PRI Discussion Paper Series (No.23A-03)

Invoice Currency Choice in Intra-Firm Trade:
A Transaction-Level Analysis of Japanese Automobile Exports
Faculty of Economics, Chuo University, Japan / Policy Research Institute,
Ministry of Finance, Japan

Taiyo YOSHIMI
Policy Research Institute, Ministry of Finance, Japan

Uraku YOSHIMOTO
Faculty of International Social Sciences, Yokohama National University,
Japan / Policy Research Institute, Ministry of Finance, Japan

Kiyotaka SATO
School of International Relations and Public Policy, Columbia
University, The United States / National Graduate Institute for Policy
Studies, Japan
Takatoshi ITO
Faculty of Economics, Gakushuin University, Japan / Policy ResearchInstitute, Ministry of Finance, Japan
Junko SHIMIZU
Faculty of Economics, Shiga University, Japan / Policy ResearchInstitute, Ministry of Finance, Japan
Yushi YOSHIDA

The views expressed in this paper are those of theauthors and not those of the Ministry of Finance or
the Policy Research Institute.

Research Department Policy Research Institute, MOF
3-1-1 Kasumigaseki, Chiyoda-ku, Tokyo 100-8940, JapanTEL 03-3581-4111

Invoice Currency Choice in Intra-Firm Trade:
A Transaction-Level Analysis of Japanese Automobile Exports**
Taiyo YOSHIMI*3
Uraku YOSHIMOTO*4
Kiyotaka SATO*5
Takatoshi ITO*6
Junko SHIMIZU*7
Yushi YOSHIDA*8

Abstract
This study empirically investigates the extent to which the choice of invoice currency differs
between intra-firm and arm’s length exports. We also examine whether other firm- and product-levelfactors affect the choice of invoice currency. This study is the first to be granted access to highly
disaggregated transaction-level data on Japanese automobile exports to France. By conducting panel
logit estimation, we demonstrate that importers’ currency tends to be chosen in intra-firm export
invoicing, which has not been rigorously shown in previous literature. Our empirical findings remainrobust when introducing different types of intra-firm export variables and other conventional
explanatory variables such as firm- and product market share, exchange rate volatility, a dummy forintermediate goods exports, euro-invoiced imports, labor productivity, and research anddevelopment intensity. Amid growing intra-firm trade and expanding global value chains, Japaneseparent firms tend to invoice using the importer’s currency, assuming the foreign exchange risk thatarises from intra-firm trade; thus, exchange rate risk management is a significant consideration forJapanese parent firms.
Keywords: Invoice currency; Intra-firm trade; Japan Customs data; Market share; Export
competitivenessJEL classification: F14; F31

 This study is the result of research conducted jointly with the Policy Research Institute (PRI) of the Japanese Ministry of Finance(MOF), which submitted an offer to the MOF based on the “Guideline on the utilization of Customs’ import and export declaration
data in a joint research with the Policy Research Institute,” and received approval in February 2022. The views expressed in thisresearch are the authors’ personal responsibility and do not represent the official views of the MOF or PRI. We would like to thankFumiharu Ito, Kenta Ando, Shintaro Negishi, and the seminar participants at PRI. We acknowledge financial support from the JSPS
KAKENHI Grant (JP20H01518 and 20KK0289 to Yoshimi, JP21K20172 to Yoshimoto, JP19H01504, 23H00836, and 23K17550
to Sato, JP18K01698 to Shimizu, and JP22K18527 to Yoshida). All subsequent errors are our own.
 Corresponding author: Taiyo Yoshimi; Address: Faculty of Economics, Chuo University, 742-1 Higashinakano, Hachioji-shi,
Tokyo, 192-0393, Japan. Tel: +81-42-674-3424; Fax: +81-42-674-3425; E-mail: yoshimi@tamacc.chuo-u.ac.jp.
Faculty of Economics, Chuo University, Japan / Policy Research Institute, Ministry of Finance, Japan
Policy Research Institute, Ministry of Finance, JapanFaculty of International Social Sciences, Yokohama National University, Japan / Policy Research Institute, Ministry of Finance, Japan
School of International Relations and Public Policy, Columbia University, The United States /National Graduate Institute for Policy Studies, JapanFaculty of Economics, Gakushuin University, Japan / Policy Research Institute, Ministry of Finance, JapanFaculty of Economics, Shiga University, Japan / Policy Research Institute, Ministry of Finance, Japan1

1.

Introduction
The choice of invoice currency has attracted considerable attention in the field of international economics.

As demonstrated by Obstfeld and Rogoff (2000), when considering the impact of macroeconomic policy acrosscountries, the choice of invoice currency (i.e., whether exporters choose the producer’s currency pricing (PCP),
the local currency pricing (LCP), or third-currency pricing) determines the extent of international shocktransmission. As a result, optimal monetary and exchange rate policies significantly depend on firms’ chosen
invoice currency for exports and imports (e.g., Devereux and Engel, 2003).
Numerous research efforts have been devoted to assessing the determinants of invoice currency choice.
Many recent studies have empirically analyzed how the choice of invoice currency is affected by micro andmacroeconomic factors using highly disaggregated transaction-level customs data to determine invoice currency
in each export/import transaction. For instance, using unpublished micro data on Canadian imports, Goldberg
and Tille (2016) revealed a correlation between the size of individual transactions and invoice currency inaddition to the impact of conventional macroeconomic factors such as exchange rate volatility and exchange rate
regime. Devereux et al. (2017) also used Canadian data to investigate the impact of exporter’s and importer’smarket share on the chosen invoice currency.1 This study is the first to employ Japan Customs’ transaction-level
data, which have not been previously disclosed to researchers. In early 2022, the Japanese Ministry of Finance(MOF) started allowing the use of large-scale customs transaction-level data for empirical research, including
detailed information on Japanese export and import transactions, on the condition of maintaining the anonymityof firms that made customs declarations in exports and/or imports. Our research group was approved for thisstudy and granted use of the transaction-level data of exports and imports for the 2014–2020 period.
The novelty of this study is its rigorous investigation of whether invoice currency choice differs between
intra-firm and arm’s-length trade. We use a panel dataset constructed employing the Japanese transaction-level
customs data. Although global value chains (GVCs) have become an important consideration in the empirics ofinternational economics (e.g., Timmer et al., 2014), a limited number of studies have investigated the invoicecurrency choice along GVCs. For instance, motivated by recent research on GVCs, Chung (2016) and Amiti etal. (2022) considered the effect of imported intermediate inputs on exporting firms’ invoice currency choice.2
These studies demonstrated that when more intermediate inputs are imported from abroad and invoiced in foreign
currencies, it is more likely for exporting firms to use foreign currencies in their exports of production goods.
Such trade transactions along production chains are usually expected to be conducted via intra-firm trade between
group companies; however, these studies did not clearly distinguish intra-firm trade from arm’s-length trade
when analyzing the effect of the invoice currency choice. Another example is Ito et al. (2018), who employed aquestionnaire survey of Japanese export firms, revealing that invoice currency choice significantly differed
between intra-firm and arm’s-length exports. While the authors presented notable findings on Japanese firms’
invoice currency choice, only 227 firms’ valid responses to the questionnaire survey were included, and the

