output and investment behavior in other regions. The methodology resembles those of Cerra and Saxena (2008) and Romer and Romer (2010), among others. Specifically, real GDP growth and real investment growth (both measured in log differences) are regressed on their lagged values to capture the normal dynamics of the growth process, as well as on contemporaneous and lagged values of a dummy variable that is equal to 1 during the policy-uncertainty shocks described above and zero otherwise.^5,6 Including lags allows for the possibility that policy-uncertainty spillovers affect other economies with a delay. The specification also includes a full set of country dummies to account for differences in normal growth rates, but the inclusion of time dummies is precluded by the fact that the variable of interest is a global variable common across all countries.

15. The model is estimated by region, using seasonally adjusted quarterly data for 43 economies from 1990 to 2012, although the wide variation in the availability of quarterly GDP data means the sample is highly unbalanced.⁷ The effects of U.S. and European policy-uncertainty shocks are estimated separately, given their high correlation; the estimated impacts should thus be considered an upper bound because each is likely picking up the effects of the other.

16. Figure 1.3 shows the estimated impact of a large but temporary policy-uncertainty shock—similar in magnitude to the shocks highlighted in Figure 1.1—on real GDP of economies in various regions. The impulse responses are shown for an eight-quarter horizon, with the 90 percent confidence bands around the estimates shaded in gray. The impact on annual growth is significant. U.S. policy-uncertainty shocks temporarily reduce GDP growth in other regions by up to ½ percentage point in the year of the shock (Figure 1.4, panel 1). European policy-uncertainty shocks temporarily reduce GDP growth in other regions by a smaller amount (Figure 1.4, panel 2).⁸

17. One of the ways that policy uncertainty affects economic activity in other regions is by reducing investment. Figure 1.5 shows the results of a similar exercise in which real investment is the dependent variable. Significant declines in investment result in all regions, except sub-Saharan Africa, with the biggest decline in the Commonwealth of Independent States (CIS).⁹ With regard to output, the effect of European policy-uncertainty shocks tends to be similar or slightly smaller than that of U.S. shocks (Figure 1.4, panels 3 and 4). In addition, European shocks tend to have a smaller effect on the United States than vice versa.

The mechanics of policy uncertainty spillovers

18. The analysis addresses the possibility that the policy-uncertainty measure is picking up the effects of other variables by controlling for general uncertainty, declining confidence, or a decline in U.S. or European economic activity. Note that the results can be interpreted in two ways:

One possibility is that the additional control variable—for example, general economic uncertainty—affects U.S. or European policy uncertainty as well as economic activity in other countries. In this case, adding the control variable improves the estimate of the spillover effects from policy uncertainty.
A second possibility is that the control variable is a mediating variable through which policy uncertainty is actually conveyed—for example, higher policy uncertainty increases general uncertainty, which, in turn, affects activity elsewhere. In this case, adding the control variable nets out any effect of policy uncertainty that was conveyed through this mediating variable, resulting in an underestimation of the overall spillover effects.

19. The likeliest scenario is that both interpretations are valid—that is, policy uncertainty affects and is affected by the control variables (general uncertainty, confidence, and activity). As a result, the true magnitude of spillover effects from policy uncertainty is most likely somewhere between the baseline effect reported in Figures 1.3 and 1.5 and the effects estimated when using the control variables shown in Figure 1.6.

20. In addition to showing the peak effect on real GDP and real investment, Figure 1.6 shows the peak effect on real consumption. The dark-blue bars show the peak effect when there are no control variables other than policy uncertainty: these are the minimum values of the impulse response functions shown in Figures 1.3 and 1.5. The red bars show the peak effect of policy uncertainty when financial-uncertainty shocks—as measured by the VXO—are added as a control in the regression.¹⁰ For the most part, the magnitude of the policy-uncertainty effect is broadly similar to the baseline. The same holds true for controls for business confidence or the level of the stock market (Figure 1.6, yellow and gray bars).

21. The pink bars in Figure 1.6 show that controlling for import growth in the United States or Europe reduces the estimated effect of policy uncertainty in many, but not all, regions.¹¹ One interpretation is that U.S. or European policy uncertainty could negatively affect domestic activity in these economies, which affects activity elsewhere via lower import demand. The reduction in the impact of policy uncertainty would then indicate the strength of this particular transmission channel. For the CIS, for example, the effects of European policy uncertainty are diminished, but the effects of U.S. policy uncertainty are not. Under this interpretation, European policy uncertainty affects the CIS primarily via trade channels, but U.S. policy uncertainty is transmitted through other channels.

22. A similar exercise can measure the extent to which the spillover effects of U.S. and European policy uncertainty are transmitted by raising uncertainty in other economies (measured by forecast dispersion). The spillover effects of policy uncertainty are reduced in some cases, but not in others (Figure 1.6, light-blue bars), suggesting that increased uncertainty can be another channel of transmission. In most regions, policy uncertainty seems to reduce investment through its effect on higher domestic uncertainty.

What happens when policy uncertainty subsides?

23. The impulse responses in Figures 1.3 and 1.5 can also provide an indication of the benefits one might expect once policy uncertainty in the U.S. and Europe starts to subside to more normal levels. The negative impact of a temporary spike in policy uncertainty lasts from between two to four quarters. Beyond that, its spillover effects start to dissipate, and output and investment in other regions begin to recover to normal levels. Figure 1.7 shows that lower U.S. and European policy uncertainty on growth is associated with a “growth dividend” of between ¼ and ½ percentage point in the year after policy uncertainty has subsided, with the impact again varying by region.

Conclusion

24. This analysis documents significant spillover effects from policy uncertainty in the United States and Europe to other regions. It finds that sharp spikes in U.S. policy uncertainty—of the magnitude observed during the U.S. debt ceiling dispute in August 2011, for example—can temporarily lower investment and output in other regions. The spillover effects from European policy uncertainty tend to be slightly smaller and less persistent and tend to have smaller effects on U.S. activity than vice versa.

25. Policy uncertainty has remained high in the United States and Europe since the Great Recession—even as more general uncertainty has receded and various measures of consumer and business confidence have recovered. The evidence presented here hints at the possibility that elevated policy uncertainty may have contributed to the serial disappointments and downward revisions in investment and output growth observed throughout the same period. The evidence also suggests that a reduction in policy uncertainty in the United States and Europe in the near term may give an added fillip to global investment and output.

References

Baker, Scott, Nicholas Bloom, and Steven J. Davis, 2012, “Measuring Economic Policy Uncertainty” (unpublished). Paper and indices are available at www.policyuncertainty.com.
- Search Google Scholar
- Export Citation
Bekaert, Geert, Robert Hodrick, and Xiaoyan Zhang, 2010, “Aggregate Idiosyncratic Uncertainty,” NBER Working Paper No. 16058 (Cambridge, Massachusetts: National Bureau of Economic Research).
- Search Google Scholar
- Export Citation
Bernanke, Ben, 1983, “Irreversibility, Uncertainty, and Cyclical Investment,” Quarterly Journal of Economics, Vol. 98, No. 1, pp. 85–106.
- Crossref
- Search Google Scholar
- Export Citation
Bloom, Nicholas, 2009, “The Impact of Uncertainty Shocks,” Econometrica, Vol. 77, No. 3, pp. 623–85.
- Crossref
- Search Google Scholar
- Export Citation
Bloom, Nicholas, Stephen Bond, and John van Reenen, 2007, “Uncertainty and Investment Dynamics,” Review of Economic Studies, Vol. 74, No. 2, pp. 391–415.
- Crossref
- Search Google Scholar
- Export Citation
Born, Benjamin, and Johannes Pfeifer, 2011, “Policy Risk and the Business Cycle,” Bonn Econ Discussion Paper No. 06/2011 (Bonn: University of Bonn).
- Search Google Scholar
- Export Citation
Carrière-Swallow, Yan, and Luis Felipe Céspedes, forthcoming, “The Impact of Uncertainty Shocks in Emerging Economies,” Journal of International Economics.
- Search Google Scholar
- Export Citation
Cerra, Valerie, and Sweta Saxena, 2008, “Growth Dynamics: The Myth of Economic Recovery,” American Economic Review, Vol. 98, No. 1, pp. 439–57.
- Crossref
- Search Google Scholar
- Export Citation
Fernández-Villaverde, Jesús, Pablo Guerrón-Quintana, Keith Kuester, and Juan Rubio-Ramírez, 2011, “Fiscal Volatility Shocks and Economic Activity,” Working Paper No. 11–32 (Philadelphia: University of Pennsylvania Press).
- Search Google Scholar
- Export Citation
International Monetary Fund (IMF), 2012, 2012 Spillover Report (Washington). www.imf.org/external/np/pp/eng/2012/070912.pdf.
- Search Google Scholar
- Export Citation
Keynes, John Maynard, 1936, The General Theory of Employment, Interest, and Money (London: MacMillan).
- Search Google Scholar
- Export Citation
Romer, Christina D., and David H. Romer, 2010, “The Macroeconomic Effects of Tax Changes: Estimates Based on a New Measure of Fiscal Shocks,” American Economic Review, Vol. 100, No. 3, pp. 763–801.
- Crossref
- Search Google Scholar
- Export Citation

2. Effects of Stabilizing Policies in the Euro Area and the US¹²

1. This note analyzes the global macroeconomic effects of policy measures taken to alleviate the sovereign debt crisis in the euro area and avert the fiscal cliff in the United States. This analysis is based on scenarios simulated with the structural macroeconometric model of the world economy, disaggregated into thirty five national economies, documented in Vitek (2013).¹³ Within this framework, each economy is represented by interconnected real, external, monetary, fiscal, and financial sectors. Spillovers are transmitted across economies via trade, financial, and commodity price linkages. Financial linkages are both direct, through cross-border debt and equity portfolio holdings, and indirect via international comovement in asset risk premia.

