Loughborough University
Browse
PhD_Thesis_Saleh_Alotaibi_ID_B533048_Final.pdf (3.98 MB)

Assessing the impact of transport investment and railway accessibility on economic productivity

Download (3.98 MB)
thesis
posted on 2022-07-04, 15:05 authored by Saleh Al-Otaibi

Several attempts have been made to empirically investigate the linkage between transport infrastructure investments and economic development. However, they yielded inconsistent results due to a variety of factors such as different analytical approaches utilized, different geographical levels, or different variables included. This research examines the impact of large-scale transport investment and the network expansion of the railway on the economic development represented in Gross Domestic Product (GDP) in the Kingdom of Saudi Arabia (KSA). Spatial and temporal economic data for the 13 regions of the country from 1999 to 2018 are analysed using parametric and non-parametric techniques. The parametric approach includes employing advanced static and dynamic panel data models to quantify the impact of transport investment and improved railway accessibility on regional economic development. The Generalized Method of Moment (GMM) models fit the data satisfactorily and offered better modelling accuracies. The results find that the impact of the monetary value of transport investment, in general, was manifested in the following year. However, the railway accessibility improvement requires two years to deliver its benefits.

The breadth of this research's contribution also includes measuring the regional efficiency change over time and determining the drivers of (in)efficiency and their scope of improvement. The study used non-parametric linear programming technique, Data Envelopment Analysis (DEA). Outcomes reveal that transport investment and improved railway accessibility, in general, have significantly improved the regional efficiency. For, example, three regions have become efficient after the new expansion in transport investment rather than just one efficient region. In addition, it has been noticed that the scale efficiency score improved for the regions that experienced railway infrastructure development. Those regions are Riyadh, Makkah, Eastern Province and Hail, which their scale efficiency score was increased by 9%, 8%, 6%, and 2%, respectively. There is also evidence of a spill-over effect in areas that are not directly connected to the new railway network.

The investigation extended to include Window DEA analysis which confirmed the dynamic improvement in the average regional efficiency over the study periods. Moreover, the Malmquist Productivity Index (MPI) showed that the technical efficiency change was the main source of regional productivity improvement in the KSA. In addition, it showed that five regions (Riyadh, Makkah, Northern Border, Najran and Qassim) were representing the KSA's best-productive regions after 2016 amongst other regions. However, there is evidence of investment allocation discrepancy among regions which could limit the achievement of development goals in long term.

The study's intended contribution is an examination of various advanced static and dynamic panel data techniques, as well as regional efficiency measures, in order to provide a better understanding of the nature of the relationship between transport investment and economic development in the context of the KSA, and to make recommendations for future infrastructure investment decision-making. These relevant findings will assist the Saudi government to develop better strategic decisions for future transport investments and their allocation at regional level.

Funding

Saudi Arabia

History

School

  • Architecture, Building and Civil Engineering

Department

  • Aeronautical and Automotive Engineering

Publisher

Loughborough University

Rights holder

© Saleh Awad Alotaibi

Publication date

2021

Notes

A Doctoral Thesis. Submitted in partial fulfilment of the requirements for the award of the degree of Doctor of Philosophy of Loughborough University.

Language

  • en

Supervisor(s)

Mohammed Quddus ; Craig Morton

Qualification name

  • PhD

Qualification level

  • Doctoral

This submission includes a signed certificate in addition to the thesis file(s)

  • I have submitted a signed certificate