1 Many other examples can be cited, including Gopinath, Itskhoki, and Rigobon et al. (2010) for the US; Casas et al. (2017) and
Gopinath et al. (2020) for Colombia; Hayakawa et al. (2019b) for Thailand; Chen et al. (2022) and Corsetti et al. (2022) for the UK;
Montfaucon et al. (2021) for Malawi; Amiti et al. (2022) for Belgium; and Saygılı (2022) for Turkey.
2 We also identify several studies in the literature of exchange rate pass-through (ERPT) that considered GVCs, which is closely
related to invoice currency choice. Neiman (2010) empirically examined possible differences in ERPT between intra-firm andarm’s-length trade using a transaction-level dataset obtained from the US Bureau of Labor Statistics, revealing that the degree of
ERPT between intra-firm and arm’s-length import transactions differs significantly. Rondeau and Yoshida (2023) investigated theeffect of value-added contributions of exporters and importers on the degree of ERPT to Japanese imports, demonstrating that thedegree of ERPT increases for industries with higher contributions from exporting countries’ value-added and/or lower contributions
from importing countries’ value-added.

2

empirical results are based on pooled cross-section data representing a limited number of observations.3
We focus on Japanese automobile exports to France to investigate how invoice currency choice differs
between intra-firm and arm’s-length trade. The automobile sector is one of Japan’s largest export sectors, andJapanese automobile firms have established a considerable number of overseas subsidiaries across the world,
actively exporting products to these subsidiaries, and intra-firm trade has a significant role in such transactions.
We choose France as the destination country because the proportion of arm’s-length exports account for around
20%–30% of the trade flow, which enables us to conduct a rigorous empirical examination of possible differences
in invoice currency choice between intra-firm and arm’s-length exports.4
The identification of intra-firm trade is the key issue in this research. Invoice currency choice has not been
rigorously examined because it is difficult without knowing detailed information on exporters and importers suchas their names and addresses to identify whether import firms are overseas subsidiaries or independent firms
without capital ties, even when we use transaction-level customs data. We matched the Japan Customs’ data withexternal sources of overseas subsidiaries and capital relationships. Focusing on Japanese automobile exports toFrance, we could precisely identify the capital ties between exporters in Japan and importers in France. In theempirical analysis, we use alternative definitions of intra-firm exports considering the degree of capital ties. We
present the details of this approach in Section 2.
Our empirical examination demonstrates that the euro is more likely to be chosen for intra-firm exports thanarm’s-length exports, implying that Japanese automobile firms tend to stabilize the euro-based export price inintra-firm exports to France, assuming all exchange rate risks that arise from euro-invoiced transactions. In arm’slength exports to France, Japanese firms prefer invoicing in yen, passing the exchange rate risk to French
importers. This result remains robust to using alternative definitions of intra-firm trade. We also find thatexporters tend to use the euro when the proportion of the euro in imports is high, the firms’ market share in
France is high or low, or when the yen is less volatile against the euro. These findings are consistent with thoseof previous studies such as Devereux et al. (2017). We also find that the euro is used more for exports of final
goods than for intermediate goods. We interpret this result as meaning that the chosen invoice currency tends tomatch the destination country’s currency when exported products are finally consumed. Furthermore, regarding
firm characteristics, we find that labor productivity and research and development (R&D) investment, which canbe considered non-price sources of export competitiveness that negatively affects the likelihood of euro-invoiced
transactions. We interpret this result as meaning that exporters can offer the use of the home currency in invoicing
when they hold significant bargaining power that is generated by competitiveness in the destination country.
The remainder of this paper is organized as follows. Section 2 describes the Japanese customs data and thetransaction-level panel dataset constructed for this study. Section 3 presents the empirical framework and ourbaseline results. Section 4 checks the robustness of the empirical findings. Finally, Section 5 concludes this paper.

2.
2.1.

Data
Matching Methodology
We use Japanese customs data that was newly disclosed to conduct this research. The data contain thefollowing information for each export and import transaction: (i) trade value (in yen), (ii) corresponding quantity
3

Friberg and Wilander (2008) also conducted a questionnaire survey of Swedish exporters, which provided us with useful
information on firm-level Swedish export invoicing decisions; however, the study did not identify significant differences between
intra-firm and arm’s-length trade in the invoice currency choice. Ito et al. (2018) conducted two questionnaire surveys of Japaneselisted firms in 2009 and 2013 for their empirical analysis; however, as noted previously, panel estimation was not conducted since
a limited number of firms responded to the surveys twice.
4 In fact, the proportion of arm’s-length trade in this sector is extremely low for some importing countries.

3

(numbers and/or weight such as tons or kilograms), (iii) invoice currency, (iv) product information (Harmonized
System (HS) nine-digit classification), (v) identification information for Japanese exporters and importers (IDnumber, name, address, and telephone number), (vi) destination or source country, (vii) trade partners’
information (name and address), and (viii) transaction date, time, and other relevant details. The sample periodspans from the first day of 2014 to the last day of 2020.
Although the data enable access to all transactions of all products for all partner countries, we focus on
automobile exports to France to precisely identify the degree of capital ties between exporters and importers.
Because we cannot directly obtain information on capital ties to differentiate intra-firm and arm’s-length tradefrom the Japanese customs data, we identify importers with financial ties to Japanese exporters by conducting
machine matching using the Python software. The machine matching was conducted based on firm-level capital
relationship data provided by the Teikoku Data Bank (the original source of which is the Bureau van Dijk’s Orbis
database), in addition to the name and address of exporters and importers obtained from the customs data. French
importers’ names and addresses are submitted by Japanese exporters or customs brokers, and unfortunately, thisinformation is not recorded in a consistent manner, and typographical errors are observed. This issue could reduce
the accuracy of the machine matching procedure; therefore, for validation and accuracy, we complementarily
match importers and exporters manually.
Furthermore, the Orbis database does not necessarily cover all overseas subsidiaries of Japanese auto
exporters; therefore, we prepare additional lists of overseas subsidiaries from two other databases, including thedatabase for Japanese companies expanding business abroad (Kaigai Shinshutsu Kigyo Soran), which is
published by Toyo Keizai Inc. and the MarkLines Information Platform, which includes extremely detailed andcomprehensive data on automobile production from countries around the world. 5 These databases are also
included in our manual matching procedure, expanding the share of matches in the manual procedure, which islarger than that of the machine procedure. As long as manual matching has an important role to compensate formachine matching, dealing with all sample countries and industries is not a reasonable option.6
We choose to focus on Japanese automobile exporters because automobiles are one of Japan’s largest export
products and have a macroeconomic impact on the Japanese economy. In addition, Japanese automobile firms
have established a considerable number of overseas subsidiaries across the world, which indicates thesignificance of intra-firm trade in the sector. To ensure a sufficient number of Japanese export firms, we chose
12 parent firms that produce completed automobiles and/or motorcycles. We also include five domestic
subsidiaries in Japan that are directly owned by the above parent firms with at least a 50% ownership stake.
Therefore, we examine data for 17 Japanese auto firms that export completed automobiles and motorcycles andrelated parts and components to France.
We choose France as the sample destination country for two reasons. First, the yen and the euro (i.e., thelocal currency) are predominantly used in this trade flow, and the proportion of other currencies is negligible.
Doing so may render the invoice currency choice in our target trade flow more immune to the dominant currency
paradigm (DCP) proposed by Gopinath et al. (2020). We are able to focus on the binary choice of invoicecurrency between PCP and LCP, which is theoretically simpler than including a third dominant currency such as
the USD. As a comparison, panels (a) and (b) in Figure 1 illustrate the share of yen and USD in Japan’s exports
and imports to/from the world for all industries, respectively, revealing a significant share of USD in contrast to

5 In addition to the above three data sources, when necessary, we double-checked the websites of import firms to confirm ourfindings.
6 For instance, in April 2014, more than 1.6 million export transactions to the world were conducted by more than 50 thousand
firms. Covering all these samples is not reasonable to conduct manual matching to compensate machine matching.

