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