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 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 B 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, 130
3rd International Conference on Management, Behavioral Sciences and Economics Issues (ICMBSE'2014) Feb. 11-12, 2014 Singapore 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. 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 increased. 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. 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. 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. a ij ij Xj 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. ij: industry i s input to the industry j X j : 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 D. RAS approach RAS approach is a regional input coefficient estimating method. This method can be used when the national figure for This can be expressed in forms of a matrix. 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. 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 occur to ultimately meet the consumptions, investigations and exportations. In other words, a country s amount of produced goods and 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 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 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 132
communication and broadcasting industry will attribute to the increase of Electronic and electrical industry in metropolitan area. Regionally, Real estate and business 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 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 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 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 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 industry in the metropolitan area, and also attribute to Finance and insurance industry in metropolitan area, Real estate and business 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 TABLE I AMOUNT OF PRODUCTION INDUCEMENT Name of sector Outflows Inflows Amount of production inducement 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 -6,189 9,107 2,918 Electronic and electrical -24,180 27,150 2,970 Precision instruments -6,711 10,196 3,485 Transportation -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 -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 -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 -38,599 21,573-17,026 Dummy sectors -429,175 36,459-392,717 insurance industry of 1,657,015 million won and real estate market and enterprise 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 133
enterprise 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 industry, 8,476 jobs, and financial and insurance industry, 7,452 jobs. Name of sector TABLE Ⅱ AMOUNT OF EMPLOYMENT INDUCEMENT Outflows V. CONCLUSION Inflows Amount of production inducement 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 -26 39 14 Electronic and electrical -59 65 6 Precision instruments -44 67 23 Transportation 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 -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 -11,625 3,149-8,476 Public administration and defense -17,392 7-17,385 Education, health and social work -980 139-841 Other -416 233-182 Dummy sectors -2,342 199-2,143 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 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 134