Post on 09-Apr-2018
Abstract—Korean public sector relocation policy has often been
justified for balanced national development. The senior echelons of
Korean civil service are disproportionately concentrated in Seoul
Metropolitan Region. Significant reductions in operating costs can be
achieved by relocating civil service functions from the capital to other
underdeveloped regions, which in return will enhance economic
development of the regions. However, negative economic impacts of
the relocation have been overlooked by its overall positive economic
impact across the nation. This paper assesses the case for public sector
relocation, and its economic impacts on all industrial competitiveness.
For this purpose, the Multi-Regional Input Output (MRIO) model was
built in order to analyze the negative economic impact on the Seoul
Metropolitan region when public research sectors were relocated to
other capital cities. But Korean Industry Input-Output Table created by
Bank of Korea is not appropriate because the table was created in
2005. Therefore, based on Industry Input-Output Table 2005, RAS
approach is applied to update it to Industry Input-Output table for
2010. Furthermore, the paper comes up with some policy suggestions
for the efficient land use of Seoul Metropolitan Region after the
relocation
Keywords—Multi-Regional Input-Output model(MRIO), RAS
approach, Public Sector Relocation
I. INTRODUCTION
GINNING with the partial relocation of central
government at the end of the 2012, the relocation of public
sectors to Sejong-Si and other inno-city is taking places. Due to
the change, decrease of population and weakening in
competitiveness of Seoul is predicted. Also not only the slight
shift in the phase of the city is expected but also quantitative
and qualitative changes in various fields such as populations,
employment and industry will result in weakening of the city’s
competitiveness.
Especially, after 2014 when nine public sectors now located
in Seoul are moved to inno-cities, population decrease and
Seungbee. Choi is with the Dept. of Urban Engineering, Yonsei University,
Seoul, Korea. (corresponding author to provide phone: 82-10-6274-2973; fax:
82-2-393-6298; e-mail:csbee@naver.com).
Kabsung. Kim was with University of Pennsylvenia, PA USA. He is now with the Department of Urban Engineering, Yonsei University, Seoul, Korea as
a professor. (e-mail: kabsungkim@yonsei.ac.kr ).
Jihye. Han is with the Dept. of Urban Engineering, Yonsei University, Seoul, Korea. ( e-mail:jiny574@naver.com).
productivity decrease are unavoidable. Therefore careful
analysis on ripple effects should be done over many different
fields, such as industry, economy, employment and etc. to
verify what the city of Seoul will be facing and to plan ahead.
A valid method to analyze the effects of such national policy
is inter industry analysis. Many preceding studies conducted
analysis on the inter industry analysis, however, the only
available Industry Input-Output table on 16 cities or province
and 28 industries that the bank of Korea published is the one
updated in 2005. Therefore, in this research, the most reliable
and accurate method of updating, RAS approach is used to
update the Korean Industry Input-Output table of 2005. The
updated Industry Input-Output table is used to analyze social
and economic effects of the relocation.
II. LITERATURE REVIEW
A. Researches on the effects of relocation of central
government and public institutions
Kim KunSu (2005) analyzed the economic effect of the
relocation of public institutions in KyeongKi area to seek the
validity. They developed regional CGE Model to predict
economic effect of the relocation.
Kim SeonWoong (2012) predicted the changes in
populations and functions of Seoul after the relocation of public
institutions and development of metropolitan area. When
administration and public institutions move to Sejong-Si and 10
other inno-cities, 7.6~9 ten thousands of the population are
predicted to leave the Seoul. The number of people leaving the
city is less than 1% of current population, therefore only minor
effects are predicted to be provoked.
Kim TaeKyung (2013) analyzed the economic depression
and its riffle effects on Gyoenggi-do caused by the relocation.
B. Researches on national ripple effects
Park SangWoo (2003) analyzed ripple effects on
populations, regional economy and environment and society by
setting three construction alternatives on new administrative
capital. In analysis of population, he proceeded the analysis by
dividing the effects into two categories, direct population
movement effects and indirect population movement effects.
