Global Backward and Forward Multiplier Analysis:
The Case Study of Japanese Automotive Industry

Sutee ANANTSUKSOMSRI 1, 2, Nattapong PATTANAPONG 3, and Nij TONTISIRIN 4

1

Waseda University, Waseda Institute for Advanced Study, 1-6-1 Nishi Waseda, Shinjuku-ku, Tokyo
169-8050, Japan
2

Chulalongkorn University, Faculty of Architecture, Department of Urban and Regional Planning, 254
Phayathai Road, Pathumwan, Bangkok 10330, Thailand
3

Thammasat University, Faculty of Economics, Tha Prachan Campus, 2 Prachan Road, Phranakorn,
Bangkok 10200, Thailand
4

Thammasat University, Faculty of Architecture and Planning. Rangsit Campus, Pathumthani 12121,
Thailand

Abstract
Thailand is one of the major investment destinations of Japanese auto-motive industry. In addition
to the major automobile companies, Japanese inves-tors have also invested in small- and mediumenterprises in automobile parts and components in Thailand. Since the 80’s, the automotive industry
has been a driv-ing force of the Thai economy. Currently, Thailand is one of the world largest automobile producers. In this study, we analyze the Global Input-Output Table. Backward and forward
multiplier analysis is used to conduct inter-industry linkage analysis of Japanese automotive industry.
Unlike a conventional trade statistical analysis, this global input-output table allows for the analysis
of interconnection between economic sectors around the world. From our multiplier analysis,
Japanese automotive industry has high backward linkages domestically. Internationally, its forward
multiplier is among the top five after metal, chemicals & rubber, electrical & optical equipment, andwholesale & retail. In addition, structural path analysis is performed to illustrate the paths of global
value chain of Japanese automotive industry. The analysis reveals the interconnection of automotive
and other industries in Japan, Thailand, and the rest of the world.

Keywords: Automotive Industry, Input-Output, Structural Path Analysis

Introduction
The automotive industry consists of a wide range of activities including design, research anddevelopment, manufacturing, and marketing. These economic activities have taken place worldwide.
In particular, Japanese automotive industry has taken the advantages of global value chain. As we
can observe in a car assembling process, a manufacturer uses intermediate inputs from around theworld. After the 1985 Plaza Accord, Japanese automotive industry has moved their production bases
to many developing countries. These Japanese direct investments in other countries not only benefit
the economies of the countries where factories are located but also the economy of Japan.
However, increasing global interdependence of automotive producers may cause disruption in
production if a producer of intermediate inputs in one country halts its production due to somedifficulties from an economic crisis or disaster. In 2011, for example, the global supply chain of
automotive industry faced difficulty from the impacts of Tsunami in Japan and flood in Thailand,emphasizing the vulnerability of the global value chain.
Thailand is one of the major investment destinations of Japanese automotive industry. It is
the largest automobile producer in Southeast Asia and one of the largest producers in the World.
Japan is the largest investor in Thailand in terms of amount of investment and number of projects. In
addition to the major automobile companies such as Toyota, Honda, Nissan, Mazda, and Isuzu,
Japanese investors has also invested in small- and medium-enterprises in automobile parts andcomponents in Thailand. The automotive industry is a driving force of the Thai economy. It ranks thefifth largest export industry and accounts for ten percent of the GDP of the country, employs morethan 500,000 direct skilled-labor jobs, and creates spillover effects to other industries in theeconomy.
In this study, we analyze the Global Input-Output Table, which is publicly available on theWorld Input-Output Database (WIOD). In addition, we introduce the methodology of extending the
WIOD table to cover additional data of Thailand based on sectoral distribution data from Global
Trade Analysis Project (GTAP). Backward and forward multiplier analysis is used to conduct interindustry linkage analysis of Japanese automotive industry. Unlike a conventional trade statisticalanalysis, this global input-output table allows for the analysis of interconnection between economic
sectors around the world. From our multiplier analysis, Japanese automotive industry has higher
backward linkages domestically. Internationally, its forward multiplier is among the top five after
metal, chemicals & rubber, electrical & optical equipment, and wholesale & retail. In addition,
structural path analysis is performed to illustrate the influence of global value chain of Japanese
automotive industry. The analysis reveals the strong interconnection of automotive industry andother industries in Japan, Thailand, and the rest of the world.

