~5~ International Journal of Statistics and Applied Mathematics 2019; 4(1): 05-17 ISSN: 2456-1452 Maths 2019; 4(1): 05-17 © 2019 Stats & Maths www.mathsjournal.com Received: 04-11-2018 Accepted: 08-12-2018 Shem Otoi Sam PhD Student, School of Mathematics, University of Nairobi, Kenya Ganesh P Pokhariyal Professor, School of Mathematics, University of Nairobi, Kenya MM Manene Professor, School of Mathematics University of Nairobi, Kenya Dr. Isaac C Kipchumba School of Mathematics University of Nairobi, Kenya Correspondence Shem Otoi Sam PhD Student, School of Mathematics, University of Nairobi, Kenya Reparameterization of vector error correction model from auto-regressive distributed lag to analyze the effects of macroeconomic shocks on youth employment in Kenya Shem Otoi Sam, Ganesh P Pokhariyal, MM Manene and Isaac C Kipchumba Abstract This study analyzes the effects of reparameterization of autoregressive distributed lag (ARDL) to vector error correction model (VECM) through cointegration of time series. It further verifies the effects of macroeconomic shocks on youth unemployment in Kenya using VECM. First, the unit root test has been done on youth unemployment (YUN), gross domestic product (GDP), external debt (ED), foreign direct investment (FDI), private investment (PI), youth literacy level (LR), and youth population (POP) to verify stationarity. The Johansen Cointegration Test has been employed and revealed three long run relationships which can be interpreted as a GDP effect, External Debt effect and Foreign Direct Investment effect relations. A structural VECM has been described through restrictions derived from the Cointegration Analysis. Based on the results of the Impulse-Response Function analysis and variance decomposition analysis of the Structural VECM, it is concluded that GDP, literacy level, population, Private Investment, External and FDI shocks have significant effects on Kenyan youth unemployment in the long run. Based on the results of the Impulse-Response Function and variance decomposition analyses of the Structural VECM, it is concluded that GDP, literacy level, population, and FDI shocks have significant effects on Kenyan youth unemployment in the long run. Whereas population, external debt, private investment, and GDP have positive effects, foreign direct investment and literacy rate have negative effects on youth unemployment in the long run. The results provide a statistical basis for assessing and prioritising investment policies and initiatives to maximise youth employment and attain the demographic dividend. Keywords: structural error correction model, cointegration 1. Introduction The demographic dividend, defined as the opportunity to achieve rapid socio-economic development resulting from decline in fertility levels and targeted investments in intensive employment sectors, has been deemed a solution to many problems being experienced by African countries. The African Union adopted a common position on the Post 2015 Development Agenda that resulted in the incorporating demographic dividend in the 2030 Agenda for Sustainable Development. In this way, the African Union formulated the theme “Harnessing the Demographic Dividend through investments in Youth” for the year 2017. The Kenya constitution defines youth as persons between the ages of 18 and 34. In Kenya, the youth constitute 35% of the population. The youth in Kenya are experiencing much higher unemployment rates 67% compared to the rest of population at 34%. The Kenyan labour market is one that is characterized by inadequate employment opportunities against a large and growing population of unemployed young people. It is dual in nature, presenting a small formal sector alongside a large informal sector. Over 30% of those on wage employment are casuals. Youth with primary education are in formal employment 4%, informal employment 54%, students 14% and unemployed 28%. Those with secondary education in: formal employment 12%; informal employment 40%; students 26%; and unemployed 22%. While those with tertiary education are in: formal employment 31%;