For former, direct influx population considering central and
regional public officers’ movement was used and for the latter,
Updating Korean Industry Input-Output Table
using RAS approach and application
-Focusing on economic impact by public sector
relocation policy in Seoul-
Seungbee. Choi, Kabsung. Kim, and Jihye Han
B
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employment population estimated using employment constant
was used.
Kim EinHee (2005) used Multiregional
Input-Output(MRIO) to analyze the effects of the relocation of
public institutions to rural area on reduction in densely
population matters in metropolitan area and regional
development and evaluated former government policies to
suggest future improvement direction. In total of 259thousands
of population will be spread out due to the relocation of 176
public institutions which 31,914 of people work for.
Kim GwangIk (2012) analyzed how the relocation of
administrative and public institutions effects on country space
through two different factors, population shifts between regions
and shifts in trip chaining structure. In order to analyze the
population shifts due to the relocation, the research estimated
the changes in terms of 5 years based on the movement of
employees of institutions and related families along with
related industries and their related families. As a result, by the
year of 2030, total population influx to non-metropolitan area
will be about 280 thousands, 190 thousands of population
moving to Chungchung and Youngnam area in the beginning.
III. RESEARCH METHOD
This research focuses on the socio-economic effects of
nation, particularly Seoul, by analyzing effect on production
inducement and effect on employment inducement evoked by
changes in final demand after the relocation of central
government offices and public institutions.
Practical bound of the research is set to Seoul, but in order to
compare relative effects of the relocation on Seoul, all affected
areas can be included.
A. Multi regional Input-Output Model
Using MRIO Model, decline in production (effects caused by
relocation out of Seoul) and incline (effects on Seoul caused by
increased production in other area) were estimated. Using
production inducement coefficients, effects of Seoul’s decrease
in the employment and job decrease were analyzed.
The equation to calculate production inducement
coefficients and employment inducement coefficients using
MRIO model is stated below.
Input coefficients is a parameter used to evaluate the amount
of effect on production inducement in respective industries
when final demand of goods or service goes up.
j
ijij Xa
ij : industry i’s input to the industry j
jX : total amount of input to the industry
Examining the relation of respective categories of industries,
sum of intermediate demand and final demand and subtracting
import matches the total outturn.
Supply and demand equations are as followed
This can be expressed in forms of a matrix.
In above matrix, A is input coefficients matrix, X is the
vector of total outturn, Y is the vector of final demand and
finally M is the vector of the mounts of imports.
The equation is multiplied out.
(I-A)
-1 is production inducement coefficient
Production inducement coefficients is an outturn unit that
has to be produced either directly or indirectly in respective
categories of industries when an unit increase in consumption,
investment, export of the final demand occurs.
Employment inducement coefficient is quantified
employment which is created either directly or indirectly in the
process of production. It stands actual employment needed to
create a unit of production in certain category of industry.
By multiplying the vector of final demand to coefficient
matrix respectively, Output value of each item of final demand,
amount of employment inducement can be estimated.
In this process, input coefficient is a parameter used to
induce the amount of effect on production inducement of
respective categories of industries when the final demand of
goods or services increased.
B. Multi Building MRIO model using RAS approach
In this research, the characteristics of metropolitan and Seoul
area’s Industry Input-Output Tables were analyzed using
production inducement coefficients. In order to do so, Industry
Input-Output Tables was created using RAS approach. The
Industry Input-Output Tables offered by the Bank of Korea was
created in the year of 2005 which made the data inappropriate
for the use. Therefore, based on the Industry Input-Output
Tables of 2005, RAS approach was applied to re-create
Industry Input-Output Tables of 2010.
C. Reason for using RAS approach
To have Industry Input-Output table completed, it take
minimum of two to three years to investigate actual economic
structure, therefore time delay in actual application is
unavoidable.
This delay of time cannot be undermined because of the
possibility of lacking accuracy if past input coefficients is used
to predict upcoming phenomena.
