## CHAPTER 3 ARE COUNTRIES LOSING CONTROL OF DOMESTIC FINANCIAL CONDITIONS?

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### Purpose, central question, and conceptual framing
- Central question: To what extent can individual countries steer domestic financial conditions in a globally integrated financial system?
- Two distinct implications of global spillovers:
  - Increased influence of external shocks on domestic financial conditions as countries integrate (does not by itself imply loss of policy autonomy).
  - Weakening of monetary policy transmission when international markets increasingly set longer‑term bond yields, reducing responsiveness to domestic short‑term rates.
- Key conceptual points:
  - Financial conditions summarize price and nonprice costs of credit and the state of financial variables influencing economic behavior.
  - Distinction between fundamentals‑driven comovement and non‑fundamental spillovers (investor sentiment, herd behavior, risk management constraints).
  - Financial trilemma and the “global financial cycle” (Miranda‑Agrippino and Rey 2015) are guiding reference points.

### Methodology and construction of Financial Conditions Indices (FCIs)
- Scope and data:
  - FCIs estimated for 43 advanced and emerging market economies during 1990–2016 (monthly frequency), depending on data availability.
- Model and estimation:
  - Time‑varying parameter factor‑augmented vector autoregression model (TVP‑FAVAR) following Koop and Korobilis (2014) with elements from Primiceri (2005) and Doz, Giannone, and Reichlin (2011).
  - Model form: x_t = λ^y_t Y_t + λ^f_t f_t + u_t; [Y_t  f_t]' = B_{1,t} [Y_{t–1}  f_{t–1}]' + B_{2,t} [Y_{t–2}  f_{t–2}]' + ... + ε_t
  - Advantage: purges FCIs of (current) macroeconomic conditions and allows relationships to evolve over time.
  - Limitation: FCIs are purged only of contemporaneous macroeconomic conditions; expectations of future macroeconomic developments may remain reflected in financial variables.
- Variable selection principles and typical variables included:
  - Exclude exchange rate and direct measures of international financing to avoid overstating global influence.
  - Typical variables: corporate spreads, term spreads, interbank spreads, sovereign spreads, change in long‑term interest rates, equity returns, house price returns, equity return volatility, change in market share of the financial sector, and credit growth; where available, survey‑based lending standards.
- Modeling tradeoffs:
  - Including more data does not always yield better results; variable choice guided by conceptual and practical considerations.

### FCIs and predictive power for GDP growth
- FCIs are significant predictors of future GDP growth across countries and flag downside risks more clearly than upside outcomes.
- Nonlinearity/state dependence:
  - At the one‑year‑ahead horizon, the negative coefficient at the 10th percentile (when growth is well below –½ percent) is about three times as large in absolute terms relative to the coefficient corresponding to the median (when growth is about 3½ percent).
  - A one standard deviation increase in the FCI (corresponding to tighter financial conditions) is associated with a 0.4 percentage point decrease in median future GDP growth at a one‑year horizon.
- Historical forecast illustration:
  - Based on information as of the second quarter of 2006, the model augmenting past growth rates with FCIs attributes approximately a 45 percent probability to the actual one‑year‑ahead growth outturn (6 percent), more than twice the probability from the model using only growth rates.
  - Using information up to the third quarter of 2008, the model with FCIs assigns higher probability to downturns and better signals the actual GDP contraction in the third quarter of 2009.

### Global factors, factor analysis, and magnitude of global influence
- Factor analysis:
  - Time series factor analysis (TSFA) on a panel of 43 countries, 1995–2016, fitted one‑factor and three‑factor models.
  - Three latent factors identified: “Emerging market” factor, “Euro area” factor, and “Global financial crisis” factor.
  - A single global factor (global financial conditions) closely tracks the U.S. FCI and the VIX.
- Explanatory power and statistics (preserved exactly):
  - On average, the one‑factor model explains about 30 percent of the variance of the FCIs in the sample.
  - On average, the three‑factor model explains about 41 percent of the variance of the FCIs in the sample.
  - The additional variance explained by the two regional factors (beyond the single global factor) is about 10 percentage points on average.
  - The average correlation between the U.S. FCI and the two measures of global financial conditions and the VIX is 82 percent.
  - On average, global financial conditions account for about 30 percent of the variation in financial conditions across countries; in several economies this reaches almost 70 percent.
  - Small open advanced economies appear more synchronized with global financial conditions than emerging market economies.
  - No conclusive evidence that the global factor has gained significant influence over the past two decades; trajectory broadly flat with cyclical patterns.

### Country characteristics and drivers of sensitivity to global shocks
- Variables influencing sensitivity to the U.S. FCI (used as proxy for global financial conditions) include:
  - Financial linkages with the United States (FDI, banking, portfolio).
  - Financial openness and development (equity and bond market depth).
  - Institutional quality (rule of law).
  - Exchange rate regime.
- Key empirical findings (summary of estimated signs and significance):
  - Direct effect of U.S. FCI on domestic FCIs: estimated positive and significant (*** p < 0.01).
  - FDI linkages with the United States: estimated positive and significant (** p < 0.05) — stronger FDI linkages → greater synchronization.
  - Portfolio and banking linkages: estimated sign mixed (+–).
  - Trade linkages with the United States: estimated positive sign (++).
  - Trade openness: estimated positive and significant (** p < 0.05).
  - Financial openness: estimated positive sign (++).
  - Exchange rate flexibility: expected negative sign; estimated sign mixed (–+).
  - Financial development: expected negative sign; estimated negative and significant (** p < 0.05) — greater domestic financial development associated with attenuated impact of global shocks.
  - Rule of law: expected negative sign; estimated negative sign (––).
- Interpretation notes:
  - Trade linkages to the United States do not seem to matter, while trade relationships with the rest of the world appear relevant (possibly capturing indirect financial linkages).
  - No clear pattern emerges for exchange rate regime and capital account openness; findings broadly consistent with prior literature.

