Good governance, innovation, economic growth and the stock market turnover rate

Mohammad Hossein Setayesh and Abbas Ali Daryaei

The Journal of International Trade & Economic Development, 2017, vol. 26, issue 7, 829-850

Abstract: This study is primarily aimed at testing the theory of good governance in the group of eight developing Islamic countries. Using a panel data regression model, we examined the data to determine the relationship between political economy and economic development of eight countries, for the period 2005 to 2014. The results show a significant positive correlation between the rule of law, corruption control with economic growth and stock market turnover rate proxy. The examination through an artificial neural network resulted in a higher determination coefficient and less average standard error. This, in turn, reveals that the fitting power and efficiency of this method is higher than the panel data regression model. Furthermore, the findings of this study suggest that the application of good governance theory calls for more inquiry.

Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (14)

Downloads: (external link)
http://hdl.handle.net/10.1080/09638199.2017.1334809 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:jitecd:v:26:y:2017:i:7:p:829-850

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RJTE20

DOI: 10.1080/09638199.2017.1334809

Access Statistics for this article

The Journal of International Trade & Economic Development is currently edited by Pasquale Sgro, David E.A. Giles and Charles van Marrewijk

More articles in The Journal of International Trade & Economic Development from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().