Department of Statistics

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Browsing Department of Statistics by Author "Alemho, J.E."

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    Forecasting Some Selected Macroeconomic Variables with BVAR Models under Natural Conjugate Prior.
    (Department of Statistics, Nasarawa Sate University Keffi., 2022-11-11) Alemho, J.E.; Adenomon, Monday Osagie
    Bayesian VARs are mostly used in computational analysis of macroeconomic variables of a nation. The natural conjugate prior when combined with the likelihood function gives a posterior distribution that belong to the same distributional family. The study investigates the forecasting of some selected macroeconomic variables with BVAR Model using special types of natural conjugate prior called the symmetric and asym- metric natural conjugate prior. The data for the macroeconomic variables were obtained from the statistical bulletin of the Central Bank of Nigeria (CBN) ranging from 1986 to 2019. The forecasting assessment used is the Root Mean Square Factor Error (RMSFE). The RMSFE with small value indicates a better forecast performance. Forecasting the Macroeconomic variables with BVAR under the natural conjugate prior (symmetric and asymmetric natural conjugate prior), it was discovered from the study that asymmetric natural conjugate Prior is the best natural conjugate prior that should be used in forecast- ing macroeconomic variables of developing country like Nigeria. There is an inverse re- lationship between unemployment rate and other selected macroeconomic variables used in this study. Therefore, the policy makers should endeavor to formulate policies that will reinvigorate the economy so that single–digit inflation rate can be achieved and unem- ployment rate will be reduced to the barest minimum. This will help to boost the GDP and economy at large.
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    SIMULATION STUDY ON THE COMPARISON OF ERROR CORRECTION MODEL AND AUTOREGRESSIVE DISTRIBUTED LAG MODEL FOR NON-NORMALLY DISTRIBUTED DATA
    (Department of Statistics, Nasarawa Sate University Keffi., 2021-02-02) Alemho, J.E.; Adenomon, Monday Osagie
    This study investigates simulation study of the comparison between Error Correction Model (ECM) and Autoregressive Distributed Lag (ARDL) Model on non-normally distributed data. The study utilized both simulated data with 5000 iterations and the real life data of inflation rate and unemployment rate in Nigeria from a period of 1981 to 2016. The Augmented-Dickey Fuller (ADF) test revealed that inflation and unemployment are stationary at first difference while cointegration test and bound testing revealed an existence of long run relationship between the macroeconomic variables. The Root Mean Square Error (RMSE) of the simulated data of the two models were compared and the normality test (Jarque-Bera test) shows that the variables are non- normally distributed. The study revealed that the ARDL model outperforms the ECM model for both the real life data and simulated data and that there is evidence of both short and long run relationship between inflation rate and unemployment rate in Nigeria. It also revealed that there is causality relationship between inflation rate and unemployment. The study therefore recommended based on the findings that the Central Bank of Nigeria should pursue monetary policy that is consistent with the maintenance of a realistic and stable inflation rate in order to reduce the unemployment rate in Nigeria and the government should formulate adequate economic policies to stimulates and sustain the economic growth. In addition, the inflation rate should adequately check to achieve viable economy.