### Relative roles of global financial shocks versus domestic monetary policy
- Econometric approach:
  - Panel VARs jointly model output, consumer prices, policy rates, domestic FCIs, and a measure of global financial conditions proxied by the U.S. FCI; baseline ordering for Cholesky decomposition: U.S. FCI, industrial production growth, inflation, domestic FCI, change in domestic policy rate.
  - Results robust to alternative specifications and complementary identification strategies for monetary policy shocks (country‑level VARs and GK identification).
- Shares of FCI variation attributed to shocks (preserved exactly):
  - On average, about 21 percent of the variation in domestic FCIs across small open economies with flexible exchange rates is attributed to global financial shocks.
  - Domestic monetary policy shocks account for about 15 percent of the fluctuations in FCIs.
  - In alternative estimations (country‑by‑country VAR), shocks to global financial conditions and to monetary policy account, on average, about 40 percent and 12 percent of countries’ domestic FCI variations, respectively.
  - For four small open advanced economies (Australia, New Zealand, Norway, Sweden) using better‑identified monetary policy shocks, the share of FCI variation characterized by fluctuations in global financial conditions and domestic monetary policy is, on average, 15 percent and 33 percent, respectively, for these four countries.
- Dynamics of responses:
  - Global financial shocks affect local financial conditions faster and more strongly than changes in domestic policy rates.
  - Local policy rate changes have an appreciable effect on local FCIs, but timely and effective monetary policy reactions are often difficult; policy intended to offset an unwelcome global shock “may have to react very quickly and strongly, with potentially undesirable side effects.”
  - Emerging market economies’ FCIs tend to be somewhat more sensitive to global financial conditions but less responsive to changes in the domestic monetary policy stance.

### Cross‑country heterogeneity, time patterns, and robustness
- Cross‑country heterogeneity:
  - Importance of global financial shocks for domestic financial conditions varies considerably across countries; in a few emerging market economies, the proportion of FCI variability attributable to global financial conditions exceeds 60 percent.
  - Fluctuations in global financial conditions are associated with a greater share of FCI variability in countries relatively more financially integrated with the rest of the world; differences are greater for emerging markets.
- Time comparisons:
  - Comparing precrisis (2001–07) and postcrisis (2010–16) samples, "the share of domestic financial conditions attributed to global financial conditions appears to be broadly stable over the two periods."
  - The 2001–07 and 2010–16 variance decompositions are not statistically different at the 95 percent level.
- Robustness and identification:
  - Findings robust to inclusion of exchange rate terms, global industrial production growth, commodity prices, and measures of global interest rates as exogenous controls.
  - Complementary identification of monetary policy shocks (Gertler and Karadi 2015; Gürkaynak, Sack, and Swanson 2005) yields broadly similar results in country case studies.

### Policy implications and recommendations
- Main implications:
  - A single global factor — global financial conditions, which move with the U.S. FCI and measures of global risk such as the VIX — summarizes a significant share of global financial‑condition dynamics.
  - Despite the influence of global financial conditions, countries on average remain able to steer domestic financial conditions; monetary policy still matters.
  - Domestic financial conditions respond faster and more strongly to global financial shocks than to domestic monetary policy changes, making timely and effective monetary responses challenging.
- Recommended policy actions:
  - Use macroprudential measures to contain buildup of vulnerabilities that increase sensitivity to external financial shocks.
  - Consider temporary capital flow management measures when disruptive outflows threaten financial stability.
  - Promote financial deepening and develop a local investor base (banks and nonbanks), and foster greater equity and bond market depth and liquidity to dampen the impact of external financial shocks.
  - Emerging market economies should guard against risks associated with sharp changes in global financial conditions.

### Annex and methodological notes
- Annex 3.1 — FCIs estimated for 1990–2016 at monthly frequency for 43 countries using 10 financial indicators; methodology builds on Koop and Korobilis 2014 and Primiceri 2005.
- Annex 3.2 — Time series factor analysis (TSFA) for 43 countries, 1995–2016; one‑factor explains about 30 percent of variance on average; three‑factor explains about 41 percent on average; regional factors add about 10 percentage points.
- Additional methodological references and literature cited included throughout the chapter.

*Source: CHAPTER 3 ARE COuNTRIES LOSING CONTROL OF DOMESTIC FINANCIAL CONDITIONS?, International Monetary Fund | April 2017*

### Introduction

### Introduction

### Purpose and central question
- To what extent can individual countries steer domestic financial conditions in a globally integrated financial system?
- Recent debate: concern that global factors’ greater potential impact on domestic asset prices and credit leave policymakers little room to influence domestic financial conditions according to domestic objectives (Rey 2013).
- Narrower focus in literature: whether monetary policy has lost its ability to independently guide domestic interest rates, even in countries with floating exchange rate regimes.

### Concept and role of financial conditions
- Financial conditions broadly reflect how easy it is to obtain financing; they summarize price and nonprice (such as terms and conditions) costs of credit for various agents.
- Alternative view: financial conditions as the current state of financial variables that influence economic behavior and future economic activity.
- Financial conditions matter because:
  - Monetary policy largely seeks to influence inflation and output through effects on financial market variables (including bank credit volumes, collateral valuations, and term premiums), along with direct effects through policy rates.
  - If the mapping from policy rates to a range of financial variables is not unique or stable, tracking financial conditions helps predict monetary policy impact (Dudley 2010).
  - Measures of financial conditions have been shown to be reliable predictors of economic activity and useful in predicting downside risks to GDP growth and detecting buildup of financial vulnerabilities.

