The role of transportation sectors in the Korean national economy: An input-output analysis

Transportation Research Part A 93 (2016) 13–22

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Transportation Research Part A journal homepage: www.elsevier.com/locate/tra

The role of transportation sectors in the Korean national economy: An input-output analysis Min-Kyu Lee a, Seung-Hoon Yoo b,⇑ a b

Port Research Division, Korea Maritime Institute, 26, Haeyang-Ro 301Beon-Gil, Yeongdo-Gu, Busan 49111, South Korea Graduate School of Energy & Environment, Seoul National University of Science & Technology, 232 Gongreung-Ro, Nowon-Gu, Seoul 01811, South Korea

a r t i c l e

i n f o

Article history: Received 6 January 2014 Received in revised form 5 August 2016 Accepted 17 August 2016

Keywords: Input-output analysis Exogenous specification Transportation sector Korea

a b s t r a c t The transportation industry has been playing an important role in the economic development of Korea and, thus, has become a critical factor in sustaining the well-being of the Korean people. This paper attempts to analyze the economic impacts of four transportation modes using input-output (I-O) analysis, with specific application to Korea. To this end, we apply the I-O models to the Korean I-O tables generated by the Bank of Korea, paying particular attention to the four transportation sectors in Korea (rail, road, water, and air transportations), considering them as exogenous, and then determining their impacts. Specifically, the production-inducing effects, supply shortage effects, sectoral price effects, forward linkage effects, and backward linkage effects of the four transportation modes are quantitatively derived over the period 2000–2010. For example, the production-inducing effect of a KRW 1.0 production or investment in transportation is larger in the petroleum and transportation equipment sectors than in other sectors. Furthermore, the rail and road transportation sectors have greater supply shortage effects than the other transportation sectors. Finally, the potential uses of the results of this analysis are presented from the perspective of policy instruments, and policy implications are discussed. Ó 2016 Elsevier Ltd. All rights reserved.

1. Introduction Transportation, which is vital for the movement of both freight and passengers, provides the thoroughfare for a nation’s products, a means for traveling to and from work, and communication networks (Coyle et al., 1990). Moreover, it is a vital link in the supply chain of goods and services, shipment of intermediate inputs, and delivery of final goods. In other words, the basic function of transportation is to provide the market with access to the resultant products. In the perspective of its role as an economic factor in the production of goods and services, transportation significantly contributes to national economic growth. The gross output of the transportation industry in Korea has continuously grown at an average annual rate of 5.8% during the period 2000–2010, from KRW 51.29 trillion in 2000 to KRW 90.15 trillion in 2010.1 The transportation industry accounted for about 3.0% of the real gross domestic product (GDP) of Korea during the last decade. In Korea, it is likely that the transportation industry will emerge as a new growth engine industry in view of its own growth trends and contribution to the increase of efficiency in other industries. In line with these expectations, the Korean government has been trying to carry out transportation ⇑ Corresponding author. 1

E-mail addresses: [email protected] (M.-K. Lee), [email protected] (S.-H. Yoo). The total gross output was adjusted at the 2005 prices. USD 1 was approximately equal to KRW 1057.

http://dx.doi.org/10.1016/j.tra.2016.08.016 0965-8564/Ó 2016 Elsevier Ltd. All rights reserved.

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M.-K. Lee, S.-H. Yoo / Transportation Research Part A 93 (2016) 13–22

development projects based on ‘‘The Basic Plan on Sustainable Transport Development” (Ministry of Land, Transport and Maritime Affairs, 2011b). In order to develop the transportation sectors, the related public transportation infrastructures must first be constructed. For example, sufficiently developed rail and road networks are needed to meet the demand for domestic transportation. In addition, adequately equipped seaports and airports to transport the import and export merchandise should be constructed. However, given the enormous costs of infrastructure construction and limited government budgets, the government has to decide on its priorities with regard to government-driven development projects. This situation necessarily drives the need for economic impact analysis of the transportation sectors. In such a situation, researchers need to provide policy-makers with accessible and responsible information on the economic impacts of the transportation industries. Above all, we need to provide a comprehensive description of the transportation industries and analyze the long historical series data to guide policy-makers since they constitute a major source of impetus for national economic growth. Thus, the objective of this paper is to investigate the role of four transportation industries in the Korean national economy for the period 2000–2010 using a static input-output (I-O) approach and provide policy-makers with a preliminary indication of the role of each transportation sector. The I-O model has been increasingly applied to a variety of areas over the past four decades (Miller and Blair, 2009). Since the model has been found useful to deal with various transportation issues, it has been widely applied in transportationrelated contexts. Using the I-O model, Plaut (1997) examined the relationship between the transportation and communications services used by industries in the European Community countries. Ham et al. (2005) also used a multi-regional I-O model to evaluate the impacts of transportation network disruptions caused by unexpected events such as earthquakes. Kwak et al. (2005) employed a comprehensive I-O model to investigate the role of water transportation in the Korean national economy. Doll and Schaffer (2007) also used the I-O model to analyze the economic impacts of the German heavy goods vehicle toll system. Using the I-O model, Nealer et al. (2011) developed a model to approximate the supply chains for embodied transportation in products. Moreover, Nealer et al. (2012) applied the I-O model to assess the energy and greenhouse gas emissions mitigation effectiveness of USA modal freight policies. As discussed above, the I-O model is quite useful for analyzing transportation-related issues in the context of a national economy because it recognizes the interdependence of all sectors of the economy and their transportation consumption embodied in sectoral output. The Korean transportation sector, however, has rarely been investigated separately using the I-O analytical method. Moreover, there is no previous longitudinal study which explores transportation sectors based on I-O analysis over a series of years. Inter-temporal comparisons can be valuable for the sake of research because the transportation sectors play different roles at different stages of economic growth. The remainder of the paper is organized as follows. Section 2 explains the status of the transportation industry in Korea. Section 3 presents an overview of the static I-O model employed in this paper. The conventional I-O model’s considerations such as the sectoral effects of transportation supply investments by the four transportation sectors and inter-industrial linkage effects by the demand-driven model are reviewed. In addition, the sectoral transportation supply shortage effects and sectoral impacts of a rise in transportation rates are discussed by sector, using an unconventional supply-driven model and the Leontief price model. Section 4 discusses the analysis results from the perspective of transportation-based I-O models. Section 5 provides the potential applications of these results for transportation policies in Korea. A summary of the main findings and some concluding remarks are presented in the final section.

