Exchange rate uncertainty and import prices in the euro area

• Author: Boris Blagov
• Published date: 01 November 2019
• DOI: http://doi.org/10.1111/roie.12434
• Date: 01 November 2019

Rev Int Econ. 2019;27:1537–1572.

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INTRODUCTION

Does an increase in exchange rate uncertainty influence import prices? How do export and import

firms react when faced with elevated levels of exchange rate fluctuations? Since abandoning the gold

standard, exchange rates have exhibited high volatility while most macroeconomic aggregates have

remained stable (Baxter & Stockman, 1989; Corsetti, Dedola, & Leduc, 2008; Obstfeld & Rogoff,

2000). In addition, it has been shown that the pass‐through from changes in the level of the exchange

rate to import prices (ERPT) for many advanced economies is low.1

From the viewpoint of international trade theory, however, exchange rate uncertainty does influence

the pricing behavior of firms. The relationship is yet complex and the reaction of import prices depends

ultimately on which party bears the exchange rate risk. In the literature on exchange rate uncertainty and

international trade flows, for example, exchange rate risk arises as a product of the leads in contracts

Received: 11 December 2018

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Revised: 12 June 2019

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Accepted: 10 July 2019

DOI: 10.1111/roie.12434

ORIGINAL ARTICLE

Exchange rate uncertainty and import prices in the

euro area

BorisBlagov

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction

in any medium, provided the original work is properly cited.

© 2019 The Authors. Review of International Economics published by John Wiley & Sons Ltd

RWI—Leibniz Institute for Economic

Research, Essen, Germany

Correspondence

Boris Blagov, RWI—Leibniz Institute for

Economic Research, Hohenzollernstr. 1–3,

45128, Essen, Germany.

Email: boris.blagov@rwi-essen.de

Abstract

This paper analyzes the effects of exchange rate uncertainty

on the pricing behavior of import firms in the euro area.

Uncertainty is measured via the volatility of the structural

shocks to the exchange rate in a nonlinear vector‐autore-

gressive model framework and is an important determinant

of import prices. An increase in exchange rate uncertainty

is associated with a fall in prices on average, which sug-

gests that the exchange rate risk is borne by the importers.

Controlling for the origin of imports (within or outside the

euro area) is important for assessing the impact of exchange

rate movements on prices.

JEL CLASSIFICATION

C11; C22; F31

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BLAGOV

and lags in payments in international trade (Canzoneri, 1984; Clark, 1973; Froot & Klemperer, 1989;

Gagnon, 1993; Hooper & Kohlhagen, 1978). If the contracts are stipulated in the exporters' currency,

it is then the importers who bear the exchange rate risk. In this case, higher uncertainty results in

lower import demand, which ultimately drives prices downwards. In contrast, if the exporters bear the

exchange rate risk, it gets priced in as means of hedging and therefore prices rise. In the literature on

ERPT for example, exchange rate risk arises from the difference in the way that products are sold in the

importing market (Devereux & Engel, 2002). Producers might choose to sell their products directly or

go through a distributor. In the former case, exporters bear the exchange rate risk, while in the latter it is

carried by the distributors/importers, who buy products in a foreign currency and sell it at the domestic

market. Thus, again it is important which party bears the risk, even if it is for different reasons.

Given this ambiguity it is natural to turn to empirical studies to examine which case gains more

support from the data. However, the empirical literature on exchange rate uncertainty and trade has

been inconclusive as well and, for the most part, it has focused on the effects on trade flows (i.e., quan-

titites) with only limited attention paid to prices. For example, Cushman (1983) analyzes the bilateral

trade flows between the United States and Germany, France, Canada, and Japan and reports negligible

effects of exchange rate risk on prices. Kroner and Lastrapes (1993) use a similar country dataset and

report statistically significant impact on prices only for Japan and the United Kingdom. Anderton and

Skudelny (2001) set up a panel for the euro area member states and find in most cases insignificant ef-

fects of exchange rate uncertainty on prices. Meanwhile, more recent studies on ERPT have advocated

the importance of the link between exchange rate volatility and import prices. For example, Campa

and Goldberg (2005), Corsetti et al. (2008), Frankel, Parsley, and Wei (2012), and Ozkan and Erden

(2015) show that the exchange rate volatility is an important determinant of the ERPT and hence

should be considered in pass‐through models to alleviate potential bias in ERPT estimates.