### Two distinct implications of global spillovers
- Distinguish between:
  - Increased influence of external shocks on domestic financial conditions as countries integrate into the global economy (policymakers must respond to a broader range of developments). This alone does not imply loss of policy autonomy (Disyatat and Rungcharoenkitkul 2016).
  - Weakening of monetary policy transmission channels when international markets increasingly set longer-term bond yields, reducing responsiveness to domestic short-term rates and exposing countries to shocks unwarranted by domestic fundamentals.

### Chapter objectives and methodology
- Examine importance of common global components of domestic financial conditions, their evolution over time, and key drivers.
- Explore country characteristics influencing the extent to which domestic financial conditions move with global factors and the ability of monetary policy to influence domestic financial conditions.
- Develop new financial conditions indices (FCIs) comparable across a large set of advanced and emerging market economies.
- FCIs consist of domestic financial variables such as corporate, interbank, and term spreads; equity and house price returns; equity return volatility; and credit growth.
- An attempt is made to purge the FCIs of (contemporaneous) macroeconomic conditions to assess how much “unwarranted” global financial shocks affect domestic financial conditions.

### Highlights and key findings
- The new FCI measures appear to signal downside risks to GDP well; economic contractions are more clearly associated with a preceding change in financial conditions in contrast to expansions.
- A single factor, “global financial conditions,” appears to account for a large share of variation in domestic financial conditions around the world; this factor moves in tandem with the U.S. FCI and measures of global risk, such as the Chicago Board Options Exchange Volatility Index (VIX).
- There is no conclusive evidence that this global factor has gained significant influence over the past two decades.
- Financial linkages (such as cross-country investments) are the most reliable indicator of global financial conditions’ influence on local FCIs.
- Greater financial development can reduce the sensitivity of domestic FCIs to global financial shocks.
- About 20 to 40 percent of the variation in domestic FCIs across countries can be attributed to global financial conditions, with domestic factors accounting for the rest.
- Monetary policy shocks account for about 15 percent of the variation across countries with flexible exchange rates, indicating that changes in the monetary policy stance still can matter for domestic financial conditions even amid exposure to external factors.

### Policy implications and recommendations
- Even with a sizable impact from global financial shocks, on average countries appear able to influence their own financial conditions; they generally have scope to use monetary policy.
- Local financial conditions react more rapidly to global financial shocks than to changes in domestic policy rates, so timely policy responses may often be difficult.
- Emerging market economies need to guard against risks associated with sharp changes in global financial conditions.
- Policy tools and actions to mitigate vulnerability to global shocks:
  - Macroprudential measures to contain potentially lingering vulnerabilities that leave domestic financial conditions sensitive to external shocks.
  - Temporary capital flow management measures when disruptive outflows threaten financial stability (as noted in IMF 2016).
  - Promote financial deepening and develop a local investor base (both banks and nonbanks) to help soften the blow of global financial shocks.

### Overview of transmission mechanisms and measurement
- Monetary policy transmission channels (two broad categories):
  - Traditional/New Keynesian channels: changes in short-term policy rates and expectations alter longer-term rates, affecting consumption, investment, and trade via exchange rates.
  - Nontraditional channels: imperfections in credit supply arising from institutional constraints and informational asymmetries (examples: balance sheet channel; bank capital channel; risk-taking channels).
- Because of market incompleteness and heterogeneous agents, the risk-free rate is not an adequate statistic for funding costs or for assessing the impact of monetary policy; FCIs aim to capture average funding costs and the prevalence of credit constraints and external financing premiums.
- Financial conditions can be transmitted across countries through multiple channels: changes in credit volumes and capital flows, comovements in risk premiums affecting collateral valuation and borrowing constraints, and exchange rate–induced changes in financial conditions.
- The Mundell-Fleming “trilemma” remains a guiding framework: policymakers can choose only two of (1) fixed exchange rates, (2) free international capital mobility, and (3) monetary autonomy; greater exchange rate flexibility typically provides some degree of flexibility in steering short-term interest rates.

*Source: ch3 - Introduction (ch3 - Introduction).*

### CHAPTER 3 ARE COuNTRIES LOSING CONTROL OF DOMESTIC FINANCIAL CONDITIONS?

### CHAPTER 3 ARE COuNTRIES LOSING CONTROL OF DOMESTIC FINANCIAL CONDITIONS?

### Overview: question and conceptual framing
- Two alternative views examined:
  - Global financial integration does not, by itself, imply that countries lose their ability to steer their domestic financial conditions.
  - Global financial integration may make it harder for domestic policymakers to control domestic financial conditions—for example, by hampering the transmission of monetary policy or limiting the effectiveness of prudential policies; the speed at which foreign shocks affect local financial conditions makes it difficult to react in a timely and effective manner.
- Conceptual distinction emphasized:
  - Financial conditions that comove across countries can reflect fundamentals (and be optimal domestically) or reflect non‑fundamental financial frictions (investor sentiment, herd behavior, risk management constraints, regulations).
  - If domestic financial conditions are predominantly influenced by spillovers not driven by fundamentals, this would indicate a “lack of control” by policymakers because policymakers will likely attempt to counteract such shocks but may lack effective or timely tools to offset them.
- Important conceptual reference points preserved:
  - “global financial cycle” (Miranda‑Agrippino and Rey 2015).
  - Financial trilemma: only two of (1) national autonomy over financial policies, (2) international financial integration, and (3) financial stability can be achieved simultaneously (Shoenmaker 2013).

