The Regional Multiplier Effect of Pilgrim Tourism PDF
The Regional Multiplier Effect of Pilgrim Tourism PDF
The Regional Multiplier Effect of Pilgrim Tourism PDF
kozak.tamas@uni-bge.hu
Associate Professor
Budapest Business School
1. Introduction
Recently, pilgrimage grew to be a significant area of religious tourism. Pilgrimage is
one of the most exciting emblems of Christian life deeply rooted in the Bible. “The ec-
clesiastical view of a human being, of a Christian as homo viator, is a person on journey, a
pilgrim on earth on the way to the heavenly life. (Timothy, J.D. and Olsen, H.D. 2006).
In several cases, related academic works discusse the complex economic, political, social,
psychological and emotional relationship between pilgrimage and economy (Nolan, M.L.,
Nolan, S., 1992).
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The main theoretical background stems from the Keynesian multiplier, which is the
ratio between output variation and the initial exogenous variation of aggregate demand
(Bénassy-Quéré et al., 2010). The primer assumption is on the Keynesian Multiplier that
the consumption is a linear of current income. The marginal propensity to consume means
that out of one additional dollar (or forint) of disposable income the people spend and
save some part. There are some factors which influence the multiplier effect, for example:
–– portion of the additional income accrues to consumers
–– portionof the additional income consumers accrues to buying products or services
–– share of disposable income leads household to consume of domestic and imported
goods
In this paper the Keynesian assumptions are presented within the aggregate supply
and aggregate demand model, assuming the production increases at any given price level.
In terms of the Leontief input – out model it is analysed how the initial demand
shock shifts the local economic performance, and how the multiplier effect change the
regional equilibrium. The majority of the current literature examines the relationship in
macroeconomic level, in this paper such a method is presented which applicable on meso
level as well.
The multiplier effect on macro-economic level was worked out by N. Gregory
Mankiw and Agnes Bénassy-Quéré, the regional effect analysed by Harvey Armstong and
Jim Taylor between the earliest in book Regional Economics and Policy.
Business actors are increasingly interested in the economic benefits of tourism at na-
tional, regional, and local levels. Regularly it is assumed that tourism supports some jobs
in an area and generates many million Euros or Forints in additional sales or income in a
city or village. Multiplier effects are often cited modelling method to calculate non-direct
effects of tourism spending and show the wide range of industries’ performance in a region
that can be benefited by tourism. Tourism‘s economic results are taken into account by
the sector for a variety of reasons. Assumptions of pilgrim tourism‘s economic relevance
ensure the industry heightened respect in the business life in general. This often translates
into business decisions or economic policies that are favourable to the local standard of
life. (Vijayanand, 2012).
In this paper the study of pilgrimage’s economic effect is based on the econometric
model. Lébény is a settlement in Győr-Moson-Sopron County, Hungary, close to the
Hungarian – Austrian border. In this small town a Romanesque monastic church van be
found, which built in 1208, named St. James parochial church. Originally, the famous
church was built cca 800 years ago as a Benedictian Monastery, thanks to this notable
building a part of the St Jacob Pilgrimage runs in Lébény.
This paper demonstrates the suitable use of regional input-output (I-O) models show-
ing the economic impact of pilgrim tourism on Lébény’s region. The described model pro-
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vides multipliers as an estimation of the economic effects that an initial change in service
activity—such as increased accommodation—has on the regional economy. The initial
change involves a change in final consumption for additional manufacturing or agricul-
ture, an increase in government purchases, or an increase in household income. The basic
data for the calculation of Lébény’s economy are the next: In 2016 the total purchasing
power was EUR 19,7 million, the number of population was 3229, and that means EUR
6100 purchasing power per capita.
Purchasing power is an indicator of per capita disposable net income after the de-
duction of taxes and social security contributions, including any received social insurance
benefits. The study uses the relative figures of per person and per year purchasing power
levels in Euros as index values (Appendix 1). GfK Purchasing Power uses to nominal dis-
posable income, which means values are not adjusted for inflation. The study applies sta-
tistics on income and tax levels, government benefits and forecasts by economic institutes.
Pilgrims use their general purchasing power to cover expenses related to eating, living,
services, as well as other expenditures such as merchant purchasing.
