Does the dollar have an outsized effect on trade prices?



An influential recent paper notes that a disproportionate share of global trade is invoiced in US dollars and claims that dollar invoicing causes trade prices to follow movements in the dollar. The implication is that when the dollar is overvalued, trade may be suppressed because the prices of traded goods are artificially high. With trade prices fixed in dollars, monetary policy outside the United States is unable to influence the relation between export and import prices and thus loses an important channel of transmission to overall economic activity. This post examines 22 economies to see if the substantial dollar appreciation of 2014–15 raised their export prices. Such an effect occurs in only two economies: Israel and Thailand. In other economies, export prices follow domestic prices or a trade-weighted average of prices in foreign currencies. For a few economies in Europe, export prices appear to follow the euro. The evidence thus indicates that any effect of dollar invoicing on trade prices is very brief and does not create a lasting distortion in global trade.

The analysis presented here focuses on the period surrounding the sharp and sustained appreciation of the dollar that began in late 2014 and ended in mid-2015. The dollar appreciated against nearly all currencies, by an average of around 20 percent, making this time frame a natural experiment to test whether the dollar has any major and persistent effect on prices in global trade. Export prices are analyzed from all economies with available data and nominal GDP greater than $50 billion in 2019, excluding the United States, members of the euro area, and economies with primary commodity exports greater than one-third of their merchandise exports.1 Data for the resulting 22 economies are displayed in the figure below.

Movements in export price (the red lines) are compared with changes in each economy's producer price indexes (exporter PPI, the green lines), the US PPI converted into exporter currency (the blue lines), and trade-weighted PPI in the rest of the world (ROW) converted into exporter currency (ROW PPI, the orange lines).2 All prices are normalized at 100 in 2013, the year before the dollar appreciation.

The comparison of export price to PPIs is apt because almost all international trade occurs between businesses and not directly with consumers. Trade prices move with producer prices at home and abroad. Movements of exchange rates show up as movements in the US PPI and ROW PPI relative to exporter PPI. The dollar appreciation, in particular, is visible as the rise in the blue line after 2013. For Hong Kong and Israel, which kept their currencies closely tied to the dollar, the blue line rises by less than in the other economies, reflecting mainly the modest rate of inflation in the US PPI.

As can be seen from the figure, export prices move with US PPI in only Israel and Thailand; even in these economies, export prices rose by less than the dollar did. In the other economies, export prices move with either exporter PPI or ROW PPI. Somewhat surprisingly, the dollar does not have an outsized effect on export prices in Mexico. However, the close trade links between Mexico and the United States imply a large weight on US prices in ROW PPI, and there is evidence of an effect of ROW PPI on export prices in Mexico.

Substantial dollar appreciation generally did not raise export prices

The table groups economies based on the change in export price from before to after the period of dollar appreciation: 2013–16. The first column displays economies for which the change in export price over this period was closest in value to the change in exporter PPI. The second column displays economies for which the change in export price was closest to the change in ROW PPI. The third and fourth columns display economies for which the change in export price was closest to the change in US PPI and euro area PPI, respectively.

Economies grouped by change in export price compared to changes in producer price indexes (PPI) converted into exporter currency, 2013-16
PPI most closely correlated with change in export price
Exporter Rest of world (foreign weighted average) Dollar Euro
China Czech Republic Israel Croatia
Hong Kong Japan Thailand Denmark
India Korea   Hungary
Romania Mexico*   Sweden
Switzerland Pakistan   United Kingdom
Vietnam Philippines    
Note: This table groups economies based on the change in export price from 2013 to 2016 compared to changes in various PPIs converted into exporter currency. The first column includes economies in which the change in export price is closest in value to the change in exporter PPI. The second column includes economies in which the change in export price is closest in value to the change in ROW PPI. The third column includes economies in which the change in export price is closest in value to the change in US PPI. The fourth column includes economies in which the change in export price is closest in value to the change in euro area PPI.
* The changes in export prices in these economies were closest to the change in the euro, but they were only slightly farther (less than 4 percentage points in each economy) from the change in foreign weighted average prices. For comparison, the distance between the maximum and minimum PPI change in each economy was more than 35 percentage points. We put these economies in the second column because we suspect the correlation with the euro is mostly spurious.
Sources: International Monetary Fund’s International Financial Statistics database, Eurostat, and J.P. Morgan (accessed via Bloomberg). The following additional sources were accessed via Macrobond: national sources, Asian Development Bank, European Commission, and Organization for Economic Cooperation and Development.

It appears that export prices follow the euro for some economies in and around Europe, but the euro did not move a lot relative to most other currencies during this period, and thus the timeframe does not pose a good test of the euro's importance in trade pricing. Excluding the euro from this exercise would result in Denmark, Sweden, and the United Kingdom being placed in the first column and Croatia and Hungary being placed in the second column. None would be added to the third column.

The main hypotheses researchers have proposed for export pricing are producer currency pricing (PCP), local (or destination) currency pricing (LCP), and dominant currency pricing (DCP). Another pricing hypothesis is global currency pricing (GCP), in which export prices are determined in global markets, similarly to the way commodities are priced. Economies in the first column would appear to be mainly in the PCP camp. Economies in the third and fourth columns appear to be in the DCP camp, under the assumption that either the dollar or the euro is a dominant currency.

It is not clear whether economies in the second column are in the LCP camp or the GCP camp. LCP would align export prices with foreign prices weighted by bilateral exports. GCP would align export prices with global average prices, weighted by GDP or total trade. The J.P. Morgan trade weights used to calculate ROW PPI are a combination of bilateral export, bilateral import, and third-party export weights. As such, they do not correspond closely to either LCP or GCP weights. Further research is needed to determine the best characterization of export pricing in economies in the second column.

Overall, there is little support for the claim that the dollar has a significant and persistent effect on global trade prices.


1. Primary commodity prices are set in global markets and do not differ significantly across exporters. Commodity exports are the sum of agricultural raw materials exports, food exports, fuel exports, and ores and metals exports (all expressed as a percentage of merchandise exports) in 2019 (2018 or 2017 data are used in some cases). Data are from the World Bank, World Development Indicators database.

2. The ROW PPI is calculated by dividing exporter PPI by J.P. Morgan's PPI-based broad real effective exchange rate. See Joseph Lupton, Gabriel de Kock, and Bruce Kasman, "Updating J.P. Morgan Effective Exchange Rate Indexes," JPMorgan Chase Bank, Economic Research, New York, April 21, 2015.

Data Disclosure

The data underlying this analysis are available here.

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