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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130

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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131

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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