Transport investment, railway accessibility and their dynamic impacts on regional economic growth
Introduction
Transport policymakers have been influenced by the belief that “roads lead to prosperity” (Deng, 2013) which motivate investments in the expansion of transport infrastructure. The link between transport investment and economic development has been discussed for decades by researchers and policymakers and yet it continues to be a subject of debate (Mikesell, Wang, Zhao, & He, 2015). Literature indicates that transport investment has the potential to enhance regional productivity which consequently leads to economic growth (Alstadt, Weisbrod, & Cutler, 2012). Chen (2019) stated that improved railway accessibility contributed to the regional economic growth in China. In addition, earlier studies by Vickerman (1997), who reviewed the development of High Speed Railway (HSR) in France, Germany, Italy and Spain, showed that investment in HSR has provided a positive economic impact to Europe's major cities. However, he argued that in order to produce the economic impact, this investment requires proper coordination and collaboration with policymakers. On the other hand, De Rus (2011) argued that investing in HSR infrastructure can be justified more by the demand for additional rail capacity as well as a means of reducing traffic congestion on highways and airports, than direct benefits such as cost and time saving.
Improvements to the railway infrastructure in terms of accessibility and coverage are an important component of a sustainable transport system. Aditjandra, Zunder, Islam, and Palacin (2016) argue that an efficient green railway corridor alongside a well-developed road network is required to boost economic growth and enhance quality of life in Europe. In Saudi Arabia, the railway network has positively contributed to the environment by removing 500,000 trucks from the roads (Muhammad, 2018). In addition, the Saudi Railway Company (SAR) has built the Haramain High-Speed (HHS) train, which is the fastest electric railway in the Middle East, using the latest technology to minimize environmental impact.
Railway network improvement has the potential to offer benefits for both passengers and freight transport. Enhanced accessibility to railway stations would improve the ease of passengers to reach opportunities and the ease of products to be efficiently transported. Under certain circumstances, rail freight can provide a better solution which is difficult to achieve by roads network. Countries such as United States and Australia provide a good example in rail freight industry, given the infrastructure's ability to bypass congested urban roads and traverse sparsely populated areas of continental land mases. In the case of the United Kingdom (UK), the rail industry is working hard to elevate their rail freight system to compete with other European countries; it has well establish rail freight operations, with 17.4 billion tonne-kilometers of freight moved across the country in 2019 by rail (Network Rail Limited, 2019).The higher accessibility to railway stations is considered as a primary driver of different economic activities (e.g. business travel and tourism). More accessible opportunities and facilities though the railway network potentially promotes communication and knowledge exchange (Asheim et al., 2011; Chatman & Noland, 2011). For example, improved railway accessibility in the UK allowed 68 billion passenger-kilometers travelled with £ 6.6 billion in revenue in 2019 (Network Rail Limited, 2019).
Even though transport investment, in general, shows an influence on economic growth, the impact differs among countries. One of the key reasons for the differences in the output elasticity in existing empirical studies relates to the variety of geographical scale employed in those studies. The selection of spatial unit is crucial for better economic analysis (Ozbay, Ozmen-Ertekin, & Berechman, 2007); the spatial level can be defined at either the national-level, regional- level (state, provincial), city-level, industrial district or company-level (Deng, 2013). Some empirical studies argue that the smaller geographical focus leads to smaller output elasticity with respect to transport infrastructure investment, and this is also known as ‘the scale effect’ in spatial econometrics (Berechman, Ozmen, & Ozbay, 2006). In addition, the estimation techniques and underlying models are another crucial cause of the variation in output elasticity in the literature (Ozbay et al., 2007). Another potential reason for this discrepancy in the existing evidence base is due to the different economic structures and infrastructure arrangements of the countries examined. The configuration of industries in countries such as the UK (i.e. service and financial) and China (i.e. manufacturing) are distinct, which may motivate different responses to transport infrastructure investment. Similarly, the existing infrastructure provision in these countries is also unique, with China establishing new infrastructures whereas the UK is expanding capacity on extant infrastructures.
One type of situation which has received less attention in the academic literature is the impact of transport infrastructure investment in mineral orientated economies with expanding infrastructures. This is the case in the Kingdom of Saudi Arabia (KSA), which plans to create a diversification in its economic activity by 2030 to reduce the economy's reliance on mineral extraction. To achieve this aim, considerable investments in the transport system is being made to enable such a dramatic change. For example, Fig. 1a and b demonstrate the remarkable change in passenger numbers and freight tonnage which has occurred during the expansion of the rail network in the KSA, respectively. In 2019, it can be seen that improved accessibility to the railway network allowed for unprecedented movement of people and goods in Saudi Arabia's railway history. Even though, this number, for example, 1.8 million passenger journeys a year is still small on an international basis, for the KSA case is a remarkable improvement.
Aldagheiri (2008) revealed that the impact of transport infrastructure investments in areas of mineral resource within the KSA could be significant because its transport infrastructure is quite poor in some mineral locations. However, the maturaity level of infrastructure also has relevance for the extent of economic impact resulting from investment. Banister (2012) state that the accumulation of the level of transport infrastructure determines the magnitude of the effect of any additional transport infrastructure investment on economic growth. This means that there are decreasing returns associated with transport investment. In the KSA, the road network is well established across the country, meaning that any additional investment in this type of transport could provide less impact on the economic growth due to marginal impact of road network accessibility. According to the law of diminishing return, the impact of the transport infrastructure investment tends to decline in a well-established transport network (Deng, 2013). Thus, attention should be given to another transport system that has a better potential to improve regional connectivity, such as the railway network. As a result, large scale transport investment may play an essential role in promoting regional productivity that could not be achieved by any additional investment in the road network.
