 Time Series Modeling and Forecasting Information: Evidence from NigeriaIkechukwu Kelikume and Adedoyin Salami The International Journal of Business and Finance Research, 2014, vol. 8, issue 2, 41-51 Abstract: A major concern of entrepreneurs and monetary authorities in Nigeria in the past decades was successful prediction general price level movements. The results allow successful planning on the part of monetary authorities and continued profit drive on the part of entrepreneurs and investors. This study uses a univariate model in the form of Autoregressive Integrated Moving Average model developed by Box and Jenkins and multivariate time series model in the form of Vector Autoregressive model to forecast inflation for Nigeria. This paper use changes in monthly consumer price index obtained from the National Bureau of Statistics and the Central bank of Nigeria over the period 2003 to 2012 to predict movements in the general price level. Based on different diagnostic and evaluation criteria, the best forecasting model for predicting inflation in Nigeria is identified. The results will enable policy makers and businesses to track the performance and stability of key macroeconomic indicators using the forecasted inflation. Keywords: Modeling Inflation; Forecasting; ARIMA; VAR (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ibf:ijbfre:v:8:y:2014:i:2:p:41-51 Access Statistics for this article The International Journal of Business and Finance Research is currently edited by Terrance Jalbert More articles in The International Journal of Business and Finance Research from The Institute for Business and Finance Research |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.