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Section 4
Analysis of the Tourism Industry Using the Tourism
Satellite Account and Input-Output Tables
SHIMODA, Mitsuru; INADA, Yoshihisa; SHIMOYAMA, Akira;and TAKABAYASHI, Kikuo

1. Objective and Positioning of this Section
In this section, we will shed light on an analysis of the influence of tourism industry in the Japanese economy and the Kansai economy using input-output analysis methods. A feature of the input-output table is that it allows the influenceof the industry in question and that of other industries to be compared. We willtake advantage of this feature to conduct a comparative analysis of the positioning and influence of the tourism industry in the national economy.
In the second subsection, we will outline the tourism industry in Japan
based on the Tourism Satellite Account. We will also process the 2017 Extended
Input-Output Tables for the purpose of analyzing the tourism industry to demonstrate the positioning of the tourism industry in the national economy in termsof employment, income, and influence on other industries.
Tourism is an important industry for Kansai, not only in the current situation in which it has been hit hard by the COVID-19 pandemic, but also for the
future. Thus, in the third subsection, we used the input-output tables for the
10 Kansai prefectures to compare the characteristics of the tourism industry
in each Kansai prefecture. Specifically, we focused on the five main industries
that constitute the tourism industry and analyzed the characteristics of eachprefecture.
In addition to the analysis of sustainable strategies for the tourism industry
in Kansai up to the previous section, the input-output analysis described in thissection and the following section should help to deepen the understanding of
the tourism industry even more.

2. Overview of the TSA and Outline of the Tourism Industry
Tourism is a broad industry, but there is no sector named “tourism” in the Japan
Standard Industrial Classification. The Tourism Satellite Account (TSA) is an
estimate used as a framework for quantitatively capturing tourism through a
unified method. The TSA is one of the satellite accounts of the System of National Accounts (SNA), and the World Tourism Organization (UNWTO) describedSection 4 / Analysis of the Tourism Industry Using the Tourism Satellite Account and Input-Output Tables

253

Part Ⅱ
Part ⅢPart Ⅳ(1) Overview of the TSA
In Japan, the latest version of TSA available as of June 2021 was for 2018. We
will outline the trends in the tourism industry based on the figures listed there.
(1.3) at the top of Table 4-4-1 is domestic tourism expenditure by foreigners visiting Japan, (2.9) is domestic tourism expenditure by Japanese citizens,(4.2) is imputed rent from vacation homes, and (4.3) is the total of the three left
columns, which the TSA refers to as internal tourism consumption. (6.15) isdomestic supply under the SNA and the percentages of internal tourism consumption in this are listed as the tourism ratios in (6.16).
Next, looking at the table, “A. Consumption products” is divided into “A.1.
Tourism characteristic products” and “A.2. Other consumption products.”“Tourism characteristic products” are major products (mainly services) used
for an international comparison of tourism expenditure. “Other consumption
products” consist of “tourism connected products” and “non-tourism related
consumption products.” “Tourism connected products” consist mainly of goods
such as souvenirs and the few services that exist are exhibition/convention participation fees, hot spring/hot bath facilities, etc. “Non-tourism related consumption products” are entirely services and consist of cleaning, hairdressing/beauty
industry, etc. Internal tourism consumption in 2018 was JPY 27,431 billion, of
which, consumption by foreigners visiting Japan was JPY 5 trillion, accountingfor 18% and consumption by Japanese citizens was JPY 21,985 billion, accounting
for 80%.
Looking first at consumption by foreigners visiting Japan (inbound tourism
expenditure), “Tourism characteristic products” were JPY 3,388 billion, while“Other consumption products” were JPY 1,585 billion. The former accounted for
67.8% and the latter 31.7% of the total inbound tourism expenditure.
“Tourism characteristic products” consist mainly of service expenditures,with expenditure high in “Accommodation services for visitors” and “Food- andbeverage-serving services,” accounting for JPY 1,391 billion and JPY 1,025 billion respectively. The next highest expenditure was in “Air passenger transport
services” at JPY 368 billion and “Railway passenger transport services” at JPY
349 billion, followed by “Road passenger transport services” at JPY 72 billion,“Sports and recreational services” at JPY 61 billion, “Transport equipment rent-Part Ⅰ

the international standard in the TSA Recommended Methodological Framework 2008 (TSA: RMF08). In this subsection, we will outline the tourism industry in Japan and conduct a unique tourism industry analysis by processing the
Ministry of Economy, Trade and Industry’s 2017 Extended Input-Output Tables(hereinafter referred to as the “Extended Tables”) based on the TSA.

