DPRIETI Discussion Paper Series 15-E-059

The Japan-U.S. Price Level Index for Industry Outputs

NOMURA Koji
RIETIMIYAGAWA Kozo
Keio University

The Research Institute of Economy, Trade and Industry

http://www.rieti.go.jp/en/

RIETI Discussion Paper Series 2015-E-059
May 2015

The Japan-U.S. Price Level Index for Industry Outputs∗
NOMURA Koji (RIETI and Keio University)
MIYAGAWA Kozo (Keio University)

Abstract
This paper provides new benchmark estimates of industry-level price differentials between Japan and the UnitedStates, based on the input-output framework expanded from the 2005 Japan-U.S. Input-Output Table published in2013 by the Ministry of Economy, Trade and Industry (METI). The purchasing power parities (PPPs) we constructcover not only the products for final demands, but also the products of outputs and for intermediate uses, using aclassification of 174 products. We postulate a price model describing the relationships among producers’ prices andpurchasers’ prices for domestically-produced and imported products, considering the differences in the trade structure,
freight and insurance rates, duty tax rates, wholesale and retail trade margins, and transportation costs in each productbetween Japan and the United States. Using demand-side data for purchasers’ price PPPs for final uses (e.g., theEurostat-OECD PPPs) and for intermediate uses (e.g., the METI survey), producers’ price PPPs for outputs are
estimated based on our price model and the related parameters. Many sources of data on price differentials byagencies and ministries of the government of Japan are used in this paper.
Compared to our previous study in Nomura and Miyagawa (1999), which developed the 1990 benchmark
estimates of industry-level price differentials between Japan and the United States, there are several improvements.
One improvement is the expansion in the framework and the price model to cover imports from China, Germany,
Korea, Malaysia, Taiwan, and Thailand. The second improvement is our revisions on PPPs for wholesale and retailtrades. The revisions of PPPs for trade have a considerable impact on the estimates of PPP for gross domestic product(GDP) from the production side. In this paper, we examine Japan’s margin rates and provide new estimates byproducts, based on establishment data from the Census of Commerce in 2002 and 2007 by METI. Our estimatessuggest that the margin rates of retail in the official benchmark input-output table may be underestimated.
Our estimates enable us to illuminate the sources of price competitiveness through inter-industry transactions. Higher
costs of products for intermediate use such as trade, electricity, and other energy in Japan have considerable and wider
impacts on the price competitiveness in all industries. Japan’s higher costs of trade (54% higher) and electricity (2.0
times higher) contribute to pushing the output prices in the manufacturing sector higher than the United States by
2.8% and 1.1%, respectively.
Keywords: Purchasing power parity, Competitiveness, Trade margins, International input-output table
JEL classification: E31, L81, R15
RIETI Discussion Papers Series aims at widely disseminating research results in the form of professional papers, thereby
stimulating lively discussion. The views expressed in the papers are solely those of the author(s), and neither represent those of theorganization to which the author(s) belong(s) nor the Research Institute of Economy, Trade and Industry.

∗ This study is conducted within the project on “Evaluating International Competitiveness” managed by Koji Nomura at the
Research Institute of Economy, Trade and Industry (RIETI). The views expressed in this paper are solely those of the authors andnot necessarily those of RIETI. On the measurement of trade margin rates in this study, the micro data pertaining to the 2002 and2007 Census of Commerce (Syogyo Tokei Chosa) conducted by the Ministry of Economy, Trade and Industry are permitted to be
used by METI. The use of the unpublished data collected within the International Comparisons Program is permitted by
STD/OECD and Development Economics/The World Bank. The authors are indebted to Kazumi Wakai, Sonoe Arai, Takamichi
Tanigawa, Makoto Kasahara, Masatoshi Yokohashi, and Maki Tokoyama for their helpful data support on METI’s PPP survey and
the Japan-U.S. Input-Output Tables, to Eunice Y. M. Lau for her valuable suggestions, and to Hiroshi Shirane for his research
assistance. The authors appreciate that various supports from RIETI and are also grateful for helpful comments and suggestions byProfessor Chihiro Shimizu (Reitaku University), Professor Kyoji Fukao (Hitotsubashi University, RIETI-PD), President and CRO
Masahisa Fujita (RIETI), Vice President Masayuki Morikawa (RIETI), and seminar participants at RIETI. Any errors that remain
are our sole responsibility.

1

Introduction
In international level comparisons, comparing the industry performance is a much hardertask than comparing the economic performance at the aggregate level. It is not only because theindustry-level comparisons are much more data-demanding, but also because the available dataon price differentials are measured mainly on final demands. These data enable us to compile
cross-country constant-price output volume indicators but only at the aggregate level, by
estimating the price level index for GDP from the expenditure side. In contrast, the feasibility ofcomparing industry performance is particularly hindered by the lack of adequate data on the pricedifferentials on domestic (gross) outputs and intermediate inputs across countries. This data gap
has, for example, greatly limited productivity comparisons at industry level and in turn, offeredlittle insight into the cross-country supply-side efficiency and possible policy implications.
The purpose of this paper is to partially fill this data gap by providing new benchmark
estimates of industry-level price differentials between Japan and the U.S., based on the Isard-type
input-output framework (Isard, 1951). The system of purchasing power parities (PPPs) weconstruct in this paper covers not only products for final uses, but also products of industry
outputs and for intermediate uses, based on the classifications of 173 products for outputs and
174 products for intermediate uses.
We construct a framework of the production system using the 2005 Japan-US Input-Output
Table published in 2013 by METI (Ministry of Economy, Trade and Industry). Under thisbilateral framework, we postulate a price model describing the relationships among producer’s
prices and purchaser’s prices for domestically-produced and imported products, considering thedifferences in the trade structure, freight and insurance rates, duty tax rates, wholesale and retailtrade margins, and transportation costs in each product between Japan and the U.S. 1 Using thedemand-side data of purchaser’s price PPPs for final uses (e.g. the Eurostat-OECD PPPs) and forintermediate uses (e.g. the METI’s Survey on Foreign and Domestic Price Differentials for
Industrial Intermediate Input 2), the producer’s price PPPs for outputs are estimated based on our
price model and the related parameters.
This paper is an update of Nomura and Miyagawa (1999), which developed the 1990
Japan-US benchmark estimates of industry-level price differentials. As globalization has
deepened since then, it has become more important to consider the differences in the importprices of the traded goods to Japan and the U.S. from other economies. We therefore expand the1
The hybrid approach to determining the product PPPs between Japan and the U.S. was developed in Jorgenson, Kuroda, andNishimizu (1987). Since the 1990s at Keio University, Tokyo, Masahiro Kuroda, Kazushige Shimpo, Koji Nomura, and Kozo
Miyagawa have improved the framework and data. In the measurement of PPPs, there is a huge advantage in the bilateralcomparisons between Japan and the U.S. due to the availability of the well-harmonized detailed bilateral input-output table(with some supplementary tables on international freight and insurance and tariffs). The first bilateral table between Japan andthe U.S. for the year 1970 was developed in Japan at the IDE (Institute of Developing Economies) as a joint project with Keio
Economic Observatory, Keio University in 1978. Then METI has been compiling the Japan-US tables since 1985 every five
years. Another significant advantage is the availability of much richer data on price differentials among major industrializedcountries, which have been investigated by the agencies and ministries of the Government of Japan since the late 1980s, as a
response to an important policy focus on international price differentials after the Plaza Accord of 1985 resulted in the rapid
appreciation of the Japanese yen.
2
METI expanded the coverage of the survey and renamed it as Survey on Foreign and Domestic Price Differentials for
Industrial Goods and Services in 2011.

2

framework of our bilateral input-output table (IOT) and develop a sub model to cover the imports
by product from six exogenous economies, i.e., China, Germany, Korea, Malaysia, Taiwan, andThailand, to Japan and the U.S., respectively. The second improvement is our revisions on PPPs
for the wholesale and retail trades. The estimates of PPPs for trades, which are mainly
determined by the Japan-US gaps in trade margin rates by product, has a considerable impact on
the aggregated measures of PPP. In this paper, we reexamine the Japan’s margin rates, based on
establishment data of Census of Commerce in 2002 and 2007 by METI. We provide the new
estimates of the margin rates for wholesales (for household, industries, and exports) and retail(for household) by products (for domestic outputs and imports). Our estimates suggest that themargin rates of retails in the official benchmark IOT in Japan may be considerably
underestimated. 3
Third, we revise the original Japan-US IOT by METI to obtain better harmonized estimatesof the bilateral comparisons. In this revision work on the bilateral IOT, the most important task is
to revise the treatment of Japan’s consumption tax as separately from other indirect taxes. In thecurrent Japanese System of National Accounts (JSNA) and Japan’s Benchmark IOTs since theintroduction of the consumption tax in 1989, the values for intermediate uses are recorded as theprices including not only the non-deductible consumption taxes, but also the deductible ones.
And the consumption taxes (deductible and non-deductible) are not separately estimated fromother indirect taxes by industries. Since the METI 2005 Japan-US IOT follows this treatment, it
makes it hard to compare Japan’s prices with those in the U.S. In this paper, we newly estimate
the deductible consumption taxes in each transaction and revised the Japan-US IOT by
subtracting them. 4
Fourth, compared to our previous work, we increase the volume of price data used frommany sources of data on price differentials by various agencies and ministries of the Governmentof Japan and business sectors. The total number of price-differential data we use in this paper is507. For each product we have 3 prices on different concepts (i.e. for industry or household use,
at producer’s or purchaser’s prices, and including imports or not) on average and try to reconcile
these prices based on the price model we develop. In addition, for the case that the appropriate
data are not available or their accuracy cannot be checked, we developed the cost index approach,in which not only price differentials on the products for intermediate uses (estimated in thispaper), but also the price differentials on labor and capital inputs as estimated in Jorgenson,
Nomura, and Samuels (2015) are taken into consideration by industry (without TFP gap).
The remainder of this paper is organized as follows: Section 2 presents our methodologicalframework. In Section 3 we outline our data sources for our Japan-US bilateral IOT and manydifferent sources of data on price differentials. Section 4 presents the framework and theestimates of trade margins. The estimated results of price level indices on industry outputs are3
The new development of the margin rates has enabled us to improve our price model to take into consideration the differences
in margin rates of imports and domestic outputs. In addition, our price model has been improved to describe the margin rates inthe domestic wholesales of exported goods.
4
These noises were ignored in our previous work for the 1990 estimates in Nomura and Miyagawa (1999). Nomura, Miyagawa,and Okamoto (2014) presents the details of our adjustment processes on the original Japan-US IOT.

3

presented in Section 5. Section 6 concludes.

2

Framework

2.1 Producer’s Prices
We start with a description of our framework of the production systems for Japan and the
U.S. Figure 1 provides the Japan-US input-output table (IOT) we have developed in this paper.
The original table is provided by the 2005 Japan-US input-output table published by METI in
2013. 5 We adjust some problems in this bilateral IOT and expand the framework to cover theimports from six exogenous economies; China (People’s Republic of China), Germany, Korea,
Malaysia, Taiwan (Republic of China), and Thailand. In the Isard-type (non-competitive import
type IOT), all purchases in Japan and the U.S. from foreign countries are recorded separatelyfrom the purchases of domestic products. The areas surrounded by dotted squares in Figure 1
represent the imports to Japan or the U.S.
The prices of domestically-produced products are evaluated at the producer’s prices(including the indirect taxes required for purchasers). The prices of imported products in Japanand the U.S., from the U.S. and Japan, respectively, are evaluated at the FOB (free on board)
prices (producers’ prices plus margin and transportation costs from producers to the custom).
Thus the freight and insurance and tariff required for the Japan-US trade and the net indirect
taxes required in imported countries (in Japan or the U.S.) are separately recorded from the
FOB-price imports. The imports from exogenous economies are evaluated at the prices including
CIF (cost, insurance, and freight), tariff, and the net indirect taxes required in imported countries(in Japan or the U.S.).

5

The 2005 Japan-US IOT estimated by METI is defined as the symmetric-IOT and estimated based on the Japan’s 2005
Benchmark IOT. The estimates of the 2005 Symmetric IOT were extended by INFORUM at University of Maryland based on
the 2002 Benchmark SUT by the U.S. BEA. In this paper, we separate crude oils and natural gas as distinct products. Thus the
products are classified to 174 groups and the industries to 173 groups.

4Japan (J)P roducts in
the U.S. (U)Freight and insurance

Tariff

Net indirect taxes on importsof the Japan-US trade

China

Germany

Korea

Malaysia

indirect taxes
TaiwanThailand

(X)

ROW

(E)

Japan (J)the U.S. (U)Japan (J)the U.S. (U)𝑝𝑝,𝐼𝑋
𝐽,𝑖 𝐽𝐽,𝑖𝑗

𝑝𝑝,𝐼𝑋
𝐽𝑈,𝑖 𝐽𝑈,𝑖𝑗

𝑒𝐽/𝑈𝑝𝑝,H𝑋
𝐽,𝑖 𝐽𝐽,𝑖𝐻,𝐻
𝑝𝑝𝐽𝑈,𝑖
𝑋𝐽𝑈,𝑖𝐻

𝑝𝑝,𝐼
𝑋
𝐽,𝑖 𝐽𝐽,𝑖𝑍

𝑝𝑝,𝐼
𝑋
𝐽𝑈,𝑖 𝐽𝑈,𝑖𝑍

𝑝𝑝𝐽𝐸,𝑖𝑋𝐽𝐸,𝑖𝐸

𝑝𝑝𝐽,𝑖 𝑋𝐽,𝑖

𝑝𝑑,𝐼
𝑈𝐽,𝑖 𝑋𝑈𝐽,𝑖𝑖

𝑝𝑑,𝐼
𝑈,𝑖 𝑋𝑈𝑈,𝑖𝑖

𝑝𝑑,H
𝑈𝐽,𝑖 𝑋𝑈𝐽,𝑖𝐻

𝑝𝑑,𝐻
𝑈,𝑖 𝑋𝑈𝑈,𝑖𝐻

𝑝𝑑,𝐼
𝑈𝐽,𝑖 𝑋𝑈𝐽,𝑖𝑍

𝑝𝑑,𝐼
𝑈,𝑖 𝑋𝑈𝑈,𝑖𝑍

𝑝𝑑𝑈𝑘,𝑖 𝑋𝑈𝑘,𝑖𝑘

𝑝𝑑𝑈,𝑖 𝑋𝑈,𝑖𝑒𝐽/𝑈

𝑇𝑋𝐼𝑈𝐽,𝑖𝑖
𝑝𝑚,𝐼
𝑋
𝐶𝐽,𝑖 𝐶𝐽,𝑖𝑗
𝑝𝑚,𝐼
𝑋
𝐺𝐽,𝑖 𝐺𝐽,𝑖𝑗
𝑝𝑚,𝐼𝑋
𝐾𝐽,𝑖 𝐾𝐽,𝑖𝑗
𝑝𝑚,𝐼𝑋
𝑀𝐽,𝑖 𝑀𝐽,𝑖𝑗
𝑝𝑚,𝐼
𝑋
𝑊𝐽,𝑖 𝑊𝐽,𝑖𝑗
𝑝𝑚,𝐼𝑋
𝑇𝐽,𝑖 𝑇𝐽,𝑖𝑗
𝑒𝐽/𝑈

(T)

Gross output

countris

the U.S. (U)

𝑒𝐽/𝑈

(W)

Value added(Z)
Japan (J)

𝑒𝐽/𝑈

(M)

(R)

output𝑒𝐽/𝑈(K)

exogenous

(E)

Gross

exogenous

𝑒𝐽/𝑈

(G)

tariff, and net

Exports to& Gross capital formation

𝑒𝐽/𝑈

(C)

at the price of cif,

Government consumption(H),𝐼𝜏𝑟𝑈𝐽 𝑝𝑓𝑓𝑓
𝑈𝐽,𝑖 𝑋𝑈𝐽,𝑖𝑖

for the Japan-US trade

countries

Household consumption(N),𝐼
𝜏𝑓𝑈𝐽 𝑝𝑓𝑓𝑓
𝑈𝐽,𝑖 𝑋𝑈𝐽,𝑖𝑖

for the Japan-US trade

Import fromIntermediate uses

𝑝𝑚,𝐼
𝑋
𝑅𝐽,𝑖 𝑅𝐽,𝑖𝑗𝑒𝐽/𝑈

𝑉𝐴 𝐽,𝑗
𝑒𝐽/𝑈

𝑝𝑝𝐽,𝑗 𝑋𝐽,𝑗
𝑒𝐽/𝑈

𝑒𝐽/𝑈

𝜏𝑓𝐽𝑈𝑝𝑓𝑜𝑏,𝐼
𝑋𝐽𝑈,𝑖𝑗𝐽𝑈,𝑖𝑒𝐽/𝑈𝜏𝑜𝐽𝑈𝑝𝑓𝑜𝑏,𝐼
𝑋𝐽𝑈,𝑖𝑗
𝐽𝑈,𝑖
𝑒𝐽/𝑈

𝑒𝐽/𝑈

,𝐻
𝜏𝑓𝑈𝐽 𝑝𝑓𝑓𝑓
𝑈𝐽,𝑖 𝑋𝑈𝐽,𝑖𝐻,𝐻𝜏𝑟𝑈𝐽 𝑝𝑓𝑓𝑓
𝑈𝐽,𝑖 𝑋𝑈𝐽,𝑖𝐻

𝑇𝑋𝐼𝐽𝑈,𝑖𝑖

𝑝𝑚,𝐼𝐶𝑈,𝑖 𝑋𝐶𝑈,𝑖𝑖
𝑝𝑚,𝐼
𝐺𝑈,𝑖 𝑋𝐺𝑈,𝑖𝑖
𝑝𝑚,𝐼
𝐾𝑈,𝑖 𝑋𝐾𝑈,𝑖𝑖
𝑝𝑚,𝐼
𝑀𝑈,𝑖 𝑋𝑀𝑈,𝑖𝑖
𝑝𝑚,𝐼
𝑊𝑈,𝑖 𝑋𝑊𝑈,𝑖𝑖
𝑝𝑚,𝐼
𝑇𝑈 ,𝑖 𝑋𝑇𝑈,𝑖𝑖
𝑝𝑚,𝐼
𝑅𝑈,𝑖 𝑋𝑅𝑈,𝑖𝑖

𝑇𝑋𝐻
𝑈𝐽,𝑖𝐻
𝑝𝑚,𝐻
𝑋
𝐶𝐽,𝑖 𝐶𝐽,𝑖𝐻
𝑒𝐽/𝑈

𝑝𝑚,𝐻
𝑋
𝐺𝐽,𝑖 𝐺𝐽,𝑖𝐻
𝑒𝐽/𝑈

𝑝𝑚,𝐻
𝑋
𝐾𝐽,𝑖 𝐾𝐽,𝑖𝐻
𝑒𝐽/𝑈

𝑝𝑚,𝐻
𝑋
𝑀𝐽,𝑖 𝑀𝐽,𝑖𝐻
𝑒𝐽/𝑈

𝑝𝑚,𝐻
𝑋
𝑊𝐽,𝑖 𝑊𝐽,𝑖𝐻
𝑒𝐽/𝑈

𝑝𝑚,𝐻
𝑋
𝑇𝐽,𝑖 𝑇𝐽,𝑖𝐻
𝑒𝐽/𝑈

𝑝𝑚,𝐻
𝑋
𝑅𝐽,𝑖 𝑅𝐽,𝑖𝐻
𝑒𝐽/𝑈

𝑒𝐽/𝑈

𝜏𝑓𝐽𝑈𝑝𝑓𝑜𝑏,𝐻
𝑋𝐽𝑈,𝑖𝐻𝐽𝑈,𝑖𝑒𝐽/𝑈𝜏𝑜𝐽𝑈𝑝𝑓𝑜𝑏,𝐻
𝑋𝐽𝑈,𝑖𝐻
𝐽𝑈,𝑖
𝑒𝐽 /𝑈

𝑇𝑋𝐻
𝐽𝑈,𝑖𝐻

𝑝𝑚,𝐻
𝐶𝑈,𝑖 𝑋𝐶𝑈,𝑖𝐻
𝑝𝑚,𝐻
𝐺𝑈,𝑖 𝑋𝐺𝑈,𝑖𝐻
𝑝𝑚,𝐻
𝐾𝑈,𝑖 𝑋𝐾𝑈,𝑖𝐻
𝑝𝑚,𝐻
𝑀𝑈,𝑖 𝑋𝑀𝑈,𝑖𝐻
𝑝𝑚,𝐻
𝑊𝑈,𝑖 𝑋𝑊𝑈,𝑖𝐻
𝑝𝑚,𝐻
𝑇𝑈,𝑖 𝑋𝑇𝑈,𝑖𝐻
𝑝𝑚,𝐻
𝑅𝑈,𝑖 𝑋𝑅𝑈,𝑖𝐻