So the method to extend validity of Input coefficients matrix
used to long-term prediction and planning is need. In other
words, creating regional Industry Input-Output table to use in
regional economy analysis requires huge costs and time so
instead of direct survey indirect estimating method, RAS is
mostly used due to its accuracy.
The figure can be not as accurate as direct survey, but RAS
method can estimate input-output structure of a region
indirectly for the years, places, and particular industries that do
not have information on.
D. RAS approach
RAS approach is a regional input coefficient estimating
method. This method can be used when the national figure for
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certain year’s input coefficient table, each industries’ regional
total outturn of pertinent year, each industries’ total regional
intermediate demand and each industries’ total regional
intermediate input are given. Regional total outturn is
multiplied by the national input coefficient table and reverted to
trade table to find alternative change factors(r) and processing
change factors(s). The adjustment iterates until the subject
year’s industrial regional total intermediate demand and
regional total intermediate input converge.
E. Updating the Industry Input-Output Tables
This research also uses same 16 cities and provinces and 28
industries as the factor as the table from the Bank of Korea.
Using regional each industries’ intermediate input and
intermediate demand data and iteration adjustment of rows and
columns is done to estimate the regional input coefficients.
The adjustment of the row is to estimate the input coefficient
of 2010’s Industry Input-Output table through adjusting the
input coefficient of 2005’s Industry Input-Output table by
reflecting total intermediate input and the changes in rate of
added value. The adjustment of the column reflects alternative
effect of inputs caused by the changes in regional price of
production.
F. Current status of central administrative and public
institutions being moved out of Seoul
Total of 127 institutions currently located in Seoul, 30
central administrative institutions and 97 public institutions, are
planned to be relocated in Sejong-si and other inno-cities.
When sorted out by the types of industry that are being
relocated, 56 institutions are Public administration and defense,
4 institutions are Education, health and social work, 12
institutions are Finance and insurance, 1 institution is
Wholesale and retail trade, 8 institutions are electricity, gas,
water resources related, 46 institutions are Real estate and
business services.
G. Building final demand data
Due to the relocation of the central government and public
institutions final demand will be changed and this will bring
about changed in national industry. All productions of goods
and services occur to ultimately meet the consumptions,
investigations and exportations. In other words, a country’s
amount of produced goods and services are determined by the
structure or the amount of the final demand so the production
and final demand are in functional relations.
H. Change in the final demand due to the relocation of
central government and public institutions
The changes in the final demand of relocating central
government and public institutions are calculated using budget
expenditure of 2012. 102 institutions’ budget data among total
of 127 were collected. Some data of public administration,
military or social security related institutions, professional
science or technology service related institutions could not be
included. For missing data, the number was estimated by
multiplying the number of employees by the collected same
categories’ average budget per employ to calculate the final
demand after the relocation.
Labor costs and operating expenses are chosen to include in
the final demands. Working expenses are excluded since that is
fixed to pertinent region while labor costs and operating
expenses are practically affecting the regional economy.
Total of 15,378,298 million won of final demands are
leaving Seoul and this expenses are moved to Sejong-Si and
other inno-cities.
IV. RESULTS
The results of final demands and 2010 MRIO using RAS
approach are as follows:
A. Interpretation of coefficient
Production inducement coefficients indicates either direct
and indirect ripple effect on productivity caused by a unit
increase in final demand. Forward linkage effect can be
calculated through sum of rows of each category of industry,
and it indicates either direct and indirect ripple effect on
productivity in pertinent industry caused by a unit increase in
final demand for products in that industry. backward linkage
effect can be calculated through sum of columns of each
category of industry, and it indicates either direct and indirect
ripple effect on productivity in overall industries caused by a
unit increase in a final demand for a pertinent industry.
Calculated forward and backward linkage effect in Public
administration and defense industry along with Real estate and
business services of metropolitan area and Seoul, using
production inducement coefficients are stated below.
Public administration and defense industry in Seoul,
Transportation industry of Seoul, Petroleum and coal products
industry in metropolitan area and Wood and paper products
industry in Chungcheong will experience largest incline in the
production. Other industries in Seoul, Chemicals, drugs and
medicines industry in metropolitan area, Food, beverages and
tobacco products industry in metropolitan will contribute to the
incline of production.
