Effects of Macroeconomic Variables on Bank Credit in Saudi Arabia: An ARDL Bounds Testing Approach to Cointegration

Abstract

The main objective of the paper is to examine the relationship between bank credit and the major macroeconomic variables of Saudi Arabia during the period from 1993 to 2019. An autoregressive distributed lag (ARDL) method was employed to estimate the short-run and long-run effects of the major macroeconomic variables on bank credit. The study revealed that the real exchange rate and money supply have positive long-run effects on bank credit compared to the negative effects of inflation on bank credit. Gross domestic product (GDP) has a negative effect on total bank credit, which is in conflict with the Keynesian view. In the short run, the effect of GDP on bank credit is negative, whereas inflation has a positive influence on bank credit. Based on the findings, the study suggests some expansionary monetary and fiscal policies, such as raising asset prices and lowering the costs of borrowing, increasing spending and cutting taxes to produce budget deficits for stabilizing the financial system and increasing national income to promote sustainable and stable growth in bank credit.

The Effects of Currency Devaluation on the Bilateral Trade Balance of Sudan: Cointegration and Error-Correction Modeling

“…Both tables show that in all cases, the unit root hypothesis cannot be rejected. Therefore, It can be concluded that most variables are I (1), except for trade balance, which was stationary at level, a result confirmed by numerous other studies such as Ibrahim and Bashir [36]; Bashir and Ibrahim, [50]; Ibrahim and Bashir, [53]; Wu [54].…”

“…If the unit root analyses suggest that all the variables are I(1) and the residuals in the model are stationary, we can conclude that the series are cointegrated in order I(1). The advantage of cointegration and error correction techniques is that they provide more efficient short-run and long-run coefficient estimates and avoid the problems of spurious regression [50]. The ARDL bounds testing procedure is sensitive to the selection of the lag structure.…”