The 5th TICC International Conference 2020
in Multidisciplinary Research Towards a Sustainable Society
November 26th – 27th, 2020, Khon Kaen, Thailand
THE ECONOMIC IMPACT OF GASTRONOMIC TOURISM DURING
THE COVID-19 PANDEMIC IN BALI: THE UBUD FOOD FESTIVAL
Sabrina Yuka Amilia1
Business and Managerial Economics Program1
Faculty of Economics
Chulalongkorn University
Bangkok, 10330, Thailand
Email: sabrinayuka@yahoo.com
Abstract: The main objective of this paper is assessing the economic impact
in Bali during the COVID-19 pandemic by proposing the case of Ubud Food
Festival 2019 with input-output analysis. Due to the outbreak, most of
scheduled festivals in 2020 have been cancelled, including Ubud Food
Festival 2020. Local business and local visitor expenditure surveys were
conducted to examine the direct effect of the festival. To compute the
indirect effect generated by 54 sectors in Bali’s economy, this study
constructs regional output, value-added, and income multipliers. The result
figured that among gastronomic tourism-related sector, Food and beverage
service industry have the largest number on regional output multiplier,
Recreational and sporting activities has the largest number on value-added
multiplier, and Transportation support service industry has the largest
number on income multiplier. Considering the backward linkage and large
multiplier numbers of tourism sector, hence gastronomic tourism could be
the ‘key’ sector to expand Bali’s economic growth. This study provides an
analysis of current tourism industry responses to Bali’s economy during
pandemic and influence regional tourism policy design in the middle of the
crisis.
Keywords: economic impact; gastronomic tourism; input–output model;
Ubud Food Festival; multiplier
1. Introduction
The economic impact analysis is a vast analytic method embracing the most common models
for travel and tourism arrangement. The applications of economic impact study in travel and
tourism determine the effects in income, expenditure, output, or jobs related to tourist
destinations, events, facilities, and policies in a specified geographic area.
As one of the fastest growing sectors by contributing to Indonesian economy, the country
welcomed 16.1 million international tourists in 2019, indicating almost two percent growth from
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The 5th TICC International Conference 2020
in Multidisciplinary Research Towards a Sustainable Society
November 26th – 27th, 2020, Khon Kaen, Thailand
2018. Tourism sector indicates annual growth with the average of 9.33 per cent increase
annually since 2013 to 2019. Tourist expenditure contributes to Indonesian economy, where the
overall impacts relies on the ways in which a certain expenditure is allocated to the different
tourism-related sectors (Blake et al., 2003). In 2019, foreign tourists spent around a fifth of their
total spending of USD 1,183.43 per visit on food and beverage while they visited Indonesia.
Through tourism, people spend their money to travel and seek for new experiences. Gastronomy
is one of the experiences and become one of the most dynamic and creative segments of tourism,
so called gastronomic tourism.
Business in culinary sector has put new perspective to one of the most contributed provinces in
Indonesia GDP through its tourism sector, named Bali Province. A small district in Bali, Ubud,
has turned into Indonesia’s first gastronomic destination endorsed by World Tourism
Organization (UNWTO) due to the expansion of cultural tourism in Bali (Pitanatri, 2016). The
case of Ubud Food Festival (UFF) 2019 was selected to make significant contribution to local
community. The festival which is founded in 2015 as an annual project of a not-for-profit
organization named Yayasan Mudra Swari Saraswati has welcomed more than 15,000 visitors
in 2019. With over than 100 local and international chefs, restaurateurs, farmers, food writers
and culinary stars, the three days of cross-cultural culinary festival highlighted Indonesian food
as the headliner. Over four fifths of the visitors were Indonesian who came from Bali, Jakarta,
Bandung, Yogyakarta, Surabaya, and Papua. The remain visitors were foodies from Australia,
Southeast Asia and beyond. There is an increase in approximately 30 percent visitors annually
since 2015.
However, industry development does not always work smoothly as it will deal with several
challenges in the future, so does tourism industry. Von Bergner & Lohmann (2014) stated that
tourism sector faces plenty of challenges which have not been a part of normal business in the
shape of global financial crisis, political issues, terrorism as well as natural disaster. A crisis,
hereafter, portrays an occasion that leads to a failure of adapting to some changes (Ritchie, 2004)
and the COVID-19 pandemic which was declared by the WHO on March 11, 2020 is considered
as a crisis since it ceased people mobility at global scope to community scope, enforced several
countries to close the border, led to a sluggish economy due to less or even terminated the
production and distribution process of products. The outbreak of this pandemic has changed
Balinese economic, social, and political structures since people attempt to deal with the ‘new
normal’.