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Table 4-4-1

Internal tourism consumption by products and tourism ratios(Billion \)Products

Inboundtourism
expenditure

Domestic
tourism
expenditure

Other
components
of tourism
consumption

(1.3)

(2.9)

(4.2)

A. Consumption productsInternal
tourism consumption

Domestic
supply (atpurchasers
prices)Tourism
ratios (%)(4.3)(6.15)(6.16) =(4.3) /(6.15) x 100

4,973

21,985446

27,404

1,061,119

2.6

A.1. Tourism characteristic
products

3,388

13,387446

17,22060,384

28.5

1. Accommodation services for visitors

1,391

3,748

446

5,585

6,147

90.9

1,391

3,748

X

5,139

5,701

90.1

X

X

446

446

446

100.0

1,025

2,694

X

3,720

26,75813.9

3. Railway passenger transport services

349

2,448

X

2,796

5,460

51.2

4. Road passenger transport services

72

611

X

683

3,363

20.3

5. Water passenger transport services

3

109

X

112

131

85.6

6. Air passenger transport
services

368

2,159

X

2,527

3,304

76.5

7. Transport equipment
rental services

56

306

X

363

1,956

18.5

8. Travel agencies and other reservation services

23

349

X

372

2,309

16.1

9. Cultural services

40

336

X

376

6,057

6.2

10. Sports and recreational
services

61

625

X

686

4,900

14.0

A.2. Other consumption
products

1,585

8,599

X

10,1841,000,735

1.0

1. tourism connected
products

1,554

7,777

X

9,331

275,079

3.4

1.a. Accommodation
services for visitors
other than 1.b
1.b. Vacation homeownership (imputed)
2. Food- and beverageserving services

1.a. goods

1,530

6,362

X

7,892

197,587

4.0

1.b. services

24

1,415

X

1,439

77,492

1.9

31

821

X

853

725,655

0.1

2. non-tourism related
consumption products
2.a. goods

X

X

X

X

270,883

0.0

2.b. service

31

821

X

853

454,772

0.2

27

X

X

27

1,570

1.7

27

X

X

27

1,570

1.7

5,000

21,985446

27,431

1,062,689

2.6

B. N
 on-consumption products
B.1. Valuable
Total
Source: the Japan Tourism Agency (2020)

Table 4-4-2

Tourism GDP and Tourism GDP/ GDP(Billion \)
2014

2016

2018

Tourism GDP

8,631

10,585

10,712

Tourism GDP/ GDP

1.7%

2.0%

2.0%

Source: the Japan Tourism Agency (2020)(2) Outline of the Tourism Industry
The Japan Tourism Agency (2018) estimated the economic ripple effect of tour-

Part Ⅱ
Part Ⅲ

al services” at JPY 56 billion, and “Cultural services” at JPY 40 billion.
In “Other consumption products,” “tourism connected products,” which aremainly souvenirs, was JPY 1,554 billion. Next, for consumption by Japanese citizens (Domestic tourism expenditure), “Tourism characteristic products” wasJPY 13,387 billion while “Other consumption products” was JPY 8,599 billion.
The former accounted for 60.9% and the latter 39.1% of the total domestic tourism expenditure.
The breakdown of “Tourism characteristic products” shows “Accommodation services for visitors” was high at JPY 3,748 billion, and then “Food- and beverage-serving services” at JPY 2,694 billion, “Railway passenger transport services” at JPY 2,448 billion, and “Air passenger transport services” at JPY 2,159
billion more or less the same. Among “Other consumption products,” “tourism
connected products” was JPY 7,777 billion, of which, “goods” had a large shareat JPY 6,362 billion. Looking at the “Tourism ratios,” it was 2.6% for the total for“Consumption products,” 28.5% for “Tourism characteristic products,” and 4.0%
for “goods” in “tourism connected products.” While the tourism ratio was 90.1%
for “Accommodation services for visitors” where the weight of “Internal tourism
consumption” is high, it remained at 13.9% in “Food- and beverage-serving services” where the weight is also high. “Water passenger transport services” and“Air passenger transport services” were high at 85.6% and 76.5% respectively,
while “Railway passenger transport services” was 51.2%.
Additionally, changes in tourism GDP based on the TSA are shown in Table
4-4-2. Tourism GDP is defined as “the gross value added of goods and services(tourism supply) provided to tourists.” It trended in the range of JPY 11 trillion
in the late 2010s, accounting for around 2% of GDP.

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Chapter 4 / Inbound Tourism in Kansai: A FY 2020 Retrospective and Outlook

ism based on the 2015 Input-Output Tables1). However, in this analysis, the relative size of the economic ripple effect of tourism as a single industry was not
identified. Thus, in this subsection, we separate the goods and services related
to tourism (tourism sector) and those not related to tourism (non-tourism sector) from the 2017 Extended Tables to identify the characteristics of the economic ripple effect of the tourism industry2).
1) Inducement Coefficient for Production, etc., Caused by Tourism
Goods and Services
To compare the tourism industry with other industries, we separated tourism
goods and services from the 2017 Extended Tables and compiled them as major
aggregated classifications (37 sectors). However, three types of compilations
were made for tourism goods and services, as shown in Table 4-4-3. Compilation type 1 has 10 sectors in the tourism sector and consists of a total of 47
sectors together with the non-tourism sectors. Compilation type 2 has 3 tourism
sectors and has a total of 40 sectors, while compilation type 3 consists of 38
sectors.
Below, we will obtain the Production inducement coefficients, gross value
Table 4-4-3

Pattern of tourism goods and services

Type 1
Tourism: Beverages and Foods
Tourism: Non-Beverages and Foods

Type 2Type 3

Tourism: Goods

Tourism: Transport (passengers)
Tourism: Accommodation
Tourism: Restaurant
Tourism: Sports Facilities

Tourism: Service

Tourism

Tourism: Information Service
Tourism: Car rental
Tourism: Trade margins
Tourism: Fare

Tourism: Fare and margins

Source: Compiled by the author.

