Appendix 1. Dominant Currency Pricing24
When prices are sticky, the invoicing currency of cross-border transactions has significant implications for external adjustment (that is, how trade prices and volumes react to exchange rate movements). To illustrate this, consider a simple representation of trade flows—
Trade prices in the exporter’s currency
Under sticky prices, quantities can be assumed to be a function of prices in the currency of the destination country (the importer)—that is, traded volumes are demand-determined—as well as some demand shock (Da→b):
In this setup, the effects of exchange rate changes on bilateral trade flows from a to b are driven (directly) by the exchange rate pass-through to prices in the exporter’s currency
The Mundell-Fleming Framework, Producer Currency Pricing, and Local Currency Pricing
Under the Mundell-Fleming framework, the most relevant exchange rate for trade between countries a and b would be their bilateral exchange rate (eab). This is because the Mundell-Fleming framework does not allow for the following:
Product market frictions, whereby exporters may charge different markups across destination markets (for example, due to strategic market complementarities). Hence, exporters’ markups (λa→b) do not respond to exchange rate changes.
Exporters’ use of imported intermediate inputs or decreasing marginal returns to labor: This means that exporters’ marginal costs
do not respond to exchange rate fluctuations either.
If exporters’ markups and marginal costs do not respond to exchange rate fluctuations, the exchange rate pass-through to prices in the exporters’ currency is zero, while the pass-through to prices in the importers’ currency is 1. These predictions are consistent with the producer currency pricing (PCP) paradigm, which assumes that international trade is invoiced in the currency of the exporter and that prices in that currency are rigid. Furthermore, nominal depreciation increases the price of imports relative to exports, thus improving competitiveness.
An alternative international pricing framework developed by Betts and Devereux (2000) and Devereux and Engel (2003)—in response to evidence against the law of one price that holds under PCP—assumes that prices are set and are rigid in the currency of the importer—so-called local currency pricing (LCP). In this case, bilateral exchange rate movements should lead to a complete pass-through to prices in the exporter’s currency
The Dominant Currency Pricing Framework
Recent empirical work raises questions about the validity of both PCP and LCP, showing that trade tends to be invoiced in a small number of “dominant currencies,” with the US dollar playing a prominent role (Goldberg and Tille 2008; Gopinath 2015), and that trade prices tend to be rigid in such currencies (Gopinath and Rigobon 2008; Fitzgerald and Haller 2012). More recently, Casas and others (2017) and Boz, Gopinath, and Plagborg-Møller (2018) show that, when prices are set in a third (dominant) currency ($), trade flows between countries a and b are also affected by exchange rates vis-à-vis the dominant currency (ea$ and ei$). They find that the exchange rate pass-through from the dominant currency to both export and import prices is high, while the pass-through of the bilateral (nondominant) exchange rate is small, thus providing evidence against both PCP and LCP.25 The authors also develop a model to explain these phenomena: the dominant currency pricing (DCP) framework.
Building on the approach proposed by Boz, Gopinath, and Plagborg-Møller (2018) and Gopinath and others (2020), the dominant role of the US dollar is explored by analyzing, at the country-pair level, the relationship of traded prices and quantities to the exchange rate vis-à-vis the trading partner (eab) and the US dollar (ea$).
The framework is extended to examine the implications of DCP for the exchange rate elasticity of the trade balance. To this end, trade prices and volumes are estimated from the perspective of both the exporter and the importer. On the export (import) side, the focus is on the effects of a depreciation of the exporter’s (importer’s) currency on trade volumes and prices in the exporter’s (importer’s) currency. All these elements are necessary to compute the trade balance effect of a depreciation, for which a country-level perspective that accounts for the exporting and importing behavior of each economy is necessary.
Specifically, while the empirical estimation focuses on trade flows between country pairs
This expression can be used to assess the impact of different exchange rate movements once the relevant price and volume elasticities vis-à-vis the bilateral and US dollar exchange rates are estimated. Finally, the country-level price and quantity elasticities are combined with measures of trade openness (X/Y and X/Y) to derive the response of the trade balance, as a share of output, which takes the following form:26
in which X/Y and M/Y denote export- and import-to-GDP ratios, respectively, and the last term on the right side indicates a similar expression for imports to the one written in full for exports.
