System and Neural Network Analysis of Economic and Financial Development – A case study of Dubai and rest of UAE



Published Apr 15, 2018
Genanew B Worku Ananth Rao


The study examines the factors affecting the economic and financial development by applying Zellner’s seemingly unrelated regressions (SURE) and Neural Network techniques. It applies multivariate and neural network frameworks for analysing the GDP of Dubai and rest of UAE using data for 2001–2015. The study shows that there exists positive interdependencies between Dubai and rest of UAE economies. This signifies that the core competencies across various sectors in Dubai and rest of UAE economies need to be promoted further to have overall diversified impact on UAE economy. The positive sizable impact of the finance sector in Dubai and negative sizable impact in the rest of the UAE provide many opportunities for designing diversification programs for sustained economic development of the entire UAE economy. The small sample size, non-availability of detailed sectoral data in four of the seven emirates constrained the scope of the study for generalization to other economies in the Middle East. The study findings are crucial for identifying structural reforms, to strengthen competitiveness and accelerate private sector-led job creation for nationals, potential on further opening up foreign direct investment (FDI), improving selected areas of the business environment, and easing access to finance for start-ups and SMEs in both the economies.

JEL: C32, C52, D85, N15, N25

How to Cite

Worku, G. B., & Rao, A. (2018). System and Neural Network Analysis of Economic and Financial Development – A case study of Dubai and rest of UAE. International Review of Advances in Business, Management and Law, 1(1), 51–67.


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SURE System analysis, Neural Network analysis, Dubai, UAE, GDP, Economic & financial Development, FDI



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