KIET Occasional Paper No. 70
The Effect of Transportation on City Distribution： DoesKorean Korean Train Express Industrial and Daejeon Policy Work?
Dongsoo Kim
May 2008 Dongsoo Kim, Associate Research Fellow Korea Institute for Industrial Economics and Trade(KIET)
All Rights Reserved by Korea Institute for Industrial Economics and Trade(KIET) 66 Hoegiro, Dongdaemun-Gu, Seoul, 130-742, Korea TEL：(82)(2)3299-3114 FAX：(82)(2) 963-8540 http：//www.kiet.re.kr ISBN 978-89-5992-180-5 93320 i
Contents
Ⅰ. Introduction ························································································ 1
Ⅱ. The Effect of Express Rail Service on City Size ····················· 5 1. Express Rail Service ············································································· 7 2. Changes in Japanese City Size by Shinkansen ································· 9 3. Changes in French City Size through the Train a Grande Vitesse(TGV) ·········································································· 10 4. Changes in Germane City by the Inter City Express(ICE) ············ 12
Ⅲ. Theoretical Analysis of Transportation on City Size ············· 15 1. Iceberg Type Price and City Size ····················································· 17 2. Old Economic Geography(OEG) model ·············································· 18 3. New Economic Geography(NEG) model ············································ 19
Ⅳ. Changes in City Size after KTX Opening ································ 21 1. Introduction ·························································································· 23 2. Cities located at both ends of the Gyungbu KTX line (Seoul and Busan) ··············································································· 24 3. Cities located in the middle(Daejeon) ················································ 26 4. Cities located at the Center with New KTX stations (Gwangmyeong, Cheonan-Asan) ························································ 29 5. Population Change Analysis with Moran I ······································· 31
Ⅴ. Summary and Policy Implications ··············································· 35 1. Summary ······························································································ 37 2. Policy Implications ··············································································· 38
References ································································································· 41
Table Contents
Table 1. World Express Rails ····································································· 8 Table 2. Passenger Traffic by Year(except Seoul Metro Subway) ···· 23 Table 3. Population in Administrative Metropolitan Cities(thousands) 25 Table 4. Population in MSAs(thousands) ················································ 26 Table 5. Employees in Manufacturing Industry(thousands) ·················· 28 Table 6. Population Changes in MSAs(thousands) ································ 29 Table 7. Exports by MSA($ million) ······················································ 30 Table 8. Large MSAs along with KTX line ············································ 43
Figure Contents
Figure 1. Shinkansen in Japan ····································································· 9 Figure 2. France TGV ················································································ 10 Figure 3. Germany’s ICE ··········································································· 12 Figure 4. Iceberg Type Price ··································································· 17 Figure 5. Marginal Transportation Cost Decreases and Market Size Changes 1 ····························································· 18 Figure 6. Marginal Transportation Cost Decreases and Market Size Change 2 ····························································· 20 Figure 7. LISA Cluster Map ······································································ 33 Figure 8. Express Rails and Highways ···················································· 39 Figure 9. KTX stops(Gyungbu line) and Korean MSAs ························ 44 1
Ⅰ Introduction 3
Ⅰ. Introduction
Since the Korean War, economic activity has been heavily concentrated in Seoul, which has increased the economic gap between Seoul and other areas. Thus, balanced national land development has become an urgent regional policy issue. Obviously, infrastructure investment plays in a key role in regional policy. Recently, Korea has built an express rail, called the KTX(Korea Trail Express), from Seoul to Busan. Nevertheless, the effect of the KTX on the population of Daejeon, located on the middle of the KTX line, is not sufficient. Duranton and Turner(2007) found that a 10% increase in road stock increased the population by 2%. In general, infrastructure investment such as transportation gives rise to more urban concentration by improving the accessibility to and interaction among cities. Thus, reduction of transportation costs is crucial to the manufac turing industry as it creates market expansion. As a result, the beneficiary, the city’s population, increases. For example, according to the US Census 2000, the following Metropolitan Statistical Areas(MSA), located at the crossroads of interstate highway and railroads, or those that have hub airports, have a large population：Chicago(9.2 million), Houston(4.7 million), Dallas(5.2 million), Atlanta(4.1 million), and Phoenix(3.3 million). This urban concentration through improvement in infrastruc ture appears not only in USA but also in Korea. 4