2. The stabilizing policy measures under consideration were taken by the euro area in the second half of 2012 and by the United States at the beginning of 2013. For the euro area, we consider: the creation of the Single Supervisory Mechanism, agreed to by the European Council on June 29; the establishment of the Outright Monetary Transactions program, foreshadowed by the European Central Bank on July 26, announced on August 2, and clarified on September 6; the backing for the European Stability Mechanism, approved by the German Constitutional Court on September 12; the provision of additional debt relief for Greece, agreed to by the European Council on November 26; and the regulation of the Single Supervisory Mechanism, agreed to by the European Council on December 13. For the United States, we consider the American Taxpayer Relief Act, passed by Congress on January 1.

3. Our scenario for the euro area represents the stabilizing policy measures taken to alleviate the sovereign debt crisis with global bond and stock market adjustments. In particular, we calibrate changes in long-term nominal market interest rates and equity prices to match their estimated responses to the stabilizing policy announcements under consideration, in the absence of conventional monetary policy reactions and automatic fiscal stabilizers worldwide. These estimated global financial market responses are based on an event study analysis using the data set documented in Sgherri (2013).¹⁴ They are phased out gradually according to a first order autoregressive process having a coefficient of 0.85, and are generated with sequences of temporary but persistent duration and equity risk premium shocks. We allow for feasible conventional monetary policy reactions to these inferred sequences of risk premium shocks, as well as the full operation of automatic fiscal stabilizers. We assume that conventional monetary policy reactions are constrained by the zero lower bound on the nominal policy interest rate through 2015Q2 in the Czech Republic, Denmark, the euro area, Japan, Saudi Arabia, Switzerland, the United Kingdom, and the United States.

4. We estimate the global financial market responses to the stabilizing policy measures taken to alleviate the sovereign debt crisis with a traditional event study analysis. This event study analysis entails the measurement of absolute changes in long-term government bond yields and proportional changes in equity prices over two day windows centered around event dates. Summing these measured changes across event dates reveals that the policy measures taken to alleviate the sovereign debt crisis in the euro area were very effective at reducing financial stress in the periphery. Indeed, long-term government bond yields in Greece, Ireland, Italy, Portugal and Spain fell by 192 basis points, while equity prices rose by 14.7 percent, on average. Meanwhile, long-term government bond yields rose in safe havens, by 43 basis points on average across Australia, Canada, Denmark, Germany, New Zealand, the United Kingdom, and the United States.

5. Our scenario for the United States represents the stabilizing policy measures taken to avert the fiscal cliff with less fiscal consolidation, as measured by the change in the structural primary fiscal balance ratio. The corresponding fiscal consolidation path is generated with sequences of temporary but persistent fiscal expenditure and revenue shocks, mixed commensurate with its composition. Our scenario also features a sustained improvement in financial market confidence from not raising concerns over the effectiveness of the political process in the United States, manifested through global stock market adjustments. In particular, we assume an increase in equity prices in the United States of 10.0 percent, in other advanced economies of 5.0 percent, in emerging economies with open capital accounts of 7.5 percent, and in emerging economies with closed capital accounts of 2.5 percent, in the absence of conventional monetary policy reactions and automatic fiscal stabilizers worldwide. These global stock market responses are phased out gradually according to a first order autoregressive process having a coefficient of 0.75, and are generated with sequences of temporary but persistent equity risk premium shocks. We allow for feasible conventional monetary policy reactions to these inferred sequences of risk premium shocks, as well as the full operation of automatic fiscal stabilizers outside of the United States. We assume that conventional monetary policy reactions are constrained by the zero lower bound on the nominal policy interest rate through 2015Q2 in the Czech Republic, Denmark, the euro area, Japan, Saudi Arabia, Switzerland, the United Kingdom, and the United States.

6. The stabilizing policy measures taken to avert the fiscal cliff are estimated to imply substantially less fiscal consolidation. Indeed, the structural primary fiscal balance ratio of the general government is estimated to increase by 2.8 percentage points less in 2013 due to averting the fiscal cliff, of which 88 percent is accounted for by revenue measures. Moreover, 79 percent of this change in the structural primary fiscal balance ratio is estimated to persist over the medium term.

7. We estimate that the stabilizing policy measures taken by the euro area, and to a lesser extent the United States, are generating large output gains there, with spillovers concentrated among geographically close trading partners. Indeed, our scenario simulation results indicate that the stabilizing policy measures taken by the euro area will raise output there by 5.3 percent in 2013, by 0.8 to 3.9 percent in other advanced economies, and by 1.5 to 4.5 percent in emerging economies, reflecting their transmission primarily via financial linkages. Within the euro area, the largest output gains are realized in the periphery, at 9.8 percent for Greece, 3.6 percent for Ireland, 6.6 percent for Italy, 7.3 percent for Portugal, and 8.2 percent for Spain. By comparison, the stabilizing policy measures taken by the United States will raise output there by 3.6 percent in 2013, by 0.9 to 1.8 percent in other advanced economies, and by 0.8 to 2.1 percent in emerging economies, commensurate with their transmission via trade linkages to a greater degree. Aggregating these simulated output gains implies a world output gain of 3.0 percent from stabilizing policies in the euro area, and of 1.7 percent from those in the United States. The associated increases in the prices of energy and nonenergy commodities are 31.0 and 20.1 percent for the euro area, versus 14.7 and 8.0 percent for the United States.

3. Market-Based Indicators of Systemic Risks¹⁵

Market-based indicators that are commonly used to gauge systemic (“tail”) risks suggest that the euro area tail risks declined markedly since mid-2012 and remain below the previous peak (spring 2012) despite some revival of concerns amid Italian elections and Cyprus bail-out in early 2013. In contrast, markets now seem to be more concerned about extreme outcomes in Japan as well as the effects of potential QE tapering in the United States. Compared to European G-SIBs, U.S. G-SIBs appear less vulnerable to contagion from other G-SIBs, reflecting a combination of greater progress in balance-sheet repair and lower exposure to the euro area risks.

Funding stress

1. LIBOR-OIS spreads provide insight into market perceptions of credit risk in funding markets, with higher spreads associated with higher risk. Funding stress peaked during the Lehman bankruptcy and remained elevated during the subsequent months (Figure 13). At present, spreads have returned to their pre-crisis levels as markets have normalized. However, worries over the European debt crisis prompted an increase in stress levels in 2011-early 2012 that declined following the LTROs and the OMT announcement. In contrast, Japanese funding markets were much more stable even at the height of the crisis.

Equity and bond market volatility

2. Equity VIX indexes (also known as “fear indexes”) are based on the relative price of put options on equity indexes. Global equity stress levels peaked during the Lehman crisis and have subsequently come down to near-record lows, in part suppressed by the QE (Figure 13). However, volatility spiked again during periods of tensions in Europe (see Figure 1). More recently, the Japanese implied volatility index (VXJ) has moved higher following the change of government and the announcement of the QE program by the Bank of Japan, as well as the bouts of volatility in the JGB market. During the recent month, investor worries about Fed tapering of QE (notably after the Chairman Bernanke’s statement on May 22 – dashed line on the current charts in Figure 13) have come to the forefront and led to a spike in the U.S. Treasury yields and implied volatility in the UST market (as reflected in the MOVE index).¹⁶

Swap market volatility

3. Swaptions are options to enter into interest rate swaps with a specified strike rate and maturity. Ten year maturity swaptions on ten year swaps are widely used as a benchmark for stress in the fixed income market, as swaptions prices typically spike in times of market stress. Swaption volatility also peaked during the Lehman crisis and declined subsequently but has not returned to pre-crisis levels due to lingering uncertainty regarding monetary policy and the effects of QE policies instituted by several major global central banks (Figure 13). In Japan, swaptions volatility has risen significantly following the QE announcement by the Bank of Japan due to disruptions in the JGB market. Although conditions are slowly returning to normal, the JGB market saw several weeks of poor liquidity and fluctuating prices as investors and banks sought to position for large scale central bank purchases. Frequent shutdowns of the JGB futures market due to tripping of volatility triggers exacerbated swaptions volatility.

