Thailand's transition to high-income status is, at its core, an urban challenge. Bangkok generates nearly half of national GDP, yet its dominance is increasingly constrained by congestion, environmental stress, and diminishing returns to further concentration. Successive National Spatial Development Strategies have called for a more multi-nodal urban hierarchy, but the analytical basis for evaluating that ambition has remained thin. This paper builds and calibrates a Dynamic Recursive Spatial Quantitative General Equilibrium model for Thailand's urban system from 2025 to 2050, and uses it to evaluate three counterfactual policy portfolios that allocate the same aggregate productivity-investment envelope (roughly 2.3 percent of 2030 urban GDP) across Bangkok and the eleven designated secondary cities in different proportions: a Bangkok-leaning portfolio (80/20), a balanced portfolio (50/50), and a secondary-leaning portfolio (20/80). The Bangkok-leaning portfolio leads through 2045, but the secondary-leaning portfolio overtakes it between 2045 and 2050, delivering a 12.38 percent gain in national GDP per capita above the no-investment baseline against 11.62 percent for the Bangkok-leaning alternative. The balanced portfolio is dominated by both skewed alternatives at 2050, reflecting a threshold property of agglomeration economies. A two-dimensional envelope-by-split sweep shows that the relative ranking is genuinely contingent on the scale and horizon of the commitment: below a certain tipping point, the Bangkok-leaning portfolio dominates; above it, the secondary-leaning portfolio does. A modest, well-allocated spatial-investment programme is unlikely to be the engine of Thailand's high-income transition; sufficient scale of commitment is a precondition.
| Repository name | URI |
|---|---|
| Reproducible Research Repository (World Bank) | https://reproducibility.worldbank.org |
Paper exhibits were reproduced on a computer with the following specifications:
• OS: Windows 11 Enterprise
• Processor: INTEL(R) XEON(R) PLATINUM 8562Y+ (2.80 GHz) (2 processors)
• Memory available: 32.0 GB
Run time: ~ 75 minutes
To reproduce the findings in this paper from raw data, a replicator must:
THAAM26.Rproj, and restore the environment by running renv::restore() and following the prompts.main.R and run the code.To reproduce the findings in this paper from processed data, a replicator must:
THAAM26.Rproj, and restore the environment by running renv::restore() and following the prompts.THAAM26_SQGE_Reproducibility_FINAL.All data sources are publicly available but not included in the reproducibility package due to file size constraints.
| Author | Affiliation | |
|---|---|---|
| Putu Sanjiwacika Wibisana | World Bank | pwibisana@worldbank.org |
| Steven Louis Rubinyi | World Bank | srubinyi@worldbank.org |
2026-07-06
| Location | Code |
|---|---|
| Thailand | THA |
The materials in the reproducibility packages are distributed as they were prepared by the staff of the International Bank for Reconstruction and Development/The World Bank. The findings, interpretations, and conclusions expressed in this event do not necessarily reflect the views of the World Bank, the Executive Directors of the World Bank, or the governments they represent. The World Bank does not guarantee the accuracy of the materials included in the reproducibility package.
| Name | URI |
|---|---|
| MIT License | https://opensource.org/license/mit |
| World Bank IGO Rider | https://github.com/worldbank/metadata-editor/blob/main/WB-IGO-RIDER.md |
| Name | Affiliation | |
|---|---|---|
| Putu Sanjiwacika Wibisana | World Bank | pwibisana@worldbank.org |
| Reproducibility WBG | World Bank | reproducibility@worldbank.org |
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Reproducibility WBG | DECDI | World Bank - Development Impact Department | Verification and preparation of metadata |
2026-07-06
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