The fundamental component is in the intermediate transaction table, which draws
on the flow of output between producer and user actors, and predicted in terms of de-
scriptions of regional activities. The regionalization of input-output coefficients is based
on non-survey method using mainly secondary data and information (Szabó, 2015). For
the purpose of local GDP calculation the total purchasing power is used for figuring
out the regional economic performance. One of the possible sources to gather additional
information is the published municipal budget. For example, in this paper the local tax
figures of 2014 budget are used to estimate the company contribution to local government
expenditure.
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effects is suggested. This is a basic introduction to the input-output analysis, which was
founded by Vassilii Leontief in the 1930s. In the applied Leontief ’s input-output model
there are four measures of changes in regional economic activity that can be estimated—
gross output of four sectors, value added, earnings, and employment.
Initial Initial
Final Total
Agriculture Mining Industry Services Demand Output
Agriculture Total
Mining Gross
Intermediate Inputs
Industry Output
Services Final Use
Primary inputs
to direct
Payment for income owners Primary inputs to industries consumption
Input Total Total Gross Output
Source: own edition
The crucial question is how the local sectors’ intermediate relationships can be quan-
tified in the local input-output model if primary data are missing? One of the method used
in this research is to use the national level sector metrics (such information are available
in the Statistical Office database), and calculated benchmark can be figured out upon na-
tional level statistics. The regional sector gross output can be compared to final consump-
tion in terms of sector matrix to calculate the benchmark figures, the local geographical,
experimental information could be used for refining these ratios. For example in a city or
village the gross output depends on the capacity and economic performance of the local
companies and the export–import relationship with external partners. After some “model
running” it can be used sector-specific multipliers as in this example, we automatically
count with the mix of produces goods and services purchased and secondary effects for
final consumers.
source to pay for income owners, which stems from the difference of totals sales and inpot
purchases, so the total gross output is equal to the sum of intermediate inputs and value
added value added summed across all industries is equal to regional GDP.
On the regional level the gross output is equal to the sum of the intermediate inputs
and value added, which can be measured as the sum of the intermediate inputs and final
use. Value added is defined as the value of gross output minus intermediate inputs exclud-
ing any income accumulations among companies. The added value is the source of the
payments made for economic actors, namely for example the rewarding of employees in
form of wages or salaries and the taxes on production and imports. So the transaction table
shows the economic actors’ contributions for the regional gross domestic product through
household consumption, (local) government expenditures, net export figures, company
investments, capital expenditures and import value (Moss, 2007).
Fi . . . Flow i
N . . . Number of rows in column
Technical coefficients express the direct effects of change in final demand for a certain
commodity. To measure indirect effects, namely interdependence coefficients reflect the
change of performance in producing and service provider sectors.
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The technical coefficients show the relation between the expenditure structure and
the level of total purchase, sector by sector (Krekó, 1964). If we want, for instance, to
determine the technical coefficient for industry, we obtain:
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import (EUR 24,06 million). The government effect is zero, because expenditure (EUR
0,60 million) equals the payments for the government (income from taxation), so the
regional GDP is EUR 19,12 million.
The example signalizes how sector-specific multipliers are used to obtain a more accu-
rate and detailed estimation of regional economic impacts. It is used to aggregate pilgrim
tourism multipliers computed from the “Totals” row of Table 3. The 2,59 aggregate sales
multiplier for services is based upon the idea that any EUR 1 thousand local expendi-
ture by pilgrims, spent for services, leads to a plus EUR 2,59 thousand indirect effect
in the region spent by those who received the initial outlay. For example, if pilgrims
pay for catering or to buy goods at a retailer, the entrepreneurs in turn spend their income
on goods and services, thus giving employment to additional firms and individuals, etc.
This way the original expenditure by the pilgrim visitors circulates repeatedly through
the economy, and the total economic activity generated (2,59) is greater than the EUR
amount of the original expenditure alone.
The jobs-to-sales ratio shows how the service companies can pay additional income
after the increased turnover of sales in the service sector. In the service sector 25% of the
total input corresponds with the payment for labor (Appendix II). This ratio readily allows
converting sales in a given sector to jobs. The employers spend more money for goods and
services, the companies can grow their margins so the consumption increases in terms of
additional paid income for household, and so on.
