DP16034 Using Social Media to Identify the Effects of Congressional Partisanship on Asset Prices
|Author(s):||Francesco Bianchi, Roberto Gomez Cram, Howard Kung|
|Publication Date:||April 2021|
|Keyword(s):||Asset Pricing, High-Frequency Identification, partisanship, social media|
|Programme Areas:||Financial Economics|
|Link to this Page:||cepr.org/active/publications/discussion_papers/dp.php?dpno=16034|
We measure the individual and collective viewpoints of US Congress members on various economic policies by scraping their Twitter accounts. Tweets that criticize (support) a particular company are associated with a significant negative (positive) stock price reaction in a narrow time window around the tweet. A sharp partisan divide emerges, with Republicans and Democrats coordinated in both their support and opposition for different industries emanating from disparate legislative agendas. Members of congress coordinate within parties to push legislation through their social media accounts. As an illustrative and relevant example, we analyze the "Tax Cuts and Jobs Act" of 2017 and document significant aggregate stock market responses to the real-time evolution of partisan viewpoints about the bill.