Currency volatility

4. In the FX market, risk reversals or the difference in price between call and put options are widely used as a gauge of risk aversion. The dollar and the yen are viewed as safe havens in crisis situations, while the euro and high yielding emerging market currencies tend to suffer. At the height of the financial crisis, euro-dollar risk reversals spiked as investors favored euro puts (dollar calls) over euro call options. At present, risk-reversals are close to pre-crisis levels again.

Likelihood of distress and value-at-risk of G-SIBs

5. Since the collapse of Lehman in September 2008, the market-implied probability of all G-SIBs falling in distress (as measured by the joint probability of distress (JPoDs)¹⁷) has continued to be driven by poor growth outlook as well as by the developments in the euro area. While JPoDs have generally tapered-off since 2009, concerns about the Greek bailout plan and spillover implications to other periphery economies precipitated a significant spike during the last quarter of 2011 (see figure below). The spike was largely driven by European banks.

6. The events early this year (Italian elections, Cyprus bail-out) have led to another increase in the JPoD of the European SIBs. In contrast, the JPoD of the U.S. SIBs has continued to steadily decline, reflecting improvement in the perceived resilience of their balance sheets.

7. The total value-at-risk of the system comprising 27 G-SIBs, conditional on one failure on average (total CoVaR¹⁸), has declined markedly since its peak in October 2008 following Lehman’s collapse, in line with the balance sheet repair and recapitalization efforts, though the total CoVaR has increased in the second half of 2011 (see figure below).

8. A noteworthy point is that the increase in overall CoVaRs has largely been driven by European SIBs, while U.S. and Asian SIBs remain relatively flat since 2011 (see figure below).

II. Unconventional Monetary Policies

4. Impact of Unconventional Monetary Policies on International Asset Prices¹⁹

Unconventional policies are often launched precisely because market conditions are unsettled, and it is in these circumstances that international financial spillovers tend to be the largest. Looking ahead, the larger impact coming from unconventional monetary policies is likely to be through forward guidance, managing market expectations of future policies.

1. The focus of this study is on the impact on foreign asset prices of conventional and unconventional monetary policies in systemic advanced economies. By examining the impact across a number of major asset prices the analysis aims at providing a relatively comprehensive picture of the likely impact on recipients. Bond yields and equity prices are important drivers of domestic demand through wealth effects and changes in the value of collateral. Exchange rates help determine competitiveness and hence the level of foreign demand.

2. Financial market spillovers from unconventional monetary policy are gauged using event studies. The impact of unconventional monetary policies is estimated on two-daily returns over a 10-year period of 2003-2013 for three asset markets (bond, equity and foreign exchange market) in a wide range of countries—23 advanced economies (AEs) and 11 emerging markets (EMs)—and reported for selected subgroups of advanced and EMs having similar characteristics.²⁰ Spillovers from pre-crisis easing, post-crisis policy announcements not involving unconventional monetary policy, and unconventional monetary announcements are examined by looking at the change in asset price for a given monetary surprise—as it is the surprise, after all, that moves asset prices.²¹

3. The analysis is adapted to take account of ‘typical” international and domestic financial linkages as well as differing time zones. High correlations in asset prices both across and within countries imply complex dynamics, even at daily frequencies. A two-stage approach is used to account for this “typical” behavior. First, the transmission of shocks between bond yields, equity prices, exchange rates and money market rates within and between the four major financial markets (Germany, Japan, the United Kingdom, and the United States) is examined in a simultaneous manner.²² Next, the corresponding underlying shocks are used as inputs into a similar system for each other small open economy in turn, to account for linkages across domestic assets within each of these smaller economies. Hence, for example, the model for Brazil takes account of financial markets shocks from the four major markets as well as interactions across Brazilian asset prices. Finally, a two-day window is used to study events given differing time zones—in particular, Asian markets in any given day are closed before the same day session in the United States starts.²³

4. The limitations of the event study approach need to be recognized. Examining short-term responses of financial markets to announcements of unconventional monetary policy helps avoid concerns that responses are being contaminated by non-policy-related news. Also, spillover effects are expected to rapidly transmit between liquid and highly integrated financial markets through portfolio rebalancing and expectation channels. However, event studies only reveal the immediate market reaction to such policies. To the extent that views on the impact of unconventional policies evolve over time, these revisions will not be captured by these event studies. In addition, as will be discussed further below, interpreting the response of financial markets to unconventional monetary policy announcements is complicated as the announcement reveals both a policy decision and an assessment of current economic conditions. If markets conclude that current conditions are worse than they had earlier perceived, the impact of a policy loosening on (say) equity prices becomes ambiguous.

5. Previous studies have shown that early announcements of asset purchases in AEs have buoyed asset prices globally by decreasing the tail risk of a severe recession, but their effects diminished once markets normalized. Previous evidence focusing on quantitative easing policy in the United States found significant spillover impact on bond yields and currency in EMs, with larger estimated effects from QE1 than from QE2.²⁴ Evidence of spillovers from unconventional monetary policy in non-U.S. AEs appears rather muted. Shocks to bond and equity markets in the United Kingdom and euro area generated mild spillovers to other AEs.²⁵

6. Divergence in the estimated spillover effects can reflect the context in which quantitative easing was implemented, country-specific factors in EMs, and endogenous policy responses. Findings of opposite spillovers on foreign asset prices of QE1 and QE2 could be due to different policy objectives and market environment.²⁶ Indeed, QE1 was intended to repair markets and provide liquidity to financial institutions, which effectively induced investors to relocate investments to the United States. As a result, QE1 announcements tend to be positively associated with a short-term improvement in global financial conditions measured by global risk appetite and global equity prices, while QE2 announcements do not. On the other hand, QE2 was implemented when many EMs were on an upward growth trend, making it difficult to distinguish the impact of the QE in creating capital outflows from the impact of better growth prospects in EMs in attracting capital flows. Finally, opposite responses of foreign exchange rates from QE2 could reflect policy reactions of EMs to intervene to stabilize exchange rates.

7. Controlling for monetary surprises and asset price endogeneity across borders and across markets broadly confirms these findings. Tables 4.2–4.4 summarize the estimated cumulative effect of the surprise for each type of announcement and each group of countries. For example, in Table 4.2, the “Latin America” bar corresponding to the U.S. “LSAP1a” entry shows that the surprise associated with the U.S. purchase of MBS and Agency bonds during the first phase of LSAP1 lowered long-term bond rates in Brazil and Mexico by over 9 basis points.

Table 4.1

Surprise Effect of UMP Announcements

Figures in italicized underlined font indicate significance at 5%.Note: For a detailed list of announcement dates, see IMF (2013a, 2013b).

Table 4.1

Surprise Effect of UMP Announcements

	Forward Libor Responses to UMP announcements bps, cumulative
	United States							United Kingdom			EA			Japan
	LSAP1A	LSAP1B	LSAP2	TWIST	LSAP3	Tapering	Forward Guidance	APP1	APP2	FLS	OMT	Speech	Rate Cut	Forward Guidance	LSAP	QQME
United States	-5.5	-9.9	-2.4	1.9	5.1	0.5	-16.1	0.5	-1.3	-1.8	1.5	-0.5	-0.5	-0.8	-1.0	-1.5
Japan	0.8	-0.3	0.3	0.5	1.2	-0.5	-1.4	-0.3	-0.5	-0.3	0.0	0.5	-0.5	-0.5	-0.5	3.0
United Kingdom	-7.7	-2.6	-0.5	0.3	-3.0	-3.1	1.8	2.6	-5.1	-5.4	1.9	2.9	-3.1	2.9	-0.7	-1.1
Euro Area	-4.8	-0.9	-1.1	0.5	-1.0	-2.5	0.4	3.8	-2.2	-1.4	0.5	0.5	-4.0	0.3	-1.5	2.0

Figures in italicized underlined font indicate significance at 5%.Note: For a detailed list of announcement dates, see IMF (2013a, 2013b).

