Aizenman, Joshua, Menzie D. Chinn, and Hiro Ito, 2015, “Monetary Policy Spillovers and the Trilemma in the New Normal: Periphery Country Sensitivity to Core Country Conditions,” NBER Working Paper No. 21128 (Cambridge, Massachusetts: MIT Press).
Aizenman, Joshua, Menzie D. Chinn, and Hiro Ito, 2010, “The Emerging Global Financial Architecture: Tracing and Evaluating New Patterns Of The Trilemma Configuration,” Journal of International Money and Finance, Vol. 29, pp. 615–641.
Arora, Vivek, and Martin Cerisola, 2001, “How Does U.S. Monetary Policy Influence Sovereign Spreads in Emerging Markets?,” Staff Papers, International Monetary Fund, Vol. 48, No. 3, pp.474–8.
Bruno, Valentina, Hyun Song Shin, 2015, “Capital Flows and the Risk-Taking Channel of Monetary Policy,” Journal of Monetary Economics, Vol. 71, pp. 11–132.
Chen, Jiaqian, Tommaso Mancini-Griffoli and Ratna Sahay, 2014, “Spillovers from United States Monetary Policy on Emerging Markets: Different This Time?,” IMF Working Paper 14/240 (Washington: International Monetary Fund).
Davis, J. Scott, 2014, “Inflation Targeting and the Anchoring of Inflation Expectations: Cross-Country Evidence from Consensus Forecasts,” Federal Reserve Bank of Dallas, Globalization and Monetary Policy Institute, Working Paper No. 174.
Ebeke, Christian, Annette Kyobe, 2014, “Global Financial Spillovers to Emerging Market Sovereign Bond Market: The Role of Foreign Participation and The Investor Base,” IMF, Republic of Poland, Selected Issues.
Edwards, Sebastian, 2015, “Monetary Policy Independence Under Flexible Exchange Rates: An Illusion?,” NBER Working Paper 20893 21128 (Cambridge, Massachusetts: MIT Press).
Frankel, Jeffrey, Sergio L. Schmukler and Luis Serven, 2004, “Global transmission of interest rates: monetary independence and currency regime,” Journal of International Money and Finance.
Henriksen, Espen, Finn E. Kydland and Roman Sustek, 2013, “Globally correlated nominal fluctuations,” Journal of Monetary Economics, Vol. 60, pp. 613–631.
Klein, Michael W., and Jay C. Shambough, 2013, “Rounding the Corners of the Policy Trilemma: Sources of Monetary Policy Autonomy,” NBER Working Paper 19461 (Cambridge, Massachusetts: MIT Press).
Krippner, Leo, 2013, “A Tractable Framework for Zero Lower Bound Gaussian Term Structure Models,” Reserve Bank of New Zealand Working Paper.
Lombardi, Marco and Feng Zhu, 2014, “A Shadow Policy Rate to Calibrate U.S. Monetary Policy at the Zero Lower Bound,” BIS Working Paper (Basel: Bank for International Settlements).
Obstfeld, Maurice, Jay C. Shambaugh, and Alan M. Taylor, 2005, “The trilemma in history: Tradeoffs Among Exchange Rates, Monetary Policies, and Capital Mobility,” The Review of Economics and Statistics, No. 87(3): pp. 423–438.
Ostry, Jonathan D., Atish R. Ghosh, and Marcos Chamon, 2012, “Two Targets, Two Instruments: Monetary and Exchange Rate Policies in Emerging Market Economies,” IMF Staff Discussion Note, SDN/12/01.
Quinn, Dennis P., 1997, “The Correlates of Change in International Financial Regulation,” American Political Science Review, Vol. 91, pp. 531–51.
Quinn, Dennis P. and A. Maria Toyoda, 2008, “Does Capital Account Liberalization Lead to Economic Growth?,” Review of Financial Studies, Vol. 21(3): pp. 1403–49.
Rey, Helene, 2014, “The International Credit Channel and Monetary Autonomy,” IMF 15th Jacques Polak Annual Research Conference, Mundell-Fleming Lecture, No. 13 (November).