1) It is estimated that the internal tourism consumption of JPY 27.4 trillion in 2018 led to an
induced production value of JPY 36.9 trillion, gross value added of JPY 18.7 trillion, andemployment of 3.145 million people. All are the total of the direct effect and the primary
indirect effect.
2) Refer to Shimoda, Inada, and Takabayashi (2021) for the specific method of dividing the
tourism sectors from the non-tourism sectors.

3) “Production inducement coefficient” commonly used in input-output analysis refers to themultiplying factor of the production value induced by a final demand item and represents
the size of production induced by one unit of demand for the final demand item. Conversely,
the “inducement coefficient for production” in this subsection is defined as the column sumof the Leontief inverse matrix. Note that this represents the size of production induced by
one unit of demand for goods and services in the column, which is a different definition
from that of “production inducement coefficient.”

Part Ⅱ
Part Ⅲ

added, and employment by compilation type. In this subsection, the inducement
coefficient caused by an industry is defined as the inducement of production,
gross value added, and employment in the overall economy when final demand
for the relevant industry increases by one unit3). Table 4-4-4 shows the inducement coefficients calculated based on compilation type 1 (47 sectors) withthe tourism sector being shaded. Those high in production inducement (leftcolumn) are the manufacturing industries, such as Transportation equipment(2.45), Iron and steel (2.43), and Pulp, paper and wooden products (1.98). Conversely, the production inducement of tourism sectors is not that high. The highest is Restaurant (1.91) ranked in 8th place, followed by Beverages and Foods(1.82) in 15th, Non-Beverages and Foods (1.77) in 19th, Accommodation (1.73)
in 23rd, and Information Service (1.70) in 24th. Other tourism sectors, such as
Transport (passengers) and Trade margins, ranked 30th or lower.
Meanwhile, in terms of gross value added inducement (center column), theranks change completely, with tourism sectors that ranked low in production
inducement moving to the higher ranks. For example, Car rental, which was
highest in value added inducement, ranked 41st in production inducement but
ranked 2nd in gross value added inducement (41st to 2nd, same hereinafter).
Other tourism sectors that moved up the ranks include Sports Facilities (43rd to4th), Trade margins (38th to 7th), Fare (42nd to 8th), Information Service (24thto 15th), Transport (passengers) (30th to 18th), and Accommodation (23rd to20th). Conversely, Restaurant, which was relatively high in production inducement, lowered its rank (8th to 23rd). In general, since the service industry has
a high value added ratio, its value added inducement tends to be relatively highcompared to production inducement.
The inducement of employment (right column) by the tourism sector showsa trend similar to the inducement of value added, ranking relatively higher than
the inducement of production. However, there are individual differences. First,
Restaurant, which was 23rd in value added inducement, rose to 2nd in employment inducement. The same applies to Accommodation, which was 20th in value
added inducement and 7th in employment inducement.
Next, below are the inducement coefficients based on compilation type 2.

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Chapter 4 / Inbound Tourism in Kansai: A FY 2020 Retrospective and Outlook

Table 4-4-4

Production Inducement coefficients, gross value added, and employment based on compilation type 1 (47 sectors)

Industry
1 Transportation equipment
2 Iron and steel
3 Pulp, paper and wooden products
4 Beverages and Foods
5 Metal products
6 Plastic products and rubber products
7 General-purpose machinery
8 Tourism: Restaurant
9 Chemical products
10 Electrical machinery
11 Information and communication electronics equipment
12 Production machinery
13 Electronic components
14 Water supply
15 Tourism: Beverages and Foods
16 Business oriented machinery
17 Construction
18 Miscellaneous manufacturing products
19 Tourism: Non-Beverages and Foods
20 Information and communications
21 Agriculture, forestry and fishery
22 Non-ferrous metals
23 Tourism: Accommodation
24 Tourism: Information Service
25 Personal services
26 Mining
27 Public administration
28 Ceramic, stone and clay products
29 Textile products
30 Tourism: Transport (passengers)
31 Business services
32 Membership-based associations, n.e.c.
33 Medical, health care and welfare
34 Transport and postal services
35 Electricity, gas and heat supply
36 Waste management service
37 Finance and insurance
38 Tourism: Trade margins
39 Education and research
40 Commerce
41 Tourism: Car rental
42 Tourism: Fare
43 Tourism: Sports Facilities
44 Real estate
45 Petroleum and coal products

Production

Industry

GVA

2.45
2.43
1.98
1.95
1.95
1.93
1.92
1.91
1.91
1.90
1.87
1.85
1.85
1.82
1.82
1.80
1.79
1.77
1.77
1.76
1.75
1.74
1.73
1.70
1.69
1.67
1.66
1.65
1.64
1.59
1.58
1.56
1.53
1.52
1.51
1.50
1.49
1.47
1.45
1.44
1.37
1.37
1.36
1.23
1.17

