Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
This paper studies shock-dependent exchange rate pass-through for Japan with a Bayesian structural vector autoregression model. We identify the structural shocks by complementing the traditional sign and zero restrictions with narrative sign restrictions related to the Plaza Accord. We find that the narrative sign restrictions are highly informative. They substantially sharpen and even change the inferences of the exchange rate shock originally identified with only the traditional sign and zero restrictions through distinguishing the exchange rate shock from the demand shock. We apply our model to “forecast” the dynamics of the exchange rate and prices conditional on certain foreign exchange interventions in 2018, which provides important policy implications for our shock-identification exercise.