Tag Archives: Unit Root

CBN Monetary Policy and Inflation Nexus in Nigeria: An empirical approach (Published)

The study explored monetary policy effect on inflation stabilization in Nigeria. Increasing levels of indebtedness may have reduced the fiscal space for fiscal policy intervention and this leaves monetary policy as the real tool of choice for macroeconomic stabilisation. The question we need to ask then is, how effective is this tool of choice? Monthly time series data from 2009-2018 were used in estimating the model. The ADF test for the stationarity, the johansen cointegration test and the vector error correction model were utilized in testing the variables. The findings from the unit root test did indicate stationarity at first difference 1(1). The cointegration (Johansen) test indicates that there was a nexus linking inflation and all the regressors adopted in the long term. The result of the VECM for the two estimated models shows a self-equilibrating mechanism of 14 per cent and 32 per cent for the first and second models respectively. The findings further reveal that the variables; liquidity ratio, policy rate (MPR), exchange rate, reserve requirement and treasury bills rate all had an effective impact on the inflation rate and that that effect was very significant.  Hence, the CBN’s monetary policy shocks do seem to have the expected traction on the Nigerian economy. The results make it pertinent for the CBN to utilize all the policy measures adopted in order to keep inflation within acceptable thresholds and prepare to keep inflation within the targeted range of 6-9 per cent, no matter the anticipated or unanticipated strong head winds.

Keywords: ADF, CBN, Cointegration, Monetary Policy, Unit Root, VECM

Autoregressive Integrated Moving Average (Arima) Model for the Major Airline Disasters in the World from 1960 Through 2013 (Published)

This research fit a univariate time series model to the major Airline Disasters in the world from 1960 through 2013. The Box-Jenkins Autoregressive Integrated Moving Average (ARIMA) model was estimated and the best fitting ARIMA model was used to obtain the post-sample forecasts for five years. The fitted model was ARIMA (0,1,1) with Akaike Information Criteria (AIC) of 323.14, Normalized Bayesian Information Criteria (BIC) of 327.04, Stationary R2 of 0.348.This model was further validated by Ljung-Box test with no significant Autocorrelation between the residuals at different lag times and subsequently by white noise of residuals from the diagnostic checks performed which clearly portray randomness of the standard error of the residuals, no significant spike in the residual plots of ACF and PACF. The forecasts value indicates that Airline Disasters will increase slightly with almost equal number of cases for the next five years (2014-2018).

Keywords: ARIMA, Airline Disasters, Box- Jenkins, Forecast, Ljung-Box, Stationarity, Time Series, Unit Root

Estimating Money Demand for Ghana (Published)

The study suggested that money demand function for Ghana using M1 and M2 remained relatively unstable between 1991 and 2011 as evidenced by trends in recursive residual and the cumulative sums of squared residuals derived from the estimated models. However, real money demand function for broad money (M2+) was found to be stable relative to real money   demand functions estimated using for M1 and M2 as dependent variables. The study therefore concluded that real money demand function for M1 and M2 are remained relatively unstable in Ghana compared with real money demand function for broad money which exhibits some degree of stability.

Keywords: Demand, Money, Recursive, Unit Root