In fact, the Korean Trail Express(KTX) made daily travel possible in Korea by reducing the travel time from Seoul to Busan to 2 hours 40 minutes. In a situation where chronic traffic congestion in highways raises time costs, transportation improvements such new express trains and highways affect cities’ populations. Many cities having an express train stations in France and Japan have significant population concentration from nearby small cities where express trains do not stop. In Korea, heavier population concentrations arise in Seoul’s metro politan area than other areas. Then, it is necessary to scrutinize the population change in Daejeon as a nodal hub of highways and roads in Korea. Furthermore, the effect of the KTX on its population will be assessed, which can serve as a guide for more balanced national land development. In the second chapter, the literature related to express railroad construction and changes in city size in Japan, France, and Germany is reviewed. The third chapter covers the economic geographical theory model that explains the effect of transporta tion improvements on cities located at the edge of transportation nodes and cities located in the middle of the nodes. Next, the passenger share of the KTX established in April of 2000 is estimated. Furthermore, the impact of the KTX on the city’s population structure by comparing the size of the city before and after KTX construction is explored. Last, the relationship between transportation and city population is considered which is meaningful to regional development policy. 5
Ⅱ The Effect of Express Rail Service on City Size 7
Ⅱ. The Effect of Express Rail Service on City Size
1. Express Rail Service
Japan’s first country‐run express rail service launched in 1964 has the longest express railroad, 1,863km (see Table 1). France, Germany, Italy, and Spain followed in the 1980s and 1990s. Recently, Asian countries including Korea, Taiwan, and China along with Russia are racing to develop express rails. Some countries such as Germany, Belgium, and Finland run express rails alongside conventional railroads. Each country’s railroad network is different. For example, Japan and Taiwan have straight line networks which means there two ending nodes, while Germany has the same straight line type of express railroad but its railroad network includes radial type railroads like France. The key economic cities are located at the center of these railroad networks. Tokyo is at the middle of the straight express railroad line. Paris, Hannover, and Frankfurt are centers for radial express railroad networks. Milano is located at the cross of the T-shape of Italy’s express railroad network. On the other hand, Korean economic centers, Seoul and Busan, are located at both ends of a tripod express railroad. Taiwan has the same type of economic center as Korea. Taipei is at the end of the straight line type railroad 8 network. In general, the improvement of transportation infrastructure brings about population increases in the transportation hub cities but population decreases in cities around the transpor tation hub cities. Due to improved accessibility, cities at the ends are also beneficiaries of lower transportation costs. Accor dingly, small cities around the metropolitan areas are subsidized not only in population but economically.
Table 1. World Express Rails
Length Max Speed Country Range Starting Year (km) (km/h) Korea(KTX) Seoul-Busan 412 2004 300 Japan(Shinkansen) Tokyo-ShinOsaka 515 1964 270 ShinOsaka-Hakata 554 1972, 1975 240 Omiya-Morioka 497 1982, 1985, 1991 240 Omiya-Niigata 270 1982 275 France(TGV) Paris-Lyon 426 1981 270 Paris-LeMans, Tours 280 1989, 1990 300 Paris-Lille, Calais 333 1993 300 Germany(ICE) Hannover-Wurzberg 327 1988 280 Mannheim-Stuttgart 100 1991 280 Spain(AVE) Madrid-Sevilla 471 1992 270 Italy(ETR) Tulin-Venice 330 1994 300 Milano-Napoli 735 1981 300 Taiwan(THSR) Taipei-Kaohsiung 345 2007 315 China Beijing-Shanghai 1330 2008 300 Source：Ministry of Construction and Transportation (http://www.moct.go.kr), Korea Railroad Corporation (http://www.korail.go.kr) Ⅱ. The Effect of Express Rail Service on City Size 9
2. Changes in Japanese City Size by Shinkansen
According to Abe(2007), the Shinkansen triggered Japanese urban development. Since the Shinkansen reduced travel time, it made Tokyo, Nagoya, and Osaka a daily commute for many economic areas. As a result, the number established in Morioka increased 1.49 times. Nikata was also included in the Nakaoka regional economic metropolitan area through lower commuting and transportation costs(Kim, 1995). However, the central function in Nagoya was weakened, because of urban sprawl in Osaka, the metropolitan area was expanded into a regional economic area(Chun et al. 2004). Two major Japanese city population changes were observed. First, the cities on the Shinkansen line grew at a faster rate
Figure 1. Shinkansen in Japan
Hokkaido
Akita Niigata Nagano Shinjo
Hachinohe Takasaki Morioka Hakada Osaka Nagoya Fukusima Omiya Tokyo Shinyatsusiro planned Gagoshima
Source：Eastern Japanese Rail(http://www.jrest.co.jp) 10 than the national average. Second, more precisely, even though small cities are on the Shinkansen line, their population could not increase without investment around the stations. To summa rize, most cities on the Shinkansen line became metropolitan areas. However, because of the location advantage shown in Figure 1, Tokyo became concentrated more heavily than before, which became an issue of simple “mono concentration”.
