PASS-THROUGH OF COMPETITORS’ EXCHANGE RATES 9 Table 1. Main empirical results

|Dependent Vble:||Real US Im|port Prices|||Real US P|roducer Pr|ices|
|---|---|---|---|---|---|---|---|---|
|(∆p over life of good)|(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|
|Bilateral RER (βBI)|0.23***|0.16***|0.15***|0.12**|-|-|-|-|
||[4.5]|[3.0]|[3.3]|[2.6]|||||
|Competitors’ RER (βC)|-|0.35***|-|0.19***|0.11***|0.34***|-|0.09***|
|||[3.9]||[3.0]|[6.6]|[22.8]||[3.7]|
|Foreign Comp Prices|-|-|0.58***|0.55***|-|-|0.16***|0.16***|
|(βF CP)|||[8.0]|[7.6]|||[13.2]|[13.0]|
|US Materials Prices|-|-|-|-|0.49***|-|0.41***|0.38***|
|(δM)|||||[24.7]||[17.0]|[14.6]|
|Observations|4953|4950|4573|4570|50513|50541|26934|26934|

Notes: Robust t-statistics are in brackets. ***,**,* indicate significance at the 1, 5 and 10 per cent levels. 1% tails dropped. All import price specifications include BLS primary lower stratum × country fixed effects, with standard errors clustered at this level. Both empirical specifications include controls for US GDP growth over the life of the good, date and life-length controls (not reported). With a common sample (including foreign competitors’ prices), estimates are very close to those in columns 2 and 5.

3.5. **Markup variation or imported intermediate inputs?** In the simple model, Equation 3 and Equation 7 show that third country RERs affect import and producer prices (respectively) via two channels: (i) a change in competitors’ prices which affects markups, and/or (ii) changes in the cost of imported intermediates from competitor countries which affect marginal costs.

For US producer prices, I can account for imported intermediates by controlling for US materials prices at the NAICS 6 digit level. If an appreciation of foreign competitors’ currencies raises imported intermediate costs, this will be reflected in total materials costs. Controlling for US materials prices in Table 1 reduces estimated pass-through of competitors’ exchange rates to US producer prices by 2/3 (from 0.34 to 0.11). This suggests that either the imported intermediates are quite important in explaining the univariate relationship between US producer prices and competitors’ exchange rates; or alternatively other variables (like global business conditions) affect materials prices, competitors’ RERs and US producer prices jointly.

For import prices, distinguishing between these two channels is difficult because I don’t have good data on imported intermediate goods prices by foreign country of origin.<sup>12</sup> It is also difficult to know the importance of imported intermediates based on aggregate imported intermediate shares. As an extension in Appendix C, I incorporate intermediate inputs in the quantitative model, and show that the extent to which imported intermediates boost pass-through of competitors’ RERs is sensitive not just to the total share of imported intermediates, but to the source country of the intermediates. For example, if intermediates are sourced from the US or from countries which are not competitors, bilateral RER pass-through is affected but pass-through of competitors’ RER might not be. Moreover, the total imported intermediate share varies substantially across countries (Figure 4), so it is unwise to rely too much on data from one country.

An alternative approach is to measure the effect of adding foreign competitors’ prices to the regression directly. Comparing Column 2 and Column 4 of Table 1, one can see that adding foreign competitors’ prices as a control almost halves pass-through of competitors’ exchange rates — however a residual effect is still significant and sizable. If foreign competitors’ prices were a sufficient statistic for the markup channel, one could argue that around half of the original βC = 0.35 coefficient were due to changes in markups via competitors’ prices, and the other half due to changes in marginal costs due to imported intermediates. However, foreign competitors’ prices are likely to be measured with some error (e.g. sampling error, or the

> 12I tried several imperfect proxies, which were either inconclusive, or failed to point to a large role of imported intermediates. Specifically, I tried to construct imported intermediate weights using the World Input Output Database (WIOD.org) and then create an imported-intermediate-weighted exchange rate (IIWER). However, the IIWER was highly collinear with competitors’ RERs, leading to over-fitting when both variables were added to the regression. In an earlier draft, I also tried interacting the coefficients of interest with a dummy variable if the country × two-digit sector had an above average imported intermediate share (using data from OECD STAN). The interactions terms were insignificant.