2. Current status of transportation sectors in Korea The different transportation modes such as rail, road, water, and air carry out their intrinsic roles. For example, water and air transportation mainly support the movement of international trade and travel of passengers, while road and rail transportation are responsible for providing domestic freight and passenger services. The import and export cargo volume in Korea has grown at an average annual rate of 3.6%, rising from 447.1 million metric tons in 2000 to 636.4 million metric tons in 2010. During this period, 99.8% of trade cargo was handled by marine transportation and 0.2% by air transportation. In fact, water transportation plays a pivotal role as means of international trade in Korea. Table 1 presents in sequence the annual domestic freight traffic trends of the four transportation modes. In 2010, the shares of domestic freight traffic were 79.6% for road, 15.3% for water, 5.0% for rail, and 0.0% for air transportation. Road transportation is used for most of the domestic freight, showing an upward trend. On the other hand, the annual domestic freight traffic by rail, water, and air transportation shows a declining trend. Long-term centralization of road transportation in domestic freight traffic can cause traffic congestions and excessive greenhouse gas emissions. Given concerns about the high share of road transportation in domestic freight traffic, the government will have to promote policies on a modal shift to reduce the concentration of road transportation. As discussed above, we need to construct public-related infrastructures to meet the demands of transportation and develop the transportation industries. Fig. 1 shows the trends of annual social overhead capital investment in the four transportation sectors. The social overhead capital investment in 2010 was KRW 8.00 trillion for roads, KRW 5.35 trillion for rails, KRW 1.86 trillion for seaports, and KRW 0.07 trillion for airports according to investment size. In terms of average annual investment growth rate during 2005–2010, road and rail constructions take precedence over seaport and airport

15

M.-K. Lee, S.-H. Yoo / Transportation Research Part A 93 (2016) 13–22 Table 1 Annual domestic freight traffic by transportation mode. (Unit: million ton, %). Source: Ministry of Land, Transport and Maritime Affairs (2011a). Year

Rail

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

45.24 45.12 45.73 47.11 44.51 41.67 43.34 44.56 46.78 38.90 39.22

Road (6.7) (6.3) (5.9) (6.2) (6.6) (6.1) (6.3) (6.2) (6.5) (5.1) (5.0)

496.17 535.73 584.57 565.46 518.86 526.00 529.28 550.26 555.80 607.48 619.53

Water (73.4) (74.2) (75.7) (74.6) (76.4) (76.5) (76.6) (76.9) (76.9) (79.2) (79.6)

134.47 140.54 141.71 145.33 115.64 119.41 117.81 120.08 126.96 120.03 119.02

Air (19.9) (19.5) (18.3) (19.2) (17.0) (17.4) (17.1) (16.8) (17.6) (15.7) (15.3)

0.43 0.43 0.43 0.42 0.41 0.37 0.36 0.32 0.25 0.27 0.26

Total (0.1) (0.1) (0.1) (0.1) (0.1) (0.1) (0.1) (0.0) (0.0) (0.0) (0.0)

676.32 721.82 772.44 758.32 679.41 687.45 690.78 715.22 722.91 766.68 778.03

Note: The figures in parentheses give the share of domestic freight traffic.

Fig. 1. Annual social overhead capital investment by four transportation infrastructures. Source: Ministry of Land, Transport and Maritime Affairs (2010).

constructions. Considering the significance of international trade in the Korean economy, the investments in seaport construction are inadequate in comparison to rail and road construction. 3. Methodology 3.1. General framework of I-O analysis The I-O model is a linear inter-sectoral one, showing the interrelationship between the productive sectors of a given economic system (Leontief, 1966). The Leontief inverse of I-O matrix is expressed as X ¼ ðI  AÞ1 F. Here, ðI  AÞ1 is a Leontief inverse matrix, in which elements ðaij ¼ @X i =@F j Þ represent the total direct and indirect outputs in sector i per unit of final demand in sector j. The standard demand-driven model explained above, however, cannot exactly assess the effects of new production in transportation on all the other sectors of the economy, because changes in the final demand can come from forces outside the model (e.g., change in consumer tastes and government purchases). Therefore, the individual transportation modes need to be considered exogenous and included in the final demand group (Miller and Blair, 2009). Adding the subscript e to the new matrices and subscript T k to the components related to the transportation sector k ðk ¼ 1; . . . ; 4Þ gives X e ¼ ðI  Ae Þ1 ðF e þ AT k X T k Þ. Assuming DF e ¼ 0, we have

DX e ¼ ðI  Ae Þ1 AT k DX T k

ð1Þ

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M.-K. Lee, S.-H. Yoo / Transportation Research Part A 93 (2016) 13–22

where ðI  Ae Þ1 represents a Leontief inverse matrix of reduced input coefficient matrix eliminating row and column of sector T k ; AT k denotes a column vector except for an element of sector T k ; DX T k identifies a scalar of the change in the gross output in sector T k . The analysis of linkage effects to quantify the causation power among industries is based on the assumption that the economy in related industries can be boosted by linking the input and output activities (Hirschman, 1958). In general, the linkage effects can be classified into backward and forward linkage effects. According to Rasmussen (1956), the forward linkage effects can be expressed as the sensitivity of dispersion, that is, the average of N elements in row i of the Leontief inverse matrix divided by all N 2 elements. Similarly, the backward linkage effects can be represented as the power of dispersion, that is, the average of N elements in column j of the Leontief inverse matrix divided by the average of all N 2 elements. The conventional I-O model, which depends on the assumption of fixed input coefficients and a perfectly elastic supply of inputs, concentrates on analyzing the impacts stemming from final demand, or backward linkage, and output-oriented activities (Oosterhaven, 1988, 1996). However, the model may not be appropriate for dealing with the impact of primary supply, or forward linkage, and input-oriented activities. Therefore, a supply-driven I-O model has been developed to deal with the direct and indirect impacts of supply restrictions (Davis and Salkin, 1984). A supply-driven I-O model is expressed as X 0 ¼ V 0 ðI  RÞ1 . The prime denotes the transpose of the given matrix and R is the output coefficient matrix; ðI  RÞ1 is the output inverse matrix, of which elements (qij ¼ @X j =@V i ) represents the total direct and indirect requirements in sector j per unit of final value added in sector i.

