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Erschienen in: Transportation 3/2014

01.05.2014

Has the transport-led economic growth effect reached a peak in China? A panel threshold regression approach

verfasst von: Taotao Deng, Shuai Shao, Lili Yang, Xueliang Zhang

Erschienen in: Transportation | Ausgabe 3/2014

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Abstract

Using China’s province-level panel data from 1987 to 2010, this study explores the optimal level of transport infrastructure accumulation maximizing the growth rate. We investigate under what circumstances can additional transportation infrastructure capacity positively affect economic growth, based on panel threshold regression models. Our empirical findings suggest that there is a non-monotonic relationship between the stock of transport infrastructure and the long-run growth rate. The magnitude of transport-led economic growth effect significantly depends on the level of the existing transport network. The empirical results identify two endogenous cut-off points of efficiency of transport-led economic growth effect. When the highway network density is lower than 0.17 km/km2, an insignificant positive relationship between highway infrastructure accumulation and economic growth was found. When the highway density is estimated between 0.17 and 0.38 km/km2 or higher than 0.38 km/km2, expanding the highway network has a significant positive effect on economic growth, but the magnitude of the impact is weaker in the latter, with the estimated coefficients equal to 0.23 and 0.09 respectively. Although China still enjoys a positive economic growth effect led by building more large-scale highway infrastructure, the magnitude of the effects of most provinces in China has already passed the saturation point and continuously expanding the highway network is not very productive.

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Fußnoten
1
See Agénor and Neanidis (2011) for a more detailed discussion of how infrastructure investments affect education and health outcome and thus indirectly affect economic growth.
 
2
Highway is a basic and the most important type of transport infrastructure. In China, the highway carries 75.5 % of the country's freight traffic and 93.4 % of the country's passenger traffic in 2010. Thus, in the following parts, we focus on the highway sector. Certainly, investment in other modes of transport, including railway, waterways, ports, civil aviation and pipelines, may influence productivity and economic growth.
 
3
A number of factors contribute to the fast development of China`s transport infrastructure. Among them, FDI-driven competition among local governments and governance level largely explain the rapid increase in infrastructure provision. (See Zhang et al. 2007 for more details).
 
4
Beginning in 2006, Ministry of Transportation in China implemented a specific project, named "five-year 100 billion", aiming to substantially improve the quality of rural roads. The year 2006 was a momentous one for the Chinese rural road construction; it witnessed a rapid, large-scale development of rural roads in the history. Thus, we use Year 2006 as a dummy variable to control the possible change.
 
5
We prefer to use the physical measure of transport infrastructure accumulation rather than the monetary investment in infrastructure for three reasons
1. Transport infrastructure facilitates economy through a networked delivery system. Since there is a lag between the times when the transport investments are made and when the economic benefits transpire, existing road supply on the year can better reflect the functioning transport network.
2. The construction cost for a road differs significantly between provinces, largely due to substantially different geological environment, such as Beijing-Tibet expressway. Thus, the monetary investment in transport infrastructure is not capable of reflecting the road kilometer that it can build.
3. In the published China Statistical Yearbook, the detailed investment specifically for the transport sector is not well documented. In some studies, the total investment in transport, storage and post was used as a proxy to aggregate transport investment, for which we believe may bias the results.
 
6
The provincial-level data include 22 provinces, 4 provincial level municipalities and 4 autonomous regions over the period from 1987 to 2010. Tibet is excluded in the sample due to lack of continuous statistics.
 
7
In the regression, both sides of equation were multiplied by 100 to reduce volatility. Thus, in the interpretation of final results, the estimated threshold of highway density should be divided by 100.
 
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Metadaten
Titel
Has the transport-led economic growth effect reached a peak in China? A panel threshold regression approach
verfasst von
Taotao Deng
Shuai Shao
Lili Yang
Xueliang Zhang
Publikationsdatum
01.05.2014
Verlag
Springer US
Erschienen in
Transportation / Ausgabe 3/2014
Print ISSN: 0049-4488
Elektronische ISSN: 1572-9435
DOI
https://doi.org/10.1007/s11116-013-9503-4

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