2016年-PIIE彼得森国际经济研究所_Estimation_of_De_Facto_Flexibility_Parameter_and_Basket_Weights_in_Evolving_Exchange_Rate_Regimes_15页_254kb

Summary of "Estimation of De Facto Flexibility Parameter and Basket Weights in Evolving Exchange Rate Regimes"

Core Content

This paper introduces a synthesis technique for estimating de facto exchange rate regimes, which combines two traditional approaches: estimating basket weights and exchange rate flexibility. The method is designed to capture the evolving nature of exchange rate regimes, where countries may switch between different policies and parameters over time.

Main Views

1. De Facto vs. De Jure Regimes

• Countries often follow de facto exchange rate regimes that differ from their de jure (officially announced) regimes.
• For example, some countries that officially float may intervene heavily, while others that fix may devalue during crises.
• Many countries that target a basket of currencies may adjust the weights of the basket in practice.

2. Limitations of Existing Techniques

• Traditional methods for estimating exchange rate regimes are inconsistent and incomplete.
• Methods that estimate basket weights often assume a fixed anchor currency (e.g., the dollar), which may not be valid for all countries.
• Methods that estimate flexibility typically ignore the possibility of multiple anchors or changing basket weights.
• These approaches also fail to account for regime changes over time, which are common in practice.

3. Synthesis Equation

• The authors propose a synthesis equation that estimates both basket weights and flexibility parameters simultaneously.

• The equation is:

  $$
  \Delta \log H_t = c + \sum w(j) \Delta \log X(j)_t + \delta {\Delta EMP_t} + u_t
  $$

  • $\Delta \log H_t$: Change in the value of the home currency.
  • $w(j)$: De facto weights of the basket currencies.
  • $\Delta EMP_t$: Change in exchange market pressure, defined as the sum of the change in the currency's value and the change in its reserves relative to the monetary base.
  • $\delta$: De facto degree of exchange rate flexibility.

• The adding-up constraint is imposed to ensure that the sum of the weights equals 1.

• The equation is implemented by regressing the change in the home currency against the changes in the values of other currencies and the exchange market pressure.

4. Structural Breaks and Regime Changes

• The authors argue that exchange rate regimes are not static and may change frequently.
• They use a multiple structural change model proposed by Bai and Perron (1998) to estimate breakpoints in the regime.
• The model allows for endogenous estimation of the number and timing of breaks, which is critical for capturing the real-world dynamics of exchange rate regimes.

5. Estimation Procedure

• The Bai-Perron method is used to estimate the number of structural breaks.
• The approach involves sequential testing of the number of breaks using a supF test.
• The best partition is found by minimizing the sum of squared residuals across different regimes.

Key Information

• The synthesis technique improves upon existing methods by estimating both basket weights and flexibility simultaneously.
• The numeraire (the currency used to express exchange rates) is important in the estimation process.
• The SDR (Special Drawing Rights) is used as the numeraire because it represents a basket of major currencies and aligns with the authorities’ reference basket.
• The method accounts for nonstationarity by using first differences and including a constant term for trends.
• The paper provides an illustration using five currencies: the Mexican peso, Chilean peso, Russian ruble, Thai baht, and Indian rupee.
• All five currencies are found to follow a managed float regime during most of the period 1999–2009, with significant structural breaks.
• The flexibility parameter $\delta$ indicates the degree to which exchange rate changes reflect market pressure rather than central bank intervention.

Conclusion

• The paper emphasizes the need for a flexible statistical technique that can capture the evolving nature of exchange rate regimes.
• The synthesis approach allows for endogenous regime detection and parameter estimation, which is more realistic and accurate than fixed or exogenous assumptions.
• The method is empirically validated with real-world data, showing that regime shifts are common and significant in many countries.

References

• Bai, Jushan, and Pierre Perron (1998, 2003)
• Frankel, Jeffrey, and Shang-Jin Wei (1995, 2007, 2008)
• Calvo and Reinhart (2002)
• Levy-Yeyati and Sturzenegger (2003, 2005)