4

our sample trade flow. One may think that we can extend the sample to other EU countries since the yen and theeuro are supposed to be dominant for other EU countries. Panels (c) and (d) in Figure 1 show the share of yen,
USD, and EU countries’ currencies, (including the euro) in Japan’s exports and imports to/from EU countries for
all industries, respectively. Compared with the case for the world, the proportion of USD has been small in recent
years, hovering around 12%–14% for both exports and imports; however, the USD still has a notable share,
implying that the USD could be one option considered by Japanese exporters and importers in these trade flows.
We subsequently focused on Japanese automobile exports to France, as only the yen and euro are used in mosttransactions. Our second reason for choosing this trade flow is that the share of arm’s-length exports is significant,which allows us to conduct a reasonable comparison between intra-firm and arm’s-length trade with a sufficientnumber of samples for both types of trade. As additional information, Figure 2 illustrates the sales of Japanese
automakers in major destination countries obtained from the MarkLines database,7 indicating that France is thefifth largest overseas market for Japanese automakers. Furthermore, Figure 3 presents foreign automaker’s sales
in France, showing that Japanese automakers have the second largest share of the French market, indicating astrong presence of Japanese automakers in France.

2.2.

===

Figure 1======

Figure 2======

Figure 3===

Definitions of Intra-firm Exports
One challenge in identifying intra-firm and arm’s-length exports is determining a definition of overseas

subsidiaries based on the degree of capital ties between Japanese exporters and French importers. We consider
the following five types of overseas subsidiaries, that are graphically illustrated in Figure 4, for inclusion in intrafirm exports.
Sub-1 firm: Overseas firms that are directly owned by a parent firm in Japan with at least a 10% ownershipstake.
Sub-2 firm: Overseas firms that are directly owned by a Sub-1 firm with at least a 50% ownership stake.
Sub-3 firm: Overseas firms that are directly owned by a Sub-2 firm with at least a 50% ownership stake.
Sub-Sub-1 firm: Overseas firms that are directly owned by domestic subsidiaries (i.e., the parent firm’s
subsidiaries in Japan) with at least a 10% ownership stake.
Sub-Sub-2 firm: Overseas firms that are directly owned by a Sub-Sub-1 firm with at least a 50% ownershipstake.

===

Figure 4===

As previously noted, we consider the exports of 17 Japanese firms, including 12 parent firms and fivedomestic subsidiaries. We set up the four definitions of intra-firm exports as follows.
Intra-firm 1: Seventeen Japanese firms’ exports to Sub-1 and Sub-2 firms.
Intra-firm 2: Seventeen Japanese firms’ exports to Sub-1, Sub-2, and Sub-3 firms.
7

Figures 2 and 3 represent the value of sales since the MarkLines database only provides this information, whereas our empiricalanalysis is conducted for each transaction (not the transaction value).

5

Intra-firm 3: Seventeen Japanese firms’ exports to Sub-1, Sub-2, Sub-Sub 1, and Sub-Sub 2 firms.
Intra-firm 4: Seventeen Japanese firms’ exports to Sub-1, Sub-2, Sub-3, Sub-Sub 1, and Sub-Sub 2 firms.
The definition of intra-firm exports is narrowest in intra-firm 1 and broadest in intra-firm 4. Intra-firm 2
adds Sub-3 firms to intra-firm 1, while intra-firm 3 adds Sub-Sub 1 and Sub-Sub 2 firms to intra-firm 1 without
including Sub-3 firms. In this sense, intra-firm 2 and intra-firm 3 complement one another. We obtain 114,335
export transactions for the whole sample period (2014–2020). Among these transactions, the share of intra-firm
exports ranges from 73.4% to 81.2%, depending on the definition of intra-firm trade. Table 1 presents the
proportion of intra-firm trade for each definition, and Figure 5 shows the share of intra-firm and arm’s-length
trade each year.

===

Table 1======Figure 5===

Table 2 presents the number and share of transactions using the yen and euro. We excluded transactions
with other currencies because they accounted for less than 0.1% of the total number of transactions and wereomitted from our empirical investigation. The upper panel shows the number and shares in the full sample. Our
sample’s total number of transactions ranges from 14.8 thousand to 18.7 thousand, depending on the year. The
euro share was larger than that of the yen in all sample years.
Nevertheless, the yen had a significant share each year, and the proportions of the two currencies arecomparable in some sample years (i.e., in 2017 and 2020). The lower panel shows the number and share by trade
type. We counted the number and calculated the share based on the four alternative classifications of intra-firmtrade introduced in Table 1. A clear contrast between intra-firm and arm’s length trade is evident, revealing thatthe euro had a dominant share in intra-firm trade, whereas the yen had a dominant share in arm’s length trade,which holds for all four classifications of intra-firm trade. Notably, the local currency (i.e., the euro) is used morein intra-firm trade than in arm’s length trade.

===
3.
3.1.

Table 2===

Empirical Analysis
Empirical Framework
To examine the choice of invoice currency in intra-firm trade, we estimate the following empirical equation

for Japanese firm i’s export transaction k of a product defined at the HS nine-digit level in year t to France:
𝑦, ,
𝑦, ,

