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.
JEL Classification Numbers: C11, C22, F31, F37