Given the inconclusive theoretical and empirical evidence of exchange rate uncertainty as a driver

of import prices and the potential importance for policy makers, in this paper we set out to investigate

the relationship empirically. Our starting point is a setup from the ERPT literature, which we aug-

ment along several dimensions. First, we use a structural vector‐autoregressive model (SVAR) with

stochastic volatility to identify the exchange rate shocks, whose conditional volatility we interpret as

a measure of exchange rate uncertainty.2

The stochastic volatility component is then introduced as an

additional exogenous regressor in the VAR, making the level of the endogenous variables a function

of the second moments. This allows us to estimate how import prices react following an increase in

the exchange rate uncertainty.3

While this paper is primarily focused on the effects of exchange rate uncertainty on import prices,

it contributes to the ERPT literature as well through its use of a novel dataset on import prices for

the euro area and some of its largest economies.4

The main advantage of these data is that the price

index is available for intra‐ and extra‐euro area trade separately. This may help alleviate potential bias

when it comes to ERPT estimates since a significant proportion (on average 40%) of euro area trade

takes place between the member states. Controlling for the origin of trade was previously possible

only when using unit value indices instead of import prices, which, however, reflect not only quantity,

but also quality changes of the goods.5

A further advantage of our dataset is the availability of addi-

tional subcomponents of the price index. It has been highlighted in the literature that the relationship

between the exchange rate dynamics and import prices is heterogeneous across industries (De Bandt,

Banerjee, & Kozluk, 2008). We can therefore use these new data to gain further insight into the inter-

play between import prices and exchange rates.

Our findings contribute to the literature in three ways. First, we show that exchange rate uncer-

tainty is an important determinant of import prices in the euro area. On average an increase of the

exchange rate uncertainty leads to a fall in import prices. This decline is primarily driven by a decrease

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in the prices of intermediate goods. On the contrary, consumer and capital goods' prices either rise

or are unresponsive. Moreover, significant effects from exchange rate volatility are observed even in

cases where the ERPT is extremely low or insignificant. Second, we find that the effects on import

prices from extra‐euro area trade are more pronounced than those from intra‐euro area trade. These

findings show that a bias in ERPT estimates would arise when the aggregate import price index is

used. Third, the country specific analysis highlights the prevalent notion in the literature of a large de-

gree of pricing behavior heterogeneity across countries. Furthermore, the effects of uncertainty vary

across product groups and origin of imports. These results suggest that even in the presence of low

ERPT exchange rate fluctuations are a source of inflation.

The remainder of this article is structured as follows. In the next section, we present our dataset

to highlight the gains from using disaggregation by origin of imports. In Section 3 we lay down the

econometric framework for the extraction of our measure of exchange rate uncertainty and present our

findings on the interplay between import prices and exchange rate uncertainty. In Section 4 we discuss

different specifications of the model to test the robustness of the findings. Section 5 concludes.

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DATA AND SPECIFICATION

In this section, we lay down the fundamentals for the analysis of the effects of exchange rate uncer-

tainty on the pricing behavior of import firms. To this end we present our dataset in the context of the

large ERPT literature and discuss the most important determinants of import prices.

We use an industrial import price index dataset from Eurostat’s short‐term business statistics. The

series start in 2005 for most countries and are available at a monthly frequency. The countries cov-

ered are the euro area 19 aggregate, Germany, France, Italy, Spain, Netherlands, Greece, Slovakia, and

Lithuania.6 The data reflect actual transaction prices including discounts (i.e., not list prices). They take

into account cost, insurance and freight at the national border of the importing country (excluding duties

or import taxes), and price determining qualities of the imported products (e.g., service and guarantee

conditions). They are recorded at the transfer of ownership, and are expressed per unit of goods.7

The dataset tracks price development of an array of goods in multiple industries based on the

Classification of Products by Activity (CPA)/NACE Rev.2 classes B, C, and D. These products are

then grouped together in end‐use categories that constitute the Main Industrial Groupings (MIG) and

further aggregated to a composite index.8

In this study we analyze the following indices: composite

import price index (CMP), consumer goods (CNS), capital goods (CAP), and intermediate goods

(NTR) and omit the energy index, mainly because of its dependence on the commodities markets,

where prices are dominated by the dynamics of the U.S. dollar.

A notable feature of the data is that it is available for intra‐euro area imports (intra), extra‐euro area

imports (extra), and as an aggregate series (agg). Intra‐euro area trade accounts for about two‐thirds

of the trade volume within the European union (EU28). This could result in a bias arising in ERPT

estimates, since a large share of the dynamics of the import prices might not be explainable through

changes in the exchange rate. Take as an example the following simplified reduced‐form analysis,

where changes of the log‐import prices,

Δp

, are regressed on log‐changes of the exchange rate,

Δe

,

and other control variables.

By definition

Δeintra =0

, hence

𝛽intra

1

is indeterminate. The aggregate price index is a (possi-

bly time‐varying) weighted average of the prices of intra‐ and extra‐euro area imports, that is,

(1)

Δ

p

agg

t

=𝛼+𝛽

extra

1

Δe

extra

t

+𝛽

intra

1

Δe

intra

t

+controls+𝜖

1,t.