3. Changes in French City Size through the Train a Grande Vitesse(TGV)
Basically, the effect of the express rail on city size in France is the same as in Japan. Cities where the TGV stops grew overall, while small cities collapsed without investment even
Figure 2. France TGV
Calais Lille
Paris
Lemans
Lyon Tours
Marseille Source：http://www.sncf.com Ⅱ. The Effect of Express Rail Service on City Size 11 though they were on the line. As seen in Figure 2, the capital city, Paris, is located at the center of the TGV network and thus it has grown further. Due to easier and shorter commuting times, people even commute from Calais, Lille, and Le Mans. Thus, Paris is becoming more concentrated even with the government’s decentralization policies of relocating certain government departments1). Lille, with a population of approximately one million is located at the end of the TGV railroad’s network. However, being close to Brussels in Belgium, it connects to regular railroads. Therefore, Lille is the economic center and has enjoyed ongoing expansion(Cho et al 2005). At the end nodals, Lyon and Le Mans have been developed with airports, highways, and express rails, which have boosted regional development(Chun, 2004). The Lyon‐ Satolas Airport Railway is a good example of logistical complex development. In addition, real estate prices have gone up drastically in Le Mans after express rail construction. On the other hand, some cities such as Le Creusot and Macon located between Paris and Lyon did not experience any benefit from new express rail stations because there was no development around the stations(Korea Land Corporation, 2005).
1) According to World Development Indicators, the population share of Paris has been steady：16.47%(8.9 million) in 1980 and 16.46% (9.7 million)in 2000. 12
4. Changes in Germane City by the Inter City Express(ICE)
It is difficult to analyze the effects of the ICE express rail on city size in Germany compared to other countries because the main factor of migration was unification in 1989 rather than the ICE in 1991. Nevertheless, Zumkeller(2003) assesses that economic conditions have improved in rural areas due to the express rail opening that connected with the European railroad network.
Figure 3. Germany’s ICE
Hannover Berlin Dusseldorf
new rail Bonn
Frankfurt
Mannheim Wurzburg
Stuttgart
Munchen Source：http://www.railfaneurope.net Ⅱ. The Effect of Express Rail Service on City Size 13
As an inner harbor city, Düsseldorf grew to the ninth largest city in Germany in 2006. As the center of the harbor and highway, it was the heart economic development on the Rhein River. After the express rail opened, the main industries changed from traditional manufacturing industries to tertiary industries such as finance. Frankfurt also has been reborn as the logistical hub with its international airport and express rail. Because of the location advantage, not only financial, but also that about 6,500 traditional manufacturing establishments play a vital role in its regional economy. 15
Ⅲ Theoretical Analysis of Transportation on City Size 17
Ⅲ. Theoretical Analysis of Transportation on City Size
1. Iceberg Type Price and City Size
Most manufacturing production prices(P) consist of an average cost(AC) and transportation cost(tx). In general, the trans portation cost is the product of the distance(x) and constant marginal transportation cost(t). Therefore, the production price increases with the distance to the final demand destination and thus there is zero demand at a certain distance because of high transportation costs. This kind of product price is called an iceberg type.
P=AC+tx (1)
In equation (1), the iceberg type price produced in the Central
Figure 4. Iceberg Type Price
P=AC+tx
AC { x A 18
Business District(CBD) in city A is the sum of average cost and transportation cost which increases at a constant rate as in Figure 4.
2. Old Economic Geography(OEG) model
According to the Old Economic Geography(OEG) model, an improvement in transportation causes a smaller number of large cities. In Figure 5, the same has been produced in three different locations(A, B, C) and thus the market size of those cities is expressed by the market radius(rA, rB, rC)2) respectively. When infrastructure investment increases or improvement in transportation causes the marginal transportation cost(t) to decrease, the slope in Figure 5 becomes flatter. For example,
Figure 5. Marginal Transportation Cost Decreases and Market Size Changes 1
P=ACC+tcx
P=ACC+tc'x
ArA BCrB rC
2) Constant Elasticity of Demand is assumed. Ⅲ. Theoretical Analysis of Transportation on City Size 19 if an express rail opens in cities A, B, and C, then the marginal transportation costs tA, tB, tC decline to tA', tB', tC'. Accor dingly, since the production price falls(PB>PA, PB>PC), the market demand increase in cities A and C only because the average cost in city B is the highest. Finally, the economy of city B is absorbed into the economies of in cities A and C.
