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A New Method for Identifying the Effects of Foreign Exchange Interventions

Author

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  • CHIH-NAN CHEN
  • TSUTOMU WATANABE
  • TOMOYOSHI YABU

Abstract

The monetary authorities react even to intraday changes in the exchange rate; however, in most cases, intervention data is available only at a daily frequency. This temporal aggregation makes it difficult to identify the effects of interventions on the exchange rate. We propose a new method based on Markov Chain Monte Carlo simulations to cope with this endogeneity problem: We use "data augmentation" to obtain intraday intervention amounts and then estimate the efficacy of interventions using the augmented data. Applying this method to Japanese data, we find that an intervention of one trillion yen moves the yen/dollar rate by 1.7 percent, which is more than twice as large as the magnitude reported in previous studies applying OLS to daily observations. This shows the quantitative importance of the endogeneity problem due to temporal aggregation.
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Suggested Citation

  • Chih-Nan Chen & Tsutomu Watanabe & Tomoyoshi Yabu, 2012. "A New Method for Identifying the Effects of Foreign Exchange Interventions," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(8), pages 1507-1533, December.
    • Handle: RePEc:mcb:jmoncb:v:44:y:2012:i:8:p:1507-1533
    DOI: j.1538-4616.2012.00542.x
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    Citations

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    Cited by:

    1. Rasmus Fatum & Yohei Yamamoto, 2012. "Does foreign exchange intervention volume matter?," Globalization Institute Working Papers 115, Federal Reserve Bank of Dallas.
    2. Masayuki MORIKAWA, 2016. "Uncertainty over Exchange Rates and Exports: Evidence from dispersion of expectations as a measure of uncertainty," Discussion papers 16010, Research Institute of Economy, Trade and Industry (RIETI).
    3. Lukas Boer, 2019. "Measuring the Effect of Foreign Exchange Intervention Policies on Exchange Rates," DIW Roundup: Politik im Fokus 128, DIW Berlin, German Institute for Economic Research.
    4. Guyot, Opale & Montgomery, Heather A., 2025. "Against the wind or with it? The intraday and daily dynamics of yen interventions," Journal of the Japanese and International Economies, Elsevier, vol. 78(C).
    5. Adler, Gustavo & Lisack, Noëmie & Mano, Rui C., 2019. "Unveiling the effects of foreign exchange intervention: A panel approach," Emerging Markets Review, Elsevier, vol. 40(C), pages 1-1.
    6. Fatum, Rasmus & Yamamoto, Yohei & Chen, Binwei, 2025. "The trend effect of foreign exchange intervention," Journal of International Money and Finance, Elsevier, vol. 156(C).
    7. Ito, Takatoshi & Yabu, Tomoyoshi, 2020. "Japanese Foreign Exchange Interventions, 1971-2018: Estimating a Reaction Function Using the Best Proxy," Journal of the Japanese and International Economies, Elsevier, vol. 58(C).
    8. Lukas Menkhoff & Malte Rieth & Tobias Stohr, 2021. "The Dynamic Impact of FX Interventions on Financial Markets," The Review of Economics and Statistics, MIT Press, vol. 103(5), pages 939-953, December.
    9. Esaka, Taro & Fujii, Takao, 2026. "The lasting effect of yen-buying interventions: Two cases of Japanese FX interventions in 1997–98 and 2022," Journal of International Money and Finance, Elsevier, vol. 160(C).
    10. Elizabeth Bucacos & Javier García-Cicco & Miguel Mello, 2023. "Foreign Exchange Interventions and Foreign Shocks. The case of Uruguay," Documentos de trabajo 2023008, Banco Central del Uruguay.
    11. Toshio Utsunomiya, 2013. "A new approach to the effect of intervention frequency on the foreign exchange market: evidence from Japan," Applied Economics, Taylor & Francis Journals, vol. 45(26), pages 3742-3759, September.
    12. Smita Roy Trivedi, 2020. "The Moses effect: can central banks really guide foreign exchange markets?," Empirical Economics, Springer, vol. 58(6), pages 2837-2865, June.
    13. Watanabe, Tsutomu & Yabu, Tomoyoshi, 2013. "The great intervention and massive money injection: The Japanese experience 2003–2004," Journal of International Money and Finance, Elsevier, vol. 32(C), pages 428-443.
    14. Svitlana Galeshchuk, 2017. "Technological bias at the exchange rate market," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 24(2-3), pages 80-86, April.
    15. Bai, Yiyi & Dang, Tri Vi & He, Qing & Lu, Liping, 2022. "Does lending relationship help or alleviate the transmission of liquidity shocks? Evidence from a liquidity crunch in China," Journal of Financial Stability, Elsevier, vol. 58(C).
    16. Moura, Marcelo L. & Pereira, Fatima R. & Attuy, Guilherme de Moraes, 2013. "Currency Wars in Action: How Foreign Exchange Interventions Work in an Emerging Economy," Insper Working Papers wpe_304, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.

    More about this item

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications

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