Real estate
Tourism: Car rental
Finance and insurance
Tourism: Sports Facilities
Commerce
Education and researchTourism: Trade margins
Tourism: Fare
Information and communications
Business services
Waste management service
Transport and postal services
Public administration
Membership-based associations, n.e.c.
Tourism: Information Service
Water supply
Medical, health care and welfare
Tourism: Transport (passengers)
Personal services
Tourism: Accommodation
Construction
MiningTourism: Restaurant
Miscellaneous manufacturing products
Tourism: Beverages and Foods
Agriculture, forestry and fishery
Production machinery
Metal products
General-purpose machinery
Beverages and Foods
Ceramic, stone and clay products
Pulp, paper and wooden products
Plastic products and rubber products
Tourism: Non-Beverages and Foods
Business oriented machinery
Electrical machineryTransportation equipment
Electronic components
Iron and steel
Chemical products
Textile products
Information and communication electronics equipment
Electricity, gas and heat supply
Non-ferrous metals
Petroleum and coal products

0.98
0.97
0.96
0.95
0.95
0.95
0.95
0.94
0.93
0.93
0.93
0.92
0.92
0.92
0.91
0.91
0.91
0.91
0.90
0.90
0.88
0.87
0.87
0.87
0.87
0.86
0.86
0.85
0.84
0.84
0.82
0.82
0.81
0.80
0.80
0.77
0.77
0.76
0.75
0.75
0.74
0.74
0.64
0.55
0.42

Employment
Agriculture, forestry and fishery
0.38
Tourism: Restaurant
0.25
Personal services
0.21
Textile products
0.17
Membership-based associations, n.e.c.
0.17
Tourism: Sports Facilities
0.16
Tourism: Accommodation
0.15
Beverages and Foods
0.15
Tourism: Beverages and Foods
0.15
Medical, health care and welfare
0.15
Tourism: Trade margins
0.14
Commerce
0.14
Tourism: Fare
0.14
Business services
0.14
Construction
0.13
Miscellaneous manufacturing products
0.13
Waste management service
0.13
Pulp, paper and wooden products
0.11
Metal products
0.11
Education and research
0.11
Tourism: Transport (passengers)
0.10
Tourism: Information Service
0.10
Plastic products and rubber products
0.10
Tourism: Non-Beverages and Foods
0.10
Public administration
0.09
Transport and postal services
0.09
Ceramic, stone and clay products
0.09
Production machinery
0.09
Information and communications
0.08
Finance and insurance
0.08
Mining
0.08
General-purpose machinery
0.08
Business oriented machinery
0.08
Electronic components
0.08Electrical machinery
0.08
Information and communication electronics equipment
0.07
Transportation equipment
0.07
Water supply
0.07
Tourism: Car rental
0.07
Chemical products
0.05
Non-ferrous metals
0.05
Iron and steel
0.04Electricity, gas and heat supply
0.04
Real estate
0.02
Petroleum and coal products
0.01
Industry

Source: Estimated by the author.

The table has been omitted. In production inducement, the rankings were low
for the tourism sector, with Goods (15th), Service (21st), and Fare and margins(34th) ranking in that order. The order was reversed for value added inducement, with Fare and margins (5th), Service (15th), and Goods (24th). Service
ranked at the top in employment inducement, with Services (6th), Fare and margins (7th), and Goods (15th).

Abstract of inducement coefficients based on compilation type 3(38 sectors)

Production

Gross Value Added

Employment

1st Transportation equipment(2.45)

14th Tourism(0.90)

7th Tourism(0.14)

2nd Iron and steel(2.43)

27th Electrical machinery(0.77)

25th Electrical machinery(0.08)

9th Electrical machinery(1.9)
21st Tourism(1.68)

28th Transportation equipment 29th Transportation equipment(0.77)(0.07)
28th Iron and steel(0.75)

33rd Iron and steel(0.02)

Source: Estimated by the author.

In Table 4-4-5, we saw that tourism’s impact on employment is relatively great.
Next, we will sort employment into the employment types of “Self-employedworker and Family worker,” “Regular employee,” and “Non-regular employee”
and calculate the inducement for each. Here, non-regular employee is defined as
the sum of “Non-regular employees/staff” and “Temporary employees” among
the full-time employees in the employment table. Figure 4-4-1 shows the employment ripple effect by employment type, with the average of manufacturing
added in addition to the industries in Table 4-4-54). What is notable for Tourism is that inducement for non-regular employees accounts for 36%, which ishigher than the 22% as the average of manufacturing. In Japan, regular employ4) The average of manufacturing is the simple average of 18 manufacturing sectors.