3. New Economic Geography(NEG) model
Unlike the OEG, the New Economic Geography(NEG) model depends on the changes in fundamentals through transportation cost decreases. When the marginal transportation cost decreases due to a new highway or express rail opening, it causes changes in the average cost. For example, as assumed in the OEG model, a new express rail opening brings more advantage to city B compared to cities A and C because of its location, which makes the average costs in city B decrease(ACB' Figure 6. Marginal Transportation Cost Decreases and Market Size Change 2 P=ACC+tcx ACB' ACrA'rB B'rC' 21 Ⅳ Changes in City Size after KTX Opening 23 Ⅳ. Changes in City Size after KTX Opening 1. Introduction Based on the previous economic geographic models, it is necessary to analyze the changes in city size by the improvement in transportation for balanced national land development. Currently, the passenger share of express rail increased rapidly after the KTX opening in 2004(see Table 2). About 32% of train passengers used the KTX in 2006. That number will rise even more after the Honam KTX line opens in 2019. According to Ministry of Construction and Transportation data, changes in the number of train passengers between 2000 and 2005 ranged from 6.04% to 8.06% but the changes in passengers Table 2. Passenger Traffic by Year(except Seoul Metro Subway) Year Passengers KTX Passengers (%) 2000 115,913,653 2001 117,617,989 2002 109,934,953 2003 105,524,031 2004 111,214,330 19,791,607 17.8 2005 115,002,291 32,103,698 27.9 2006 114,331,456 36,016,990 31.5 Source：Korea Transport Database(http://www.ktdb.go.kr) 24 per distance has not changed much. Chun(2004) anticipated that the KTX would expand the Seoul metropolitan area as far as Cheonan-Asan in the long term, because cities located in the northern part of Chungcheong provinces are going to be absorbed into the Seoul metropolitan area due to the improved accessibility. In addition, Cho(2003) and Lee(2006) assessed the positive effect of the express rail on the population in Daejeon, even though the reason is unclear. Therefore, in the next sections, population changes will be compared to city locations：cities such as Seoul and Busan located at the both ends of the KTX rail network, cities located in the middle, and cities such as Gwangmyeong, Cheonan, and Asan located in the middle, but only having newly opened express rail stops. 2. Cities located at both ends of the Gyungbu KTX line(Seoul and Busan) The Korean Census of 2000 and 2005 showed that Seoul’s population has not changed much during the years before and after the Gyungbu(Seoul-Busan) KTX line opened. Interestingly, the population in Busan has fallen by 3.8%. It is difficult to analyze the net effect of the KTX on the population in Seoul and Busan, because of the urban sprawl in Seoul. Therefore, Seoul’s suburban population increased signifi cantly, but not in its administrative area. Thus, it is necessary to redefine the geographic area, to something like a Metropolitan Ⅳ. Changes in City Size after KTX Opening 25 Table 3. Population in Administrative Metropolitan Cities (thousands) 2000 2005 rate(%) Seoul 9,895 9,820 -0.76 Busan 3,663 3,524 -3.80 Daegu 2,481 2,465 -0.65 Incheon 2,475 2,531 2.27 Gwangju 1,353 1,418 4.80 Daejeon 1,368 1,443 5.46 Ulsan 1,014 1,049 3.43 Nation 46,136 47,279 2.48 Source：Census 2000, 2005 (http://www.nso.go.kr) Statistical Area(MSA) as in the United States. Therefore, in this paper, Korean MSAs are redefined by their accessibility to metropolitan cities estimated by their commuting rate, which is detailed in Appendix Table 8. According to Appendix Table 8, 18 cities in Gyeonggi province were included in the Seoul MSA；Gimhae and Yangsan were reclassified into the Busan MSA. The change in population is different from the definition of area. In MSA terms, the population of Seoul increased more than the national population(see Table 4). Seoul’s population grew by 5.47%, which was more than twice the national rate of 2.48%. In addition, Kim (2007) found that reverse commuting from Seoul to suburban Gyeonggi province steadily increased also3). Strong evidence of urban sprawl was lack of population 3) Kim(2007) found that the reverse commuting rate in Seoul was 26 Table 4. Population in MSAs(thousands) MSA 2000 2005 rate(%) Seoul 15,765 16,627 5.47 Busan 4,187 4,173 -0.34 Daegu 2,709 2,707 -0.07 Incheon 2,462 2,519 2.32 Gwangju 1,452 1,505 3.62 Daejeon 