,

,

𝛼

𝛽𝐼𝑛𝑡𝑟𝑎 , ,

,

𝛾𝑋

𝜀, ,

(1),

,

is a dummy variable that takes a value of one for transactions invoiced in the euro and zero for

those invoiced in the yen. As noted above, since most transactions are conducted in terms of either the euro oryen, we excluded samples with other types of invoice currency. 𝐼𝑛𝑡𝑟𝑎 , ,,is a dummy variable that takes avalue of one for intra-firm export transactions and zero otherwise. We hypothesize that the euro is more likely to
be chosen in intra-firm trade, implying a positive sign of 𝛽. We interchangeably use the alternative definitionsof intra-firm trade shown in Table 1 to validate the robustness of the results. 𝑋 is the vector of other explanatory
variables. In the baseline analysis, we employ four variables in addition to the intra-firm dummy. First, we include
an intermediate goods dummy 𝐼𝑛𝑡𝑒𝑟𝑚𝑒𝑑𝑖𝑎𝑡𝑒, which takes a value of one if the product in the transaction
6

represents intermediate goods and zero for final goods.8 We expect that the euro (i.e., the local currency) is more
likely to be used for final goods exports, as final goods are sold to French customers in the euro when imported
from Japan; thus, importers had significant motivation to invoice these final goods in the euro, indicating anegative coefficient for 𝐼𝑛𝑡𝑒𝑟𝑚𝑒𝑑𝑖𝑎𝑡𝑒. It is also expected that this variable could correlate with the intra-

firm dummy, as intermediate goods might be exported to a manufacturing center of the same company group in
the local market. Nevertheless, our baseline results remain unchanged when we introduce intra-firm and theintermediate goods dummies separately.9
Second, we consider the share of invoice currency in imports, capturing this variable (𝐼𝐼𝑆 , ) by using thenatural log of the share of the number of import transactions invoiced in the euro in the total number of importtransactions conducted by the firm each year. We are also allowed to use Japan’s transaction-level customs importdata, although our focus is on firms’ export behavior. We use this import information to examine the possible
effect of invoice currency share in intermediate input imports on the exporters’ invoice currency decision, which
has been well documented by Chung (2016).10 Firms tend to choose the same currency for exports and imports
of intermediate inputs to offset the exchange rate risk arising from export and import transactions; therefore, we
expect a positive coefficient for this variable.
Third, we include the natural log of the exchange rate volatility of the yen vis-à-vis the euro in each year
(𝑉𝑜𝑙 ). We define this volatility as the standard deviation of the daily average exchange rate. As noted by
Devereux et al. (2004), risk-averse exporters prefer the exporter’s currency when the value of the currency isvolatile against the importer’s currency. In our context, we expect that the euro is less likely to be chosen when
the yen is more volatile against the euro. In this regard, we expect a negative coefficient for 𝑉𝑜𝑙 . The exchange
rate data are obtained from the Pacific Exchange Rate Service from the University of British Columbia.
Fourth, we use the natural log of each firm’s market share in each product category at the HS six-digit levelin each year (𝐹𝑖𝑟𝑚𝑀𝑆 ,, ). The numerator of this market share variable is calculated based on the export valueof the HS six-digit product from Japan to France, which is obtained from the Japanese customs data. The
denominator is the total global export value, including Japan to France, calculated based on data obtained fromthe UN Comtrade database and Trade Statistics of Japan. Several previous studies have demonstrated thatinvoicing currency is related to exporters’ market share. For instance, Devereux et al. (2017) showed thatexporters’ market share has a nonlinear impact on the choice of invoice currency using transaction-level Canadian
import data, determining that small exporters are more likely to choose LCP as market share rises; however,when the market share reaches a certain threshold, increased market share makes exporters more likely to choose
PCP. We construct the market share variable by dividing the total exports of each product by each exporter by
the total exports of that product from the world to France. Table 3 presents the descriptive statistics of ourempirical variables in the full sample and for each type of trade.

===

Table 38===

We regard 39, 40, and 72–90 in HS two-digit, 8706–8708 and 8714 in HS four-digit, and 870990 and 871690 in HS six-digit asintermediate goods. The other categories in 87 (HS two-digit) are considered as final goods. We exclude HS8710 (Tanks and otherarmoured fighting vehicles, motorized, whether or not fitted with weapons, and parts of such vehicles) and HS8715 (Baby carriages
and parts thereof), as they are not relevant to this study.
9 As an alternative interpretation of the intermediate goods dummy, this variable may capture whether the export destination is amanufacturing center or a sales center. It is more likely that the importer is a manufacturing center for intermediate goods
transactions, while the importer may be a sales center in the case of final goods transactions.
10 The impact of the import side variable on export performance has been examined in previous research. For example, using
Belgian firm-product-level data, Amiti et al. (2014) showed that more import-intensive exporters have significantly lower exchange
rate pass-through into their export prices, as they face offsetting exchange rate effects on their marginal costs. In the context of tradefacilitation, Hayakawa et al. (2019a) documents that import processing time affects export performance using the Thai customs
data.

7

3.2.

Baseline Results
We examine how invoice currency choice in intra-firm trade differs from that in arm’s-length trade. Table
4 presents our baseline results. 𝐼𝑛𝑡𝑟𝑎1 , , , to 𝐼𝑛𝑡𝑟𝑎4 , , , are constructed based on intra-firm 1 to intrafirm 4, respectively. All estimations are conducted using the logit model. The table presents the marginal effectfor all explanatory variables. The marginal effect is evaluated using the mean value of all explanatory variables.
We do not employ any fixed effects (FEs) in columns (I)–(IV), and firm, HS six-digit, and year FEs are included
in columns (V)–(VIII). Including these FEs does not affect the signs of the coefficients and their significance inmost cases.

===

Table 4

Examining column (I), we find that 𝐼𝑛𝑡𝑟𝑎1 , ,,===has a positive impact, indicating that the euro is more

likely to be chosen in intra-firm trade. This implies that Japanese automobile firms tend to use the euro more in
intra-firm exports to France, with the parent firm in Japan assuming all exchange rate risks arising from LCP. In
arm’s-length exports to France, Japanese firms prefer invoicing in yen, passing on the exchange rate risk to
French importers. It is also found that 𝐼𝑛𝑡𝑒𝑟𝑚𝑒𝑑𝑖𝑎𝑡𝑒11

likely to be used in exports of intermediate goods.

has a negative impact, indicating that the euro is less

Regarding the share of the euro in imports, 𝐼𝐼𝑆 , positively

affects the likelihood of using the euro in exports; thus, Japanese automobile firms tend to choose the same
invoice currency for both exports and imports to offset the exchange rate risk. Exchange rate volatility, 𝑉𝑜𝑙 ,has a negative impact on euro-invoiced exports from Japan to France, which is consistent with the theoreticalprediction in Devereux et al. (2004) that Japanese automobile exporters prefer invoicing in yen when the yen ismore volatile against the euro. 𝐹𝑖𝑟𝑚𝑀𝑆 ,,has a positive impact, indicating that firms with a larger market

share in the destination market tend to use the euro, implying that Japanese automobile exporters may invoice
exports in the euro to increase market share in France. We examine the possibility that market share has anonlinear impact in the robustness checks below (Section 4), as proposed by Devereux et al. (2017). The results
remain unchanged when we employ alternative definitions of the intra-firm trade dummy, as shown in columns(II)–(IV).
The magnitude of the impact of all these explanatory variables is reduced by the inclusion of FEs. We
examine the magnitude of the impact of the intra-firm trade dummy in the case with the FEs provided that pseudo
R-squares are significantly higher in this case than in the case without the FEs. Exchange rate volatility (𝑉𝑜𝑙 ) is
dropped in columns (V)–(VIII) as it has a perfect correlation with the year FE. The marginal effect of𝐼𝑛𝑡𝑟𝑎1 , ,,is 0.098 in column (V), indicating that the probability of choosing the euro is 9.8% higher inintra-firm trade than in arm’s-length trade. This magnitude does not change much across alternative definitionsof intra-firm trade, as shown in columns (VI)–(VIII).

4.