Global Value Chain and World Input-Output Databases
This increasing interdependence of different economic sectors across the globe hasdeveloped a need for more comprehensive databases that can be used to analyze suchphenomenon. Global Trade Analysis Project (GTAP) was founded in the early 90’s as a network forresearchers interested in global analysis issues. GTAP serves as a framework for multilateral trade
analysis and provides data, models, and resources. Nonetheless, GTAP database is still needed to be
adjusted to reflect more accurate trade balance. To analyze value-added from international supply
chain, Ahmad et al. (2011), Daudin et al. (2009), Johnson and Noguera (2012), and Koopman et al.
(2008 and 2011) used the GTAP database and found the values of trade balance have to be adjusted

to reflect the volume of international shipment of intermediate goods. In Koopman et al. (2011),
when adjusted, the US’s trade deficit to China may decrease about 30-40%.
The notion of accounting for international supply chain has established a collaboration tocreate a global input-output database. Based on the data structure concept and applications of
Leontief and Strount (1963) and Sanyal and Jones (1982), the World Input-Output Database (WIOD)
was constructed by Dietzenbacher et al. (2013). The WIOD is a result of the compilation of 19952011 annual statistics of international trade and production structure of 35 sectors and 40
economies. The development of WIOD tables leads to the widespread application, especially for a
deeper and broader insight of global production network. These WIOD tables are also main data
sources for Timmer et al. (2013) and Ottaviano (2014) to study impacts of the global production
network on European economy. However, there is a limitation on a specific country’s application
due to the limited number of economies covered in the original data set. Therefore, this study
introduces the methodology of extending the WIOD table to cover additional data of a specificeconomy. The method is described in the following section.

Methodology
World Input-Output Database Tables
World Input-Output Database (WIOD) serves as an important data system for analyzing the
global value chain of Japanese Automotive industry in this study. The WIOD contains sectoraltransactions of 35 sectors in 40 major economies from 1995 to 2011. Since Thailand is not a country
on the list of WIOD table, it is necessary to modify WIOD table so that it explicitly shows the tradeand production statistics of Thailand. There are two major steps involved in this modification
procedure. First, the dimension of WIOD table must be adjusted so that it is compatible with thoseof GTAP’s global trade data because GTAP data is the main source of Thailand trade and production
data. The second step involves consolidating two sources of data from WIOD and GTAP to formulate
a modified WIOD table. In this study, 2007 data are used because it is the latest matching year forboth WIOD table and GTAP’s data (Puttanapong, 2015). The consolidation of the WIOD table and
GTAP’s data yields the global input-output table explicitly with Thailand economy.

Structural Path Analysis
Structural Path Analysis (SPA) can be employed as an extension of the input-output analysis
to identify and measuring flows in economy (Defourny and Thorbecke, 1984). SPA decomposes the
input-output multipliers and identifies a network of paths that are transmitted in the economic
system. We calculated the multiplier effects of World Input-Output Tables using the MATLAB code,originally developed by Cornell University Center for Advanced Computing (CAC).

Results
Japan Backward and Forward Multipliers
Backward and forward multipliers of Japanese sectors are calculated to show the linkages toboth domestic and international industries. Figure 1 shows domestic backward and forward linkagesof production sectors in Japan. Transport Equipment sector is used as a proxy to the automotive
industry. Among the 26 sectors, the automotive industry has the highest domestic backward
multiplier, suggesting a strong interconnection of the automotive industry and its local suppliers. As
expected, Wholesale, Retail, Hotel, & Restaurant sector has the highest forward multiplier. Although
the forward multiplier of the automotive industry is not the highest domestically, it is among the top
ten industries that have strong domestic linkages. Internationally, Japan automotive industry is
among the highest forward multipliers industries. As shown in Figure 2, the forward multiplier ofJapan automotive industry is the fifth highest, following Metal, Chemical & Rubber, Electrical &Optical Equipment, and Wholesale, Retail, Hotel, & Restaurant sectors, respectively. The highforward multiplier of automotive industry suggests the strong interconnection of Japan automotive
industry to its customers around the world.

