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Global liquidity effect of quantitative easing on emerging markets

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Abstract

Using a panel quantile vector autoregression model, we investigate the global liquidity effect of quantitative easing (QE) in the US on emerging markets (EMs) over the period 2010:Q1 to 2019:Q3. Our empirical result suggests that tapering of QE in the US triggers a large capital outflow from the EMs. In addition, we find a significant asymmetric effect of QE on portfolio investment flows to EMs with a stronger effect in the higher quantiles. The implication of these findings is that tapering the large-scale asset purchases and other instruments of unconventional monetary policy have a larger effect on EMs.

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Notes

  1. See Montes‐Rojas (2019) for a similar quantile VAR model, where quintiles are not restricted to be equal.

  2. Note that the choice of the countries and time length chosen are motivated by the availability of data.

  3. Shadow short rate (SSR) proposed by Krippner (2012) and further extended by Krippner (2014) is derived from empirical yield curves as the shortest maturity rate. The SSR is essentially an estimate of the policy rate, which could be negative that would generate the observed yield curve.

References

  • Anderson TW, Hsiao C (1982) Formulation and estimation of dynamic models using panel data. J Econ 18(1):47–82

    Article  Google Scholar 

  • Bacchetta P, Benhima K, Kalantzis Y (2020) Money and capital in a persistent liquidity trap. J Monet Econ 116:70–87

    Article  Google Scholar 

  • Balcilar M, Ozdemir ZA, Ozdemir H, Wohar ME (2020) Fed’s unconventional monetary policy and risk spillover in the US financial markets. Q Rev Econ Finance 78:42–52

    Article  Google Scholar 

  • Bauer MD, Rudebusch GD (2013) The signaling channel for federal reserve bond purchases. Federal Reserve Bank of San Francisco, Working Paper Series, 1–48. https://doi.org/10.24148/wp2011-21.

  • Bernanke BS, Reinhart VR (2004) Conducting monetary policy at very low short-term interest rates. Am Econ Rev 94(2):85–90

    Article  Google Scholar 

  • Black F (1995) Interest rates as options. J Financ 50(5):1371–1376

    Article  Google Scholar 

  • Borio C, Disyatat P (2010) Unconventional monetary policies: an appraisal. Manch Sch 78:53–89

    Article  Google Scholar 

  • Bowman D, Londono JM, Sapriza H (2015) US unconventional monetary policy and transmission to emerging market economies. J Int Money Financ 55:27–59

    Article  Google Scholar 

  • Cepni O, Gul S, Gupta R (2019) Local currency bond risk premia of emerging markets: the role of local and global factors. Financ Res Lett. https://doi.org/10.1016/j.frl.2019.05.001

    Article  Google Scholar 

  • Chernozhukov V, Hansen C (2004) The effects of 401 (k) participation on the wealth distribution: an instrumental quantile regression analysis. Rev Econ Stat 86(3):735–751

    Article  Google Scholar 

  • Chernozhukov V, Hansen C (2005) An IV model of quantile treatment effects. Econometrica 73(1):245–261

    Article  Google Scholar 

  • Chernozhukov V, Hansen C (2008) Instrumental variable quantile regression: a robust inference approach. J Econ 142(1):379–398

    Article  Google Scholar 

  • Cochrane JH, Piazzesi M (2005) Bond risk premia. Am Econ Rev 95(1):138–160

    Article  Google Scholar 

  • Fic T (2013) The spillover effects of unconventional monetary policies in major developed countries on developing countries. United Nations, Department of Economic and Social Affairs.

  • Fratzscher M, Lo Duca M, Straub R (2017) On the international spillovers of US quantitative easing. Econ J 128(608):330–377

    Google Scholar 

  • Galvao AF (2011) Quantile regression for dynamic panel data with fixed effects. J Econ 164(1):142–157

    Article  Google Scholar 

  • Geraci M, Bottai M (2007) Quantile regression for longitudinal data using the asymmetric Laplace distribution. Biostat 8(1):140–154

    Article  Google Scholar 

  • Giannone D, Reichlin L, Small D (2008) Nowcasting: the real-time informational content of macroeconomic data. J Monet Econ 55(4):665–676

    Article  Google Scholar 

  • Joyce M, Miles D, Scott A, Vayanos D (2012) Quantitative easing and unconventional monetary policy–an introduction. Econ J 122(564):F271–F288

    Article  Google Scholar 

  • Koenker R (2004) Quantile regression for longitudinal data. J Multivar Anal 91(1):74–89

    Article  Google Scholar 

  • Koenker R, Bassett G (1978) Regression quantiles. Econometrica 46(1):33–50

    Article  Google Scholar 

  • Krippner L (2013) Measuring the stance of monetary policy in zero lower bound environments. Econ Lett 118(1):135–138

    Article  Google Scholar 

  • Krippner L (2012) Modifying Gaussian term structure models when interest rates are near the zero lower bound. CAMA working paper No. 2012–05. centre for applied macroeconomic analysis, Crawford School of Public Policy, The Australian National University.

  • Krippner L (2014) Measuring the stance of monetary policy in conventional and unconventional environments. CAMA Working Papers 2014–06, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.

  • Krippner L (2015) A comment on Wu and Xia (2015), and the case for two-factor Shadow Short Rates. CAMA Working Paper No. 48/2015, Available at SSRN: https://doi.org/10.2139/ssrn.2705222

  • Krippner L (2020) A note of caution on shadow rate estimates. JMCB 52(4):951–962

    Google Scholar 

  • Lamarche C (2010) Robust penalized quantile regression estimation for panel data. J Econom 157(2):396–408

    Article  Google Scholar 

  • Lim JJ, Mohapatra S (2016) Quantitative easing and the post-crisis surge in financial flows to developing countries. J Int Money Financ 68:331–357

    Article  Google Scholar 

  • Montes-Rojas G (2019) Multivariate quantile impulse response functions. J Time Ser Anal 40(5):739–752

    Article  Google Scholar 

  • Nickell S (1981) Biases in dynamic models with fixed effects. Econometrica 49:1417–1426

    Article  Google Scholar 

  • Tillmann P (2016) Unconventional monetary policy and the spillovers to emerging markets. J Int Money Financ 66:136–156

    Article  Google Scholar 

  • Ugai H (2007) Effects of the quantitative easing policy: A survey of empirical analyses. Monet Econ Stud-Bank Japan 25(1):1

    Google Scholar 

  • Wallace N (1981) A Modigliani-miller theorem for open-market operations. Am Econ Rev 71:267–274

    Google Scholar 

  • Woodford, M (2012) Methods of policy accommodation at the interest-rate lower bound. In: Proceedings - Economic Policy Symposium - Jackson Hole, p. 185–288, https://EconPapers.repec.org/RePEc:fip:fedkpr:y:2012:p:185-288.

  • Wu JC, Xia FD (2016) Measuring the macroeconomic impact of monetary policy at the zero lower bound. J Money, Credit, Bank 48(2–3):253–291

    Article  Google Scholar 

Download references

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Mehmet Balcilar involved in conceptualization, methodology, formal analysis, writing—reviewing and editing, data curation, and software. Ojonugwa Usman involved in writing—original draft preparation. Mark E. Wohar involved in writing—reviewing and editing, supervision and resources. David Roubaud involved in resources. Hasan Gungor involved in data acquisition.

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Correspondence to Mark Wohar.

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Balcilar, M., Usman, O., Wohar, M. et al. Global liquidity effect of quantitative easing on emerging markets. Empir Econ (2024). https://doi.org/10.1007/s00181-024-02625-9

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