Table 4.1

Surprise Effect of UMP Announcements

	Forward Libor Responses to UMP announcements bps, cumulative
	United States							United Kingdom			EA			Japan
	LSAP1A	LSAP1B	LSAP2	TWIST	LSAP3	Tapering	Forward Guidance	APP1	APP2	FLS	OMT	Speech	Rate Cut	Forward Guidance	LSAP	QQME
United States	-5.5	-9.9	-2.4	1.9	5.1	0.5	-16.1	0.5	-1.3	-1.8	1.5	-0.5	-0.5	-0.8	-1.0	-1.5
Japan	0.8	-0.3	0.3	0.5	1.2	-0.5	-1.4	-0.3	-0.5	-0.3	0.0	0.5	-0.5	-0.5	-0.5	3.0
United Kingdom	-7.7	-2.6	-0.5	0.3	-3.0	-3.1	1.8	2.6	-5.1	-5.4	1.9	2.9	-3.1	2.9	-0.7	-1.1
Euro Area	-4.8	-0.9	-1.1	0.5	-1.0	-2.5	0.4	3.8	-2.2	-1.4	0.5	0.5	-4.0	0.3	-1.5	2.0

Figures in italicized underlined font indicate significance at 5%.Note: For a detailed list of announcement dates, see IMF (2013a, 2013b).

Table 4.2

Impact of Surprises—10-Year Bond Yields Responses

Notes: Core EA comprises: Austria, Belgium, Finland, France, and Netherlands; Periphery EA comprises: Greece, Ireland, Italy, Spain, and Portugal; European Safe Havens comprise Denmark and Switzerland; Inflation Targeters comprise Australia, Canada, New Zealand, Norway, and Sweden; Latin America comprises Brazil and Mexico; Asia comprises Indonesia, Malaysia, South Korea, and Thailand; Europe comprises Czech Republic and Poland; Other EMs comprise Russia, South Africa, and Turkey. Only significant responses are reported.

Table 4.2

Impact of Surprises—10-Year Bond Yields Responses

			1-year Bond Yields Response to UMP Announcements bps, 2-day cumulative
			United States							United Kingdom			EA			Japan
			LSAP1A	LSAP1B	LSAP2	TWIST	LSAP3	Tapering	Forward Guidance	APP1	APP2	FLS	OMT	Speech	Rate Cut	Forward Guidance	LSAP	QQME
Advanced Economies
	United States		-8.7	-11.6	-4.4	-14.2		8.3		4.4		-1.3		13.7	11.6	2.0
	United Kingdom		-15.7
	Japan		-4.2				21.7				11.4
	Germany		-6.3	-5.7	-2.7	-6.8	-7.4		3.8	3.5		-2.3	0.5	8.7			-2.4
	Euro Area
		Core	-4.8	-4.7	-2.2	-3.8	-7.0	3.3		1.9							-0.5	-4.1
		Periphery	-3.8	-3.8	-1.6	-3.3	-13.9	6.9		-1.4	3.7		-2.9	-15.2			-0.5	-6.3
	EUR Safe Havens		-4.2	-3.2	-1.9	-5.4	-6.4	6.1		2.6		-0.8		9.2	3.2		-0.4	-5.6
	Inflation Targeters		-1.8	-2.6	-2.4	-3.2				2.2		-3.0		5.0
Emerging Market			-2.9	-1.9	-0.7			3.1			-2.6		0.4				-0.3	-3.7
	China and India								-6.5
	Emerging Asia		-2.2		-1.4							-0.6
	Emerging Europe		-2.5					7.9	7.6		-8.2		1.6				-0.6	-6.2
	Latin America		-9.3	-9.6		5.8			9.7					14.7
	Other		-6.0	-5.6	-2.2	6.0		8.1				2.2				-4.3		-9.3

Table 4.2

Impact of Surprises—10-Year Bond Yields Responses

			1-year Bond Yields Response to UMP Announcements bps, 2-day cumulative
			United States							United Kingdom			EA			Japan
			LSAP1A	LSAP1B	LSAP2	TWIST	LSAP3	Tapering	Forward Guidance	APP1	APP2	FLS	OMT	Speech	Rate Cut	Forward Guidance	LSAP	QQME
Advanced Economies
	United States		-8.7	-11.6	-4.4	-14.2		8.3		4.4		-1.3		13.7	11.6	2.0
	United Kingdom		-15.7
	Japan		-4.2				21.7				11.4
	Germany		-6.3	-5.7	-2.7	-6.8	-7.4		3.8	3.5		-2.3	0.5	8.7			-2.4
	Euro Area
		Core	-4.8	-4.7	-2.2	-3.8	-7.0	3.3		1.9							-0.5	-4.1
		Periphery	-3.8	-3.8	-1.6	-3.3	-13.9	6.9		-1.4	3.7		-2.9	-15.2			-0.5	-6.3
	EUR Safe Havens		-4.2	-3.2	-1.9	-5.4	-6.4	6.1		2.6		-0.8		9.2	3.2		-0.4	-5.6
	Inflation Targeters		-1.8	-2.6	-2.4	-3.2				2.2		-3.0		5.0
Emerging Market			-2.9	-1.9	-0.7			3.1			-2.6		0.4				-0.3	-3.7
	China and India								-6.5
	Emerging Asia		-2.2		-1.4							-0.6
	Emerging Europe		-2.5					7.9	7.6		-8.2		1.6				-0.6	-6.2
	Latin America		-9.3	-9.6		5.8			9.7					14.7
	Other		-6.0	-5.6	-2.2	6.0		8.1				2.2				-4.3		-9.3

Table 4.3

Impact of Surprises—Stock Price Responses

Table 4.3

Impact of Surprises—Stock Price Responses

			Stock Prices Response to UMP Announcements percentage points, 2-day cumulative
			United States							United Kingdom			EA			Japan
			LSAP1A	LSAP1B	LSAP2	TWIST	LSAP3	Tapering	Forward Guidance	APP1	APP2	FLS	OMT	Speech	Rate Cut	Forward Guidance	LSAP	QQME
Advanced Economies
	United States		-1.5	-2.2		-3.9			5.1		1.4			3.3	1.8	-0.6	-0.6
	United Kingdom					-3.3
	Japan		-1.1		-0.5	-3.4	-3.2	-2.6	3.1	0.8		-0.6		5.1
	Germany		-1.3	-1.0	-0.4	-4.5			3.8	0.7	2.3	-0.4		3.5	2.4	-0.9	-1.3
	Euro Area
		Core	-0.7		-0.3	-3.2	-2.2	-1.4	1.6			-0.4		2.6		1.2	-0.3
		Periphery	-0.7			-3.5	-2.6	-1.6	1.4			-0.3		2.2		0.9	-0.1
	EUR Safe Havens		-1.4	-1.5	-0.3	-2.5		-1.2	3.9	0.5		-0.2		1.7		0.9	-0.2
	Inflation Targeters		-1.2	-1.3	-0.4	-2.2		-2.1	2.9					2.6		1.8	-0.3
Emerging Market			-0.7	-0.6		-1.7		-1.3	2.4			-0.4		1.7		0.6	-0.2
	China and India					-2.8						-0.5	0.2
	Emerging Asia		-0.8	-1.0		-2.5		-3.2	2.6		1.4	-0.4		1.6		1.3	-0.4
	Emerging Europe		-0.8						1.5	0.5		-0.3					-0.1
	Latin America		-1.4	-1.9		-3.3			4.5				-0.6		5.4
	Other		-0.9			-2.6	-1.8	-2.2	3.6			-0.5		1.4		0.9	-0.3

Table 4.3

Impact of Surprises—Stock Price Responses

			Stock Prices Response to UMP Announcements percentage points, 2-day cumulative
			United States							United Kingdom			EA			Japan
			LSAP1A	LSAP1B	LSAP2	TWIST	LSAP3	Tapering	Forward Guidance	APP1	APP2	FLS	OMT	Speech	Rate Cut	Forward Guidance	LSAP	QQME
Advanced Economies
	United States		-1.5	-2.2		-3.9			5.1		1.4			3.3	1.8	-0.6	-0.6
	United Kingdom					-3.3
	Japan		-1.1		-0.5	-3.4	-3.2	-2.6	3.1	0.8		-0.6		5.1
	Germany		-1.3	-1.0	-0.4	-4.5			3.8	0.7	2.3	-0.4		3.5	2.4	-0.9	-1.3
	Euro Area
		Core	-0.7		-0.3	-3.2	-2.2	-1.4	1.6			-0.4		2.6		1.2	-0.3
		Periphery	-0.7			-3.5	-2.6	-1.6	1.4			-0.3		2.2		0.9	-0.1
	EUR Safe Havens		-1.4	-1.5	-0.3	-2.5		-1.2	3.9	0.5		-0.2		1.7		0.9	-0.2
	Inflation Targeters		-1.2	-1.3	-0.4	-2.2		-2.1	2.9					2.6		1.8	-0.3
Emerging Market			-0.7	-0.6		-1.7		-1.3	2.4			-0.4		1.7		0.6	-0.2
	China and India					-2.8						-0.5	0.2
	Emerging Asia		-0.8	-1.0		-2.5		-3.2	2.6		1.4	-0.4		1.6		1.3	-0.4
	Emerging Europe		-0.8						1.5	0.5		-0.3					-0.1
	Latin America		-1.4	-1.9		-3.3			4.5				-0.6		5.4
	Other		-0.9			-2.6	-1.8	-2.2	3.6			-0.5		1.4		0.9	-0.3