2. Research Objectives
Due to the shortage of systematic comprehension on economic impact assessment on tourism
sector that potentially provides insights and lessons for policymakers to improve and adjust the
existing tourism policy options particularly at national level during the crisis, to achieve the
research objective and provide a guidance for this research analysis, two objectives were
formulated. Firstly, this study aims to enhance the understanding of tourism sector contribution,
especially gastronomic tourism, to Bali’s economy with the propensity to encourage sustainable
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November 26th – 27th, 2020, Khon Kaen, Thailand
development in terms of creating economic impacts stimulated by the tourism products and
services. This could be a booster to regenerate heritage restoration as well as raise local
community identity. Due to the annual increase in visitor size, the tourism sector is indicated to
support local communities. Bali Province is quite popular with their nature and culture for tourist
attractions. This is, therefore, highly necessary for the province to gain a return on their
investment to tourism sector in terms of local communities and local enterprises who attempt to
attract more tourist to Bali by running their culinary and other businesses. However, the
emergence of a crisis cannot be avoided along the way. Thus, the second objective indicates the
economic impacts of tourism sector during crisis through the case of COVID-19 pandemic
would be an indication to whether local community’s investment will worth their while. This
study will review the economic effect of gastronomic tourism by highlighting the number of
tourists who visited Ubud Food Festival, their average spending during their visit, and regional
multipliers generated by tourism sector. Therefore, the research question which would guide the
thesis is exhibited the direct and indirect impacts of gastronomic tourism towards Bali’s
economy generated by Ubud Food Festival through 54 sectors in economy by constructing
regional output, value added, income, and employment multipliers during COVID-19 pandemic.
3. Literature Review
Multiple models have been developed to compile the economic impacts of tourism, namely
Input-Output (I-O), Social Economic Matrix (SAM), Computable General Equilibrium (CGE),
and Tourism Satellite Account (TSA) models. Each of these models will be used depends on
the purposes as well as scale of the analysis. The I-O model study can be employed to improve
regional statistical system and provide reliable information to make regional tourism policies
(Waluyo, 2015). The model has been broadly used in empirical study to forecast the economic
impacts of tourism. Tourism-related information as data and models requires to influence both
tourism activities and their relationship with local and regional economic activities. As stated
by Van Wyk et al. (2015), the I-O model is ideally suitable to estimate the economic impacts of
short-run regional development projects like events or festivals. This model is more popular for
economic impact assessment due to its ability to presents accurate and detailed information on
direct, indirect, and induced effects of visitors’ or tourists’ spending on certain ‘key’ industries
in economy, thus Loomis & Walsh (1997) highlighted this as one of I-O model’s strengths.
When tourists visit a certain area, there is an increase in this area’s economic activity due to
tourist activities that directly and indirectly create more demands for local goods and services.
Estimating economic impact aims to measure the changes in sales, income, tax revenues, as well
as employment from tourism activities.
The economic impacts in tourism activities as classified by Tribe (2011) is differentiated to
primary and secondary effects. The significant input to the economic impact analysis of tourism
activity usually addresses to tourist spending in the area, the portion of sales generated by
tourism-related local businesses, the income generated by tourism industry for households and
local enterprises, the employment in the area and tax revenue supported by tourism sector. The
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November 26th – 27th, 2020, Khon Kaen, Thailand
primary effect contains the direct effects of extra demand occur within main tourism activities
e.g. tourist spending on lodging, food and beverage, recreational, transportation, and retail trade.
The secondary effect makes the economic impact assessment more accurate, since tourism will
acknowledge the linkage of most sectors in economy as well as how dependable this region to
good and service imports. Indirect and induced effects are included in secondary effect. This is
assessed by multipliers through computing the leakage of new spending in the area (Janeczko
et al., 2002). Indirect effects refer to additional demand for goods and services by industries that
provide tourist needs in a target region e.g. the extra food ingredients that restaurants require to
purchase, the extra inputs on supply and labor for hotels needs to serve their guests, and so forth.