1,533 1,600 4.38 Ulsan 1,014 1,049 3.43 Nation 46,136 47,279 2.48 increase in the previous administrative area of Seoul. However, the population in Busan has stagnated over time. This was due in part because Busan, a logistical hub city, did not take advantage of its location as did Masan, Changwon, and Gumi, specialized mid‐size cities close to Busan. Again, it is difficult to say that the KTX was the critical reason for the expansion in the Seoul MSA as it did not affect the size of the Busan MSA. 3. Cities located in the middle(Daejeon) Cho(2003) reported in the Korea Research Institute for Human rising from 5% in 1980, 7% in 1990, 10% in 1995, to 11% in 2000 from the commuting pattern analysis. In addition, the reverse commuting rate in Busan was also rising from 2%, 4%, 6%, to 7%at the same time periods. Therefore, he explained this as urban sprawl. Ⅳ. Changes in City Size after KTX Opening 27 Settlement survey, that there were few companies and commuters that planned to move to Daejeon after the KTX opened. So, he expected that the effect on the population of Daejeon was not great. According to his simulation results, a population increase of 728 was projected for Daejeon, while Busan would increase by 2000. Interestingly, Osong located just outside of Daejeon and the area transit station of Honam and Gyungbu KTX lines had a population decreased. Lee et al(2003, 2006) proved that there is not one single measurement for city size. Nevertheless, he reported that the number of establishments was stable and the office vacancy rate dropped slightly since 2004, which could be interpreted positively in Daejeon. Lee et al (2004) insisted there was a direct effect from the express rail on tran sportation costs, which covers about 15% of final product prices. According to Tables 3 and 4, the population in Daejeon increased by 5.46% and 4.38% respectively, which is much higher than the national population increase of 2.48%. As Lee et al(2004) pointed out; it is difficult to say that the KTX played a key role in the population increase in Daejeon. It is also possible that the improvement in transportation infras tructure around Daejeon such as the Daejeon‐Tongyoung highway (2001) and Youngdong highway expansion(2001) affected the population increase, because the accessibility to east coast and south coast is improved. To summarize, Daejeon’s expansion interpreted with a NEG model shows that the improvement in transportation decreases both transportation and production costs, which causes a population increase. Because the manufacturing industry is the biggest beneficiary 28 from transportation cost reductions, it is necessary to verify the effect of transportation improvements on the population increase by scrutinizing the share of employees in the manu facturing industry .Unfortunately, the share of employees in the Daejeon MSA’s manufacturing industry was the smallest among the seven MSAs in 2000 and 2005(see Table 5). Further more, the share in the Daejeon MSA declined from 13.9% to 12.2%, while the shares in Gwangju and Ulsan rose. The population in the Daejeon MSA of approximately 1.6 million has a localized rather than urbanized economy. So it seems that the 12.2% of manufacturing industry employment is relatively small. Therefore, it seems that the regulations in the Seoul MSA and the government’s proposed relocation to Yeongi in Chungcheong province, which was based on a balanced national land policy, appear to be the actual factors in the popula Table 5. Employees in Manufacturing4) Industry(thousands) 2000 2005 MSA tot emp mfg emp (%) tot emp mfg emp (%) Seoul 6,241 1,344 21.5 6,704 1,1733 17.5 Busan 1,539 388 25.2 1,573 353 22.4 Daegu 976 256 26.3 995 232 23.3 Incheon 954 300 31.4 989 266 26.9 Gwangju 516 77 14.8 564 89 15.7 Daejeon 561 78 13.9 607 74 12.2 Ulasn 391 150 38.4 418 167 39.9 Nation 18,456 3,923 21.3 19,277 3,804 19.7 Source：Census 2000, 2005 (http://www.nso.go.kr) 4) Census two-digit industry classification Ⅳ. Changes in City Size after KTX Opening 29 tion increase in the Daejeon MSA. Table 5 illustrates that Daejeon’s population was supposed to increase more than it was actually did. In addition, the indu strial structure in the Daejeon MSA was problematic, because it did not gain the location advantage. Therefore, to maintain the population size, it is more efficient to attract manufacturing firms to Daejeon MSA for the domestic market. 