Table 4.4

Impact of Surprises—Foreign Exchange Rate Responses

Table 4.4

Impact of Surprises—Foreign Exchange Rate Responses

			Cross FX Rates Response to Suprises of UMP Announcements percentage points, 2-day cumulative
			United States							United Kingdom			EA			Japan
			LSAP1A	LSAP1B	LSAP2	TWIST	LSAP3	Tapering	Forward Guidance	APP1	APP2	FLS	OMT	Speech	Rate Cut	Forward Guidance	LSAP	QQME
Advanced Economies
	United States									0.3		-0.7	1.0	1.7				-1.5
	United Kingdom		0.9	0.4	-0.1	1.4	0.8		-2.9						-0.6			-1.5
	Japan		-0.4	-0.8	-0.3			-1.3	-0.9	0.3		-0.6		2.5	1.1
	Germany				-0.3	1.1	1.7		-2.6			-0.2						-2.0
	Euro Area
		Core			-0.3	1.1	1.7		-2.6			-0.2
		Periphery			-0.3	1.1	1.7		-2.6			-0.2
	EUR Safe Havens		0.2			2.3	0.8		-2.2			-0.3					0.4	-1.5
	Inflation Targeters				-0.3	1.2	1.5		-2.8			-0.2						-1.9
Emerging Market			0.2		-0.8	1.1	1.2		-1.2			-0.4					0.2	-1.7
	China and India		0.9	0.9		0.2	0.4		-0.3	0.3		-0.6		1.2				-1.4
	Emerging Asia					0.6	0.9	0.4	-0.5			-0.5		1.2			0.2	-1.7
	Emerging Europe		0.6		-0.4	1.8	1.9		-3.5					-0.7		0.4	0.2	-2.2
	Latin America		0.6	0.7		2.7	2.1	0.9	-2.1	-0.5		-0.5	0.2				0.3	-2.2
	Other			-0.9		1.8	2.5					-0.6			-0.9	0.4	0.3	-2.4

Table 4.4

Impact of Surprises—Foreign Exchange Rate Responses

			Cross FX Rates Response to Suprises of UMP Announcements percentage points, 2-day cumulative
			United States							United Kingdom			EA			Japan
			LSAP1A	LSAP1B	LSAP2	TWIST	LSAP3	Tapering	Forward Guidance	APP1	APP2	FLS	OMT	Speech	Rate Cut	Forward Guidance	LSAP	QQME
Advanced Economies
	United States									0.3		-0.7	1.0	1.7				-1.5
	United Kingdom		0.9	0.4	-0.1	1.4	0.8		-2.9						-0.6			-1.5
	Japan		-0.4	-0.8	-0.3			-1.3	-0.9	0.3		-0.6		2.5	1.1
	Germany				-0.3	1.1	1.7		-2.6			-0.2						-2.0
	Euro Area
		Core			-0.3	1.1	1.7		-2.6			-0.2
		Periphery			-0.3	1.1	1.7		-2.6			-0.2
	EUR Safe Havens		0.2			2.3	0.8		-2.2			-0.3					0.4	-1.5
	Inflation Targeters				-0.3	1.2	1.5		-2.8			-0.2						-1.9
Emerging Market			0.2		-0.8	1.1	1.2		-1.2			-0.4					0.2	-1.7
	China and India		0.9	0.9		0.2	0.4		-0.3	0.3		-0.6		1.2				-1.4
	Emerging Asia					0.6	0.9	0.4	-0.5			-0.5		1.2			0.2	-1.7
	Emerging Europe		0.6		-0.4	1.8	1.9		-3.5					-0.7		0.4	0.2	-2.2
	Latin America		0.6	0.7		2.7	2.1	0.9	-2.1	-0.5		-0.5	0.2				0.3	-2.2
	Other			-0.9		1.8	2.5					-0.6			-0.9	0.4	0.3	-2.4

8. Evidence points to the effectiveness of conditional forward guidance in managing market expectations of future policy and the importance of a clear central bank communication on exit strategy from highly accommodative monetary policies. At the zero boundary, forward guidance can be used to convince markets that the central bank will keep rates low for longer (allow inflation to go higher) than consistent with its usual policy rule. Results show, for example, that the surprise effect of Fed’s conditional forward guidance lowered expectations of future short-term interest rates, as measured by the 1-year ahead 3-month Libor, and boosted asset prices both domestically and internationally. Most recently, though, market expectations about a faster unwinding of monetary stimulus in the United States have led to a generalized repricing of risks, rising domestic interest rates and weakening equity prices in most emerging markets, among higher foreign exchange rate volatility.

9. The results suggest that the financial market spillovers of unconventional monetary policies vary by market conditions as well as the nature of the intervention. Such policies appear to have been particularly effective in supporting global financial market conditions at times when financial conditions in the major country or region and, likely as a result, globally are particularly volatile. In these situations, unconventional monetary announcements have often led to outsized improvements in global market conditions. This includes the early announcements by the United States and more recent announcements in the euro area. As markets normalize, however, the impacts of policies have been smaller and more ambiguous. However, the results also reflect shifts in the surprise content of the announcements, as shown in Table 4.1. However, evidence mostly relates to the extension of similar bond purchase programs. A substantially different program—either in size or in scope—could still have strong effects, as suggested by the latest BoJ’s QQME announcement.

10. Assessing the overall impact from unconventional policy announcements on a particular asset price in a particular country or region is complicated by the simultaneous response of asset prices in other markets and in other countries. The international transmission of financial shocks (such as a monetary policy surprise) is highly complex, as shocks tend to generate co-movements across asset prices around the world. Results show that the direct impact of a monetary surprise on an asset price in a given country is often magnified through indirect spillovers via third countries (especially other systemic markets) as well as via the response of other domestic assets. Analogously, the direct effect of early U.S. unconventional policy announcements on EM bond yields appears to be almost doubled by indirect spillovers through simultaneous asset price movements in other S4 economies.

11. The impact of unconventional policy announcements on global financial conditions is further complicated by the fact that they often occur when financial volatility is high. Unconventional policies are often launched precisely because market conditions are unsettled, and it is in these circumstances that the financial spillovers tend to be the largest. Whether the spillovers are helpful or not depends not only on the spillovers themselves, but also on the cyclical conditions in recipients. A boost to domestic demand from lower bond yields, higher equity prices, and a reduction in tail risks to the global economy can be helpful if an economy is operating below capacity. However, it may complicate policy making if an economy is overheating, a relevant factor given large differences in cyclical conditions during this recovery. In addition, because decisions on unconventional monetary policies tend to be less easy to predict, they tend to be associated with times when it is more difficult to anticipate the future path of global monetary and financial conditions.

12. Over time, however, the larger impact coming from unconventional monetary policies is likely to be through their effectiveness in guiding market expectations and their impact on underlying market conditions. To the extent that unconventional monetary policies help lower uncertainty and tail risks, they can reduce underlying volatility. If, however, they are simply used as a salve to avoid more fundamental reforms, then they are likely to prolong an environment with high levels of uncertainty that will ultimately put more pressure on other financially open economies. Unconventional policies are a bridge to a solution, not the solution itself.