### Constructing Financial Conditions Indices (FCIs)
- Scope and data:
  - Comparable monthly FCIs estimated for 43 advanced and emerging market economies during 1990–2016, depending on data availability.
- Methodology:
  - A time‑varying parameter factor‑augmented vector autoregression model (TVP‑FAVAR) based on Koop and Korobilis (2014) is used to estimate latent FCIs.
  - Key advantages of TVP‑FAVAR:
    - Jointly considers dynamic interactions of the FCI and macroeconomic fundamentals and aims to purge the FCI of the effects of macroeconomic conditions.
    - Time‑varying parameters allow the model to account for evolving relationships between macroeconomic and financial variables over time and changes in (policy) regimes.
  - Limitation noted: FCIs are initially purged only of the effect of current macroeconomic conditions; expectations of future macroeconomic developments may still be reflected in financial variables and are not purged in baseline estimations.
- Variable selection principles:
  - Conceptual: exclude variables measuring ease of access to finance on international markets to focus on indirect channels whereby global factors drive domestic financial conditions; exclude the exchange rate from the FCI to avoid overstating global influence.
  - Practical: choose variables consistent across countries and reflecting as many segments of the financial system as possible (equity, housing, bond, interbank markets).
- Typical variables included:
  - Various interest rates and spreads (changes in longer‑term interest rate, corporate, interbank, and term spreads).
  - Asset price returns (equity and house price returns).
  - Equity return volatility.
  - Credit growth.
  - Where available, survey‑based information (lending standards).
- Modeling tradeoffs:
  - Including more data does not always yield better results (Boivin and Ng 2006); choice of variables guided by conceptual/practical considerations.

### Financial conditions around the world: salient patterns and country examples
- U.S. benchmark:
  - The U.S. FCI developed here closely tracks counterparts developed by the IMF and other institutions (Federal Reserve Banks of Chicago and Kansas City) during 1990–2016.
  - Historical U.S. episodes captured:
    - Tightening after Long‑Term Capital Management collapse (1998).
    - Tightening during the dot‑com crash (2000) and subsequent corporate scandals (Arthur Andersen, WorldCom).
    - Unprecedented spike during the global financial crisis (2008).
    - Gradual uptrend more recently while still indicating broadly accommodative conditions.
- Selected other economies (stylized facts):
  - Russia: FCI tightened dramatically during 1998; tightening then outpaced that during the global financial crisis.
  - Korea: FCI tighter during the global financial crisis than during the Asian financial crisis (1997–98).
  - Chile: global financial crisis represents the sharpest spike in the FCI over the past two decades.
  - Netherlands (small open euro‑area economy): financial conditions tightened to almost the same extent during the euro area crisis and the global financial crisis.
- Common drivers across countries:
  - Interbank and corporate spreads, equity return volatility, and changes in house prices are top contributors to countries’ FCIs for both advanced and emerging market economies.

### Financial conditions and GDP growth: predictive relationships and nonlinearities
- FCIs as predictors of GDP:
  - Domestic FCIs are significant predictors of future GDP growth across countries.
  - The inverse relationship between FCIs and future GDP growth is state‑dependent: stronger during economic contractions than during expansions.
- Quantitative indicators preserved exactly:
  - At the one‑year‑ahead horizon, the negative coefficient at the 10th percentile (when growth is well below –½ percent) is about three times as large in absolute terms relative to the coefficient corresponding to the median (when growth is about 3½ percent).
  - A one standard deviation increase in the FCI (corresponding to tighter financial conditions) is associated with a 0.4 percentage point decrease in median future GDP growth at a one‑year horizon.
- Historical illustration:
  - Two dates considered: second quarter of 2006 (precrisis expansion) and third quarter of 2008 (onset of the global financial crisis) demonstrate the predictive power of FCIs for future economic downturns.

### Empirical challenges and interpretation caveats
- Distinguishing fundamentals‑driven comovement from non‑fundamental spillovers is empirically difficult; purging FCIs of macroeconomic fundamentals is conceptually desirable but limited by data and model constraints.
- Excluding exchange rates and direct measures of international funding in the FCI is intentional to avoid overstating the direct influence of global financial conditions on domestic financial conditions.
- FCIs are latent constructs; different construction methods and variable choices can influence measured FCIs and their interpretation.

*Italic: Source — CHAPTER 3 ARE COuNTRIES LOSING CONTROL OF DOMESTIC FINANCIAL CONDITIONS?, International Monetary Fund | April 2017*

### CHAPTER 3 ARE COuNTRIES LOSING CONTROL OF DOMESTIC FINANCIAL CONDITIONS?

### CHAPTER 3 ARE COuNTRIES LOSING CONTROL OF DOMESTIC FINANCIAL CONDITIONS?

### FCIs improve forecasts of future GDP and flag downside risks
- Two empirical one-year-ahead forecasting models are compared: one using current and past growth rates alone, and one augmenting the first model by including FCIs (financial conditions indices).
- Based on information available as of the second quarter of 2006, the model with the FCIs attributes approximately a 45 percent probability to the actual one-year-ahead growth outturn (6 percent), which is more than twice the probability generated by the model that uses only growth rates.
- Using information up to the third quarter of 2008, the distribution from the model with FCIs exhibits a long left tail and assigns a higher probability to economic downturns, more starkly signaling the actual GDP contraction in the third quarter of 2009.
- Figure-based evidence: quantile regressions and conditional probability distributions show that FCIs contain valuable information about the future state of the economy and are particularly useful in flagging downside risks to economic activity.

### Global factors summarizing financial conditions across countries
- A statistical dynamic factor model identifies three latent factors that summarize the main patterns across countries’ FCIs:
  - “Emerging market” factor
  - “Euro area” factor
  - “Global financial crisis” factor
- Although each factor spikes during the global financial crisis, the emerging market and euro area factors also depict markedly tighter financial conditions during the late 1990s and around 2012, respectively.
- A single global factor (global financial factor or global financial conditions) adequately summarizes financial conditions across countries and closely tracks movements in the U.S. FCI and the VIX.
- The average correlation between the U.S. FCI and the two measures of global financial conditions and the VIX is 82 percent.