While induced effects generate after tourism’s direct and indirect effects emerging due to an
increase of demand for goods and services in specified region e.g. the labors whose jobs are
supported within the value chain and spend their incomes on local goods and services therewith
assisting the other economic activities.
The most common multipliers employed to analyze the economic impact are the output, income,
employment, and value-added multipliers (Hughes, 2018). Stynes (1997) constructed the simple
formula to estimate the economic impact of tourism as follow:
𝐸𝑐𝑜𝑛𝑜𝑚𝑖𝑐 𝐼𝑚𝑝𝑎𝑐𝑡 𝑜𝑓 𝑇𝑜𝑢𝑟𝑖𝑠𝑚
= 𝐶ℎ𝑎𝑛𝑔𝑒 𝑖𝑛 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑡𝑜𝑢𝑟𝑖𝑠𝑡𝑠 𝑥 𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝑠𝑝𝑒𝑛𝑑𝑖𝑛𝑔 𝑏𝑦 𝑣𝑖𝑠𝑖𝑡𝑜𝑟 𝑥 𝑀𝑢𝑙𝑡𝑖𝑝𝑙𝑖𝑒𝑟
This formula suggests three procedures: (1) estimating the change in number and type of tourist
who visit a region due to a policy, (2) analysing the average levels of tourist expenditure (on
several sectors) in a region, and (3) assessing the changes in expenditure of regional economy
model or multipliers to determine the secondary effects of tourism. Total visits, average
spending by visitor and an aggregate sales multiplier are inserted on a simple worksheet to
analyze the direct and total sales effects of visitor expenditure. Sales effects are converted to
income and employments using simple ratios of income to sales and employment to sales.
The general I-O model used to compute multipliers is the demand-side of I-O table which is
determined by demand for its outputs. The aim of employing the demand-side model is to
estimate direct, indirect, as well as induced impacts in an economy and grasp the differences
between certain types of multipliers in each category. The direct effect of visitor expenditure on
the regional economy could be simply enforced as mostly involves a comprehensive sampling
procedure. Assessing the indirect effect can be more demanding since obtaining the appropriate
multipliers is mandatory to organize a reliable and sufficient study. Assessing the impact on
regional income and employment, I-O model constructs some multipliers and provides the
linkages among sectors, personal income, as well as the total employment (Mazumder et al.,
2009).
Output is the basis multiplier of the other derived multipliers. The output multipliers describe
the total value of production by all domestic sectors in an economy required in order to produce
one extra million Rupiah’s worth of final demand for that sector’s output. Therefore, if an output
multiplier of a sector is 2. xx, it means for every million Rupiah of production in this sector,
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The 5th TICC International Conference 2020
in Multidisciplinary Research Towards a Sustainable Society
November 26th – 27th, 2020, Khon Kaen, Thailand
IDR 2. xx million of activity is created in the local economy: total of original Rupiah (IDR 1.00
million) and an additional IDR 1.xx million. The first requirement for an extra million Rupiah’s
worth of a given sector’s output is named the initial output effect. The amount of output needed
from all sectors of the economy in order to produce initial output effect is called the first round
effect. The first round effect can be estimated by deriving a table from the flow table by dividing
every column by Total domestic input at basic prices of that sector (the column total) to construct
Direct requirements coefficients which analyze the advantage of the backwards linkages.