𝑒𝐽/𝑈

,𝐼
𝜏𝑓𝑈𝐽 𝑝𝑓𝑓𝑓
𝑈𝐽,𝑖 𝑋𝑈𝐽,𝑖𝐺,𝐼
𝜏𝑟𝑈𝐽 𝑝𝑓𝑓𝑓
𝑈𝐽,𝑖 𝑋𝑈𝐽,𝑖𝑍

𝑇𝑋𝐼𝑈𝐽,𝑖𝑍
𝑝𝑚,𝐼
𝑋
𝐶𝐽,𝑖 𝐶𝐽,𝑖𝑍
𝑒𝐽/𝑈

𝑝𝑚,𝐼
𝑋
𝐺𝐽,𝑖 𝐺𝐽,𝑖𝑍
𝑒𝐽/𝑈

𝑝𝑚,𝐼
𝑋
𝐾𝐽,𝑖 𝐾𝐽,𝑖𝑍
𝑒𝐽/𝑈

𝑝𝑚,𝐼
𝑋
𝑀𝐽,𝑖 𝑀𝐽,𝑖𝑍
𝑒𝐽/𝑈

𝑝𝑚,𝐼
𝑋
𝑊𝐽,𝑖 𝑊𝐽,𝑖𝑍
𝑒𝐽/𝑈

𝑝𝑚,𝐼
𝑋
𝑇𝐽,𝑖 𝑇𝐽,𝑖𝑍
𝑒𝐽/𝑈

𝑝𝑚,𝐼
𝑋
𝑅𝐽,𝑖 𝑅𝐽,𝑖𝑍
𝑒𝐽/𝑈

𝑒𝐽/𝑈

𝑒𝐽/𝑈

𝑒𝐽/𝑈

𝜏𝑓𝐽𝑈𝑝𝑓𝑜𝑏,𝐼
𝑋𝐽𝑈,𝑖𝑍𝐽𝑈,𝑖𝑒𝐽/𝑈𝜏𝑜𝐽𝑈𝑝𝑓𝑜𝑏,𝐼
𝑋𝐽𝑈,𝑖𝑍𝐽𝑈,𝑖𝑒𝐽/𝑈

𝑇𝑋𝐼𝐽𝑈,𝑖𝑍

𝑝𝑚,𝐼
𝐶𝑈 ,𝑖 𝑋𝐶𝑈,𝑖𝑍
𝑝𝑚,𝐼
𝐺𝑈,𝑖 𝑋𝐺𝑈,𝑖𝑍
𝑝𝑚,𝐼
𝐾𝑈,𝑖 𝑋𝐾𝑈,𝑖𝑍
𝑝𝑚,𝐼
𝑀𝑈,𝑖 𝑋𝑀𝑈,𝑖𝑍
𝑝𝑚,𝐼
𝑊𝑈,𝑖 𝑋𝑊𝑈,𝑖𝑍
𝑝𝑚,𝐼
𝑇𝑈 ,𝑖 𝑋𝑇𝑈,𝑖𝑍
𝑝𝑚,𝐼
𝑅𝑈,𝑖 𝑋𝑅𝑈,𝑖𝑍

𝑉𝐴 𝑈,𝑖

𝑝𝑑𝑈,𝑖 𝑋𝑈,𝑖Figure 1: Japan-US Input-Output Table (the Isard-Type)To describe equations, we define six groups of demands, denoting:Nfor intermediate uses,Hfor household consumption (including consumption by NPISHs),G

for government consumption,F

for investment (GFCF and changes in inventories) by industries and government,Efor exports to exogenous economies, andM

for imports,

and the following three broad groups of the demands,Z

for domestic final demand excluding household consumption (Z={G, F}),5

I

for domestic demand by industries and government (I={N, G, F}) 6, andD

for domestic demand (D={I,H}={N, H, G, F}).
To construct the price model describing the production system in Figure 1, we define somenotations of variables as follows,
𝑑
𝑝𝑘,𝑖

𝑑
𝑝𝑘𝑘,𝑖

Price of product i produced in country k at producer’s prices in currency of country k,
Price of product i produced in country k, purchased by exogenous economies at
producer’s prices (excluding net indirect taxes on products and consumption tax) incurrency of country k,

𝑑,𝑙
𝑝𝑘,𝑖

Price of product i produced in country k, purchased by industries (I) or household (H) in
country k at producers’ prices in currency of country k, (If l = I, the product ispurchased by industries for intermediate uses or investment, and the price includes net
indirect taxes on products. If l = H, the product is purchased by household for final
consumption, and the price includes net indirect taxes on products and consumptiontax.),

𝑑,𝑙𝑝𝑘𝑘′,𝑖Price of product i produced in country k, purchased by industries (I) or household (H) in
country k’ at producers’ prices in currency of country k, (If l = I, the product ispurchased by industries. If l = H, the product is purchased by household. The bothprices exclude net indirect taxes on products.),𝑚,𝑙𝑝𝑘𝑘′,𝑖Price of product i imported from country k, purchased by industries (I) or household(H) in k’-country at the CIF prices plus tariff and net indirect taxes on imports incurrency of country k’, (If l = I, the product is purchased by industries, and the priceexcludes consumption tax. If l = H, the product is purchased by household, and theprice includes consumption tax.),𝑓𝑓𝑓,𝑙𝑝𝑘𝑘′,𝑖Price of product i imported from country k, purchased by industries (I) or household(H) in country k’ at the FOB prices in currency of country k, (If l = I, the product ispurchased by industries. If l = H, the product is purchased by household.)

𝑐,𝑙
𝑝𝑘,𝑖

Price of i-th composite product (domestic products plus imports), purchased byindustries (I) or household (H) in country k at producers’ prices in currency of country k,(If l = I, the product is purchased by industries, and the price includes net indirect taxes
on products. If l = H, the product is purchased by household, and the price includes net
indirect taxes on products and consumption tax.),

𝑋𝑘𝑘′,𝑖𝑖𝑋𝑘,𝑖𝑓𝜏𝑘𝑘′,𝑖𝑟𝜏𝑘𝑘′,𝑖𝑙𝜏𝑘,𝑖Volume of product i produced in country k and purchased by sector j in country k’,
Volume of product i produced in country k,Rate of freight and insurance of product i imported from country k, purchased incountry k’,
Rate of tariff of product i imported from country k, purchased in country k’,
Rate of net indirect taxes on products of product i in country k for industries (I) or

6

Since the government consumption is defined at the actual base, the products for I={N, G, F} mainly refer the products
consumed for industries’ intermediate uses (N) and investment by industries and government (F). For simplicity, we use I to
denote demand for industry uses.

6household (H), (If l = I, the rate is for industries and excludes consumption tax. 7 If l =H, the rate is for households and includes consumption tax.),
𝑑
𝜏𝑘,𝑖
𝑑
𝑇𝑇𝑘,𝑖

The effective rate of indirect taxes for product i in country k,
The amount of indirect taxes of i th domestic products in country k𝑒𝑘/𝑘′Exchange rate of currency of country k against the currency of country k’, (e.g. Japan’s
exchange rate to the U.S. dollar is 𝑒𝐽/𝑈 )

𝑒,𝑙
𝑇𝑘,𝑖

Transportation service input for one unit of exported product i in country k, (If l = I, theservice is input for industries. If l = H, the service is input for households.),

𝑒,𝑙
𝑊𝑘,𝑖

Trade service input for one unit of exported i-product in country k, (If l = I, the service
is input for industries. If l = H, the service is input for households.),

𝑇,𝑒,𝑙
𝑚𝑘,𝑖

𝑊,𝑒,𝑙
𝑚𝑘,𝑖

Rate of transportation cost (T) of product i in country k for exported products, (If l = I,
the rate is for industries. If l = H, the rate is for households.),
Rate of trade margin (W) of product i in country k for exported products, (If l = I, therate is for industries. If l = H, the rate is for households.).

We begin with clarifying the treatment of indirect taxes in our model. In Japan’stransactions of Figure 1, the consumption tax is included only in the prices of household𝑑,𝐼consumptions. Thus the producer’s prices of the domestically produced outputs, 𝑝𝐽,𝑖(for
𝑑,𝐻(for household) are distinguished in our model. 8 Corresponding to thisindustry) and 𝑝𝐽,𝑖

identification, the rates of net indirect taxes on products for industries and households are also𝐼
𝐻and 𝜏𝐽,𝑖, respectively. As for the prices of exports, since both of
distinguished as 𝜏𝐽,𝑖

consumption tax and other indirect taxes on products are deductible, Japan’s export prices to the𝑑,𝐻𝑑,𝐼U.S. (𝑝𝐽𝐽,𝑖and 𝑝𝐽𝐽,𝑖) are assumed as:

𝑑,𝑙
𝑑,𝑙
𝑙
𝑝𝐽𝐽,𝑖
= 𝑝𝐽,𝑖�(1 + 𝜏𝐽,𝑖)(𝑘 = 𝐽, 𝑈 and 𝑙 = 𝐼, 𝐻).
(1)𝑑On the other hand, the Japanese producer’s price 𝑝𝐽,𝑖is defined as a composition of the

producer’s prices for all types of demand. The total of the domestic indirect taxes (excluding
indirect tax for imported products) of product i is described as:
(2)

𝑑
𝑇𝑇𝐽,𝑖
=�

𝐼
𝜏𝐽,𝑖

𝑑,𝐼
𝐼 � 𝑝𝐽,𝑖 ∑𝑗∈𝐼 𝑋𝐽𝐽,𝑖𝑖 + �

1+𝜏𝐽,𝑖𝐻
𝜏𝐽,𝑖𝐻
1+𝜏𝐽,𝑖𝑑,𝐻� 𝑝𝐽,𝑖
𝑋𝐽𝐽,𝑖𝑖 .

The first term on the right-hand side represents the amount of other indirect tax paid by industries(I) and the second term is the amount of the consumption tax and other indirect tax paid by𝑑households (H). Based on 𝑇𝑇𝐽,𝑖, the effective rate of indirect taxes for domestic product i inJapan is defined as:
(3)

𝑑
𝑑
𝑑
𝑑
𝜏𝐽,𝑖
= 𝑇𝑇𝐽,𝑖�(𝑝𝐽,𝑖
𝑋𝐽,𝑖 − 𝑇𝑇𝐽,𝑖),

7

The consumption tax on the products purchased by the producers who produce consumption tax exempt products (e.g.
𝐼in the description of our pricemedical care) are non-deductible. We describe that the consumption tax is excluded from 𝜏𝑘,𝑖model for simplicity, but some non-deductible consumption taxes in domestic final demand excluding household consumption(Z) are considered in our actual estimation.
8
In addition to the differences in indirect taxes for industry and household uses, our price model permits the differences in thebasic prices for industry and household uses, reflecting the observed price differentials in different demand types of the productwhich are classified to the same group. These may indicate that the types or qualities of the same product at the more detaillevel are different, but we treat them as if they were additive for simplicity of our price model.

7𝑑𝑑where 𝑝𝐽,𝑖
𝑋𝐽,𝑖 is gross output in Japan. Using 𝜏𝐽,𝑖
, Japan’s export price to the exogenous

economies is assumed as:

𝑑
𝑑
𝑑
𝑝𝐽𝐽,𝑖
= 𝑝𝐽,𝑖�(1 + 𝜏𝐽,𝑖).

(4)

In the case of exports to exogenous economies, the difference in the uses in the imported
countries (for industry or household) are not identified in our model, due to data constraints.
Equations (1) to (4) are held for the U.S. similarly.
The output balance of the Japanese products at current prices based on the first-row matrixof the non-competitive import type IOT in Figure 1 is described as,
𝑑,𝐼
𝑑,𝐼
𝑑,𝐻
𝑑,𝐻
𝑑
𝑑
∑𝑗∈𝐼 𝑋𝐽𝐽,𝑖𝑖 + 𝑝𝐽𝐽,𝑖∑𝑗∈𝐼 𝑋𝐽𝐽,𝑖𝑖 + 𝑝𝐽,𝑖
𝑝𝐽,𝑖
𝑋𝐽,𝑖 = 𝑝𝐽,𝑖
𝑋𝐽𝐽,𝑖𝑖 + 𝑝𝐽𝐽,𝑖
𝑋𝐽𝐽,𝑖𝑖 + 𝑝𝐽𝐽,𝑖
𝑋𝐽𝐽,𝑖

(5)

The first term on the right-hand side stands for industry uses (intermediate uses and investment)
in Japan, the second term is the imports by the U.S. industries for the intermediate uses, the third
term is the household uses in Japan, the fourth term is the imports by the U.S. households, andthe final term is the exports to exogenous economies.
Corresponding to the Isard-type IOT in Figure 1, we define the Chenery-Moses-type IOT(the competitive import type IOT) for each of Japan and the U.S. (Chenery, 1953; Moses, 1955)
Figure 2 represents this table for Japan (a similar table can be defined for the U.S.).

Intermediate inputs(N)

Householdconsumption(C)

Government
consumption& Gross capitalformation(Z)

𝑝𝐽𝑐,𝑖,𝐼𝑋𝐽,𝑖𝑖

𝑐,𝐻
𝑝𝐽,𝑖
𝑋𝐽,𝑖𝐻

𝑐,𝐼
𝑝𝐽,𝑖
𝑋𝐽𝐽,𝑖𝑍Intermediate
inputsExports (E)𝑑,𝐼𝑑,𝐻� 𝑝𝐽𝑈,𝑖
𝑋𝐽𝑈,𝑖𝑖 + 𝑝𝐽𝑈,𝑖
𝑋𝐽𝑈,𝑖𝐻𝑖∈𝐼

𝑝+ 𝑝𝐽𝐸,𝑖
𝑋𝐽𝐸,𝑖𝐸(–)Imports (M)Gross output (X)𝑚,𝐻� (�𝑝𝑚,𝐼
𝑘𝐽,𝑖𝑋𝑘𝐽,𝑖𝑖 + 𝑝𝑘𝐽,𝑖 𝑋𝑘𝐽,𝑖𝐻)

𝑑
𝑝𝐽,𝑖
𝑋𝐽,𝑖

𝑘=𝑈,𝑘 𝑖∈𝐼

𝑉𝐴𝐽,𝑖Value added

𝑑 𝑋
𝑝𝐽,𝑖
𝐽,𝑖

Gross output

Figure 2: Japanese Input-Output Table (the Chenery-Moses-Type)
Based on the Chenery-Moses-type input-output framework in Figure 2, the output balance
including Japan’s uses of imports at current prices is described as:
(6)

𝑐,𝐼
𝑐,𝐻
𝑑,𝐼
𝑑,𝐻
𝑑
𝑑
𝑝𝐽,𝑖
𝑋𝐽,𝑖 = ∑𝑗∈𝐼 𝑝𝐽,𝑖
𝑋𝐽,𝑖𝑖 + 𝑝𝐽,𝑖
𝑋𝐽,𝑖𝑖 + �∑𝑗∈𝐼 𝑝𝐽𝐽,𝑖
𝑋𝐽𝐽,𝑖𝑖 + 𝑝𝐽𝐽,𝑖
𝑋𝐽𝐽,𝑖𝑖 + 𝑝𝐽𝐽,𝑖
𝑋𝐽𝐽,𝑖 �𝑚,𝐼𝑚,𝐻
− ∑𝑘=𝑈,𝐸 �∑𝑗∈𝐼 𝑝𝑘𝑘,𝑖
𝑋𝑘𝑘,𝑖𝑖 + 𝑝𝑘𝑘,𝑖
𝑋𝑘𝑘,𝑖𝑖 �,

where 𝑋𝐽,𝑖𝑖 is the domestic demands of product i by sector j in Japan including both domestic𝑐,𝐼stands for the corresponding prices of the composite products
products and imports, and 𝑝𝐽,𝑖(of domestic- produced products plus imports). These demand prices are defined as:
(7)

𝑐,𝑙
𝑑,𝑙
𝑚,𝑙
𝑚,𝑙
𝑝𝐽,𝑖
𝑋𝐽,𝑖𝑖 = 𝑝𝐽,𝑖
𝑋𝐽𝐽,𝑖𝑖 + 𝑝𝑈𝑈,𝑖
𝑋𝑈𝑈,𝑖𝑖 + 𝑝𝐸𝐸,𝑖
𝑋𝐸𝐸,𝑖𝑖( 𝑙 = 𝐼, 𝐻) .

The outputs at constant prices are assumed to be additive among the product for different
demands;(8)

𝑋𝐽,𝑖 = ∑𝑗∈𝐷 𝑋𝐽𝐽,𝑖𝑖 + ∑𝑗∈𝐷 𝑋𝐽𝐽,𝑖𝑖 + 𝑋𝐽𝐽,𝑖= ∑𝑗∈𝐷 𝑋𝐽,𝑖𝑖 + ∑𝑗∈𝐷 𝑋𝐽𝐽,𝑖𝑖 + 𝑋𝐽𝐽,𝑖 − ∑𝑗∈𝐷 𝑋𝑈𝑈,𝑖𝑖 − ∑𝑗∈𝐷 𝑋𝐸𝐸,𝑖𝑖 .
8The former equation corresponds with the nominal balance of Equation (5) and the lattercorresponds to Equation (6). For simplicity, we also assume the additivity among domestic inputs
and imports:
𝑋𝐽,𝑖𝑖 = 𝑋𝐽𝐽,𝑖𝑖 + 𝑋𝑈𝑈,𝑖𝑖 + 𝑋𝐸𝐸,𝑖𝑖(9)(𝑗 ∈ 𝐷).

We define the demand share at constant prices:
(10)

𝑑,𝑙
𝑤𝐽𝐽,𝑖
= ∑𝑗∈𝑙 𝑋𝐽𝐽,𝑖𝑖 ⁄𝑋𝐽,𝑖𝑑(𝑘 = 𝐽, 𝑈, 𝑙 = 𝐼, 𝐻) and 𝑤𝐽𝐽,𝑖= 𝑋𝐽𝐽,𝑖 ⁄𝑋𝐽,𝑖 ,

𝑑,𝐼
𝑑,𝐼
𝑑,𝐻
𝑑,𝐻
𝑑
+ 𝑤𝐽𝐽,𝑖+ 𝑤𝐽𝐽,𝑖+ 𝑤𝐽𝐽,𝑖+ 𝑤𝐽𝐽,𝑖= 1. Based on Equations (5) to (10), Japan’s output
where 𝑤𝐽𝐽,𝑖price of product i is described as:(11)𝑑,𝐼 𝑑,𝐼𝑑,𝐼𝑑,𝐼𝑑,𝐻 𝑑,𝐻𝑑,𝐻 𝑑,𝐻𝑑𝑑𝑑𝑝𝐽,𝑖= 𝑝𝐽,𝑖
𝑤𝐽𝐽,𝑖 + 𝑝𝐽𝐽,𝑖𝑤𝐽𝐽,𝑖+ 𝑝𝐽,𝑖
𝑤𝐽𝐽,𝑖 + 𝑝𝐽𝐽,𝑖
𝑤𝐽𝐽,𝑖 + 𝑝𝐽𝐽,𝑖𝑤𝐽𝐽,𝑖.