This study focuses on the KSA in terms of network expansion of the railway system and investment in transport sectors in general. This research is necessary due to the discrepancy in the existing literature about transport investment and subsequent improvement in economic productivity. Additionally, the impacts of transport investment on regional productivity have received less attention for countries where the economy is highly reliant on mineral extraction, such as in the case of the KSA. Although previous studies would provide the context with respect to the methodology, the findings may not be directly transferable to the case of the KSA which is unique in many aspects such as political, geographic location, and budget allocation. As the Saudi government is currently planning for the railway network expansion, this study is timely in its ability to inform their future decisions.
This paper attempts to fill this knowledge gap by examining the impact of large-scale transport investment on the economic development at the regional level for the KSA. The intended contribution of this study is an analysis of different advanced panel data techniques, including autoregressive models, to provide a better understanding of the nature of the relationship between transport investment and economic growth in the context of the KSA so as to provide recommendations for future infrastructure investment decision-making. It is anticipated that investing in different transport sectors and increasing the railway network coverage would boost the economic development in the KSA.
Section snippets
Literature review
One of the crucial factors that plays a significant role in a region's economic development is the existence of reliable and efficient transport infrastructure (Ozbay, Ozmen-Ertekin, & Berechman, 2003). This is generally explained by the assumption that a developed transport infrastructure which provides adequate access to the region is indispensable for the efficient operation of businesses. Developed countries enhance their productivity and trade through investment in the transport sector,
Theoretical framework
The empirical models are theoretically based on the conventional production function as shown in Eq. (1) (e.g. Aschauer, 1989). It is a common functional form as its assumptions are satisfied and statistically thorough. Following prior studies, the equation considers transport investment among several factors which may affect the regional economic development of a country (Démurger, 2001; Li, Liu, & Peng, 2018; Sahoo & Dash, 2010). Transport infrastructure development is deemed as a sign of
Case study outline
One of the goals of the KSA is to become a regional and international logistics hub by 2030. The government's strategy to achieve this goal identified transport infrastructure as a key component. Therefore, to meet the needs of economic growth and a growing population, the government is pursuing several transport projects. For instance, the road network has been expanded to reach 71,500 km.
Recently, the government granted the ministry of transport with SAR 1730 million ($461.3 million) to build
Data sources and processing
As discussed, the purpose of this study is to investigate the impact of transport investment on productivity (while controlling for other factors) in the KSA. In order to achieve this aim, data from the KSA on a range of variables is required. Since transport investment and economic productivity vary by space and time, a spatial-temporal database is essential to fully explore the relationship. Berechman et al. (2006) stated that the impact of highway investment on economic growth tends to
Model specifications
In the panel data regression analysis, the dependent variable is the log of regional economic growth, estimated by the real GDP. All independent variables are described in the previous section. To achieve the aim of this study, three variations of econometric models have been explored: (i) pooled regression models – OLS (Aschauer, 1990; Graham & van Dender, 2011; Hong, Chu, & Wang, 2011; Jiwattanakulpaisarn et al., 2009) (ii) panel data regression (e.g. fixed effects models and random effects
Measurements of model accuracy
To obtain the most accurate model among several empirical models, this study applies the regression accuracy measures. Mean Absolute Percentage Error (MAPE) is considered as one of the most common accuracy measures (Shcherbakov & Brebels, 2013). MAPE is applied in this study to check the level of accuracy of all the developed models. It indicates the size of the error of the model by comparing the predicted value with the real value. Moreover, other accuracy measures, such as Mean Absolute
Results and discussion
The results of the models are summarized in Table 3, Table 4. As can be seen in Table 3, the estimates of different static model specifications are presented: OLS, FEM, and REM respectively. Table 4 provides the estimates of two dynamic panel data techniques: the first difference GMM and system GMM which include different model specifications. The following paragraphs present and discuss the main output of the above-mentioned models.
Conclusion
This study contributes to literature by examining how transport investment promotes economic prosperity in the KSA. We investigate how transport investment in general and railway sector in specific (large-scale projects) has influenced regional productivity. Based on panel data for 13 KSA regions from 1999 to 2018, the results obtained from several alternative (static and dynamic) modelling frameworks persistently show that transport investments, measured in terms of the transport budget
Disclosure of interest statement
The scholarship reported in this paper is not impinged by any outside interest and the publication of the paper provides no further benefit to the authors other than through their academic careers.
Author statement
The research reported in this paper stems from doctoral studies undertaken by Saleh Alotaibi. The remaining authors listed on the paper represent the supervisory team which guided the doctoral studies of Saleh Alotaibi.
While the research is funded by the Kingdom of Saudi Arabia government, the study is impartial and is not affected by any political agenda.
Acknowledgements
The authors would like to acknowledge the help and support from the Public Transport Authority and the Saudi Railway Company for providing all the needed data and GIS used in this study. This work was presented at Transportation Research Board 98th Annual Meeting by the authors. The authors sincerely appreciate the feedbacks received at the conference. This research project has received funding from the Kingdom of Saudi Arabia.
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