Mohammad Akbar Hossen; Smaria, Ibnali Issah Kulo, Sunusi Ahmad Abdullahi
Abstract: The unemployment rate remains a significant issue worldwide for the most recent couple of years for both developed and developing nations. It has consistently been an exceptionally engaged issue making a country lose its monetary and budgetary commitment. This study aims to forecast the changes in the unemployment rate after the attack of COVID-19. This study recommends an incorporated methodology dependent on direct and nonlinear models that can anticipate the unemployment rates. The projected crossbreed model of the unemployment rate can improve their estimates by mirroring the unemployment rate’s irregularity. The model’s purposes have been demonstrated after the attack of COVID-19, utilizing seven unemployment rate informational collections from different nations, in particular, United Arab Emirates, Saudi Arabia, Azerbaijan, Malaysia, South Korea, and Kazakhstan.
The outcomes for asymptotic stationarity of the anticipated mixture move toward utilizing Markov chains and nonlinear time arrangement investigation strategies are given. This paper ensures that the future model can’t illustrate ‘hazardous’ conduct or developing change after some time.
[ FULL TEXT PDF 1-7 ] DOI: 10.30566/ijo-bs/2020.39