By substituting Equations (1) and (4) into Equation (11), we obtain:
(12)

𝑑,𝐼
𝑑,𝐼
𝑑
𝑝𝐽,𝑖
= �𝑝𝐽,𝑖�𝑤𝐽𝐽,𝑖
+

𝑑,𝐼

𝑤𝐽𝐽,𝑖

𝑙
1+𝜏𝐽,𝑖𝑑,𝐻𝑑,𝐻� + 𝑝𝐽,𝑖�𝑤𝐽𝐽,𝑖
+

𝑑,𝐻

𝑤𝐽𝐽,𝑖

𝑙
1+𝜏𝐽,𝑖����1 −𝑑𝑤𝐽𝐽,𝑖𝑑1+𝜏𝐽,𝑖

�.

𝑑,𝐼
𝑑,𝐻
𝑑
Thus Japan’s output price, 𝑝𝐽,𝑖
, is measured using 𝑝𝐽,𝑖and 𝑝𝐽,𝑖, the demand shares, and therates of indirect taxes.

𝑑,𝑙On the other hand, in order to clarify the relationship between U.S. producer’s price 𝑝𝑈𝑈,𝑖𝑚,𝑙, we describe the U.S. FOB price as:
and Japan’s import prices from the U.S., 𝑝𝑈𝑈,𝑖

(13)

where

𝑓𝑓𝑓,𝑙

𝑑,𝑙
𝑑,𝑙
𝑑,𝑙
𝑒
𝑒
𝑝𝑈𝑈,𝑖 = 𝑝𝑈𝑈,𝑖+ 𝑝𝑈𝑈,𝑇
𝑇𝑈,𝑖+ 𝑝𝑈𝑈,𝑊
𝑊𝑈,𝑖

𝑑,𝑙
𝑝𝑈𝑈,𝑇

and

𝑑,𝑙
𝑝𝑈𝑈,𝑊

(𝑙 = 𝐼, 𝐻),

are the prices of U.S. transportation and trade sectors for the exports to𝑒,𝑙𝑒,𝑙and 𝑊𝑈,𝑖are the volumes of transportation and trade services forJapan, respectively, and 𝑇𝑈,𝑖

one unit of exports of product i required in the U.S. We define the rate of transportation cost
𝑇,𝐸,𝑙
𝑊,𝑒,𝑙
𝑚𝑈,𝑖
and the rate of trade margin 𝑚𝑈,𝑖for exported products as,

(14)

𝑓𝑓𝑓,𝑙

𝑇,𝑒,𝑙
𝑑,𝑙
𝑒
𝑚𝑈,𝑖
= 𝑝𝑈𝑈,𝑇
𝑇𝑈,𝑖
�𝑝𝑈𝑈,𝑖

𝑓𝑓𝑓,𝑙

𝑊,𝑒,𝑙
𝑑,𝑙
𝑒
and 𝑚𝑈,𝑖= 𝑝𝑈𝑈,𝑊
𝑊𝑈,𝑖
�𝑝𝑈𝑈,𝑖(𝑙 = 𝐼, 𝐻),

respectively. From Equation (13) and (14), the FOB prices for households and industries are
represented as:
(15)

𝑓𝑓𝑓,𝑙

𝑑,𝑙
𝑇,𝑒,𝑙
𝑊,𝑒,𝑙
𝑝𝑈𝑈,𝑖 = 𝑝𝑈𝑈,𝑖�(1 − 𝑚𝑈,𝑖
− 𝑚𝑈,𝑖)(𝑙 = 𝐼, 𝐻).

𝑚,𝐼𝑚,𝐻The prices of imports for industry and household uses, 𝑝𝑈𝑈,𝑖and 𝑝𝑈𝑈,𝑖, are calculated by adding

the custom duty and indirect taxes on products to the CIF price as:
(16)

𝑓

𝑓𝑓𝑓,𝑙

𝑚,𝑙
𝑑,𝑙
𝑙
𝑟
𝑙
𝑝𝑈𝑈,𝑖
= 𝑒𝐽/𝑈 �1 + 𝜏𝐽,𝑖��1 + 𝜏𝑈𝑈,𝑖��1 + 𝜏𝑈𝑈,𝑖 �𝑝𝑈𝑈,𝑖 = 𝑒𝐽/𝑈 𝜔𝑈𝑈,𝑖𝑝𝑈𝑈,𝑖(𝑙 = 𝐼, 𝐻),𝑓𝑟where 𝑒𝐽/𝑈 is the exchange rate of the Japanese yen against the U.S. dollar, 𝜏𝑈𝑈,𝑖and 𝜏𝑈𝑈,𝑖are

the rates of the international freight and insurance and the tariff for one unit of product i imported𝑓𝑟𝑙𝑙
are defined as �1 + 𝜏𝑘′,𝑖��1 + 𝜏𝑘𝑘′,𝑖��1 + 𝜏𝑘𝑘′,𝑖 �/from the U.S. to Japan, respectively, and 𝜔𝑘𝑘′,𝑖
𝑇,𝑒,𝑙
𝑊,𝑒,𝑙
− 𝑚𝑈,𝑖) for 𝑙 = 𝐼, 𝐻 for simplicity.
(1 − 𝑚𝑈,𝑖9

Meanwhile, the demand share of the domestic product and the imported product is defined

as:

(17)
where

𝑐,𝑙
𝑤𝑘𝑘,𝑖
= ∑𝑗∈𝑙 𝑋𝑘𝑘,𝑖𝑖 ⁄∑𝑗∈𝑙 𝑋𝐽,𝑖𝑖

𝑐,𝑙
𝑐,𝑙
𝑐,𝑙
𝑤𝐽𝐽,𝑖
+ 𝑤𝑈𝑈,𝑖+ 𝑤𝐸𝐸,𝑖=1(7), we obtain:(18)
9(𝑘 = 𝐽, 𝑈, 𝐸 and 𝑙 = 𝐼, 𝐻),

for 𝑙 = 𝐼, 𝐻 . By assigning Equations (16) and (17) to Equation𝑐,𝑙𝑑,𝑙 𝑐,𝑙𝑑,𝑙𝑐,𝑙𝑚,𝑙 𝑐,𝑙𝑙𝑝𝐽,𝑖= 𝑝𝐽,𝑖
𝑤𝐽𝐽,𝑖 + 𝑒𝐽/𝑈 𝜔𝑈𝑈,𝑖
𝑝𝑈𝑈,𝑖
𝑤𝑈𝑈,𝑖
+ 𝑝𝐸𝐸,𝑖𝑤𝐸𝐸,𝑖𝑓(𝑙 = 𝐼, 𝐻).

𝑟
The data 𝜏𝑈𝑈,𝑖 and 𝜏𝑈𝑈,𝑖
are available from the 2005 Japan-US IOT by METI or its supplementary tables.

9

Similarly, the demand prices in the U.S. are shown as:
(19)

𝑐,𝑙
𝑑,𝑙 𝑐,𝑙
𝑑,𝑙
𝑐,𝑙
𝑚,𝑙
𝑐,𝑙
𝑙
𝑝𝑈,𝑖
= 𝑝𝑈,𝑖𝑤𝑈𝑈,𝑖 + 𝜔𝐽𝐽,𝑖
𝑝𝐽𝐽,𝑖
𝑤𝐽𝐽,𝑖
�𝑒𝐽/𝑈 + 𝑝𝐸𝑈,𝑖𝑤𝐸𝐸,𝑖(𝑙 = 𝐼, 𝐻).

Equations (18) and (19) describe the price relationship between the producer’s prices of Japanand the U.S. through their bilateral trade.
Based on the definitions of our prices, we define several price level indices (PLI) between
Japan and the U.S. as,(20)𝑑
𝐏𝐽/𝑈,𝑖
=

𝑑
𝑝𝐽,𝑖

𝑑,𝑙
𝑑 , 𝐏𝐽/𝑈,𝑖 =𝑒𝐽/𝑈 𝑝𝑈,𝑖

𝑑,𝑙

𝑝𝐽,𝑖

𝑐,𝑙
𝑑,𝑙 , 𝐏𝐽/𝑈,𝑖 =𝑒𝐽/𝑈 𝑝𝑈,𝑖

𝑐,𝑙

𝑝𝐽,𝑖

(𝑙 = 𝐼, 𝐻),𝑐,𝑙𝑒𝐽/𝑈 𝑝𝑈,𝑖𝑑is the PLI of output at producer’s price of product i between Japan and the U.S. 10
where 𝐏𝐽/𝑈,𝑖The second equation describes the definition of the PLIs of output at producer’s price for𝑑,𝐻𝑑,𝐼households and for industries, 𝐏𝐽/𝑈,𝑖and 𝐏𝐽/𝑈,𝑖, respectively. The third equation describes the𝑐,𝐻𝑐,𝐼
PLIs of demand prices at producer’s price, 𝐏𝐽/𝑈,𝑖and 𝐏𝐽/𝑈,𝑖, respectively. By substituting

Equations (18) and (19), into (20), the Japan-US PLI of domestic demand prices for households
and industries are obtained as follows:
(21)

𝑐,𝑙
𝐏𝐽/𝑈,𝑖
=

𝑑,𝑙

𝑐,𝑙

𝑐,𝑙

𝑚,𝑙

𝑐,𝑙

𝑙
𝑙
𝐏𝐽/𝑈,𝑖 𝑤𝐽𝐽,𝑖 +𝜔𝑈𝑈,𝑖
𝑤𝑈𝑈,𝑖 �(1+𝜏𝑈,𝑖)+𝐏𝐸𝐽/𝑈,𝑖 𝑤𝐸𝐸,𝑖(𝑙 = 𝐼, 𝐻).

𝑐,𝑙
𝑑,𝑙
𝑐,𝑙
𝑐,𝑙
𝑙
𝑙 )+𝐏 𝑚,𝑙𝑤𝑈𝑈,𝑖+𝐏𝐽/𝑈,𝑖𝜔𝐽𝐽,𝑖𝑤𝐽𝐽,𝑖�(1+𝜏𝐽,𝑖
𝐸𝐸/𝑈,𝑖 𝑤𝐸𝐸,𝑖𝑚,𝑙
𝐏𝐸𝐸/𝑈,𝑖is the PLI of the imports from exogenous economies to Japan or the U.S., relative to thedomestic producer’s prices in the U.S., which are defined as:
(22)

𝑚,𝑙
𝐏𝐸𝐸/𝑈,𝑖
=

𝑚,𝑙

𝑝𝐸𝐸,𝑖

𝑚,𝑙

𝑝𝐸𝐸,𝑖

𝑚,𝑙
and 𝐏𝐸𝐸/𝑈,𝑖=𝑑,𝑙𝑒𝐽/𝑈 𝑝𝑈,𝑖(𝑙 = 𝐼, 𝐻).

𝑑,𝑙
𝑝𝑈,𝑖

𝑚,𝑙
𝑚,𝑙
and 𝑝𝐸𝐸/𝑈,𝑖respectively, are determined
The import price indices for Japan and the U.S., 𝑝𝐸𝐸/𝑈,𝑖by the sub model, as presented in Section 2.3. From Equation (21), we obtain:
(23)

𝑑,𝑙
𝐏𝐽/𝑈,𝑖
=

𝑐,𝑙

𝑚,𝑙

𝑐,𝑙

𝑐,𝑙

𝑐,𝑙

𝑚,𝑙

𝑐,𝑙

𝑙
𝑙
𝜔𝑈𝑈,𝑖
𝑤𝑈𝑈,𝑖�(1+𝜏𝑈,𝑖)+𝐏𝐸𝐸/𝑈,𝑖 𝑤𝐸𝐸,𝑖 −𝐏𝐽/𝑈,𝑖 �𝑤𝑈𝑈,𝑖 +𝐏𝐸𝐸/𝑈,𝑖 𝑤𝐸𝐸,𝑖 �
𝑐,𝑙
𝑐,𝑙
𝑙
𝑙 )−𝑤 𝑐,𝑙
𝐏𝐽/𝑈,𝑖𝜔𝐽𝐽,𝑖𝑤𝐽𝐽,𝑖�(1+𝜏𝐽,𝑖𝐽𝐽,𝑖(𝑙 = 𝐼, 𝐻).

If the PLIs of the demand prices and the imports from exogenous economies are available, the
PLI of output at producer’s price are measured by this equation, for industry or household.
𝑑,𝐼𝑑,𝐻When the PLIs of 𝐏𝐽/𝑈,𝑖and 𝐏𝐽/𝑈,𝑖
are measured, we can measure the PLI of domestic𝑑outputs, 𝐏𝐽/𝑈,𝑖, based on Equation (12) as:

(24)

𝑝

𝑑,𝐼

𝑤

𝑑,𝐼

𝑑,𝐼
𝑑
𝐏𝐽/𝑈,𝑖= �𝐏𝐽/𝑈,𝑖
� 𝑈,𝑖𝑑 𝐽𝐽,𝑖 +
𝑝𝑈,𝑖

𝑑,𝐼

𝑑,𝐼

𝑝𝑈,𝑖 𝑤𝐽𝐽,𝑖

𝑝

𝑑,𝐻

𝑤

𝑑,𝐻

𝑈,𝑖 𝐽𝐽,𝑖𝑑,𝐻+𝑑 � + 𝐏𝐽/𝑈,𝑖 �𝑑𝐼 )𝑝(1+𝜏𝐽,𝑖
𝑈,𝑖

𝑝𝑈,𝑖

𝑑,𝐻

𝑑,𝐻

𝑝𝑈,𝑖 𝑤𝐽𝐽,𝑖

𝐻 �𝑝 𝑑�1+𝜏𝐽,𝑖𝑈,𝑖����1 −𝑑𝑤𝐽𝐽,𝑖𝑑1+𝜏𝐽,𝑖�.

𝑑
In this equation, 𝐏𝐽/𝑈,𝑖is defined including the indirect taxes. Since our framework is based on𝑑𝑑the METI’s symmetric IOT, this product-PLI is identical to the industry-PLI (𝐏𝐽/𝑈,𝑖= 𝐏𝐽/𝑈,𝑗). To

enable us to compare the prices and volumes of outputs, the PLI of j-industry outputs at basic𝑑∗as:prices 𝐏𝐽/𝑈,𝑗
(25)

𝑑∗
𝑑
𝐏𝐽/𝑈,𝑖= 𝐏𝐽/𝑈,𝑖𝑑
1+𝜏𝑈,𝑖𝑑
1+𝜏𝐽,𝑖.

In our study, only the Japan-US differences in the indirect taxes on the consumption of liquor,
tobacco, and gasoline are considered.

10𝑑
To distinguish the price level index from the prices, we use the bold as 𝐏𝑈𝑈,𝑖.

10

2.2 Purchaser’s Prices
The section 2.1 describes the price model based on the producer’s prices. However, the PPP
data in main sources are measured at the purchaser’s prices. In this section, we describe therelationship between the producer’s prices and purchaser’s prices. Some notations are defined
additionally as follows:
𝑝𝑝,𝑙

𝑝𝑘,𝑖

Price of product i produced in country k, purchased by industries (I) or household (H) in
country k at purchasers’ prices in currency of country k, (If l = I, the product ispurchased by industries for intermediate uses or investment. If l = H, the product ispurchased by household for final consumption.),𝑝𝑝,𝑙𝑝𝑘𝑘′,𝑖Price of product i produced in country k, purchased by industries (I) or household (H) in
country k’ at purchasers’ prices in currency of country k, (If l = I, the product ispurchased by industries. If l = H, the product is purchased by household.),𝑝𝑝,𝑙𝑝𝑘𝑘′,𝑖Price of product i imported from country k, purchased by industries (I) or household(H) in country k’ at purchasers’ prices in currency of country k’, (If l = I, the product ispurchased by industries. If l = H, the product is purchased by household.),𝑙𝑇𝑘,𝑖Transportation service input for one unit of imported and domestic product i in countryk, (If l = I, the service is input for industries. If l = H, the service is input forhouseholds.),

𝑑,𝑙
𝑊𝑘,𝑖

Trade service input for one unit of domestic product i in country k, (If l = I, the service
is input for industries. If l = H, the service is input for households.),

𝑚,𝑙
𝑊𝑘,𝑖

Trade service input for one unit of imported product i in country k, (If l = I, the service
is input for industries. If l = H, the service is input for households.),

𝑇,𝑙
𝑚𝑘,𝑖

Rate of transportation cost (T) of product i in country k for imported and domestic
products, (If l = I, the rate is for industries. If l = H, the rate is for households.)

𝑊,𝑙
𝑚𝑘,𝑖

Rate of trade margin (W) of i-product in k-country for imported and domestic products,(If l = I, the rate is for industries. If l = H, the rate is for households.)

𝑊,𝑑,𝑙
𝑚𝑘,𝑖

Rate of trade margin (W) of product i in country k for domestic products, (If l = I, therate is for industries. If l = H, the rate is for households.)

𝑊,𝑚,𝑙
𝑚𝑘,𝑖

Rate of trade margin (W) of product i in country k for imported products, (If l = I, therate is for industries. If l = H, the rate is for households.)

The purchaser’s price purchased by industries and households is defined as the sum of the
producer-price value, the transportation cost, and the trade margin as:
(26)
where
𝑙
𝑇𝐽,𝑖

𝑑,𝑙
𝑝𝐽,𝑇

and

𝑝𝑝,𝑙

𝑑,𝑙
𝑑,𝑙 𝑙
𝑑,𝑙
𝑝𝐽,𝑖 = 𝑝𝐽,𝑖
+ 𝑝𝐽,𝑇
𝑇𝐽,𝑖 + 𝑝𝐽,𝑊
𝑊𝐽,𝑖𝑑,𝑙and

𝑊𝐽,𝑖𝑑,𝑙𝑑,𝑙𝑝𝐽,𝑊(𝑙 = 𝐼, 𝐻),

are the output prices of the transportation and trade services in Japan andare the transportation and the trade services required for one unit of product i. In

our model, since the trade margin rate are distinguished for domestic products and imports, the11superscript “d” is added for the trade margin. The rates of transportation cost and trade margin to
the purchaser’s prices of domestic products are defined as:
(27)

𝑝𝑝,𝑙

𝑇,𝑙
𝑑,𝑙 𝑙
𝑚𝐽,𝑖
= 𝑝𝐽,𝑇
𝑇𝐽,𝑖 �𝑝𝐽,𝑖

𝑝𝑝,𝑙

𝑊,𝑑,𝑙
𝑑,𝑙
and 𝑚𝐽,𝑖= 𝑝𝐽,𝑊
𝑊𝐽,𝑖𝑑,𝑙 �𝑝𝐽,𝑖(𝑙 = 𝐼, 𝐻),

respectively, for each of industry or household uses. Based on Equations (26) and (27), therelationship between the producer’s prices and the purchaser’s prices is given by:
(28)

𝑝𝑝,𝑙

𝑑,𝑙
𝑇,𝑙
𝑊,𝑑,𝑙
𝑝𝐽,𝑖
= 𝑝𝐽,𝑖 �1 − 𝑚𝐽,𝑖
− 𝑚𝐽,𝑖�(𝑙 = 𝐼, 𝐻).