### Magnitude of global influence on domestic financial conditions
- On average, global financial conditions account for about 30 percent of the variation in financial conditions across countries; in several economies this reaches almost 70 percent.
- The three-factor model explains a larger proportion of FCI variability than the single-factor model—greater than 40 percent in aggregate.
- Small open advanced economies appear more synchronized with global financial conditions than emerging market economies.
- Over the past two decades, there is no clear evidence of a marked upward trend in the share of variation attributable to global financial conditions; the trajectory is broadly flat with cyclical patterns, especially during the global financial crisis.

### Country characteristics associated with sensitivity to global financial shocks
- The U.S. FCI is used as a proxy for global financial conditions given the prominence of the United States in the international monetary system.
- Variables considered that influence sensitivity of domestic FCIs to U.S. FCI include:
  - Financial linkages with the United States (FDI, banking, portfolio)
  - Financial openness and development (including equity and bond market depth)
  - Institutional quality (rule of law)
  - Exchange rate regime
- Key empirical findings (Table 3.1 summary):
  - Direct effect of U.S. FCI on domestic FCIs: estimated positive and significant (*** p < 0.01).
  - Interaction effects:
    - FDI linkages with the United States: estimated positive and significant (** p < 0.05) — stronger FDI linkages → greater synchronization with global financial conditions.
    - Portfolio linkages with the United States: estimated sign mixed (+–).
    - Banking linkages with the United States: estimated sign mixed (+–).
    - Trade linkages with the United States: estimated positive sign (++).
    - Trade openness: estimated positive and significant (** p < 0.05).
    - Financial openness: estimated positive sign (++).
    - Exchange rate flexibility: expected negative sign; estimated sign mixed (–+).
    - Financial development: expected negative sign; estimated negative and significant (** p < 0.05) — greater domestic financial development, especially financial markets depth (equity, bond), is associated with attenuated impact of global shocks on domestic FCIs.
    - Rule of law: expected negative sign; estimated negative sign (––).
- Trade linkages to the United States do not seem to matter, while trade relationships with the rest of the world appear relevant (possibly capturing indirect financial linkages).
- No clear pattern emerges for exchange rate regime and capital account openness; findings broadly consistent with prior literature cited.

### Relative roles of global financial shocks and domestic monetary policy
- Complementary econometric approaches based on VAR models jointly model output, consumer prices, policy rates, domestic FCIs, and a measure of global financial conditions proxied by the U.S. FCI.
- For small open advanced and emerging market economies with flexible exchange rates:
  - Global financial shocks have a notable impact on domestic financial conditions.
  - Monetary policy still accounts for a notable share of the variation in domestic financial conditions.
- Methodological notes:
  - Baseline panel VAR ordering: U.S. FCI, industrial production growth, inflation, domestic FCI, and change in the domestic monetary policy rate; shocks identified using a Cholesky decomposition.
  - Results are robust to alternative specifications (levels vs changes, inclusion of exchange rate terms, inclusion of global industrial production growth, commodity prices, and measures of global interest rates as exogenous controls).
  - Complementary identification of monetary policy shocks is discussed; average responses from country-level VARs yield broadly similar findings.

*Source: CHAPTER 3 ARE COuNTRIES LOSING CONTROL OF DOMESTIC FINANCIAL CONDITIONS?, International Monetary Fund | April 2017.*

### Annex 3.4 for details.

### Annex 3.4 for details.

### Response of domestic financial conditions to shocks
- Global financial shocks affect local financial conditions faster and more strongly than changes in domestic policy rates.
- Local policy rate changes have an appreciable effect on local FCIs, but timely and effective monetary policy reactions may often be difficult because a policy intended to offset an unwelcome global shock "may have to react very quickly and strongly, with potentially undesirable side effects."
- Emerging market economies’ FCIs tend to be somewhat more sensitive to global financial conditions but less responsive to changes in the domestic monetary policy stance.

### Share of FCI fluctuations attributable to global financial and monetary policy shocks
- On average, about 21 percent of the variation in domestic FCIs across small open economies with flexible exchange rates is attributed to global financial shocks.
- Domestic monetary policy shocks account for about 15 percent of the fluctuations in FCIs.
- In alternative estimations (country-by-country VAR), shocks to global financial conditions and to monetary policy account, on average, about 40 percent and 12 percent of countries’ domestic FCI variations, respectively.
- For four small open advanced economies (Australia, New Zealand, Norway, Sweden) using better-identified monetary policy shocks, the share of FCI variation characterized by fluctuations in global financial conditions and domestic monetary policy is, on average, 15 percent and 33 percent, respectively, for these four countries.

### Cross-country heterogeneity and time patterns
- The importance of global financial shocks for domestic financial conditions varies considerably across countries; in a few emerging market economies, the proportion of FCI variability accounted for by global financial conditions exceeds 60 percent.
- Fluctuations in global financial conditions are associated with a greater share of FCI variability in countries that are relatively more financially integrated with the rest of the world; these differences are greater for emerging market economies.
- Comparing precrisis (2001–07) and postcrisis (2010–16) samples, "the share of domestic financial conditions attributed to global financial conditions appears to be broadly stable over the two periods."
- The 2001–07 and 2010–16 variance decompositions are not statistically different at the 95 percent level.

### Case studies and identification of monetary policy shocks
- Recent methods (following Gertler and Karadi 2015 and Gürkaynak, Sack, and Swanson 2005) use unexpected changes in bond yields on central bank policy announcement dates to measure policy surprises; VAR models using these shocks for Australia, New Zealand, Norway, and Sweden yield results similar to earlier findings.
- Impulse response functions and 90 percent confidence bands show domestic FCI responses to domestic monetary policy shocks using two complementary identification methods: GK (Gertler and Karadi) and Cholesky.