4. Cities located at the Center with New KTX stations(Gwangmyeong, Cheonan-Asan) In Cho’s(2003) simulation, it is predicted that the population inflow to Gyeonggi province including Gwangmyeong would be 1431 by express rail, while population outflow from Osong, which has a KTX transit station. Even though Gwangmyeong and Osong have newly opened KTX stations, Gwangmyung would be absorbed into the Seoul MSA and Osong would be Table 6. Population Changes in MSAs(thousands) MSA 2000 2005 rate(%) Seoul 15,765 16,627 5.47 Gwangmyeong* 334 320 -4.14 Cheonan* 418 522 24.90 Asan* 181 208 15.30 Cheonan-Asan 599 730 22.00 Daejeon 1,533 1,600 4.38 Nation 46,136 47,279 2.48 * Administrative cities 30 included in the Daejeon MSA, because they are located very close to the large MSAs. Table 6 shows that there might be a different pattern among cities located in the middle of the express rail network. For example, Gwangmyeong shrank as expected because of its inclusion into Seoul’s MSA after the KTX opening. On the other hand, Cheonan-Asan and Daejeon expanded. Cheonan-Asan MSA experienced 22% population increase at the same time. There are two possible important reasons for this population increase. First, the transportation infrastructure has been im proved：opening the express rail(2004), Nonsan-Cheonan highway (2002), and the Youngdong highway expansion(2001). The second is the distance between the Cheonan-Asan MSA and Seoul MSA, which is not commutable either in time or cost. For these reasons, the Cheonan-Asan MSA was developed indepen Table 7. Exports by MSA($ million) MSA 2000 (%) 2005 (%) Seoul 42,111 24.4 44,719 15.7 Busan 6,532 3.8 9,748 3.4 Daegu 3,232 1.9 3,892 1.4 Incheon 7,537 4.4 13,040 4.6 Gwangju 3,200 1.9 7,217 2.5 Daejeon 895 0.5 2,273 0.8 Ulsan 19,972 11.6 45,182 15.9 Suwon-Hwaseong-Osan 12,076 7.0 12,307 4.3 Cheonan-Asan 12,666 7.4 27,529 9.7 Total 83,479 62.8 126,071 58.3 Nation 172,268 284,419 Source：Korea International Trade Association(http://www.kita.go.kr) Ⅳ. Changes in City Size after KTX Opening 31 dently from the Seoul MSA(see Table 6). The improvement in accessibility is a significant location advantage in for the Cheonan-Asan MSA. Thus, it seems that many manufacturing export industries relocated to that MSA. Table 7 shows that the share of exports from the Cheonan-Asan MSA rose from 7.4% in 2000 to 9.7% in 2005. Exports in dollar terms have more than doubled. On the other hand, the export share from the Suwon-Hwaseong-Osan MSA declined, partially because of the relocation of firms to the Cheonan-Asan MSA due to increased land prices and transportation costs in the Suwon-Hwaseong-Osan MSA. Then, there is a policy implication issue that the active regional economy around the Cheonan-Asan MSA was supposed to be in Daejeon, which had better conditions in terms of a balanced national land development including city size, infrastructure, and location which is mentioned in the next chapter. 5. Population Change Analysis with Moran I To scrutinize the population change before and after the KTX opening, spatial autocorrelation is considered by the Moran I index. Moran I is a ratio of the weighted cross product of differences to the variance, which is expressed as： (2) 32 where N is the number of regions and wij is the weight. Therefore, if the values in neighboring areas are similar, the Moran I will be positive. This could be interpreted that those areas are clustered. The closer the value is to 1, the more clustered. On the other hand, if values are dissimilar, then the Moran I will be negative, meaning both neighboring areas are dispersed in terms of the variable. However, since the Moran I is a global index, the Local Indicator of Spatial Association (LISA) shown in equation (3) is more appropriate to determine how a certain area is auto-correlated locally. (3) where n is the number of local regions. By LISA, regions with High-High are classified as urban clusters, regions with High-Low are isolated urban regions, and those with Low-High are rural close to urban areas, and regions with Low-Low are considered rural areas. According to the LISA Cluster Map, there is no significant change in population distribution before and after the Gyungbu KTX line. In Figure 8, the cluster map shows that the Seoul MSA is highly auto correlated, while the auto-correlations in Daejeon, Daegu, and Busan are not significant. In other words, Seoul is a heavily concentrated urban cluster. In addition, the population