Similar equations are developed for the U.S. products as well. The PLI of the purchaser’s pricesof domestic products is described as:
(29)

𝑝𝑝,𝑙

𝐏𝐽/𝑈,𝑖 =

𝑝𝑝,𝑙

𝑝𝐽,𝑖

𝑑,𝑙
𝑝𝑝,𝑙 = 𝐏𝐽/𝑈,𝑖𝑒𝐽/𝑈 𝑝𝑈,𝑖

𝑇,𝑙

𝑊,𝑑,𝑙

�1−𝑚𝑈,𝑖 −𝑚𝑈,𝑖�(𝑙 = 𝐼, 𝐻).

𝑇,𝑙
𝑊,𝑑,𝑙
�1−𝑚𝐽,𝑖 −𝑚𝐽,𝑖 �This equation gives the relationship between the producer-price PLI and the purchaser-price PLIof domestic products.
The PLI of demand prices, which are the prices of the composite product made up of both
imports and its domestic counterpart, is represented as:
(30)

𝑝𝑝,𝑙

𝐏𝐽/𝑈,𝑖 =

𝑝𝑝,𝑙

𝑝𝐽,𝑖

𝑝𝑝,𝑙
𝑒𝐽/𝑈 𝑝𝑈,𝑖𝑐,𝑙= 𝐏𝐽/𝑈,𝑖𝑇,𝑙𝑊,𝑙�1−𝑚𝑈,𝑖 −𝑚𝑈,𝑖 �
𝑇,𝑙𝑊,𝑙�1−𝑚𝐽,𝑖−𝑚𝐽,𝑖�(𝑙 = 𝐼, 𝐻).

The rate of transportation cost for the component of imports is the same as that for the domestic
𝑇,𝑙𝑇,𝑙and 𝑚𝑈,𝑖
are applied in Equations (29) and (30). On the
products. Thus the same rates of 𝑚𝐽,𝑖𝑊,𝑚,𝑙other hand, the rate of domestic trade margin for imports 𝑚𝑘,𝑖is different from that for

𝑊,𝑑,𝑙
𝑊,𝑙
𝑊,𝑙
domestic products 𝑚𝑘,𝑖in our model. Thus Equation (30) is described using, 𝑚𝐽,𝑖and 𝑚𝑈,𝑖,

which are the rates of trade margin for composite products measured as:
(31)

𝑝𝑝,𝑙

𝑝𝑝,𝑙

𝑝𝑝,𝑙

𝑊,𝑙
𝑊,𝑚,𝑙
∑𝑗∈𝑙 �𝑝𝑘 ′ 𝑘,𝑖 𝑋𝑘 ′𝑘,𝑖𝑖 + 𝑝𝐸𝐸,𝑖 𝑋𝐸𝐸,𝑖𝑖 ��∑𝑗∈𝑙 𝑝𝑘,𝑖 𝑋𝑘,𝑖𝑖
𝑚𝑘,𝑖= 𝑚𝑘,𝑖
𝑝𝑝,𝑙

𝑝𝑝,𝑙

𝑊,𝑑,𝑙
+𝑚𝑘,𝑖
∙ ∑𝑗∈𝑙 𝑝𝑘𝑘,𝑖 𝑋𝑘𝑘,𝑖𝑖 �∑𝑗∈𝑙 𝑝𝑘,𝑖 𝑋𝑘,𝑖𝑖(𝑘𝑘 ′ = 𝐽𝐽 𝑜𝑜 𝑈𝑈 and 𝑙 = 𝐼, 𝐻).

𝑊,𝑙is measured as
Equation (31) indicates that the rate of trade margin for composite products 𝑚𝑘,𝑖

𝑊,𝑚,𝑙
𝑊,𝑑,𝑙
a weighted average of 𝑚𝑘,𝑖and 𝑚𝑘,𝑖, whose weights are the nominal value shares evaluatedat the purchaser’s prices. This study estimates the rates of trade margins using establishment datafrom the Japanese Census of Commerce, as explained in section 4.

𝑝𝑝,𝐼
𝑝𝑝,𝐻
The PLIs, 𝐏𝐽/𝑈,𝑖and 𝐏𝐽/𝑈,𝑖in Equation (30), presents the Japan-US level comparison ofdemand prices evaluated by purchaser’s prices for industry and household uses, respectively.

Using this PLI of the products for household uses, the Japan-US Purchasing Power Parity (PPP)
for household consumption by product is shown as:
(32)

𝑝𝑝,𝐻

𝐻
𝐏𝐏𝐏𝐽/𝑈,𝑖= 𝑒𝐽/𝑈 𝐏𝐽/𝑈,𝑖 .

𝑝𝑝,𝐻𝐻, or the purchaser-price PLI, 𝐏𝐽/𝑈,𝑖, on household consumption between
If the PPP data, 𝐏𝐏𝐏𝐽/𝑈,𝑖𝑐,𝐻Japan and the U.S. are available, we can measure the producer-price PLI of demand prices, 𝐏𝐽/𝑈,𝑖,𝑑,𝐻from Equation (30), and then the PLI of domestic products, 𝐏𝐽/𝑈,𝑖, can be measured from

Equation (23).

Based on the price model we formulated above, we can illustrate the relationships among
several PLIs and define four types of estimation processes from the observed PLIs to derive other
PLIs using the price model in Figure 3. The PLI surrounded by each box means the observed PLI
12

in each type of estimation process.
𝑑
is available
Type-1 indicates the case that the producer-price PLI of domestic outputs 𝐏𝐽/𝑈,𝑖𝑑,𝐼(the arrow to
based on surveys. 11 In this case, it is assumed that the difference between 𝐏𝐽/𝑈,𝑖𝑑,𝐻(the arrow to the higher left) is caused only by thethe lower left in Figure 3) and 𝐏𝐽/𝑈,𝑖𝑑∗difference in the treatment of consumption tax. Therefore, after 𝐏𝐽/𝑈,𝑖is determined based on𝑑,𝐼𝑑,𝐻and 𝐏𝐽/𝑈,𝑖
are calculated as:
Equation (25), 𝐏𝐽/𝑈,𝑖

(33)

𝑑,𝑙
𝑑∗
𝐏𝐽/𝑈,𝑖= 𝐏𝐽/𝑈,𝑖𝑙
1+𝜏𝐽,𝑖𝑙
1+𝜏𝑈,𝑖(𝑙 = 𝐼, 𝐻).

𝑐,𝐼Next, the producer-price PLI of composite products for intermediate use 𝐏𝐽/𝑈,𝑖and for𝑐,𝐻household use 𝐏𝐽/𝑈,𝑖
are derived based on Equation (21), considering the difference in importprices for Japan and the U.S. Finally, the purchaser-price PLI of the products for intermediate use
𝑝𝑝,𝐼

𝑝𝑝,𝐻

𝐏𝐽/𝑈,𝑖 and for household use 𝐏𝐽/𝑈,𝑖 are estimated using Equation (30), reflecting the difference inthe trade margins and the transportation costs by product between Japan and the U.S.

𝑝𝑐,𝐻

𝐏𝐽/𝑈,𝑖𝑝𝑐,𝐼

𝐏𝐽/𝑈,𝑖𝑐,𝐻
𝐏𝐽/𝑈,𝑖𝑑,𝐻
𝐏𝐽/𝑈,𝑖𝑑
𝐏𝐽/𝑈,𝑖𝑐,𝐼
𝐏𝐽/𝑈,𝑖𝑑,𝐼
𝐏𝐽/𝑈,𝑖

Type1

Type2

Type3

Type4

Figure 3: Estimation Process in Four Types of Price Scenarios

𝑝𝑝,𝐼
𝐏𝐽/𝑈,𝑖Type-2 is the case where data for the purchaser-price PLI of the products for industry use
𝑝𝑝,𝐻
𝑐,𝐼
𝑐,𝐻
and household use 𝐏𝐽/𝑈,𝑖
are available. Based on this data, 𝐏𝐽/𝑈,𝑖and 𝐏𝐽/𝑈,𝑖(the arrow to𝑑,𝐼𝑑,𝐻and 𝐏𝐽/𝑈,𝑖are
the right in Figure 3) are calculated based on Equation (30). And then, 𝐏𝐽/𝑈,𝑖𝑑
is derived as the aggregates based on theestimated in accordance with Equation (23) and 𝐏𝐽/𝑈,𝑖Equation (24).

𝑝𝑝,𝐻
In Type-3 scenarios, only the purchaser-price PLI of the products for household use 𝐏𝐽/𝑈,𝑖

is available as observations (like the Eurostat-OECD PPPs). By considering the differences in𝑐,𝐻𝑑,𝐻
trade margins and the transportation costs, 𝐏𝐽/𝑈,𝑖and 𝐏𝐽/𝑈,𝑖
are estimated based on Equations𝑑,𝐼(30) and (23), respectively. In this case, 𝐏𝐽/𝑈,𝑖is derived (the arrow pointing down in Figure 3)

𝑑,𝐼
𝑑,𝐻
𝑑
is determined using 𝐏𝐽/𝑈,𝑖and 𝐏𝐽/𝑈,𝑖based on Equation (24).
satisfying Equation (33) and 𝐏𝐽/𝑈,𝑖𝑝𝑝,𝐼𝑐,𝐼
Additionally, 𝐏𝐽/𝑈,𝑖 and 𝐏𝐽/𝑈,𝑖 are estimated taking the difference in the import prices, thepercentage of import, the trade margins, and the transportation costs between Japan and the U.S,

11
The Type-1 scenarios include two approaches of the use of cost index and the reference PPP. The details of these approaches
are explained in Section 3.2.

13

𝑝𝑝,𝐼
𝑝𝑝,𝐻
into the consideration. In Type 4 scenarios, 𝐏𝐽/𝑈,𝑖
is first observed instead of 𝐏𝐽/𝑈,𝑖 in Type-3

cases, but the processes to estimate other PLIs are similar.

2.3 Import Prices from Exogenous Economies
This paper expands the price model to incorporate the prices of the imports from exogenous𝑚,𝑙𝑚,𝑙economies (E) to Japan (J) and the U.S. (U). The estimates of these prices, 𝑝𝐸𝐸,𝑖and 𝑝𝐸𝐸,𝑖,𝑑,𝑙respectively, are used to deduce the producer-price PLI of domestic products 𝐏𝐽/𝑈,𝑖in Equation𝑚,𝑙𝑚,𝑙(23). We define 𝑝𝐸𝐸,𝑖and 𝑝𝐸𝐸,𝑖as the combined import prices from exogenous economies:

(34)

𝑚,𝑙
𝑚,𝑙
𝑚,𝑙
𝑑,𝑙 𝑚,𝑙
𝑚,𝑙
𝑚,𝑙
𝑙
𝑝𝐸𝑘
′ ,𝑖 = ∑𝑘 𝑝𝑘𝑘 ′ ,𝑖 𝑣𝑘𝑘 ′ ,𝑖 = ∑𝑘≠𝑅 𝑒𝑘′/𝑘 𝜔𝑘𝑘′,𝑖 𝑝𝑘,𝑖 𝑣𝑘𝑘′,𝑖 + 𝑝𝑅𝑅′,𝑖 𝑣𝑅𝑅′,𝑖 ,where the

𝑚,𝑙
𝑣𝑘𝑘
′ ,𝑖

(𝑙 = 𝐼, 𝐻, 𝑘 = 𝐶, 𝐺, 𝐾, 𝑀, 𝑊, 𝑇, 𝑅, and 𝑘′ = 𝐽 𝑜𝑜 𝑈),

stands for the import shares at current prices from country k (the exogenous𝑚,𝑙economies) to country k’(Japan and the U.S.). The sum of the import shares ∑𝑘 𝑣𝑘𝑘′ ,𝑖 is one.

𝑚,𝑙𝑙𝑝𝑅𝑅′,𝑖is the average price of imported goods from the rest of the world (ROW). 𝜔𝑘𝑘′,𝑖, which isdefined in Equation (16), is the combined coefficient to transform the output prices in country k

to the import prices in country k’ from country k. Since it is difficult to obtain the output prices in𝑑,𝑙country k (𝑝𝑘,𝑖) directly from statistical data, we construct the following sub model to determine𝑑,𝑙𝑝𝑘,𝑖in six exogenous economies (k) excluding the ROW.

12

We describe the demand price (of the composite products) in country k as:

(35)
where

𝑐,𝑙
𝑑,𝑙 𝑐,𝑙𝑑,𝑙 𝑐,𝑙𝑙𝑝𝑘,𝑖= 𝑝𝑘,𝑖𝑣𝑘𝑘,𝑖 + ∑𝑘≠𝑘 ′ 𝑒𝑘/𝑘′ 𝜔𝑘𝑙 ′ 𝑘,𝑖 𝑝𝑘𝑑,𝑙′ ,𝑖 𝑣𝑘𝑐,𝑙′ 𝑘,𝑖 + 𝑒𝑘/𝐽 𝜔𝐽𝐽,𝑖
𝑝𝐽,𝑖
𝑣𝐽𝐽,𝑖
𝑑,𝑙 𝑐𝑐𝑚,𝑙 𝑐,𝑙𝑙+𝑒𝑘/𝑈 𝜔𝑈𝑈,𝑖𝑝𝑈,𝑖𝑣𝑈𝑈,𝑖 + 𝑝𝑅𝑅,𝑖𝑣𝑅𝑅′,𝑖 ,

𝑐,𝑙
𝑣𝑘𝑘
′ ,𝑖

(𝑘 = 𝐶, 𝐺, 𝐾, 𝑀, 𝑊, 𝑇, 𝑘′ = 𝐶, 𝐺, 𝐾, 𝑀, 𝑊, 𝑇, and 𝑙 = 𝐼, 𝐻).

is the demand share of the domestic product and the imported product at current𝑐,𝑙prices from country k to country k’. The sum of the demand shares ∑𝑘 𝑣𝑘𝑘′ ,𝑖 is one. In this𝑑,𝑙in the first and second terms of the right hand are the prices to be determined
equation, 𝑝𝑘,𝑖endogenously in the sub model. The third and fourth terms are the import prices from Japan and𝑑,𝑙𝑑,𝑙and 𝑝𝐽𝐽,𝑖, are pre-determined in the main model
the U.S., respectively, whose output prices, 𝑝𝑈𝑈,𝑖and are treated as exogenous variables in the sub model. And the final term is the exogenous
import prices from the ROW.
𝑐,𝑙
If the U.S. demand price 𝑝𝑈,𝑖is pre-determined in our main model described in theprevious sections and the demand-price PPPs are observed in the Eurostat-OECD PPPs, METI𝑐,𝑙, are calculated. The
PPP survey, or other PPP surveys, the demand price in country k, 𝑝𝑘,𝑖Equation (35) is measured in each of six countries. If other variables in Equation (35) are given
exogenously, the output prices of product i in six countries are determined by solving theseequations. 13𝑑,𝑙By substituting the estimated 𝑝𝑘,𝑖for six countries into Equation (34), import prices from𝑚,𝑙𝑚,𝑙exogenous economies to Japan and the U.S., 𝑝𝐸𝐸,𝑖and 𝑝𝐸𝐸,𝑖, are determined. Any revisions in
12

In the sub model, indirect taxes are not considered for simplicity.
In our study, exogenous variables related to China, Korea, Malaysia, Taiwan, Thailand are obtained from the AsianInternational IOT published by IDE (Institute of Developing Economies) and the variables related to Germany are obtained
from WIOD (World Input-Output Database) funded by European Commission.
13

14

𝑑,𝑙
𝑑,𝑙
and 𝑝𝐽𝐽,𝑖in the main model. Through several
these prices change the estimates of 𝑝𝑈𝑈,𝑖reiterations between the main model and the sub model, we obtain the final results of all types of
PLIs between Japan and the U.S.

3

Data

3.1 Elementary Level Purchasing Power Parities
In our study, we use the price-differential data obtained from the Eurostat-OECD PPPs, the
METI survey, and many sources published by agencies and ministries of the Government ofJapan and business sectors. The total number of price data at the elementary level used in thisstudy was 507. Since the number of product in our model is 174, multiple data for one productwere used. The product level PLIs are calculated as the translog indices using the elementarylevel price data. If the weight for the elementary level is unavailable in aggregation, the product’s
PLI is calculated as a simple geometric average index.
Table 1: Concepts of Collected Data at the Elementary Level
Purchaser's priceHousehold consumption

Intermediate uses
𝑝𝑐,𝑁
𝐏𝐽/𝑈,𝑖Other
Total
M ETI PPP Other PPP
surveysurveys surveys onunit prices
CPC code
0 Agriculture, forestry and fishery
1 Ores and minerals; electricity, gas
and water
2 Food, beverages and tobacco;
textiles, apparel and leather
3 Other transportable goods, except
metal products, machinery,equipment
4 M etal products, machinery andequipment
5 Constructions and construction
services
6 Trade; accommodation, food andbeverage serving; transport
7 Financial and related services; realestate; rental and leasing services
8 Business and production services
9 Community, social and personal
services
Total

𝑝𝑐,𝐻

𝐏𝐽/𝑈,𝑖Eurostat- Other PPP
Other
Total
OECD
surveys surveys on
PPPsunit prices
6

10

3

5
67

6

104

6

15

1

6

46

5

51

9

82

11

13

24

3

107

17

7

5

29

20

1

3

28

10

1

1

12

1

5

10

4

1

18

18

8

5

12
14

15

𝑑
𝐏𝐽/𝑈,𝑖

Other
Cost index Total
surveys onorunit prices reference
PPP
10
1
11
5

10

249

𝑝𝑐,𝐹

𝐏𝐽/𝑈,𝑖EurostatOECD
PPPs

2

1
23

Producer's priceInvestment

12

20

1

278

123

33

3

6
13

163

2
1

24

17

1

6

21

3

3

60

4

7

113

3

3

159

4

4

44

4

21
7

Total

20

1

3

19

3

3

35

2

2

35

22

42

507

Table 1 represents the concepts of the collected data at the elementary level PPPs by broadgroup of product. Each row corresponds to a sector of Central Product Classification Ver.2. Oneof the most important data sources is the Eurostat-OECD PPPs, which is based on the ICP(International Comparison Programme) coordinated jointly by the World Bank, OECD andEurostat. The latest survey is the 10th survey for 2011, but we mainly use the 8th survey for 2005
covering 45 countries. At the most detailed level, the 8th survey includes price data for 226
products which are called “basic headings”. We use the detailed data provided by the OECD
Statistics Directorate. The survey observes PPPs at purchaser’s prices of composite products
purchased by households or used as investment. As shown in Table 1, 123 price data for
𝑝𝑝,𝐻
𝑝𝑝,𝐹
households and 24 price data for investment were used to correspond to 𝐏𝐽/𝑈,𝑖and 𝐏𝐽/𝑈,𝑖,15

respectively.