References

Bauer and Neely (2012) “International Channels of the Fed’s Unconventional Monetary Policy,” Working Paper Series 2012-12, Federal Reserve Bank of San Francisco.
- Search Google Scholar
- Export Citation
Bayoumi and Bui (2011) “Unforeseen Events Wait Lurking: Estimating Policy Spillovers from U.S. To Foreign Asset Prices,” IMF Working Papers 11/183, International Monetary Fund.
- Crossref
- Search Google Scholar
- Export Citation
Chen, Filardo, He and Zhu (2012), “International Spillovers of Central Bank Balance Sheet Policies,” BIS Paper No. 66p.
- Search Google Scholar
- Export Citation
Ehrmann, Fratzscher, and Rigobon (2011) “Stocks, Bonds, Money Markets and Exchange Rates: Measuring International Financial Transmission,” Journal of Applied Econometrics, Vol. 26, No. 6, pp. 948—974.
- Crossref
- Search Google Scholar
- Export Citation
Fratzscher, Lo Duca, and Straub (2012) “A Global Monetary Tsunami? On the Spillovers of U.S. Quantitative Easing,” CEPR Discussion Papers No. 9195.
- Search Google Scholar
- Export Citation
Glick and Leduc (2011) “Are Large-Scale Asset Purchases Fueling the Rise in Commodity Prices?” Economic Letters 2011-10, Federal Reserve Bank of San Francisco.
- Search Google Scholar
- Export Citation
IMF (2011) United States – Spillover Report for the 2011 Article IV Consultation, IMF Country Report No. 11/203, July.
- Search Google Scholar
- Export Citation
IMF (2012) 2012 Spillover Report, IMF Policy Papers, July.
- Search Google Scholar
- Export Citation
IMF (2013) Global Financial Stability Report, April, International Monetary Fund.
- Search Google Scholar
- Export Citation
Joyce, Lasaosa, Stevens, Tong (2011) “The Financial Market Impact of Quantitative Easing,” International Journal of Central Banking, Vol. 6, pp. 113-161.
- Search Google Scholar
- Export Citation
Moore, Nam, Suh, and Tepper (2013) “Estimating the Impacts of U.S. LSAPs on Emerging Market Economies’ Local Currency Bond Markets,” Federal Reserve Bank of New York, Staff Report No. 595.
- Search Google Scholar
- Export Citation
Neely (2012) “The Large-Scale Asset Purchases Had Large International Effects,” Federal Reserve Bank of St. Louis, Working Paper 2010-018D.
- Search Google Scholar
- Export Citation
Sgherri (2013) “(Unconventional) Financial Transmission Across Systemic Advanced Economies,” forthcoming IMF Working Paper.
- Search Google Scholar
- Export Citation

5. Effects of Unconventional Monetary Policies by the Systemic Advanced Economies Using the G-35 Model²⁷

1. This note analyzes the global macroeconomic effects of unconventional monetary easing measures recently taken by the euro area, Japan, the United Kingdom, and the United States. This analysis is based on scenarios simulated with the structural macroeconometric model of the world economy, disaggregated into thirty five national economies, documented in Vitek (2013). Within this framework, each economy is represented by interconnected real, external, monetary, fiscal, and financial sectors. Spillovers are transmitted across economies via trade, financial, and commodity price linkages. Financial linkages are both direct, through cross-border debt and equity portfolio holdings, and indirect via international comovement in asset risk premia.

2. The unconventional monetary easing measures under consideration vary considerably in design across the systemic advanced economies. For the euro area, we consider the Outright Monetary Transactions program foreshadowed by the European Central Bank on July 26 of 2012, announced on August 2 of 2012, and clarified on September 6 of 2012. For Japan, we examine the asset purchase program announced by the Bank of Japan on October 5 of 2010 and subsequently revised many times, in particular on April 3 of 2013. For the United Kingdom, we consider the two asset purchase programs announced by the Bank of England on January 19 of 2009 and October 6 of 2011 together with their numerous expansions, as well as the Funding for Lending Scheme announced on July 12 of 2012. For the United States, we examine the three asset purchase programs announced by the Federal Reserve on November 25 of 2008, August 10 of 2010 and August 31 of 2012 together with their revisions, as well as Operation Twist announced on September 21 of 2011. Most of these unconventional monetary easing measures involved an expansion of the monetary base, with notable exceptions being the Outright Monetary Transactions program and Operation Twist.

3. Our scenarios represent these unconventional monetary easing measures with global money, bond, stock, and foreign exchange market adjustments. In particular, we calibrate changes in short-term nominal market interest rates, long-term nominal market interest rates, equity prices and nominal bilateral exchange rates to match their estimated responses to unconventional monetary easing announcements, in the absence of conventional monetary policy reactions and automatic fiscal stabilizers worldwide. These estimated global financial market responses are based on an event study analysis using the data set documented in Sgherri (2013). They are phased out gradually according to a first order autoregressive process having a coefficient of 0.75, and are generated with sequences of temporary but persistent credit, duration, equity and currency risk premium shocks. We allow for feasible conventional monetary policy reactions to these inferred sequences of risk premium shocks, as well as the full operation of automatic fiscal stabilizers. We assume that conventional monetary policy reactions are constrained by the zero lower bound on the nominal policy interest rate in the Czech Republic, Denmark, the euro area, Japan, Saudi Arabia, Switzerland, the United Kingdom, and the United States.

4. We estimate the global financial market responses to the unconventional monetary easing announcements under consideration with a traditional event study analysis. This event study analysis entails the measurement of absolute or proportional changes in money market interest rates, long-term government bond yields, equity prices and bilateral exchange rates over those windows centered around event dates on which the unconditional probability of observing a larger reduction in the long-term government bond yield in the systemic advanced economy under consideration, or Italy in the case of the euro area, is less than 0.005. This extreme threshold criterion ensures that these measured global financial market adjustments are predominantly reactions to the unconventional monetary easing announcement under consideration, thereby solving an otherwise difficult identification problem. A two day event window is used except for Japan, where a one day window is used to abstract from a major unrelated event. We sum these measured changes across event dates, and normalize them such that the long-term government bond yield in the systemic advanced economy under consideration, or Italy in the case of the euro area, declines by 100 basis points. These relative measures are adopted instead of absolute measures because our event study analysis only captures responses to the unanticipated components of announcements, and misses more gradual adjustments to their anticipated components. Finally, we pool these estimated relative cumulative global financial market impacts across structurally similar economies by calculating group medians. In particular, we group together other advanced economies, emerging economies with open capital accounts, and emerging economies with closed capital accounts. In the case of the euro area, we also group together the members of the periphery. This pooling may be expected to yield mean squared error reductions while achieving robustness to outliers, which are prevalent.

5. Our event study analysis indicates that unconventional monetary easing by the United States, and to a lesser extent the euro area, loosens global financial conditions substantially. In the case of the United States, the unconventional monetary easing measures under consideration reduced money market interest rates and long-term government bond yields substantially worldwide, loosening financial conditions in emerging economies with open capital accounts in particular, while depreciating the dollar moderately with respect to the currencies of other advanced economies. For the euro area, the unconventional monetary easing measure under consideration reduced long-term government bond yields substantially in the periphery and raised them slightly in other advanced economies, while increasing equity prices substantially worldwide and appreciating the euro moderately with respect to the currencies of emerging economies. By comparison, our event study analysis suggests that financial market spillovers from unconventional monetary easing by Japan, and in particular the United Kingdom, are small. In the case of Japan, the unconventional monetary easing measures under consideration reduced long-term government bond yields moderately worldwide, while increasing equity prices enormously domestically and reducing them moderately in the rest of the world, consistent with an enormous improvement in external price competitiveness derived from a depreciation of the yen with respect to other currencies. For the United Kingdom, the unconventional monetary easing measures under consideration reduced money market interest rates moderately worldwide, reduced long-term government bond yields moderately in other advanced economies while raising them moderately in emerging economies, and depreciated the pound slightly with respect to other currencies.

6. Our scenario simulation results indicate that unconventional monetary easing by the United States, and to a lesser extent the euro area, generates large output gains worldwide. Indeed, unconventional monetary easing by the United States raises output growth there by 3.4 percentage points during the first year, by 0.4 to 1.3 percentage points in other advanced economies, by 1.2 to 2.2 percentage points in emerging economies with open capital accounts, and by 1.1 to 1.4 percentage points in emerging economies with closed capital accounts. By comparison, unconventional monetary easing by the euro area raises output growth there by 1.7 percentage points, by 0.3 to 1.4 percentage points in other advanced economies, by 0.5 to 1.5 percentage points in emerging economies with open capital accounts, and by 0.8 to 1.0 percentage points in emerging economies with closed capital accounts. In contrast, unconventional monetary easing by Japan and the United Kingdom tends to generate small negative and positive output spillovers, respectively. To put them into perspective, unconventional monetary easing by the United States and the euro area raises world output growth by 1.7 and 1.1 percentage points, whereas unconventional monetary easing by Japan and the United Kingdom raises world output growth by 0.4 and 0.5 percentage points, respectively. The associated increases in the prices of energy and nonenergy commodities are 20.6 and 13.7 percent for the United States, 13.1 and 8.6 percent for the euro area, 1.8 and 0.2 percent for Japan, and 4.2 and 2.4 percent for the United Kingdom, respectively.

