High-speed rail may hurt intermediate places: The role of long-haul economies

Hans Koster, Takatoshi Tabuchi, Jacques-François Thisse 09 May 2021

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In 2014 Vox column, Bernard et al. (2014) argue that high-speed rail is crucial for the development of firm supply networks, while Charnoz et al. (2016) show how the decrease in passenger travel time between headquarters and affiliates has allowed management functions to be concentrated in headquarters. In a recent Vox column, we discussed the general equilibrium effects of large-scale investments in high-speed rail (HSR), showing that the local effects can be large and depend on a complex interplay between the relative position of municipalities within the network as well as the underlying location fundamentals (Hayakawa et al. 2021).

In a recent paper (Koster et al. 2020), we focus specifically on whether intermediate ‘in-between’ areas benefit from investments in high-speed rail. This is important because it is commonplace for local governments and regional interest groups to lobby the federal/national government (and international bodies such as the European Commission or the World Bank) for their region to be connected to the new infrastructure.1 The question, however, is whether these intermediate areas benefit or lose from this connection. It appears that existing research shows fairly mixed results.

We argue that an important reason for differences in results is, at least to a certain extent, the presence of ‘long-haul economies’ (LHEs). Long-haul economies imply that it becomes cheaper to travel once your trip is longer. To put it more formally, the marginal travel costs decrease with trip length. To see how this affects firms’ location decisions, we develop a simple model with four regions where we aim to investigate the effects on employment in intermediate regions. We then compare connected regions (region three in the figure below) to unconnected regions (region two in the figure below). Our results show that whether ‘region three’ benefits in terms of employment relative to ‘region two’ (which remains unconnected), depends on (i) the strength of the long-haul economies effect and (ii) the size of the intermediate region. When there are no long-haul economies effect and region three is large, this region always benefits from the connection. By contrast, when the long-haul economies effects are substantial and region three is small, this region may actually lose out from being connected to the infrastructure network. 

The explanation for these seemingly conflicting findings is that there is a trade-off between a ‘hub effect’ and a ‘market size effect’. In presence of long-haul economies, the hub effect implies that a connection to the new infrastructure makes it easier to reach other places through lower transport costs. This in turn attracts more firms and employment. By contrast, the market size effect implies that if a region is small, it is easier for firms to set up a business in a core region and to transport goods or people to the small, connected region instead.

Figure 1

We then bring this model to the data by investigating the effects of high-speed rail on intermediate areas in Japan. The high-speed rail network in Japan is commonly referred to as the Shinkansen, which means ‘new trunk line’. The figure below provides a map of Japan's transportation networks in 2014. There are several reasons why studying the Shinkansen is important. First, one of the main objectives of the Shinkansen was to promote economic growth and development outside Tokyo – in smaller ‘intermediate’ places (Sato 2015). Second, we show that the Shinkansen displays strong long-haul economies. Our estimations show that a 1% increase in travel distances increases travel time by only 0.8%. Long-haul economies in the Shinkansen are found to be stronger than for travel on the Japanese road network or the Dutch rail or road network.

Figure 2

Third, out of 160 million passengers per year, a very large share (approximately 65% in 2010) are technical workers and business travelers. Such a high number suggests that the Shinkansen may be considered as a transportation mode that affects significantly firms' location choices, through the travel of non-production workers (whose share in Japan has increased from 22% to 41% between 1952 and 2015). Last, the first Shinkansen lines were built more than 50 years ago, meaning their long-run effects should have materialised by now. All of this makes the Shinkansen a natural candidate to study the impact of long-haul economies on the location of firms.

We only keep municipalities that are outside ‘central’ cities – as defined by Kanemoto and Tokuoka (2002) – and compare the change in employment between 1957 (before the first Shinkansen line was opened) and 2014. Our empirical strategy addresses the issue that the most attractive and dense places may receive infrastructure investments and may be the first places that are connected. Our results deliver a consistent picture: intermediate areas lose employment when they are connected to the Shinkansen. The effects range from about 10-40%. While this effect may seem large, it is very much in the same order of magnitude as Faber (2014) and Baum-Snow et al. (2017) have found in their studies of the impact of new highways in China.

Our findings have an interesting political economy implication as they indicate that lobbying for intermediate places to receive a station may actually hurt the area. More specifically, they explain why the construction of a highway ramp or a high-speed rail station does not necessarily deliver its sought-after payoffs. Even though casual evidence suggests that our results are not out of the ordinary, the finding that intermediate areas may lose from being connected also depends on the attributes (e.g. the size, the type of employment etc) of the region that is connected, and the strength of long-haul economies in the transport mode considered. For example, a small and highly productive region which is part of an international trade network may benefit from connection. 

References

Baum-Snow, N, L Brandt, J V Henderson, M A Turner and Q Zhang (2017), “Roads, railroads, and decentralization of Chinese cities”, Review of Economics and Statistics 99: 435-448.

Bernard, A, A Moxnes and Y Saito (2014), “Fast trains, supply networks, and firm performance”. VoxEU.org, 24 September.

Charnoz, P, C Lelarge and C Trevien (2018), “Communication costs and the internal organisation of multi-plant businesses: Evidence from the impact of the French high-speed rail”, Economic Journal 128: 949-994.

Faber, B (2014), “Trade integration, market size, and industrialization: Evidence from China's National Trunk Highway System”, Review of Economic Studies 81: 1046-1070.

Hayakawa, K, H R A Koster, T Tabuchi and J F Thisse (2021), “How high-speed rail changes the spatial distribution of economic activity: Evidence from Japan’s Shinkansen”, VoxEU.org, 29 March. 

Kanemoto, Y and K Tokuoka (2002), “Proposal for the standards of metropolitan areas of Japan (in Japanese)”, Oyo Chiikigaku Kenkyu 7: 1-5.

Koster, H R A, T Tabuchi and J F Thisse (2021), “To be connected or not to be connected? The role of long-haul economies”, CEPR Discussion Paper 15905.

Sato, N (2015), History of Shinkansen (In Japanese), Tokyo: Chuokoron-Shinsha

Endnotes

1 There are actually many examples of relatively small places that are connected to the HSR, also in Europe. Examples are Calatayud on the high-speed rail line between Madrid and Barcelona; Ashford on the Eurostar line between Paris and Brussels; Noorderkempen on the high-speed rail line between Rotterdam and Antwerp; Uglovka and Okulovka on the Moscow-St. Petersburg line in Russia, etc.

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Topics:  Industrial organisation Labour markets Productivity and Innovation

Tags:  infrastructure, rail, Japan, investment, economic geography, economic activity, Travel

Professor of Urban Economics and Real Estate, Vrije Universiteit Amsterdam

Professor at the Graduate School of Economics, University of Tokyo; Faculty Fellow, Research Institute of Economy, Trade and Industry

Professor of Economics and Regional Science, Université catholique de Louvain and CEPR Research Fellow

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