Regionally, public administration and military industry in
Seoul shows Seoul(1.4869), metropolitan area excluding
Seoul(0.1586), Kyeongnam(0.0847) of backward linkage effect.
In case of forward linkage effect, Seoul(1.0302),
Chungcheong(0.0199) and Jeonra(0.0183) are shown.
Excluding Public administration and defense industry in
Seoul, regionally analyzed backward linkage effect showed
Dummy sectors in Seoul(0.1231), Chemicals, drugs and
medicines industry in metropolitan area(0.0189) and Food,
beverages and tobacco products industry in metropolitan
area(0.0150).
Industries that generate significant forward linkage effect to
Public administration and defense industry in Seoul were
Transportation industry(0.0116), Petroleum and coal products
industry in metropolitan area(0.0012), Wood and paper
products industry in Chungcheong(0.0011).
Real estate and business services industry in Seoul will earn
largest increase on product due to the increase in the
communication and broadcasting industries’ production of
Chungcheong, Jeonra, Kyeongnam area. Also the
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communication and broadcasting industry will attribute to the
increase of Electronic and electrical equipment industry in
metropolitan area.
Regionally, Real estate and business services industry in
Seoul will bring backward linkage effect to Seoul(1.4287),
metropolitan area excluding Seoul(0.1542) and Kyeongnam
(0.0729), and in the case of forward linkage effect
Chungcheong(5.5799), Kyeongnam(5.0998) and
Jeonra(5.0373) showed largest numbers.
Excluding real Real estate and business services of Seoul,
regionally analyzed backward linkage effect of industries
showed highest figure in Communication and broadcasting
industry in Seoul(0.0729), followed by Finance and insurance
industry in Seoul(0.0692) and Electrictity, gas, steam and water
supply industry in metropolitan area(0.0316).
Industries that generate most forward linkage effect to the
Real estate and business services of Seoul were the
Communication and broadcasting industry in
Chungcheong(0.4305), the Communication and broadcasting
industry in Jeonra(0.4101) and the Communication and
broadcasting industry in Kyeongnam(0.3985).
Increase in production of Public administration and defense
industry in Seoul and Wood and paper products industry in
Chungcheong attribute the most to the effect of increasing
production, and also attribute to other industries in metropolitan
area, Finance and insurance industry in Seoul and the Real
estate and business services industry of Seoul.
Regionally, the Public administration and defense industry in
Seoul bring about the largest backward linkage effect to the
metropolitan area excluding Seoul(2.6712) followed by
Seoul(0.4023), Kyeongnam(0.2851), and bring about the
largest forward linkage effect to the metropolitan area(2.6712),
Chungcheong(0.0135), Jeonra(0.0115).
Excluding Public administration and defense industry in
Seoul, regionally analyzed backward linkage effect of
industries showed highest figure in Dummy sectors in
metropolitan area(0.1322), followed by and Finance and
insurance industry in Seoul(0.0958) and the Real estate and
business services industry in Seoul(0.0913).
Industries that effect most forward linkage effect to the
public administration and military industry of the metropolitan
area were the Dummy sectors in metropolitan area(0.0183),
Transportation industry in metropolitan area(0.0129) and the
Wood and paper products industry in Chungcheong(0.0008).
Increase in production of Wholesale and retail trade industry
in metropolitan area other industries in metropolitan area,
Precision instrument industry in Kyeongnam will attribute the
most to the Real estate and business services industry in the
metropolitan area, and also attribute to Finance and insurance
industry in metropolitan area, Real estate and business services
industry of Seoul and Finance and insurance industry in
metropolitan area.
Regionally, the Finance and insurance industry in
metropolitan area brings about the largest backward linkage
effect to the metropolitan area(2.6337) followed by
Seoul(0.5086), Kyeongnam(0.1497), and bring about the
largest forward linkage effect to the metropolitan area(4.6625),
Kyeongnam(1.8385) and Chungcheong(1.8216).