Rogers, John H., Chiara Scotti, Jonathan H. Wright, 2014, “Evaluating Asset-Market Effect of Unconventional Monetary Policy: A Multi-Country Review,” Economic Policy pp.749–799.
Sahay, Ratna, Vivek Arora, Thanos Arvanitis, Hamid Faruqee, Papa N’Diaye, Tommaso Mancini-Griffoli and an IMF Team, 2014, “Emerging Market Volatility: Lessons from the Taper Tantrum,” IMF Staff Discussion Note, SDN/14/09.
Taylor, John B., 1993, “Discretion Versus Policy Rules in Practice,” Carnegie-Rochester Conference Series on Public Policy No. 39, pp. 195–214.
Wu, Jing Cynthis, Fan Dora Xia, 2014, “Measuring the Macroeconomic Impact of Monetary Policy at the Zero Lower Bound,” Working Paper.
Appendix. Additional Material
We would like to thank participants in the Jun. 2014 IMF/WHD, Sep. 2014 IMF/Surveillance Meeting, Oct. 2014 WB-LAC, Nov. 2014 IADB, Nov. 2014 WB, Feb. 2015 IMF/WHD-macro seminars, May 2015 The Graduate Institute of International and Development Studies seminar, as well as Tam Bayoumi, Olivier Blanchard, Diego Cerdeiro, Giovanni Dell’Ariccia, Metodij Hadzi-Vaskov, Gian Maria Milesi-Ferretti, Maurice Obstfeld, Sam Ouliaris, Ugo Panizza, Peter Pedroni, Andrea Pescatori, Alejandro Werner, and Charles Wyplosz for invaluable comments. We would also like to thank Krippner, Wu, Xia, Lombardi, and Zhu for sharing data with us. Daniela Cortez offered invaluable research assistance.
Recent episodes of the influence of euro area monetary policy developments on global rates would require a separate exercise, as the sample is not long enough for our analysis. For an analysis of the spillovers from four center economies (the U.S., Japan, the Eurozone and China), see Aizenman et al. (2015).
We check the robustness of our key results against several alternative measures of exchange rate regime or capital controls (results available upon request).
According to the country-by-country Durbin-Watson unit root test, only a small fraction of countries in the regression sample reject the null hypothesis at 10 percent level. The baseline model strongly rejects the null hypothesis of no co-integration for the regression in levels.
The U.S. shadow policy rate is set to zero for the pre-2009 period, and the average of the three estimates proposed in the following papers: Krippner (2013), Wu and Xia (2014), and Lombardi and Zhu (2014). All three papers use information on the long end of the U.S. yield curve to characterize the impact of unconventional monetary policy. Lombardi-Zhu also utilizes the size of Fed’s balance sheet and other quantitative easing related variables in the estimation. The baseline Matching Model includes only the shadow rate, but the estimated coefficients are robust if—at the same time—a post-2009 time dummy is included.
For both CPI and IP series, the respective first principle component explains a large portion (over 40 percent), while the marginal value added by the subsequent principle components is relatively small (the 2nd component adds around 10 percent). In the augmented models, we include only the first principle components.
It may appear as puzzling (and would deserve further investigation) the result that some coefficients are negative. However when bearing in mind that theory would suggest that the distribution of coefficients for floaters should be centered around zero (MP independence for the average floater), then it is less surprising that some coefficients are negative.
Klein and Shambaugh (2013) find that episodic control—what they call “gates”—does not seem to allow more monetary independence than open capital accounts. Only the long-standing capital controls—“walls”—permit monetary autonomy.
Our Figure 2 shows that U.S. long term rates respond one to one to the policy rate on average, which implies that on average, i.e. over most of the sample, there was no “Greenspan conundrum” in the U.S.
Regressions in level available upon request.
Results without the local policy rates are available upon request.
We fail to reject the unit root hypothesis for a large number of countries in the sample with country-by-country test at usual significance level. Both baseline Matching Model and Yield Curve strongly reject the no-cointegration null hypothesis in the ECM panel cointegration test.