Spatial analysis of urbanization and economic development in Thailand

This study aims to guide regional and urban development policy by addressing Thailand's extreme spatial inequality and inadequate urban planning. The study seeks to reduce regional economic disparity and promote sustainable urban development by investigating the mechanisms governing the spatial distribution of economic activities. This study employed both conventional ground surveys and satellite data to overcome the limitations that previous research efforts have incurred.Chapters 2 and 3 examined the causal relationship between economic outcomes and urbanization. Chapter 2 utilized a two-stage estimation method, incorporating clay content in the soil as an instrumental variable. The findings reveal that wage differentials were significantly influenced by workers' education, experience, and agglomeration externalities in larger cities. The study recommends creating multiple regional cities to generate agglomeration externalities.Based on the recommendations of Chapter 2, Chapter 3 investigated the driving factors of urbanization over the past two decades. The study shows that urbanization in Thailand was driven by urban sector productivity growth, the share of workers with higher education, and favorable environmental factors such as water availability. Spatial spillover of urbanization was also observed. The findings suggest maximizing the economic potential of each region to support polycentric urbanization through productivity enhancement mechanisms.Chapter 4 forecasted urban land expansion and economic growth in Ban Chang district, a rapidly developing city in Thailand. Geospatial data from Google Earth Engine and a web-based application developed for the study were utilized. A recursive dynamic model was applied to achieve the research's goals and demonstrated an average spatial accuracy of 92 percent. The model's ability to forecast urban land expansion and economic growth at the district level was also showcased. This framework, relying on open data and open-source software, enables cost-effective monitoring and forecasting of urbanization and economic development, facilitating a proactive approach to urban planning.The study highlights the need to address spatial inequality and inadequate urban planning through evidence-based approaches, recommending strategies such as creating regional cities, productivity enhancement mechanisms, and proactive urban planning processes.

本研究旨在解决泰国极端空间不平等与城市规划不足的问题，为区域与城市发展政策提供指引。本研究通过探究经济活动空间分布的作用机制，以期缩小区域经济差距、推动可持续城市发展。为克服既往研究存在的局限性，本研究结合了传统实地调研与卫星数据。第2章与第3章分析了经济成果与城市化之间的因果关系。第2章采用两阶段估计方法，以土壤黏土含量作为工具变量。研究结果显示，大城市的工资差距显著受劳动者受教育程度、工作经验以及集聚外部性（agglomeration externalities）的影响。本研究建议打造多中心区域城市，以释放集聚外部性效应。基于第2章的研究结论，第3章探究了过去二十年的城市化驱动因素。研究表明，泰国城市化受城市部门生产率增长、高等教育劳动者占比，以及水资源可获得性等有利环境因素驱动。同时研究还观测到城市化的空间溢出效应。研究结果提出，应通过生产率提升机制，充分释放各区域的经济潜力，以支撑多中心城市化发展。第4章对泰国快速发展的区域——班昌县（Ban Chang district）的城市土地扩张与经济增长进行了预测。本研究使用了来自谷歌地球引擎（Google Earth Engine）的地理空间数据，以及为本研究开发的网页应用程序。研究采用递归动态模型达成研究目标，该模型的空间平均准确率达92%，并验证了其在县域尺度下预测城市土地扩张与经济增长的能力。本框架依托开放数据与开源软件，可实现城市化与经济发展的低成本监测与预测，助力采取前瞻性的城市规划策略。本研究强调需通过循证方法解决空间不平等与城市规划不足的问题，并建议采取打造区域城市、完善生产率提升机制、优化前瞻性城市规划流程等相关策略。