Figure 1: Japan Domestic backward and forward multipliers

Figure 2: Japan International backward and forward multipliersThailand Backward and Forward Multipliers
Thailand domestic backward and forward multipliers are shown in Figure 3. The sectors in
Thailand with the highest domestic backward multiplier are: (1) Inland Transport, (2) Food,
Beverage, & Tobacco, (3) Air Transport, (4) Textiles, and (5) Water Transport, respectively. Unlike
Japan, the automotive industry in Thailand does not have a strong backward linkage locally. On theother hand, the sectors in Thailand with the highest domestic forward multiplier illustrate the
manufacturing-based nature of Thailand economy. These sectors with the highest domestic forward
multiplier are (1) Coke, Refined Petroleum & Nuclear Fuel, (2) Wholesale, Retail, Hotel, &Restaurant, (3) Mining, (4) Electricity, Gas, & Water Supply, and (5) Chemical & Rubber, most ofwhich are intermediate inputs for production. Overall, automotive industry in Thailand has amoderate forward and backward linkage locally.
Thailand international multipliers, however, are different from its domestic multipliers.
Figure 4 shows international backward and forward multipliers of Thailand sectors. Internationally,
backward multipliers of sectors in Thailand are significantly higher than forward multipliers. Thesehigh backward multipliers suggest that Thailand industries are strongly linked to the global supply
chain through their international suppliers. The sectors with the highest backward multipliers are:(1) Machinery, (2) Automotive industry (Transport Equipment), (3) Construction, (4) Metal, and (5)Electrical & Optical Equipment, respectively. The multipliers also show that Thailand industries relyon their international suppliers much more than Japan industries.

Figure 3: Thailand domestic backward and forward multipliers.

Figure 4: Thailand international backward and forward multipliers.

Structural Path Analysis
The Top 100 Highest Influence Values
To analyze the global influence of Japan industries, multipliers of all sectors from eight
economies are decomposed and ranked. Among the 100 highest influence paths, 77 paths are
originated in Japan, while the remainder is from other seven economies. The sum of total influence
from Japan is 0.78, which accounted for 90 percent of the sum of total influences of these highest
100 paths. The results suggest the dominance of Japan industries and its interconnectedness to theglobal economies.

The Top 200 Highest Influence Values
Out of the top 200, 145 paths have originated in Japan, while the other 55 are originatedelsewhere. Japan sectors are among the top that is the source of most of the highest influences to
the global economy. In comparison to 145 paths from Japan, 11 paths are from China, 9 from
European economies, and 11 from the United States. Out of these 145 paths, Basic Metals andFabricated Metal is the sector with the highest value of influences with 33 paths, followed by 24
paths from Chemical & Rubber sector, 18 paths from Wholesale, Retail, Hotel, & Restaurant, and 18
paths from Electrical and Optical Equipment. Automotive industry is ranked the ninth in Japan andhas originated 6 paths with the influence value of 0.021. As for Thailand, there are two sectors thathave high influence from Thailand: transport equipment and Electrical & Optical Equipment sectors.

Conclusions
The change of production process has made economies throughout the world increasinglyinterconnected. A country specializes in a particular stage of the production of goods and becomes apart of international supply chain. International trade is no longer for raw materials or final goods
but for intermediate inputs for a production of goods. As a result, economies throughout the world
become highly interlinked through this network of international supply chain.
Japanese automotive industry is among the industries that take advantage of this global
value chain since the automotive industry involves many production processes, from design,
manufacturing, to marketing. A car, for example, may be designed in Japan, while the car assemblingprocess may take place in a plant in Thailand using the intermediate inputs from around the world.
This study examines the global backward and forward multiplier of industries in Japan and Thailand,
focusing on the automotive industry, as well as global influences of production sectors from 8
economies. It employs input-output multiplier analysis and structural path analysis as an analyticalframework. The analysis utilizes the World Input-Output Database (WIOD) table as a data systemwith some modifications to incorporate Thailand data in the table. Inland transport sector is used asa proxy for automotive industry.
The results of input-output multiplier analysis show that domestically Japan automotive
industry has a very strong backward linkage to other local industries. Internationally, Japan
automotive industry is among the top sectors with high forward influence. Thailand automotive
industry does not have as strong domestic linkage as Japan. However, Thailand automotive industry
is the second highest backward linkage to international economies. The results of the structural pathanalysis reveal that Japan is the leader in generating economic impacts both locally and globally.
Japan industries contribute to 77 out of 100 highest influence paths and 145 out of 200 highest
influence paths in the world. Japan automotive industry originates 1 dominant impact in the top 100
and 6 paths in the top 200.
The extensions of this analysis include disaggregating automotive industry from inlandtransport sector and building a global CGE model to examine the interconnection of the automotive
industry to other economies in the world.