DX 0e ¼ RT k DX T k ðI  Re Þ1

ð2Þ

where RT k denotes a row vector except for an element of sector T k ; ðI  Re Þ1 represents the output inverse matrix eliminating row and column of sector T k . Given that any column in the I-O table describes the constitution of each sector as the cost structure of the production activity of each sector, it is possible to analyze the impacts of price. Assuming that the price of a one-unit output in each sector is one dollar (i.e., normalized price), we can evaluate the impacts of a change in transportation rates on prices throughout the economy using the I-O tables with physical units. Without any price changes in the value-added sector, the conventional Leontief price model can be rewritten as 1 ^ DP ¼ ðI  A0e Þ A T k DP T k

ð3Þ

where DPT k identifies a scalar of the price change of sector T k . 3.2. I-O tables used and data transformation To investigate the role of the transportation industry, this study uses three sets (2000, 2005, and 2010) of the original benchmark I-O domestic tables available for Korea (Bank of Korea, 2012).2 For our transportation-based analysis, we aggregate three original tables into 32-sector tables, including transportation, as shown in the first column of Table 2. To alleviate arbitrariness in aggregation and minimize any sectoral aggregation bias, this study conforms to Bank of Korea’s 28-sector classification method. In the original table, sector 21 includes transportation and warehousing services, but for the transportation-based I-O analysis, this sector is divided into five sectors, that is, rail, road, water, air, and warehousing services. 4. Results 4.1. Production-inducing effects Table 2 summarizes the sectoral impacts of transportation investments in the four transportation sectors.3,4 Rail transportation shows the highest total impact—a KRW 1.0 change in transportation investment—on the output of other sectors, ranging from KRW 0.688 to KRW 0.798, with narrow fluctuations. In sequence, road transportation has the second highest production-inducing effects, ranging from KRW 0.616 to KRW 0.730, with an upward trend. The impacts of water transportation range from KRW 0.306 to KRW 0.408, and those of air transportation range from KRW 0.408 to KRW 0.638. The amounts of total gross output in the four transportation sectors in 2010 are KRW 4.63 trillion for rail, KRW 46.22 trillion for road, KRW 34.05 trillion for water, and KRW 16.43 trillion for air transportation. From these, we note that the net production of each transportation 2 This paper applies the non-competitive imports I-O tables that distinguish domestic goods from imported goods, because the objective of this study is related to the measurement of the impacts of the four transportation sectors on domestic production (Miller and Blair, 2009). Moreover, it is reasonable to use the domestic table to analyze inter-industry impacts, which are ex-post concepts (Jones, 1976). 3 An anonymous referee indicated that the results presented in Tables 2–5 may be inaccurate to more than two significant digits, but four significant digits are routinely reported. It is likely that the inaccuracies come from model assumptions and data variability. 4 At first, we derive large amounts of numerical outputs, and then summarize the implications by focusing on notable results. Comprehensive results will provide useful information to help policymakers formulate policies regarding the mutual growth of transportation sectors and strongly related sectors.

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M.-K. Lee, S.-H. Yoo / Transportation Research Part A 93 (2016) 13–22 Table 2 The transportation sector’s supply investment effects on all other sectors. Sectors

1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. Total

Agriculture, forestry, and fisheries Mining and quarrying Food and food products Textiles and products Paper and wood products Printing and publishing products Petroleum and coal products Chemicals and allied products Non-metallic mineral products Primary metal products Fabricated metal products General machinery and equipment Electronic and other electric equipment Precision instruments Transportation equipment Miscellaneous manufacturing products Electric, gas, and water services Construction Wholesale and retail trade Restaurants and lodging Warehousing Communications Finance and insurance Real estate and business services Public administration and defense Education and health services Social and personal services Dummy sector Rail transportation Road transportation Water transportation Air transportation

