Financial sector and manufacturing sector performance: evidence from Nigeria
Financial sector and manufacturing sector performance: evidence from Nigeria
Author(s): Abiola John Asaleye, Ibrahim Joseph Adama, Olufemi Joseph OgunjobiSubject(s): Economy, National Economy, Financial Markets
Published by: ТОВ “Консалтингово-видавнича компанія “Ділові перспективи”
Keywords: financial; manufacturing sector; Vector Error Correction Model; Least Square;
Summary/Abstract: Nigerian economy depends on oil as the major source of revenue, failure to diversify the revenue base has raised questions about its sustainability and implication on the economy. This study uses market capitalization, broad money stock, credit to private sector, prime interest rate and deposit liability as proxies for the financial sector, while output in the manufacturing sector and manufacturing employment are used as proxies for manufacturing performance. The study examines the causal effects, shock effect and long-run impact using Granger Non-Causality, Vector Error Correction Model, and Dynamic Ordinary Least Square method, respectively. The results showed unidirectional causality, confirming the hypothesis of the ‘supply-leading view’ and ‘demand-following view’ except for market capitalization and output in the manufacturing sector, where independence was observed. The variance decomposition shows that the forecast error shock of credit to private sector and prime interest rate show more variations in manufacturing sector performance than other financial indicators. The long-run result using output in manufacturing sector as dependent variable shows a positive significant relationship with other financial sector indicators, except for broad money stock and deposit liability. This study recommended credit channel for transmission of monetary policy using interest rate to improve the performance of manufacturing sector, among others.
Journal: Investment Management and Financial Innovations
- Issue Year: 15/2018
- Issue No: 3
- Page Range: 35-48
- Page Count: 14
- Language: English