Part Ⅱ

Table 4-4-5

Part Ⅲ

2) Comparison with Other Industries
Next, we will outline the results for compilation type 3, which consolidates thetourism sector into one (Table 4-4-5). For comparison, we will show the resultsfor Iron and steel, Electrical machinery, and Transportation equipment as well.
For production inducement, the ripple effect was greatest in the order ofTransportation equipment, Iron and steel, Electrical machinery, and Tourism,
but this order was reversed for value added inducement to Tourism, Electricalmachinery, Transportation equipment, and Iron and steel. Looking at the relative sizes, in production inducement, Transportation equipment at the top is
about 1.5 times the size of Tourism at the bottom. Conversely, the difference
was nearly seven-fold for employment inducement. The inducement effect for
employment varied greatly depending on the sector, and we can see that the
impact on employment was particularly strong in the tourism industry.
3) The Impact on Employment

Part Ⅰ

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Part Ⅳ

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260

Chapter 4 / Inbound Tourism in Kansai: A FY 2020 Retrospective and Outlook(Persons/Million¥)
0.16
0.14
0.12

36%

0.10
0.08

24%

0.06
0.04

20%

0.02

73%

0.00

7%
Iron and steel

69%
6%Electricalmachinery

22%
72%

22%
46%
62%

16%
6%
Transportation
Averageequipmentof manufacture

18%
Tourism

Self-employed worker and Family worker
Regular employee

Figure 4-4-1

Non-regular employee

Ripple effect on employment by employment type

Source: Estimated by the author.

ees increased by 330,000 while non-regular employees decreased by 970,000
on average in FY 2020. We can see from here also that the decreased demand
for tourism due to the COVID-19 pandemic had a direct impact on non-regular
employees.
(3) Summary: Characteristics of the Tourism Industry
Thus far, we have outlined the characteristics of the tourism industry nationwide based on TSA. According to the most recent TSA available, tourism consumption in 2018 was JPY 27,431 billion, of which, approximately 20% was consumption by foreigners visiting Japan and 80% by Japanese citizens. Expenditure
on goods was around 30% for both, and the rest was service expenditure, withexpenditure particularly high in the accommodation services and food- andbeverage-serving services. However, the percentage of tourism consumption indomestic supply (tourism ratio) differed, with approximately 90% for accommodation services and 14% for food- and beverage-serving services. Tourism GDP
remained around 2% of the total in the late 2010s.
We also combined the 2017 Extended Tables and the TSA to create an input-output table separating out the tourism sector and measured the relative
size of the economic ripple effect of the tourism industry. The production inducement coefficients of the tourism industry was 21st, ranking low among the
36 sectors (excluding activities not elsewhere classified and office supplies), but
it ranked higher in the inducement coefficient for value added (14th) and theinducement for employment (7th). The tourism industry falls short of manufacturing in terms of the production ripple effect, but it exceeds manufacturing

Section 4 / Analysis of the Tourism Industry Using the Tourism Satellite Account and Input-Output Tables

261

for the ripple effect on value added and employment, particularly employment.
Additionally, in terms of employment, we saw that the impact on non-regular
employment was particularly great, relatively. This suggests that the impact of
COVID-19 pandemic on non-regular employment has been more serious.

Part Ⅱ
Part Ⅲ(1) Characteristics of the Tourism Industry in Each Prefecture
In this subsection we will examine the tourism industry in 10 prefectures in Kansai, but since the consumption trend of domestic tourists is not clearly indicatedby prefecture in the statistics publications, it is difficult to separate sectors associated with tourism in the input-output tables to analyze the tourism industry, as
we did nationally. In general, when analyzing the tourism industry in prefecturesusing input-output tables, the economic ripple effect is often examined by associating existing industry sectors with tourism sectors. The input-output table,
due to its structure, assumes that if there is no difference in quality and thatthe input structure is the same, so the accommodation industry is considered
to conduct similar production regardless of whether its purpose is tourism or
non-tourism. Thus, in this section we will follow the methods of earlier studies
and associate the TSA tourism industry sectors with the industry sectors in the
input-output tables of the 10 prefectures.
First, Table 4-4-6 shows the association between the industrial classification by the TSA, the common industrial classification, and the input-output tableof each prefecture.
The industrial classification by the TSA consists of Accommodation services
for visitors, Vacation home ownership (imputed), Food- and beverage-serving,Part Ⅳ

When considering what’s on the horizon for Kansai, the tourism industry is very
important for it, with the Expo 2025 Osaka, Kansai, Japan to be held in 2025,
among other things. In the previous subsection, we discussed the importanceof the tourism industry based on the input-output tables for Japan. In this subsection, we will use the input-output tables for each prefecture to examine thecharacteristics of the tourism industry in Kansai’s economy.
The main analysis method is as follows. First, we will look at the characteristics in terms of the scale of the tourism industry within Kansai’s economy. Then,we will look at the economic ripple effect of the tourism industry based on the
production/employment inducement coefficients and the diversity of industries
that are affected by the economic ripple effect.

Part Ⅰ

3. The Tourism Industry in Kansai: Analysis Based on the2015 Table for Each Prefecture

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Chapter 4 / Inbound Tourism in Kansai: A FY 2020 Retrospective and Outlook

Table 4-4-6

Tourism
Industry

Tourism industry in TSA and industries in the input-output table

Industrial Classification
by TSA

Industrial Classification
by SNA

Industrial Classification(Input-Output Table, Osaka)

Accommodation services
for visitors

Accommodations

HotelsVacation home ownership(imputed)

Real estate lessors－

Food- and beverageserving services

Eating and drinking
services

Eating and drinking
services

Railway passenger
transport services

Railway passenger
transport

Railway transport

Road passenger transport
services

Road passenger transport

Road freight transport(except self-transport)

Water passenger transport
services

Water transport

Water transport

Air passenger transport
services

Air transport

Air transport

Services relating totransport

Other transport

Services relating totransport

Sports and recreational
services

Services for amusement
and hobbies

Amusement andrecreational services

Other services

Services, N.E.C－

Source: Created by the author.

