Page 390 - 360.revista de Alta Velocidad - Nº 5

Zhenhua Chen

is much more economical than HSR. Hence, they believe that there is no need for a massive
development of HSR. The argument was endorsed by Zhao et al. (2015), who further indicates
that a large scale HSR construction in China is likely to lead to an increase in market risk and
economic loss due to the limited benefits of travel-time savings.

Ansar et al. (2016) also raised concerns on the massive infrastructure investment in China
as they argue that such a large-scale investment in projects such as HSR is associated with
a high risk due to the builtup of debt, monetary expansion, instability in financial markets
and economic fragility. In fact, some scholars, such as Vickerman (2017), pointed out that
the effectiveness of HSR investment on regional economic growth can be less transformative,
because the contribution from HSR can be redistributive with some regions benefiting and
others suffering depending on their abilities to take advantage of new opportunities. Hence, its
overall wider economic benefits may not necessary be positive.

Although the intercity travel demand is likely to grow continuously for at least a few years given
the strong momentum of regional economic development in China, it remains unclear what the
long-term regional economic impacts of rail, in particular, HSR infrastructure development
would become. In addition, given that the national rail planning strategies were intended to
eliminate disparity across different parts of China so as to achieve a regional coordinated
development, it is also essential to understand how do the economic impacts vary among
different regions in China as a result of HSR development.

This study addresses these key questions using a dynamic spatial computable general equilibrium
(SCGE) model. Our study has three major research highlights as compared to previous studies.
First, the regional economic impacts of rail infrastructure investment in China are evaluated
using a dynamic SCGE with considerations of capturing both a dynamic temporal evolutions of
economic systems as well as the spatial (multiregional) general equilibrium interactions. The
model is calibrated and updated with data that reflecting the Chinese economic system and
the modeling framework was validated through a comparison with our previous analysis (Chen
et al., 2016) that evaluated using a different CGE model at the national level. Hence, the
empirical results are expected to be more robust and comprehensive.

Second, a detailed modeling framework based on a dynamic SCGE is developed for the first
time, for the assessment of rail infrastructure development. The framework captures both the
short-term direct impacts caused by capital investment in the process of rail infrastructure
development and the long-term indirect impacts as a results of productivity improvement and
technology progress. We believe that such a comprehensive modeling framework provides
more meaningful implications to decision-makers and broader applications to practitioners to
evaluate regional economic impacts of other types of infrastructures.
Third, an empirical analysis provides a thorough demonstration of the dynamic SCGE modeling
process. Specifically, the CGE assessment allows us to capture the evolutions of regional
economic impacts in a long-term period as more HSR systems being deployed. The empirical
assessment of the long-term regional economic impacts of HSR is critical as it may facilitate
future decision-making on infrastructure investment by improving our understanding on the
effectiveness of current rail investment policies. In addition, a comprehensive understanding of
the regional economic impacts of the Chinese HSR system also provides valuable implications to
other countries that are either currently developing HSR or plan to build one in the near future.

The rest of the paper is organized as follows. Section 2 provides a methodological review of
economic impact assessments with a focus on rail infrastructure systems. Section 3 introduces
the key modeling framework for evaluating the long-term rail infrastructure development.
Section 4 introduces the specific modeling structure of the dynamic SCGE model. Section 5
and 6 present data and the simulation results, respectively, whereas Section 7 summarizes and
concludes.

388 360.revista de alta velocidad