Monetary Policy and Economic Growth in Nigeria: An Autoregressive Distributed Lag (ARDL) Analysis.

Abstract

The study assessed the impact of monetary policy on economic growth in Nigeria. Three objectives guided the study. It employed quarterly data spanning 1986:Q1-2018:Q4, and used the Autoregressive Distributed Lag (ARDL) model, and the Granger causality test to carry out its empirical analysis and achieving its objectives. Findings from the study revealed that the monetary policy rate (MPR) had a positive impact on economic growth, but it was however not statistically significant. The broad money supply (M2) as a monetary policy instrument had a much more positive and highly statistically significant impact on economic growth in Nigeria. As such, the study recommended that the CBN should embark on a comprehensive monitoring of monetary instruments and aggregates and place less emphasis on inflation targeting (IT) alone. It is important to use other instruments which the central bank can control effectively like the broad money supply (M2) as it is more effective on the economy.

The Effect of Monetary Policy on Economic Growth of selected SAARC countries

“…It contradicts with the literature: Srithilat and Sun (2017), Fasanya et al (2013), Madurapperuma, (2016), Hossin (2015, Saaed (2007), Ahmad et al (2016). The explanatory variable broad money is found to be statistically significant and has a positive effect to economic growth as measured by GDP where the result in line with literature: Patricia and Izuchukwu (2016), Nouri andSamimi (2011), Joshi (2022), Gnawali (2019), Hameed and Amen (2011), Ahmad et al (2016), Ibrahim (2019. However, the result contradicts with: Sulaiman and Migiro (2014), Tadesse and Melaku (2019).…”

Stabilizing Error Correction Mechanism in the Presence of Explosiveness

“…Attempt to uncover the long-run/equilibrium relationship is equivalent to separating it from its short-term dynamics which shows evidence for/against the equilibrium relationship Kripfganz and Schneider [2]. The ARDL model can be applied to study the relationship between different economic indicators such as gross domestic product, exchange rate, money supply, inflation, and interest rate over time, Pesaran et al [3], Adamu and Usman [4], Aronu et al [5], Ibrahim [6], Charles et al [7], Elem-Uche et al [8]; to examine the relationship between financial variables such as stock prices and economic indicators, Adeleye et al [9], Narayan and Smyth [10], Catau and Asmah [11], Mustafa [12], Celina, U.C. [13], Enisan and Olufisayo [14], Rostin et al [15], Liaqat et al [16]; to investigate the impact of exchange rate on trade balance; Bahmani and Narayan [17], Belloumi [18]; to examine the effect of environmental factors, policies, or regulations on economic variables, Ozturk and Acaravci [19], Hamid et al [20], Saida and Kais [21]; to study the long-run and short-term effect of healthcare policies, expenditures, and other health-related variables, Mamun and Sohag [22]; to examine the relationship between energy prices, consumption, and economic growth over time, Zhigang and Huang [23].The idea of differencing of integrated time series before modelization was advocated by Box and Jenkins [24] while Engle and Granger [25] formalized the idea of cointegration, which is used in a variety of economic models (Iyeli et al, [26], Nkoro and Uko [27].…”