Railway passenger transport services, Road passenger transport services, Water passenger transport, Air passenger transport services, Services relating totransport, Sports and recreational services, and Other services. These industries are mostly classified as those that produce tourism-specific products andthat cannot exist without tourists or the consumption level drops significantly
without them, and they are believed to play a central role in the tourism industry5). Associations of these industries with the common industrial classifications by the SNA are listed in the center column, and the right column shows
the associations with the industrial classifications by the input-output table6).
Of these industrial classifications, we targeted the five sectors with relatively
high domestic tourism expenditure in Table 4-4-1; namely Hotels, Eating anddrinking services, Amusement and recreational services, Railway transport, andRoad freight transport (except self-transport) (described according to classification in input-output table, hereinafter referred to as the “Five tourism industry
5) To ascertain the situation in the tourism industry in accordance with international standards, standards for tourism-specific products were presented in the World Tourism Organization’s (UNWTO) International Recommendations for Tourism Statistics 2008.
6) For the industrial classifications for Osaka, the medium aggregated classification (107 sectors) from the most recent FY 2015 input-output tables for Osaka were used.

Table 4-4-7

Specialization coefficients by prefecture for the five tourism
industry sectors
Nationwide=1
Shiga Kyoto Osaka Hyogo Nara Wakayama Tottori Tokushima

Fukui

Mie

Railway transport

0.16

0.60

0.59

1.65

1.51

1.05

1.18

0.31

0.28

0.12

Road freight transport(except self-transport)

1.18

0.85

0.77

1.07

1.06

1.41

0.86

0.92

1.14

1.29

Hotels

1.32

1.00

0.72

1.91

0.91

1.19

0.66

1.36

1.94

1.09

Eating and drinking
services

1.15

0.74

0.59

1.37

1.22

1.16

1.12

0.76

1.02

0.44

Amusement and recreational services

0.65

0.75

0.66

0.94

0.98

1.09

0.95

0.67

0.84

2.56

5,959 19,269 12,381 18,002 67,148 38,959

6,194

7,356

3,252

5,076

GRP (Billion\)

Source: Estimated by the author.

7) Since Air transport is normally a means to travel to a destination and is generally expected
to be excluded from consumption by tourists visiting Kansai, it is not analyzed.
8) Specialization coefficient describes how specialized an industry of a prefecture is and compares the ratio of the production value of an industry of a prefecture with the national ratio.
Thus, if it exceeds 1, it indicates that the production value is great in that industry sector
compared to nationally.
9) In many of these prefectures, the impact of hot springs resorts as tourism accommodation
is believed to be significant.

Part Ⅱ
Part Ⅲsectors.”)7).
To compare with nationwide, Table 4-4-7 looks at the specialization coefficients based on the production values of the five tourism industry sectors in
the national input-output table8). Industries and prefectures with a specialization
coefficient value of 1.05 or higher are shaded. Looking at the characteristics byprefecture, even in Kyoto, the specialization coefficient is higher than 1 in four
sectors except for Amusement and recreational services, and it is particularly high in Hotels and Eating and drinking services. In Hyogo, all five sectors
have specialization coefficients higher than 1 but lower than Kyoto in Hotels
and Eating and drinking services. By industry, Railway transport and Eating
and drinking services were high mainly in Osaka and Kyoto. Road freight transport (except self-transport) is higher in areas where automobiles are used morethan railway (rural areas). Hotels were high in Kyoto and Tottori, followed by
Wakayama and Fukui9). Amusement and recreational services was below the national average in all prefectures except in Hyogo and Tokushima. Thus, we cansee that in the tourism industry in the Kansai economy, the weights of Hotels
and Eating and drinking services are higher than nationwide.

Part Ⅰ

263

Part Ⅳ

Section 4 / Analysis of the Tourism Industry Using the Tourism Satellite Account and Input-Output Tables

264

Chapter 4 / Inbound Tourism in Kansai: A FY 2020 Retrospective and Outlook(2) Size of Employment Inducement and Impact on a Wide Range
of Industries
Next, we will examine the characteristics of the economic ripple effect of the
tourism industry from the perspective of production and employment inducement coefficients and which industries are affected by the economic ripple effect.
1) Inducement Coefficient for Production/Employment
As in the previous subsection, we will calculate the inducement coefficients for
production and employment for the five tourism industries by prefecture. The
production inducement coefficient caused by an industry is defined as the inducement on production in the overall economy when final demand for the relevant industry increases by one unit. The results are shown in Table 4-4-8. The
production inducement coefficient and the ranking in the prefecture by industry, and the employment inducement coefficient and the ranking in the prefecture by industry, are listed by industry and by prefecture. Since the medium aggregated classifications are used in the input-output table of the prefectures, thetotal number of sectors is between 103 sectors (Fukui) and 108 sectors (Nara,
Tottori, Tokushima), and the rankings show the relative sizes of the economic
ripple effect in the region. Additionally, the shaded area in the box indicating the
rankings indicates a case that exceeds the rankings of the production-induced
coefficient and the employment-induced coefficient.
First, looking at the characteristics of the production inducement coefficientby industry, the rankings of the prefectures for Hotels and Eating and drinking
services were between 9th (Shiga) and 23rd (Tokushima), and 15th (Kyoto)and 48th (Mie) respectively, indicating that they are industries with a high production inducement. The coefficient values were also 1.3 or higher in Hotels
and Eating and drinking services and approximately 0.1 point higher than Railway transport, Road freight transport (except self-transport), and Amusement
and recreational services. On the other hand, Road freight transport (except
self-transport) was quite low, between 92nd (Fukui) and 100th (Tokushima)10).
Looking at the characteristics by prefecture, Railway transport’s production inducement was relatively high in Fukui, Shiga, Kyoto, and Hyogo, while it wasaround the middle in Mie, Osaka, and Tottori. Additionally, for Eating and drinking services, Mie was 48th, ranking low compared to other prefectures, while for10) Since the medium classifications are used for Road freight transport (except self-transport)
for both the production inducement effect and employment effect, it may have been more
impacted by “road freight” than “road passenger.”265

Section 4 / Analysis of the Tourism Industry Using the Tourism Satellite Account and Input-Output Tables

Table 4-4-8

Production inducement coefficients, employment inducement
coefficient and ranking
Railway transport

Road freight transport (except self-transport)

Fukui

1.313

(32)

0.183

(11)

1.179

(92)

0.113

(32)

Mie

1.213

(68)

0.053

(56)

1.125

(93)

0.124

(18)

Shiga

1.291

(23)

0.046

(62)

1.141

(97)

0.160

(15)

Kyoto

1.305

(23)

0.042

(82)

1.145

(97)

0.163

(19)

Osaka

1.248

(65)

0.042

(76)

1.179

(96)

0.150

(9)

Hyogo

1.282

(39)

0.038

(79)

1.154

(96)

0.123

(17)

Nara

1.220

(54)

0.064

(60)

1.130

(94)

0.155

(20)

Wakayama

1.264

(52)

0.111

(28)

1.182

(83)

0.141

(16)

Tottori

1.272

(65)

0.080

(62)

1.158

(96)

0.139

(28)

Tokushima

1.229

(57)

0.122

(31)

1.108

(100)

0.105

(45)

HotelsPart Ⅰ

Production (Rank) Employment (Rank) Production (Rank) Employment (Rank)

Eating and drinking services

(11)

0.190

(8)

1.349

(24)

0.169

1.335

(22)

0.110

(20)

1.262

(48)

0.169

(14)
(9)

Shiga

1.389

(9)

0.159

(16)

1.320

(17)

0.181

(11)

Kyoto

1.403

(11)

0.140

(27)

1.370

(15)

0.405

(4)

Osaka

1.387

(21)

0.111

(24)

1.367

(23)

0.164

(7)

Hyogo

1.362

(16)

0.110

(22)

1.336

(24)

0.192

(4)

Nara

1.320

(13)

0.300

(4)

1.258

(30)

0.248

(5)

Wakayama

1.428

(19)

0.168

(7)

1.348

(26)

0.228

(5)

Tottori

1.413

(20)

0.206

(10)

1.376

(25)

0.228

(8)

Tokushima

1.314

(23)

0.161

(18)

1.286

(29)

0.270

(4)

Amusement and recreational services
Production (Rank) Employment (Rank)
Fukui

1.303

(36)

0.128

(25)

Mie

1.144

(88)

0.123

(19)

Shiga

1.210

(62)

0.128

(21)

Kyoto

1.239

(51)

0.126

(31)

Osaka

1.229

(73)

0.105

(26)

Hyogo

1.201

(86)

0.092

(30)

Nara

1.203

(66)

0.156

(19)

Wakayama

1.229

(66)

0.126

(20)

Tottori

1.274

(64)

0.125

(34)

Tokushima

1.211

(71)

0.106

(43)

Source: Estimated by the author.

Amusement and recreational services, Fukui ranked high at 36th.

Part Ⅲ

1.493

Mie

Part Ⅳ

Fukui

Part Ⅱ

Production (Rank) Employment (Rank) Production (Rank) Employment (Rank)