B. Ripple effects on each industry in Seoul
The results of the amounts of production inducement of
industries in Seoul using MRIO are stated in the table below.
It can be predicted that most of the amount of production will
decrease due to the change in the final demand. Especially,
electricity, gas and water resource industry will experience
decrease of 3,989,949 million won, followed by financial and
insurance industry of 1,657,015 million won and real estate
market and enterprise services industry of 1,168,461 million
won.
Total changes in production of Seoul due to the relocation is
about 0.74% compare to the sales account of 2010(statistics in
Seoul and National Statistical Office did not provide the
amount of production of industries in Seoul for 2010 therefore
substituted with sales account of industries in Seoul for 2010).
Also considering the relocating institutions that did not provide
the budget data, 0.74% of 2010’s Seoul’s total sales account
will be discharged. 1.15% of decrease in real estate market and
TABLE I
AMOUNT OF PRODUCTION INDUCEMENT
Name of sector Outflows
(Won)
Inflows
(Won)
Amount of
production
inducement (Won)
Agriculture, forestry and fishing -11,407 8,366 -3,041
Mining and quarrying -17,730 6,562 -11,167 Food, beverages and tobacco
products -18,575 4,710 -13,865
Textile and apparel -28,061 38,388 10,327 Wood and paper products -4,385 3,034 -1,351
Printing and reproduction of
recorded media -24,098 14,667 -9,431
Petroleum and coal products -3,012 2,570 -442
Chemicals, drugs and
medicines -18,011 10,145 -7,866
Non-metallic mineral products -1,336 647 -689
Basic metal products -7,721 7,099 -621
Fabricated metal products except machinery and funiture
-3,900 4,816 916
General machinery and
equipment -6,189 9,107 2,918
Electronic and electrical
equipment -24,180 27,150 2,970
Precision instruments -6,711 10,196 3,485 Transportation equipment -653 639 -14
Precision instruments -11,362 5,042 -6,320
Furniture and other manufactured products
-4,006,424 16,475 -3,989,949
Construction -32,400 25,021 -7,379
Wholesale and retail trade -153,273 97,147 -56,126 Accommodation and food
services -209,602 39,291 -170,311
Transportation -119,796 68,962 -50,833 Communications and
broadcasting -234,649 119,893 -114,756
Finance and insurance -1,884,142 227,127 -1,657,015 Real estate and business
services -1,602,503 434,041 -1,168,461
Public administration and defense
-2,359,420 879 -2,358,542
Education, health and social
work -72,898 10,353 -62,546
Other services -38,599 21,573 -17,026
Dummy sectors -429,175 36,459 -392,717
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enterprise services industry is predicted.
The calculated results of employment inducement in Seoul
using MRIO model are stated below.
Due to the changes in the final demand, most of the
employment inducements are decreasing. public administration
and military industry shows the largest decrease in number of
employments, 17,385 jobs, followed by real estate market and
enterprise services industry, 8,476 jobs, and financial and
insurance industry, 7,452 jobs.
V. CONCLUSION
Changes in the final demand due to the relocation of central
government and public institutions were calculated using the
2012 budget expenditure of relocating institutions. Through
that effect on production inducement and effect on employment
inducement were also calculated. Also the riffle effects on
R&D of Seoul were analyzed using examining the effects on
research institutions which are under the real estate market and
enterprise services industry.
The results were compared with the research done by Kim
EinHee (2005) which also used MRIO model to examine the
changes in production and employment. As the result, the final
demand shows twice the difference. The reason for the gap is
that this research considered 5.96 trillion won as the total, the
operating expenses(3.76trillion won) and the labor
costs(2.2trillion won), while Kim considered 3.12trillion won
as the total including the expenses cost(1.22trillion won), local
taxes(0.13trillion won), and the labor costs(2.2trillion won).