This general expression can be used for two thought experiments of interest:
External adjustment: The relevant thought experiment from the perspective of correcting a country’s external imbalance is a movement of its exchange rate vis-à-vis all other currencies. In the example above, this would imply a shift in a’s currency vis-à-vis all other currencies, including the US dollar (that is, deaj = dea$ = de for all j ≠ a. The exchange rate between a and any other country would vary (in the same proportion), while exchange rates between any other two currencies would remain unchanged.
Global US dollar shifts: If prices are set in US dollars, movements in the value of this currency vis-à-vis others would have implications for bilateral trade not only between the United States and the rest of the world, but also among third countries. These effects can be gauged by studying the responses of bilateral trade flows to movements in the exchange rate vis-à-vis the US dollar, while other bilateral exchange rates remain unchanged (that is, dea$ = de; deaj = 0 for all j ≠ $).
Appendix 2. Measuring Foreign Currency Debt Exposure in the Nonfinancial Corporate Sector28
The refined measure of foreign currency debt exposure in the nonfinancial corporate sector follows the methodology outlined in Box 2. The overall measure is available for 36 major advanced and emerging market economies for 2001–19. Advanced economies comprise Australia, Austria, Canada, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Japan, the Netherlands, Norway, Portugal, Sweden, United Kingdom, and the United States. Emerging market economies comprise Argentina, Brazil, Chile, China, the Czech Republic, Hungary, India, Indonesia, Israel, Korea, Malaysia, Mexico, the Philippines, Poland, Russia, South Africa, Thailand, and Turkey. Financial centers, such as Switzerland, Hong Kong SAR, Singapore, and the United Kingdom, are excluded from the analysis.
Several facts are worth mentioning regarding the two indicators of foreign currency debt exposure presented in Box 2. First, although the two measures correlate well (the correlation between the two measures is greater than 0.8), the “top-down” approach generally yields slightly higher exposure levels than the “bottom-up” approach. This difference stems from the fact that the top-down approach can fail to purge noncorporate items from the total amount reported in the Bank for International Settlements (BIS) Global Liquidity Indicators, whereas the bottom-up approach does not capture some corporate-related items (for example, holdings of foreign currency corporate debt that are held locally). As a result, we use an average of the two measures to generate the indicators of foreign currency exposure through debt in the nonfinancial corporate sector depicted in Figures 11 and 12 of this Staff Discussion Note. Second, some disaggregated components in the BIS Locational Banking Statistics and IMF Monetary and Financial Statistics are not always available since 2001 for all countries. As a result, long time series for the top-down indicator do not purge for residual foreign currency loans (both cross border and local) on the government and household sectors, which are available only since 2013. Similarly, the long-time-series version of the bottom-up approach does not include cross-border foreign currency loans to nonfinancial corporations, which are also available only since 2013. For the regression analysis, the top-down measure is used due to its superior coverage across time and countries, although results are robust to using different versions (or combinations) of the two measures.
Appendix 3. The Financial Channel of Exchange Rates—Macroeconomic Empirical Specification and Data29
The macroeconomic empirical model builds on Gopinath and others (2020) and IMF (2019). Estimations are conducted at the bilateral level, where each observation is composed of the observed price and volume of a cross-border transaction between two countries. The model is extended to include exchange-rate-induced balance sheet effects for both the exporter and importer. The following equations are estimated as the baseline specification:
in which Δlnei$t is the change in country i’s currency vis-à-vis the US dollar, and
Each equation includes the following controls:
country-pair fixed effects to capture structural characteristics of any bilateral trade relationship, such as distance, common language, and so on
time fixed effects to capture global shocks that can affect trade in any given year
exporters’ producer price index growth to proxy for exporters’ production costs
importers’ consumer price index and GDP growth to capture, respectively, competitors’ prices and demand shocks
The estimated equations include three lags for all variables to explore short- as well as medium-term effects.
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