Road transportation

Water transportation

Air transportation

2000

Rail transportation 2005

2010

2000

2005

2010

2000

2005

2010

2000

2005

2010

0.0032

0.0051

0.0031

0.0034

0.0037

0.0028

0.0019

0.0014

0.0013

0.0032

0.0030

0.0017

0.0010 0.0055 0.0054 0.0064 0.0033

0.0011 0.0087 0.0056 0.0050 0.0045

0.0007 0.0053 0.0035 0.0039 0.0027

0.0005 0.0058 0.0038 0.0056 0.0022

0.0009 0.0067 0.0045 0.0047 0.0027

0.0007 0.0054 0.0036 0.0048 0.0024

0.0003 0.0033 0.0022 0.0028 0.0019

0.0004 0.0025 0.0015 0.0014 0.0013

0.0003 0.0025 0.0014 0.0020 0.0013

0.0003 0.0056 0.0027 0.0041 0.0022

0.0007 0.0056 0.0031 0.0034 0.0023

0.0004 0.0032 0.0019 0.0024 0.0014

0.1449

0.0918

0.0971

0.1851

0.2252

0.2453

0.1138

0.1158

0.1011

0.0890

0.1917

0.1510

0.0284

0.0275

0.0257

0.0379

0.0409

0.0471

0.0115

0.0087

0.0117

0.0123

0.0200

0.0159

0.0034

0.0040

0.0027

0.0021

0.0018

0.0018

0.0012

0.0006

0.0009

0.0013

0.0016

0.0011

0.0276 0.0068 0.0132

0.0242 0.0111 0.0151

0.0263 0.0119 0.0162

0.0119 0.0046 0.0068

0.0181 0.0070 0.0069

0.0190 0.0084 0.0079

0.0066 0.0046 0.0045

0.0063 0.0050 0.0031

0.0097 0.0055 0.0038

0.0063 0.0042 0.0038

0.0166 0.0103 0.0065

0.0126 0.0082 0.0052

0.0219

0.0184

0.0177

0.0128

0.0118

0.0139

0.0051

0.0036

0.0059

0.0072

0.0111

0.0090

0.0047 0.1357 0.0029

0.0047 0.0946 0.0041

0.0029 0.1061 0.0038

0.0011 0.0657 0.0019

0.0010 0.0885 0.0027

0.0009 0.0873 0.0027

0.0006 0.0236 0.0011

0.0004 0.0187 0.0008

0.0005 0.0381 0.0013

0.0019 0.0122 0.0018

0.0023 0.0483 0.0021

0.0013 0.0342 0.0015

0.0745

0.0780

0.0774

0.0093

0.0124

0.0257

0.0058

0.0047

0.0072

0.0078

0.0105

0.0095

0.0081 0.0172 0.0122 0.0076 0.0125 0.0434 0.0458

0.0128 0.0186 0.0152 0.0027 0.0142 0.0411 0.0878

0.0092 0.0177 0.0113 0.0025 0.0115 0.0361 0.0666

0.0035 0.0260 0.0129 0.0444 0.0175 0.0426 0.0552

0.0022 0.0290 0.0118 0.0458 0.0124 0.0466 0.0475

0.0018 0.0288 0.0114 0.0464 0.0121 0.0519 0.0457

0.0036 0.0106 0.0074 0.0469 0.0130 0.0362 0.0668

0.0012 0.0101 0.0045 0.0199 0.0065 0.0393 0.0292

0.0021 0.0181 0.0053 0.0229 0.0079 0.0440 0.0751

0.0042 0.0141 0.0125 0.0362 0.0162 0.0344 0.0700

0.0033 0.0182 0.0098 0.0763 0.0168 0.0476 0.0754

0.0020 0.0153 0.0070 0.0561 0.0108 0.0352 0.0563

0.0000

0.1321

0.1328

0.0000

0.0004

0.0004

0.0000

0.0003

0.0002

0.0000

0.0018

0.0080

0.0102

0.0189

0.0150

0.0052

0.0061

0.0065

0.0013

0.0011

0.0017

0.0030

0.0041

0.0031

0.0058

0.0085

0.0067

0.0174

0.0171

0.0154

0.0044

0.0027

0.0036

0.0139

0.0145

0.0086

0.0251 – 0.0096 0.0009 0.0010 0.6884

0.0318 – 0.0087 0.0006 0.0015 0.7982

0.0216 – 0.0067 0.0005 0.0016 0.7467

0.0265 0.0005 – 0.0009 0.0026 0.6157

0.0246 0.0012 – 0.0008 0.0030 0.6882

0.0219 0.0011 – 0.0009 0.0059 0.7298

0.0152 0.0005 0.0094 – 0.0021 0.4082

0.0093 0.0012 0.0037 – 0.0008 0.3060

0.0102 0.0011 0.0042 – 0.0011 0.3917

0.0257 0.0002 0.0108 0.0006 – 0.4081

0.0205 0.0007 0.0081 0.0019 – 0.6379

0.0133 0.0005 0.0051 0.0012 – 0.4830

sector in the other sectors amounted to KRW 3.46 trillion for rail, KRW 33.73 trillion for road, KRW 13.34 trillion for water, and KRW 7.94 trillion for air transportation.5 ‘‘Petroleum and coal products,” ‘‘transportation equipment,” ‘‘finance and insurance”, and ‘‘real estate and business services” rank higher in the sectoral impacts of transportation investments.6 This shows that the costs of petroleum and coal products, transportation equipment, finance and insurance, and real estate and business services constitute the largest part in the production costs of the transportation sectors except for rail transportation. In the case of rail transportation, high effects are found in different sectors owing to its distinct characteristics. For example, high sectoral rail transportation impacts are

5 The net production of each transportation sector in the other sectors can be derived by multiplying total production-inducing effects by gross output. For example, in the case of rail sector, the net production in the other sectors amounted to KRW 3.46 trillion in 2010 by multiplying total production-inducing effects (0.7467) by gross output (KRW 4.63 trillion). 6 In terms of petroleum and coal products, rail and road transportations primarily consume light oil. On the other hand, water and air transportations mainly need heavy oil and jet oil, respectively. As intermediate inputs of transportation sectors, real estate and business services carried out various roles, which encompassed the real estate rental service for road and air transportation, the cleaning and disinfection service for rail transportation, and the machinery rental service for water transportation. In particular, production-inducing effects of road and air transportation on real estate and business services showed an downward trend during the period of 2005–2010.

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M.-K. Lee, S.-H. Yoo / Transportation Research Part A 93 (2016) 13–22

found in ‘‘electric, gas, and water services” and ‘‘public administration and defense.” The production activity of rail transportation needs high amount of electricity and the maintenance service of railroad track by the central government funding contrary to the other three transportation sectors. 4.2. Inter-industry linkage effect If in some industries the values of both the power of dispersion and sensitivity of dispersion are greater than one for both forward and backward linkage effects, these industries play a significant role in national economic development by supporting (forward linkage effects) as well as boosting (backward linkage effects) other industries. Focusing on transportation, backward linkage effects indicate that the production activities of the transportation sector may induce greater use of other sectors as inputs for transportation. On the other hand, forward linkage effects mean that transportation may be used as an input to other sectors for their own production. A high amount of intermediate inputs means that the nature of transportation involves the assembly of many different products purchased from a large number of industries. Forward and backward linkage effects are useful in assessing the impacts of transportation on the national economy as a whole. Table 3 indicates the forward and backward linkage effects for the major sectors of Korea in 2000, 2005, and 2010. Two important results can be found from the table. First, the forward linkage effect of the transportation sectors is less than one, indicating that when there is a boom in economic activities, the transportation sectors will be less stimulated by overall industrial growth than other sectors. In other words, the transportation industries are not much influenced by business fluctuations. Second, the backward linkage effects of the transportation sectors are also less than one, implying the transportation sectors have a smaller impact in terms of investment expenditures on the national economy than other sectors. In other words, the transportation sectors have a relatively weak capacity to pull in other industries. Given their low forward and backward linkage effects, the transportation industries can be classified under the final primary production category.7 4.3. Sectoral supply shortage effect As shown in Table 4, the effects of sectoral supply shortage in four transportation sectors display historically with an upward trend. The total supply shortage effects of the four sectors is 0.621–1.311 for road, 0.679–0.997 for rail, 0.547– 0.757 for air, and 0.081–0.107 for water transportation. If there were no transportation services supplied in 2010, the shortage costs by each transportation sector would have been KRW 60.60 trillion for road, KRW 12.44 trillion for air, KRW 4.62 trillion for rail, and KRW 3.26 trillion for water transportation.8 High supply shortage effects are commonly found in transport-intensive consuming industries such as chemical and allied products, electronic and other electric equipment, construction, and wholesale and retail trade.9 On the other hand, the industries with low shortage effects of transportation services are mining and quarrying, printing and publishing products, and precision instruments. 4.4. Pervasive effect of price change The results of sectoral percentage changes of a 10% increase in transport service rates by each transportation sector are shown in Table 5. These results indicate that the national economic effects of a 10% increase in transportation rates are 0.010–0.016% for rail, 0.099–0.219% for road, 0.008–0.011% for water, and 0.028–0.040% for air transportation.10 Note that the price impacts are heavily dependent on modal share and the values of road transportation are far greater than those of the other sectors. Except for air transportation, high sectoral price impacts are found in mining and quarrying and nonmetallic mineral products in 2010. The sectoral price impacts present a wide range of values based on transportation type, while the national economic price impacts of increases in transportation service rates are relatively very small. 5. Potential uses of the results The results of this study provide useful insights for formulating transportation policies in Korea.11 The sectoral impacts of transportation investments in a demand-driven model can be interpreted as benefits of sectoral transportation development 7 If the backward and forward linkage effects of an industry are respectively high and high, low and high, and low and low, the industry can be classified into intermediate manufacture, intermediate primary production, and final primary production, respectively. 8 We can derive the shortage costs of each transportation sector in the other sectors by multiplying total supply shortage effects by total gross output. For instance, the shortage costs of road sector amounted to KRW 60.60 trillion in 2010 by multiplying total shortage effects (1.3111) by gross output (KRW 46.22 trillion). 9 There are also some huge outliers for rail transportation, such as finance and insurance, and real estate and business services in 2005 and 2010. Since Korea Train Express (KTX) services, Korea’s high-speed rail system, were launched in 2004, rail transportation sector has been significant in production of those two sectors. The new service in trail transportation has allowed such sectors to consume more rail transport services. 10 These values are calculated as a weighted average of the sectoral price impacts with regard to the total output of each sector. 11 Specific policy implications should be interpreted in terms of the assumptions inherent in the I-O model. First, the assumption that cost changes are assumed to be completely transferred to other sectors is unlikely to be correct in a competitive marketplace. Second, the production function in the I-O model reflects the assumption of constant return to scale. Generally, transportation may be inherently subject to scale economies. However, empirical studies of the transport industry have provided little evidence for the presence of scale economies (Oum and Zhang, 1997).

