BIS Working Papers | No 884 | 08 September 2020 by Fernando Pérez-Cervantes PDF full text (473kb) | 44 pages Paper produced as part of the BIS Consultative Council for the Americas Research Network project "Exchange rates: key drivers and effects on inflation and trade" Summary Focus I use a simple model to study the econometric implications of allowing multi-product retailers to choose their markups on a price dynamics identification equation. To test the implications, I use a novel set of micro data which includes 23 million observations of
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Paper produced as part of the BIS Consultative Council for the Americas Research Network project "Exchange rates: key drivers and effects on inflation and trade"
I use a simple model to study the econometric implications of allowing multi-product retailers to choose their markups on a price dynamics identification equation. To test the implications, I use a novel set of micro data which includes 23 million observations of merchandise prices and identifies the type of store where the product is sold.
The model gives a closed form for the optimal markup of retailers that produces an estimate of the exchange rate pass-through (ERPT). The markup is equal to those in the previous literature (where retailers are assumed to operate under perfect competition) plus a correction (or flexible) term, proportional to the market shares of retailers. This term is usually negative. If retailers have no market power, the ERPT in my model is the usual ERPT, as estimated by the traditional literature. But if some retailers have market power, for example, because they are a large chain, then the ERPT as usually measured has a (most likely negative) bias that can be corrected easily. This contribution allows researchers with information on stores in price data sets to easily correct ERPT estimations both prospectively and historically. This also raises the question of the implications for monetary policy, given that ERPT has been underestimated for decades.
I first find that, in Mexico, ERPT varies by the type of store: stores that belong to a chain have a lower ERPT. Then, consistent with the model, I find that, controlling for the store type, the ERPT estimate is larger than the usual ERPT, which does not control for store type. This is because the store type coefficient captures the store's flexibility in setting its markup. Finally, when using data only for stores that do not belong to a chain, I find (i) that the ERPT estimate is larger than the usual estimate, and (ii) that this estimate does not change if the store type is used as a control.
I develop a structural model with nested CES preferences to obtain optimal markups for heterogeneous retailers when the prices of all their inputs are exogenous. The model predicts that, if the taste parameters are constant over time, the markups for retailers with higher market share are higher but have more flexibility, implying an incomplete pass-through of retailer input price into final retailer prices. I then focus on the exchange rate pass-through (ERPT) and use a unique data set of all the price changes of tradeable merchandise in the Mexican Consumer Price Index (CPI) data by store type to test the model. I find, consistent with the model, that (1) ERPT is different by store type; and (2) products sold in stores with negligible market share have the same ERPT regardless of the store type. Both results imply that the ERPT is estimated with bias when the store information is not used.
Keywords: exchange rate pass-through, markups, retailers