Skip to main content

Causality between financial development and economic growth: an application of vector error correction and variance decomposition methods to Saudi Arabia

Buy Article:

$47.50 plus tax (Refund Policy)

This article makes an attempt to test the possible directions of causality between financial development and economic growth, which were labelled by Patrick (1966) as the supply-leading and demand-following hypothesis. Saudi Arabia is taken as a case study. The methods applied are the error correction and variance decompositions techniques including the most recently developed 'long-run structural modelling (LRSM)' (Pesaran and Shin, 2002), which by imposing exactly identifying and overidentifying restrictions on the cointegrating vector has taken care of a major limitation of the conventional cointegrating estimates in that they were atheoretical in nature. To the best of our knowledge, there has not been any study on this issue with the application of the techniques that incorporate 'LRSM'. The stability of the functions has also been tested by Cumulative Sum (CUSUM), Cumulative Sum of Squares (CUSUMSQ) and Chow Test (CHOW) tests. Our findings, based on the above mentioned rigorous techniques, tend to suggest that the direction of causation between financial development and economic growth is supply-leading (rather than demand-following), as expected at the early stage of development. These findings have clear policy implications in that a pro-active policy of growth and reform of the financial sector will help enhance economic growth in an open developing economy like Saudi Arabia.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
No Metrics

Document Type: Research Article

Affiliations: College of Industrial Management, King Fahd University of Petroleum & Minerals 31261, Dhahran, Saudi Arabia

Publication date: 01 May 2009

More about this publication?
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more