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M.-K. Lee, S.-H. Yoo / Transportation Research Part A 93 (2016) 13–22 Table 3 Forward and backward linkage effects in Korea. Sectors

Forward linkage effects 2000

1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32.

Agriculture, forestry, and fisheries Mining and quarrying Food and food products Textiles and products Paper and wood products Printing and publishing products Petroleum and coal products Chemicals and allied products Non-metallic mineral products Primary metal products Fabricated metal products General machinery and equipment Electronic and other electric equipment Precision instruments Transportation equipment Miscellaneous manufacturing products Electric, gas, and water services Construction Wholesale and retail trade Restaurants and lodging Warehousing Communications Finance and insurance Real estate and business services Public administration and defense Education and health services Social and personal services Dummy sector Rail transportation Road transportation Water transportation Air transportation

Backward linkage effects

2005

2010

2000

2005

2010

Value

Rank

Value

Rank

Value

Rank

Value

Rank

Value

Rank

Value

Rank

1.1059 0.6562 1.1241 0.8795 1.2595 0.7013 1.4911 1.9868 0.8492 1.8932 0.8707 0.9207 1.0934

12 25 10 17 6 23 4 1 19 3 18 16 13

1.0244 0.6153 1.1356 0.8572 1.0705 0.7087 1.5702 1.9917 0.7682 2.0410 0.9805 0.9151 1.0545

14 28 8 19 11 23 4 2 20 1 15 18 12

0.9871 0.5852 1.1545 0.8129 1.0932 0.6666 1.5714 1.9680 0.7371 2.1437 1.0216 0.8992 1.1643

15 30 9 19 10 23 4 2 21 1 14 18 8

0.9049 0.8672 1.1607 1.1421 1.0732 1.1533 0.6272 1.1159 1.1148 1.2423 1.1964 1.1855 0.9437

19 22 6 8 15 7 32 9 10 3 4 5 17

0.9253 0.9184 1.1105 1.0926 1.0600 1.0831 0.6033 1.0921 1.0726 1.1972 1.2497 1.2397 0.9780

20 21 7 8 15 11 32 9 13 5 3 4 17

0.9770 0.8905 1.1225 1.0527 1.0403 1.0921 0.6427 1.0601 1.0172 1.2029 1.2526 1.2405 1.0456

19 24 7 13 15 9 32 12 16 5 2 3 14

0.6434 1.0168 0.6267

26 14 28

0.6061 1.0848 0.6345

29 10 26

0.5961 1.0458 0.6370

28 13 25

1.1120 1.3043 1.0983

11 2 12

1.0851 1.3047 1.1613

10 2 6

1.0898 1.2137 1.1721

10 4 6

1.1710 0.7124 1.2193 1.1084 0.6855 0.9921 1.4363 1.9864 0.5525 0.6366 0.7532 1.1430 0.5702 0.7430 0.5688 0.6025

8 22 7 11 24 15 5 2 32 27 20 9 30 21 31 29

1.1637 0.6414 1.3775 1.0545 0.7449 0.9551 1.3024 1.9243 0.6166 0.6495 0.7520 1.0970 0.5599 0.9678 0.5502 0.5850

7 25 5 13 22 17 6 3 27 24 21 9 31 16 32 30

1.2323 0.6168 1.4165 1.0722 0.7336 0.9046 1.3396 1.9075 0.6110 0.6546 0.7787 1.0508 0.5509 0.9114 0.5452 0.5906

7 26 5 11 22 17 6 3 27 24 20 12 31 16 32 29

0.8270 1.0813 0.8447 1.0903 0.7662 0.8935 0.8192 0.8095 0.8414 0.8573 1.0699 1.4620 0.9332 0.9020 0.7784 0.7822

26 14 24 13 31 21 27 28 25 23 16 1 18 20 30 29

0.7726 1.0711 0.8765 1.0731 0.8004 0.9588 0.8413 0.8185 0.8289 0.8266 1.0300 1.5059 0.9531 0.9045 0.6932 0.8718

30 14 23 12 29 18 25 28 26 27 16 1 19 22 31 24

0.7754 1.1058 0.9066 1.0822 0.8178 0.9884 0.8957 0.8258 0.8135 0.8366 1.0127 1.4773 0.9172 0.9193 0.7323 0.7810

