2013年-IMF国际货币组织全球_Factors_Influencing_Emerging_Market_Central_Banks’_Decision_to_Intervene_in_Foreign_Exchange_Markets_28页_1mb

Summary of "Factors Influencing Emerging Market Central Banks' Decision to Intervene in Foreign Exchange Markets"

Core Content

This working paper by Matthew Malloy examines the factors influencing foreign exchange (FX) intervention by central banks in emerging markets (EMs) with flexible or moderately managed exchange rate regimes. The study uses panel data from 15 EMs between 2001 and 2012 to analyze the determinants of FX intervention, focusing on both short-run and medium-run exchange rate pressures, as well as broader macroeconomic variables. The goal is to understand why EM central banks intervene in FX markets and why their intervention rates differ.

Main Determinants of FX Intervention

1. Short-run Exchange Rate Pressures

• Central banks tend to "lean against the wind," buying or selling FX in response to short-term appreciation or depreciation pressures.
• The short-run exchange rate pressure is measured by the monthly change in the nominal U.S. dollar bilateral exchange rate ($\Delta e$).
• A 1% monthly appreciation of $\Delta e$ is associated with a 0.16% of GDP increase in FX intervention for non-commodity producers.
• The VIX index, which proxies for global risk sentiment, is used as an alternative measure for short-run FX pressures. A 10% increase in the VIX is associated with a 0.32% of GDP decrease in FX intervention, consistent with its role in capturing global risk aversion.

2. Medium-run Real Effective Exchange Rate (REER) Pressures

• The REER is modeled as the percentage change between the current REER and its rolling five-year average.
• A 10% appreciation of REER (lagged by two months) is associated with a 0.43% of GDP increase in FX intervention for non-commodity producers.
• The positive and statistically significant coefficient suggests that central banks may consider competitiveness when making intervention decisions.

3. Precautionary Motives

• Reserve adequacy is measured using the IMF reserve adequacy metric, which considers potential liability drains during a crisis.
• Two dummies are used: RAD1 (reserves above 150% of the metric) and RAD2 (reserves below 100% of the metric).
• RAD1 has a positive and statistically significant coefficient for non-commodity exporters, suggesting that even with high reserves, central banks continue to accumulate FX.
• RAD2 has a negative and statistically significant coefficient, indicating that EMs with low reserves tend to reduce FX intervention.

4. External Competitiveness Motives

• The study suggests that external competitiveness may also be a factor, though the evidence is mixed.
• A positive coefficient on EXGDP (exports as a share of GDP) indicates that EMs with larger export sectors are more likely to intervene, possibly due to a combination of precautionary and competitiveness motives.
• Interactions between EXGDP and RAD1 and $\Delta e(-1)$ show that higher export sectors are more sensitive to both reserve adequacy and short-run exchange rate movements.

5. Inflation

• A 1% increase in year-on-year CPI inflation is associated with a 0.1% of GDP decrease in FX intervention for non-commodity producers.
• This effect becomes more pronounced in the 2007-2012 period, with a coefficient of 0.7% of GDP.
• The negative association suggests that inflation may influence intervention decisions, possibly by affecting sterilization costs or the need to manage inflation through exchange rate adjustments.

Key Findings

• Central banks in EMs with flexible exchange rates tend to intervene in response to both short-run and medium-run exchange rate pressures.
• EXGDP is the most significant variable in explaining differences in FX intervention rates.
• The RAD1 and RAD2 dummies provide evidence of precautionary and competitiveness motives, though the results are not fully consistent with a pure precautionary interpretation.
• The study finds that the VIX and $\Delta e(-1)$ are significant in capturing short-run FX pressures, while REER is more relevant for medium-term competitiveness considerations.
• The results suggest that central banks may have multiple, overlapping motives for FX intervention, including both smoothing exchange rate fluctuations and building reserves for precautionary and competitiveness reasons.

Methodology and Data

• The study uses a panel least squares model with AR1 residuals and heteroskedasticity-corrected standard errors (White).
• It includes 15 EM cross-sections with monthly data from 2001 to 2012.
• The dependent variable, INT, is defined as the ratio of total monthly FX intervention to GDP.
• Independent variables include:
  • $\Delta e(-1)$: One-month lag of short-run exchange rate changes.
  • REER: Real effective exchange rate relative to a 5-year rolling average (lagged by two months).
  • EXGDP: Exports as a share of GDP.
  • RAD1 and RAD2: Reserve adequacy dummies based on the IMF metric.
  • CPI inflation: Year-on-year change in CPI.

Limitations and Robustness

• The use of lagged variables helps mitigate simultaneity bias but may introduce omitted variable bias.
• The VIX is used as a proxy for global risk sentiment, though it does not capture economy-specific factors.
• The IMF reserve adequacy metric is used to assess precautionary reserve needs, but results suggest that EMs may have different views on what constitutes adequate reserves.
• Robustness checks confirm the significance of all four reserve adequacy measures, though EXGDP remains the most robust.

Conclusion

• The study confirms that central banks in EMs with flexible exchange rates intervene to smooth short-term exchange rate fluctuations.
• It also finds evidence of precautionary and competitiveness motives for reserve accumulation.
• The results suggest that EXGDP is a key factor in explaining differences in FX intervention rates among EMs.
• The interactions between variables indicate that intervention decisions are influenced by a combination of macroeconomic factors, including exchange rate pressures, inflation, and reserve adequacy.