The coefficients in a given sector’s column indicates the amount of added output required from
every sector to produce an extra million Rupiah’s worth of output from that sector. The
combined effect of the initial effect added by all the production induced rounds of extra output
are named the simple multipliers (McLennan, 1996). The simple multipliers can be computed
by deriving the first rows and columns in Direct Requirements Coefficients table and form the
A matrix, then set up an Identity matrix with similar size to the A matrix dimension to gain a
new Leontief’s matrix (I – A), accordingly calculate the Leontief’s inverse matrix (I – A)-1 to
build the column total. The next step is assessing the effects of second and subsequent rounds
in induced production by calculating the industrial-support:
𝐼𝑛𝑑𝑢𝑠𝑡𝑟𝑖𝑎𝑙 𝑠𝑢𝑝𝑝𝑜𝑟𝑡 𝑒𝑓𝑓𝑒𝑐𝑡𝑠
= 𝑠𝑖𝑚𝑝𝑙𝑒 𝑚𝑢𝑙𝑡𝑖𝑝𝑙𝑖𝑒𝑟 − 𝑖𝑛𝑖𝑡𝑖𝑎𝑙 𝑒𝑓𝑓𝑒𝑐𝑡𝑠 − 𝑓𝑖𝑟𝑠𝑡 𝑟𝑜𝑢𝑛𝑑 𝑒𝑓𝑓𝑒𝑐𝑡𝑠
as well as calculating the production induced effects:
𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 𝑖𝑛𝑑𝑢𝑐𝑒𝑑 𝑒𝑓𝑓𝑒𝑐𝑡𝑠 = 𝑓𝑖𝑟𝑠𝑡 𝑟𝑜𝑢𝑛𝑑 𝑒𝑓𝑓𝑒𝑐𝑡𝑠 + 𝑖𝑛𝑑𝑢𝑠𝑡𝑟𝑖𝑎𝑙 𝑠𝑢𝑝𝑝𝑜𝑟𝑡 𝑒𝑓𝑓𝑒𝑐𝑡𝑠
The household industry receives wages after production work and spends this income on goods
and services. The wages are denoted by the matrix multiplication of Compensation of employee
row and the Consumption by private household column. It is showed in Final consumption
expenditure column as shown in the flow table. The induced production of extra goods and
services in response to private fine consumption expenditure is portrayed as the consumption
induced effects. Thus, we can calculate new multiplier set called the total multipliers by
summing up the initial effects, the production induced effects and the consumption induced
effects. The total output multipliers are computed by assigning an Identity matrix with the same
size as dimension of A matrix added by the Compensation of employees row and Final
consumption expenditure column, thus a new framework matrix called B matrix is build up as
shown in Figure
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The 5th TICC International Conference 2020
in Multidisciplinary Research Towards a Sustainable Society
November 26th – 27th, 2020, Khon Kaen, Thailand
consumption
expenditure
Quadrant I
Final
Intermediate Usage
Compensation of employees
Figure 1 The matrix B framework
The Leontief’s inversed B matrix, (I-B)-1 or symbolized as B* is built from the first six rows and
columns of the B matrix includes the columns totals. This is called the total output multipliers.
Then, the consumptions induced effects is computed as follows:
𝐶𝑜𝑛𝑠𝑢𝑚𝑝𝑡𝑖𝑜𝑛 𝑖𝑛𝑑𝑢𝑐𝑒𝑑 𝑒𝑓𝑓𝑒𝑐𝑡𝑠 = 𝑡𝑜𝑡𝑎𝑙 𝑜𝑢𝑡𝑝𝑢𝑡 𝑚𝑢𝑙𝑡𝑖𝑝𝑙𝑖𝑒𝑟 + 𝑠𝑖𝑚𝑝𝑙𝑒 𝑚𝑢𝑙𝑡𝑖𝑝𝑙𝑖𝑒𝑟
The second multplier is the income multiplier. It indicates the increase in the total value of
employee’s income required to fulfill a million Rupiah’s worth of final demand for the output of
the target sector. An income multiplier of 2.xx exhibit that for every million Rupiah of
Compensation of employees in certain sector another IDR 1.xx million of employee’s income is
created in the local economy. After estimating the househould coefficients in Compensation of
employees row in Appendix B, these are the initial household income effects, or denoted as the
vector i. Part of income multipliers can be computed by employing matrix multiplication
function as follows:
𝐹𝑖𝑟𝑠𝑡 𝑟𝑜𝑢𝑛𝑑 𝑖𝑛𝑐𝑜𝑚𝑒 𝑒𝑓𝑓𝑒𝑐𝑡𝑠 = 𝑖 ∗ 𝐴
𝑆𝑖𝑚𝑝𝑙𝑒 𝑖𝑛𝑐𝑜𝑚𝑒 𝑚𝑢𝑙𝑡𝑖𝑝𝑙𝑖𝑒𝑟𝑠 = 𝑖 ∗ (𝐼 − 𝐴)
𝑇𝑜𝑡𝑎𝑙 𝑖𝑛𝑐𝑜𝑚𝑒 𝑚𝑢𝑙𝑡𝑖𝑝𝑙𝑖𝑒𝑟𝑠 = 𝑖 ∗ 𝐵∗
The remaining income multipliers can be computed in the same way as the corresponding output
multipliers.