266

Chapter 4 / Inbound Tourism in Kansai: A FY 2020 Retrospective and Outlook

Next, in terms of the employment inducement coefficient, Kyoto, Hyogo, and Tokushima were 4th for Eating and drinking services and the lowest
rank was Fukui’s at 14th, which indicates that it is an industry with a relatively
high employment effect. Additionally, Hotels was between 4th (Nara) and 27th
(Kyoto), with results similar to Eating and drinking services. Amusement andrecreational services was slightly lower than Eating and drinking services andHotels, but it was generally around the 20th to 40th range, indicating that theemployment effect is relatively high. Meanwhile, the employment effect variedin Railway transport and Road freight transport (except self-transport). The former ranked quite high at 11th in Fukui, but Osaka (76th), Hyogo (79th), andKyoto (82nd) show that the regional gap is large. The latter was generally highexcept for Fukui (32nd) and Tokushima (45th).
Lastly, we look at the differences in rankings between the production inducement coefficient and the employment inducement coefficient. In Hotels, whichranked relatively high for the production inducement coefficient to start with,the rankings for the employment inducement coefficient were slightly lower in
Shiga, Kyoto, and Hyogo but were more or less the same, showing that both its
production inducement effect and employment coefficient are high. Similarly,
in Eating and drinking services where the production inducement coefficientwas high, employment inducement coefficient rankings were even higher in all
prefectures, with results similar to the analysis in the previous section. Fromthese results, we can see that in Hotels and Eating and drinking services inparticular, there is the strong tendency for not only production inducement, butalso employment inducement to be high.
2) Which Industries are Affected by the Economic Ripple Effect?
Lastly, we will look at which industries are affected by the economic ripple effect. A greater economic ripple effect is more desirable, but even if the economic
ripple effect is great, if it only affects certain industries, the effect on the overall
region will be localized. Conversely, if it affects various industries, the effect on
the overall region will be broad. Thus, of the five tourism industries, we will focus on Hotels, which had a high influence coefficient in the previous subsection,and examine its impact on other industries. In so doing, we will compare it withelectrical machinery, which is one of the main industries in Kansai. The values
excluding the production ripple effects to the industry concerned and summarized into nine sectors are represented in Figure 4-4-2.
Hotels was highest in Fukui at 0.493 and lowest in Tokushima at 0.282. The
impact on other industries was relatively great in the three sectors of Electricity,
gas and heat supply, Transport and postal service, and Service, but Agriculture,

Section 4 / Analysis of the Tourism Industry Using the Tourism Satellite Account and Input-Output Tables

267[Hotels]
Agriculture, forestry and ﬁshery
Commerce
Service

Manufacturing
Finance and insurance
OthersElectricity, gas and heat supply
Transport and postal services

Fukui

0.493

Mie

0.335

Shiga

0.346

Kyoto

0.367

Osaka

0.363

Hyogo

0.317

Nara

0.285

Wakayama

0.381

Tottori

0.377

Tokushima

0.282

0.000

0.050

0.100

0.150

0.200

0.250

0.300

0.350

0.400

0.450

0.500

[Electrical machinery]
Manufacturing
Finance and insurance
OthersFukui

Electricity, gas and heat supply
Transport and postal services

0.212

Mie

0.233

Shiga

0.218

Kyoto

0.187

Osaka

0.215

Hyogo

Tottori

0.323

Tokushima

Figure 4-4-2

0.213
0.050

0.100

0.150

0.200

0.250

0.300

0.350

0.400

0.450

0.500

Production inducement destination of Hotels (excluding inducement to own industry)

Source: Estimated by the author.

forestry and fishery, Commerce, and Finance and insurance were also somewhat impacted. On the other hand, in Electrical machinery, which is a key industry in Kansai, the impact on other industries excluding the value for the industry
concerned was small among the prefectures compared to Hotels, with Tottori’s
being the highest at 0.323 and Kyoto’s the lowest at 0.187. Looking at the impact
on other industries, it was mostly in the manufacturing industry and the impact
on other industries was around half.
(4) Summary: Characteristics of the Tourism Industry in the 10 Kansai Prefectures
In this subsection, we looked at the characteristics of the tourism industry in
the Kansai economy using the latest input-output tables for the 10 Kansai prefectures. As a result, we saw that 1) in the tourism industry in the Kansai economy,
the importance of Hotels and Eating and drinking services is high compared tonationwide, 2) it strongly impacts other industries, mainly Hotels, in the region
and can generate earnings from other regions, and therefore is a very important
industry for each region, and 3) the economic ripple effect does not only affectPart Ⅲ

0.192

Part Ⅳ

0.243

Wakayama

Part Ⅱ

0.234

Nara

0.000

Part Ⅰ

Agriculture, forestry and ﬁshery
Commerce
Service268

Chapter 4 / Inbound Tourism in Kansai: A FY 2020 Retrospective and Outlook

certain industries but also affects various industries, and its impact on the overall region is broad. Thus, the importance of the tourism industry in the Kansai
economy has been clarified.
References
Doi, E., Asari, I., and Nakano, C. (2019), “Regional Input-Output Analysis for Beginners: Basics—From Introduction to Practice in Excel (Revised Edition)”(Japanese title: Hajimeyo Chiiki Sangyo Renkan Bunseki: Kisohen—Excel deShoho kara Jissen made [Kaiteiban]), Nippon Hyoron sha, p. 69
Japan Tourism Agency (2020), Research study on economic impacts of tourism
in Japan, Japanese Tourism Satellite Account, 2018, (https://www.mlit.go.
jp/common/001354466.pdf, last viewed: November 19, 2021)
Shimoda, M., Inada, Y., and Takabayashi, K. (2021), “Chapter 6 Section 1 Quantitative Assessment Using the Tourism Satellite Account and the National Input-Output Tables” (Japanese title: Dai 6 Sho 1 Setsu Ryoko/Kanko Satellite
Kanjo to Zenkoku Sangyo Renkan Hyo niyoru Teiryoteki Hyoka), APIR Kansai
and the Asia Pacific, Economic Outlook: 2020-21, Nikkei Printing Inc.