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5. Conclusion
The calculated multipliers are defined as the ration of the change of economic out-
put to change of spending in service sector by pilgrims. It is examined how much the
regional equilibrium level of output change when assumed pilgrim spending change.
It is nor goal to explain why planned and assumed spending change. The increase in
planned corporate performances comes from more pilgrim consumption. The retailers
or restaurant inventories decline, so they need to buy ones, in response to decreased in-
ventory suppliers increase output. Output and input cab rise significantly by more than
fout times in Lébény region.
However, using this econometric model the effect of retail spending can be quanti-
fied as every additional EUR 1 thousand spent by pilgrims in a region (i.e. town) leads
to a total economic effect of EUR 4,4 thousand on the sales. For this analysis, the value
of the multiplier used for the pilgrim tourism in Lébény is 4,4. This multiplier attempts
to take into account the important leakages which occur out of any locality or region in
the form of export or imports. The figure of the pilgrimage multiplier is derived detailed
in the paper. This implies that the EUR million extra income will generate an increase
of EUR 18,22 million in the regional gross domestic product.
The main goal of this research paper is to present the method which can be applica-
ble to examine the multiplier effect on regional level in terms of input – output model.
Due to the dominating the analysis in macroeconomic level, excellent research topic is
to work out new methods to examine the effect of the demand shock on local economy.
The basic conclusion of my research is using the statistical macroeconomic benchmarks
to regional analysis provides a useful model for local economic decision makers to evalu-
ate the change of business relationships.
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References:
1. Acemoglu, D. et al. (2016): Macroeconomics, Pearson, p313.
2. Armstrong, H., Taylor, J., (1985): Regional Economy and Policy, Camelot Press
Southampton, pp 34-35
3. Benassy-Quéré A., Coeuré, B., Jacquet, P., and Pisany-Ferry, J,. (2010) Economic
Policy, Oxford University Press, pp 180-181.
4. Bess, R., Ambargis Z. (2011): Input-Output Models for Impact Analysis: Suggestions
for Practitioners Using RIMS II Multipliers, Southern Regional Science Association
Conference March 23-27, 2011
5. Dedák I (2010): Makroökonómia, Saldo, Budapest, pp 40-41
6. Krekó B. (1964) Matrix calculation, Közgazdasági és Jogi Könyvkiadó, Budapest, p
105)
7. Moss D. (2007): Macroeconomics, Harvard Business School Press, p.11
8. O’Connor R., Henry E. W., (1975): Input-Output Analysis and its Applications.
Griffin’s statistical monographs and courses. Charles Griffin and Company Ltd, Lon-
don and High Wycombe, p 42
9. Scharnitzky V. (1986): Mátrixszámítás (Műszaki Könykiadó, p. 169
10. Szabó N. (2015): Methods For Regionalizing Input-Output Tables, Regional Statis-
tics. p 47
Internet source:
https://lebeny.hu/egyeb-dokumentumok
http://statinfo.ksh.hu/Statinfo/haViewer.jsp?wcf27302f6b=x
https://msu.edu/course/prr/840/econimpact/multipliers.htm
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Appendix I
Assumptions Ratios
Import to consumption
Agriculture 20%
Manufacturing 50%
Services 15%
Export to consumption
Agriculture 46%
Manufacturing 37%
Services 45%
Investments to consumption 5%
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Appendix II
Manufacturing
Gross Output
Government
consumption
Investments
Households
Agriculture
Transaction
spending
Services
Exports
Table
The
Output produced by
Agriculture 6,72 8,40 1,68 5,60 7,76 0,28 30,44
Manufacturing 13,44 26,88 4,48 5,60 16,48 0,28 67,16
Services 1,44 1,92 1,44 4,80 - 2,14 0,24 11,98
Payments for -
Household services 4,32 11,16 3,04 - 0,60 - - 19,12
Government Services 0,20 0,20 0,20 - - - - 0,60
Imports into the region 4,32 18,60 1,14 - - - - 24,06
Gross input 30,44 67,16 11,98 16,00 0,60 26,38 0,80 153,36
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