14

For intermediate products, the METI’s Survey on Disparities between Domestic and Foreign
Prices of Industrial Intermediate Inputs is the main data source. This survey has been conducted
every year since 1993. The 2005 survey, collecting the price data of 193 goods and 56 services
for intermediate uses, covered 6 countries namely, Japan, the U.S., China, Germany, Korea, andTaiwan. Data in this survey is measured in the purchaser’s price PPPs. As seen in Table 1, 249
𝑝𝑝,𝑁
data are collected from this survey and used to estimate 𝐏𝐽/𝑈,𝑖, in our framework. 15

Although these two surveys don’t cover all the products, there are rich data on international

price differentials based on the surveys implemented by a number of Japanese ministries. We use
Survey of PPPs on Consumer Goods and Services (METI, 2002), Survey of PPPs on Drugs andMedical Products (Ministry of Health, Labour and Welfare, 2003), Survey of Retail Prices ofFood Products in Tokyo and Foreign Major 6 Cities (Ministry of Agriculture, Forestry and
Fisheries, 2006), and so on.16 From these surveys, 14 price data for intermediate use and 33 price
𝑝𝑝,𝑁
𝑝𝑝,𝐻
data for household use are used to estimate 𝐏𝐽/𝑈,𝑖and 𝐏𝐽/𝑈,𝑖respectively. 17

In addition, other surveys on unit prices are used in this study. For example, the output

prices of some agricultural products evaluated at the producer’s price are directly observed from
Table on Value and Quantity (Butsuryo Hyo) which was compiled as a supplementary table of theJapanese IOT and Rice Outlook, Oil Crops Outlook, or Sugar and Sweeteners Outlook publishedby the U.S. Department of Agriculture. The output prices for cattle, poultry and hog in Japan andthe U.S. are directly obtained from the statistical data on livestock and its products published by
the ALIC (Agriculture and Livestock Industries Corporation, Japan). The output prices of coal,crude oil, and natural gas are obtained from Trends of the Japanese Mining Industry published by
METI and Annual Energy Review published by the U.S. Energy Information Administration. As𝑑. Moreover, there are some other surveys on
the result, 20 price data are used to determine 𝐏𝐽/𝑈,𝑖unit prices observing demand prices evaluated at purchaser’s price are used and 15 price data for
𝑝𝑝,𝑁
𝑝𝑝,𝐻
intermediate use and 7 data for household use are used as, 𝐏𝐽/𝑈,𝑖and 𝐏𝐽/𝑈,𝑖, respectively.

The cost index approach is also adopted for some products, whose prices are difficult to

directly observe. In the cost index approach, the producer-price PLIs of domestic products are
estimated by the PLIs of all intermediate products we estimated in this paper and the estimates of
the PLIs for labor and capital inputs estimated in Jorgenson, Nomura, and Samuels (2015), using
the weights of the cost structures obtained from the Japan-US IOT. For some products whose data
14

𝑝𝑝,𝑁

𝑝𝑝,𝐹

In Table 1, the purchaser’s demand price for intermediate uses 𝐏𝐽/𝑈,𝑖 and for investments 𝐏𝐽/𝑈,𝑖 are distinguished. Both of𝑝𝑝,𝐼them are treated as 𝐏𝐽/𝑈,𝑖in the price framework explained in Section 2.
The PPPs for 179 goods and 56 services were obtained from the 2005 survey, and the PPPs for 12 goods and 2 services areused from the surveys in other years. These PPPs in other years are converted to the 2005 PPPs using the Japanese PPI (CGPI
for goods and CSPI for service by the Bank of Japan) and the U.S. PPI (by the BLS).
16
In addition, Survey of PPPs on Transportation and Related Services (Ministry of Land, Infrastructure and Transport, 2005),
Survey of PPPs on Residential Buildings and Infrastructure (MLIT, 2003), Survey of PPPs on Wood Products (Forest Agency,
1995), Survey of PPP on Information Services (Ministry for Internal Affairs and Communications, 2005), Survey of PPP on
Telecommunication Services (Ministry for Internal Affairs and Communications, 2005), Survey of PPPs on Major Consumer
Goods and Services (Cabinet Office, 2001), and Survey of PPPs on Consumer Durables by Functional Attributes (METI, 2002)
are used in our study.
17
These data are estimated for different years and different stages of demand. The differences in timing of the surveys were
adjusted using the CPI and PPI (CGPI and CSPI by the Bank of Japan) in both countries. We have reconciled these data within
our price model.
15

16

are not available, we apply the reference PPP approach, in which the PPPs of the similar products
are applied. In this study, the cost index approach is applied for 10 elementary level products
such as government service, education, and research (without giving consideration to TFP gaps
between Japan and the U.S.), and the reference PPP approach is applied for 12 elementary levelproducts.

3.2 Product Level Purchasing Power Parities and Price ModelAs shown in Table 1, many of obtained price data are based on the purchaser’s demand
𝑝𝑝,𝐼
𝑝𝑝,𝐻
𝑑
prices. Therefore, 𝐏𝐽/𝑈,𝑖is estimated in this study using 𝐏𝐽/𝑈,𝑖
and/or 𝐏𝐽/𝑈,𝑖for many products,

based on the types of estimation process defined in Figure 3. Table 2 presents the number of
products corresponding to the types of estimation process we applied. Each row shows theCentral Product Classification Ver.2, and the number in the column of “Total” equals the numberof products classified in each group (the total is the number of all products, 174).
Table 2: Number of Products by Types of Estimation Scenarios
Type 1
Producer's price

CPC code
0 Agriculture, forestry and fishery
1 Ores and minerals; electricity, gas andwater
2 Food, beverages and tobacco; textiles,
apparel and leather
3 Other transportable goods, except metal
products, machinery, equipment
4 Metal products, machinery andequipment
5 Constructions and construction services
6 Trade; accommodation, food andbeverage serving; transport
7 Financial and related services; real estate;rental and leasing services
8 Business and production services
9 Community, social and personal services
Total𝑑
𝐏𝐽/𝑈,𝑖Type 2Type 3
Type 4Purchaser's priceHousehold Household
Industry&Industry
use
use
use

𝑝𝑐,𝐻

𝐏𝐽/𝑈,𝑖&𝑝𝑐,𝐼

8

𝐏𝐽/𝑈,𝑖

5

1

1

3

4
1

𝑝𝑐,𝐻
𝐏𝐽/𝑈,𝑖

4

𝑝𝑐,𝐼
𝐏𝐽/𝑈,𝑖(Type 4.1)
(Type 4.2)
(Type 4.3)
Intermediate Intermediate Investment
uses&Invest
uses
ment
𝑝𝑐,𝑁
𝐏𝐽/𝑈,𝑖&𝑝𝑐,𝐹
𝐏𝐽/𝑈,𝑖𝑝𝑐,𝑁
𝐏𝐽/𝑈,𝑖𝑝𝑐,𝐹
𝐏𝐽/𝑈,𝑖

Total

12

3

3

9

20

1

1

25

8

8

14

14

34

6

10

28

1

3

8

3

1

1

1

3

2

1

1

7

3
2
27

4
2
35

3
6
57

1
3
55

1
3
40

11
13
174

2

5

16

7
3

5

45
4
14

10

𝑑
According to Table 2, Type-1, which observes 𝐏𝐽/𝑈,𝑖firstly, was applied for 27 products,𝑑which were mainly classified in Agriculture and Mining sector. Since the estimation of 𝐏𝐽/𝑈,𝑖isthe target of this study, Type-1 is the most preferable case. On the one hand, the PLIs for 35

𝑝𝑝,𝐼
𝑝𝑝,𝐻
products are estimated by Type-2 process, in which 𝐏𝐽/𝑈,𝑖and 𝐏𝐽/𝑈,𝑖 are observed first. This type

𝑝𝑝,𝐻
can be considered as the second best type. Type-3 determines 𝐏𝐽/𝑈,𝑖first. 57 products, most ofwhich are final consumption goods and services, are estimated by this method. This is the most𝑝𝑝,𝐼frequent case among our four scenarios. Although Type-4, which first observes 𝐏𝐽/𝑈,𝑖, is similar toType-3, this is divided into three sub-types depending on the kinds of the observed PLIs. In the𝑝𝑝,𝐼first case, written as Type-4.1 in , the PLI of purchaser’s demand price for industries 𝐏𝐽/𝑈,𝑖is
𝑝𝑝,𝑁

determined as using both the PLI of the products for intermediate use and investment, 𝐏𝐽/𝑈,𝑖 and
17

𝑝𝑝,𝐹

𝐏𝐽/𝑈,𝑖 , respectively. Type-4.1 is applied only to 5 products classified in Metal products, machinery, and
𝑝𝑝,𝑁

𝑝𝑝,𝐼

equipment. Type-4.2 uses 𝐏𝐽/𝑈,𝑖 to determine 𝐏𝐽/𝑈,𝑖 and 40 products belong to this case. The PLIs

𝑝𝑝,𝐹
𝑝𝑝,𝐼
of only 10 products are estimated by Type-4.3, which uses only 𝐏𝐽/𝑈,𝑖to determine 𝐏𝐽/𝑈,𝑖 .

4

Trade Margin

4.1 Issues
In this section, we examine the details on trade margins. Determining the trade margins are
one of the most important topics in the PLI estimation due to its larger volume and potential
impacts to the estimates of the producer-price PLIs for all kind of goods, except in the process ofthe type-1. We discuss some issues on the estimates of wholesale and retail margins in Japan.
In our previous study Nomura and Miyagawa (1999), the margin rates were obtained fromthe benchmark SUT/IOTs for Japan and the U.S.; i.e. the Japan’s 1990 Benchmark IOT and the
U.S. 1987 Benchmark SUT. As with that case, we firstly applied the margin rates obtained fromthe Japan’s 2005 Benchmark IOT and the U.S. 2002 Benchmark SUT for our estimation of PLIs.
Wholesale margin for industry use

Wholesale margin for household use

100%

100%

90%

90%

80%

80%

70%

70%

60%
50%

60%

the U.S.

the U.S.

50%

40%

40%

30%

30%

20%

20%

Japan

10%

Japan

10%

0%

0%
0.6<0.65

0.65<0.7

0.7<0.75

0.75<0.8

0.6<0.65

0.65<0.7

0.7<0.75

0.75<0.8

0.55<0.6

0.5<0.55

0.45<0.5

0.4<0.45

0.35<0.4

0.3<0.35

0.25<0.3

0.2<0.25

0.15<0.2

Retail margin for household use
100%

90%

90%

80%

80%

70%

70%

60%

60%

50%

50%

40%

40%

30%

0.1<0.15

0.05<0.1

0<0.0500.75<0.8

0.7<0.75

0.65<0.7

0.6<0.65

0.55<0.6

0.5<0.55

0.45<0.5

0.4<0.45

0.35<0.4

0.3<0.35

0.25<0.3

0.2<0.25

0.15<0.2

0.1<0.15

0.05<0.1

0<0.050Wholesale margin for export
100%

the U.S.

30%

20%

the U.S.

20%

Japan

10%

Japan

10%

0%

0%
0.55<0.6

0.5<0.55

0.45<0.5

0.4<0.45

0.35<0.4

0.3<0.35

0.25<0.3

0.2<0.25

0.15<0.2

0.1<0.15

0.05<0.1

0<0.0500.75<0.8

0.7<0.75

0.65<0.7

0.6<0.65

0.55<0.6

0.5<0.55

0.45<0.5

0.4<0.45

0.35<0.4

0.3<0.35

0.25<0.3

0.2<0.25

0.15<0.2

0.1<0.15

0.05<0.1

0<0.050

Figure 4: Japan-US Cumulative Histogram of Margin Rate (1: Japan IOT Case)
Figure 4 shows the cumulative histograms of margin rates (three wholesale margins forindustry use, household use, and export and one retail margin) between Japan for 2005 and the
U.S. for 2002. According to Figure 4, the U.S. wholesale margin rates are distributed more inlower rates compared to those in Japan, for all kinds of wholesale margins. In the retail margins,
however, Japanese rates are distributed more in lower rates compared to the U.S. Our motivation
is to check the accuracy of the lower rates of retail margins in Japan.
18

We start to examine the data source of the margin rates in the 2005 Japanese IOT. The 2002
Census of Commerce (COC) by METI, is used as the major source to compile the wholesale andretail margins. 18 In the COC, although data of sales by product are collected from all
establishments, data of purchases is collected only by corporation, which may consists of someestablishments. 19 Due to this data constraint, the wholesale and retail margins by product in theJapanese IOT are estimated based on a simplified assumption that the margin rates for all
products sold by one corporation are the same. Thus the margin rates by products are measured as
the weighted average using the sales matrix of products by corporation. Moreover, the 2005
margin rate in the Japanese IOT is estimated by multiplying the change in the rate of margin from2002 to 2005 obtained from the Financial Statements Statistics of Corporations by Industry(FSSCI) (see footnote 18). However, since the FSSCI collects the margin rates of only two
sectors, wholesale and retail, these rates observed at the aggregate level are applied to extrapolate
all kinds of the margin rates. 20 These can generate a large bias in the estimates of the margin
rates by product in 2005.
Another problem is consideration of the quality difference of trade. For example, the qualityof the wholesale service for imported products can differ from that of domestic products. The
quality of electronic commerce may be different from that of the ordinary trade. The Japanese
IOT assumes that the margin rates of imported and domestic products are identical and it doesn’t
consider the difference between the electronic and ordinary commerce. These differences inquality of trade are directly taken into consideration in our study. 21 To check the accuracy and tocontrol these quality differences in measurement of margins, we estimate the margin rates byproduct using establishment-level data of the 2002 and 2007 COC.

4.2 Estimation of Margin Rates
The estimated equations are formulated as:
(36)
(37)

ℎ
ℎ
𝑚𝑗ℎ = 𝛼 ℎ + 𝛽 ℎ ∙ 𝐸𝐸𝑗ℎ + ∑𝑘∈𝐼𝐼𝐼 𝛾𝑘ℎ ∙ 𝐷𝑘𝑘∙ 𝐼𝐼𝑗ℎ + ∑𝑘∈𝐼𝐼𝐼 𝛿𝑘ℎ ∙ 𝐷𝑘𝑘∙ 𝐸𝐸𝑗ℎ + ∑𝑖∈𝑃𝑃𝑃𝑃 𝜇𝑖ℎ ∙ 𝑆𝑖𝑖ℎ + 𝜀𝑗ℎ ,𝑟
𝑚𝑗𝑟 = 𝛼 𝑟 + 𝛽 𝑟 ∙ 𝐸𝐸𝑗𝑟 + ∑𝑘∈𝐼𝐼𝐼 𝛾𝑘𝑟 ∙ 𝐷𝑘𝑘∙ 𝐼𝐼𝑗𝑟 + ∑𝑖∈𝑃𝑃𝑃𝑃 𝜇𝑖𝑟 ∙ 𝑆𝑖𝑖𝑟 + 𝜀𝑗𝑟 .

Equations (36) and (37) are the formulae for the wholesale and the retail establishments,
respectively. And, 𝑚𝑗𝑥 represents the margin rate of establishment 𝑗. If x=h, the establishment is

18

Since this census was not conducted in 2005, the estimates for 2005 are estimated based on the 2002 estimates.
The basic process of compilation is as follows: 1) The sales by sector are obtained from the 2002 COC,;2) The
sales of year 2005 are estimated by multiplying the sales of year 2002 by the change in sales from 2002 to 2005
obtained from the Current Survey of Commerce; 3) The margin rates of corporations by industry are calculated
based on the 2002 COC (the COC does not collect the values of purchase for the unincorporated); 4) The marginrate of year 2005 is estimated by multiplying the margin rate of year 2002 by the change in the rate of marginvalue from 2002 to 2005 obtained from the Financial Statements Statistics of Corporations by Industry (FSSCI)
published by Ministry of Finance; 5) The provisional amount of margin by industry is estimated by multiplying
the sales calculated in Step 2 by the rate of margin calculated in Step 4; and finally 6) By some adjustments, thefinal estimates of margins are determined.
19
In the 2002 COC, 100 products are included in the wholesale and 91 products are included in the retail.
20
In the 2002 COC, the wholesale consists of 78 industries and the retail consists of 72 industries.
21
There are many other factors which generate the quality difference in trades: e.g., opening hours of shop, floor
space, attitude of clerks, facilities of establishments, location of establishments, and so on. These factors are notcontrolled in our current estimation model and some are to be treated in our future research.
19

classified in the wholesale. If x=r, the establishment is classified in the retail. 𝐸𝐸𝑗𝑥 is the ratio of𝑥electronic commerce to total sales of establishment 𝑗. 𝐷𝑘𝑘, is industry dummy variables. When𝑥𝑥
the establishment 𝑗 is classified in industry 𝑘, 𝐷𝑘𝑘= 1, and when it isn’t, 𝐷𝑘𝑘= 0. 𝐼𝐼𝑗𝑥 and𝐸𝐸𝑗𝑥 represent the ratios of import and export, respectively, to total sales. Since there are few

exporting retailers, the term of 𝐸𝐸𝑗𝑟 is eliminated in Equation (37). 𝑆𝑖𝑖𝑥 is the ratio of sales of
product i in the total sales of establishment 𝑗. Finally, 𝜀𝑗𝑥 is the error terms.

In Equations (36) and (37), 𝛼 𝑥 , 𝛽 𝑥 , 𝛾𝑘𝑥 , 𝛿𝑘𝑥 , and 𝜇𝑖𝑥 are the parameters to be estimated. 𝛽 𝑥

stands for the difference in margin rates between electronic commerce and ordinary trade. 𝛾𝑘𝑥

stands for the difference in margin rates between imported and domestic goods in industry 𝑘.

Similarly, 𝛿𝑘𝑥 means the difference in margin rates between exported and domestic goods inindustry 𝑘. The sum, (𝛼 𝑥 + 𝜇𝑖𝑥 ), is the estimated margin rate of product i. 22 Since COC collects
data of purchases only from each establishment, the margin rate of each product cannot bedirectly observed and thus the margin rates by product are estimated using equations presented.
The weighted least squares, whose weights are defined as the square root of establishment’s sales,
are applied for estimation. 23
Figure 5 compares our estimates and the margin rates in the official Japanese IOT. As aresult of our estimation, the margin rates by product change considerably, compared to ourprevious study. Especially in case of the retail margin for households, our estimates of retailmargin rates for many products were higher than those in the IOT. In contrast, in the case ofwholesale margin for exports, our estimates are lower than those in the IOT for many products.
As for individual products, the retail margin rates of foods, drinks, and agricultural products suchas 29.Tea and coffee, 8.Poultry and egg production, 18.Meat and meat products, 19.Dairy
products, 3.Fruits, 20.Seafood products, 21.Grain milling, and 30.Soft drinks were below 20
percent in the IOT. Our estimates, however, suggest they are underestimated. The estimated rates
for these products were increased by 5 to 20 percentage points and these revisions seemreasonable. On the other hand, the wholesale margin rate for industry in 107.Motor vehicles
exceeded 20 percent in the IOT. Based on our estimates, this wholesale margin rate is revised to
15 percent. The upward bias of five percentage point as the difference generates a sizeable
overestimation of one trillion yen in purchaser’s prices of motor vehicle.

22
Since ∑𝑖 𝑆𝑖𝑖𝑥 = 1 for all establishments, one product of 𝑆𝑖𝑖𝑥 is removed from the equations when the equations are estimated.
Therefore, 𝜇𝑖𝑥 measures the difference of margin rate between the removed product and product 𝑖 and 𝛼 𝑥 estimates themargin rate of the removed product.
23
We estimated Equations (36) and (37) using the data of two surveys, the 2002 and 2007 COC. The margin rates by product in2005 are the results provided by a simple linear interpolation of the estimates in 2002 and 2007.

