Investigating Predictors of Inflation in Nigeria: BMA and WALS Techniques

Mohammed M Tumala, Olusanya E Olubusoye, Baba N Yaaba, Olaoluwa Yaya and Olawale B Akanbi
Authors registered in the RePEc Author Service: Yaaba Baba Nmadu ()

MPRA Paper from University Library of Munich, Germany

Abstract: The recent economic conundrum arising from the fall in the international oil price has threatened the maintenance of price stability, a key function of the central bank, therefore the need to investigate predictors of inflationary measures arises. The model averaging method considers uncertainty as part of the model selection, and include information from all candidate models. We analysed a wide spectrum of inflation predictors and all the possible models for Nigeria CPI inflation using the Bayesian Model Averaging and Weighted Average Least Squares. The study uses fifty-nine (59) predictor variables cutting across all sectors of the Nigerian economy and three (3) measures of inflation, namely; all items consumer price index, core consumer price index and food consumer price index. The results from both model averaging techniques showed that maximum lending rate, world food price index and Bureau de change exchange rate are the significant drivers of inflationary measures among focus variables, while foreign assets, credit to private sectors, net credit to government and real effective exchange rate are the drivers of inflationary measures, for the auxiliary variables, strongly supporting the monetarist and open economy views on inflation. The structuralist view is reported to be relatively weaker because government expenditure is only significant at 10.0 per cent..

Keywords: Bayesian estimation; BMA; Frequentist approach; Inflation rate (search for similar items in EconPapers)
JEL-codes: C20 C4 (search for similar items in EconPapers)
Date: 2017, Revised 2018-02
New Economics Papers: this item is included in nep-mac and nep-mon
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Published in African Journal of Applied Statistics 1.5(2018): pp. 301-321

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