30 8 22 11 27 18 23 26 28 25 17 1 21 20 31 29

projects. Policy decisions as to whether to proceed with a transportation development project could be made from an analysis of costs and benefits associated with such an optimal mix.12 From the results of production-inducing effects, we find that the major production-induced sectors are transferred from the primary and secondary industries to petroleum and coal products, transportation equipment, and finance and insurance. This indicates that the costs of these sectors constitute a large part of the production costs of the transportation industry. Especially, the support policies on fuel costs for transportation industries will strengthen the competitiveness of these industries. An analysis of inter-industry linkage effects can lead to implications on the structures of the four transportation industries. A comparison of the strengths of the sectoral linkages in a single economy can provide the framework for identifying the leading sectors in the economy and for grouping the sectors into spatial clusters. For example, the results of this study show that the transportation industries may have more strength in absorbing the products of related industries, rather than being used as inputs by other industries. The results of the supply-driven model may offer key information on the economic effects of the transportation industry’s supply shortages. This can be used not only in setting the economic reliability standards in transportation industry production, but also in determining pricing and management strategies. Thus, transportation supply has both direct and indirect effects on the production activities of other sectors. Especially, supply constraints affect the rail and road transportation sectors severely because these sectors serve largely as domestic freight carriers. With regard to supply constraint effects, its impacts on water and air transportation, which mainly support the movements of international trade, are contrary to rail and road transportation. Given the high domestic freight transportation share of the road transportation sector, supply constraints of the road transportation sector could cause serious national economic losses. To reduce the supply shortage effects

12 Transportation development projects consist of specific infrastructure construction and investment decisions. In preliminary feasibility study, the sectoral impacts of transportation investments using input-output model and cost-benefit analysis serve as a solid foundation on transportation development projects (Korea Development Institute, 2008).

20

M.-K. Lee, S.-H. Yoo / Transportation Research Part A 93 (2016) 13–22

Table 4 Supply shortage effects of transportation sectors. Sectors

1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. Total

Agriculture, forestry, and fisheries Mining and quarrying Food and food products Textiles and products Paper and wood products Printing and publishing products Petroleum and coal products Chemicals and allied products Non-metallic mineral products Primary metal products Fabricated metal products General machinery and equipment Electronic and other electric equipment Precision instruments Transportation equipment Miscellaneous manufacturing products Electric, gas, and water services Construction Wholesale and retail trade Restaurants and lodging Warehousing Communications Finance and insurance Real estate and business services Public administration and defense Education and health services Social and personal services Dummy sector Rail transportation Road transportation Water transportation Air transportation