Robustness Check
We conduct three robustness tests in this section, including (a) the nonlinear impact of firm market shareand the impact of product market share, (b) alternative definitions of the invoice currency share of imports, and(c) the impact of firm productivity and R&D investment. The results of these robustness checks are presented in

11

It may be assumed that most trade of intermediate goods is conducted between group companies, which indicates that theintermediate goods dummy may have a positive correlation with the intra-firm trade dummy. Indeed, approximately 90% of intrafirm transactions in our dataset represent intermediate goods trade, but the results change negligibly when we exclude
from our estimations.
𝐼𝑛𝑡𝑒𝑟𝑚𝑒𝑑𝑖𝑎𝑡𝑒8

Table 5, with columns (I)–(III) for presenting the results of analysis (a), columns (IV) and (V) for analysis (b),and (VI) and (VII) for analysis (c). The significant positive impact of the intra-firm trade dummy persists in allthese robustness checks, while the magnitude of the marginal effect changes somewhat, validating our baseline
findings.

===

Table 5===

4.1.

Market Share Variables
Devereux et al. (2017) asserted that firms’ market share has a nonlinear impact on the choice of invoicecurrency. Referencing this assumption, we examine the nonlinear impact of 𝐹𝑖𝑟𝑚𝑀𝑆 , , by introducing its
squared term 𝑠𝑞 𝐹𝑖𝑟𝑚𝑀𝑆 ,,. The result is shown in column (I) of Table 5, and the impact for the squared

term is insignificant, while the impact of firms’ market share remains significantly positive. Thus, we do not finda nonlinear impact of 𝐹𝑖𝑟𝑚𝑀𝑆 ,,as demonstrated by Devereux et al. (2017).

We also investigate the impact of (the natural log of) of Japanese exporters’ market share in total exports
from the world to France for each HS6 product category (𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑀𝑆, ), which is calculated based on theexport value and the total export from the rest of the world to France obtained from the UN Comtrade database.
We consider this variable to modestly capture the competitiveness of Japanese products in the French market.
We use product and firm market share separately as we use the same data (i.e., product-level total exports toFrance) for the denominator of both measures, leading to a systematic positive correlation between the measures.
Column (II) of Table 5 shows that product market share has a significant negative impact, indicating that the yen
is more likely to be chosen when the exported product has competitiveness in the French market, which isconsistent with Ito et al.’s (2012) findings regarding the invoicing decisions of Japanese exporters in automobile,electrical machinery, and general machinery industries. This result suggests that Japanese firms that export highly
differentiated products tend to use the yen in export invoicing. Regarding nonlinearity, the squared term of thisvariable 𝑠𝑞 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑀𝑆,, has a significant negative impact, as shown in column (III). This indicates thatthe effect of product-level market competitiveness increases with products’ market share, where a higher market
share makes it easier for exporters to implement home currency invoicing (PCP) to avoid exchange rate risk.

4.2.

The Share of the Invoice Currency in Imports
Firms may offset payments for imports and receipts from exports denominated in a foreign currency tominimize exposure to exchange rate fluctuations, as noted by Chung (2016). To examine this offsetting behavior,
we employed 𝐼𝐼𝑆 , in the baseline analysis, which is the share of euro invoicing in imports calculated based on
the number of transactions. In this subsection, we use two alternative measures of import invoice share to assessrobustness. First, we employ the euro invoicing share of imports, which is calculated based on the import value(𝐼𝐼𝑆_𝑣𝑎𝑙𝑢𝑒 , ). The invoice currency share used in high-value transactions is reflected more significantly using
this definition compared with the baseline measure. The result is presented in column (IV) of Table 5. The impactof this measure is significantly positive, similar to the baseline results in column (V) of Table 4. Compared withthe baseline findings, the coefficient is somewhat lower (0.034

0.022), indicating that the transaction-based

import invoice share is more closely related to the choice of invoice currency in export transactions than thevalue-based import invoice share. The second alternative measure 𝐼𝐼𝑆_𝑖𝑛𝑡 , is defined by the proportion of
euro-based transactions of intermediate goods in firms’ total imports of intermediate goods, based on the numberof transactions following the baseline measure. We examine this measure considering that Japanese automakers
may use imported intermediate goods to produce final or intermediate goods that are then exported abroad.
Therefore, the link between this measure and the choice of invoice currency for exports may be more significant
9compared to our baseline measure. The result is shown in (V) of Table 5, and we find a significantly positive
impact of this measure. The magnitude is almost comparable to the baseline measure, although it is slightly larger
for this alternative measure.

4.3.

Firm Productivity and R&D Investment
Numerous studies have argued that firm characteristics are important elements affecting invoice currency

choice. For example, using a Belgian firm-level dataset, Amiti et al. (2022) determined that the choice of invoicecurrency is “an active firm-level decision” and that firms’ size, exposure to imported inputs, and competitors’
choice have significant impacts. We consider firm characteristics of labor productivity (𝐿𝑎𝑏𝑜𝑟𝑃𝑟𝑜𝑑 , ) and R&D
investment (𝑅&𝐷/𝑆𝑎𝑙𝑒𝑠 , ). The former variable is defined as the natural log of total sales divided by the numberof employees, and the latter variable is defined as the natural log of R&D expenditure divided by total sales. We
introduce these two variables separately because total sales are used to define both variables, and there is asystematic negative correlation between these two variables. Despite time-series variation, both variables are
relatively stable during our sample period and have a notable high correlation with firm FE. In addition, thenumber of samples (especially the number of exporters) significantly decreases when we introduce detailed FEs.
To avoid this issue, we define quartile dummy variables that take a value of one for each quartile of firm sales
and zero otherwise and employ these dummies instead of firm FE. We also use the HS two-digit FE for productFE instead of the HS six-digit FE.
Referencing previous research, we may expect either sign of productivity. 12 Based on the model ofendogenous price markup, higher productivity leads to higher price markup through improvement in productquality (e.g., Antoniades, 2015). In the flexible price equilibrium, the elasticity of the trade price becomes higher
with respect to changes in production cost caused from exchange rate fluctuations when the price markup ishigher. Considering the case in which a profit maximizing exporter chooses invoice currency, which replicatesthe flexible price allocation in the presence of price stickiness referencing Gopinath and Itskhoki (2010),
productive exporters may prefer the foreign currency, implying a positive coefficient for our productivity
measure. In contrast, if productivity captures the firm-level competitiveness in the destination market, productive
exporters may use their own currency for trade invoicing, as Ito et al. (2013, 2018) demonstrated with a productlevel analysis. Column (VI) of Table 5 reveals that the impact of 𝐿𝑎𝑏𝑜𝑟𝑃𝑟𝑜𝑑𝑖,𝑡 is significantly negative,
supporting the latter scenario. Furthermore, 𝑅&𝐷/𝑆𝑎𝑙𝑒𝑠𝑖,𝑡 is also interpreted as a source of firms’ non-priceexport competitiveness. Column (VII) shows that this variable has a significantly negative impact.

5.

