Technology is progressing rapidly and is increasingly disrupting production patterns around the world. A recent study by the World Bank shows that the increasing use of industrial automation, modern robotics and smart factories is transforming the manufacturing process and change work (Hallward-Dremayer and Nayar, 2017). Imports by developing countries of these new technologies can boost productivity, drive down costs, and support the speed of technology diffusion and catch-up. the technologies, However, create risks for those countries to the degree that they might be labor-saving and replace low-skilled jobs (Frey and Dereh, 2016).

The purpose of this study is to investigate the direct and indirect impact of technology imports on industrial employment in 10 East and Southeast Asian countries during the period 2000-2021. For this purpose, the panel smooth transition regression model (PSTR), which is very suitable for heterogeneous panel data, has been used.

the PSTR approach has been proven to manage perfectly different types of nonlinearities (sharp or smooth switch between regimes) without any extant information about the structural change of the transition variable. Secondly, the PSTR model handles main econometric issues such as heterogeneity and time variability by permitting parameters to vary smoothly on individual cross-sections and time (Wang and Wei, 2019).

The PSTR approach is more appropriate for modeling the heterogeneous effect due to differences in different levels of technology imports, in examining the direct and indirect impact of technology imports on industrial employment in East and Southeast Asian countries.

The present study aims to investigate the direct and indirect impact of technology imports on industrial employment in 10 East and Southeast Asian countries over the period 2000-2021, modeling the relationship between the variables under study using the PSTR econometric technique and a nonlinear approach.