20

Wholesale, for industry use
0.40

003 Fruits
023 Other processed agricultural…
028 Liquor
024 Sugar
042 Furniture, accessories and fixtures
065 Foot wears
012 Fishing
018 Meat and meat products
114 Photographic and photocopying…
002 Vegetables and potatoes
117 Toys and sporting goods
057 Pharmaceutical products
020 Seafood products
115 Surgical, medical and dental…
044 Paper
123 Other miscellaneous…
069 Cement
107 Motor vehicles
019 Dairy products
084 Farm machinery and equipment
071 Cement products and structural…
116 Other precision instruments
037 Other textile product mills
062 Petroleum and coal products
053 Fertilizers
087 Special industrial machinery
072 Pottery and ceramic products
059 Cosmetics and dentifrices
038 Apparel and apparel accessories
001 Grain farming
090 Vending, commercial and…
050 Inorganic chemical products
106 Other electric equipment
060 Paints and printing ink
030 Soft drinks
081 Other metal products
077 Aluminum and rolled…
004 Other crop farming
029 Tea and coffee
039 Lumber and wooden chips
083 Construction machinery and…
026 Seasoning and dressing…
076 Copper, rolled and drawn…
034 Textile and fabric mills, fabric…
045 Paper containers
109 Motorcycle and bicycle
092 Household electrical appliances
046 Other converted paper products
033 Fiber, yarn, and thread mills
017.1 Crude oil
113 Other transportation equipment
061 Other chemical products
056 Synthetic fibers
079 Other non-ferrous metals and…
121 Small personal adornments
075 Iron and steel products
078 Communication and energy…
108 Motor vehicle body and parts
022 Bread and confectionery
058 Soap, synthetic detergents and…
032 Tobacco
049 Publishers

Wholesale, for household use
0.35

003 Fruits
023 Other processed agricultural…

047 Newspaper publishers

107 Motor vehicles

057 Pharmaceutical products

028 Liquor

121 Small personal adornments

049 Publishers

032 Tobacco

090 Vending, commercial and…

068 Glass and glass products

109 Motorcycle and bicycle

108 Motor vehicle body and parts

062 Petroleum and coal products

123 Other miscellaneous…

106 Other electric equipment

012 Fishing

114 Photographic and…

081 Other metal products

030 Soft drinks

059 Cosmetics and dentifrices

Figure 5: Estimated Margin Rates in Comparison with the Official Estimates

053 Fertilizers
028 Liquor
024 Sugar
115 Surgical, medical and dental…
087 Special industrial machinery
018 Meat and meat products
012 Fishing
019 Dairy products
062 Petroleum and coal products
065 Foot wears
020 Seafood products
002 Vegetables and potatoes
117 Toys and sporting goods
069 Cement
034 Textile and fabric mills, fabric…
042 Furniture, accessories and fixtures
107 Motor vehicles
071 Cement products and structural…
114 Photographic and…
077 Aluminum and rolled…

021 Grain milling

118 Musical instruments

117 Toys and sporting goods

042 Furniture, accessories and fixtures

020 Seafood products

036 Carpet, floor mat, and rug mills

038 Apparel and apparel accessories

003 Fruits

019 Dairy products

018 Meat and meat products

037 Other textile product mills

065 Foot wears

072 Pottery and ceramic products

008 Poultry and egg production

120 Writing instruments and…

006 Other non-edible crops

087 Special industrial machinery

029 Tea and coffee

116 Other precision instruments

034 Textile and fabric mills, fabric…

009 Other animal production

21

059 Cosmetics and dentifrices
090 Vending, commercial and…
057 Pharmaceutical products
044 Paper
004 Other crop farming
030 Soft drinks

003 Fruits
037 Other textile product mills
023 Other processed agricultural…
033 Fiber, yarn, and thread mills
028 Liquor
024 Sugar
012 Fishing
053 Fertilizers
044 Paper
115 Surgical, medical and dental…
042 Furniture, accessories and fixtures
002 Vegetables and potatoes
123 Other miscellaneous…
019 Dairy products
018 Meat and meat products
057 Pharmaceutical products
020 Seafood products
066 Leather and fur products
069 Cement
117 Toys and sporting goods
056 Synthetic fibers
081 Other metal products
004 Other crop farming
050 Inorganic chemical products
034 Textile and fabric mills, fabric…
065 Foot wears
076 Copper, rolled and drawn…
026 Seasoning and dressing…
062 Petroleum and coal products
071 Cement products and structural…
083 Construction machinery and…
001 Grain farming
082 Engines, turbines and boilers
084 Farm machinery and equipment
038 Apparel and apparel accessories
039 Lumber and wooden chips
090 Vending, commercial and…
089 Other general machinery
045 Paper containers
116 Other precision instruments
072 Pottery and ceramic products
114 Photographic and photocopying…
107 Motor vehicles
060 Paints and printing ink
085 Metal processing machinery…
087 Special industrial machinery
030 Soft drinks
075 Iron and steel products
092 Household electrical appliances
029 Tea and coffee
049 Publishers
113 Other transportation equipment
058 Soap, synthetic detergents and…
121 Small personal adornments
022 Bread and confectionery
108 Motor vehicle body and parts

IOT

Estimate
0.60

IOT
Estimate
0.35

089 Other general machinery
108 Motor vehicle body and parts
029 Tea and coffee
026 Seasoning and dressing…
081 Other metal products
092 Household electrical appliances
060 Paints and printing ink
109 Motorcycle and bicycle
113 Other transportation equipment
082 Engines, turbines and boilers
046 Other converted paper products
121 Small personal adornments
061 Other chemical products
033 Fiber, yarn, and thread mills
049 Publishers
032 Tobacco
058 Soap, synthetic detergents and…
022 Bread and confectionery
045 Paper containers
050 Inorganic chemical products
079 Other non-ferrous metals and…
075 Iron and steel products

Wholesale, for export
0.40

IOT
Estimate
0.30

IOT
Estimate
0.35

0.30

0.25

0.20

0.10

0.15

0.05

0.00

0.25

0.20

0.15

0.10

0.05

0.00

0.30

0.25

0.20

0.10

0.15

0.05

0.00

0.70

Retail, for household use

0.50

0.40

0.30

0.20

0.10

0.00

Wholesale margin for household use

Wholesale margin for industry use
100%

100%

90%

90%

80%

80%

70%

70%
60% the U.S.
50%

60%
50%

the U.S.

40%

40%

30%

30%

20%

20%

Japan

10%

10%

0%

0%

Japan

0.6<0.65

0.65<0.7

0.7<0.75

0.75<0.8

0.6<0.65

0.65<0.7

0.7<0.75

0.75<0.8

0.55<0.6

0.5<0.55

0.45<0.5

0.4<0.45

0.35<0.4

0.3<0.35

0.25<0.3

0.2<0.25

0.15<0.2

Retail margin for household use
100%

90%

90%

80%

80%

70%

70%

60%

60%

50%
40%

0.1<0.15

0.05<0.1

0<0.0500.75<0.8

0.7<0.75

0.65<0.7

0.6<0.65

0.55<0.6

0.5<0.55

0.45<0.5

0.4<0.45

0.35<0.4

0.3<0.35

0.25<0.3

0.2<0.25

0.15<0.2

0.1<0.15

0.05<0.1

0<0.050Wholesale margin for export
100%

50%

the U.S.

40%

30%

30%

20%

20%

Japan

10%

Japan

10%

0%

the U.S.

0%0.55<0.6

0.5<0.55

0.45<0.5

0.4<0.45

0.35<0.4

0.3<0.35

0.25<0.3

0.2<0.25

0.15<0.2

0.1<0.15

0.05<0.1

0<0.0500.75<0.8

0.7<0.75

0.65<0.7

0.6<0.65

0.55<0.6

0.5<0.55

0.45<0.5

0.4<0.45

0.35<0.4

0.3<0.35

0.25<0.3

0.2<0.25

0.15<0.2

0.1<0.15

0.05<0.1

0<0.050

Figure 6: Japan-US Cumulative Histogram of Margin Rate (2:Our Revised Estimates)
Figure 6 shows the cumulative histogram of margin rates by product estimated using the
COC. Compared to Figure 4, the histograms of the wholesale margin for export and the retailmargin for household in Japan are approaching to those in the U.S. in Figure 6. On the other hand,
the histograms in the wholesale margins for industry and household uses in Figure 6 are almost
the same as Figure 4. We applied these results to calculate the PLIs.
As shown in Equations (36) and (37), the margin rates for imported and domestic products
are distinguished for Japan in our estimation model. However, they are not separated in the U.S.
SUT. In this study, the Japanese parameter, 𝛾�𝑖𝑥 , which are estimated above and represent thedifference of margin rates between imported and domestic products, are assumptively applied for
the U.S. case. Figure 7 compares the estimated margin rates between Japan and the U.S., fordomestic products. Japan’s margin rates are higher in two-thirds of the domestic products thanthose in the U.S.

22

Household use

Industry use
the U.S.

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.0

0.8

Japan

the U.S.

Japan

0.1

121 Small personal adornments
032 Tobacco
049 Publishers
105 Batteries
116 Other precision instruments
107 Motor vehicles
092 Household electrical appliances
095 Wired telecommunication machinery
059 Cosmetics and dentifrices
047 Newspaper publishers
022 Bread and confectionery
027 Other food manufacturing
056 Synthetic fibers
082 Engines, turbines and boilers
123 Other miscellaneous manufacturing
109 Motorcycle and bicycle
115 Surgical, medical and dental instrument
066 Leather and fur products
119 Audio and video media reproducing
088 Semiconductor machinery
103 Electric bulbs
101 Magnetic tape and flexible disk
015 Other non-metal ores
045 Paper containers
006 Other non-edible crops
060 Paints and printing ink
120 Writing instruments and stationary
011 Forestry
025 Vegetable oil
079 Other non-ferrous metals and products
033 Fiber, yarn, and thread mills
055 Synthetic resin
046 Other converted paper products
112 Aircraft and repairing
009 Other animal production
098 Watch, clock, and measuring devices
018 Meat and meat products
117 Toys and sporting goods
004 Other crop farming
083 Construction machinery and conveyors
085 Metal processing machinery and metal machine tool
058 Soap, synthetic detergents and surfactant
008 Poultry and egg production
077 Aluminum and rolled aluminum products
076 Copper, rolled and drawn copper products
026 Seasoning and dressing manufacturing
061 Other chemical products
021 Grain milling
005 Sugarcane and sugar beet farming
097 Applied electronic equipment
108 Motor vehicle body and parts
110 Ship building and repairing
042 Furniture, accessories and fixtures
075 Iron and steel products
087 Special industrial machinery
100 Electron tubes
013 Metal ores
007 Cattle ranching, dairy cattle and milk production
035 Knit fabric mills
017.1 Natural gas
012 Fishing
111 Railroad rolling stock and repairing
052 Organic chemical products
030 Soft drinks
113 Other transportation equipment
017.1 Crude oil
072 Pottery and ceramic products
081 Other metal products
074 Miscellaneous nonmetallic mineral products
050 Inorganic chemical products
031 Animal food manufacturing
053 Fertilizers
093 Electronic computer
062 Petroleum and coal products
016 Coal mining
023 Other processed agricultural food products
038 Apparel and apparel accessories
034 Textile and fabric mills, fabric dyeing
089 Other general machinery
054 Agricultural chemicals
019 Dairy products
064 Rubber products
091 Audio and video equipment
070 Ready-mixed concrete
014 Stone, gravel and ceramic mining and quarrying
086 Other general machinery for industrial use
071 Cement products and structural clay products
078 Communication and energy wires and cables
106 Other electric equipment
024 Sugar
063 Plastic products
099 Semiconductor and related devices
065 Foot wears
090 Vending, commercial and office machinery
069 Cement
104 Other electronic component
002 Vegetables and potatoes
051 Petrochemical products
080 Metal products for construction and architecture020 Seafood products
003 Fruits
029 Tea and coffee
094 Computer peripheral equipment
036 Carpet, floor mat, and rug mills
084 Farm machinery and equipment001 Grain farming
028 Liquor
114 Photographic and photocopying equipment

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9
009 Other animal production
121 Small personal adornments
045 Paper containers
123 Other miscellaneous manufacturing
072 Pottery and ceramic products
059 Cosmetics and dentifrices
008 Poultry and egg production
006 Other non-edible crops
012 Fishing
092 Household electrical appliances
101 Magnetic tape and flexible disk
107 Motor vehicles
015 Other non-metal ores
047 Newspaper publishers
037 Other textile product mills
044 Paper
038 Apparel and apparel accessories
057 Pharmaceutical products
029 Tea and coffee
031 Animal food manufacturing
065 Foot wears
106 Other electric equipment
117 Toys and sporting goods
114 Photographic and photocopying equipment
018 Meat and meat products
020 Seafood products
089 Other general machinery
042 Furniture, accessories and fixtures
113 Other transportation equipment
109 Motorcycle and bicycle
091 Audio and video equipment
022 Bread and confectionery
034 Textile and fabric mills, fabric dyeing
036 Carpet, floor mat, and rug mills
014 Stone, gravel and ceramic mining and quarrying
019 Dairy products
116 Other precision instruments
093 Electronic computer
049 Publishers
060 Paints and printing ink
058 Soap, synthetic detergents and surfactant
021 Grain milling
054 Agricultural chemicals
108 Motor vehicle body and parts
079 Other non-ferrous metals and products
027 Other food manufacturing
086 Other general machinery for industrial use
118 Musical instruments
053 Fertilizers
025 Vegetable oil
030 Soft drinks
003 Fruits
081 Other metal products
119 Audio and video media reproducing
041 Other wooden products
082 Engines, turbines and boilers
033 Fiber, yarn, and thread mills
032 Tobacco
050 Inorganic chemical products
110 Ship building and repairing
046 Other converted paper products
104 Other electronic component
103 Electric bulbs
023 Other processed agricultural food products
080 Metal products for construction and architecture
096 Other telecommunication machinery
074 Miscellaneous nonmetallic mineral products
002 Vegetables and potatoes
071 Cement products and structural clay products
048 Printing
004 Other crop farming
115 Surgical, medical and dental instrument
094 Computer peripheral equipment
063 Plastic products
035 Knit fabric mills
024 Sugar
120 Writing instruments and stationary
067 Other leather products
098 Watch, clock, and measuring devices
090 Vending, commercial and office machinery
064 Rubber products
028 Liquor
075 Iron and steel products
062 Petroleum and coal products

Figure 7: Japan-US Differentials in Margin Rates for Domestic Products

23

4.3 Price Level Indices for Wholesale and Retail Trades
The PLIs of wholesale and retail trades are measured based on some assumptions. The
parameters (𝛼 ℎ + 𝜇𝑖ℎ ) and (𝛼 𝑟 + 𝜇𝑖𝑟 ) in Equations (36) and (37) mean the margin rates of ordinary
trade of product i of domestically produced and consumed in Japan. We define the margin rates inJapan as:(38)
where 𝛼�𝑥

𝑥,𝑑,𝑙∗𝑚𝐽,𝑖= 𝛼� 𝑥 + 𝜇̂ 𝑖𝑥

and

𝜇̂ 𝑖𝑥

(𝑙 = 𝐼, 𝐻, 𝑥 = ℎ, 𝑟),

are the parameters estimated in Equations (36) and (37). Although the similarkinds of estimated margin rates for the U.S. are required, the U.S. Economic Census, Annual
Retail Trade Survey, or Annual Wholesale Trade Survey publishes the margin rates in which
many types of transactions are included. Therefore, in this study, the estimated parameters forJapan are applied to estimate the adjusted margin rates in the U.S.
𝑥,𝑑,𝑙∗
𝑥,𝑑,𝑙
The relationship between the adjusted margin rate 𝑚𝑈,𝑖and the actual margin rate 𝑚𝑈,𝑖for the U.S. domestic transactions is described as:
𝑥,𝑑,𝑙∗
𝑥,𝑑,𝑙𝑚𝑈,𝑖= 𝑚𝑈,𝑖− 𝛽̂ 𝑥 ∙ 𝐸𝐸𝑖𝑥

(𝑙 = 𝐼, 𝐻, 𝑥 = ℎ, 𝑟),𝑥̂where 𝛽 is a parameter estimated in Equations (36) and (37) and 𝐸𝐸𝑖𝑥 shows the ratio of the(39)

𝑥,𝑑,𝑙∗
𝑥,𝑑,𝑙∗and 𝑚𝑈,𝑖, the PLIs ofelectric commerce to total sales of product i in the U.S. Using 𝑚𝐽,𝑖

retail and wholesale trades are derived. The relative measure of the margin rates between Japanand the U.S. are described by definition as:
(40)

𝑝𝑝,𝑙

𝑝𝑝,𝑙

𝑥,𝑑,𝑙∗
𝑥,𝑑,𝑙∗
𝑑,𝑙,𝑖
𝑑,𝑙,𝑖
𝑥,𝑑,𝑙
𝑚𝐽,𝑖
�𝑚𝑈,𝑖
= �𝑝𝐽,𝑥𝑊𝐽,𝑖𝑥,𝑑,𝑙 �𝑝𝐽,𝑖 ���𝑝𝑈,𝑥
𝑊𝑈,𝑖
�𝑝𝑈,𝑖 �(𝑙 = 𝐼, 𝐻 and 𝑥 = ℎ, 𝑟).

𝑑,𝑙,𝑖
𝑥,𝑑,𝑙
𝑊𝐽,𝑖𝑥,𝑑,𝑙 and 𝑊𝑈,𝑖are the volumes of trades required for one unit of product i, and 𝑝𝐽,𝑥
and
𝑑,𝑙,𝑖
𝑝𝑈,𝑥 are the corresponding prices, in Japan and the U.S., respectively. We assume the volume oftrade required for one unit of product i,
(41)

𝑝𝑝,𝑙

𝑥
𝜃𝑘,𝑖

𝑥,𝑑,𝑙
𝑑,𝑙
𝑊𝑘,𝑖
= 𝜎𝑖𝑥 �𝑝𝑘,𝑖 �𝑝𝑘,𝑖�

𝑥
�𝜎𝑖𝑥 > 0, 0 ≤ 𝜃𝑘,𝑖
≤ 1� (𝑘 = 𝐽, 𝑈, 𝑙 = 𝐼, 𝐻, and 𝑥 = ℎ, 𝑟).

Equation (41) indicates that the trade service is decomposed into two parts: first is thevolume-term 𝜎𝑖𝑥 and the second is the quality-term. We assume the volume-term is the same forJapan and the U.S. by product. In the quality-term, 𝜃𝑖𝑥 is the parameter expressing how consumers

evaluate the price difference between the purchaser’s and producer’s prices as the quality
difference in trade by product. For example, wholesalers and retailers need to control thetemperature and humidity of trading vegetables for keeping their freshness and to sell them under

the clean condition. Thus the price difference between the purchase’s price and producer’s price,
𝑝𝑝,𝑙

𝑑,𝑙
ln�𝑝𝑘,𝑖 �𝑝𝑘,𝑖
�, is larger than zero. If consumers fully evaluate this price difference as the quality

𝑝𝑝,𝑙
𝑑,𝑙
𝑥
is close to one), the difference, 𝑝𝑘,𝑖
�𝑝𝑘,𝑖, should be counted as the difference
difference in trade (𝜃𝑘,𝑖in volume of trade, rather than the difference in price of trade. If consumers do not care freshness and

𝑝𝑝,𝑙
𝑑,𝑙
𝑥
is close to zero), the difference, 𝑝𝑘,𝑖
�𝑝𝑘,𝑖, should be counted as thecleanness so much (𝜃𝑘,𝑖𝑥isdifference in price of trade, rather than the difference in volume of trade. Thus the parameter 𝜃𝑘,𝑖determined depending on the product and country.