distribution pattern in other MSAs barely changed from 2000 and 2005. This is consistent with a previous point Ⅳ. Changes in City Size after KTX Opening 33 that the population increase in the Daejeon MSA is not enough to be interpreted as clustered. Therefore, the effect of the KTX on the population in Daejeon is not significant. Figure 7. LISA Cluster Map 2000 2005 High-High Low-Low Low-High High-Low 35 Ⅴ Summary and Policy Implications 37 Ⅴ. Summary and Policy Implications 1. Summary The Featured Plan model illustrates that the production location is determined by minimizing transportation costs between production sites and consumer markets. From this point of view, Daejeon is the most attractive MSA. Located at the center of the Korean peninsula, it is the logistic hub, which crosses express rails and highways(see Figure 8). There has been a significant amount of ongoing infrastructure investment. Following are infrastructure investments planned and completed around the Daejeon MSA. Daejeon-Tongyoung Highway partial Opening to Jinju (2001) Youngdong Highway expansion (2001) Gyungbu KTX rail (2004) Cheongju‐Sangju Highway (2007) Daejeon‐Dangjin Highway (2009) Honam KTX rail (2017) These recent transportation infrastructure investments might have caused the merging of small suburban cities in Gyeonggi province into the Seoul MSA and expansion of the Daejeon MSA. The distance from the other MSAs to the Seoul MSA 38 is the most important factor for MSAs’ size. When the distance is not commutable to a large MSA such as seoul MSA, the regional economy is oftentimes developed independently by improvements in the transportation infrastructure, which could be the case in both the Cheonan-Asan and Daejeon MSAs. However, the population increases in the Daejeon MSA through transpor tation improvement was not clear nor enough. Because of the location decision for exporting manufacturing clusters in the 1970s from southern coastal cities, Daejeon did not have balanced industry structure. The employee share in manufacturing industry is only 12.4%；export share of the nation was 0.8% in 2005 (see Table 5 and 7), which are well below the national average. 2. Policy Implications Since infrastructure investment would be accelerated in the Daejeon area, economic development is anticipated. Then, just as in Gwangmyeong, it is possible that Osong and Cheongju (KTX transit cities) and Yeongi and Gongju(new government cities), should be included in the Daejeon MSA. Even innovative cities Nonsan and Eumseong would affect the Daejeon MSA positively in terms of population size. Several regional policies are recommended to capitalize on this location advantage in the Daejeon MSA. First, as mentioned, industrial restructuring is needed in the Daejeon MSA to take advantage of its location. In general, the manufacturing industry is the main beneficiary of transportation cost reductions rather Ⅴ. Summary and Policy Implications 39 Figure 8. Express Rails and Highways Incheon Gyungin(68) DongSeoul Chuncheon Kangneung Gwangmyeong Youngdong(94,01) Yeoju Wonju Donghae(75) Donghae Cheonan Jungbu Inner(04) Dangjin Cheongju Jungang(99) Osong Cheongju-Sangju Daejeon (07) Nonsan-Cheonan(02) Sangju Seohaean(01) Nonsan Daejeon-Tongyoung(87) (12) Honam(73,96) Hamyang Daegu 88 Olympic(84) Kyungju Gwangju Dalsung (17) (10) Namhae(77) Mokpo Suncheon Jinju Masan Busan Tongyoung KTX (year) Highway Planned Source：Korean Railroad Corporation, Korean Expressway Corporation 40 than specialized industries including Research and Development and Special Video in Daejeon. The Bio-industrial cluster in Osong is not a key beneficiary either. Second, in order to attract firms to the area, a more skilled labor force will demand higher educa tion levels in local universities. Third, in addition to attracting firms, inducing endogenous industry development is the key policy for regional development. 41 References ․Kim, Dongsoo(2007), “Changes in Commuting Patterns and Determinants of Commuting Time：Seven Korean Cities”, The Korea Spatial Planning Review, Vol.53, pp. 223-240 ․Kim, Sun-Bae, Jun-Ho Jung, and Jin-Myun Lee(2005), “Linkage Structures and Spatial Patterns of Industrial Clusters in Korea”, Korean Institute for Industrial Economics and Trade (in Korean) ․Kim, Young-Mo(1995), “The Research on High Speed Rail and Balanced Regional Development”,「Reform of the National Land Spatial Structure in High Speed Rail Era」Korea Research Institute for Human Settlements, pp. 3-65(in Korean) ․Moon, Kyung-Won, Beom-Kyu Lee(2001), “The Effect of Gyungbu High Speed Rail Open on Daejeon and Countermeasures”, Daejeon Development Institute, Policy Seminar(in Korean) ․Lee, Yong-Woo, Jinkyu Chung, Yang-Soo Yun, and Sang-Yeon Lim (2006), “High Speed Rail and the Changes of Spatial Structure (2)”, Kuk To Yeon 2006-19 (in Korean) ․Lee, Changmoo et al.