### Policy implications and recommendations
- A single factor — global financial conditions, which move with the U.S. FCI and measures of global risk such as the VIX — summarizes a significant share of global financial-condition dynamics.
- Despite the influence of global financial conditions, countries on average remain able to steer domestic financial conditions.
- Because domestic financial conditions respond faster and more strongly to global financial shocks than to domestic monetary policy changes, implementing timely and effective monetary policy reactions is often challenging.
- Emerging market economies should prepare for the implications of global financial tightening given a larger fraction of FCI variability attributable to global financial conditions in these countries.
- Other policy tools are available:
  - Macroprudential measures can be used to limit risks from a further buildup of vulnerabilities that increase sensitivity to external financial shocks.
  - There may be circumstances that warrant a temporary role for capital flow management measures.
- Governments should prioritize domestic financial deepening to enhance resilience to global financial shocks by:
  - Developing a local investor base encompassing both bank and nonbank financial intermediaries.
  - Fostering greater equity and bond market depth and liquidity to help dampen the impact of external financial shocks.

### Annex 3.1 — Estimating Financial Conditions Indices (FCIs)
- The FCIs are estimated for 1990–2016 at monthly frequency for 43 advanced and emerging market economies using a set of 10 financial indicators.
- The vector of financial variables includes: corporate spreads, term spreads, interbank spreads, sovereign spreads, the change in long-term interest rates, equity and house price returns, equity return volatility, the change in the market share of the financial sector, and credit growth.
- FCIs are estimated based on Koop and Korobilis 2014 and build on Primiceri’s (2005) time-varying parameter VAR model and dynamic factor models of Doz, Giannone, and Reichlin (2011).
- Advantages of the approach:
  - Can purge financial conditions of (current) macroeconomic conditions.
  - Allows for dynamic interaction between FCIs and macroeconomic conditions that can evolve over time.
- Model form (as presented):
  - x_t = λ^y_t Y_t + λ^f_t f_t + u_t
  - [Y_t  f_t]' = B_{1,t} [Y_{t–1}  f_{t–1}]' + B_{2,t} [Y_{t–2}  f_{t–2}]' + ... + ε_t
  - where x is a vector of financial variables, Y_t is a vector of macroeconomic variables (including growth in industrial production and inflation), λ^y_t are regression coefficients, λ^f_t are factor loadings, and f_t is the latent factor interpreted as the FCI.

*International Monetary Fund | April 2017*

### Annex 3.2. Factor Model Analysis

### Annex 3.2. Factor Model Analysis

### Methodology
- Time series factor analysis (TSFA) methodology described in Gilbert and Meijer 2005 is used; this methodology does not require independent and identically distributed observations.
- Sample: panel of 43 countries, 1995 to 2016.
- Models fitted: one-factor and three-factor TSFA models.

### Factor model specification
- Factor model:
  FCI_{c,t} = λ_{1,c} x_{1,t} + λ_{2,c} x_{2,t} + λ_{3,c} x_{3,t}
  - x_{1,t} and λ_{1,c}, for example, represent the first common time-varying factor and the country-specific loading associated with it (c and t denote country and time, respectively).
- Rationale for three factors:
  - Allows more accurate decomposition of common dynamics across countries.
  - Recognizes regional dynamics apart from global financial conditions.

### Empirical results and key statistics
- On average, the one-factor model explains about 30 percent of the variance of the FCIs in the sample.
- On average, the three-factor model explains about 41 percent of the variance of the FCIs in the sample.
- The additional variance explained by the two regional factors (beyond the single global factor) is limited: about 10 percentage points on average.
- Interpretation: the largest share of common dynamics across countries is driven by a single global factor, which moves in lock-step with the U.S. FCI.
- Note: explanatory power can vary notably across countries.

### Interpretation and implications
- A dominant global factor implies strong commonality in financial conditions across countries over the full sample.
- Regional factors capture important country-group dynamics during particular events, but contribute less to overall explained variance across the full sample.
- The findings justify focusing on the global FCI (notably the U.S. FCI) when assessing common movements in country-level financial conditions, while acknowledging episodic regional dynamics.

