Export led growth hypothesis and endogenous growth theory asserting that exports of goods and services and imports of capital goods can influence the economic growth. This paper investigates the dynamic relationship betwixt regional exports and growth of economy in East African countries particularly Kenya and Tanzania, grounded in the export-led growth hypothesis and endogenous growth theory. Utilizing a panel dataset from the World Development Indicators spanning 1970 to 2023, we analyze economic growth, proxied by GDP in current US dollars, alongside regional exports from Sub-Saharan Africa, South Asia, East Asia and Pacific, the Arab World and Imports. We utilize the Levin-Lin-Chu (LLC) test for assessing unit roots, as well as the Kao cointegration test to evaluate cointegration relationships. Thereafter panel ARDL-Pooled Mean Group (Panel-ARDL-PMG) was estimated. Empirical findings reveal that all variables are non-stationary at level and once differenced becomes stationary. Again, variables have long run relationship means are cointegrated. Employing the panel ARDL-Pooled Mean Group methodology, our findings indicate that exports from South Asia and East Asia and Pacific, along with imports, significantly contribute to economic growth, while exports from Sub-Saharan Africa and the Arab World adversely impact growth in the long run. In the short run, only imports and exports from the Arab World positively influence economic growth, whereas other regions hinder growth. These results suggest that policymakers should enhance international trade policies to boost export contributions to economic growth, particularly by focusing on improving export quality and diversifying trade partnerships. Strengthening these aspects can foster sustainable economic development in Kenya and Tanzania.
Relevance of the Study. Given the digital transformation of the economy and the growing social importance of healthcare, analyzing the efficiency of financial resource use in the sector and its impact on medical personnel productivity is particularly relevant. Increased government and insurance spending, the introduction of mandatory social health insurance, and the rapid development of digital technologies, including artificial intelligence-based solutions, require a rethinking of traditional approaches to assessing the effectiveness of healthcare financing. The aim of the study is to identify and economically substantiate the relationship between healthcare financing and labor productivity in the context of digital technology implementation. The results demonstrate that increased healthcare financing, accompanied by the digitalization of processes and the implementation of AI solutions, contributes to increased labor productivity by reducing unproductive labor costs, streamlining clinical and administrative processes, and more efficient use of human resources. It has been established that, given the limited share of healthcare spending in GDP, the key factor in sustainable growth is improving the efficiency of financial resource use, rather than increasing its quantitative growth. Conclusions. It is concluded that digital technologies and artificial intelligence are important tools for transforming financial resources into increased labor productivity and the sustainability of the healthcare system. The effect of digitalization is most significant with targeted financing and the comprehensive implementation of digital solutions integrated into the management and performance evaluation system.
