This paper's main aim is to analyse the linkage between technology and Long-Run (LR) Economic Growth (EG) in the context of selected countries with and without abundant natural resources, considering a balanced panel dataset from 1994 to 2019. We find the existence of cross-sectional dependence across the total and split samples of resource-rich and resource-scarce countries. Given the high persistence of cross-sectional dependence, we apply the second-generation Durbin-Hausman cointegration test and find that the variables from the proposed models across samples indicate cointegrated relationships in the LR. We use the second-generation dynamically improvised Cross-Sectional Distributed Lag (CS-DL) method for the LR estimations. We reveal that there is a significant growth dynamics heterogeneity between and within resource-rich and resource-scarce cohorts. Countries within each cohort have been progressing regarding the technological impact in the LR EG due to their respective development stages, behavioural patterns, and group-specific economic structural aspects. However, we find evidence of the resource curse symptom between sub-cohorts since the impact of technology on LR EG is greater in sub-cohorts that have limited resources. We also provide a few useful recommendations, such as improving human capital for better adaption of technology and institutional reforms in resource-rich countries.