Financial Markets and Politics- Studying the Effect of Policy Risk on Stock Market Volatility in France 1967-2015
This study examines the impact of having a divided government (as opposed to a unified government) on stock market volatility in France. The role the French government plays throughout the different industries operating on its land is undoubtedly significant as it is through the government that laws...
Saved in:
Main Author: | |
---|---|
Format: | Dissertation |
Language: | English |
Published: |
ProQuest Dissertations & Theses
01-01-2015
|
Subjects: | |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Summary: | This study examines the impact of having a divided government (as opposed to a unified government) on stock market volatility in France. The role the French government plays throughout the different industries operating on its land is undoubtedly significant as it is through the government that laws and regulations are shaped and implemented. The main theory this paper aims to test empirically relates to the relationship between repartitions of governmental powers and policy risk. According to some literature, a divided government, due to what is referred to as a gridlock effect is less likely to implement policy changes and therefore policy risk is lower. As policy risk is lower, stock market volatility and returns are expected to be lower as well. The intuition behind this theory will be tested by firstly identifying the French government’s status (divided vs. unified) throughout the period spanning from 1967 till 2015, and then paralleling those results with the volatility of stock market returns the various periods considered. I find positive and significant results indicating a higher volatility in times of divided government thus refuting the gridlock theory. These findings are in line with the standard balancing model (Fiorina, 1992) and Mayhew’s Divided We Governhypothesis. Results remain robust after being subjected to tests for omitted variable bias, autocorrelation, multicollinearty and omission of abnormal observations. |
---|---|
ISBN: | 9798382577357 |