The value added multipliers indicate the initial increment in output utilized from a sector and the
total increase value added by all sectors. A value added multiplier of 2.xx shows that for every
million Rupiah of direct value added in target industy another IDR 1.xx million of value added
is creared in the local economy. The interpolation in value added bears with an increase in gross
domestic product (GDP) as the GDP is established by sum of value added and net taxes as
followed formula:
𝐺𝐷𝑃 = 𝑉𝑎𝑙𝑢𝑒 𝑎𝑑𝑑𝑒𝑑 + 𝑁𝑒𝑡 𝑡𝑎𝑥𝑒𝑠
= (𝑂𝑢𝑡𝑝𝑢𝑡 – 𝐼𝑛𝑡𝑒𝑟𝑚𝑒𝑑𝑖𝑎𝑡𝑒 𝑖𝑛𝑝𝑢𝑡𝑠) + (𝑇𝑎𝑥𝑒𝑠 – 𝑆𝑢𝑏𝑠𝑖𝑑𝑖𝑒𝑠 𝑜𝑛 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑠)
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To compute value added multipliers, the vector h (the Value Added row) from direct
requirements table is required that shows the initial effect on the excess of value added in
response to output’s direct increase by a million Rupiah. Hence, this vector h is multiplied by
the Leontief’s inverse matrix as follows:
𝑆𝑖𝑚𝑝𝑙𝑒 𝐺𝑉𝐴 𝑚𝑢𝑙𝑡𝑖𝑝𝑙𝑖𝑒𝑟𝑠 = ℎ ∗ (𝐼 − 𝐴)
The employement multipliers portray the total jobs created through an increase in initial output.
If an employment multiplier is 2.xx, it means that every direct job generates 2.xx jobs in total
economy: the original job (1.00 job) and 1.xx additional jobs. This multiplier is not obtained
from the elements in I-O table, like in output and income multipliers, as I-O table does not
include the employment-related elements indeed. Adding a new row to put the total amount of
employment in a region or country in I-O table requires employment coefficients which can be
derived from dividing each number of employment in given domestic sector by th etotal output
generated by that domestic sector.
The previous empirical studies regarding the economic impact analysis tend to apply a common
methodology, Input-Output model, even though there are certain diversities in application as it
depends on the flows, agents, as well as tools utilized in the study. Those studies emphasize
Input-Output analysis to calculate the multiplier effects and conduct visitor survey. Visitor
survey is commonly employed by researches as it allows the visitors to share their spending
pattern. Therefore, the survey also provides demographic questions that lead the researchers to
understand the target market better. This study employs the first classification from Fletcher
(1989) and Archer & Fletcher (1990) studies which assesses the economic impact of tourism in
certain regions or countries with common Input-Output model.
4. Research Methodology
Before analyzing the economic impact of gastronomic tourism, assessing the economic value of
tourism sector, and converting into the economic value of 54 sectors within 2007 Updated I-O
table of Bali Province Domestic Transaction at Producer Price are required. The constructed I-
O table fundamentally consider Law of the Republic of Indonesia Number 10 of 2009
concerning Tourism (State Gazette of the Republic of Indonesia of 2009 Article 11, Supplement
to Official State Gazette of the Republic of Indonesia Number 4966) which emphasizes the
management of government and tourism-related institutions in conducting research and
development to support the tourism affairs development. The dimension of this research I-O
table is classified by 54 x 54 sectors.
Estimating the linkage among sectors in Bali’s economy aims to identify that tourism sector has
strong correlation with other sectors. The gastronomic tourism-related sectors such as
accommodation, food and beverage, as well as recreational, cultural and sporting activities only
bring tourism sector backward further rather than bring it forward. This is assumed that tourism
sector has high backward linkage with other sectors compared to other sectors’ enforcement.
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November 26th – 27th, 2020, Khon Kaen, Thailand
The total output generated by Ubud Food Festival was analyzed towards local attendees and
business level researches. For business level research, a survey is included all visitors’
expenditures to estimate the locals and visitors’ spending during the festival. The data set used
referred to The Ubud Food Festival 2019 held on April 26-28, 2019. The local attendees survey
was conducted by contacting local visitor and asking them to complete a questionnaire translated
in Indonesian regarding their demographics and influenced factors to attend UFF 2019. The
visitor list was derived from secondary data of UFF and contacting them through email to
distribute the online questionnaire that gain their festival-related spending in the area. A total
628 questionnaires are completed.