Concluding Remarks
Recent empirical research in international economics and finance has emphasized GVCs in which active

intra-firm trade transactions between group companies are observed; however, rigorous empirical analysis
regarding the choice of invoice currency in intra-firm trade is limited. The contributions of this study are twofold. First, we rigorously examine which invoice currency is chosen and the factors related to the determinationof invoice currency in intra-firm trade. Second, this study uses the highly detailed transaction-level data obtained
from Japan Customs, which have not previously been accessed for empirical research. Thus, our study presents
the first empirical research regarding the determinants of invoice currency in intra-firm trade using the highly
disaggregated Japan Customs transaction-level data.
Our empirical examination demonstrates that the euro is more likely to be chosen for intra-firm exports
12

To the best of our knowledge, no studies have directly examined the impact of productivity on the choice of invoice currency,
while several studies have investigated the relationship between exchange rate pass-through and productivity (e.g., Berman et al.,2012).

10

from Japan to France than for arm’s-length exports, implying that Japanese automobile firms tend to use the euro
more so that parent firms in Japan can assume the exchange rate risks arising from euro-invoiced exports. In
arm’s-length exports to France, Japanese firms prefer invoicing in yen, passing the exchange rate risk to French
importers. We also find that other conventional firm- and product-level factors have similar impacts on the choiceof invoice currency in our dataset compared with existing studies. As another aspect of this study’s novelty, we
determine that labor productivity and R&D investment, which can be considered sources of non-price export
competitiveness, have a negative impact on the likelihood of LCP. The impact of these firm characteristics on
the choice of invoice currency has rarely been investigated in a direct manner.
Our findings offer important insights into multinational companies’ exchange rate risk management,
showing that Japanese parent firms may choose LCP to centrally manage the group-wide exchange rate risk
arising from intra-firm trade. Therefore, as a natural consequence, firms increase LCP-based transactions as intrafirm trade expands with the widening and deepening of GVCs, making exchange rate risk management a moresignificant concern for Japanese parent firms. If firms are eager to reduce the exchange rate risk by using the yen,
one possible approach is to improve the non-price competitiveness of export products against non-groupimporters. By doing so, they can offer PCP to importers to reduce the exchange rate risk, at least in arm’s-length
trade. Even when exported from Japanese parent firms to overseas subsidiaries, strongly competitive products
enable overseas subsidiaries to have stronger negotiation power with local buyers, which may result in bettergroup-wide exchange risk management. According to our empirical findings, improving firm productivity andexpanding R&D investment are also effective.
Another interesting question is which currency is chosen in intra-firm trade between Japan and Asian
countries, since USD invoicing has been observed more strongly in Asian regional trade (Ito et al., 2018). Thisissue is also worth investigating in the context of DCP. This research question is left for our future research.

11

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Invoicing and Why It Matters” Quarterly Journal of Economics, 137(3), 1435–1493.
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Paradigm: A New Model for Small Open Economies” IMF Working Paper, WP/17/264.
Chen, Natalie, Wanyu Chung, and Dennis Novy (2022) “Vehicle Currency Pricing and Exchange Rate Passthrough” Journal of the European Economic Association, 20(1), 312–351.
Chung, Wanyu (2016) “Imported Inputs and Invoicing Currency Choice: Theory and Evidence from UK
Transaction Data” Journal of International Economics, 99, 237–250.
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Setting and Exchange-rate Flexibility” Review of Economic Studies, 70(4), 765–783.
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Devereux, Michael B., Wei Dong, and Ben Tomlin (2017) “Importers and Exporters in Exchange Rate Passthrough and Currency Invoicing” Journal of International Economics, 105, 187–204.
Friberg, Richard, and Fredrik Wilander (2008) “The Currency Denomination of Exports—A Questionnaire Study”
Journal of International Economics, 75(1), 54–69.
Goldberg, Linda S., and Cédric Tille (2016) “Micro, Macro, and Strategic Forces in International Trade
Invoicing: Synthesis and Novel Patterns” Journal of International Economics, 102, 173–187.
Gopinath, Gita, and Oleg Itskhoki (2010) “Frequency of Price Adjustment and Pass-through” Quarterly Journalof Economics, 125(2), 675–727.
Gopinath, Gita, Oleg Itskhoki, and Roberto Rigobon (2010) “Currency Choice and Exchange Rate Pass-through”
American Economic Review, 100(1), 306–336.
Gopinath, Gita, Emine Boz, Camila Casas, Federico J. Díez, Pierre-Olivier Gourinchas, and Mikkel PlagborgMøller (2020) “Dominant Currency Paradigm” American Economic Review, 110(3), 677–719.
Hayakawa, Kazunobu, Nuttawut Laksanapanyakul, and Taiyo Yoshimi (2019a) “How Does Import Processing
Time Impact Export Patterns?” World Economy, 42(7), 2070–2088.
Hayakawa, Kazunobu, Toshiyuki Matsuura, Nuttawut Laksanapanyakul, and Taiyo Yoshimi (2019b) “Export
Dynamics and the Invoicing Currency” ERIA Discussion Paper, ERIA-DP-2018-14.
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Currency by Globally Operating Firms: A Firm-level Analysis of Japanese Exporters” International
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Evidence from a Questionnaire Survey of Japanese Export Firms” RIETI Discussion Paper Series 13-E034.
12

Ito, Takatoshi, Satoshi Koibuchi, Kiyotaka Sato and Junko Shimizu (2018) “Managing Currency Risk: How
Japanese Firms Choose Invoicing Currency” Edward Elgar.
Montfaucon, Angella Faith, Kiyotaka Sato, Nagendra Shrestha, and Craig Parsons (2021) “Exchange Rate Passthrough and Invoicing Currency Choice between Fixed and Floating Exchange Rate Regimes: Evidence
from Malawi’s Transaction-level Data” Economic Analysis and Policy, 72, 562–577.
Neiman, Brent (2010) “Stickiness, Synchronization, and Passthrough in Intrafirm Trade Prices” Journal of
Monetary Economics, 57(3), 295–308.
Obstfeld, Maurice, and Kenneth Rogoff (2000) “New Directions for Stochastic Open Economy Models” Journalof International Economics, 50(1), 117–153.
Rondeau, Fabien, and Yushi Yoshida (2023) “Global Value Chains and Exchange Rate Pass-through into the
Import Prices of Japanese Industries” RIETI Discussion Paper Series 23-E-013.
Saygılı, Hülya (2022) “Invoicing Currency, Exchange Rate Pass-through, and Value-added Trade: The Case ofTurkey” International Journal of Finance & Economics, published online.
Timmer, Marcel P., Abdul Azeez Erumban, Bart Los, Robert Stehrer, and Gaaitzen J. de Vries (2014) “Slicing
Up Global Value Chains” Journal of Economic Perspective, 28(2), 99–118.

