FUW TRENDS IN SCIENCE & TECHNOLOGY JOURNAL
(A Peer Review Journal)
e–ISSN: 2408–5162; p–ISSN: 2048–5170
keywords: ARIMA, forecast, unemployment rates, ADF unit roots test, macroeconomic
Unemployment rate is a big macroeconomic issue of our time. Unemployment disrupts lives and is associated with an irrecoverable loss of real output. This paper aims to modeling and forecast the evolution of unemployment rates in Nigeria using ARIMA model on annual data for the period of 1972 to 2014. The Augmented Dickey-Fuller (ADF) test for unit root was carried out on the unemployment rate time series, the result revealed a stationary time series at first difference. The empirical study revealed that the most adequate model for modelling and forecasting the unemployment rates within this period in Nigeria is ARIMA (2,1,2). The forecast of unemployment rate in Nigeria revealed an increasing rate from 2015 to 2017 while a slight decrease in 2018. During this period of 2015 to 2018 unemployment rates is still very high in Nigeria. This present administration should focus on capital project that has the capacity to create employment.
Adekeye KS & Aiyelabegan AB 2006. Fitting an ARIMA Model to Experimental Data.Nigerian Statistical Association (NSA) Conference Proceedings, pp. 65 – 72. Adenomon MO 2016. An Introduction to Univariate and Multiple Time Series Analysis wit Examples in R, Jube-Evans Books and Publications, Niger State, Nigeria, p. 8. Adeyi EO 2012. Unemployment and Inflation in Nigeria: An Empirical Investigation. Economic Dynamics & Policies, 85 - 88. Aminu U, Manu D, El-Maude JG & Kabiru MY 2013. Relationship between crime level, unemployment, poverty, corruption and inflation in Nigeria (An empirical analysis). Glo. Adv. Res. J. Mgt. Bus. Stud., 2(8): 411- 422. Box GEP, Jenkins GM & Reindel GC 1994. Time Series Analysis, Forecasting and Control, 3rd edn. Prentice-Hall, Inc., New Jersey, pp. 89–96. Bula YB 2014. The Relationship between Inflation, Employment and Economic Growth in Nigeria: 1970-2012. M.Sc Thesis, Ahmadu Bello University, Zaria. Byrne D & Strobl E 2001. Defining Unemployment in Developing Countries: The Case of Trinidad and Tobago. CREDIT Research Paper No. 01/09. University of Nothingham. Dobre I & Alexandru AA 2008. Modelling unemployment rate using Box-Jenkins procedure. J. Appl. Quantit. Methods, 3(2): 156 – 166. Ejikeme JN 2014. Unemployment and poverty in Nigeria: A link to national insecurity. Global J. Politics & Law Res., 2(1): 19 - 35. Eme OI 2014. Unemployment Rate in Nigeria: Agenda for Government. Acad. J. Interdis. Studies, 3(4): 103 - 114. Furuoka F 2008. Unemployment and inflation in the Philippines. Philippine J. Dev., XXXV(1): 93 - 106. Granger CWJ & Newbold P 1974. “Spurious regressions in econometrics”. Journal of Econometrics, 2: 111 120 Gujarati DN 2003. Basic Econometrics, 4th edn. The McGraw-Hill Co, New Delhi, pp. 835 – 848. Kendall M & Ord JK 1990. Time Series, 3rd edn. Edward Arnold ,Great Britain, pp. 104 – 120. Lipsey RG & Chrystal KA 1999. Principles of Economics, 9th edn. Oxford University Press, United States. pp. 529 – 544. Ljung GM & Box GEP 1978. On a Measure of Lack of Fit in Time Series Models. Biometrika 69: 297 - 303. Msigwa R & Kipesha ER 2013. Determinants of youth unemployment in developing countries: Evidence from Tanzania. J. Eco. & Sust. Dev., 4(14): 67 – 76. Salvatore D & Reagle D 2002. Schaum’s Outline of the Theory and Problems of Statistics and Econometrics, 2nd edn. McGraw-Hill Company, New York, pp. 242 – 248. Shangodoyin DK & Ojo JF 2002. Elements of Time Series Analysis. Rashed Publications Ltd, Ibadan, pp. 34 – 59 Vodopivec M 2009. Introducing Unemployment Insurance to Developing Countries. SP Discussion Paper No. 0907. The World Bank. Yule GU 1926. Why do we sometimes get nonsense correlation between time series? A study in sampling and the nature of time series. J. Royal Stat. Soc., 89: 1 - 64.