By Equations (40) and (41), the PLIs of the wholesale and retail trades for product i can beformulated as,

24

(42)

𝑥
𝑝𝑝,𝑙 1−𝜃𝑘,𝑖𝑑,𝑙,𝑖𝐏𝐽/𝑈,𝑥= �𝐏𝐽/𝑈,𝑖 �𝜃𝑥𝑑,𝑙
𝑥,𝑑,𝑙∗
𝑥,𝑑,𝑙∗
�𝐏𝐽/𝑈,𝑖
� 𝑘,𝑖 �𝑚𝐽,𝑖�𝑚𝑈,𝑖�(𝑙 = 𝐼, 𝐻, 𝑥 = ℎ, 𝑟),

𝑑,𝑙
𝑝𝑝,𝑙
and 𝐏𝐽/𝑈,𝑖
are the purchaser-price PLI and the producer-price PLI of domestic
where 𝐏𝐽/𝑈,𝑖𝑥
output of product i. In this study, as a first approximation, we assumed that 𝜃𝑘,𝑖
is 0.5 for all

𝑝𝑝,𝑙
𝑑,𝑙
and 𝐏𝐽/𝑈,𝑖, are
products in both of Japan and the U.S. The PLIs on the right-hand side, 𝐏𝐽/𝑈,𝑖𝑥,𝑑,𝑙∗
𝑥,𝑑,𝑙∗and 𝑚𝑈,𝑖,measured from our price model described in Section 2. The margin rates, 𝑚𝐽,𝑖

are calculated in Equations (38) and (39). As a result, the PLIs of the wholesale and retail trades𝑑𝑑and wholesale trade 𝐏𝐽/𝑈,𝑟for product i are estimated. Moreover, the PLI of retail trade 𝐏𝐽/𝑈,ℎ

𝑑,𝑙,𝑖
𝑑,𝑙,𝑖
and 𝐏𝐽/𝑈,𝑟, respectively, whose weights are theare aggregated by the weighted average of 𝐏𝐽/𝑈,ℎ𝑑𝑑and 𝐏𝐽/𝑈,𝑟are
current value of the respective margins of each product. Our estimates of 𝐏𝐽/𝑈,ℎ1.56 and 1.62, respectively.

5

Results

5.1 Price Level Indices by Product
Table 3 presents the estimated results of the representative measures of PLIs by the broad
product groups based on the ISIC sections and divisions. 24 The first four columns present theprice differentials in domestic outputs (the PLI excluding net indirect taxes, including taxes, forindustry use, and for household use) and the next four columns show the PLIs for the composite
of domestic and imported products (two PLIs at the producer’s prices and two at the purchaser’s
prices). And the last two columns indicate the price differentials between Japan and the U.S. intheir imports. 25 These PLI measures are consistently linked one another based on our pricemodel, described in Section 2.
Our estimates show there are large differences among the PLI estimates based on the
different concepts. For example, Japan’s import prices of 29.Motor vehicles and trailers arehigher than those in the U.S. (by 27.7 percent for industry use and by 10.4 percent for householduse). However, the purchaser-price PLIs, which cover domestic products and imports, are almost
equivalent (12.8 percent lower for industry use and 1.3 percent lower for household use in Japan
than the US). When the impact of the differences in their margin rates from the purchaser-price
PLIs is excluded, Japan’s producer-price PLIs of the composite products are lower than the U.S.
prices (by 21.1 percent for industry use and by 23.5 percent for household use). Especially,
Japan’s producer-price PLIs of the domestic products are considerably lower than those in the
U.S. (by 24.3 percent for industry use and by 30.2 percent for household use). Furthermore, when
we focus on the price differential in domestic product (excluding net indirect taxes), output priceof Japan’s motor vehicles and trailers is 25.9 percent lower than the U.S. counterpart. This resultshows a strong price competitiveness of Japan’s producers of motor vehicles and trailers.
24

In some products of our 174 classification, the unpublished data at the most detailed level (basic headings) of the𝑝𝑝,𝐻Eurostat-OECD PPPs are directly used as 𝐏𝑈𝑈,𝑖 . Since they are not in the public domain, we use 42 types of the broad productgroup for describing the demand-side PLIs.
25
The differences in the quality of products imported by Japan and the U.S. may be somewhat reflected in the pricedifferentials of imports from exogenous countries, although they should be counted in the volume differentials.

25

In contrast, although the PLI of imports of agriculture, forestry and fishing are about 30
percent higher in Japan, the PLI of domestic outputs are 2.2 times higher in Japan compared to
the U.S. counterpart. This result shows Japanese producers are considerably inferior to the U.S.
producers in price competitiveness of agricultural products. As such, in order to compare theprice competitiveness by industry, these cases show that it is indispensable to estimate thedifferentials in output prices, which can considerably differ from the purchaser-price PLIs ofcomposite products that are observed more easily.

Table 3: Estimated Results of Japan-US PLIs in 2005
Domestic outputs

Imports

Composite products

A - Agriculture, forestry and fishing

𝑑∗
𝐏𝐽/𝑈
,𝑖

2.189

𝑑
𝐏𝐽/𝑈
,𝑖

2.254

𝑑,𝐼
𝐏𝐽/𝑈
,𝑖

2.594

𝑑,𝐻
𝐏𝐽/𝑈
,𝑖

1.504

𝑐,𝐼
𝐏𝐽/𝑈
,𝑖

2.192

𝑐,𝐻
𝐏𝐽/𝑈
,𝑖

1.505

𝑝𝑐,𝐼,
𝐏𝐽/𝑈 ,𝑖

2.201

𝑝𝑐,𝐻
𝐏𝐽/𝑈,𝑖

1.786

𝑚,𝐼
𝐏𝐽/𝑈
,𝑖

B - M ining and quarrying

1.359

1.365

1.351

2.422

1.115

2.407

1.103

1.786

1.045

2.064

C - M anufacture

.949

.979

.972

1.262

.966

1.215

1.016

1.403

.950

1.033

10 - Food products

1.785

1.843

1.911

1.929

1.737

1.861

1.954

2.280

1.601

1.574

11 - Beverages

1.609

1.932

1.772

1.931

1.787

1.937

1.725

1.938

1.844

1.854

12 - Tobacco products

.266

.489

.467

.490

.515

.552

.763

.550

2.992

3.102

13 - Textiles

.708

.716

.714

.768

.694

.721

.691

1.129

.638

.646

14 - Wearing apparel

.948

.969

.948

.995

1.046

1.067

1.096

1.678

1.098

1.103

15 - Leather and related products

1.455

1.500

1.458

1.525

1.182

1.270

1.254

1.317

1.153

1.203

16 - Wood and wood products, except furniture

.859

.859

.850

1.195

.822

.860

.854

.885

.740

.825

17 - Paper and paper products

.945

.949

1.010

.566

1.032

.585

1.114

.727

1.185

.867

1.259

𝑚,𝐻
𝐏𝐽/𝑈
,𝑖

1.299

18 - Printing and reproduction of recorded media

.893

.897

.891

.961

.896

.965

.974

1.247

1.156

1.027

19 - Coke and refined petroleum products

1.124

1.478

1.149

2.553

1.158

2.547

1.163

1.581

1.206

2.384

20 - Chemicals and chemical products

1.027

1.030

1.109

.554

1.100

.593

1.167

.849

1.107

.835

21 - Pharmaceutical products

.791

.802

.898

.607

.940

.741

.916

.908

1.078

.799

22 - Rubber and plastics products

.773

.776

.749

1.269

.759

1.278

.755

1.074

.739

.692

23 - Other non-metallic mineral products

.902

.902

.907

1.189

.914

1.103

.942

1.256

.946

.997

24 - Basic metals

.801

.801

.810

.828

.840

.842

.886

.734

1.078

.906

25 - Fabricated metal products, except M &E

.914

.914

.897

1.058

.909

.939

.946

1.044

.609

.794

26 - Computer, electronic and optical products

.997

1.009

1.017

.871

1.033

.920

1.097

1.121

1.007

.744

27 - Electrical equipment

.946

.948

.968

1.159

.831

1.295

.810

1.327

.556

.815

28 - M achinery and equipment n.e.c.

1.060

1.064

1.146

1.259

1.092

1.133

1.121

1.212

.777

.610

29 - M otor vehicles and trailers

.741

.748

.757

.698

.789

.765

.872

.987

1.277

1.104

30 - Other transport equipment

1.021

1.029

1.107

.840

1.113

.837

1.137

1.124

1.101

.851

31 - Furniture

1.069

1.076

1.058

1.195

1.061

.995

1.054

1.474

1.064

1.023

32 - Other manufacturing

.714

.719

.760

.670

.783

.846

.927

1.289

.882

.905

33 - Repair and installation of machinery and equipment

1.026

1.034

1.045

1.235

1.054

1.219

1.095

1.205

1.037

1.028

D - Electricity, gas, steam and air conditioning supply

1.984

2.018

1.988

2.035

1.984

2.034

1.979

2.034

1.240

1.168

E - Water supply

1.191

1.211

1.260

1.065

1.266

1.065

1.268

1.113

.953

.901

F - Construction

1.052

1.054

1.067

.880

1.067

.880

1.067

.880

---

.754

G - Wholesale and retail trade

1.543

1.584

1.568

1.601

1.535

1.596

1.532

1.596

.796

.749

H - Transportation and storage

1.234

1.259

1.146

1.466

1.137

1.467

1.137

1.473

1.040

1.405

I - Accommodation and food service activities

1.205

1.240

1.183

1.329

1.177

1.286

1.177

1.290

.957

.989

J - Information and communication

1.051

1.063

1.040

1.135

1.039

1.136

1.066

1.197

1.045

1.150
1.005

K - Financial and insurance activities

1.142

1.140

1.029

1.348

1.025

1.348

1.029

1.348

.908

L - Real estate activities

1.730

1.745

1.738

1.745

1.738

1.745

1.738

1.745

---

---

M - Professional, scientific and technical activities

.843

.845

.827

.986

.821

.983

.819

.974

.752

.880

N - Administrative and support service activities

1.269

1.281

1.219

1.362

1.215

1.353

1.215

1.353

.855

.902

O - Public administration and defence

1.118

1.118

1.118

1.057

1.118

1.057

1.118

1.057

---

---

P - Education

1.287

1.287

1.287

1.287

1.209

1.287

1.207

1.287

.917

---

Q - Human health and social work activities

.626

.626

.627

.626

.627

.626

.628

.626

---

.548

R - Arts, entertainment and recreation

.973

1.010

.821

1.074

.819

1.071

.819

1.072

.790

.898

S - Other service activities

1.185

1.234

1.015

1.249

1.067

1.247

1.114

1.234

1.054

.921

----1.102
1.243
1.087
1.234
Note: Industry classification is based on the ISIC Rev.4. The average exchange rate used for 2005 is 110.22 yen per dollar.

1.099

1.288

.981

1.051

Total

Figure 8 compares the differences in the purchaser-price PLIs for the composite of domestic
𝑝𝑝,𝐼
𝑝𝑝,𝐻
and imported products between for industry and household uses, 𝐏𝐽/𝑈,𝑖and 𝐏𝐽/𝑈,𝑖 , respectively,26

by the product group. Although there is a positive correlation between them, the pricedifferentials for household uses in most products (31 of 42 products) are larger than those forindustry use; e.g., 13.Textiles, 14.Wearing apparel, 27.Electrical equipment, and 22.Rubber
products. On the other hand, in some products like A-Agriculture, 17.Paper, 20.Chemicals, and
F-Construction, the prices for industry use are higher than those for household use. If thedifferences in quality of the products for industry and household uses are negligible, it may
indicate a possibility of inefficient transactions among industries, which may reduce the pricecompetitiveness of industries to purchase them.

0.5

1.5

1.0

2.0

0.5

1.0

2.20
1.10
1.02
1.95
1.73
0.76
0.69

1.5

2.0

0.5

1.79
1.79
1.40
2.28
1.94

1.11
1.16
1.17
0.92
0.76
0.94
0.89
0.95

0.72
1.13
1.68
1.32

1.63
1.53
1.05
1.04

0.88
0.73

0.97

0.65
1.25
1.58

1.28
1.36

0.85
0.91

0.73
0.99
1.07
1.26

1.42
1.33

0.73

1.12
0.87

0.83
1.04
1.12
1.33
1.21

1.10
0.81

1.10
1.02
1.64
1.08
1.13

0.99
1.12
1.47
1.29
1.21
2.03
1.11

1.14
1.05
0.93
1.09
1.98
1.27
1.07
1.53
1.14
1.18
1.07
1.03
1.74
0.82

0.99
1.40
1.39
1.10
1.03
0.88
0.82

0.88
1.60
1.47
1.29
1.20
1.35
1.75

1.04
1.30
1.10
1.12
1.31
1.00
1.19
1.11

0.97
1.21
1.12
1.21

0.63
0.82

1.35
1.06
1.29

0.95
1.07

0.63
1.11

1.5
1.62
1.38
1.17
1.12

0.55
1.10
1.25

0.85

1.0
0.81

1.00
1.07
1.23

1.31
1.11

A - Agriculture
B - Mining
C - Manufacture
10 - Food
11 - Beverages
12 - Tobacco
13 - Textiles
14 - Wearing apparel
15 - Leather
16 - Wood
17 - Paper
18 - Printing
19 - Coke and petroleum products
20 - Chemicals
21 - Pharmaceutical
22 - Rubber
23 - Non-metallic mineral
24 - Basic metals
25 - Fabricated metal
26 - Computer
27 - Electrical equipment
28 - Machinery
29 - Motor vehicles and trailers
30 - Transport
31 - Furniture
32 - Other manufacturing
33 - Repair and installation
D - Electricity, gas
E - Water supply
F - Construction
G - Trade
H - Transportation
I - Accommodation
J - Information
K - Financial
L - Real estate
M - Professional activities
N - Administrative activities
O - Public administration
P - Education
Q - Human health
R - Arts, entertainment
S - Other service

Figure 8: Purchaser-Price PLIs for Industry and Household Demands in 2005
The price competitiveness by industry is discussed in more detail in the next section. In thissection we focus on the aggregate measures of PPP and PLI. Table 4 compares the aggregate
PPPs between our estimates (using the translog index) and the Eurostat-OECD PPPs in 2005. Ourestimate of PPP for GDP is slightly lower than the Eurostat-OECD PPP. 26 Table 4 also presents
the alternative estimate of the PPP for GDP based on the trade margin rates in the 2005
Benchmark IOT in Japan, as a reference. This alternative case gives the estimate of 132.2 yen per
dollar, which is slightly higher than the Eurostat-OECD PPP. Since the Eurostat-OECD PPP
covers the final demands at purchaser’s prices, it may include the impact of the indirect taxes on
the domestic products for final uses. On the other hand, our model estimate is derived fromaggregating the PPPs for industry-GDP at basic prices, excluding the impact of indirect taxes on
products. Since Japan has higher rate of effective indirect taxes compared to the U.S. on average,
it would be reasonable that our PPP for GDP at the production side is lower than the PPP for26
It is understandable that our estimate of the aggregate PPP for household consumption is almost identical to theEurostat-OECD PPP, since we used their PPP data for many products at the elementary level.

27

GDP at the expenditure side in the Eurostat-OECD PPP. Thus we conclude that the alternative
case overestimates the PPP for GDP at production side due to the lower estimates in retailmargins in Japan’s IOT.
There are some differences in the PPP for GFCF (gross fixed capital formation), of which
the PPP for building and construction (B&C) is almost equivalent (115.5 yen and 119.0 yen), but
for machinery and equipment (M&E) our estimate (126.1 yen) is considerably lower than theEurostat-OECD PPP (164.0 yen). However, it may be hard to justify that the Eurostat-OECD PPP
for M&E in GFCF is 15 percent higher than the PPP for household consumption, when
considering our estimate of the price differential between industry and household by product, asshown in Figure 8.
Table 4: Aggregated PPPs in Comparison with Eurostat-OECD PPPs in 2005
GDP
Our estimates

Householdconsumption

PPP
GFCF
B&C

M&E

127.10141.93121.13115.49126.09(Alternative case)132.21142.53122.44115.48128.56

Eurostat-OECD PPPs

129.55142.94136.00119.00164.00Note: The average exchange rate used for 2005 is 110.22 yen per dollar. The alternative case is our estimates using the trade margin
rates in the Japan’s 2005 Benchmark IOT, not our revised estimates.

Figure 9 shows the extrapolated estimates of PPPs for GDP and household consumption up
to 2014, using our benchmark PPP estimates in 2005 and the price indices from the national
accounts in Japan (ESRI, Cabinet Office) and the U.S. (BEA) from 2005 to 2014, compared with
the Eurostat-OECD estimates. The trends of both series are similar, but our estimate of the PPP
for GDP is somewhat lower, reflecting the lower benchmark estimate. However, in the PPP
estimate for household consumption, the order reversed and our estimate is slightly higher thanthe Eurostat-OECD PPP. In 2014, our estimates of PPPs for GDP and household consumption are
99.8 and 114.6 yen per dollar, respectively. The current exchange rate of 119.6 yen as of the endof February 2015 is already well above our PPP aggregates. Both producers and consumers inJapan could benefit the price advantages under the current exchange rate, which has been
depreciated since December 2012 when Abenomics started.
141.93

PPP for GDP
140

1.4

140

142.94

PPP for household consumption
1.4

137.82137.87129.55133.51133.581301.3
127.101.3

126.76129.06

Eurostat-OECD (left axis)

122.51

GDP price in the
U.S.[BEA] (right axis) 1.2

120.30120129.81130124.66121.95116.85124.95Eurostat-OECD (left axis)

120

Our estimates (left axis)
118.691.2

120.84115.50115.44113.83117.71

Our estimates (left axis)

116.10111.63113.95112.47110114.62

1.1

107.45104.63108.68113.22110104.56100112.26

1.1

Household consumption
price in the U.S.[BEA](right axis)

104.09101.71
99.67

99.84

2013

2014

1.0

100

0.9

90

Household consumption
price in the Japan[ESRI](right axis)

1.0

GDP price in theJapan[ESRI] (right axis)
90
2005

2006

2007

2008

2009

2010

2011

2012

0.9
2005

2006

2007

2008

2009

2010

2011

2012

Figure 9: Extended Estimates of Aggregated PPPs until 2014
28

2013

2014

5.2 Industry Price Competitiveness
Figure 12 presents the industry PLI of domestic outputs based on 173 classifications𝑑∗(excluding the net indirect taxes), 𝐏𝐽/𝑈,𝑗, in 2005. There is a large diversity among the broader

industry groups. Most estimates of PLIs classified in Agriculture, forestry and fishery, Mining,and Food and beverage are significantly over 1.0, with only two exceptions of 6.Other non-edible
crops (0.62) and 17.Crude oil and natural gas (0.90). 27 Figure 10 illustrates the relationshipbetween the Japan-US difference in the rate of tariff (the rate in Japan minus the rate in the U.S.)
and the price gaps in domestic outputs (taking the log of PLI of outputs). The dots are plotted forthe industries classified in Agriculture, forestry and fishery, Mining, and Food and beverage andthe circles are used for others. Many of those industries in which the production prices in Japanare much higher than those in the U.S. are protected by the higher rates of tariff.
Japan-US differentials in tariff rates

25%

20%

15%

007 Cattle ranching,dairy cattle and milk
production

027 Other food
manufacturing
022 Bread andconfectionery
019 Dairy products
018 Meat and meatproducts

008 Poultry and egg
production
029 Tea and coffee

10%026 Seasoning anddressing manufacturing

003 Fruits

009 Other animal
production

023 Other processed
agricultural foodproducts

017.1 Crude oil
030 Soft drinks

5%012 Fishing

002 Vegetables andpotatoes
020 Seafood products
016 Coal mining
001 Grain farming
004 Other crop farming

017.1 Natural gas

0%013 Metal ores
005 Sugarcane and sugar
beet farmingln(PLIs of outputs)

-5%
-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

Figure 10: Price Competitiveness and Rate of Tariff and in 2005
The PLIs of outputs in 53 of 92 industries in manufacturing (except food and beverage) are
below 1.0. Especially in the case of the large-scale industries whose production values in both
Japan and the U.S. are over 100 billion dollars, Japan’s output prices are lower in 75.Iron andsteel products (0.72), 107.Motor vehicles (0.69), and 108.Motor vehicle body and parts (0.77),
with a unique exception of 62.Petroleum and coal products (1.12). Figure 11 plots the export
shares of domestic outputs and the price competitiveness in manufacturing. Some industries inJapan, such as 88. Semiconductor machinery, 107.Motor vehicles, and 105.Batteries, being
superior in price competitiveness, succeed in increasing exports. On the other hand, 94.Computer
peripheral equipment 110.Ship building and repairing, and 61.Other chemical products achieved
an export promotion regardless of higher prices of their products.