In this research, when the relocation occurs operating
expenses are considered also to be moved to pertinent region
therefore included the operating expense of institutions, which
led to the gap in the change in final demand with Kim. The
decrease and increase in the amount of production estimated
using the MRIO, and net change also showed twice of
difference in the number. In case of employment, both
researches predicted decrease of about 50 thousand jobs. Even
though the final demand differs largely in number the
employments show little change. This can be explained by the
fact that industry that consists the largest portion of the final
demand, the electricity, gas, and water resources industry
shows fairly low employment inducement coefficients when
comparing to other industries. Also Kim EinHee (2005) did not
consider the relocation of the Electricity, gas, steam and water
supply industry.
The results of analysis in this research only considered the
effects of relocation of administrative offices and public
institutions. There will be other effects if new industries appear
after the relocation. In order to maintain current industry
structure in Seoul, more proper application plan should be
suggested.
REFERENCES
[1] Kim. K. S, “The forecast and the effects of the Public Institution
relocation”, Journal of the Urban Problems, 2004
[2] Kim. K. I, Seo. T. S, Kim. T. W, Byun. P. S, Yoon. Y. M, “In accordance with the Public Institution relocation, Metropolitan Policy Research”,
Korea Research Institute for Human Settlements, 2012
[3] Kim, K. S, “Estimating the Economic Impacts of the District Transfer of Public Institutions in Gyeonggi Province”, Gyeonggi Research Institute,
2005
[4] Kim. S. W, Kwon. Y. D, “Changes in Population and Function of Seoul through the Relocation of Public Organizations and Residential
Developments in the Capital Region”, The Seoul Institute, 2012
[5] Kim. E. H, “The Effect of relocation of Public Institution analysis”, The Seoul Institute, 2005
[6] Kim. T. K, “A Study for the Impacts of Public Agencies’ Relocation”,
Gyeonggi Research Institute, 2013 [7] Kim. H. S, “Integrated Urban Management in Seoul Metropolitan
Region”, Gyeonggi Research Institute, 2006 [8] Park. S. W, Kim. S. W, Park. H. S, “The Socio – Economic Impact
Analysis on the Construction of New Capital in Korea”, Korea Research
Institute for Human Settlements, 2003 [9] Song. G. Y, Kim. E. J, “The Effect of Relocation of Public Agencies on
National and Regional Products”, The Seoul Institute, 2007
[10] Song. G. S, Lee. G. S, “Economic Ripple Effects of Public Institutions to Local Moving: Focused on the Daegu and Gyeongbuk Areas”, Korean
Association for Policy Sciences, 2007
[11] Lee. H. R, “A study on the job creation effects in Korea's large areas by the government investment”, Master Paper, Chunnam University, 2009
TABLE Ⅱ
AMOUNT OF EMPLOYMENT INDUCEMENT
Name of sector Outflows
(Won) Inflows (Won)
Amount of
production inducement
(Won)
Agriculture, forestry and fishing -5 4 -1
Mining and quarrying -92 33 -59
Food, beverages and tobacco
products -1,504 381 -1,123
Textile and apparel -656 897 241 Wood and paper products -408 282 -126
Printing and reproduction of
recorded media -265 161 -104
Petroleum and coal products 0 0 0
Chemicals, drugs and
medicines -42 24 -18
Non-metallic mineral products -5 2 -4
Basic metal products -7 6 -1
Fabricated metal products except machinery and funiture
-27 34 7
General machinery and
equipment -26 39 14
Electronic and electrical
equipment -59 65 6
Precision instruments -44 67 23 Transportation equipment 0 0 0
Precision instruments -102 46 -56
Furniture and other manufactured products
-5,645 23 -5,622
Construction -283 217 -66
Wholesale and retail trade -2,063 1,308 -755 Accommodation and food
services -3,977 745 -3,232
Transportation -1,167 672 -495 Communications and
broadcasting -1,926 984 -942
Finance and insurance -8,472 1,021 -7,452
Real estate and business
services -11,625 3,149 -8,476
Public administration and
defense -17,392 7 -17,385
Education, health and social work
-980 139 -841
Other services -416 233 -182
Dummy sectors -2,342 199 -2,143
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