13

Table 1. Definitions of Intra-Firm Export
Intra-Firm Ratio
Definition

Scope of Intra-Firm Importers[2014–2020][Transaction-based]

Intra-firm 1

Sub-1 and Sub-2 firms

73.4%

Intra-firm 2

Sub-1, Sub-2, and Sub-3 firms

81.0%

Intra-firm 3

Sub-1, Sub-2, Sub-Sub 1, and Sub-Sub 2 firms

73.7%

Intra-firm 4Sub-1, Sub-2, Sub-3, Sub-Sub 1, and Sub-Sub 2 firms

81.2%

Source: Authors’ calculation

14

Table 2. Distribution of Invoice Currency
All
Number of transactions
Yen
Euro
2014
5,851
11,0952015
6,169
10,303
2016
7,749
10,916
2017
8,172
9,601
2018
6,269
10,115
2019
5,926
8,870
2020
8,309
9,297
By trade type
Intra1
Number of transactions
Intra-firm trade
Yen
Euro
2014
2,354
10,730
2015
2,029
9,956
2016
3,173
10,521
2017
2,351
9,015
2018
2,362
9,767
2019
2,883
8,608
2020
4,425
8,958
Intra2
Number of transactions
Intra-firm trade
Yen
Euro
2014
2,558
10,731
2015
2,549
9,964
2016
3,902
10,522
2017
4,202
9,016
2018
3,762
9,769
2019
4,495
8,617
2020
7,011
9,015
Intra3
Number of transactions
Intra-firm trade
Yen
Euro
2014
2,401
10,730
2015
2,095
9,956
2016
3,204
10,521
2017
2,383
9,015
2018
2,394
9,774
2019
2,907
8,611
2020
4,436
8,968
Intra4
Number of transactions
Intra-firm trade
Yen
Euro
2014
2,605
10,731
2015
2,615
9,964
2016
3,933
10,522
2017
4,234
9,016
2018
3,794
9,776
2019
4,519
8,620
2020
7,022
9,025

Share
Yen
2014
2015
2016
2017
2018
2019
2020

0.345
0.375
0.415
0.460
0.383
0.401
0.472

Euro
0.655
0.625
0.585
0.540
0.617
0.599
0.528

Share
Arm's-length trade
Yen
Euro
3,497
365
4,140
347
4,576
395
5,821
586
3,907
348
3,043
262
3,884
339

2014
2015
2016
2017
2018
2019
2020

Intra-firm trade
Arm's-length trade
Yen
Euro
Yen
Euro
0.180
0.820
0.905
0.095
0.169
0.831
0.923
0.077
0.232
0.768
0.921
0.079
0.207
0.793
0.909
0.091
0.195
0.805
0.918
0.082
0.251
0.749
0.921
0.079
0.331
0.669
0.920
0.080

Share
Arm's-length trade
Yen
Euro
3,293
364
3,620
339
3,847
394
3,970
585
2,507
346
1,431
253
1,298
282

2014
2015
2016
2017
2018
2019
2020

Intra-firm trade
Arm's-length trade
Yen
Euro
Yen
Euro
0.192
0.808
0.900
0.100
0.204
0.796
0.914
0.086
0.271
0.729
0.907
0.093
0.318
0.682
0.872
0.128
0.278
0.722
0.879
0.121
0.343
0.657
0.850
0.150
0.437
0.563
0.822
0.178

Share
Arm's-length trade
Yen
Euro
3,450
365
4,074
347
4,545
395
5,789
586
3,875
341
3,019
259
3,873
329

2014
2015
2016
2017
2018
2019
2020

Intra-firm trade
Arm's-length trade
Yen
Euro
Yen
Euro
0.183
0.817
0.904
0.096
0.174
0.826
0.922
0.078
0.233
0.767
0.920
0.080
0.209
0.791
0.908
0.092
0.197
0.803
0.919
0.081
0.252
0.748
0.921
0.079
0.331
0.669
0.922
0.078

Share
Arm's-length trade
Yen
Euro
3,246
364
3,554
339
3,816
394
3,938
585
2,475
339
1,407
250
1,287
272

2014
2015
2016
2017
2018
2019
2020

Intra-firm trade
Arm's-length trade
Yen
Euro
Yen
Euro
0.195
0.805
0.899
0.101
0.208
0.792
0.913
0.087
0.272
0.728
0.906
0.094
0.320
0.680
0.871
0.129
0.280
0.720
0.880
0.120
0.344
0.656
0.849
0.151
0.438
0.562
0.826
0.174

Source: Authors’ calculation
Notes: Numbers and shares are calculated focusing on transactions invoiced in yen or euro.

15

Table 3. Descriptive Statistics

All
Obs
Mean S.D.
y (euro dummy) 114,364 0.614 0.487
Intra1
114,364 0.762 0.426
Intra2
114,364 0.840 0.366
Intra3
114,364 0.764 0.425
Intra4
114,364 0.843 0.364
Intermediate
114,364 0.909 0.288
IIS
114,336 -1.741 0.496
IIS_value
114,336 -2.009 0.816
IIS_int
114,309 -1.851 0.565
FirmMS
114,364 -6.456 2.107
sq(FirmMS)
114,364 46.081 29.715
ProductMS
114,364 -3.617 1.445
sq(ProductMS) 114,364 15.169 11.141
ERVol
114,364 1.260 0.301
LaborProd
114,364 4.157 0.362
R&D/Sales
114,364 -3.164 0.243

Intra-firm trade
Obs
Mean S.D.
87,133 0.775 0.417
87,133 1.000 0.000
87,133 1.000 0.000
87,133 1.000 0.000
87,133 1.000 0.000
87,133 0.922 0.268
87,105 -1.620 0.464
87,105 -1.961 0.831
87,078 -1.736 0.557
87,133 -6.183 2.013
87,133 42.284 27.167
87,133 -3.578 1.444
87,133 14.887 10.934
87,133 1.250 0.296
87,133 4.148 0.374
87,133 -3.170 0.205

Source: Authors’ calculation

16

Arm's-length trade
Obs
Mean S.D.
27,231 0.097 0.296
27,231 0.000 0.000
27,231 0.330 0.470
27,231 0.010 0.098
27,231 0.339 0.474
27,231 0.865 0.341
27,231 -2.127 0.385
27,231 -2.160 0.745
27,231 -2.216 0.419
27,231 -7.330 2.161
27,231 58.229 33.955
27,231 -3.741 1.441
27,231 16.074 11.735
27,231 1.291 0.313
27,231 4.187 0.311
27,231 -3.140 0.348

Table 4. Baseline Results(I)
Intra1

(II)

(III)

(IV)

0.344 **

(V)

(VII)

(0.002)0.288 **

0.090 **

(0.006)(0.002)
0.344 **

Intra30.099 **

(0.004)(0.002)0.288 **

Intra40.091 **

(0.006)
Intermediate
IIS
FirmMS(VIII)

0.098 **

(0.004)Intra2(VI)(0.002)-0.296 **-0.357 **-0.297 **-0.358 **-0.124 **-0.136 **-0.124 **-0.136 **(0.008)(0.009)(0.009)(0.009)(0.009)(0.010)(0.009)(0.010)0.275 **

0.393 **

0.277 **

0.394 **

0.034 **

0.034 **

0.033 **

0.033 **

(0.003)(0.003)(0.003)(0.003)(0.007)(0.007)(0.006)(0.007)0.018 **

0.017 **

0.018 **

0.018 **

0.009 **

0.008 **

0.009 **

0.008 **

(0.001)(0.001)(0.001)(0.001)(0.001)(0.001)(0.001)(0.001)-0.009 **-0.017 **-0.008 **-0.017 **(0.003)(0.003)(0.003)(0.003)Firm FE

NO

NO

NO

NO

YES

YES

YES

YES

Year FE

NO

NO

NO

NO

YES

YES

YES

YES

ERVol

Product FE

NO

NO

NO

NO

YES

YES

YES

YES

Obs.