Road transportation

Water transportation

Air transportation

2000

Rail transportation 2005

2010

2000

2005

2010

2000

2005

2010

2000

2005

2010

0.0066

0.0086

0.0089

0.0132

0.0168

0.0165

0.0012

0.0021

0.0017

0.0060

0.0070

0.0074

0.0016 0.0198 0.0193 0.0066 0.0014

0.0062 0.0283 0.0188 0.0112 0.0023

0.0042 0.0290 0.0157 0.0101 0.0022

0.0010 0.0349 0.0364 0.0133 0.0026

0.0089 0.0772 0.0330 0.0265 0.0083

0.0064 0.0730 0.0276 0.0250 0.0069

0.0001 0.0026 0.0023 0.0008 0.0002

0.0001 0.0054 0.0022 0.0016 0.0002

0.0001 0.0047 0.0016 0.0012 0.0002

0.0006 0.0149 0.0222 0.0047 0.0017

0.0006 0.0182 0.0176 0.0053 0.0026

0.0004 0.0186 0.0141 0.0050 0.0023

0.0072

0.0172

0.0273

0.0053

0.0126

0.0210

0.0020

0.0024

0.0034

0.0044

0.0052

0.0092

0.0366

0.0699

0.0694

0.0533

0.1297

0.1240

0.0103

0.0116

0.0101

0.0352

0.0469

0.0476

0.0265

0.0280

0.0214

0.0130

0.0655

0.0577

0.0079

0.0078

0.0062

0.0074

0.0084

0.0080

0.0460 0.0121 0.0263

0.0422 0.0146 0.0361

0.0481 0.0160 0.0382

0.0305 0.0112 0.0252

0.1125 0.0413 0.0545

0.1311 0.0436 0.0568

0.0084 0.0031 0.0040

0.0099 0.0039 0.0069

0.0091 0.0036 0.0065

0.0122 0.0075 0.0220

0.0183 0.0133 0.0330

0.0249 0.0149 0.0345

0.0392

0.0584

0.0749

0.0476

0.0805

0.1017

0.0048

0.0061

0.0070

0.0621

0.0662

0.0729

0.0033 0.0309 0.0048

0.0058 0.0406 0.0060

0.0063 0.0404 0.0052

0.0037 0.0446 0.0068

0.0068 0.0862 0.0139

0.0070 0.0800 0.0122

0.0003 0.0057 0.0006

0.0004 0.0108 0.0009

0.0004 0.0083 0.0007

0.0050 0.0235 0.0052

0.0055 0.0326 0.0049

0.0054 0.0337 0.0044

0.0059

0.0067

0.0078

0.0051

0.0068

0.0068

0.0015

0.0012

0.0012

0.0043

0.0045

0.0043

0.0534 0.0292 0.0090 0.0021 0.0074 0.0291 0.0600

0.0644 0.0500 0.0133 0.0064 0.0146 0.0583 0.1209

0.0539 0.0628 0.0147 0.0062 0.0159 0.0810 0.1503

0.0565 0.0329 0.0216 0.0021 0.0070 0.0320 0.0297

0.1089 0.1420 0.0321 0.0040 0.0151 0.0279 0.0486

0.0903 0.1702 0.0330 0.0036 0.0163 0.0324 0.0483

0.0121 0.0014 0.0015 0.0004 0.0003 0.0004 0.0019

0.0104 0.0076 0.0021 0.0006 0.0006 0.0005 0.0020

0.0075 0.0082 0.0019 0.0006 0.0007 0.0006 0.0019

0.0267 0.0871 0.0089 0.0024 0.0198 0.0344 0.0460

0.0377 0.1306 0.0127 0.0038 0.0346 0.0362 0.0619

0.0340 0.1567 0.0131 0.0037 0.0304 0.0419 0.0640

0.0842

0.0484

0.0756

0.0231

0.0232

0.0242

0.0010

0.0013

0.0011

0.0117

0.0310

0.0290

0.0193

0.0354

0.0446

0.0178

0.0380

0.0408

0.0014

0.0022

0.0022

0.0131

0.0182

0.0211

0.0228

0.0319

0.0330

0.0178

0.0287

0.0242

0.0009

0.0014

0.0012

0.0281

0.0256

0.0234

0.0587 – 0.0054 0.0036 0.0009 0.6791

0.0132 – 0.0111 0.0061 0.0018 0.8769

0.0127 – 0.0116 0.0078 0.0018 0.9970

0.0229 0.0008 – 0.0059 0.0035 0.6213

0.0295 0.0010 – 0.0021 0.0022 1.2840

0.0248 0.0007 – 0.0031 0.0018 1.3111

0.0014 0.0001 0.0014 – 0.0003 0.0805

0.0021 0.0001 0.0015 – 0.0009 0.1067

0.0023 0.0001 0.0012 – 0.0006 0.0958

0.0174 0.0003 0.0080 0.0041 – 0.5468

0.0133 0.0006 0.0107 0.0017 – 0.7086

0.0126 0.0004 0.0168 0.0023 – 0.7571

of road transportation, we need to pursue strongly the policy of modal shift of freight movement from road transportation to water services. The pervasive effects of price changes in this study are relatively small and differ by transportation type. These results are significant for the transportation investment and pricing policies of Korea. Transportation rates in Korea have been strictly regulated and have been managed as a part of the pricing policy by the government. The government has been concerned that even a small increase in transportation rates will cause a significant increase in overall price levels. However, the economy-wide price effects in this study are relatively small. These results will help the government build a more efficient and effective pricing policy for the transportation industry and oversee the pricing impacts more accurately and promptly. Longitudinal analysis results present the changes in each industrial sector over a period of 10 years. While rail transportation has consumed high amount of electricity since Korea Train Express (KTX) services were launched in 2004, the other three transportation still need petroleum products as main fuels. The support policies on fuel costs for transportation industry should be formulated in the other way according to transportation modes. Meanwhile, the government can consider adjusting annual social overhead capital investment in accordance with trends of the transportation sector’s supply investment effects and supply shortage effects referentially.

21

M.-K. Lee, S.-H. Yoo / Transportation Research Part A 93 (2016) 13–22 Table 5 Sectoral price effects of the 10% increase in transportation rates. Sectors

1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. Total

Agriculture, forestry, and fisheries Mining and quarrying Food and products Textile and product Paper and wood products Printing and publishing products Petroleum and coal products Chemicals and allied products Non-metallic mineral products Primary metal products Fabricated metal products General machinery and equipment Electronic and other electric equipment Precision instruments Transportation equipment Miscellaneous manufacturing products Electric, gas, and water services Construction Wholesale and retail trade Restaurants and lodging Warehousing Communications Finance and insurance Real estate and business services Public administration and defense Education and health service Social and personal services Dummy sector Rail transportation Road transportation Water transportation Air transportation

Rail transportation (%)

Road transportation (%)

Water transportation (%)

Air transportation (%)