*The author of this annex is Romain Lafarguette.*

### CHAPTER 3 ARE COuNTRIES LOSING CONTROL OF DOMESTIC FINANCIAL CONDITIONS?

### CHAPTER 3 ARE COuNTRIES LOSING CONTROL OF DOMESTIC FINANCIAL CONDITIONS?

### Financial conditions indices and measurement studies
- Davis, E. Philip, Simon Kirby, and James Warren. 2016. “The Estimation of Financial Conditions Indices for the Major OECD Countries.” OECD Economics Department Working Paper 1335, Organisation for Economic Co-operation and Development, Paris.
- Dudley, William C. 2010. “Comments: Financial Conditions Indexes: A Fresh Look after the Financial Crisis.” Remarks at the University of Chicago Booth School of Business Annual U.S. Monetary Policy Forum, New York, February 26.
- ———, and Jan Hatzius. 2000. “The Goldman Sachs Financial Conditions Index: The Right Tool for a New Monetary Policy Regime.” Global Economics Paper 44, Goldman Sachs, New York.
- Freedman, Charles. 1994. “The Use of Indicators and of the Monetary Conditions Index in Canada.” In Frameworks for Monetary Stability: Policy Issues and Country Experiences, edited by Tomas J. T. Balino and Carlo Cottarelli. Washington, DC: International Monetary Fund, 458–76.
- Gauthier, Celine, Christopher Graham, and Ying Liu. 2004. “Financial Conditions Indexes for Canada.” Working Paper 22, Bank of Canada, Ottawa.
- Gilbert, Paul D., and Erik Meijer. 2005. “Time Series Factor Analysis with an Application to Measuring Money.” Working Paper, University of Groningen.
- Gertler, Mark, and Peter Karadi. 2015. “Monetary Policy Surprises, Credit Costs, and Economic Activity.” American Economic Journal: Macroeconomics 7 (1): 44–76.
- Hatzius, Jan, Peter Hooper, Frederic S. Mishkin, Kermit L. Schoenholtz, and Mark M. Watson. 2010. “Financial Conditions Indexes: A Fresh Look after the Financial Crisis.” NBER Working Paper 16150, National Bureau of Economic Research, Cambridge, MA.
- Hollo, Daniel, Manfred Kremer, and Marco Lo Duca. 2012. “CISS-A Composite Indicator of Systemic Stress in the Financial System.” ECB Working Paper 1426, European Central Bank, Frankfurt.
- Illing, Mark, and Ying Liu. 2003. “An Index of Financial Stress for Canada.” Working Paper 2003/14, Bank of Canada, Ottawa.
- Kliesen, Kevin L., Michael T. Owyang, and E. Katarina Vermann. 2012. “Disentangling Diverse Measures: A Survey of Financial Stress Indexes.” Federal Reserve Bank of St. Louis Review 94 (5): 369–97.
- Koop, Gary, and Dimitris Korobilis. 2014. “A New Index of Financial Conditions.” European Economic Review 71: 101–16.
- Matheson, Troy D. 2012. “Financial Conditions Indexes for the United States and Euro Area.” Economics Letters 115 (3): 441–46.
- Moccero, Diego Nicolas, Matthieu Darracq Pariès, and Laurent Maurin. 2014. “Financial Conditions Index and Identification of Credit Supply Shocks for the Euro Area.” International Finance 17 (3): 297–321.
- Swiston, Andrew J. 2008. “A U.S. Financial Conditions Index: Putting Credit Where Credit Is Due.” IMF Working Paper 08/161, International Monetary Fund, Washington, DC.
- Gumata, Nombulelo, Nir Klein, and Eliphas Ndou. 2012. “A Financial Conditions Index for South Africa.” IMF Working Paper 12/196, International Monetary Fund, Washington, DC.
- Kara, A. Hakan, Pinar Ozlu, and Deren Unalmis. 2012. “Financial Conditions Indices for the Turkish Economy.” CBT Research Notes in Economics 1231, Central Bank of the Republic of Turkey, Ankara.

### Global financial cycle, spillovers, and monetary independence
- Disyatat, Piti, and Phurichai Rungcharoenkitkul. 2016. “Financial Globalisation and Monetary Independence.” BIS Paper 88, Bank for International Settlements, Basel.
- Forbes, Kristin J., and Menzie D. Chinn. 2004. “A Decomposition of Global Linkages in Financial Markets over Time.” Review of Economics and Statistics 86 (3): 705–22.
- Forbes, Kristin J., and Roberto Rigobon. 2002. “No Contagion, Only Interdependence: Measuring Stock Market Comovements.” Journal of Finance 57 (5): 2223 –61.
- Fratzscher, Marcel. 2012. “Capital Flows, Push Versus Pull Factors and the Global Financial Crisis.” Journal of International Economics 88 (2): 341–56.
- He, Dong, and Robert N. McCauley. 2013. “Transmitting Global Liquidity to East Asia: Policy Rates, Bond Yields, Currencies, and Dollar Credits.” BIS Working Paper 431, Bank for International Settlements, Basel.
- Kamin, Steven B. 2010. “Financial Globalization and Monetary Policy.” International Finance Discussion Paper 1002, Federal Reserve Bank, Washington, DC.
- Kearns, Jonathan, and Nikhil Patel. 2016. “Does the Financial Channel of Exchange Rates Offset the Trade Channel?” BIS Quarterly Review (December), Bank for International Settlements, Basel.
- Klein, Michael W., and Jay C. Shambaugh. 2015. “Rounding the Corners of the Policy Trilemma: Sources of Monetary Policy Autonomy.” American Economic Journal: Macroeconomics 7 (4): 33–66.
- Miranda-Agrippino, Silvia, and Hélène Rey. 2015. “World Asset Markets and the Global Financial Cycle.” NBER Working Paper 21722, National Bureau of Economic Research, Cambridge, MA.
- Obstfeld, Maurice. 2015. “Trilemmas and Trade-Offs: Living with Financial Globalization.” BIS Working Paper 480, Bank for International Settlements, Basel.
- Passari, Evgenia, and Hélène Rey. 2015. “Financial Flows and the International Monetary System.” Economic Journal 125 (584): 675–98.
- Rey, Hélène. 2013. “Dilemma Not Trilemma: The Global Financial Cycle and Monetary Policy Independence.” Paper presented at Global Dimensions of Unconventional Monetary Policy Symposium, Jackson Hole, WY, August 24.
- ———. 2016. “International Channels of Transmission of Monetary Policy and the Mundellian Trilemma.” IMF Economic Review 64 (1): 6–35.
- Kose, M. Ayhan, Csilla Lakatos, Franziska Ohnsorge, and Marc Stocker. 2017. “The Global Role of the U.S. Economy: Linkages, Policies, and Spillovers.” CEPR Discussion Paper 11836, Centre for Economic Policy Research, London.
- Ilzetzki, Ethan, Carmen M. Reinhart, and Kenneth S. Rogoff. 2017. “Exchange Rate Arrangements Entering the 21st Century: Which Anchor Will Hold?” NBER Working Paper 23134, National Bureau of Economic Research, Cambridge, MA.