The business survey for supply approach focuses on six industries; accommodation, food and
beverage service, inland transport service, retail trade industry, recreational, cultural, and
sporting activities, as well as craftsman work industry. A total of 101 organizations and
companies participated on the business survey.
5. Results
According to the calculation of backward linkage index (BL) and forward linkage index (FL) of
the 54 sectors in Bali’s economy can accordingly be grouped into four categories depending on
their values (i.e. size):
1) Key Sectors; strong BL and FL: BL > 1 and FL > 1
2) Strong BL but weak FL: BL > 1 and FL < 1
3) Weak BL but strong FL: BL < 1 and FL > 1
4) Weak Linkage Sectors: weak BL and FL: BL < 1 and FL < 1
To emphasize the use of numerical linkage index calculation, taking fifteen gastronomic
tourism-related sectors from Bali’s economy and collecting in Table 1 that presents four of them
have strong tourism components, including Textile, apparel, and leather products, Food and
beverage services, Star hotels, and Air freight services. Five sectors have strong backward
linkage index and weak forward linkage index, only one sector has weak backward linkage
index and strong forward linkage index, and five sectors have both weak backward and forward
linkage indices.
BL > 1 BL > 1 BL < 1 BL < 1
Industries
FL > 1 FL < 1 FL > 1 FL < 1
Food, beverage, tobacco, coffee industries x
Textile, apparel, and leather products x
Craftsman industry and excavated products x
Jewellery manufacturer x
Food and beverage services x
Star hotels x
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Non-star hotels x
Inland transportation x
Sea freight services x
Air freight services x
Travel agent x
Transportation support services x
Money changer x
Cultural attractions x
Recreational and sporting activities x
Table 1 Inter-industry linkages for gastronomic tourism-related industries
Among the leading gastronomic tourism-related industries, most of their tourism components
have strong backward linkages to other industries but weak forward linkages as well as have
both weak backward and forward linkages. In particular, the backward and forward linkage
indices differ among gastronomic tourism-related industries.
The average change in revenues of each sector assigned in this study shown in Table 2.
Business revenues during
Change in Business revenues on the
Selected sector
UFF 2019 (IDR) revenues (%) weekend after UFF 2019 (
Accommodation 3,194,443,376 10.6 2,885,915,631
Food & beverage 2,843,429,382 64.88 1,724,572,350
Inland transport 87,111,175 36.43 63,850,237
Retail trade 1,584,848,316 5.01 1,509,206,968
Craftsman work 63,469,235 84.13 34,469,235
Recreational, cultural and
sporting activities 569,556,634 23.39 461,577,059
Table 2 Comparison of business revenues
Assessing the total expenditure of the local visitors during the event, the average expenditure
on products and services served through six industries of interest is computed. The impact
analysis of this study excludes the expenditures on festival admission and registration as they
had seven purchased events during the three-day festival. Since the allocation of revenue by
festival organizer is confidential, it is impossible to specify the percentage of their revenues
spent in Bali or the industries where they are spent. Instead of presuming the purchases by the
festival organizer obey the pattern of predefined sectors above, this research assumes that the
UFF revenue is not involved in Bali’s economy. Thus, the table of visitor’s expenditure is shown
in Table 3.
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Non-festival Expenditure Expenditure (IDR) Percentage (%)
Accommodations 79,117,000 15.6%
Foods and Beverages 96,615,500 19.1%
Transport Services 135,355,000 26.7%
Retail Shopping 110,551,500 21.8%
Craftsman Works 9,465,000 1.9%
Recreational Activities 74,901,000 14.8%
Total 506,005,000 100%
Table 3 Visitors’ expenditure to UFF 2019
Computing the output multipliers, Leontief inverse matrix is derived. This type I inverse matrix
represent the output amount required from each sector according to direct as well as indirect
requirments to compose one unit (or IDR 1 million in this case) of output from a certain sector.
The formula to get the output amount is:
L = (I – A)-1
where L = the Leontief inverse matrix;
I = the Identity matrix;
A = the Direct Requirement matrix.
The Direct Requirement coefficients are computed using primary inputs and intermediate output
table, directly divided every column by the Total Domestic Input at Basic Prices columns, hence
producing Direct Requirement matrix.
