Ports as catalysts: spillover effects of neighbouring ports on regional industrial diversification and economic resilience

ABSTRACT

Recognising the intricate link between ports and regional economies, this study investigates the spillover effects of neighbouring ports on regional industrial diversification and economic resilience. Analysing South Korea’s 2006–20 export data from port and neighbouring port regions, it uncovers the unique feature of ports as a distinctive knowledge source within their port regions, mainly attributable to the respective logistic and trade systems governing similar product groups. The paper confirms that ports facilitate industrial diversification through spillover effects when it is related with the regional industries. Emphasising ports’ role in strengthening economic resilience, it highlights their significance in nurturing emerging industries post-crisis.

KEYWORDS:

• regional development
• relatedness
• industrial diversification
• knowledge spillover
• global production networks

JEL:

• L52
• O14
• O33
• R11

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the authors.

Notes

1. To compensate for the loss of information caused by ruling out such missing values, we consider the number of ports where each region ships each product as a control variable to the regression model.

2. According to the literature (Catalán et al., 2020; Jun et al., 2020), a three-way fixed-effect regression model, including a product fixed-effect term, would be a good alternative in this study. Therefore, we also conduct a three-way fixed-effect estimation using the extended version of the original two-way fixed-effect model with the two-digit product fixed effect to control the distinct characteristics of each product group at the industry level. The corresponding results are shown in Tables A5–A8 in Appendix A in the supplemental data online.

3. For the period 2008–16, we apply both the forward and backward conditions, but we only apply the forward condition for 2017–18 and the backward condition for 2006–07 due to the data limitations.

4. According to Hidalgo et al. (2007), we can apply the revised version of the classification introduced by Leamer (1984): petroleum (Leamer 1), raw materials (Leamer 2), forest products (Leamer 3), tropical agriculture (Leamer 4), animal agriculture (Leamer 5), cereals (Leamer 6), labour intensity (Leamer 7), capital intensive (Leamer8), machinery (Leamer 9) and chemicals (Leamer 10).

5. In Table A6, column (8), in Appendix A in the supplemental data online, only with variables related to neighbouring ports shows a similar size of the estimator of ω compared with the result in Table 3 with no significant difference, suggesting that the knowledge spillover from ports is neither a competitive nor a substitutive effect to the typical production knowledge spillover within regions.

 

Additional information

Funding

This project was funded by the National Research Foundation of Korea [grant numbers NRF-2022R1A2C1012895 and NRF-2022R1A5A7033499]. We also acknowledge the support from Inha University.