(2004), “City and Regional Ripple Effect of High Speed Rail Opening”, Dae Han Kuk To Do Si Gye Hoek Han Hoe, Vol. 8, pp. 3-18(in Korean) ․KIET et al.(2007),「Regional Industrial Development Roadmap」(in Korean) ․Jeon, Young-Ok et al.(2004), “The Impact of High Speed Rail and Implication”, Issue Paper, Samsung Economic Research Institute (in Korean) ․Jeon, Young-Ok(2004), “Three Hour Nationwide, High Speed Rail Era Begins”, CEO Information, Vol. 442, Samsung Economic Research Institute(in Korean) ․Jung, Jun-Ho, Mungu Heo, and Chang-Uk Byeon(2005), “Balanced 42 National Land Development Policy in High Speed Rail Era”, Korean Institute for Industrial Economics and Trade (in Korean) ․Cho, Nam-Geon, Jinkyu Chung, Jonghak Kim(2005), “High Speed Rail and the Changes of Spatial Structure (1)”, Kuk To Yeon 2005-34 (in Korean) ․Cho, Nam-Geon et al.(2003), “The Spatial Impact of the High Speed Rail and its Countermeasures”, Kuk To Yeon 2003-40 (in Korean) ․Korea Land Corporation(2005), 「Basic Research for High Speed Rail Stop Areas」(in Korean) ․Heo, Mungu, Jae-Hong Chang, and Yun-Ki, Choi(2004), “Economic Growth and Regional Economic Disparity”, Korean Institute for Industrial Economics and Trade (in Korean) ․Abe, Seizi(2007), “Future of Japanese Express Trail”, Han Kuk Cheol Do Hak Hoe Ji, Vol.10(1), pp. 14-22 (in Korean) ․Duranton, G., and Turner, M.(2007), “Urban Growth and Transportation”, unpublished ․Krugman, P.(1998), “What’s New about the New Economic Geography?”, Oxford Review of Economic Policy, Vol.14, No.2, pp. 7-17 ․O'Sullivan, A.(2000), “Urban Economics”, McGraw-Hill, 4th Edition ․Villegas, D.J.(1982), “Comparative Performance of Spatial Models of Economic Market with Linear Household Demand”, Southern Economic Journal, Vol.48, No.4, pp. 893-908 43 A MSA (Metropolitan Statistical Area) is the same geogra phically classified concept of the MSA in the United States. It is the set of Si, Gun, and Gu considering the accessibility and closeness. In this paper, a MSA was defined by the commu ting rate from a suburban city to the center city : 1) The populat ion of a central city is more than 50,000, 2) Any Si, Gun, or Gu in the MSA are adjacent, 3) If the commuting rate from the cities in the suburban areas of a central city are more than 10%, or 4) If the commuting rate from a central city to its suburban cities is more than 10%5). Table 8. Large MSAs along with KTX line MSA Administrative Si, Gun, Gu included in MSAs Seongnam, Uijeongbu, Anyang, Gwangmyeong, Bucheon, Goyang, Gwacheon, Guri, Seoul Namyangju, Gunpo, Uiwang, Hanam, Yongin, Paju, Gimpo, Gwangju*, Yangju, Pocheon Busan Gimhae, Yangsan Daegu Kyeongsan Gwangju Naju Daejeon Nonsan, Kyeryong Suwon-Hwaseong-Osan Suwon, Hwasung, Osan Cheonan-Asan Cheonan, Asan * Gwangju in Gyeongi Province 5) According to Census(2000, 2005), there is no changes in the reclassification of MSAs in Table 8 in between 2000 and 2005. 44 Figure 9. KTX stops(Gyungbu line) and Korean MSAs Seoul Suwon-Hwaseong-Osan Cheonan-Asan Daejeon Daegu Busan Compared to the US MSA definition6), 10 percent of the inter-commuting rate is a bit low. However, many previous 6) Inter-commuting rate for US MSA definition by the Office of Manage ment and Budget (2000) is 25%. Appendix 45 studies for defining Korean MSAs have used 10 percent or even 5 percent, because the Korean Si, Gun, and Gu are small in area and close to each other7). Among the seven administrative metrocities, the Incheon MSA excludes its Ongjin-Gun, because it is an island and the Ulsan MSA are exactly same as the administrative metrocity. The biggest change was in the Seoul MSA. It includes 18 cities in Gyeonggi province but some cities such as Suwon and Anyang are excluded from the Seoul MSA, because their residents commute within their own MSAs, which means Suwon and Ansan have their own regional economies. As shown, Suwon MSA includes Hwaseong and Osan in Table 8. Ansan MSA includes Siheung. 7) Kwon(2001) and Kwon and Chung(2005, 2007) used 5% as the criteria level of inter‐commuting rate to define Korean MSAs.