2000

2005

2010

2000

2005

2010

2000

2005

2010

2000

2005

2010

0.0033

0.0077

0.0078

0.0734

0.1355

0.1439

0.0041

0.0098

0.0108

0.0107

0.0158

0.0229

0.0116 0.0065 0.0080 0.0076 0.0071

0.0734 0.0151 0.0174 0.0221 0.0127

0.0527 0.0142 0.0142 0.0168 0.0119

0.0830 0.1286 0.1691 0.1713 0.1499

0.9515 0.3713 0.2762 0.4719 0.4118

0.8055 0.3569 0.2504 0.4136 0.3823

0.0070 0.0062 0.0067 0.0066 0.0059

0.0090 0.0149 0.0105 0.0159 0.0059

0.0086 0.0169 0.0104 0.0141 0.0063

0.0165 0.0176 0.0331 0.0194 0.0317

0.0169 0.0244 0.0411 0.0261 0.0351

0.0196 0.0323 0.0454 0.0295 0.0445

0.0026

0.0087

0.0093

0.0215

0.0569

0.0714

0.0051

0.0062

0.0085

0.0058

0.0066

0.0111

0.0080

0.0193

0.0144

0.1308

0.3226

0.2561

0.0161

0.0167

0.0154

0.0278

0.0325

0.0350

0.0300

0.0454

0.0290

0.1648

0.9550

0.7786

0.0636

0.0654

0.0618

0.0301

0.0340

0.0383

0.0150 0.0112 0.0119

0.0139 0.0129 0.0200

0.0102 0.0101 0.0155

0.1112 0.1165 0.1270

0.3330 0.3284 0.2715

0.2768 0.2745 0.2304

0.0194 0.0202 0.0127

0.0168 0.0178 0.0197

0.0141 0.0166 0.0194

0.0142 0.0249 0.0356

0.0150 0.0293 0.0457

0.0187 0.0333 0.0497

0.0054

0.0118

0.0102

0.0729

0.1467

0.1381

0.0047

0.0064

0.0070

0.0305

0.0336

0.0352

0.0092 0.0081 0.0094

0.0195 0.0118 0.0169

0.0165 0.0089 0.0133

0.1136 0.1301 0.1476

0.2049 0.2258 0.3551

0.1825 0.1752 0.3100

0.0058 0.0106 0.0088

0.0078 0.0163 0.0132

0.0075 0.0134 0.0128

0.0492 0.0220 0.0362

0.0459 0.0237 0.0345

0.0502 0.0263 0.0399

0.0036

0.0056

0.0047

0.0350

0.0511

0.0411

0.0068

0.0051

0.0051

0.0096

0.0094

0.0092

0.0105 0.0080 0.0042 0.0064 0.0043 0.0089 0.0082

0.0165 0.0181 0.0091 0.0233 0.0114 0.0255 0.0227

0.0132 0.0182 0.0085 0.0190 0.0124 0.0282 0.0253

0.1238 0.1000 0.1140 0.0717 0.0450 0.1096 0.0452

0.2508 0.4635 0.1963 0.1319 0.1069 0.1096 0.0823

0.2216 0.4920 0.1901 0.1084 0.1271 0.1126 0.0812

0.0169 0.0027 0.0051 0.0086 0.0014 0.0009 0.0018

0.0137 0.0142 0.0073 0.0110 0.0026 0.0011 0.0019

0.0136 0.0174 0.0082 0.0130 0.0039 0.0015 0.0023

0.0188 0.0851 0.0150 0.0258 0.0410 0.0379 0.0225

0.0242 0.1185 0.0215 0.0346 0.0680 0.0396 0.0292

0.0297 0.1610 0.0268 0.0404 0.0842 0.0518 0.0382

0.0376

0.0271

0.0367

0.1151

0.1169

0.1176

0.0033

0.0039

0.0039

0.0188

0.0434

0.0500

0.0060

0.0118

0.0116

0.0620

0.1138

0.1059

0.0031

0.0039

0.0042

0.0146

0.0152

0.0195

0.0119

0.0210

0.0192

0.1040

0.1697

0.1407

0.0035

0.0047

0.0050

0.0529

0.0421

0.0485

0.0404 – 0.0049 0.0051 0.0025 0.0095

0.0124 – 0.0124 0.0117 0.0071 0.0163

0.0107 – 0.0116 0.0106 0.0050 0.0148

0.1761 0.0949 – 0.0932 0.1076 0.0987

0.2501 0.0859 – 0.0362 0.0800 0.2189

0.2082 0.0665 – 0.0415 0.0504 0.1969

0.0068 0.0092 0.0089 – 0.0060 0.0081

0.0102 0.0063 0.0086 – 0.0188 0.0104

0.0145 0.0053 0.0088 – 0.0116 0.0106

0.0430 0.0102 0.0258 0.0208 – 0.0276

0.0314 0.0153 0.0297 0.0082 – 0.0332

0.0376 0.0156 0.0597 0.0112 – 0.0400

6. Conclusion To address the role of the four transportation industries in the Korean national economy for the period 2000–2010, we have examined some useful models in applying I-O analysis to the transportation sectors over the long term. Specifically, we have analyzed the demand-driven model, inter-industry linkage effects, the supply-driven model, and the Leontief price model. Except for our inter-industry linkage effects analysis, each transportation sector is treated as exogenous, and we evaluated only the net effects by changes in investment, supply, or price in each sector. In terms of role of the four transportation sectors in the national economy, rail and road transportation ranks higher than the other two on a whole. Sectoral impacts in all the transportation industries appear to rank higher in specific sectors uniformly. For example, petroleum and coal products, transportation equipment, and finance and insurance rank higher in the sectoral impacts of transportation supply investments, while chemical and allied products, electronic and other electric equipment, construction, and wholesale and retail trade rank higher in the sectoral impacts of supply shortage. From our inter-industry linkage effects analysis, we find that the transportation industries are more able to absorb the products of related industries, rather than other industries using them as inputs.

22

M.-K. Lee, S.-H. Yoo / Transportation Research Part A 93 (2016) 13–22

From a review of the literature, few studies apply the I-O model to analyze separately the transportation industry based on transportation type. In terms of research methodology, beyond the intrinsic interest in the results of transportation policy, we demonstrate in this study the feasibility of extending the application of I-O analysis at least to the transportation industry in Korea. Moreover, longitudinal analysis results serve as an indication of the change of the transportation sectors and as a reliable starting point in formulating transportation policies in Korea. This paper focuses on evaluating the national economic effects of the four transportation sectors in Korea. The extension of the present framework needs to be tried in a future study. In this regard, we can consider an application of a dynamic I-O analysis where the input coefficients are allowed to change over time or a computable general equilibrium analysis where non-linear functional forms of production function are adopted. Moreover, a multi-regional I-O analysis is required to identify the significant distance-based spatial impacts of transportation sectors. References Bank of Korea, 2012. Economic Statistics System (retrieved 05.12.12). Coyle, J.J., Bardi, E.J., Cavinato, J.L., 1990. Transportation, third ed. West Publishing Company, Cincinnati. Davis, H.C., Salkin, E.L., 1984. Alternative approaches to the estimation of economic impacts resulting from supply constraints. Ann. Regional Sci. 18 (3), 25– 34. Doll, C., Schaffer, A., 2007. Economic impact of the introduction of the German HGV toll system. Transp. Policy 14 (1), 49–58. Ham, H., Kim, T.J., Boyce, D., 2005. Assessment of economic impacts from unexpected events with an interregional commodity flow and multimodal transportation network model. Transp. Res. Part A: Policy Practice 39 (10), 849–860. Hirschman, A.O., 1958. The Strategy of Economic Development. Yale University Press, New Haven. Jones, L.P., 1976. The measurement of Hischmanian linkage hypothesis. Quart. J. Econ. 90 (2), 323–333. Korea Development Institute, 2008. Preliminary Feasibility Study General Guidelines (In Korean), fifth ed. Korea Development Institute, Seoul. Kwak, S.-J., Yoo, S.-H., Chang, J.-I., 2005. The role of the maritime industry in the Korean national economy: an input-output analysis. Marine Policy 29 (3), 371–383. Leontief, W., 1966. Input-Output Economics. Oxford University Press, New York. Miller, R.E., Blair, P.D., 2009. Input-Output Analysis: Foundations and Extension, second ed. Cambridge University Press, Cambridge. Ministry of Land, Transport and Maritime Affairs, 2010. Port Affairs Manual (In Korean). Ministry of Land, Transport and Maritime Affairs, Kwacheon. Ministry of Land, Transport and Maritime Affairs, 2011a. Statistical Yearbook of MLTM (In Korean). Ministry of Land, Transport and Maritime Affairs, Kwacheon. Ministry of Land, Transport and Maritime Affairs, 2011b. The Basic Plan on Sustainable Transport Development (In Korean). Ministry of Land, Transport and Maritime Affairs, Kwacheon. Nealer, R., Matthews, H.S., Hendrickson, C., 2012. Assessing the energy and greenhouse gas emissions mitigation effectiveness of potential US modal freight policies. Transp. Res. Part A: Policy Practice 46 (3), 588–601. Nealer, R., Weber, C.L., Hendrickson, C., Matthews, H.S., 2011. Modal freight transport required for production of US goods and services. Transp. Res. Part E: Logist. Transp. Rev. 47 (4), 474–489. Oosterhaven, J., 1988. On the plausibility of the supply-driven input-output model. J. Regional Sci. 28 (2), 203–217. Oosterhaven, J., 1996. Leontief versus Ghoshian price and quantity models. South. Econ. J. 62 (3), 750–759. Oum, T.H., Zhang, Y., 1997. A note on scale economies in transport. J. Transp. Econ. Policy 31, 309–315. Plaut, P.O., 1997. Transportation-communications relationships in industry. Transp. Res. Part A: Policy Practice 31 (6), 419–429. Rasmussen, P., 1956. Studies in Inter-Sectoral Relations. Einar Harks, Copenhagen.