### Credit, sovereign risk, and systemic stress
- Gilchrist, Simon, and Egon Zakrajšek. 2012. “Credit Spreads and Business Cycle Fluctuations.” American Economic Review 102 (4): 1692–720.
- Longstaff, Francis A., Jun Pan, Lasse H. Pedersen, and Kenneth J. Singleton. 2011. “How Sovereign Is Sovereign Credit Risk?” American Economic Journal: Macroeconomics 3 (2): 75 –103.
- Oet, Mikhail V., Ryan Eiben, Timothy Bianco, Dieter Gramlich, and Stephen J. Ong. 2011. “The Financial Stress Index: Identification of Systemic Risk Conditions.” Federal Reserve Bank of Cleveland, Working Paper 11–30, Cleveland, OH.
- Hakkio, Craig S., and William R. Keeton. 2009. “Financial Stress: What Is It, How Can It Be Measured, and Why Does It Matter?” Federal Reserve Bank of Kansas City, Economic Review (2): 5.
- Hollo, Daniel, Manfred Kremer, and Marco Lo Duca. 2012. “CISS-A Composite Indicator of Systemic Stress in the Financial System.” ECB Working Paper 1426, European Central Bank, Frankfurt.

### Macroprudential policy, capital flows, and institutional guidance
- International Monetary Fund (IMF). 2014a. “Global Liquidity—Issues for Surveillance.” IMF Policy Paper, Washington, DC.
- ———. 2014b. “Staff Guidance Note on Macroprudential Policy—Detailed Guidance on Instruments.” IMF Policy Paper, International Monetary Fund, Washington, DC.
- ———. 2015. “Financial Conditions in Asia: How Accommodative Are They?” Regional Economic Outlook: Asia and Pacific, Box 1.4, International Monetary Fund, Washington, DC.
- ———. 2016. “Capital Flows—Review of Experience with the Institutional View.” IMF Policy Paper, Washington, DC.
- ———, Financial Stability Board, and Bank for International Settlements. 2016. “Elements of Effective Macroprudential Policies: Lessons from International Experience.” Note to the G20, August 2016, International Monetary Fund, Washington, DC.
- Sahay, Ratna, Vivek Arora, Athanasios V. Arvanitis, Hamid Faruqee, Papa M. N’Diaye, and Tommaso Mancini-Griffoli. 2014. “Emerging Market Volatility: Lessons from the Taper Tantrum.” IMF Staff Discussion Note 14/09, International Monetary Fund, Washington, DC.
- Sahay, Ratna, Martin Cihak, Papa M. N’Diaye, Adolfo Barajas, Ran Bi, Diana Ayala, Yuan Gao, Annette Kyobe, Lam Nguyen, Christian Saborowski, Katsiaryna Svirydzenka, and Seyed Reza Yousefi. 2015. “Rethinking Financial Deepening: Stability and Growth in Emerging Markets.” IMF Staff Discussion Note 15/08, International Monetary Fund, Washington, DC.
- Kennedy, Mike, and Angel Palerm. 2014. “Emerging Market Bond Spreads: The Role of Global and Domestic Factors from 2002 to 2011.” Journal of International Money and Finance 43: 70–87.

### Methodological and econometric contributions
- Doz, Catherine, Domenico Giannone, and Lucrezia Reichlin. 2011. “A Two-Step Estimator for Large Approximate Dynamic Factor Models Based on Kalman Filtering.” Journal of Econometrics 164: 188–205.
- Pesaran, Hashem M., Yongcheol Shin, and Ron P. Smith. 1999. “Pooled Mean Group Estimation of Dynamic Heterogeneous Panels.” Journal of the American Statistical Association 94 (446): 621–34.
- Primiceri, Giorgio. 2005. “Time Varying Structural Vector Autoregressions and Monetary Policy.” Review of Economic Studies 72: 821–52.
- Sugihara, George, Robert May, Hao Ye, Chih-hao Hsieh, Ethan Deyle, Michael Fogarty, and Stephan Munch. 2012. “Detecting Causality in Complex Ecosystems.” Science 338: 496–500.
- Schüler, Yves Stephan, Paul Hiebert, and Tuomas A. Peltonen. 2016. “Coherent Financial Cycles for G-7 Countries: Why Extending Credit Can Be an Asset.” https://ssrn.com /abstract=2539717 or http://dx.doi.org/10.2139/ssrn.2539717.
- Van den Heuvel, Skander J. 2002. “Does Bank Capital Matter for Monetary Transmission?” Economic Policy Review 8 (1): 259–65.
- Guichard, Stéphanie, David Haugh, and David Turner. 2009. “Quantifying the Effect of Financial Conditions in the Euro Area, Japan, United Kingdom and United States.” OECD Economics Department Working Paper 677, Organisation for Economic Co-operation and Development, Paris.
- Kliesen, Kevin L., Michael T. Owyang, and E. Katarina Vermann. 2012. “Disentangling Diverse Measures: A Survey of Financial Stress Indexes.” Federal Reserve Bank of St. Louis Review 94 (5): 369–97.

### Speeches, remarks, and policy perspectives
- Dudley, William C. 2010. “Comments: Financial Conditions Indexes: A Fresh Look after the Financial Crisis.” Remarks at the University of Chicago Booth School of Business Annual U.S. Monetary Policy Forum, New York, February 26.
- Yellen, Janet L. 2016. “Current Conditions and the Outlook for the U.S. Economy.” Speech at the World Affairs Council of Philadelphia, Philadelphia, PA, June 6.

*Source: CHAPTER 3 ARE COuNTRIES LOSING CONTROL OF DOMESTIC FINANCIAL CONDITIONS?, Global Financial Stability Report: Getting the Policy Mix Right, International Monetary Fund | April 2017*

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_Source: https://www.imf.org/-/media/files/publications/gfsr/2017/april/ch3.pdf_