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Research Article Open access CC BY 4.0

An Empirical Analysis of Monetary Policy Transmission Instruments and Non-oil Real Sector Private Investment in Nigeria

O. S. Uwakaeme

Asian Journal of Economics, Business and Accounting · pp. 34–53 · Published 21 Jun 2022

10.9734/ajeba/2022/v22i1930657

Abstract

In recent times, the performance of Non-oil real Private investment in Nigeria has remained suboptimal. This has been generally attributed to ineffective monetary policy, among others. This study therefore examines the impact of selected Monetary Policy transmission instruments namely: Monetary Policy Rate (MPR), Cash Reserve Ratio, (CRR) Liquidity Ratio, (LR) and Foreign Exchange Rate (NFXR), on Non-oil Real Sector Private Investment (NRSPI). The time series data is sourced from CBN, spanning through a period of 1981 to 2020. Johansen Co-integration and Error correction model (ECM) econometric analysis was employed.The empirical findings established that in the long run, inverse and significant relationships exist between (NRSPI) and MPR, LR, and CRR while FXR is positively and significantly related. The coefficient of the ECM (-1.16) which measures NRSPI’s speed of equilibrium adjustment to changes in the selected policy instruments, is significant and correctly signed. It suggests that in the long run, NRSPI adjusts slowly to short-run disequilibrium in the selected policy instruments; indicating a lag effect. Overall, the policy instruments do not contribute effectively to NRSPI growth in Nigeria. Therefore, the monetary authorities should lay emphasis on aligning their policy contractionary measures, to reduce adverse effect of these selected instruments, They should maintain optimal lending rate that reflects the overall internal rate of return on investment, with due attention to market fundamentals. Lastly, Policy makers should take into consideration the lag effect, and design policies in line with the magnitude of expected changes.

Monetary policy instruments Non-oil real private investment Co-integration and error correction models

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