7. These unconventional monetary easing scenarios imply moderate net capital inflows into each systemic advanced economy to finance the deterioration in its current account balance, as well as into some emerging economies with open capital accounts. In particular, unconventional monetary easing by the United States decreases its current account balance ratio by 0.3 percentage points during the first year, while also reducing that of the Czech Republic by 0.7 percentage points, of Korea by 0.4 percentage points, of Turkey by 0.2 percentage points, and of Poland and Thailand by 0.1 percentage points. These current account balance deteriorations are generally financed by net capital outflows from commodity exporters and emerging economies with closed capital accounts. In response to unconventional monetary easing by the United States, the largest increases in current account balance ratios are for Saudi Arabia at 2.2 percentage points and for Norway at 0.7 percentage points.

6. Effects of Quantitative Easing in Systemic Advanced Economies Using GIMF²⁸

The analysis presented here uses the Global Integrated Monetary and Fiscal Model (GIMF) to illustrate the potential spillovers to emerging economies of quantitative easing in advanced economies.

1. GIMF is a multicountry dynamic structural general equilibrium model with optimizing behavior by households and firms, and full intertemporal stock-flow accounting. Frictions in the form of sticky prices and wages, real adjustment costs, liquidity constrained households, along with finite planning horizons of households, mean that there is an important role for monetary and fiscal policy in economic stabilization. GIMF is multi-region, encompassing the entire world economy, explicitly modeling all the bilateral trade flows and their relative prices for each region, including exchange rates. The international linkages in the model allow the analysis of policy spillovers at the regional and global level.²⁹ The standard production version comprises 6 regions: the United States; the euro area; Japan; emerging Asia; Latin America and, as a single entity, the rest of the world. For presentation here, the model’s outputs have been aggregated into two regions, advanced economies (United States, the euro area, and Japan) and emerging economies (emerging Asia and Latin America).

2. The scenarios presented are stylized and are not designed to proxy for any specific episodes of quantitative easing in advanced countries, but rather are designed to illustrate the potential transmission channels and the implications of various policy responses in emerging economies. Four scenarios are presented. In the first scenario, advanced economies experience sharp reductions in private consumption and investment expenditures and it is assumed that monetary policy is unable to respond for a period of two years because the nominal policy interest rate is constrained by the zero interest rate floor (ZIF). In the second scenario, advanced economies pursue quantitative easing. The third scenario builds on the second and in addition to the impact on emerging market exchange rates from advanced economy quantitative easing, it is assumed that capital inflows to emerging markets also reduce their corporate risk premiums. The final scenario assume that emerging market economies prevent the appreciation of their currencies when advanced countries implement quantitative easing and are able to prevent the capital inflows that reduce corporate risk premium.

3. Under the first scenario, the reduction in domestic demand in advanced economies (G3) leads to a reduction in imports from emerging economies (blue solid line in figure). However, with policy rates unchanged in the G3 and inflation declining owing to weak aggregate demand, real G3 real interest rates rise. In addition, emerging economies reduce policy interest rates, further widening the real interest rate differential with G3 economies and G3 currencies appreciate relative to those of emerging markets. Emerging market currency depreciation helps increase the competitiveness of their exports and mitigates the impact of declining aggregate demand in the G3. However, real GDP still falls below baseline in emerging economies.

4. Under the second scenario, the G3 engage in quantitative easing (red dashed line in the figure). The easing in policy significantly reduces the reduction in G3 aggregate demand. However, the impact on demand for emerging market exports is partially offset by relative appreciation in emerging market currency as the real interest rate differential versus the G3 reverses relative to the case of no quantitative easing. However, emerging market exports still recover faster when the G3 engage in quantitative easing. Aside from a slightly larger negative impact in the first year, GDP in emerging markets returns to baseline faster when the G3 pursue quantitative easing.

5. Under the third scenario (green dotted line in figure), capital inflows to emerging markets resulting from quantitative easing are assumed to reduce corporate risk premium lowering the cost of capital for emerging market firms. Consequently, real investment rises notably and the larger capital stock leads firms to demand more labor. The resulting increase in household income raises private consumption expenditure and real GDP in emerging economies rises above baseline prompting a tightening in monetary policy to constrain domestic demand and re-anchor inflation at the target. The policy tightening leads to further currency appreciation, which slows the recovery in exports.

6. Under the final scenario (yellow line in the figure), where emerging economies prevent currency appreciation and capital inflows, the recovery in GDP in emerging economies closely matched that in the second scenario. However, the composition of GDP is quite different. Preventing the currency appreciation helps support emerging economies exports and they fall less initially and recover back to baseline more quickly. Domestic demand, however, declines by more than in all other three scenarios reflecting the fact that monetary policy needs to ease very little as it is assumed that other policy tools are relied on to prevent currency appreciation and capital inflows.

III. Global Capital Flows

Capital flows are experiencing a resurgence in the post-crisis period. Our analysis suggests that both push and pull factors continue to be important for explaining the recent surge; but, that risk in particular has grown in importance, reflecting a dramatic drop in the VIX over the post-crisis period. One interpretation of the results is that the impact of UMP has mostly been felt through its impact on risk perceptions. Factor analysis tends to support this view, with the findings suggesting that a common global factor explains up to one-half of the recent flows to key emerging markets. Case studies, meanwhile, suggest that country authorities have tended to respond with both a mix of foreign exchange intervention and macro-prudential measures.

7. Global Capital Flows in the QE Era³⁰

Recent trends

1. Capital flows to emerging markets (EMs) have increased significantly in the last two decades. As documented elsewhere (IMF (2012) for example), although capital flows into EMs remain small compared to flows into advanced markets (AMs), the size of gross flows has grown dramatically, with substantial increase in portfolio and other investment in the last decade.

2. In the more recent post-crisis period, flows have rebounded strongly, but remain volatile. Following a dramatic slowdown in late 2008/early 2009, capital inflows to most EMs recovered sharply over 2009–10 as market fears ebbed. Indeed, by mid 2011 flows had reached the high levels seen just prior to the crisis. At that point however, increased uncertainty associated with the euro area crisis prompted another decline in inflows lasting until late 2012. Flows have since resumed with an easing of euro area tensions. The volatility of flows has increased since the early years of the great moderation although it is hard to link this with UMP measures per se.

3. The composition of outflows from AMs, especially for the QE countries, have also altered post crisis. As is well documented,³¹ flows into fixed income securities have increased as local debt markets expanded. Gross portfolio investment outflows from QE countries actually declined in recent years, especially from the euro area and the United States, while outflows were on a rise in Japan until 2011. Direction of flows, however, points to a change in QE portfolio investment pattern from QE to non-QE countries. The group of other advanced economies has been the main recipient of QE bond flows. In particular, the U.S. and Japan’s holdings of other non-European advanced economies’ (Australia, Canada, Israel, and New Zealand) bonds almost doubled between 2007 and 2011. Latin American countries were the second largest beneficiaries of the QE bond portfolio reallocations, followed by advanced European countries outside the euro area and the Asian economies. Changes in regional reallocations of equity portfolios varied among QE countries, but generally favored the U.S. equities and, to some extent, equities of other advanced countries. These small compositional changes may have a large impact on flows to EMs.

4. Deleveraging in Europe’s core, meanwhile, has created an opportunity for Asian banks to increase their cross-border claims.³² Banking systems have significantly cut back their cross-border exposures since the start of the GFC. This happened in two phases: (i) a reduction in cross-border activity by many banking systems in the wake of the Lehman Brothers collapse; and (ii) a continued cutback in cross-border claims by euro area banks from the start of the euro area crisis in 2010. Meanwhile, Asian banks have relatively stronger balance sheets and were less affected by the GFC. As a result, these banks have continued to increase their cross-border claims and have helped to offset partially the cutback by euro area banks in Asia, particularly in syndicated lending and project finance areas. But these banks face new vulnerabilities, emerging from a wider use of short-term capital markets to fund the expansion in U.S. dollar exposures.

5. Against this background, we update and extend the Fund’s past empirical work on the determinants of capital flows. In section B, the main results are presented confirming the continued importance of both push and pull factors. Section C complements this analysis with further analytical work that looks at the relative importance of push and pull factors and the initial impacts of UMP through event study analysis. Section D reviews relevant case studies.

Main Drivers of Push and Pull

6. Previous studies have identified that both push and pull factors play important roles in capital flows to emerging markets. Empirical studies, including those from the Fund, have concluded that both push and pull factors are important drivers of capital flows to EMs.³³ In these studies, push factors mostly include U.S. interest rates and risk aversion measures while pull factors generally include EM GDP growth and other EM macroeconomic performance variables.

