STEVEN PENNINGS 18 bilateral PT regression (similar to Table 4, Column 3), the coefficient on the sectoral PPI is around 0.6 (not reported). While this is smaller than the comparable estimates in the data, the model does correctly predict much larger pass-through of the sectoral PPI than foreign competitors’ prices.

# 7. Conclusions

In this paper, I show that a multi-country extension of a general class of models with variable markups (and possibly imported intermediates) predicts that movements in competitors’ exchange rates should affect US import and producer prices. Because bilateral and competitors’ RERs are generally positively correlated, excluding competitors’ RERs will bias upward measures of bilateral pass-through in the univariate passthrough regressions common in the literature. The model’s mechanism suggests that competitors’ RERs affect foreign competitors’ prices as an intermediate step. I find evidence in favor of these predictions using BLS microdata at the product level.

Using a specific form of the model based on AB, I run similar regressions on simulated data. Quantitatively, the model is able to explain around half of pass-through of competitors’ RERs to import prices and almost all of pass-through to US producers prices. While the presence of imported intermediates can boost pass-through of competitors’ RERs to import prices, the size of the effects depend on the exact structure of international production.

An online appendix is available at: https://sites.google.com/site/stevenpennings/PenningsCompPTAppendixFinalWeb.pdf

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