114,335

114,335

114,335

114,335

108,131108,131108,131108,131

Pseudo R2

0.457

0.385

0.456

0.384

0.872

0.854

0.873

0.854

Notes: The dependent variable is a dummy which takes a value of one if the transaction is invoiced in the euro and zero otherwise. The
logit model and robust standard errors are used in all estimations. ** indicates a 1% level of significance. Columns (I)–(IV) exclude
fixed effects (FEs), while we employ the firm, year, and HS six-digit product FEs in the remaining columns.

17

Table 5. Robustness Check
Intra1
Intermediate
IIS

(I)

(II)

(III)

(IV)

(V)

(VI)

(VII)

0.098 **

0.099 **

0.099 **

0.099 **

0.099 **

0.259 **

0.264 **

(0.002)(0.002)(0.002)(0.002)(0.002)(0.006)(0.006)-0.124 **-0.167 **-0.174 **-0.125 **-0.126 **-0.103 **-0.183 **(0.009)(0.009)(0.009)(0.009)(0.009)(0.002)(0.003)0.034 **

0.028 **

0.025 **

0.007 *

0.090 **

(0.007)(0.007)(0.007)(0.003)(0.004)0.022 **

IIS_value(0.002)0.035 **

IIS_intermediate_num(0.005)
FirmMSsq(FirmMS)

0.009 **

0.009 **

0.009 **

0.008 **

-0.001(0.002)(0.001)(0.001)(0.000)(0.001)0.000(0.000)

ProductMS-0.013 **-0.031 **(0.001)(0.003)-0.002 **sq(ProductMS)(0.000)-0.605 **LaborProd(0.007)-0.112 **R&D/Sales(0.006)
Firm FE

YES

YES

YES

YES

YES

Quartile

Year FE

YES

YES

YES

YES

YES

YES

YES

Product FE

YES

YES

YES

YES

YES

HS2

HS2

Obs.

108,131108,131108,131108,131108,131

110,060

110,060

Pseudo R2

0.872

0.869

0.869

0.872

0.872

0.752

0.671

Quartile

Notes: The dependent variable is a dummy variable that takes a value of one if the transaction is invoiced in the euro and zero otherwise.
The logit model and robust standard errors are used in all estimations. ** indicates a 1% level of significance. Firm, year, and HS sixdigit product fixed effects (FEs) are introduced in columns (I)–(V). In columns (VI) and (VII), we use dummy variables that take avalue of one for each quartile of firm sales and zero otherwise (i.e., quartile FEs) in addition to year and HS two-digit product FEs. The
squared term coefficient for firm MS in column (I) is −0.00000856.

18

Figure 1. Invoice Currency Choice in Japanese Trade with the World and EU Countries

2013

2016

2019

2022

2016

2019

2022

2007

2010

(c) Japanese Exports to EU Countries

2013

Yen

2004

2001

1998

1995

1992

1989

1980

2022

USD

2010

Yen

2019

0

2016

10

0

2013

20

10

2010

30

20

2007

40

30

2004

50

40

2001

60

50

1998

70

60

1995

80

70

1992

90

80

1989

100

90

1986

100

1983

(%)

1980

(%)

1986

(b) Japanese Imports from the World

1983(a) Japanese Exports to the World

USD(d) Japanese Imports from EU Countries

(%)

(%)

100

100

90

90
80

80

70
60

70
60

USD

EU currencies

Yen

USD

2007

2004

2001

2022

2019

2016

2013

2010

2007

2004

2001

1998

1995

1992

1989

1986

1983

1980

Yen

1998

0

1995

0

1992

20
10

1980

10

20

1989

30

1986

40

1983

50
40
30

50

EU currencies

Sources: Bank of Japan, Yushutsu Shinyojo Tokei (Export Letter of Credit Statistics); Ministry of International Trade and Industry(MITI), Yushutsu Kakunin Tokei (Export Confirmation Statistics); MITI, Yushutsu Hokokusho Tukadate Doko (Export Currency
Invoicing Report); MITI, Yushutsu Kessai Tsukadate Doko Chosa (Export Settlement Currency Invoicing); MITI, Yunyu Shonin
Todokede Hokokusho (Import Approval Notification Report); MITI, Hokokushorei ni Motozuku Hokoku (Report Based on Report
Guidance); MITI, Yunyu Hokoku Tokei (Import Report Statistics); MITI, Yunyu Hokokusho Tukadate Doko (Import Currency Invoicing
Report); MITI, Yunyu Kessai Tsukadate Doko Chosa (Import Settlement Currency Invoicing); website of Japan Customs.
Notes: 1999 data are not available. September data are used for 1992–1997, March data are used for 1998, and data for the second halfof the year are used for 2000–2022. 1986 data are fiscal year data for Japanese imports.

19

Figure 2. Japanese Automakers’ Sales in 10 Major Countries, Including Japan(Number of Unit)
35,000,000

30,000,000

25,000,000

20,000,000

15,000,000

10,000,000

5,000,000

0
China

US

Japan Germany
2014

2015

2016

India

France2017

2018

Brazil2019

Source: MarkLines Information Platform
Notes: Automobile sales in 48 major countries, including Japan, by manufacturers’ country.

20

UK
2020

Korea

RussiaFigure 3. Automobile Sales by Foreign Automakers in France(Number of Unit)

600,000
500,000
400,000
300,000
200,000
100,000
0

2014

2015

2016

2017

Source: MarkLines Information Platform

21

2018

2019

2020

Figure 4. Definitions of Foreign Subsidiaries

Japanese Firms

Parent Firm

Domestic
Subsidiary◆ 50% or more of aggregate ownership from
Parent Firm
◆ Automobile-related companies◆ Companies with foreign subsidiaries◆ Finished automobile and motorcycle
vehicle manufacturer

Sub-1 Firm
◆ 10% or more of aggregate ownership from
Parent Firm

Sub-Sub-1 Firm
◆ 10% or more of aggregate ownership from
Domestic SubsidiarySub-2 Firm
◆ 50% or more of aggregate ownership fromSub-1 Firm

Sub-Sub-2 Firm
◆ 50% or more of aggregate ownership fromSub-3 Firm

Sub-Sub-1 Firm

◆ 50% or more of aggregate ownership from

Foreign Subsidiaries

Sub-2 Firm

22

Figure 5. The Share of Intra-firm and Arm’s-length Exports in the Total Number of Export Transactions

2014
2015
2016
2017
2018
2019
2020

intra1
intra2
intra3
intra4
intra1
intra2
intra3
intra4
intra1
intra2
intra3
intra4
intra1
intra2
intra3
intra4
intra1
intra2
intra3
intra4
intra1
intra2
intra3
intra4
intra1
intra2
intra3
intra40

5,000

10,000Intra-Firm Trade

Source: Authors’ calculation

23

15,00020,000Arm's-Length Trade