The value added multipliers can be calculated by applying value added coefficients in Value
Added at basic prices row of the Direct Requirement matrix. This coefficients are symbolized
as the vector h. To compute the First round effect, Simple income multipliers, as well as Total
income multipliers of each sectors, the matrix multiplication function is utilized. Manually, this
calculation is a 1 x 54 and 54 x 54 matrix multiplication1. Followed by 1 x 54 array represented
by the Innitial effects column and 54 x 54 array refered to matrix A for First round effects,
matrix (I – A)-1 for Simple value added multipliers, and matrix B* for Total value added
multipliers. The remaining value added multipliers can be computed in the same way as the
corresponding output multipliers.
The income multipliers can be computed by applying household coefficients in Compensation
of employee row of the Direct Requirement matrix. These coefficients are denoted as the private
income effects and symbolized as the vector i. To compute the First round effect, Simple income
multipliers, as well as Total income multipliers of each sectors, the matrix multiplication
function is utilized. Manually, this calculation is a 1 x 54 and 54 x 54 matrix multiplication.
1
For simplicity, MMULT function in Microsoft Excel is applied.
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The 5th TICC International Conference 2020
in Multidisciplinary Research Towards a Sustainable Society
November 26th – 27th, 2020, Khon Kaen, Thailand
Followed by 1 x 54 array represented by the Initial effects column and 54 x 54 array referred to
matrix A for First round effects, matrix (I – A)-1 for Simple income multipliers, and matrix B*
for Total income multipliers. The remaining income multipliers can be computed in the same
way as the corresponding output multipliers, finally the income multipliers are constructed as
shown in Appendix F.
The output, value added, income, as well as employment multipliers for gastronomic tourism-
related sector in Bali’s economy are presented in Table 4.
Value
Output Income
Sector Added
Multiplier Multiplier
Multiplier
Food, beverage, tobacco, coffee
2.09 3.59 0.29
industries
Textile, apparel, and leather
1.75 2.96 0.26
products
Craftsman industry and excavated
1.80 3.64 0.31
products
Jewellery manufacturer 1.69 3.44 0.37
Food and beverage services 2.15 4.25 0.34
Star hotels 1.82 4.34 0.27
Non-star hotels 1.89 3.70 0.32
Inland transportation 1.55 3.82 0.26
Sea freight services 1.53 4.41 0.27
Air freight services 1.47 3.97 0.12
Travel agent 1.57 2.81 0.23
Transportation support services 1.83 4.29 0.38
Money changer 1.57 4.46 0.17
Cultural attractions 1.59 4.58 0.27
Recreational and sporting
1.57 4.74 0.30
activities
Average 1.72 3.93 0.28
Table 4 Multipliers of gastronomic tourism-related sectors
6. Discussion and Conclusion
A prominent feature of gastronomic tourism is that a rise in final demand shows an injection
of funds beyond the economy. Accordingly, it is suitable to analyse tourism impacts on Bali’s
economy as if tourism output was an expand in final demand. In order to measure the economic
impact on tourism sector, this study focuses on international tourist expenditure. By
multiplying the Leontief inverse matrix of final demand vector with all sectors other than
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The 5th TICC International Conference 2020
in Multidisciplinary Research Towards a Sustainable Society
November 26th – 27th, 2020, Khon Kaen, Thailand
tourism inserted as zero, the level of economic activities supported this consumption,
differentiating between direct and ‘direct + indirect’ effects. The output, value added, and
income impacts are presented in Table 4.
Table 4 identified that Recreational and sporting activities has the largest amount of Value
Added Multiplier of 4.74. This number denotes an extra million Rupiah’s worth in final
demand of Recreational and sporting activities will impact to overall value added increase in
Indonesian economy of IDR 4.74 million. Furthermore, Craftsman industry and excavated
products, star and non-star hotels, as well as food and beverage, have Value Added Multiplier
of 3.64, 4.37 and 3.7, as well as 4.25 respectively. The largest amount of Income Multiplier is
defined by Transportation support services with 0.38. This number identified that every 100
people increase in certain sector will create job opportunity in other sectors of 38 people. The
multiplier analysis concludes that gastrononmic tourism has quite large Value Added multipler
effect as the average number of this multipliers is larger than 2.00. Considering the backward
linkage and large multiplier numbers of tourism sector, hence gastronomic tourism could be
the ‘key’ sector to expand Bali’s economic growth through its relation with other sectors which
play a role as tourism sector’s input.
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The 5th TICC International Conference 2020
in Multidisciplinary Research Towards a Sustainable Society
November 26th – 27th, 2020, Khon Kaen, Thailand
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