27
Japan’s production of crude oil and natural gas is very small (only 0.36 percent of that in the U.S.) in 2005. Some of the
products are regionally consumed at low prices.

29

80%

70%

60%

Export share in demestic products

90%

098 Watch, clock, andmeasuring devices

109 Motorcycle andbicycle094 Computer
peripheral equipment

110 Ship building andrepairing

088 Semiconductor
machinery099 Semiconductor andrelated devices

087 Special industrial
machinery

097 Applied electronicequipment

107 Motor vehicles

50%

073 Carbon and graphite
products

093 Electronic computer

40%

061 Other chemical
products

105 Batteries
100 Electron tubes
118 Musical instruments

085 Metal processing
machinery and metalmachine tool30%

103 Electric bulbs

20%

050 Inorganic chemical
products

072 Pottery and ceramic
products
10%013 Metal ores

015 Other non-metaloresln(PLIs of outputs)
0%
-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

Figure 11: Price Competitiveness and Export Share in 2005
In services, Japanese industries are inferior in price competiveness in 36 of 50 industries in
Figure 12, especially in 144.Warehousing and storage (3.34), 159.Motor vehicles rental andleasing (2.25), 128. Electricity (2.00), 129.Gas (1.89), 157.Internet service providers and related
services (1.64), and 146.Postal service (1.44). However there are some service industries, inwhich Japan is much superior in price competitiveness compared to the U.S., like 152.Medical
and health service (0.63) and 153.Veterinary service (0.65), mainly reflecting lower PLI for labor
inputs in Japan relative to the U.S. 28
Table 5 presents the Price Competitiveness Map of Japan in 2005, which describes theoutput price gaps (defined by the log of industry PLIs of outputs excluding net indirect taxes,𝑑∗
𝐏𝐽/𝑈,𝑗) and the contributions by the price gaps in the products for intermediate uses (defined by
𝑝𝑝,𝐼

the nominal share of inputs times the log of purchaser-price PLIs of composite goods, 𝐏𝐽/𝑈,𝑖 ). The

industries are arranged in rows and the products for intermediate uses in columns. The white bars

indicate that the Japanese prices are higher than the corresponding U.S. prices and the gray bars
indicate the opposite cases.
As aforementioned, Japan’s agriculture, food and beverage industries have inferior pricecompetitiveness to their U.S. counterparts. An interesting property that Table 5 illuminates is thatthe intermediate inputs purchased by those industries tend to be also higher than those in the U.S.
Although this is a property emerged from the aggregation process of the 174 products, this may
reflect some inefficiencies down the supply chain, regardless of alternative opportunities topurchase the products with lower prices. In contrast, industries like 29.Motor vehicles and trailers,
24.Basic metals, and 13.Textile industries seem to sustain efficient transactions with their
28

Another source is the TFP gap. Jorgenson, Nomura, and Samuels (2015) indicates that the Medical Care’s TFP levels were
almost the same between Japan and the U.S. in the 1950s and the 1960s. Since the mid-1970s the TFP gap has widened
substantially, mainly due to a steady decline in TFP in the U.S. industry and a stable TFP level in Japan. A gap of more than 50
percent has opened up since the end of 1990s.

30

counterparts to provide intermediate products. In 29.Motor vehicles and trailers industry, thelower costs of the products for intermediate uses improve its price competitiveness by 12.2
percent.
The 10.Food products industry is considerably inferior to the U.S. counterpart, with Japan’s
output price 55.8 percent higher. However, more than half of this inferior competitiveness isoriginated in the higher costs of agricultural products for intermediate uses (by 32.8 percent toincrease the output prices). Decreasing tariffs on agricultural imports may considerably restore
the price competitiveness of 10.Food products industry.
Although the products for intermediate uses by G-Wholesale and retail trade and
D-Electricity are not the main sources of their inferior price competitiveness, higher costs of the
products for intermediate uses of trade, electricity, and other energies in Japan have considerable
and wider impacts on the price competitiveness in all industries. The higher costs of trade (54.3
percent higher) and electricity (2.0 times higher) in Japan contribute to pushing the output prices
in C-Manufacturing sector higher than the U.S. by 2.8 percent and 1.1 percent, respectively. By
these estimates, if the price competitiveness in these sectors could be improved to the U.S. level,
it would foster price competitiveness in C-Manufacturing and I-Accommodation and food service
activities by 3.9 percent and 6.2 percent, respectively.

6

Conclusion
We provided the new benchmark estimates of Japan-US industry-level price differentials forthe year 2005, based on our price model describing the relationships among the different
concepts of price level indices. The volume comparisons among countries are a challenging task,
but it is an indispensable process for evaluating the price competitiveness and the efficiencies incountry’s production system relative to other countries. Compared to the U.S. as the reference
country, our estimates illuminate the industry/product sources and the impacts of the weaknesses
in Japan’s industry competitiveness, highlighting potential areas for policy considerations.
The estimates of the Japan-US price level indices in this paper enable us to illuminate thesources of price competitiveness though the inter-industry transactions. Higher costs of the
products for intermediate uses like trade, electricity, and other energies in Japan haveconsiderable and wider impacts on the price competitiveness in all industries. The higher costs oftrade (54.3 percent higher) and electricity (2.0 times higher) in Japan contribute to pushing theoutput prices in C-Manufacturing sector higher than the U.S. by 2.8 percent and 1.1 percent,respectively. The difference in qualities pf products, especially of retail trade, will be examined
more in our further research.

31

0.0

0.5

1.0

1.5
9.11
2.55
1.86
5.16
4.19

0.62
3.61
1.43
2.50
1.07
1.05
1.10
6.02
1.59
2.75
3.31
0.90
2.45
1.48
2.27
1.87
1.45
3.52
3.17
2.06
1.60
1.56
1.42
1.38
1.78
1.70
0.27
0.77
0.63
1.47
0.80
0.70
0.95
0.84
0.76
0.92
1.07
1.18
0.93
1.03
0.85
0.92
0.88
1.07
2.17
1.17
0.88
1.53
1.43
0.94
0.53
0.79
1.06
0.43
0.36
2.11
1.12
0.76
0.83
1.44
1.46
1.47
0.72
0.72
1.01
1.17
0.39
1.05
1.05
0.72
1.14
1.32
1.24
0.77
0.75
0.99
1.32
1.22
2.02
1.68
1.07
0.79

2.0

2.5

3.0

0.0
001 Grain farming
002 Vegetables and potatoes
003 Fruits
004 Other crop farming
005 Sugarcane and sugar beet farming
006 Other non-edible crops
007 Cattle ranching, dairy cattle and milk…
008 Poultry and egg production
009 Other animal production
010 Agricultural, forestry services
011 Forestry
012 Fishing
013 Metal ores
014 Stone, gravel and ceramic mining and…
015 Other non-metal ores
016 Coal mining
017 Crude oil and natural gas
018 Meat and meat products
019 Dairy products
020 Seafood products
021 Grain milling
022 Bread and confectionery
023 Other processed agricultural food…
024 Sugar
025 Vegetable oil
026 Seasoning and dressing manufacturing
027 Other food manufacturing
028 Liquor
029 Tea and coffee
030 Soft drinks
031 Animal food manufacturing
032 Tobacco
033 Fiber, yarn, and thread mills
034 Textile and fabric mills, fabric dyeing
035 Knit fabric mills
036 Carpet, floor mat, and rug mills
037 Other textile product mills
038 Apparel and apparel accessories
039 Lumber and wooden chips
040 Plywood
041 Other wooden products
042 Furniture, accessories and fixtures
043 Pulp
044 Paper
045 Paper containers
046 Other converted paper products
047 Newspaper publishers
048 Printing
049 Publishers
050 Inorganic chemical products
051 Petrochemical products
052 Organic chemical products
053 Fertilizers
054 Agricultural chemicals
055 Synthetic resin
056 Synthetic fibers
057 Pharmaceutical products
058 Soap, synthetic detergents and surfactant
059 Cosmetics and dentifrices
060 Paints and printing ink
061 Other chemical products
062 Petroleum and coal products
063 Plastic products
064 Rubber products
065 Foot wears
066 Leather and fur products
067 Other leather products
068 Glass and glass products
069 Cement
070 Ready-mixed concrete
071 Cement products and structural clay…
072 Pottery and ceramic products
073 Carbon and graphite products
074 Miscellaneous nonmetallic mineral…
075 Iron and steel products
076 Copper, rolled and drawn copper…
077 Aluminum and rolled aluminum products
078 Communication and energy wires and…
079 Other non-ferrous metals and products
080 Metal products for construction and…
081 Other metal products
082 Engines, turbines and boilers
083 Construction machinery and conveyors
084 Farm machinery and equipment
085 Metal processing machinery and metal…
086 Other general machinery for industrial…
087 Special industrial machinery

0.5

1.0

1.5

0.79
0.69
2.79
0.80
0.76
0.94
2.18
0.64
0.85
0.91
1.16
0.96
1.05
0.88
1.06
2.32
1.16
0.79
0.64
0.69
0.77
0.79
1.38
1.40
0.72
0.71
0.90
1.05
1.18
0.85
0.30
1.42
0.80
0.29
0.95
0.73
1.02
0.69
1.24
1.39
2.00
1.89
1.13
1.24
1.53
1.56
1.25
0.92
1.74
1.73
1.62
1.39
0.90
1.27
1.39
1.00
3.34
1.02
1.44
1.03
0.99
1.12
1.29
0.94
0.63
0.65
1.35
0.76
1.02
1.64
1.02
2.25
0.87
0.82
1.14
1.19
1.07
0.80
1.29
0.97
1.38
0.76
1.32
1.20
1.04
0.97

2.0

2.5

3.0
088 Semiconductor machinery
089 Other general machinery
090 Vending, commercial and office…
091 Audio and video equipment
092 Household electrical appliances
093 Electronic computer
094 Computer peripheral equipment
095 Wired telecommunication machinery
096 Other telecommunication machinery
097 Applied electronic equipment
098 Watch, clock, and measuring devices
099 Semiconductor and related devices
100 Electron tubes
101 Magnetic tape and flexible disk
102 Rotating electric machinery
103 Electric bulbs
104 Other electronic component
105 Batteries
106 Other electric equipment
107 Motor vehicles
108 Motor vehicle body and parts
109 Motorcycle and bicycle
110 Ship building and repairing
111 Railroad rolling stock and repairing
112 Aircraft and repairing
113 Other transportation equipment
114 Photographic and photocopying…
115 Surgical, medical and dental instrument
116 Other precision instruments
117 Toys and sporting goods
118 Musical instruments
119 Audio and video media reproducing
120 Writing instruments and stationary
121 Small personal adornments
122 Ordnance
123 Other miscellaneous manufacturing
124 New residential construction
125 New non-residential construction
126 Building repairing
127 Other construction
128 Electric power generation and distribution
129 Gas distribution
130 Water, sewage and thermal energy supply
131 Waste management
132 Wholesale trade
133 Retail trade
134 Financial service
135 Insurance
136 Real estate
137 Lessors of dwellings (including OOH)
138 Rail transportation
139 Road passenger transportation
140 Road freight transportation
141 Water transportation
142 Air transportation
143 Other transport services
144 Warehousing and storage
145 Travel arrangement services
146 Postal service
147 Telecommunications
148 Broadcasting
149 Government services
150 Educational services
151 Research services
152 Medical and health service
153 Veterinary service
154 Other non-profit organization
155 Advertising and related services
156 Information service
157 Internet service providers and related…
158 Commercial and industrial equipment…
159 Motor vehicles rental and leasing
160 Other rental and leasing
161 Motor vehicle repair
162 Other repairs
163 Building maintenance service
164 Legal, financial, and accounting services
165 Other business services
166 Motion pictures
167 Other amusement and recreation services
168 Drinking and eating place
169 Hotels and other accommodations
170 Barber shops
171 Other personal services
172 Scrap, used and secondhand goods
173 Unclassified, etc.

Figure 12: Industry PLI of Domestic Outputs in 2005
32

.082
.000
.026
.328
.048
-.049
.000
.000
.000
.004
.000
.000
.000
.001
.000
.000
.000
.000
.000
.000
.000
.000
.000
.000
.000
.006
.000
.000
.000
-.001
.000
.000
.017
.000
.000
.000
.000
.000
.000
.002
.002
.002
-.001

.001
-.002
-.016
.008
.001
.000
.000
.000
.008
.000
.000
.000
.000
.001
.000
-.002
-.001
.000
.000
.020
.010
.023
-.130
-.045
-.004
.000
.032
.000
.000
-.009
.001
.002
.014
.000
.000
.000
.000
.000
.001
.001
.001
.005
.000

.041
-.001
.003
.068
.059
.000
-.078
-.076
-.016
-.034
-.003
-.016
.000
.001
.003
-.001
-.002
.000
-.001
-.002
-.002
-.001
-.001
-.001
-.027
-.018
-.001
-.001
-.001
-.004
-.001
-.001
.080
-.003
-.002
.000
-.003
-.004
-.002
.002
.004
-.003
-.003

.006
.025
.011
.008
.008
.003
.014
.008
.008
.011
.029
.006
.006
.021
.006
.014
.019
.019
.010
.006
.014
.007
.006
.010
.007
.005
.010
.025
.032
.003
.010
.012
.012
.005
.002
.002
.004
.001
.007
.008
.007
.019
.008

3
4
5
6
M ineral and M achinery, Other
Electricity
M etalelectronic, manufacturi
products
andngtransport
equipment
.000
-.001
-.024
.000
-.004
.001
.000
.000
.000
.000
.000
.000
.000
-.001
-.003
-.002
-.020
-.121
-.060
-.005
-.018
-.024
-.015
-.016
-.020
-.008
-.011
.000
.000
-.024
.000
.000
-.002
.000
.000
.000
.000
.000
.000
.000
-.001
.000
-.002

7
Other
Energy

.011
.037
.005
.004
.004
.002
.006
.002
.037
.004
.003
.001
.019
.019
.002
.001
.011
.006
.003
.002
.002
.002
.002
.003
.002
.004
.002
.018
.010
.007
.007
.017
.008
.002
.001
.001
.003
.002
.005
.004
.003
.006
.009

.025
.023
.028
.042
.037
.010
.033
.045
.053
.035
.043
.031
.007
.022
.022
.035
.025
.023
.028
.034
.025
.030
.023
.022
.043
.045
.045
.013
.011
.032
.008
.008
.050
.008
.005
.001
.007
.010
.008
.007
.025
.014
.014

8
Wholesaleand retail
trade

.003
.007
.004
.005
.005
.003
.004
.004
.004
.003
.004
.005
.025
.003
.005
.004
.007
.004
.004
.003
.003
.003
.001
.002
.002
.003
.002
.008
.003
.001
.006
.009
.002
.003
.006
.000
.003
.003
.011
.003
.001
.002
.003

.001
.011
.003
.002
.003
.005
.009
.010
.003
.004
.004
.004
.000
.003
.003
.002
.006
.002
.004
.003
.003
.003
.001
.004
.005
.013
.003
.008
.002
.003
.012
.007
.004
.003
.022
.013
.007
.010
.001
.000
.003
.004
.006

9
10
Transportat Financial
ion andandstorageinsurance
activities

Table 5: Price Competitiveness Matrix of Japan in 2005

.014
.004
-.005
-.002
-.008
-.008
-.038
-.023
-.015
.013
.000
-.033
.001
.045
-.001
-.053
.004
.002
-.005
-.008
-.005
-.005
-.010
-.013
-.015
-.011
-.007
.001
.001
-.007
-.001
.000
.000
.000
-.001
.000
.000
.001
.000
.000
-.021
-.002
-.002

Product
12Agriculture Chemicals
andchemicalproducts
Industry
A - Agriculture, forestry and fishing
B - M ining and quarrying
C - M anufacture
10 - Food products
11 - Beverages
12 - Tobacco products
13 - Textiles
14 - Wearing apparel
15 - Leather and related products
16 - Wood and wood products, except furniture
17 - Paper and paper products
18 - Printing and reproduction of recorded media
19 - Coke and refined petroleum products
20 - Chemicals and chemical products
21 - Pharmaceutical products
22 - Rubber and plastics products
23 - Other non-metallic mineral products
24 - Basic metals
25 - Fabricated metal products, except M &E
26 - Computer, electronic and optical products
27 - Electrical equipment
28 - M achinery and equipment n.e.c.
29 - M otor vehicles and trailers
30 - Other transport equipment
31 - Furniture
32 - Other manufacturing
33 - Repair and installation of machinery and equipment
D - Electricity, gas, steam and air conditioning supply
E - Water supply
F - Construction
G - Wholesale and retail trade
H - Transportation and storage
I - Accommodation and food service activities
J - Information and communication
K - Financial and insurance activities
L - Real estate activities
M - Professional, scientific and technical activities
N - Administrative and support service activities
O - Public administration and defence
P - Education
Q - Human health and social work activities
R - Arts, entertainment and recreation
S - Other service activities

11
Real estate
activities

.000
.005
.002
.001
.001
.000
.002
.003
.001
.001
.002
.002
.000
.002
.005
.002
.002
.001
.002
.002
.003
.002
.001
.001
.003
.001
.001
.006
.002
.002
.016
.011
.008
.012
.008
.003
.003
.007
.001
.001
.003
.008
.009

12
Industrial
services

.002
.024
-.003
-.003
-.008
-.021
-.001
-.004
-.003
.003
-.004
-.007
.000
-.006
-.014
-.002
.000
.000
-.001
-.004
-.002
-.002
-.004
-.002
-.005
-.003
-.003
.001
-.004
-.009
-.001
-.005
-.003
-.017
-.012
.000
-.007
-.008
.000
-.001
.000
-.007
-.003

13
Other
services

.001
.007
.002
.002
.002
.002
.002
.002
.003
.002
.003
.005
.001
.003
.004
.003
.003
.001
.003
.003
.003
.002
.001
.001
.002
.003
.002
.002
.003
.002
.003
.003
.004
.009
.004
.000
.006
.003
.002
.001
.005
.005
.007

14
Others

.001
.004
.003
.002
.002
-.001
.002
.002
.001
.001
.002
.001
.001
.004
.004
.002
.022
.003
.003
.002
.003
.002
.001
.003
.002
.002
.002
.015
.017
.005
.003
.005
.008
.007
.004
.010
.002
.003
.010
.005
-.004
.010
.014

Total sum

.188
.144
.039
.464
.148
-.053
-.044
-.028
.083
.045
.083
.000
.060
.118
.036
.003
.076
-.060
-.011
.057
.038
.042
-.122
-.028
-.006
.041
.078
.097
.077
.001
.062
.068
.202
.028
.036
.030
.024
.028
.042
.032
.029
.063
.059

𝑑
ln(𝐏𝐽/𝑈,𝑖 )Outputprice gaps

.868
.468
-.012
.558
.654
-.716
-.344
-.031
.405
-.160
-.053
-.113
.390
.068
-.220
-.251
-.142
-.255
-.094
.014
-.048
.065
-.281
.054
.073
-.381
.080
.704
.191
.069
.457
.205
.202
.052
.132
.553
-.195
.169
.111
.252
-.469
.010
.219

33

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