The spatial spillover effects of small and medium-sized enterprise clusters and industrial estates on the unemployment rate: evidence from Java

Reflecting the dominance of Java’s manufacturing industry at the national level, this study examines the relationships between industrial agglomeration at the micro, small, and medium enterprise (MSME) cluster level, medium and large industrial estate (IE) industries, and the unemployment rate (UR). The study investigates the spread and backwash effects that arise from industrial agglomeration and resulting spatial externalities on surrounding areas. The panel dataset covering 119 districts/cities in Java, Indonesia from 2014 to 2021 includes degrees of agglomeration in IE areas and among MSMEs, regions’ unemployment rate, and regional socioeconomic variables. The study applies exploratory spatial data analysis (ESDA) and a spatial autoregressive (SAR) model to describe and examine spatial externalities. The ESDA reveals highly centralized IEs and MSMEs in northern and central Java, respectively. The SAR model demonstrates that IE agglomeration has a significantly positive direct effect on the unemployment rate, whereas MSME agglomeration has a negative but statistically negligible impact. The positive correlation between agglomeration in industrial areas and the unemployment rate indicates that the quality of current human resource mechanisms does not match the industry expectations, and the negative correlation between MSME agglomeration and unemployment rate reinforces this challenge. These insights suggest a need to developin tegrated policies to address regional unemployment challenges considering the decentralized authority of each district/city. The significant spatial externalities of unemployment rates between regions and the repercussions of industrial areas’ agglomeration in Java necessitate effective labour market integration and regional cooperation. The study demonstrates this need by examining the different labour absorption mechanisms between IEs and MSMEs for confronting unemployment challenges.