Relationship Between Money Supply and Some Macroeconomic Variables in The Libyan Economy During Period (1990-2022)
Year: 2025
Type: article
Abstract: This study objective to examine the relationship between money supply and some macroeconomic variables (inflation, government expenditure, exchange rate, and economic growth) in Libya from 1990 to 2022. To achieve that above objective, thestudy employs the Augmented Dickey Fuller (ADF) and Autoregressive Distributed Lag (ARDL), Bounds Testing Approach” for “Co-integration were applied to study the cointegration among, the above-mentioned variables, Granger causality testand error correction mechanism to estimation of the relevant equations. The results of the cointegration tests showed that there is a long-run relationship among the macroeconomic variables in the model and money supply. And the coefficient ofthe the inflation (LNIFLT) and coefficient of the government expenditure (NEXPN ) have positive significant effect on money supply in long--run , But the other variables coefficients (economic growth and exchange rate ) have not positive significant effect on money supply in long--run . While in short run the coefficient of the lagged economic growth (GDP-1), lagged inflation (LNIFLT-1) and exchange rate (LNEXCH ), government expenditure (LNEXPN) have significant effect on money supply in short--run . With the speed of adjustment is fast from short-run to long-run which slightly more than -.82 %. Furthermore, the results of the granger causality test showed that the existence of bi-directional causality relationship between inflation and money supply. Also, and bi-directional causality relationship between government expenditure and money supply. In addition to that there is uni-directional causality from money supply to exchange rate. but there is no anycausality relationship between money supply and economic growth. KEY WORDS: Money supply, Macroeconomic Variables, AutoregressiveDistributed Lag (ARDL), Granger Causality Test
Author: Libyan Accounting and Auditing syndicate (LAAS)
Language: English
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7076448474
FWCI:
Cites:
Cited by:
Related to: