Chih-nan ChenBack to index

  • A New Method for Identifying the Effects of Foreign Exchange Interventions

    Abstract

    Central banks 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 apply the Bayesian MCMC approach to this endogeneity problem. We use “data augmentation” to obtain intraday intervention amounts and estimate the efficacy of interventions using the augmented data. Applying this new 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 much 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.

    Introduction

    Are foreign exchange interventions effective? This issue has been debated extensively since the 1980s, but no conclusive consensus has emerged. A key difficulty faced by researchers in answering this question is the endogeneity problem: the exchange rate responds “within the period” to foreign exchange interventions and the central bank reacts “within the period” to fluctuations in the exchange rate. This difficulty would not arise if the central bank responded only slowly to fluctuations in the exchange rate, or if the data sampling interval were sufficiently fine.

  • A New Method for Identifying the Effects of Central Bank Interventions

    Abstract

    Central banks 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.

    Introduction

    Are foreign exchange interventions effective? This issue has been debated extensively in the 1980s and 1990s, but no conclusive consensus has emerged. A key difficulty faced by researchers in answering this question is the endogeneity problem: the exchange rate responds “within the period” to central bank interventions and the central bank reacts “within the period” to fluctuations in the exchange rate. As an example, consider the case of Japan. The monetary authorities of Japan, which are known to be one of the most active interveners, started to disclose intervention data in July 2001, and this has rekindled researchers’ interest in the effectiveness of interventions. However, the information disclosed is limited: only the total amount of interventions on a day is released to the public at the end of a quarter, and no detailed information, such as on the time of the intervention(s), the number of interventions over the course of the day, and the market(s) (Tokyo, London, or New York) in which the intervention(s) were executed, is disclosed. Most importantly, the low frequency of the disclosed data poses a serious problem for researchers because it is well known that the Japanese monetary authorities often react to intraday fluctuations in the exchange rate

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