7. There is only a handful studies that focus on the effect of UMP on capital flows to EMs. Fratzscher, Lo Duca and Straub (2012), which look at global portfolio allocation and the effects of the U.S. UMP, conclude that the effects of U.S. QE measures on capital flows to EMEs have been relatively small compared to other factors, but they have exacerbated the pro-cyclicality of EME capital flows. In late 2008–09, Fed measures contributed significantly to net capital outflows from EMEs—in a period when EMs experienced sudden stops and massive capital flight overall—and then since mid-2009 induced a gradual reversal of these outflows, contributing to the surge in capital inflows to EMs during that period. Hence one key message of the empirical findings of the paper is that U.S. UMP measures have not so much affected the overall magnitude of capital flows to EMs, but have magnified the variability and procyclicality of capital flows.

Baseline push pull regressions

8. Capital flow regressions with push and pull factors are employed in this exercise. The main push factors considered include U.S. interest rates and VIX (a measure of global risk aversion). As UMP lowers the cost of funds along the yield curve when short-term rates already hit zero bound, 10 year yields are used as the primary measure of interest rates. (See below robust check on alternative measures.) Pull factors include GDP growth, inflation and economy size in the capital recipient countries.

9. Panel fixed effect regressions are run with quarterly data from 1990 to 2012 Q3 of 42 EMs. The dependent variable is the log of gross capital flows, adjusted with a constant for all countries to keep the value positive. To minimize endogeneity, both GDP growth and inflation are entered with one quarter lag.

10. The results suggest that the effects of push factors have changed over time with increasing importance of risk aversion in the post-crisis period (Table 7.1). As expected, both U.S. interest rate and VIX have strong and significant effects on capital flows to EMs. In the post crisis period, the strength of the relationship between interest rates and capital flows has significantly weakened and has turned positive. This could be interpreted that the signaling effects of future growth of the yield could be dominant in the post-crisis period. The effect of VIX on capital flows to EMs has however increased over the post-crisis period. This is consistent with our priors, where we have seen VIX, in particular, as driving market sentiment (see below).

Table 7.1

Baseline Regressions

^{^1/}Post crisis dummy is equal from one from 2008q4

^{^2/}Average for 1990s and post 2000

Table 7.1

Baseline Regressions

VARIABLES	(1)	(2)	(3)	(4)
	Full sample	Full sample with post crisis dummy on both sides	Pre crisis sample	Post crisis sample
PUSH
US 10 year yield	-0.0146***	-0.0112***	-0.00914***	0.0136**
	(0.0038)	(0.004)	(0.0032)	(0.0061)
Log VIX	-0.0472***	-0.0423***	-0.0422***	-0.0844***
	(0.0102)	(0.010)	(0.0102)	(0.0233)
Post crisis dummy ^1/		0.0546
		(0.085)
Post crisis * US 10 yr yield		0.0288***
		(0.009)
Post crisis * Log VIX		-0.0403*
		(0.021)
PULL
Recipients’ GDP Growth (t-1)	0.000231***	0.000200***	0.000212***	0.00288**
	(0.0001)	(0.000)	(0.0001)	(0.0012)
Recipients’ log average nominal GDP ^2/	0.0168**	0.00468***	0.0220***
	(0.0066)	(0.001)	(0.0057)
Recipients’ inflation (t-1)	-1.91E-05	0.0161**	-1.26E-05	0.000239
	(0.0000)	(0.006)	(0.0000)	(0.0006)
Post crisis * Recipients’ GDP Growth (t-1)		-1.92e-05*
		(0.000)
Constant	4.123***	4.089***	4.058***	4.226***
	(0.0475)	(0.042)	(0.0362)	(0.0781)
Observations	2,892	2,892	2,300	592
R-squared	0.11	0.138	0.098	0.136
Number of IFS	42	42	42	42

^{^1/}Post crisis dummy is equal from one from 2008q4

^{^2/}Average for 1990s and post 2000

Table 7.1

Baseline Regressions

VARIABLES	(1)	(2)	(3)	(4)
	Full sample	Full sample with post crisis dummy on both sides	Pre crisis sample	Post crisis sample
PUSH
US 10 year yield	-0.0146***	-0.0112***	-0.00914***	0.0136**
	(0.0038)	(0.004)	(0.0032)	(0.0061)
Log VIX	-0.0472***	-0.0423***	-0.0422***	-0.0844***
	(0.0102)	(0.010)	(0.0102)	(0.0233)
Post crisis dummy ^1/		0.0546
		(0.085)
Post crisis * US 10 yr yield		0.0288***
		(0.009)
Post crisis * Log VIX		-0.0403*
		(0.021)
PULL
Recipients’ GDP Growth (t-1)	0.000231***	0.000200***	0.000212***	0.00288**
	(0.0001)	(0.000)	(0.0001)	(0.0012)
Recipients’ log average nominal GDP ^2/	0.0168**	0.00468***	0.0220***
	(0.0066)	(0.001)	(0.0057)
Recipients’ inflation (t-1)	-1.91E-05	0.0161**	-1.26E-05	0.000239
	(0.0000)	(0.006)	(0.0000)	(0.0006)
Post crisis * Recipients’ GDP Growth (t-1)		-1.92e-05*
		(0.000)
Constant	4.123***	4.089***	4.058***	4.226***
	(0.0475)	(0.042)	(0.0362)	(0.0781)
Observations	2,892	2,892	2,300	592
R-squared	0.11	0.138	0.098	0.136
Number of IFS	42	42	42	42

^{^1/}Post crisis dummy is equal from one from 2008q4

^{^2/}Average for 1990s and post 2000

11. The size of the coefficients, however, is not very large. A one standard deviation decline in the VIX index—corresponding to a 30 percent change–is associated with an increase in capital flows of just over 2 percent. The results for interest rates are equally small (see chart). This suggests that other country-specific factors are quite influential.

How well do the regressions explain the post crisis period?

12. The regression explains the surge in capital flows in the post-crisis period better than it does in the pre-crisis period. To investigate the explanatory power of the regression, forecast errors are computed for the full sample period, with error terms aggregated across countries for each time period (see text chart).³⁴ A positive error term indicates that countries are receiving higher capital flows than predicted by the regression coefficients. The chart shows that in the pre-crisis period, aggregate capital flows were significantly higher than predicted. In contrast, the surge in the post-crisis period is better explained by the regression as the surge was accompanied by both a declining 10-year yield and a reduction in risk aversion (the VIX).

13. Still, there are many differences across countries, with the regression substantially underestimating flows for several high profile cases. For both Brazil and India, the regression under predicts flows in both the pre-crisis and post-crisis period. One interpretation is that the regression is missing an important pull factor that may have changed recently; alternatively, the current inflows received by these countries is excessive. Looking at the fuller sample, the results are more balanced with several countries also reporting lower flows than predicted, especially in EM Europe and the Middle East.

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Countries

Series

About

Resources

Abstract

Cross-Country Studies

I. Stabilization Dividends

1. Spillovers from Policy Uncertainty in the United States and Europe1

Uncertainty and economic activity

Measuring economic policy uncertainty

The evolution of U.S. and European policy uncertainty

Spillovers from policy uncertainty

The mechanics of policy uncertainty spillovers

What happens when policy uncertainty subsides?

Conclusion

References

2. Effects of Stabilizing Policies in the Euro Area and the US12

3. Market-Based Indicators of Systemic Risks15

Funding stress

Equity and bond market volatility

Swap market volatility

Currency volatility

Likelihood of distress and value-at-risk of G-SIBs

II. Unconventional Monetary Policies

4. Impact of Unconventional Monetary Policies on International Asset Prices19

References

5. Effects of Unconventional Monetary Policies by the Systemic Advanced Economies Using the G-35 Model27

6. Effects of Quantitative Easing in Systemic Advanced Economies Using GIMF28

III. Global Capital Flows

7. Global Capital Flows in the QE Era30

Recent trends

Main Drivers of Push and Pull

Baseline push pull regressions

How well do the regressions explain the post crisis period?

1. Spillovers from Policy Uncertainty in the United States and Europe¹

2. Effects of Stabilizing Policies in the Euro Area and the US¹²

3. Market-Based Indicators of Systemic Risks¹⁵

4. Impact of Unconventional Monetary Policies on International Asset Prices¹⁹

5. Effects of Unconventional Monetary Policies by the Systemic Advanced Economies Using the G-35 Model²⁷

6. Effects of Quantitative Easing in Systemic Advanced Economies Using GIMF²⁸

7. Global Capital Flows in the QE Era³⁰