This study empirically developed a multivariate autoregressive distributed-lag (ARDL) model and a univariate autoregressive integrated moving average (ARIMA) model for inflation in Nigeria, ascertained the stability of the models, and compared the performance of the models. This study used quarterly time series data from 1988 to 2017. The data were sourced from the publications of the Central Bank of Nigeria (CBN) and the National Bureau of Statistics (NBS).The study applied the ordinary least squares (OLS) method with the aid of EViews software for estimation purposes. The study found that: (1) ARDL (4, 2, 2, 1) and ARIMA (2, 1, 3) were the most appropriate models of inflation in Nigeria under model identification, identification, estimation, and diagnostic checking; (2) inflation in Nigeria was largely expectations-driven; and (3) inflation in Nigeria was influenced by the exchange rate, interest rate, and broad money supply (liquidity) both in the short-run and in the long-run.The study recommended that: (1) a “one-model-fits-all” for inflation rate dynamics in Nigeria should be discouraged and that different models should employed to complement one another; (2) regulatory authorities should ensure a high degree of transparency in monetary policy making and implementation; and (3) efforts should be made by the regulatory authorities to control money supply and ensure exchange rate and interest stability, in order to stem inflationary tendencies.
A Comparative Analysis of Inflation Dynamics Models in Nigeria
Ibrahim Shaibu, Ph.D.
Associate Professor, Department of Business Administration, University of Benin, Benin City
Email: ibb.shaibu2013@gmail.com
Ifuero Osad Osamwonyi, Ph.D.
Professor, Department of Banking and Finance, University of Benin, Benin City
Email: ifueroosad@yahoo.co.uk
Abstract
This study empirically developed a multivariate autoregressive distributed-lag (ARDL) model and a univariate autoregressive integrated moving average (ARIMA) model for inflation in Nigeria, ascertained the stability of the models, and compared the performance of the models. This study used quarterly time series data from 1988 to 2017. The data were sourced from the publications of the Central Bank of Nigeria (CBN) and the National Bureau of Statistics (NBS).The study applied the ordinary least squares (OLS) method with the aid of EViews software for estimation purposes. The study found that: (1) ARDL (4, 2, 2, 1) and ARIMA (2, 1, 3) were the most appropriate models of inflation in Nigeria under model identification, identification, estimation, and diagnostic checking; (2) inflation in Nigeria was largely expectations-driven; and (3) inflation in Nigeria was influenced by the exchange rate, interest rate, and broad money supply (liquidity) both in the short-run and in the long-run.The study recommended that: (1) a “one-model-fits-all” for inflation rate dynamics in Nigeria should be discouraged and that different models should employed to complement one another; (2) regulatory authorities should ensure a high degree of transparency in monetary policy making and implementation; and (3) efforts should be made by the regulatory authorities to control money supply and ensure exchange rate and interest stability, in order to stem inflationary tendencies.
Keywords: Inflation Dynamics, ARDL, ARIMA, Expectations, EViews.
Introduction
Concern over inflation is a legitimate policy concern because persistence inflation is perhaps the second most serious macroeconomic problem confronting the world economy today—second only to hunger and poverty in the third World (Dwivedi, 2008). High inflation is detrimental to an economy because it distorts prices, depletes savings, discourages investment, fuels capital flight, hinders growth, and makes economic planning difficult. For these reasons, keeping inflation under control has been one of the most daunting tasks of monetary authorities of countries.
Achieving the objective of keeping inflation low and stable requires that its causes be identified and understood. The construction of scientific econometric models for inflation has become important in Nigeria because strategic decisions at all levels have been criticized for lack of analytical rigour and without the benefit of appropriate empirical framework (Adenikinju, Busari, & Olofin, 2009). The result has been that decision-making at all levels tend to rely relied upon macroeconomic forecasts that may not be anchored on scientific models that track major economic indices. Scientific economic models will enable policy makers to exercise their judgemental analysis in a much more structured and quantified manner and to develop a more adequate understanding of macroeconomic time line.
Some researchers have investigated the nature and causes of inflation in Nigeria (such as Adenekan & Nwanna, 2004; Asogu, 1991; Fakiyesi, 1996; Moser, 1995; Oyaromade, 2009; Rapu, Gaiya, Eborieme, Nkang, Audu, Golit, & Okafor, 2016). A variety of ARIMA methods have been used for modelling time series in the literature. ARIMA methods have been used to model inflation (examples are Adebiyi, Adenuga, Abeng, Omamukue, & Ononugo, 2010; Samad, Ali, & Hossain, 2002; Stockton & Glassman, 1987; Valle, 2002). ARIMA models have also been used to model exchange rates (such as Ajao, Obafemi, & Bolarinwa, 2017; Chamalwa, Rann, & Idris, 2016; Nwankwo, 2014; Nyoni, 2018; Olatunji & Bello, 2015; Onasanya & Ade
In-Text Citation: (Shaibu & Osamwonyi, 2020)
To Cite this Article: Shaibu, I., & Osamwonyi, I. O. (2020). A Comparative Analysis of Inflation Dynamics Models in Nigeria. International Journal of Academic Research in Business and Social Sciences, 10(2), 558–557.
Copyright: © 2020 The Author(s)
Published by Human Resource Management Academic Research Society (www.hrmars.com)
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