Abstract

http://ssrn.com/abstract=1927985
 
 

References (48)



 
 

Citations (1)



 


 



Presidential Approval Models Revisited: A New Perspective


Betul Dicle


Louisiana State University, Baton Rouge - Department of Political Science

Mehmet F. Dicle


Loyola University New Orleans - Joseph A. Butt, S.J. College of Business

September 15, 2011


Abstract:     
Use of quarterly economic data in presidential job approval models implies that polls are reactions, in part, to quarterly economic performance. Perhaps this implication is not intended but it is due to the availability of low frequency economic data. We argue that voters have a shorter reaction time and do not wait for periodic data while the economy is in motion. We suggest the use of high frequency financial variables that proxy past, present and expected economic performance. Since opinions are formed based on continuous information, we also suggest employing Geweke type instantaneous feedback as well as traditional Granger type sequential causal feedback. The results show that for presidential candidates, weekly financial risk may be just as important as quarterly GDP growth or monthly unemployment.

Number of Pages in PDF File: 23

Keywords: Presidential job approval, economic performance, financial markets, financial risk, instantaneous feedback

JEL Classification: D72, P16

working papers series





Download This Paper

Date posted: September 16, 2011  

Suggested Citation

Dicle, Betul and Dicle, Mehmet F., Presidential Approval Models Revisited: A New Perspective (September 15, 2011). Available at SSRN: http://ssrn.com/abstract=1927985 or http://dx.doi.org/10.2139/ssrn.1927985

Contact Information

Betul Dicle
Louisiana State University, Baton Rouge - Department of Political Science ( email )
Baton Rouge, LA
United States
Mehmet F. Dicle (Contact Author)
Loyola University New Orleans - Joseph A. Butt, S.J. College of Business ( email )
6363 St. Charles Avenue
New Orleans, LA 70118
United States
HOME PAGE: http://researchforprofit.com
Feedback to SSRN


Paper statistics
Abstract Views: 215
Downloads: 49
References:  48
Citations:  1

© 2014 Social Science Electronic Publishing, Inc. All Rights Reserved.  FAQ   Terms of Use   Privacy Policy   Copyright   Contact Us
This page was processed by apollo6 in 0.328 seconds