Abstract
Inadequate transport infrastructure in South Asian economies is one of the critical factors as this phenomenon hinders market competition due to the lack of goods transportation from urban to rural areas or vice versa. Given this, we solve the plausible research question of whether transport infrastructure development is adequate for inclusive growth in South Asian countries. This study contributes to constructing inclusive growth and transport infrastructure indices. However, this study measures transport infrastructure's impact on inclusive growth by applying the cross-sectional auto-regressive distributed lag model (CS-ARDL) approach from 1990 to 2020. Our empirical findings confirm that transport infrastructure significantly elevates inclusive growth by declining income inequalities in South Asian Economies in both the short and long runs. Finally, the two-way fixed effect with Driscoll and Ķraay standard error (DKSE), the dynamic ordinary least square (DOLS) and the fully modified ordinary least square (FMOLS) techniques are applied for the findings' robustness test. The results from the CS-ARDL method are consistent with the outcomes found from these three alternative parameters, i.e., DKSE, DOLS and FMOLS. Therefore, our findings suggest reinforcing the transport infrastructure to promote spectacular inclusive growth in South Asian countries.
| Original language | English |
|---|---|
| Article number | 101013 |
| Journal | Research in Transportation Business and Management |
| Volume | 49 |
| DOIs | |
| State | Published - Aug 2023 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2023 Elsevier Ltd
Keywords
- CS-ARDL technique
- Driscoll and Ķraay standard error approach
- Inclusive growth
- South Asian economies
- Transport infrastructure
ASJC Scopus subject areas
- General Decision Sciences
- Business and International Management
- Transportation
- Economics, Econometrics and Finance (miscellaneous)
- Tourism, Leisure and Hospitality Management
- Strategy and Management
- Management Science and Operations Research